144 48 10MB
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Gaurav Mishra Krishna Giri Arun Jyoti Nath Rosa Francaviglia Editors
Soil Carbon Dynamics in Indian Himalayan Region
Soil Carbon Dynamics in Indian Himalayan Region
Gaurav Mishra • Krishna Giri • Arun Jyoti Nath • Rosa Francaviglia Editors
Soil Carbon Dynamics in Indian Himalayan Region
Editors Gaurav Mishra Indian Council of Forestry Research and Education Dehradun, Uttarakhand, India Arun Jyoti Nath Department of Ecology and Environmental Science Assam University Silchar, Assam, India
Krishna Giri Indian Council of Forestry Research and Education Dehradun, India Rosa Francaviglia Research Centre for Agriculture and Environment Council for Agricultural Research and Economics Rome, Italy
ISBN 978-981-99-3302-0 ISBN 978-981-99-3303-7 https://doi.org/10.1007/978-981-99-3303-7
(eBook)
# The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore
Preface
Soil organic carbon (SOC) is one of the vital resources of any natural and managed terrestrial ecosystem, which helps in studying the carbon cycle of ecosystems, monitoring soil health, and mitigating the negative impacts of climate change. Actually, billions of people depend on the SOC pool for their food supplies and many other ecosystem services. Furthermore, areas with high amounts of SOC might help to buffer and mitigate abrupt climate change. The Indian Himalayan Region (IHR), occupying an area of 53.7 Mha and constituting 16.4% of India, is one of the biodiversity hot spots of the country. IHR has two distinct sub-regions, viz. the eastern Himalayas region and the western Himalayas region, with the eastern region receiving four times more rainfall than the western region. Moreover, in the eastern Himalayas, the dominant vegetation is evergreen forests, and in the western region coniferous forests and alpine vegetation. The high dependency of indigenous populations on forest resources, frequent forest fire, shifting cultivation, and landuse changes resulted in unparalleled forest degradation and biodiversity loss in the IHR. Moreover, this region is also vulnerable to climatic changes due to the presence of a large number of glaciers and glacial lakes. This book consists of 20 chapters based on the assessment of SOC sequestration in the IHR landscape. It is imperative to understand the influence of land use, vegetation, altitude, and edaphic factors on SOC dynamics, accomplished by advanced techniques like remote sensing/GIS and SOC modeling. We hope that the book will be helpful for students, teachers, and researchers who are interested in studying soil carbon sequestration, especially with reference to climate change. We are highly grateful to all contributors for accepting our invitation, not only for sharing their knowledge and research but also for integrating their expertise in drafting the chapters and enduring editorial suggestions to finally produce this book. We greatly appreciate their dedication. We also thank Springer-International team for their generous cooperation at every stage of the book production. Dehradun, India Dehradun, India Silchar, India Rome, Italy
Gaurav Mishra Krishna Giri Arun Jyoti Nath Rosa Francaviglia
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Contents
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An Overview of Soil Carbon Sequestration and Food Security in the Indian Himalayan Region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jayanta Layek, Shidayaichenbi Devi, Anup Das, Khrawbor Dkhar, Biswajit Pramanick, Vinay Kumar Mishra, Nongmaithem Uttam Singh, R. Krishnappa, and Bappa Paramanik Soil C Sequestration in Himalayan Landscape: Impacts of Vegetation and Edaphic Interactions Under Changing Climate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Iftekhar U. Ahmed, Yonten Dorji, and Purna B. Chhetri Soil Carbon Stock Along an Altitudinal Gradient in the Indian Himalayas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Shahina Noushad Najima, Manendra Singh, Sajitha Siril, Gopal Shukla, Pankaj Panwar, and Sumit Chakravarty Impact of Land Uses on Soil Organic Carbon Dynamics in the Indian Himalayan Region . . . . . . . . . . . . . . . . . . . . . . . . . . . Anshuman Das, Gaurav Mishra, Pramod Chand Lakra, Sanjeev Kumar, and Shambhu Nath Mishra Terrestrial Carbon Stock and Sink Potential of Indian Himalayan Forest Ecosystem: A Tool for Combating Climate Change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Anil Kumar, Pawan Kumar, Vimal Chandra Srivastava, Anand Giri, Deepak Pant, and Raj Kumar Verma Conservation Agriculture for Soil Health and Carbon Sequestration in the Indian Himalayan Region . . . . . . . . . . . . . . . . Ashish Rai, Sumit Tripathi, Ayush Bahuguna, Sumit Rai, Jitendra Rajput, Anshu Gangwar, Rajeev Kumar Srivastava, Arvind Kumar Singh, Satish Kumar Singh, Dibyanshu Shekhar, Rahul Mishra, Eetela Sathyanarayana, and Supriya Pandey
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Establishing Linkages of Soil Carbon Dynamics with Microbes Mediated Ecological Restoration of Degraded Ecosystems in Indian Himalayan Region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 Supriya Pandey, Sumit Rai, Anand Singh Bisht, and Ashish Rai
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Harnessing Soil Ecosystem Services for Achieving Soil-Based SDGs in Indian Himalaya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147 Deepa Rawat, Debaaditya Mukhopadhyay, Vinod Prasad Khanduri, Bhupendra Singh, Manoj Kumar Riyal, and Sarswati Prakash Sati
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AFOLU Sectors of North East India and Their Potential for Soil Carbon Storage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171 Kingshuk Modak, Nibedita Guru, Gaurav Mishra, and Abhishek Jangir
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Soil Microbial Carbon Pools as an Indicator of Soil Health in Different Land Use Systems of Northeast India . . . . . . . . . . . . . . 189 Lungmuana, Ramchhanliana Hauchhum, and Paul Lalremsang
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Bamboo Resources in Karbi Anglong District of Assam and Their Role in Soil Carbon Management . . . . . . . . . . . . . . . . . . 205 Pator Singnar, Panna Chandra Nath, Arun Jyoti Nath, and Ashesh Kumar Das
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Land Use Change and Its Impacts on Soil Carbon Dynamics in Mizoram, Northeast India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217 Jitendra Ahirwal, Uttam Thangjam, and Uttam Kumar Sahoo
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Vegetation and Recalcitrant Soil Carbon Recovery Along an Age Chronosequence of Jhum Fallows in North East India . . . . 235 Panna Chandra Nath, Arun Jyoti Nath, and Ashesh Kumar Das
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Soil Organic Carbon Modeling in Indian Eastern Himalayan Region: A Review of Case Studies . . . . . . . . . . . . . . . . . . . . . . . . . . 245 Gaurav Mishra and Rosa Francaviglia
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Digital Mapping of Soil Carbon: Techniques and Applications . . . . 259 Surabhi Hota, Krishna Kumar Mourya, Lalchand Malav, and Brijesh Yadav
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Geospatial Analysis of Soil Organic Carbon Dynamics in the Indian Himalayas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 287 Shubham Kumar and Laxmi Kant Sharma
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Spatial Monitoring of Soil Health Using Remote Sensing of Distinct Land Cover in the Central Himalayan Region Using GEE Platform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 303 Alok Raj, Laxmi Kant Sharma, and Rajashree Naik
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Digital Mapping of Soil Organic Carbon Using Legacy Data in the Northeast Himalayas . . . . . . . . . . . . . . . . . . . . . . . . . . . 321 Pravash Chandra Moharana, Roomesh Kumar Jena, Nirmal Kumar, Abhishek Jangir, Gulshan Kumar Sharma, and Siladitya Bandyopadhyay
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Advanced Techniques in Estimating Soil Erosion and Associated Carbon Loss in the Himalayan Region . . . . . . . . . . . . . . . . . . . . . . 341 Suresh Kumar, K. R. Sooryamol, Anu David Raj, Justin George Kalambukattu, and Sankar Mariappan
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Soil Carbon Pools in Different Land Use Systems in the Indian Himalayan Region and Their Role in Climate Change Mitigation and Ecological Sustainability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373 Shilky, Ratul Baishya, and Purabi Saikia
Editors and Contributors
About the Editors Gaurav Mishra is currently working as Scientist in the Centre of Excellence on Sustainable Land Management at the Indian Council of Forestry Research and Education, Dehradun (Uttarakhand). He is a soil scientist and his research interests include soil quality assessment, sustainable land management, digital soil mapping, soil carbon dynamics, and carbon modeling at the regional level. Krishna Giri is presently working as Scientist-D in the Centre of Excellence on Sustainable Land Management at the Indian Council of Forestry Research and Education, Dehradun, India, and did M.Sc. and Ph.D. in Environmental Science from G.B. Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India. He has worked on soil microbiology associated with shifting cultivation land use systems, soil microbiome analysis of Himalayan Alder-based agroforestry, and other traditional farming systems in Nagaland state. Arun Jyoti Nath is an Associate Professor of Ecology and Environmental Science at the Assam University. He is an ecologist with a diverse experience in research and teaching. He has over 15 years’ experience in carbon dynamics research. His research interest includes mitigation, sustainability, ecosystem carbon dynamics at regional and landscape scale. Dr. Nath has authored more than 100 scientific, technical, and educational publications. Rosa Francaviglia with expertise in agronomy, is a senior researcher at the Council for Agricultural Research and Economics, Research Centre for Agriculture and Environment, in Rome, Italy, since 1981 (now retired). Her main research topics include the effects of climate change on agriculture, carbon sinks and agricultural soils, soil organic carbon simulation models, soil fertility, conservation agriculture, crop diversification, agro-environmental evaluations, soil quality indicators, and good agro-environmental conditions (GAEC) under the EU Common Agricultural Policy.
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Editors and Contributors
Contributors Jitendra Ahirwal Department of Forestry, School of Earth Sciences and Natural Resources Management, Mizoram University Aizawl, Aizawl, Mizoram, India Iftekhar U. Ahmed Institute of Forest Ecology, University of Natural Resources and Life Sciences, BOKU, Vienna, Austria Ayush Bahuguna Department of Agriculture Chemistry and Soil Science, Ch. Chhotu Ram (PG) College, Muzaffarnagar, Uttar Pradesh, India Ratul Baishya Department of Botany, University of Delhi, Delhi, India Siladitya Bandyopadhyay ICAR-National Bureau of Soil Survey and Land Use Planning, Regional Centre, Kolkata, India Anand Singh Bisht Centre for Environment Assessment and Climate Change, G. B. Pant National Institute of Himalayan Environment, Almora, India Sumit Chakravarty Department of Forestry, Uttar Banga Krishi Viswavidyalaya, Cooch Behar, West Bengal, India Purna Chhetri The School for Field Studies, Paro, Bhutan Bhutan Ecological Society, Thimphu, Bhutan Anshuman Das Forest Ecology and Climate Change Division, ICFRE-Institute of Forest Productivity, Ranchi, Jharkhand, India Anup Das ICAR Research Complex for Eastern Region, Patna, India Ashesh Kumar Das Department of Ecology and Environmental Science, Assam University, Silchar, Assam, India Shidayaichenbi Devi ICAR Research Complex for NEH Region, Umiam, Meghalaya, India Khrawbor Dkhar School of Agricultural Sciences and Rural Development (SASRD), Medziphema, Nagaland, India Yonten Dorji Department of Forest Science, College of Natural Resources, Royal University of Bhutan, Punakha, Bhutan Department of Spatial Structures and Digitization of Forests, Georg-AugustUniversität Göttingen, Göttingen, Germany Rosa Francaviglia Research Centre for Agriculture and Environment, Council for Agricultural Research and Economics, Rome, Italy Anshu Gangwar Krishi Vigyan Kendra Parsauni, East Champaran, Dr Rajendra Prasad Central Agricultural University, Pusa, Bihar, India Anand Giri School of Civil and Environmental Engineering, Indian Institute of Technology Mandi, Mandi, HP, India
Editors and Contributors
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Nibedita Guru Forest Ecology and Climate Change Division, Rain Forest Research Institute, Jorhat, Assam, India Ramchhanliana Hauchhum Mizoram University, Aizawl, Mizoram, India Surabhi Hota ICAR-National Bureau of Soil Survey and Land Use Planning, Jorhat, Assam, India Abhishek Jangir ICAR-National Bureau of Soil Survey and Land Use Planning, Regional Centre, Udaipur, India Roomesh Kumar Bhubaneswar, India
Jena ICAR-Indian
Institute
of
Water
Management,
Justin George Kalambukattu Agriculture and Soils Department, Indian Institute of Remote Sensing, Indian Space Research Organization (ISRO), Dehradun, Uttarakhand, India Vinod Prasad Khanduri College of Forestry, VCSG Uttarakhand University of Horticulture and Forestry, Tehri Garhwal, Uttarakhand, India R. Krishnappa ICAR Research Complex for NEH Region, Umiam, Meghalaya, India Anil Kumar Forest Ecology and Climate Change Division, Himalayan Forest Research Institute, Shimla, India Forest Research Institute Deemed to be University, Dehradun, Uttarakhand, India Nirmal Kumar ICAR-National Bureau of Soil Survey and Land Use Planning, Nagpur, India Pawan Kumar Regional Research Centre, Chandsoli, Maharana Pratap Horticultural University, Karnal, Haryana, India Sanjeev Kumar Forest Ecology and Climate Change Division, ICFRE-Institute of Forest Productivity, Ranchi, Jharkhand Shubham Kumar Department of Environmental Science, School of Earth Sciences, Central University of Rajasthan, Bandarsindri, Rajasthan, India Suresh Kumar Agriculture, Forestry and Ecology Group, Indian Institute of Remote Sensing, Indian Space Research Organization (ISRO), Dehradun, Uttarakhand, India Pramod Chand Lakra Silviculture Division, ICFRE-Institute of Forest Productivity, Ranchi, Jharkhand, India Paul Lalremsang North Eastern Hill University, Tura, Meghalaya, India Jayanta Layek ICAR Research Complex for NEH Region, Umiam, Meghalaya, India Lungmuana ICAR-RC-NEH Region, Mizoram Centre, Kolasib, Mizoram, India
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Editors and Contributors
Lalchand Malav ICAR-National Bureau of Soil Survey and Land Use Planning, Udaipur, Rajasthan, India Sankar Mariappan Indian Institute of Soil and Water Conservation (ICARIISWC), Dehradun, Uttarakhand, India Gaurav Mishra Indian Council of Forestry Research and Education, Dehradun, Uttarakhand, India Rahul Mishra ICAR-Indian Institute of Soil Science, Bhopal, Madhya Pradesh, India Shambhu Nath Mishra Forest Ecology and Climate Change Division, ICFREInstitute of Forest Productivity, Ranchi, Jharkhand, India Vinay Kumar Mishra ICAR Research Complex for NEH Region, Umiam, Meghalaya, India Kingshuk Modak Forest Ecology and Climate Change Division, Rain Forest Research Institute, Jorhat, Assam, India Pravash Chandra Moharana ICAR-National Bureau of Soil Survey and Land Use Planning, Nagpur, India Krishna Kumar Mourya ICAR-National Bureau of Soil Survey and Land Use Planning, Jorhat, Assam, India Debaaditya Mukhopadhyay ICFRE-Rain Forest Research Institute, Jorhat, Assam, India Rajashree Naik Environmental Remote Sensing Lab, Department of Environmental Science, School of Earth Sciences, Central University of Rajasthan, Ajmer, India Shahina Noushad Najima Department of Forestry, Uttar Banga Krishi Viswavidyalaya, Cooch Behar, West Bengal, India Arun Jyoti Nath Department of Ecology and Environmental Science, Assam University, Silchar, Assam, India Panna Chandra Nath Department of Ecology and Environmental Science, Assam University, Silchar, Assam, India Supriya Pandey Centre for Environmental Assessment and Climate Change, GB Pant National Institute of Himalayan Environment, Almora, India Deepak Pant Department of Environmental Sciences, Central University of Himachal Pradesh, Dharamshala, India Pankaj Panwar ICAR-Indian Institute of Soil and Water Conservation, Research Centre, Chandigarh, India Bappa Paramanik Uttar Banga Krishi Viswavidyalaya (UBKV), Cooch Behar, West Bengal, India
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Biswajit Pramanick Dr. Rajendra Prasad Central Agricultural University, PUSA, Samastipur, Bihar, India Ashish Rai Krishi Vigyan Kendra Parsauni, East Champaran, Dr Rajendra Prasad Central Agricultural University, Pusa, Bihar, India Sumit Rai Centre for Environmental Assessment and Climate Change, GB Pant National Institute of Himalayan Environment, Almora, India Alok Raj Environmental Remote Sensing Lab, Department of Environmental Science, School of Earth Sciences, Central University of Rajasthan, Ajmer, India Anu David Raj Agriculture and Soils Department, Indian Institute of Remote Sensing, Indian Space Research Organization (ISRO), Dehradun, Uttarakhand, India Jitendra Rajput Division of Agricultural Engineering, ICAR-Indian Agricultural Research Institute, New Delhi, India Deepa Rawat College of Forestry, VCSG Uttarakhand University of Horticulture and Forestry, Tehri Garhwal, Uttarakhand, India Manoj Kumar Riyal College of Forestry, VCSG Uttarakhand University of Horticulture and Forestry, Tehri Garhwal, Uttarakhand, India Uttam Kumar Sahoo Department of Forestry, School of Earth Sciences and Natural Resources Management, Mizoram University Aizawl, Aizawl, Mizoram, India Purabi Saikia Department of Environmental Sciences, Central University of Jharkhand, Ranchi, India Eetela Sathyanarayana Department of Soil Science and Agricultural Chemistry, Agricultural College, Palem, PJTSAU, Hyderabad, India Sarswati Prakash Sati College of Forestry, VCSG Uttarakhand University of Horticulture and Forestry, Tehri Garhwal, Uttarakhand, India Gulshan Kumar Sharma Indian Institute of Soil and Water Conservation, Research Centre, Kota, Rajasthan, India Laxmi Kant Sharma Department of Environmental Science, School of Earth Sciences, Central University of Rajasthan, Bandarsindri, Rajasthan, India Environmental Remote Sensing Lab, Department of Environmental Science, School of Earth Sciences, Central University of Rajasthan, Ajmer, India Dibyanshu Shekhar Krishi Vigyan Kendra Jale Darbhanga, Dr Rajendra Prasad Central Agricultural University, Pusa, Bihar, India Shilky Department of Environmental Sciences, Central University of Jharkhand, Ranchi, India Gopal Shukla Department of Forestry, Uttar Banga Krishi Viswavidyalaya, Cooch Behar, West Bengal, India
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Arvind Kumar Singh Krishi Vigyan Kendra Parsauni, East Champaran, Dr Rajendra Prasad Central Agricultural University, Pusa, Bihar, India Bhupendra Singh College of Forestry, VCSG Uttarakhand University of Horticulture and Forestry, Tehri Garhwal, Uttarakhand, India Manendra Singh Department of Forestry, Uttar Banga Krishi Viswavidyalaya, Cooch Behar, West Bengal, India Nongmaithem Uttam Singh ICAR Research Complex for NEH Region, Umiam, Meghalaya, India Satish Kumar Singh Department of Plant Breeding and Genetics, Dr. Rajendra Prasad Central Agriculture University, Pusa, Bihar, India Pator Singnar Department of Ecology and Environmental Science, Assam University, Silchar, Assam, India Sajitha Siril Department of Forestry, Uttar Banga Krishi Viswavidyalaya, Cooch Behar, West Bengal, India K. R. Sooryamol Indian Institute of Soil and Water Conservation (ICAR-IISWC), Dehradun, Uttarakhand, India Rajeev Kumar Srivastava Directorate of Seed and Farms, TCA Dholi, Dr Rajendra Prasad Central Agricultural University, Pusa, Bihar, India Vimal Chandra Srivastava Department of Chemical Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India Uttam Thangjam Department of Forestry, School of Earth Sciences and Natural Resources Management, Mizoram University Aizawl, Aizawl, Mizoram, India Sumit Tripathi Department of Soil Science and Agricultural Chemistry, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh, India Raj Kumar Verma Forest Ecology and Climate Change Division, Himalayan Forest Research Institute, Shimla, India Brijesh Yadav ICAR-National Bureau of Soil Survey and Land Use Planning, Udaipur, Rajasthan, India
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An Overview of Soil Carbon Sequestration and Food Security in the Indian Himalayan Region Jayanta Layek , Shidayaichenbi Devi, Anup Das , Khrawbor Dkhar, Biswajit Pramanick , Vinay Kumar Mishra Nongmaithem Uttam Singh, R. Krishnappa , and Bappa Paramanik
,
Abstract
The Indian Himalayan Region (IHR) is considered as a “bowl of biological hotspots” as it has diverse and endemic species of plants and animals. It includes 12 Indian states i.e., Jammu and Kashmir (J&K), Himachal Pradesh (HP), Uttarakhand (UK), Assam (AS), Arunachal Pradesh (AP), Meghalaya (ML), Nagaland (NL), Tripura (TR), Manipur (MN), Sikkim (SK), and West Bengal (WB). It extends over 2500 km from the east (AP) to west (J&K) across 250–300 km as width, contributing 16.2% by land to the country area and supporting 3.86% of the population, i.e., 51 million. The anthropogenic activities such as conventional farming system, soil erosion and degradation, wide destruction of forest, and intensive agricultural practices to sustain the ever-increasing population affect the ecological diversity and the livelihoods and food security of the IHR. These activities also deteriorate the soil’s organic and inorganic carbon stocks and so impact soil health and ultimately soil productivity. The major J. Layek (✉) · S. Devi · V. K. Mishra · N. U. Singh · R. Krishnappa ICAR Research Complex for NEH Region, Umiam, Meghalaya, India e-mail: [email protected] A. Das ICAR Research Complex for Eastern Region, Patna, India e-mail: [email protected] K. Dkhar School of Agricultural Sciences and Rural Development (SASRD), Medziphema, Nagaland, India B. Pramanick Dr. Rajendra Prasad Central Agricultural University, PUSA, Samastipur, Bihar, India e-mail: [email protected] B. Paramanik Uttar Banga Krishi Viswavidyalaya (UBKV), Cooch Behar, West Bengal, India # The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Mishra et al. (eds.), Soil Carbon Dynamics in Indian Himalayan Region, https://doi.org/10.1007/978-981-99-3303-7_1
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reason for the reduction in soil carbon stocks in IHR is due to the slash and burn of forest for “Jhumming cultivation.” This not only affects the soil quality but also releases carbon dioxide (CO2), carbon monoxide (CO), methane (CH4), nitrous oxide (NOx), etc., as greenhouse gases (GHGs) to the atmosphere and thus affects climate change.
1.1
Introduction
The Indian Himalayan Region (IHR) is considered as a “bowl of biological hotspots” as it has diverse and endemic species of plants and animals. It includes 12 Indian states i.e., Jammu and Kashmir (J&K), Himachal Pradesh (HP), Uttarakhand (UK), Assam (AS), Arunachal Pradesh (AP), Meghalaya (ML), Nagaland (NL), Tripura (TR), Manipur (MN), Sikkim (SK), and West Bengal (WB) (Sharma 1999). It extends over 2500 km from the east (AP) to west (J&K) across 250–300 km as width, contributing 16.2% by land to the country area and supporting 3.86% of the population, i.e., 51 million (Singh 2015; Bhatt et al. 1999). The anthropogenic activities such as conventional farming system, soil erosion and degradation, wide destruction of forest, and intensive agricultural practices to sustain the everincreasing population affect the ecological diversity and the livelihoods and food security of the IHR (Pratap 1999; Das et al. 2014). These activities also deteriorate the soil’s organic and inorganic carbon stocks and so impact soil health and ultimately soil productivity. The major reason for the reduction in soil carbon stocks in IHR is due to the slash and burn of forest for “Jhumming cultivation.” This not only affects the soil quality but also releases carbon dioxide (CO2), carbon monoxide (CO), methane (CH4), nitrous oxide (NOx), etc., as greenhouse gases (GHGs) to the atmosphere and thus affects climate change (Devi and Singh 2023). The continuous exploitation of soil carbon stocks in IHR can be mitigated through “carbon sequestration (CS).” CS is the long-term capturing and storing of atmospheric carbon compounds, especially CO2, in the soil through vegetation that absorb atmospheric CO2 along with water and sunlight for the photosynthetic process. The growing of a plant converts atmospheric CO2 into organic matter and stocks in the soil as soil organic carbon (SOC) that is stored for years thereby mitigating climate change. CS could comprise the conversion of barren land into vegetated land, slash and burns into slash and char, and conventional farming systems into conservation or sustainable system. The slash and char can sequester 0.21 Pg (penta gram) of atmospheric carbon (Layek et al. 2022). The IHR stocks a total of 5.4 bt (billion tonnes) of carbon and has a potential for carbon sequestration of 65 mt (million tonnes) per year (Tolangay and Moktan 2020). However, due to an increment in human pressure and construction activities, the degradation of forest land in IHR is very commonly impacting the SOC stocks and environmental degradation (Baland et al. 2010; Singh et al. 2019). The reduction in SOC content degrades the soil’s physical, chemical, and biological properties and reduces plant growth and development so that CS potential is lower. However, the adoption of CS
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techniques is not widespread, so that there is a continuous decline in SOC content and food security in IHR is at risk. The interrelations among SOC, soil health, vegetation, CS, climate change, and food security and a balance among them can allow achieving a sustainable environment without compromising crop productivity. However, the rate of climate change in IHR is increasing as compared with the past century (Brohan et al. 2006; Diodato et al. 2012). Many strategies are implemented to enhance CS through Good Agricultural Practices (GAPs) for a sound sustainable environment and mitigating climate change (Das et al. 2017), such as the supply of organic matter (farmyard manure, compost, vermicompost), integrated farming systems, agroforestry, conservation farming systems, optimum nutrients application, and in situ and ex situ residue management. The widespread adoption of CS techniques in IHR is the only option for sustainable agriculture.
1.2
The Present Climatic Scenario of IHR
The region is vulnerable to climate change due to a faster increase of air temperature, a decreasing precipitation rate, and a low snowfall rate in the twentieth century (Bhutiyani et al. 2007; Dimri and Kumar 2008). Climate change can impact the natural environment and socio-economic status and can change the natural resources in their quality, distribution, and type in the Himalayan regions (Beniston 2003). The change in climate is due to the emission of greenhouse gases (GHGs) into the atmosphere (Goswami et al. 2014), and the widespread destruction of forests in IHR is the primary reason for GHGs emissions.
1.3
Environmental and Agricultural Constraints Faced in IHR
The Indian Himalayan Region (IHR) is bestowed with natural resources such as forest, water, landscape, diversities of plant and animal species, precipitation, and optimum temperature. The landscape is mainly mountainous or hilly and is under natural and anthropogenic environmental insecurities. The natural environmental insecurities are due to high seismicity, frequent landslides and avalanches, soil degradation and erosion, the decline in genetic diversity, catastrophic flooding, wildfires, high wind speed, elevated temperature, and radiation. Whereas, anthropogenic environmental insecurities include global warming associated with climate change, overexploitation by the human population, destruction of forest and local biodiversity, wildfire of the forest, urbanization, construction of infrastructures, and spread of the tourism sector (Khawas 2009). Moreover, there are other risks in IHR due to instability in tectonic plates, fragile ecosystems, poverty of farmers, and subsistence agriculture (Tiwari and Joshi 2015). Besides, the regions have fundamental agricultural insecurities due to inaccessibility, sensitivity and marginality, and other socio-economic risks (Pratap 1999; Gioli et al. 2019). These constraints hinder the environmental cycle and reduce natural resources. The only promising
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approach to manage this problem is carbon sequestration, which can maintain the natural resources cycle of IHR for a sustainable environment.
1.4
Carbon Sequestration
Carbon sequestration (CS) is defined as the long-term capture and storage of carbon in terrestrial land (soil and vegetation) and in the hydrosphere to reduce the excessive emission of carbon dioxide (the major GHG) to the atmosphere (DOE 2006). CS is of two types: naturally driven and geologically driven. The former includes humification of plant materials, accumulation of CO2 as secondary carbonates, production of biomass, and the management of above and belowground storage, so that the rate and magnitude of sequestration can be enhanced within an ecosystem. Geologic sequestration has the largest potential to store the maximum amount of atmospheric CO2 but is very expensive to practice and guarantees no losses (Lal et al. 2007). However, the natural storage of soil carbon is different from carbon sequestration which is permanently storing the atmospheric CO2 in geological reservoirs (Layek et al. 2022). In addition, soil carbon storage has the potential to be easily released as CO2 into the atmosphere if improper soil management systems are adopted (Siegelman et al. 2019).
1.5
Need for Carbon Sequestration in IHR
The Indian Himalayan Region (IHR) shares 75% of the forest land of India’s total forest cover. The IHR has a significant role in the global carbon cycles as forest contributes 60% of the total terrestrial’s carbon stocks (Sandeep et al. 2014) and in India is considered a zone of carbon sink. The amount of net carbon in the atmosphere and carbon sink in the soil can be examined by considering the total soil biomass content and the rate between production and exploitation (Singh et al. 1985). Due to the overexploitation of forest land, the IHR represents a source of CO2 emission to the atmosphere, contributing to global warming; thus forests are now the largest contributor to atmospheric CO2 in IHR. This excess atmospheric CO2 can be trapped through CS and stored in the soil as carbon stocks, which is possible with the conservation of forest land, management of soil, and cultivation under sustainable agriculture and can reduce the atmospheric CO2 content. The CS process is necessary for reducing the excess CO2 content from the atmosphere to mitigate climate change and enriching the soil with organic matter stored as SOC stock, thereby enhancing the soil diversity and improving the soil’s physicochemical properties for optimum crop yield. In IHR, atmospheric carbon can be potentially sequestered up to 3000 mt (million tons) which is 40% of the carbon stock of total India’s forest carbon (Rawal et al. 2021). The sequestered atmospheric carbon is stored in the soil as SOC content and stocks, i.e., 4.3–27 g/kg-1 and 6.6–54 Mg ha-1, respectively (Dar and Sahu 2018). The SOC maintains ecosystem functions and increases soil and crop
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productivity (Yadav et al. 2017), depending on land use and land use change, soil management, vegetation types, and altitude of the area (Han et al. 2010).
1.6
The Potential of Soil Carbon Stocks in IHR
The natural ecosystem of IHR is the most fragile and largest carbon storage mitigating the excess atmospheric CO2 content with a positive impact on the livelihoods of humans and animals (Sheikh et al. 2021). It is the home of diverse species of flora and fauna presenting the highest potential of sequestering carbon and accumulating biomass. The forests of the Himalayan regions are classified into dry temperate, moist temperate, subalpine, and montane wet temperate. The dry temperate forest has a soil carbon stock of 217.9 Mg/ha, the moist temperate forest of 216.9 Mg/ha, the subalpine forest of 213.2 Mg/ha, and the wet montane temperate forest of 172.3 Mg/ha. Among the Indian Himalayan states, the forest of Sikkim exhibits the highest soil carbon stocks (171.0 Mg/ha) followed by Jammu and Kashmir (165.3 Mg/ha) and Himachal Pradesh (163.5 Mg/ha) (Kumari et al. 2022). However, achieving carbon storage and mitigating climate change in the upper altitude of Himalayan regions is difficult due to the dry cold climate, land use type, and maximum land holding capacity by people (Chisanga et al. 2018).
1.7
Status of Food Production in IHR
Rice followed by maize is the staple food of majority people living in Eastern Himalayas, and the cropping intensity is very low (Das et al. 2020). The natural resources in IHR are under threat due to unsustainable human activities, environmental hazards, and diversity fragmentation. Besides, the farmers of IHR are still adopting a subsistence farming system due to less infrastructure, poor facilities, and even natural calamities (Kumar et al. 2021). Despite these constraints, the food production system and households’ needs are sustained over periods. The land for food production (agricultural land) is often abandoned in IHR due to climate factors such as drought, flood, mass landslides, forest fire, overexploitation of natural resources, etc. (Tiwari and Joshi 2015). Therefore, the region becomes insecure about food and nutrition, with 50% of the population suffering from malnutrition (Rasul et al. 2019). Moreover, 38% of the total families in IHR are challenged by food insecurity (IMI FAO Report 2019). The production of total cereals in Northeast India has increased at the rate of 1.83% annually during last decade (2009–2010 to 2018–2019) (Table 1.1). There is 41% increase in the total cereal production in NE region as during TE 2018–2019 (TE: triennium production, average of 3 years) as compared to TE 2008–2009. Northeast India has produced 10 % more cereals than the requirement. Nevertheless, the IHR is bestowed with many agroecosystems consisting of various niche regions suitable for value-added crops such as medicinal and aromatic plants, organic agriculture, and other agri-based technologies. The conservation of
116
5686
251
5091
2880 1156 9825
260 187
9.10
2.00
3.67
2.79
4.03 2.24 1.28
5.70 0.94
462 237
4469 1424 10,979
6177
377
8111
244
Triennium production (2016– 2017 to 2018–2019) in “000” tonsa 7258 513 7867
78 26
55 23 12
20
50
43
110
% increase in production during TE 2008–2009 to TE 2018–2019 34 75 41
-30
-161
645 537
1791 5372 88,309
5372
537
2678 -3948 77,330 -183 -301
-28 -56
150 -73 -88
15
-6
-484
8595
805
-83
-1189
1433
10
704
7163
Percent (%) deficit/ surplus
Deficit/ surplus in 000 tons
Triennium requirement (2016– 2017 to 2018–2019) in “000” tons
Data sources: Directorate of Economics and Statistics, Department of Agriculture, Cooperation and Farmers Welfare, Ministry of Agriculture and Farmers Welfare, Govt. of India
a
Commodity Rice Maize Total cereals Total pulses Total food grains Total Oilseed Total vegetables Total fruits Milk Eggs (lakh nos.) Fish Meat
Triennium production (2006– 2007 to 2008–2009) in “000” tonsa 5425 294 5570
Compound growth rate (%) (2009–2010 to 2018–2019) 1.61 6.91 1.83
Table 1.1 Northeast India: status of food production and requirement
6 J. Layek et al.
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natural resources of IHR for attaining sustainable agriculture is possible through proper planning, investment in scientific technologies, and management of soil and a land approaching “carbon sequestration.”
1.8
Carbon Sequestration: Mitigating Climate Change and Enhancing Food Security
In the last few decades, the destruction of the natural environment by clearing forest land, intensive agricultural practices, and overpopulation have altered the CO2 and O2 cycle, increased the excess CO2 content in the atmosphere, and led to climate change. Climate change is not only the rise in atmospheric temperature but also impacts precipitation pattern and amount, alters soil quality, and degrades land and floral and faunal diversities of the region. With the advancement of scientific agricultural knowledge, carbon sequestration is made possible through the anthropogenic activity. It is an indirect way of carbon sequestration supporting the growth of plants and can include the conversion of barren land into productive land, slash and char, conservation agriculture, and natural farming. In all these processes, growing plants is a must, i.e., plants only can mitigate climate change. The atmospheric CO2 absorbed by plants is stored in the form of cellulose, hemicellulose, lignin, lipids, etc. and becomes a source of soil organic matter that is converted to soil organic carbon (SOC) by the decomposition process. The SOC is the energy and carbon source of soil microorganisms and is the driver of the whole ecosystem. The concentration of SOC is an indicator of soil quality, and further, it impacts flora and fauna and then the human population well-being. The optimum level of SOC content in soil is 10–15 g/kg in the rhizospheric zone of plants (Lal 2015). The enhancement of the SOC level is necessary for improving food and nutritional security, mitigating climate change, and approaching sustainable agriculture. The depletion of SOC degrades the soil quality and reduces crop biomass production. Restoration of the SOC is an important strategy and the biomass of forest plantation of IHR has the largest scope for carbon sequestration. The SOC pool size has a direct impact on crop productivity and food security. An increase of stock of 1 ton SOC/ha/year can enhance crop production (cereal, legumes, roots, and tubers) by 30–50 million tons/year (Lal et al. 2007).
1.9
Methods of Adoption for Carbon Sequestration in IHR
Many international policies are approaching low-cost methods suitable for maximizing the sequestration of atmospheric carbon and mitigating climate change. The most attractive methods are agroforestry, growing perennial grasses, resource conservation practices, organic farming, nutrient management, application of biochar, residue management, and crop diversification. Different indigenous farming systems are also being practiced in the Indian part of eastern Himalaya, viz., Zabo systems (combination of agriculture, livestock, fishery, and forestry) of Nagaland,
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rice (Oryza sativa L)-based Apatani system of Arunachal Pradesh, Alder-based system in Nagaland, etc., that have been sustainable over the centuries (Das et al. 2020). Agroforestry consists of tree species and crop grown together within a specified area, improving crop diversification and providing more soil biomass content (Das et al. 2018). The high percentage of diversification is an indication of more carbon sequestration that, thereby, positively impacts environmental sustainability, resource conservation, and food security in the IHR (Bhatt et al. 2006). The Himalayan region follows various types of agroforestry such as agrihorticulture, agri-silviculture, agri-horti-silvi-pasture, agri-pisciculture, and multitier systems. The Eastern Himalayan region is famous for multistory agroforestry. The most suitable trees to increase carbon sequestration in the IHR are Alnus nepalensis, Pinus kesiva, and Michelia oblonga (Ghosh et al. 2009). The growing of perennial grasses covers the land and soil, prevents the loss of soil carbon from erosion, and increases the concentration of available N, P, and K (Das et al. 2016). The napier grass-covered soil has the highest content of SOC followed by Congo-signal grass among the other perennial grasses (Ghosh et al. 2009). The grass-covered soil can stock SOC in the range of 5.4% to 7.5% under forage and 2.3% to 10.4% under fertilization practices. The high root volume of perennial grasses is the source of soil organic matter which after decomposition increase the SOC content (Bonin and Lal 2014; Conant et al. 2001). A perennial grass system contains 30% more SOC in the long term (Ghosh et al. 2009). The tillage practice enhances the decomposition and mineralization of soil organic matter thereby decreasing SOC content in soil due to CO2 emission to the atmosphere. The soil management to conserve SOC stock is a prerequisite for carbon sequestration. It includes conservation tillage such as minimum/reduced tillage and zero tillage. Organic farming provides high-quality food production under sustainable agriculture. It increases SOC content through organic manures and has a great potential for soil carbon stock (Marriott and Wander 2006; Pimentel et al. 2005) and highly contributes to carbon sequestration as compared with a conventional farming systems (Garcia-Palacios et al. 2018). However, some research indicates that organic farming has no impact on carbon sequestration, as organic fertilization is not uniquely organic farming (Leifeld et al. 2013). Another strategy is integrated nutrient management (INM), with the utilization of both organic and inorganic fertilizers to restore SOC in degraded soils. The application of organic fertilizers alone impacts SOC and crop productivity (Ali et al. 2019). However, INM influences the sensitive carbon pools such as dissolved organic C, microbial biomass C, readily mineralizable C, and particulate organic C (Devi et al. 2017). Biochar is the pyrolyzed product of plant biomass that conserves biomass carbon in char form. It has the greatest potential of sequestering atmospheric CO2 among the various carbon sequestration approaches (Spokas et al. 2009; Karimi et al. 2022). The biochar application in soil represents a long-term sink of atmospheric CO2 and will be able to store 9.5 T of carbon by the year 2100 (Lehmann et al. 2006). As per the estimate, 1.3 Tg biochar containing 70% organic carbon can sequester 3.5 Tg of atmospheric CO2 (Mandal and Sharda 2013). The crop residues are usually removed from field sites for other household purposes (e.g., heating) or burnt in the field. These reduce the amount of organic material returned to the field and emit CO2
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to the atmosphere. The in situ and ex situ residue management with the incorporation of crop residue in the soil is a promising strategy for carbon sequestration by increasing the SOM content, mitigating climate change, and enhancing soil health for better crop productivity.
1.10
Conclusion
Very high rainfall over a short span of time and cultivation with unsustainable agronomic practices in steep slopes of hills accelerate soil erosion and soil carbon and nutrient loss. With the advancement in agricultural technologies, there is a rapid rate of degradation of the forest of IHR. The decline in SOC content due to anthropogenic activities, which emit excessive amounts of CO2 into the atmosphere, disrupts the natural ecosystem and negatively impacts climate and food production. Carbon sequestration is a strategy to minimize the CO2 concentration in the atmosphere by wide spreading cultivation of plants under proper management measures and planning. Adoption of integrated farming system, contour cultivation, reduction of biomass burning in shifting cultivation, agroforestry intervention, organic farming, integrated nutrient management, residue recycling, conservation agriculture, legume incorporation, etc. offer great scope for C-sequestration and improvement of soil properties and food security in Eastern Himalayan region. This mitigates climate change, supports a sustainable environment, and prevents the IHR population from food and nutritional insecurity.
References Ali W, Nadeem M, Ashiq W, Zaeem M, Thomas R, Kavanagh V, Cheema M (2019) Forage yield and quality indices of silage-corn following organic and inorganic phosphorus amendments in podzol soil under boreal climate. Agronomy 9:489 Baland JM, Bardhan P, Das S, Mookherjee D (2010) Forests to the people: Decentralization and forest degradation in the Indian Himalayas. World Dev 38(11):1642–1656 Beniston M (2003) Climatic change in mountain regions: a review of possible impacts. Clim Chang 59:5–31 Bhatt DK, Joshi VK, Arora RK (1999) Conodont biostratigraphy of the lower Triassic in Spiti Himalaya, India. J Geol Soc India 54(2):153–167 Bhatt BP, Bujarbaruah KM, Sharma YP (2006) Integrated farming system: a sustainable alternative for the benefit of small scale farmers and the environment. In: Bhatt BP, Bujarbaruah KM (eds) Agroforestry in North East India: opportunities and challenges. ICAR Research Complex for NEH Region, Umiam, pp 537–555 Bhutiyani MR, Kale VS, Pawar NJ (2007) Long-term trends in maximum, minimum and mean annual air temperatures across the northwestern Himalaya during the twentieth century. Clim Chang 85:159–177 Bonin C, Lal R (2014) Aboveground productivity and soil carbon storage of biofuel crops in Ohio. GCB Bioenergy 6:67–75 Brohan P, Kennedy JJ, Harris I, Tett SF, Jones PD (2006) Uncertainty estimates in regional and global observed temperature changes: a new data set from 1850. J Geophys Res Atmos 111:D12
10
J. Layek et al.
Chisanga K, Bhardwaj DR, Pala NA, Thakur CL (2018) Biomass production and carbon stock inventory of high-altitude dry temperate land use systems in North Western Himalaya. Ecol Process 7(1):1–13 Conant RT, Paustian K, Elliott ET (2001) Grassland management and conversion into grassland: effects on soil carbon. Ecol Appl 11:343–355 Dar DA, Sahu P (2018) Assessment of soil organic carbon stock in five forest types of northern Kashmir and Himalaya. India Forest Res 3(114):2 Das A, Patel DP, Ramkrushna GI, Munda GC, Ngachan SV, Buragohain J, Kumar M, Naropongla A (2014) Crop diversification, crop and energy productivity under raised and sunken beds: results from a seven-year study in a high rainfall organic production system. Biol Agric Hortic 30(2):73–87 Das A, Patel DP, Lal R, Kumar M, Ramkrushna GI, Layek J, Buragohain J, Ngachan SV, Ghosh PK, Choudhury BU, Mohapatra KP, Shivakumar BG (2016) Impact of fodder grasses and organic amendments on productivity and soil and crop quality in a subtropical region of eastern Himalayas, India. Agric Ecosyst Environ 216:274–282 Das A, Ramkrushna GI, Makdoh B, Sarkar D, Layek J, Mandal S, Lal R (2017) Managing soils of the lower Himalayas. In: Encyclopedia of soil science, 3rd edn. Routledge, London Das A, Layek J, Yadav GS, Babu S, Sarkar D, Meena RS, Lal R (2018) Managing nitrogen in small landholder hill farms of North Eastern Indian Himalayas. In: Lal A, Rattan A, Stewart BA (eds) Soil nitrogen uses and environmental impacts series: advances in soil science. Routledge, London, pp 257–282 Das A, Yadav GS, Layek J, Lal R, Meena RS, Babu S, Ghosh PK (2020) Carbon management in diverse land-use systems of Eastern Himalayan Subtropics. In: Carbon management in tropical and sub-tropical terrestrial systems. Springer, Singapore, pp 123–142 Devi S, Singh S (2023) Soil organic carbon sequestration in dryland soils to alleviate impacts of climate change. In: Enhancing resilience of dryland agriculture under changing climate: interdisciplinary and convergence approaches. Springer, Singapore, pp 221–245 Devi S, Gupta C, Jat SL, Parmar M (2017) Crop residue recycling for economic and environmental sustainability: the case of India. Open Agric 2:486–494 Dimri AP, Kumar A (2008) Climatic variability of weather parameters over the western Himalayas: a case study. In: Satyawali PK, Ganju A (ed) Proceedings of the national snow science workshop, Chandigarh (India): snow and avalanche study establishment, pp 167–173 Diodato N, Bellocchi G, Tartari G (2012) How do Himalayan areas respond to global warming? Int J Climatol 32(7):975–982 DOE (2006) Carbon sequestration. Department of Energy. http://cdiac2.esd.ornl.gov/index.html Garcia-Palacios P, Gattinger A, Bracht-Jørgensen H, Brussaard L, Carvalho F, Castro H, Milla R (2018) Crop traits drive soil carbon sequestration under organic farming. J Appl Ecol 55(5): 2496–2505 Ghosh PK, Saha R, Gupta JJ, Ramesh T, Das A, Lama TD, Munda GC, Bordoloi JS, Verma MR, Ngachan SV (2009) Long- term effect of pastures on soil quality in acid soil of North–East India. Aust J Soil Res 47:372–379 Gioli G, Thapa G, Khan F, Dasgupta P, Nathan D, Chhetri N, Adhikari L, Mohanty SK, Aurino E, Scott LM (2019) Understanding and tackling poverty and vulnerability in mountain livelihoods in the Hindu Kush Himalaya. In: Wester P, Mishra A, Mukherji A, Shrestha A (eds) The Hindu Kush Himalaya assessment. Springer, Cham Goswami S, Verma KS, Kaushal R (2014) Biomass and carbon sequestration in different agroforestry systems of a Western Himalayan watershed. Biol Agric Hortic 30(2):88–96 Han XH, Atsushi T, Mitsuru T, Shiqing L (2010) Effects of land-cover type topography on soil organic carbon storage on Northern Loess Plateau, China. Acta Agric Scand B Soil Plant Sci Acta Agr Scand 60:326–334 IMI FAO Report (2019) State of the Himalayan armers and arming. A part of the project “Strengthening Institutional Capacities for Sustainable Mountain Development in the Indian Himalayan Region” awarded by FAO under the TCP/IND/3601/C1 to IMI
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Karimi M, Shirzad M, Silva JA, Rodrigues AE (2022) Biomass/biochar carbon materials for CO2 capture and sequestration by cyclic adsorption processes: a review and prospects for future directions. J CO2 Util 57:101890 Khawas V (2009) Environmental challenges and human security in the Himalaya. In: Environmental concerns and sustainable development: some perspectives from India. TERI, New Delhi, p 32 Kumar P, Sharma PK, Kumar P, Sharma M, Butail NP (2021) Agricultural sustainability in Indian Himalayan region: constraints and potentials. Indian J Ecol 48(3):649–661 Kumari R, Kumar A, Saikia P, Khan ML (2022) Vulnerability assessment of the Indian Himalayan forests in terms of biomass production and carbon sequestration potential in changing climatic conditions. In: Handbook of climate change mitigation and adaptation. Springer, Cham, pp 147–161 Lal R (2015) Soil carbon sequestration in agro ecosystems of India. J Indian Soc Soil Sci 63(2): 125–143 Lal R, Follett RF, Stewart BA, Kimble JM (2007) Soil carbon sequestration to mitigate climate change and advance food security. Soil Sci 172(12):943–956 Layek J, Narzari R, Hazarika S, Das A, Rangappa K, Devi S, Mishra VK (2022) Prospects of biochar for sustainable agriculture and carbon sequestration: an overview for eastern Himalayas. Sustain For 14(11):6684 Lehmann J, Gaunt J, Rondon M (2006) Bio-char sequestration in terrestrial ecosystems—a review. Mitig Adapt Strateg Glob Chang 11:403–427 Leifeld J, Angers DA, Chenu C, Fuhrer J, Katterer T, Powlson DS (2013) Organic farming gives no climate change benefit through soil carbon sequestration. Proc Natl Acad Sci 110(11):E984– E984 Mandal D, Sharda VN (2013) Appraisal of soil erosion risk in the Eastern Himalayan region of India for soil conservation planning. Land Degrad Dev 24(5):430–437 Marriott EE, Wander MM (2006) Total and labile soil organic matter in organic and conventional farming systems. Soil Sci Soc Am J 70:950–959 Pimentel D, Hepperly P, Hanson J, Douds D, Seidel R (2005) Environmental, energetic, and economic comparisons of organic and conventional farming systems. Bioscience 55:573–582 Pratap T (1999) Sustainable land management in marginal mountain areas of the Himalayan region. Mt Res Dev 19(3):251–260 Rasul G, Saboor A, Tiwari PC, Hussain A, Ghosh N, Chettri GB (2019) Food and nutrition security in the Hindu Kush Himalaya: unique challenges and niche opportunities. In: Wester P, Mishra A, Mukherji A, Shrestha A (eds) The Hindu Kush Himalaya assessment. Springer, Cham, pp 301–338 Rawal R, Negi VS, Bhatt ID (2021) Changing outlook on harnessing biodiversity values–A special focus on Indian Himalaya. J Graph Era Univ 9:55–82 Sandeep S, Sivaram M, Henry M, Birigazzi L (2014) Inventory of volume and biomass tree allometric equations for South Asia. KFRI, Peechi, India Food & Agriculture Organization of the United Nations Rome Italy. UN-REDD Programme MRV report 15 Sharma K (ed) (1999) Encyclopaedia of Himalayas. Vol 3 central Himalayas. Anmol Publications Pvt Ltd, New Delhi Sheikh MA, Tiwari A, Anjum J et al (2021) Dynamics of carbon storage and status of standing vegetation in temperate coniferous forest ecosystem of north western Himalaya India. Vegetos 34:822–833 Siegelman RL, Milner PJ, Kim EJ, Weston SC, Long JR (2019) Challenges and opportunities for adsorption based CO2 capture from natural gas combined cycle emissions. Energy Environ Sci 12:2161–2173 Singh AK (2015) Advances in Indian cold water fisheries and aquaculture. J Fish Sci 9(3):48 Singh JS, Tiwari AK, Saxena AK (1985) Himalayan forests: a net source of carbon for the atmosphere. Environ Conserv 12(1):67–69
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Singh SP, Pandey A, Singh V (2019) Nature and extent of forest degradation in Central Himalayas. In: Tropical ecosystems: structure, functions and challenges in the face of global change. Springer, Cham, pp 27–43 Spokas KA, Koskinen WC, Baker JM, Reicosky DC (2009) Impacts of woodchip biochar additions on greenhouse gas production and sorption/degradation of two herbicides in a Minnesota soil. Chemosphere 77:574–581 Tiwari PC, Joshi B (2015) Climate change and rural out-migration in Himalaya. Change Adapt Socio-Ecol Syst 2(1):8–25 Tolangay D, Moktan S (2020) Trend of studies on carbon sequestration dynamics in the Himalaya hotspot region: a review. J Appl Nat Sci 12(4):647–660 Yadav GS, Lal R, Meena RS, Datta M, Babu S, Das A, Layek J, Saha P (2017) Energy budgeting for designing sustainable and environmentally clean/safer cropping systems for rainfed rice fallow lands in India. J Clean Prod 158:29–37
2
Soil C Sequestration in Himalayan Landscape: Impacts of Vegetation and Edaphic Interactions Under Changing Climate Iftekhar U. Ahmed
, Yonten Dorji
, and Purna B. Chhetri
Abstract
The vulnerability of Himalayan ecosystems under the present climate change scenario is receiving much attention because of its direct link with the ecological and socio-economic conditions of the vast area of South Asia. The region has an equal potential in contributing to global climate safeguard initiatives through its pristine vegetation covers. Soil C sequestration, i.e., transferring and storage of atmospheric CO2 as soil organic matter (SOM), not only mitigates climate impacts but also enhances food security of Indian Himalayan and the adjacent regions. We discussed the mechanistic understanding of how the unique climatevegetation-soil continuum of this region shapes up soil C sequestration with potential uncertainties. We explained recent paradigm shift on formation and fate of SOM that affects the interpretations of C sequestration process under local land-use systems with special reference to altitudinal forests of Indian Himalayas. The mountainous terrains of the region with mostly very to moderate dense canopy forests have the potential of positive feedback to elevated atmospheric CO2 by fixing C in biomass and soil. However, the response of climate change on I. U. Ahmed (✉) Institute of Forest Ecology, University of Natural Resources and Life Sciences, BOKU, Vienna, Austria e-mail: [email protected] Y. Dorji Department of Forest Science, College of Natural Resources, Royal University of Bhutan, Punakha, Bhutan Department of Spatial Structures and Digitization of Forests, Georg-August-Universität Göttingen, Göttingen, Germany P. B. Chhetri Bhutan Ecological Society, Kawajangsa, Thimphu, Bhutan # The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Mishra et al. (eds.), Soil Carbon Dynamics in Indian Himalayan Region, https://doi.org/10.1007/978-981-99-3303-7_2
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soil C stock in these dense vegetation covers is largely unknown. As a case study, here we investigated above and belowground tree biomass, litter-fall, soil physicochemical, and microbial properties in relation to soil C stocks in two forests of subalpine coniferous, dominated by hemlock (Tsuga dumosa), and temperate mixed broadleaved, dominated by oak (Quercus lanata and Quercus griffithii) at altitudes of 3300 and 2300 m, respectively. We found that C storage differed significantly along vertical distribution across the forest types. However, the influence of vegetation cover on soil C was inconsistent; rather, local climateinduced soil and site properties seemed to be predominant factors. Finally, we reviewed existing knowledge gaps and current challenges in understanding the nature-based climate solution through long-term soil C sequestration in Indian Himalayan regions. Keywords
C sequestration · Indian Himalaya · Altitudinal forest · Soil organic C · Aboveground biomass · Fine root
2.1
Introduction
2.1.1
Significance of C in Global Climate
With a high degree of certainty, elevated atmospheric carbon dioxide (CO2)-induced global warming is the main cause of recent unprecedented climatic variations all over the world. There is a common consensus among the scientists that global warming and consequent climate change are influenced largely by the increasing atmospheric concentration of CO2 (Beedlow et al. 2004). Approximately 650 thousand years ago, during the glacial-interglacial period, the atmospheric concentration of CO2 was between 180 ppm (glacial maxima) to 300 ppm (warm interglacial maxima) (Siegenthaler et al. 2005). Before the industrial revolution (1750), it was relatively constant at 280 ± 10 ppm for several thousand years (IPCC 2001). After 1750, the CO2 concentration has been increasing gradually, and in June 2022, it was 420.99 ppm (www.co2.earth), and the predicted concentration in 2100 would be 450 to 475 ppm depending on the rising temperature of 1.8 and 2.0 °C, respectively (www.co2.earth). Although only 0.04% of atmosphere, CO2 is the leading greenhouse gas to absorb and radiate heat from and toward earth’s surface. Thus, the most basic building material of life on the earth has become civilization’s greatest threat (Roston 2008). Therefore, removing CO2 from atmosphere and reducing terrestrial emission of greenhouse gases to air are critical to getting rid of the catastrophic consequences of climate change. In addition to tremendous research initiatives, various technologies and strategies have been employed to achieve the carbon (C) reduction targets. Absorbing atmospheric CO2 in trees, plants, and soil of global forests has been recognized as a pilot strategy to mitigate climate change impacts (IPCC 2019). Globally, forest
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ecosystems absorb, on average, 2 billion metric tons of C per year from the atmosphere (Harris et al. 2021). In the USA, forest removes 13 % of the total greenhouse gas that emit annually (NCSL 2022). However, there are the opposite scenarios as well because a considerable part of the absorbed C releases to atmosphere through soil respiration and land-filling of forest products. The bottom line is the residence time of locked C in forest ecosystems either in woody biomass or in soil organic matter (Pierson et al. 2021). Although some researchers argued that conversion of biomass C to soil C, especially as “stable humus” is a more lasting solution than C in standing biomass (Batjes 1998). However, recent paradigm shift of soil organic matter stability revealed the risk of C escape from so-called stable pool in soil (Dynarski et al. 2020). Although at the global scale, C stocks in the forest biomass and soil were estimated around 44 and 45% of total forest C, respectively (Food and Agriculture Organization of the United Nations 2010), other pools such as dead wood (5%) and forest litter (6%) also significantly contribute to world’s forest C stocks.
2.1.2
Soil C Sequestration: Net Balance Between Inputs and Outputs
The basic concepts of C sequestration rely on the removal of atmospheric CO2 to plant biomass and/or soil pools with a longer mean residence time (MRT, usually 100 years in agricultural systems) without re-emitting to atmosphere (Lal et al. 2015; Stockmann et al. 2013). Mechanistically, primary productivity in nature is a major pathway to remove atmospheric C and fix in terrestrial biomass pools. However, atmospheric deposition of organic C through precipitation is also considered a major C transformation pathway to lithosphere (Iavorivska et al. 2016). In forest ecosystems, C flux includes a long-term biogeochemical transformation starting from carbohydrate (initial product of photosynthesis) to hydrocarbon (fossil fuel) and a short spectrum of biomass to humus with a time frame of several years to millennia. A significant part of photosynthesized C may release into atmosphere during these transformations depending on many external biotic and abiotic factors and the quality of C compounds evolved. The input C may accumulate in woody and leafy biomass, litter on forest floor, root biomass, etc. The output processes include soil respiration, leaching loss, and harvesting of forest products (Fig. 2.1). The balance between C inputs and the outputs in forest systems represents the C sequestration potential. However, due to variable amounts of labile and recalcitrant C pools that are changing over time, the exact quantification may fluctuate depending on temporal attributes (Mendes et al. 2020). Forest management interventions can manipulate these C pools and fluxes, creating the potentiality for mitigation of climate change impacts. Soil C is much more complex than the aboveground part in forest both in the direction of accumulation and dynamics. Tree biomass is analogous to primary production as biomass accumulates atmospheric carbon through photosynthesis. Therefore, the net primary production (NPP) is generally estimated by measuring plant biomass and is thus considered as a basic
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Fig. 2.1 Ecosystem C sequestration: balance between C inputs and outputs
parameter in ecosystem research (Landsberg and Gower 1997). However, estimation of forests biomass has received much attention in recent years because, firstly, anthropogenic emissions of CO2 are thought to be partially offset by increasing forest biomass and, secondly, a change of biomass regionally is associated with important components of climate change (Houghton 2005). Tree biomass can be divided into two broad categories based on temporal sensitivity to climatic feedback: short-lived biomass (i.e., leaf, fine root, and litter) and long-lived components (i.e., woody biomass and structural roots), with contrasting responses on the source-sink behavior of forest ecosystems (Bloom et al. 2016). Biomass allocation between above and belowground organs of trees has profound impacts on terrestrial C storage, and recent study reported a shift in allocation pattern (C allocation on shoot vs. root) due to global warming and other global changes (Zhou et al. 2022). Fine roots play an important role not only in the uptake of nutrients and water but are also an important sink for carbon acquired in terrestrial net primary productivity. The total fine root carbon pool is 5% of the size of the atmospheric carbon pool and 33% of annual net primary productivity. Fine root biomass promotes soil C sequestration by providing slow-cycling C; the contribution is more efficient than the aboveground biomass such as leaves and needles (Keller et al. 2021). The root system of more than 80% of terrestrial plants is colonized with mycorrhizal fungi, creating a significant stock of photosynthetic C in large hyphal networks.
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Soil C Forms, Dynamics, and Potentials
Soil organic carbon (SOC) is the second largest reservoir of organic carbon (C) in earth systems, after the oceans. Building stocks of SOC has recently been promoted as a natural climate solution through its potential long-term sequestration and protection against further CO2 emissions (Bossio et al. 2020). Globally, the soil C pool is estimated to be 1500 Gt C within the top meter, with the largest concentration of organic C occurring within the top 30 cm, i.e., the zone of maximum soil microbial and root activities (Seuradge et al. 2017). However, recent studies have shown that a considerable amounts of C are stored in subsoil layers (below 40 cm), and in some ecosystems, more than half of stabilized C is located 30 cm below the surface (Balesdent et al. 2018). In most mineral soils, organic carbon (C) protection has been attributed primarily to abiotic mechanisms, including physical protection, organo-metal complexes and association with crystalline phyllosilicates (Gabriel et al. 2018). Physical protections through the formation of micro- and macroaggregates cause spatial in accessibility of OC against microbial decomposers. Organo-metal complexes are the most common C-fixing processes in soil that include absorption of organic molecules on the surfaces of Fe, Al Mn-oxides, ligand exchange with organo-metal, and polyvalent metal-cation bridges (Fig. 2.2). However, recent studies revealed that Fe (hydro) oxide-associated protection occur only in static conditions; in oxygen-limited environments, Fe enhances SOC mineralization (Chen et al. 2020). Although organic C associated with crystalline clay minerals contributes a minor fraction, the strong fixation implies a significant role in promoting long-term C storage (Churchman et al. 2020). Dissolved organic C (DOC) is an important pathway of fresh, labile organic C flux into the deep soil layers, which is hydrologically transported from the forest
Fig. 2.2 Different components of organic C in soil, although interexchange between components is a continuous process in SOC dynamics
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floor or rhizosphere to subsoil layers and surface water. Although decomposed forest floor materials are recognized as the major source of DOC, labile organic compounds in subsoil mainly originate from root turnover and exudates (Sokol et al. 2019). As a part of dissolved organic matter, DOC forms clay oxide associations and aggregates, which are considered fundamental mechanisms for C stability in all transportation, including deep soil C stock (Gmach et al. 2020). Since DOC contains readily available C (labile C and root exudates), it serves as a source of energy to stimulate soil microbial degradation of stable organic C (Liao et al. 2020). DOC generally leaches from the surface or litter layer into mineral soil and then discharges into underground water tables or streams. The biogeochemical consequences of these huge amounts of active C on deep soil C reserves are seldom investigated. Traditionally long-term stability of soil organic C is thought to have occurred through the formation of humus (certain complex substances resulting from microbial decay products, resistant to further decay with inherent characteristics of stability). In addition, other chemically “recalcitrant” substances (i.e., lignin, suberin, chitin derivatives) can form more stable substances associated with microbial by products (Kallenbach et al. 2016). However, recent advances revealed that the stability of soil organic C are associated with interactions of physical, chemical, and biological attributes of soil environment, not an inherent property of any chemical compound (Schmidt et al. 2011; Chen et al. 2019). The concept of “chemical recalcitrant” organic fraction was also criticized as, under appropriate environment, these materials can also be decomposed (Schmidt et al. 2011). In exchange, soil organic C in particulate organic matter (POM) and mineral-associated organic matter are considered as more stable forms.
2.1.4
C in Deep Soils
The contribution of deep soil C to soil C pools is enormous due to its quantity and quality. Understanding the physical, chemical, and biological mechanisms that control deep soil organic C cycling is crucial to promote soil management activities that enhance the long-term sequestration of SOC (Gross and Harrison 2019; van der Voort et al. 2019). It is often assumed that soil C age is positively correlated with soil profile depth and that organic C susceptibility to decay processes decreases with depth Indeed. In an early study, Ohno et al. (2017) estimated the mean residence time of soil organic matter in B horizon of a temperate deciduous forest to be 1350 years, while a recent review showed that deep soil C is a major component of the global terrestrial SOC pool that is hundreds to thousands of years old (Gross and Harrison 2019; Shahzad et al. 2018). Although the reasons for this long-term stability are unclear, incorporating fresh C leachate from upper horizons might be instrumental to mineralizing these enormous old C, especially in sloppy landscapes. The potential destabilization of these old and deep SOC reserves would undoubtedly be detrimental to soil carbon storage and potentially fuel climate-carbon feedback to
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the atmosphere. Therefore, understanding the dynamics of deep soil C cycling is critical to protecting this valuable ecosystem resource.
2.2
Indian Himalayan Regions
2.2.1
Multidimensional Diversity and Vulnerability
Indian Himalayan regions (IHR), originally the major parts of Hindu KushHimalayan mountain ranges, extend horizontally 2500 km from Jammu and Kashmir to the northeastern state of Arunachal, and vertically, altitudinal forests vary between 300 m and 5000 m (Singh and Singh 1987). Although the extet and active influencing periphery of IHR cover vast areas of 12 states, we are considering only altitudinal forests along the mountain ranges for the current study (Fig. 2.3). Himalayan ecosystems are vulnerable to global climate change, and some studies indicated that the impacts are three times higher than the global average (Xu et al. 2009). Recent assessments of current situations and future predictions revealed increased temperature and anomalies of rainfall patterns over the Indian Himalayan region (Dimri et al. 2021). Another hydro-climatic issue of the Himalayan region is the delay or failure of monsoons. The Asian summer monsoon is associated with availability of water resources for the livelihood of densely populated South and Southeast Asia and the sustainability of its natural ecosystems. Although Asian
Fig. 2.3 Extend of three Indian Himalayan regions, viz., Western, Central, and Eastern. Yellow star points indicate elevation of local mountains
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monsoon failure is an old phenomenon due to combined effects of El Niño and Southern Oscillation by altering the zonal pattern of moisture transport (Webster et al. 1998), recent studies predicted the event would be more frequent in future because of adding climate change effects (Schewe and Levermann 2012). The temporal water stress caused by monsoon failure might impact the forest ecosystems because variations in seasonal precipitation can influence tree growth at species level (Clark and Clark 1994).
2.2.2
Forest Pattern at Altitude: Control of Moisture
Heat deficiency at mountain regions’ high elevation is generally considered the major limiting factor for tree growth because of decreasing soil and air temperature (Holtmeier 2009). However, tree growth in mountain is limited by soil moisture as well. Precipitation pattern in Himalayan region is generated under the interactions between two contrasting climate systems: warm subtropical climate with moist air of Indian Himalaya and cold and dry air from Tibetan Plateau. Consequently, the region is influenced by the monsoon across the Eastern, Central, and part of the Western Indian Himalayas. Bhat et al. (2012) observed different soil moisture levels under specific species-dominated forests along an elevation gradient in Garhwal area of Western Himalaya (Fig. 2.4). While the Himalayan mountains are considered as young, from a geodynamical point of view, altitudinal and climatic gradients generated incredibly diverse vegetations. For example, in the Eastern Himalayan State of Arunachal, altitudinal forests (>300 m asl) comprise 67,000 km2 of area, with 25% forests above 2000 m and 15% above 3000 m (Fig. 2.5; Saikia et al. 2020). Undoubtedly these overwhelmingly species-rich forests are a source of enormous belowground C reserves. However, the factors affecting the stability and protection of this valuable ecosystem resource are extremely important in global climate change perspectives. Fig. 2.4 Soil moisture under different vegetation along an elevation gradient in Garhwal region of Western Himalaya. (Data source: Bhat et al. 2012)
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Fig. 2.5 Extend of different forest types with canopy cover along an altitudinal gradient in Eastern Himalayan State of Arunachal. (Data source: Saikia et al. 2020; FSI Report 2015; Singh and Singh 1987)
2.2.3
Climate Shapes-up Vegetation Zone
In Himalayan regions, altitudinal gradation, combined with local temperature and precipitation, create a unique forest vegetation gradient that ranges from subtropical forests at lower altitude followed by mixed deciduous and evergreen broadleaved at the mid and again coniferous at the highest altitude. Soil moisture has been recognized as one of the major factors behind such species distribution along an altitudinal gradient (Wangda and Ohsawa 2006). Under the changing climate, the responses of these moisture-induced forests are uncertain as temperature and moisture are two driving factors of climate change impacts. The formation of vegetation zones in relation to climate and elevation is generally complex, and influences of other factors, such as soil, latitude, solar radiation, etc., are substantial (Malizia et al. 2020). In Indian Himalayan regions, the details of vegetation zones were reviewed by Singh and Singh (1987) (Fig. 2.6), and broad forest ranges between submontane broadleaved forest (which is analogous to tropical rain forest) to subalpine to alpine along an altitudinal gradient were reported. In addition, the region’s horizontally drier climate in Western Himalayan to relatively moist Eastern parts affects the vegetation structures in the entire region. Elevation-induced variations in forest species obviously affect soil organic C storage, but due to erosion vulnerability, loss of dissolved organic matter (DOM) through landslides and surface overflow in Himalayan regions should be considered (Goyal et al. 2022).
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Fig. 2.6 Vegetation (tree) pattern along altitude in three Indian Himalayan regions. Temperature and rainfall at different altitudes play a major role in the formation of forest types. The climatic zones correlate with altitude to create the vegetation zones. (Data source: Ramachandran and Roy 2018; Singh and Singh 1987)
2.2.4
Soil C Sequestration & Land-use Pattern
The land-use patterns in Indian Himalayan regions are largely developed under the influences of altitudinal zonation of climate and vegetation on one hand and the utilization of natural resources to secure the livelihood of local communities on the other. In general, the land-use pattern in the region consists of a tropical/subtropical forests at the lower altitude (2500 and 3200 m elevation range with a mixture of coniferous (Tsuga dumosa, as dominant tree species) and broadleaved (Quercus semecarpifolia as dominant species) trees. On the other hand, the broadleaved site (Pangsho Gompa) recognized under the warm-temperate climatic zone ranges between 2000 and 2500 m elevation with both evergreen and deciduous broadleaved species (Quercus lanata and Quercus griffithii as dominant trees). The detailed characterization of the two sites is presented in Table 2.2 and Fig. 2.7.
2.3.2
Soils
Bhutan is located on the South face of Eastern Himalayas and is considered to have one of the most complex landscapes in the world, ranging from high altitude with very steep slopes to deep valleys with big rivers and flat valley-bottom. The soil parent materials originated from Tethyan metamorphic sediments with considerable colluvium drifts (Jangpangi 1978; Baillie et al. 2004). Like other Himalayan regions, the soils of Bhutan were formed under the combined influences of local climatic
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Table 2.2 Site characteristics of coniferous mixed and broadleaved forests under studya Location and climate Site
Plot size and number Elevation (m) and slope Air temperature Rainfall Climatic zone Vegetation zone Forests Composition (over and understory vegetation) Height and DBH (m and cm) Tree density (tree per ha) Basal area (BA) (m2 h-1) Soils Classification (WRB, FAO) Textural class Bulk density (g cm-3) Soil pH CEC (cmol kg-1) Soil organic matter (SOM) a
Coniferous mixed forest Tashigang, Thimphu District, Bhutan (27°28′00″N; 89°44′31″E) 25 × 29 m, 4 3260 m, 25–30° 8 °C (range: 13.7–2.5°) 1175 mm Cold-temperate Mesic species
Broadleaved forest Pangsho and Wangduephodrang districts, Bhutan (28°28′51″N; 89°51′28″E) 25 × 29 m, 4 2460 m, 15–25° 12 °C (range: 17.4–6.3°) 1027 mm Dry temperate Xeric species
Tsuga dumosa, Quercus semecarpifolia, and Rhododendron arboreum 20.3 ± 11.6 and 41.1 ± 33.5
Quercus griffithii, Quercus lanata, and Rhododendron arboreum 13.7 ± 8.4 and 25.9 ± 16.4
401 ± 83 77.8 ± 14.2
667 ± 145 47.3 ± 12.4
Endoskeletic Cambisols
Endostagnic Luvisols
Clay loam 0.66 ± 0.03 5.2 ± 0.2 90.5 ± 14 16.02 ± 1.02
Silty clay 0.60 ± 0.02 5.0 ± 0.2 35.6 ± 4 15.78 ± 1.49
Details of site description in Wangdi et al. (2017)
conditions, altitude, steepness of slopes, and vegetation succession, resulting in a diverged soil characteristic within short spatial variation. However, in the forest of Bhutan, a strong interaction between forest vegetation and soil parent materials contributed to the formation of distinct soil types along altitudinal gradients (Ohsawa 1987). The soils of coniferous and broadleaved forests are recognized as brown and yellow-brown forest soils, respectively, based on field survey and soil properties (Okazaki 1987). Baillie et al. (2004) suggested that the soils of mid-altitude (between 2200 and 3500 m) in Himalaya are generally qualified as Cambisols (Worl Reference Base (WRB) system) because of their moderate to advanced level of weathering and leaching. Although our both experiment sites were within the altitudinal range of Cambisols, the soil qualified as Luvisols due to agricultural land-use history with clay illuviation in broadleaved site (Table 2.2).
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Fig. 2.7 Basal area and tree composition (% of total tree number) of mixed coniferous and broadleaved forests
2.3.3
Aboveground Biomass
Biomass C in the living tree includes C stock in aboveground vegetation plus stocks in root systems which are primary sources of C for soil and atmosphere (through burning of wood products). We measured height and DBH of all trees in two locations and estimated total aboveground biomass (woody and leafy) using allometric equations developed for coniferous and broadleaved species of respective vegetation zones (Tashi et al. 2017). The common pattern of the allometric model was: Log AGB = α + β1 log (DBH2), with zone-specific values of coefficient α and β1 for cold-temperate broadleaved, cold-temperate coniferous, and warm-temperate broadleaved trees, where AGB = aboveground biomass. The spatial distribution of tree species in Himalayan landscape is broadly regulated by the combined impacts of local climate (i.e., temperature and precipitation), soil characteristics, and elevation (Ramachandran and Roy 2018). The variations in tree species identity and composition in our two locations clearly resulted in more than double aboveground biomass in coniferous forests compared to the broadleaved forest (Table 2.3). Aboveground biomass can be divided into three components: woody biomass (stem and branches), leaves, and bark. Although
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Table 2.3 Sequestrated C in different components of forest ecosystems in two forests under study. Biomass and litter were expressed as dry weight of plant tissue, and forest floor materials were presented as density of each fraction Ecosystem C pools Aboveground biomass (kg m-2) Annual litterfall (g m-2) Fresh litter Forest floor density (kg m-3) Partly decayed Decomposed litter Fine (>2 mm dia.) Root biomass (g m-2) Coarse (2–5 mm) Top (0–50 cm) Soil organic C stock (kg m-2) Deep (50–70 cm)
Coniferous mixed forest 89.02 ± 11.14 697 ± 29 19.21± 5.30 21.81 ± 6.15 143.01 ± 41.40 463 ± 56 218 ± 42 19.18 ± 1.28 4.65 ± 0.70
Broadleaved forest 37.33 ± 5.18 677 ± 10 38.00 ±8.57 24.10 ± 3.81 136.42 ± 13.45 627± 81 422 ± 47 11.00 ± 1.05 2.31 ± 0.16
the C concentration in all biomass fractions is roughly 50% of dry mass, longevity of C as living biomass varies considerably according to forest management, disturbances, and the life span of trees. Neumann and Lawes (2021) estimated that bark constitutes about 20% of the total aboveground biomass of trees and significantly differs in density from wood. In our study, broadleaf trees of Quercus spp. had fissured bark, and coniferous Tsuga spp. showed scaly bark indicating the accumulation of a considerable share of biomass and C allocation. In natural old-growth forests, all stem wood parts, including bark, branches, foliage, tree tops, and twigs, are treated as an input to the soil as litter and detritus if not extracted. However, there is an uncertainty regarding C flux from aboveground biomass to soil organic matter over harvesting of forest products in unmanaged stands. In general, sequestrated C remains in extracted wood biomass until the wood products are decomposed or burned. Sato and Nojiri (2019) evaluated different approaches to reporting harvested wood products (HWP) emission in several countries and found that the contribution of HWP is nearly 1% of total national emission; however, for accuracy of assessment, it is necessary to estimate wood products related C emission at a national level.
2.3.4
Litterfall
Litterfall process is the most active mechanism that translocates C from aboveground biomass to soil and is an important pathway of nutrient cycling. However, major portions of falling litter are leaves, resulting in a significant part of biomass C release to atmosphere during the decay processes depending on the chemical and anatomical traits of the leaf (Portillo-Estrada et al. 2016). Therefore, the quality and quantity of the litter influence soil C sequestration potentials. More or less the same annual litterfall (on average 687 g m-2) were recorded in the mixed coniferous and broadleaved forests of our present study (Table 2.3). Tiwari and Joshi (2015) reported annual litter flux of 716 g m-2 and 623 g m-2 in Q semecarpifolia dominated and mixed forests, respectively, at 2250–2500 m elevation of Western
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Himalaya, Uttarakhand. In a recent study, Ahirwal et al. (2021) investigated patterns and influencing factors of litter dynamics in forests of major climatic zones of Indian Himalayan regions. The results demonstrated 545 gm-2 annual litterfall in subtropical and temperate forests with significant effects of precipitation on litterfall patterns. These findings and our data indicate the impacts of elevation-induced climatic variation on litterfall in Himalayan forest ecosystems.
2.3.5
Forest Floor
Forest floor litter pools are a transient stage of C flux between leaf litter (from litterfall inputs) and soil organic matter. Humification is the long-term process by which decomposed plant litter is converted to soil organic matter – the key pool of sequestrated C in the entire ecosystem (Ni et al. 2016). The third category of forest floor materials in our study is decomposed litter, the previous stage of humification (Table 2.3). Our data suggest that although density of fresh litter is higher in broadleaved forests, decomposed materials are higher in coniferous forests, indicating a higher source of stable C in the coniferous site. Our results are consistent with previous observations that coniferous species accumulate more organic C in the forest floor than the deciduous species (Augusto et al. 2015; Vesterdal et al. 2013). Forest floor substances are obviously subjected to numerous microbial attacks; therefore, litter quality might have played a dominant role in attracting decomposer organisms. Coniferous litter contains more recalcitrant compounds than broadleaved (Berg 2000), resulting in a larger litter deposition on the forest floor of mixed coniferous forest.
2.3.6
Fine Root
Fine root production and turnover have enormous ecological and climate change impacts but are also vulnerable to environmental stress (Olesinski et al. 2011). In general, fine root production contributes 22–40% of net primary productivity (NPP) in terrestrial ecosystems (McCormack et al. 2015). Root-mycorrhizal association is a dominant mechanism in transferring root-derived C to SOM through the turnover of the mycorrhizal external mycelium (Godbold et al. 2006). Due to rapid turnover, fine roots are recognized as a very dynamic C pool in soil and significantly contribute to soil organic matter accumulation. We used 80 cm soil corer (7.6 cm diameter) to extract fine roots from both locations. Evaluation of standing fine root biomass revealed that broadleaved forest had 1.3 times higher biomass than the mixed coniferous (627 and 463 g m-2, respectively, at the top 30 cm) and 0–10 cm soil layer contained 58% and 45% of total fine root biomass, respectively (Table 2.3). This pattern of fine root stock and distribution are consistent with the previous studies of similar forest composition and altitude of Himalaya. Joshi and Garkoti (2021) estimated fine root biomass of 824 g m-2 in Q. leucotrichophora and 729 g m-2 in mixed species of Q. leucotrichophora and A. nepalensis with 48% in
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0–10 cm layer in Uttarakhand of Central Himalaya. In a recent study, Rawat (2012) reported 494 and 322 g m-2 fine root biomass with 82% in the top 40 cm in Himalayan moist temperate oak (Quercus leucotrichophora) and subtropical pine (Pinus roxburghii) forests, respectively. Verma et al. (2021) estimated 134–285 g m-2 fine root biomass in a mixed forest of these two species at lower elevations. However, the variability in fine root biomass might be attributed to species composition and local climatic variations. High fine root concentration results in a greater annual turnover rate and more C input to soil. Liu et al. (2019) found that environmental factors play a driving role in fine root production and decomposition toward forming soil organic matter.
2.3.7
Soil Organic C
Soil organic C stock is the major and relatively stable C pool in forest ecosystems. Therefore, C sequestration in soil organic matter is the main focus of forest-based climate mitigation strategies. In our study, mixed coniferous forest exhibited 72% more C stock than broadleaved forest at 0.5 m soil depth (Table 2.3). Vertically, deep soils (50–70 cm soil depth) contain 24% of the upper stock in coniferous forests and 20% in the broadleaved forest. For 0–50 cm depth, C stock in coniferous and broadleaved sites was 19 kg m-2 and 11 kg m-2 (Table 2.3). Sheikh et al. (2020) reported a decrease in soil organic C stock with increasing elevation in Central Himalaya (Cedrus deodara forests at an elevation of 1750 m, 1900 m and 2050 m contain 10.4, 10.5, and 8.9 kg m-2 soil C stock, respectively). In a recent study, Ahirwal et al. (2021) estimated 16.8 kg m-2 of organic C storage in the top meter of forest soil in the Indian Himalayan region. The topsoil contains the highest amount of organic C and a higher turnover of C and is generally confined to the top 45 cm, as maximum soil microbial activity is restricted to this depth (Ravindranath and Ostwald 2007). Since most of the root activities are also concentrated within the top 30 cm, this sampling depth has been recommended by IPCC for soil C inventories (IPCC 2001). However, the typical sampling depth for estimating soil C stocks is 1 m (Bradley et al. 2005). Most of the previous studies on soil C were limited to the upper 15–30 cm of soil because of the difficulties associated with sampling. However, a recent study has suggested that considerable amounts of soil organic matter are stored in the subsoil layers (below the A horizon), which due to high residence time, maybe a potentially stable soil C stock (Rumpel and KögelKnabner 2011). Strahm et al. (2009) reported the translocation of dissolved organic carbon (DOC) through the soil profile contributing to the recalcitrant C pool between 20 and 100 cm depths in managed forest sites. Estimation of organic carbon reserve in forest soil is indispensable for quantifying size, distribution, and changes in national carbon stocks in relation to the UN climate change conventions. Although time-consuming, field investigations are the most reliable and frequently used approach for SOC inventories.
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2.3.8
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Controlling Soil C in Himalayas
The current study determined the amount of sequestered C under two coniferous and broadleaf forests with three distinct variables, viz., climatic, vegetative, and edaphic, with an overall strong influence of elevation. Higher precipitation and lower temperature in mixed coniferous forests favor higher soil C stock. However, higher precipitation in sloppy terrain can cause leaching loss of DOC. In contrast, warmer and dry climates can enhance the loss of SOC by enhancing microbial decay in broadleaved forests. Rainfall and temperature are generally considered as a strong secondary indicators for soil C storage and stabilization mechanisms (Juhos et al. 2021). For example, microbial community structure (i.e., fungus: bacteria) often changes over seasonal variation in precipitation and soil moisture (Wu et al. 2021; Ahmed et al. 2019), implying variation in the turnover of soil organic C stocks. Regarding vegetation cover, mixed coniferous forests with higher aboveground biomass and broadleaved forest with larger fine root biomass pools and identical litter flux at both locations seem to be no clear indication of a link with soil organic C storage. Higher fine root biomass in broadleaved sites than mixed coniferous cannot be correlated with soil organic matter stock without fine root production and turnover data (Godbold, DL, personal communication), which are lacking in our present study. In addition, the vertical distribution pattern of fine root biomass pattern was not consistent with distribution of soil organic C concentrations (Fig. 2.8), indicating other factors such as root litter quality/degradability might be the affecting factor in the processes. Control of edaphic factors on sequestrated C might be qualitative rather than qualitative. Soil properties such as clay content, pH, CEC, aggregates, etc. clearly influence the stability of SOC. Soils of broadleaved forests have slightly higher clay content than coniferous sites; however, the later demonstrated significantly higher CEC. Crystalline and amorphous clay minerals play a major role in the protection of organic C against decomposers. Organic C
Fig. 2.8 Vertical distribution of soil organic C and fine root biomass in mixed coniferous and broadleaved forests
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(especially high molecular weight sugar) can be protected from bacteria through sorption on charged-clay surfaces and within clay aggregates (Yang et al. 2021). The relationship between CEC and clay content is mainly regulated by soil pH, and Solly et al. (2020) reported that SOC is effectively adsorbed by reactive available soil surfaces at pH > 5.5. Together with soil pH and high CEC levels, mineral-induced protective mechanisms might be stronger in mixed coniferous sites than in broadleaved forests. In the current study, soil aggregate occluded C was not determined, which should also be considered as a key mechanism to prevent the de-stabilization of sequestrated C (Lehmann and Kleber 2015). It is now well recognized that long-term organic C preservation in soil is due to physical protection through soil aggregates and mineral interactions within large surface areas of mineral particles. Principal component analysis was performed with climatic, vegetative, and soil variables to explore correlation between soil C storage and other variables (Fig. 2.9). In the mixed coniferous forest, first and second principal components explained 74.04 and 18.02% variations which were mainly driven by soil and vegetative variables, respectively. In this higher-elevation forest, soil C storage was closely correlated with vegetative variables followed by CEC. On the other hand, in the broadleaved forest, PC1 and PC2 explained 54.7 and 42.7% of variations which were driven by vegetative + soil and soil variables, respectively. Soil C stock in the broadleaved forest was strongly correlated with fine root biomass, followed by soil variables. Overall our data revealed that soil organic C storage in the mixed coniferous forests was mostly regulated by vegetation (particularly aboveground biomass) with the influence of soil CEC on C stability. In contrast, sequestrated C in dry broadleaved forests was affected mostly by belowground biomass with considerable influence of soil properties.
Fig. 2.9 Principal component analysis: unconstrained ordination of 12 ecosystem variables (climatic 2, vegetative 4, and soil 6) in mixed coniferous and broadleaved forests
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Conclusions
The forest soils of Indian Himalaya are blessed by incredibly diverse vegetation, developed over a wide range of altitudinal gradients and horizontal climatic zones. Due to unique geographical locations between cold and dry Tibetan Plateau and warm and moist Indian subcontinent, the monsoon climatic systems have a paramount influence on the formation and distribution of forest vegetation. Atmospheric C is absorbed, sequestrated, and transported through these forests to lithosphere and hydrosphere as a part of global C cycle. Carbon sequestration in the soils of the Himalayan Region is a complex phenomenon under active influences of climateinduced vegetation, topography, hydrology, and soil edaphic factors. The quantity of sequestrated C in these soils is inherently linked with above and belowground vegetation. However, the long-term stability depends on biogeochemical properties of soil. The case study of soil C sequestration in two forests of mixed coniferous and broadleaved under cool moist and warm dry temperate zones revealed 19 and 11 kg m-2 C stocks at top half meter soil. However, as the pool sizes of soil organic C widely differ over spatial and temporal variations, emphasis was given to identifying and evaluating the factors that might regulate the C sequestration in the Himalayan soils. Our analyses showed a clear evidence that temperate mixed forest at 3300 m altitude sequestrated more soil C than temperate broadleaved forest at 2500 m, with aboveground and fine root biomass as major influencing factors, respectively. Soil edaphic factors such as CEC and clay content positively influenced C storage in soils of two forest sites. One of the limitations of this study is that we did not estimate particulate organic matter (POM) and mineral-associated organic matter in our study, and the issue is worthy of consideration. Acknowledgment Part of this study was conducted under the BC-CAP project (Climate Change Adaptation Potentials of Forests in Bhutan—Building Human Capacities and Knowledge Base), jointly carried out by Department of Forest and Park Services, Bhutan, and the University of Natural Resources and Life Sciences, Vienna, Austria, with funding from the government of Austria.
References Ahirwal J, Saha P, Nath A, Nath AJ, Deb S, Sahoo UK (2021) Forests litter dynamics and environmental patterns in the Indian Himalayan region. For Ecol Manag 499:119612 Ahmed IU, Mengistie HK, Godbold DL, Sandén H (2019) Soil moisture integrates the influence of land-use and season on soil microbial community composition in the Ethiopian highlands. Appl Soil Ecol 135:85–90 Augusto L, De Schrijver A, Vesterdal L, Smolander A, Prescott C, Ranger J (2015) Influences of evergreen gymnosperm and deciduous angiosperm tree species on the functioning of temperate and boreal forests. Biol Rev 90(2):444–466 Babu S, Singh R, Avasthe RK, Yadav GS, Mohapatra KP, Selvan T, Das A, Singh VK, Valente D, Petrosillo I (2020) Soil carbon dynamics in Indian Himalayan intensified organic rice-based cropping sequences. Ecol Indic 114:106292. https://doi.org/10.1016/j.ecolind.2020.106292 Baillie IC, Tshering K, Dorji T, Tamang HB, Dorji T, Norbu C, Hutcheon AA, Bäumler R (2004) Regolith and soils in Bhutan, eastern Himalayas. Eur J Soil Sci 55(1):9–27
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Balesdent J, Basile-Doelsch I, Chadoeuf J, Cornu S, Derrien D, Fekiacova Z, Hatté C (2018) Atmosphere–soil carbon transfer as a function of soil depth. Nature 559:599–602. https://doi. org/10.1038/s41586-018-0328-3 Batjes NH (1998) Mitigation of atmospheric CO2 concentrations by increased carbon sequestration in the soil. Biol Fertil Soils 27:230–235. https://doi.org/10.1007/s003740050425 Beedlow PA, Tingey DT, Phillips DL, Hogsett WE, Olszyk DM (2004) Rising atmospheric CO2 and carbon sequestration in forests. Ecol Environ 2(6):315–322 Berg B (2000) Litter decomposition and organic matter turnover in northern forest soils. For Ecol Manag 133:13–22 Bhardwaj DR, Sanneh AA, Rajput BS, Kumar S (2013) Status of soil organic carbon stocks under different land use systems in wet temperate North Western Himalaya. J Tree Sci 32(1-2):14–22 Bhat JA, Kumar M, Negi AK, Pala NA, Todaria NP (2012) Soil organic carbon stock and sink potential in high mountain temperate Himalayan forests of India. Int J Curr Res 4(12):206–209 Bloom AA, Exbrayat JF, Van Der Velde IR, Feng L, Williams M (2016) The decadal state of the terrestrial carbon cycle: Global retrievals of terrestrial carbon allocation, pools, and residence times. Proc Natl Acad Sci U S A 113:1285–1290 Bossio DA, Cook-Patton SC, Ellis PW, Fargione J, Sanderman J, Smith P et al (2020) The role of soil carbon in natural climate solutions. Nat Sustain 3:1–8. https://doi.org/10.1038/s41893-0200491-z Bradley RI, Milne R, Bell J, Lilly A, Jordan C, Higgins A (2005) A soil carbon and land use database for the United Kingdom. Soil Use Manag 21:363–369 Chen L, Liu L, Qin S et al (2019) Regulation of priming effect by soil organic matter stability over a broad geographic scale. Nat Commun 10:5112. https://doi.org/10.1038/s41467-019-13119-z Chen C, Hall SJ, Coward E et al (2020) Iron-mediated organic matter decomposition in humid soils can counteract protection. Nat Commun 11:2255. https://doi.org/10.1038/s41467-020-16071-5 Churchman GJ, Singh M, Schapel A, Sarkar B, Bolan N (2020) Clay minerals as the key to the sequestration of carbon in soils. Clay Clay Miner 68(2):135–143 Clark DA, Clark DB (1994) Climate-induced annual variation in canopy tree growth in a Costa Rican tropical rain forest. J Ecol 82:865–872 Dabi H, Bordoloi R, Das B, Paul A, Tripathi OP, Mishra BP (2021) Biomass, carbon stock and soil physicochemical properties in plantation of East Siang district, Arunachal Pradesh, India. Environ Chall 4:100191. https://doi.org/10.1016/j.envc.2021.100191 Dad JM (2019) Organic carbon stocks in mountain grassland soils of northwestern Kashmir Himalaya: spatial distribution and effects of altitude, plant diversity and land use. Carbon Manage 10(2):149–162. https://doi.org/10.1080/17583004.2019.1568137 Devi SB, Sherpa SS (2019) Soil carbon and nitrogen stocks along the altitudinal gradient of the Darjeeling Himalayas, India. Environ Monit Assess 191:361. https://doi.org/10.1007/s10661019-7470-8 Dimri AP et al (2021) Climate change, cryosphere and impacts in the Indian Himalayan Region. Curr Sci 120(5):774–790. https://doi.org/10.18520/cs/v120/i5/774-790 Dinakaran J, Chandra A, Chamoli KP, Deka J, Rao KS (2018) Soil organic carbon stabilization changes with an altitude gradient of land cover types in central Himalaya, India. Catena 170: 374–385. https://doi.org/10.1016/j.catena.2018.06.039 Dynarski KA, Bossio DA, Scow KM (2020) Dynamic stability of soil carbon: reassessing the “permanence” of soil carbon sequestration. Front Environ Sci 8:514701 Food and Agriculture Organization of the United Nations (2010) Global forest resources assessment 2010, FAO Forestry Paper 163 Forest Survey of India (2015) India state of forest report. Ministry of environment, forest and climate change. Dehraun, Uttarakhand, India. ISBN 97881929285-2-4 Gabriel CE, Kellman L, Prest D (2018) Examining mineral-associated soil organic matter pools through depth in harvested forest soil profiles. PLoS One 13(11):e0206847. https://doi.org/10. 3389/fenvs.2022.1023277
2
Soil C Sequestration in Himalayan Landscape: Impacts of Vegetation. . .
35
Gmach MR, Cherubin MR, Kaiser K, Cerri CEP (2020) Processes that influence dissolved organic matter in the soil: a review. Sci Agric 77:1–10. https://doi.org/10.1590/1678-992X-2018-0164 Godbold DL, Hoosbeek MR, Lukac M, Cotrufo MF, Janssens IA, Ceulemans R, Polle A, Velthorst EJ, Scarascia-Mugnozza G, De Angelis P, Miglietta F (2006) Mycorrhizal hyphal turnover as a dominant process for carbon input into soil organic matter. Plant Soil 281(1):15–24 Goyal D, Joshi V, Gupta N, Cabral-Pinto MM (2022) Soil quality assessment in a landslide chronosequence of Indian Himalayan Region. Landscape 11(10):1819 Gross CD, Harrison RB (2019) The case for digging deeper: soil organic carbon storage, dynamics, and controls in our changing world. Soil Syst 3(28):1–24 Harris NL, Gibbs DA, Baccini A, Birdsey RA, de Bruin S, Farina M, Fatoyinbo L et al (2021) Global maps of twenty-first century forest carbon fluxes. Nat Clim Chang 11(March):234–240. https://doi.org/10.1038/s41558-020-00976-6 Holtmeier FK (2009) Mountain timberlines. Springer, Cham. https://doi.org/10.1007/978-1-40209705-8 Houghton RA (2005) Aboveground forest biomass and the global carbon balance. Glob Chang Biol 11:945–958. https://doi.org/10.1111/j.1365-2486.2005.00955.x Iavorivska L, Boyer EW, DeWalle DR (2016) Atmospheric deposition of organic carbon via precipitation. Atmos Environ 146:153–163 IPCC (2001) Climate change 2001: working group I: the scientific basis. Cambridge University Press, New York IPCC (2019) Climate change and land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems. Cambridge University Press, Cambridge. https://www.ipcc.ch/site/assets/ uploads/2019/11/SRCCL-Full-Report-Compiled-191128.pdf Jangpangi BS (1978) Stratigraphy and structure of Bhutan Himalaya. Tect Geol Himalaya 15:221– 242 Joshi RK, Garkoti SC (2021) Influence of nepalese alder on soil physico-chemical properties and fine root dynamics in white oak forests in the central Himalaya, India. Catena 200:105140 Juhos K, Madarász B, Kotroczó Z, Béni Á, Makádi M, Fekete I (2021) Carbon sequestration of forest soils is reflected by changes in physicochemical soil indicators–A comprehensive discussion of a long-term experiment on a detritus manipulation. Geoderma 385:114918 Kallenbach CM, Frey SD, Grandy AS (2016) Direct evidence for microbial-derived soil organic matter formation and its ecophysiological controls. Nat Commun 7(1):1 Keller AB, Brzostek ER, Craig ME, Fisher JB, Phillips RP (2021) Root-derived inputs are major contributors to soil carbon in temperate forests, but vary by mycorrhizal type. Ecol Lett 24:626– 635 Kumar SS, Wani OA, Mir SA, Babu S, Sharma V, Chesti MUH, Baba ZA, Sofi PA, Wani FJ, Dar SR, Singh R, Yadav D (2022) Soil carbon dynamics in the temperate Himalayas: impact of land use management. Front Environ Sci 10:1009660. https://doi.org/10.3389/fenvs.2022.1009660 Lal R, Negassa W, Lorenz K (2015) Carbon sequestration in soil. Curr Opin Environ Sustain 15: 79–86 Landsberg JJ, Gower ST (1997) Applications of physiological ecology to forest management. In: Mooney HA (ed) Physiological Ecology. Academic Press, San Diego, 354p Lehmann J, Kleber M (2015) The contentious nature of soil organic matter. Nature 528(7580): 60–68 Liao C, Li D, Huang L, Yue P, Liu F, Tian Q (2020) Higher carbon sequestration potential and stability for deep soil compared to surface soil regardless of nitrogen addition in a subtropical forest. PeerJ 8:e9128. https://doi.org/10.7717/peerj.9128 Liu L, Yang F, Wang Y, Shen X, Janssens IA, Guenet B, Xiao C (2019) Fine-root turnover, litterfall, and soil microbial community of three mixed coniferous–deciduous forests dominated by Korean pine (Pinus koraiensis) along a latitudinal gradient. Front Plant Sci 10:1298 Malizia A, Blundo C, Carilla J, Osinaga Acosta O, Cuesta F, Duque A, Aguirre N, Aguirre Z, Ataroff M, Baez S, Calderón-Loor M (2020) Elevation and latitude drives structure and tree
36
I. U. Ahmed et al.
species composition in Andean forests: results from a large-scale plot network. PLoS One 15(4): e0231553 Marian F, Sandmann D, Krashevska V, Maraun M, Scheu S (2017) Leaf and root litter decomposition is discontinued at high altitude tropical montane rainforests contributing to carbon sequestration. Ecol Evol 7(16):6432–6443. https://doi.org/10.1002/ece3.3189. PMID: 28861246; PMCID: PMC5574766. McCormack ML, Dickie IA, Eissenstat DM, Fahey TJ, Fernandez CW, Guo D, Helmisaari HS, Hobbie EA, Iversen CM, Jackson RB, Leppälammi-Kujansuu J (2015) Redefining fine roots improves understanding of below-ground contributions to terrestrial biosphere processes. New Phytol 207(3):505–518 Mendes KR, Campos S, da Silva LL, Mutti PR, Ferreira RR, Medeiros SS, Santos e Silva CM (2020) Seasonal variation in net ecosystem CO2 exchange of a Brazilian seasonally dry tropical forest. Sci Rep 10(1):1–16 Mishra G, Sarkar A (2020) Studying the relationship between total organic carbon and soil carbon pools under different land management systems of Garo hills, Meghalaya. J Environ Manag 257:110002. https://doi.org/10.1016/j.jenvman.2019.110002 Mishra G, Giri K, Jangir A, Francaviglia R (2020) Projected trends of soil organic carbon stocks in Meghalaya state of Northeast Himalayas, India. Implications for a policy perspective. Sci Total Environ 698:134266. https://doi.org/10.1016/j.scitotenv.2019.134266 NCSL (2022) State forest carbon incentives and policies. https://www.ncsl.org/research/ environment-and-natural-resources/state-forest-carbon-incentives-and-policies.aspx Neumann M, Lawes MJ (2021) Quantifying carbon in tree bark: the importance of bark morphology and tree size. Methods Ecol Evol 12(4):646–654 Ni X, Yang W, Tan B, Li H, He J, Xu L, Wu F (2016) Forest gaps slow the sequestration of soil organic matter: a humification experiment with six foliar litters in an alpine forest. Sci Rep 6(1): 1–3 Ohno T, Heckman KA, Plante AF, Fernande IJ, Parr TB (2017) 14C mean residence time and its relationship with thermal stability and molecular composition of soil organic matter: a case study of deciduous and coniferous forest types. Geoderma 308:1. https://doi.org/10.1016/j. geoderma.2017.08.023 Ohsawa M (1987) Vegetation zones in the Bhutan Himalaya. In: Life zone ecology of the Bhutan, Himalaya, pp 1–71 Okazaki M (1987) Soils of the Bhutan Himalaya. In: Ohsawa M (ed) Life zone ecology of Bhutan Himalaya II. Chiba University, Chiba, p 149 Olesinski J, Lavigne MB, Krasowski MJ (2011) Effects of soil moisture manipulations on fine root dynamics in a mature balsam fir (Abiesbalsamea L. Mill.) forest. Tree Physiol 31(3):339–348. https://doi.org/10.1093/treephys/tpr006 Pierson D, Peter-Contesse H, Bowden RD, Nadelhoffer K, Kayhani K, Evans L, Lajtha K (2021) Competing processes drive the resistance of soil carbon to alterations in organic inputs. Front Environ Sci 9:527803 Portillo-Estrada M, Pihlatie M, Korhonen JF, Levula J, Frumau AK, Ibrom A, Lembrechts JJ, Morillas L, Horváth L, Jones SK, Niinemets Ü (2016) Climatic controls on leaf litter decomposition across European forests and grasslands revealed by reciprocal litter transplantation experiments. Biogeosciences 13(5):1621–1633 Ramachandran Nair PK, Nair VD, Kumar BM, Showalter JM (2010) Carbon sequestration in agroforestry systems. In: Sparks DL (ed) Advances in agronomy, vol 108. Academic, New York, pp 237–307. https://doi.org/10.1016/S0065-2113(10)08005-3 Ramachandran RM, Roy PS (2018) Vegetation response to climate change in Himalayan hill ranges: a remote sensing perspective. Plant Div Himalaya Hotspot Reg 1:369–392 Ravindranath NH, Ostwald M (2007) Carbon inventory methods: handbook for greenhouse gas inventory, carbon mitigation and roundwood production projects. Springer, Cham Rawat VS (2012) Fine root biomass and nutrient availability in a community-managed forest. Indian J Plant Sci 1:1–8
2
Soil C Sequestration in Himalayan Landscape: Impacts of Vegetation. . .
37
Roston E (2008) The carbon age: how life’s core element has become civilization’s greatest threat. Walker & Company, New York Rumpel C, Kögel-Knabner I (2011) Deep soil organic matter—a key but poorly understood component of terrestrial C cycle. Plant Soil 338:143–158. https://doi.org/10.1007/s11104010-0391-5 Saikia P, Kumar A, Lal P, Khan ML (2020) Ecosystem-based adaptation to climate change and disaster risk reduction in Eastern Himalayan forests of Arunachal Pradesh, Northeast India Sato A, Nojiri Y (2019) Assessing the contribution of harvested wood products under greenhouse gas estimation: accounting under the Paris Agreement and the potential for double-counting among the choice of approaches. Carbon Balance Manag 14(1):1–9 Schewe J, Levermann A (2012) A statistically predictive model for future monsoon failure in India. Environ Res Lett 7:044023 Schmidt MW, Torn MS, Abiven S, Dittmar T, Guggenberger G, Janssens IA, Trumbore SE (2011) Persistence of soil organic matter as an ecosystem property. Nature 478(7367):49–56 Seuradge BJ, Oelbermann M, Neufeld JD (2017) Depth-dependent influence of different land-use systems on bacterial biogeography. FEMS Microbiol Ecol 9382:239. https://doi.org/10.1093/ femsec/fiw239 Shahzad T, Perveen N, Mougin C, Maire V, Rashid MI, Barot S, Alvarez G, Fontaine S (2018) Root penetration in deep soil layers stimulates mineralization of millennia-old organic carbon. Soil Biol Biochem 124:150–160. https://doi.org/10.1016/j.soilobio.2018.06.010 Sheikh MA, Kumar M, Todaria NP, Pandey R (2020) Biomass and soil carbon along altitudinal gradients in temperate Cedrusdeodara forests in Central Himalaya, India: implications for climate change mitigation. Ecol Indic 111:106025. https://doi.org/10.1016/j.ecolind.2019. 106025 Siegenthaler U, Stocker TF, Monnin E, Luethi D, Schwander J, Stauffer B, Raynaud D (2005) Stable carbon cycle-climate relationship during the late Pleistocene. Science 310:1313–1317 Singh JS, Singh SP (1987) Forest vegetation of the Himalaya. Bot Rev 53:80–192. https://doi.org/ 10.1007/BF02858183 Sokol NW, Sanderman J, Bradford MA (2019) Pathways of mineral-associated soil organic matter formation: Integrating the role of plant carbon source, chemistry, and point of entry. Glob Chang Biol 25:12–24. https://doi.org/10.1111/gcb.14482 Solly EF, Weber V, Zimmermann S, Walthert L, Hagedorn F, Schmidt MW (2020) A critical evaluation of the relationship between the effective cation exchange capacity and soil organic carbon content in Swiss forest soils. Front For Glob Change 3:98 Stockmann U, Adams MA, Crawford JW, Field DJ, Henakaarchchi N, Jenkins M, Zimmermann M (2013) The knowns, known unknowns and unknowns of sequestration of soil organic carbon. Agric Ecosyst Environ 164:80–99 Strahm BD, Harrison RB, Terry TA, Harrington TB, Adams AB, Footen PW (2009) Changes in dissolved organic matter with depth suggest the potential for postharvest organic matter retention to increase subsurface soil carbon pools. For Ecol Manag 258(10):2347–2352 Tashi S, Keitel C, Singh B, Adams M (2017) Allometric equations for biomass and carbon stocks of forests along an altitudinal gradient in the eastern Himalayas. Forestry 90(3):445–454 Tiwari PC (2000) Land use changes in Himalaya and their impact on the plain’s ecosystem. Land Use Policy 17(2):101–111. https://doi.org/10.1016/S0264-8377(00)00002-8 Tiwari SD, Joshi R (2015) Litter-fall production in cool-temperate forests of the Nanda Devi Biosphere Reserve, Uttarakhand Himalaya, India. Braz J Biol Sci 2(3):147–154 van der Voort TS, Mannu U, Hagedorn F, McIntyre C, Walthert L, Schleppi P, Haghipour N, Eglinton TI (2019) Dynamics of deep soil carbon – insights from 14C time series across a climatic gradient. Biogeosciences 16:3233–3246. https://doi.org/10.5194/bg-16-3233-2019 Verma AK, Garkoti SC, Singh S, Kumar S, Kumar M (2021) Fine root production and nutrient dynamics in relation to stand characteristics of chir pine mixed banj oak forests in central Himalaya. Flora 279:151808
38
I. U. Ahmed et al.
Vesterdal L, Clarke N, Sigurdsson BD, Gundersen P (2013) Do tree species influence soil carbon stocks in temperate and boreal forests? For Ecol Manag 309:4–18 Wangda P, Ohsawa M (2006) Structure and regeneration dynamics of dominant tree species along altitudinal gradient in a dry valley slopes of the Bhutan Himalaya. For Ecol Manag 230(1-3): 136–150 Wangdi N, Om K, Thinley C, Drukpa D, Dorji T, Darabant A, Chhetri PB, Ahmed IU, Staudhammer CL, Jandl R, Schindlbacher A, Hietz P, Katzensteiner K, Godbold D, Gratzer G (2017) Climate change in remote mountain regions: a throughfall-exclusion experiment to simulate monsoon failure in the Himalayas. Mountain Res Dev 37(3):294–309 Webster PJ, Magana VO, Palmer TN, Shukla J, Tomas RA, Yanai M, Yasunari T (1998) Monsoons: processes, predictability, and theprospects for prediction. J Geophys Res Ocean 103:14451–14510. https://doi.org/10.1029/97JC02719 Wu J, Jia W, Zhang D, Liu G, Cheng X (2021) Case study on a coniferous plantation site about inter-annual shifts in microbial communities under short-term detritus input manipulations. Ecol Indic 130:108053 Xu J, Grumbine RE, Shrestha A, Eriksson M, Yang X, Wang YUN, Wilkes A (2009) The melting Himalayas: cascading effects of climate change on water, biodiversity, and livelihoods. Conserv Biol 23(3):520–530 Yadav GS, Kandpal BK, Das A, Babu S, Mohapatra KP, Devi AG, Devi HL, Chandra P, Singh R, Barman K (2021) Impact of 28 year old agroforestry systems on soil carbon dynamics in Eastern Himalayas. J Environ Manag 283:111978. https://doi.org/10.1016/j.jenvman.2021.111978 Yang JQ, Zhang X, Bourg IC, Stone HA (2021) 4D imaging reveals mechanisms of clay-carbon protection and release. Nat Commun 12(1):1–8 Zhou L, Zhou X, He Y, Fu Y, Du Z, Lu M, Sun X, Li C, Lu C, Liu R, Zhou G (2022) Global systematic review with meta-analysis shows that warming effects on terrestrial plant biomass allocation are influenced by precipitation and mycorrhizal association. Nat Commun 13(1):1
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Soil Carbon Stock Along an Altitudinal Gradient in the Indian Himalayas Shahina Noushad Najima, Manendra Singh, Sajitha Siril, Gopal Shukla, Pankaj Panwar, and Sumit Chakravarty
Abstract
Soil organic carbon stock, the largest terrestrial global carbon pool is a dynamic system, which varies based on physiographic and altitudinal characteristics. The carbon sequestration potential of soil is considered a major climate change mitigation pathway by the IPCC. Indian forest soils store 5.4–6.81 Pg carbon, and the contribution of Himalayan forests to world forest biomass carbon and soil carbon stock is 14 % (119 ± 6 Pg). Environmental factors alter the capacity for soil carbon sequestration in moist temperate forests of the western Himalayas and tropical mountain forests of the eastern Himalayas of India. The 4 per thousand is a voluntary commitment that aims to increase or maintain the carbon stock in the soil of agricultural lands as well as to conserve other carbon-rich soils. In India, increasing the tree cover on degraded lands and forest soil carbon conservation are considered potential management practices for the implementation of the 4 per mille initiative. The conversion of forest land to agriculture severely contributes to the depletion of SOC, which eventually degrades soil health and ecosystem sustainability. In addition to climate change mitigation, SOC ensures soil-derived ecosystems requiring carbon-friendly land-use and land management practices. SOC pool, due to its immense significance in the present era of climate change and land degradation, needs more advanced studies for achieving SDGs and ensuring sustainability.
S. N. Najima · M. Singh · S. Siril · G. Shukla (✉) · S. Chakravarty Department of Forestry, Uttar Banga Krishi Viswavidyalaya, Cooch Behar, West Bengal, India P. Panwar ICAR-Indian Institute of Soil and Water Conservation, Research Centre, Chandigarh, India # The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Mishra et al. (eds.), Soil Carbon Dynamics in Indian Himalayan Region, https://doi.org/10.1007/978-981-99-3303-7_3
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Keywords
Soil carbon · 4 per mille · Himalayas
3.1
Introduction
Soils are intrinsically dynamic and represent the largest terrestrial carbon pool, containing three times more carbon than vegetation and two times more carbon than that present in the atmosphere. Carbon (C) sequestration and soil storage potential act as sinks for atmospheric carbon and are critical in mitigating the consequences of climate change (Shaheen et al. 2017). Greenhouse gases (GHGs) act as a source of C in soil organic carbon stock (SOC), and their crucial role is increasing the carbon content of soil, i.e., important for maintaining and developing food production systems and reducing carbon dioxide (CO2) from the atmosphere (Lal 2004). At the national level, assessing SOC stock is essential for climate change mitigation through manipulation and management of floral diversity (Rodríguez Martín et al. 2016). The chemical and physical interaction of soil carbon with minerals plays a significant role in carbon storage (Georgiou et al. 2022). Total soil carbon stock (SCS) comprises soil organic carbon (SOC) and soil inorganic carbon (SIC). Lorenz and Lal (2018) reported that almost half of the total SOC in the terrestrial ecosystem is stored in forest soils. Globally, total SOC stock ranges between 1325–1500 Pg C and 2300 Pg C in top 1- and 3-meter (m) of soil, respectively. Moreover, up to 1 meter, the soil profile contains about 3000 Pg C as SCS. Tropical and temperate grasslands and cultivated land store 716 Pg SOC at 1-meter depth. Most estimates report that global SOC is approximately 1500 Pg C and organic C stocks in soil exceed those in plant biomass (860 Pg C)in most IPCC climatic regions. Globally, more than 40% of the total organic C in terrestrial ecosystems is stored in forest soils (IPCC 2007; Wei et al. 2014). Total soil C stocks (including litter) were estimated at 202, 69, and 155 Pg for boreal, temperate, and tropical forests, respectively. These soil C stocks represent ~70% of the ecosystem C stock in the boreal forest, ~60% in temperate forests, and ~30% in tropical forests, respectively (Pan et al. 2011). The soil C stock represents the balance between inputs of organic matter to soils and the loss of carbon through decomposition, leaching, and erosion of organic matter. The SIC stock, primarily occurring in soils of arid regions, is estimated at 700–1700 Pg C in the top 1 m of soil (Ming 2006; Lorenz and Lal 2018). The two principal components of SIC include the lithogenic inorganic carbon (LIC) or primary carbonates, containing C-derived from soil parent material, and the pedogenic inorganic carbon (PIC) or secondary soil carbonates formed by lithogenic or pedogenic processes (Eswaran et al. 2000; Schlesinger 2006). The SIC stocks are probably higher in temperate regions and deeper layers of soils. The Himalayan region, associated with complex physiographic features and extreme altitudinal gradients (from tropical lowland to high mountains), has diverse vegetation patterns and thus variation in soil carbon storage (CEPF 2007; Chettri
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et al. 2010; Shukla et al. 2013; Sarkar et al. 2020; Vineeta et al. 2022). Globally, forest soils are the storehouse of 383 ± 30 Pg or 44% carbon in soil up to a depth of 1 m. Indian forest soils store 5.4–6.81 Pg carbon (Chhabra et al. 2003; Ravindranath and Ostwald 2008), and Himalayan forests’ contribution to world forest carbon stock is 14 % (119 ± 6 Pg) (Ravindernath et al. 1997). The soils of the Indian sub-Himalayan region are often characterized by a shallow soil depth (20 cm), a high percentage of gravels (70–75%) and sand (20–25%), and a low proportion of silt (3–5%) and clay (2–4%), as well as low SOC and water-holding efficiency (Rathore et al. 2018). Moreover, environmental factors such as soil moisture and microbial activity alter the capacity for soil carbon sequestration in moist temperate forests of the western Himalayas and tropical mountain forests of the eastern Himalayas. The impacts of climate change and anthropogenic pressure in the Himalayan region are major concerns in terms of ecosystem degradation, which directly influence biomass and soil carbon (Shukla and Chakravarty 2018; Shukla et al. 2017; Pradhan et al. 2022). Significant changes in climatic conditions, particularly precipitation and temperature, are potentially expected to lead to large-scale displacement of SOM due to uneven net primary productivity (NPP), which balances the carbon losses of soils (Townsend et al. 1995; Falloon et al. 2007). There is a possibility of soil carbon losses arising after land-use change; thus degraded land use must be recognized to convert into carbon storage compensatory land use (Keller et al. 2022). Soil resources are gradually at risk due to (a) dynamics of natural processes including climate, (b) land-use change, and (c) anthropogenic pressure such as deforestation, man-made fire, over harvesting, etc. that can degrade soil and result in the rapid loss of carbon. Soil management strategies can help to improve and conserve existing soil carbon reserves, and future sequestration is critical to maintaining the carbon balance. During the COP21 in Paris, the “4 per mille or 4 per 1000” Soils for Food Security and Climate initiative was launched on 1 December, 2015. This initiative received over 150 signatures from different stakeholders including national governments, local and regional governments and authorities, nongovernmental organizations (NGOs), etc. All the signatories agree on a voluntary action plan to implement farming practices that maintain or improve soil carbon stocks in agricultural soils and preserve carbon-rich soils (Chambers et al. 2016; Lal 2016). It enables stakeholders to participate in a transition to regenerative, efficient, and highly resilient agriculture that is based on sustainable land and soil stewardship. The goal is to increase global soil organic matter stocks by “4 per 1000” (or 0.4%) per year to compensate for anthropogenic worldwide emissions of greenhouse gases (Minasny et al. 2017) through the implementation of farming practices adapt to specific conditions, such as agroecology, agroforestry, conservation agriculture, landscape management, etc. Considering the potential importance and the role of different tree-based landscapes and forest ecosystems in carbon storage, this chapter provides a holistic view of the soil carbon storage potential of the Eastern and Western Himalayas. Furthermore, the role of climate change mitigation strategies is discussed in view of their implication to reduce the impact of CO2 through carbon storage in soil.
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Soil Carbon Stock in the Western Himalayas
The western Himalayan region has enormous ecological value, and the diverse vegetation patterns include forests, traditional agroforestry, orchards, grassland, and agriculture, which are recognized as vital for the regional carbon balance (Rawat et al. 2021). Soil carbon stocks vary with soil depths in different forest ecosystems, governed by tree and shrub density and hence by litter production. The plant diversity and their accompanying understorey vegetation influence SOC accumulation in moist temperate forest ecosystems (Dar and Sundarapandian 2013). Lower carbon density at higher altitudes indicates the immature character of natural Himalayan forests due to slow vegetation growth and low litter production led by harsh climatic conditions (Shaheen et al. 2017). The decomposition of organic matter depends on litter components, climatic conditions and microbes which determine the retention time of litter in soil (Parton and Rasmussen 1994; Kumar et al. 2022). However, uncontrolled grazing and overgrazing in the Himalayan grassland ecosystems are major causes of soil degradation which directly reduces the SOC (Khan et al. 2019). SOC stocks in different tree-based land uses across the climatic conditions exhibited maximum SOC (0.7–41.6%) in the deeper soil depth. However, soil depths have quadratic relations with soil moisture and soil temperature (Singh et al. 2018). Previously conducted studies envisaged that SOC stock varied with the depth, altitudinal gradients, and vegetational patterns in different land uses/covers (Table 3.1). Altitudinal gradients influence soil characteristics via soil erosion and discharge and affects the nutrient cycling, decrease soil pH, salt construct in the root zone, decrease in soil fauna and species diversity, ultimately decrease the SOC pool (Lal 2004). Similarly, the SOC stocks are positively influenced by soil particles size, land-use factors, and elevation gradient and negatively by slope and soil pH (Singh et al. 2018). Agriculture and tree-based land uses have immense potential for SOC storage (Sleutel et al. 2003; Tamang et al. 2021a, b; Buraka et al. 2022). SOC mainly reliant on regional climatic conditions, i.e., temperature and precipitation control decomposition process, is vital for organic matter (OM) addition to the soil; therefore, regional climate controls the terrestrial SOC pool (Bird et al. 2001). By altering the rates of input or release of C from soils, forest management activities can influence soil carbon stocks in forests. Afforestation of croplands generally increases soil carbon stocks, whereas on former grasslands and peatlands, soil C stocks are unchanged or irregular. The conversion of primary forests to secondary forests generally reduces soil carbon stocks (Mayer et al. 2020). Climate, geology, and land management practices are the principal factors controlling the magnitude of the SOC, as they are determinants of the soil type and are representative of vegetation type with diverse topography. Temperate climate has maximum SOC stock, followed by non-grazed alpine grassland, subtropical and tropical climate (Table 3.1 and Fig. 3.1).
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Table 3.1 Variation in SOC in previously conduct studies in the Himalayas Vegetation type/ land uses Abies pindrow and Pinus wallichiana forests of western Kashmir Himalayas Alpine grassland
High-altitude dry temperate forests land use systems
Agroforestry systems along an altitudinal gradient
SOC stock in Himalayan land uses and climate
Soil carbon stock SOC ranged from 50.37 to 55.38 Mg C ha-1
Findings Total SOC up to 30 cm was higher in P. Wallichiana forest
Source Dar and Sundarapandian (2013)
The average SOC of 120.0 Mg C ha-1 was highest at 3650 m asl and lowest (47.0 Mg C ha-1) at 3500 m asl Maximum soil carbon density (151.77 and 185.99 Mg C ha-1) was estimated in agrihorticulture system at 1900–2170 and 2170– 2240 m asl, respectively. Maximum SOC (1.41%) was estimated in silvipasture system
Significant variation in SOC of grazed and non-grazed areas governed by size of herd
Khan et al. (2019)
Soil carbon density at soil depths of 0–20, 20– 40, and 40–100 cm did not substantially differed in land use systems between altitude gradients, except the barren land at soil depths of 0–40 soil depths Irrespective of the land use system, SOC increased with the increase in altitude and decreased with the increase in soil depth SOC density significantly affected by altitudinal gradients and agroforestry system
Chisanga et al. (2018)
The trend of SOC stock across the altitude was: temperate > lower alpine > upper alpine > subtropical
Singh et al. (2011)
Mean SOC density up to 30 cm soil depth was maximum in grassland (53.45 Mg C ha-1) followed by agri-hortisilviculture (52.57 Mg C ha-1), agri-horticulture (51.88 Mg C ha-1), agrisilvi-horticulture (51.18 Mg C ha-1), and agri-silviculture (50.01 Mg C ha-1). Higher SOC density (53.91 Mg Cha-1) at 1701–2100 m asl in the Quercus leucotrichophora forest The SOC stock and soil carbon concentration were maximum in temperate climate (101.8 Mg ha-1 in 0–30 cm, 227.97 Mg ha-1 in 0–100 cm), and lowest in
Singh et al. (2018)
(continued)
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Table 3.1 (continued) Vegetation type/ land uses
Subalpine temperate coniferous forests
A synthesis of 67 studies of Indian Himalayan region (IHR)
Soil carbon stock subtropical climate (37 Mg ha-1 in 0–30 cm, 107.04 Mg ha-1 in 0– 100 cm) In comparison to the soil depth, topsoil exhibited the maximum percentage of SOM and SOC
The trend of SOC in the IHR was temperate climate (153.6 ± 82.76 Mg C ha-1) > subtropical (111.8 ± 88.79 Mg C ha-1) > tropical (99.28 ± 66.26 Mg C ha-1)
Findings
Source
Annual fluctuation was found maximum at a depth of 30 cm, the autumn season having the highest carbon, followed by spring and summer SOC stock was maximum in the temperate climate by subtropical and tropical climate between the altitude of 1024–8583 m asl
Sheikh et al. (2021)
Ahirwal et al. (2021)
Fig. 3.1 SOC (Mg C t ha-1) stock estimated in previous studies. AP Abies pindrow, PW Pinus wallichiana
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Soil Carbon Stock in the Eastern Himalayas
More than one-third of the carbon pool in India is from Himalayan hotspots, in which eastern Himalayas contribution is not neglectable. Eastern Himalayas of the Bhutan region were studied well in terms of soil carbon with an altitudinal gradient, but studies are scanty in Indian Himalayas. Devi and Sherpa (2019) studied Darjeeling Himalayas to assess the forest type and change in SOC and soil carbon stock along the altitudinal gradient (elevation ranges from >100 m to 3636 m). Positive relationships were identified in major forest types such as tropical moist deciduous forest, east Himalayan temperate forest and east Himalayan subalpine forest among gradients in elevation and SOC. According to Banerjee (2014), SOC is directly proportional to elevation with higher values in subalpine forests than in temperate forests. Forests of Darjeeling Himalayas store around 158.3–525.7 Mg ha-1 of SOC stock in the top 1-meter of soil profile. Temperate evergreen and temperate deciduous forests store 31% and 41% of the soil organic carbon pools, which accounts for a total of 262 Pg carbon in temperate forest soils (Jobbágy and Jackson 2000). A study in the Ziro Valley, Arunachal Pradesh (2300–3000 m altitude), found a high correlation between total soil carbon with soil organic carbon, pH, silt, and clay in temperate forest ecosystems (Yam et al. 2021). In selected five forest stands of the eastern sub-Himalayan region, Tectona grandis, Shorea robusta, Michelia champaca, Lagerstroemia parviflora, and mixed forest, Rai et al. (2021) documented a storage of 75.9 and 107.7 Mg ha-1 SOC up to 60 cm soil depth, with highest SOC in mixed forest type. SOC in the sub-Himalayan forests of West Bengal was also assessed by Shukla and Chakravarty (2018) who reported 40.27 and 35.56 Mg ha-1 at 0–15 cm and 15–30 cm soil depths, respectively. Soil organic carbon under agroforestry systems is not well studied as aboveground biomass, even though they play a crucial role in maintaining the fertility of lands and productivity of intercrops. Agroforestry systems are proven as a restoration strategy for billions of hectares of degraded lands with additional benefits for soil and water conservation (Nair et al. 2010; Thangavel et al. 2018; Panwar et al. 2022). A study in a 28-year-old agroforestry block in Tripura (46 m altitude) with multipurpose trees (Tectona grandis, Dalbergia sissoo, Eucalyptus globulus, and Azadirachta indica) and pineapple (Ananas comosus) showed a SOC storage in the range 65.3–71.6 Mg ha-1 in top 100 cm soil profile (Yadav et al. 2021a). The tree combinations with pineapple significantly increased the soil quality by improving SOC compared with the monocrop fields. Furthermore, such agroforestry systems outstretch livelihood options and socio-economic growth strategies for people living in hilly and sloping lands. Lepcha and Devi (2020) assessed the change in microbial biomass carbon (MBC) and soil parameters with the season, land-use type, and soil depth in eastern Himalayan soils. Forests had higher MBC followed by cardamom agroforestry and
S. N. Najima et al.
Land Use Type
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Paddy Cropland Cardamom Agroforestry Forest 0
317.47 392.86 455.03 100 300 400 500 200 Mean Annual Microbial Biomass Carbon (mg/g)
Fig. 3.2 Mean annual microbial biomass change with land use types in eastern Himalayas (modified from Lepcha and Devi 2020)
paddy field (Fig. 3.2), which is attributed to the prominent litter layer, which further enhances the microbial activity and soil fertility. Similarly, another study in the North Eastern Himalayan region of India (altitude 950–1350 m) demonstrated the maximum of SOC in 0–45 cm depth of undisturbed forest soils (145.8 Mg ha-1) followed by Alder+ large cardamom, Alder+ turmeric, Ginger+ maize, and Ginger (Babu et al. 2020), indicating a SOC loss in monocrop systems in Himalayan soils. Experiments were also conducted to assess the effect of tillage operation on crops and SOC, since poor SOC and water-holding capacity limit the sustainable practice of agriculture in the Himalayas (Shukla et al. 2012). Yadav et al. (2021b) observed high SOC stock at 0–30 cm depth under no-tillage-flat bed planting (28.5 Mg ha-1) and maximum SOC sequestration rate under no-tillageraised bed planting practice (0.85 Mg ha-1 year-1) in maize-based cropping in the eastern Himalayas. Home gardens are one of the important agroforestry systems in the eastern Himalayan region, which reflect the culture, choice of species, and economic status of people (Roy et al. 2022a, b). Numerous studies reported the carbon sequestration potential of home gardens; Subba et al. (2018) analyzed the SOC in home gardens of Terai region in West Bengal and documented the carbon value at two different soil depths 0–20 cm and 20–40 cm as 25.96 Mg ha-1 and 18.96 Mg ha-1, respectively. The characteristic stratification and species richness with diversity in functions make each home garden unique. Hence, more diverse studies on home gardens with SOC quantification should be encouraged to simulate models and research in future. Litter contributes principally to the soil organic matter and the corresponding SOC. The quantitative litter analysis by Shukla et al. (2017) in forest plantations of eastern Himalayan foothills revealed the potential of Tectona grandis plantations to store 2.52 Mg ha-1 litter carbon. Teak stands in the foothill forests in Indian Eastern Himalayas stored 71.29 Mg ha-1 total soil carbon in an earlier study by Shukla et al. (2014). In the urban treescapes of eastern sub-Himalayan regions, total soil carbon is reported as 50.82 Mg ha-1, which confirms the role of trees in achieving sustainable carbon storage and mitigating climate change (Pradhan et al. 2022). Gmelina arborea plantations from the agricultural landscape in the foothills of the Eastern Himalayas sequestered 48.18–55.73 Mg ha-1 organic carbon in the soil (Tamang
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et al. 2021a, b) that highlighted the farm forestry (the practice of incorporating trees in farm lands) concept as a suitable way to reduce CO2 emissions. In additions, farm forestry will increase the livelihood option for people and maintain ecological stability.
3.4
4 per 1000 Initiative: Soils for Food Security and Climate
COP21 is unique among the Conference of Parties of the United Nations due to its emphasis on soil carbon. The concept of the 4 per mille initiative originated from COP21 which mainly focuses on enhancing the global soil organic content of carbon, at the rate of 0.4% (4 per mille) per year to a depth of 40 cm. The main strategy of this proposal is to enhance the sequestration of soil organic carbon through the adoption of various management practices recommended, viz., conservation agriculture, agroforestry, restoration, and rehabilitation of degraded lands. Soil carbon sequestration is an important climate change mitigation pathway since a small increment in the soil carbon stock could produce a considerable effect on greenhouse gas mitigation, as the carbon storage capacity of soil is about two to three times that of the atmosphere and around three times than the vegetation (Zomer et al. 2003). Carbon storage in soil is an important ecosystem service that could make a pathway for achieving nutritional and food security, restoring the quality of soil and overall improvement of the environment. The highly ambitious target of 4 per mille also helps in advancing the Sustainable Development Goals (SDG), particularly SDG 2 (Zero Hunger) and 15 (Life on Land) (Lal 2016). The 4 per mille is a voluntary commitment that aims to increase or maintain the carbon stock in the soil of agricultural lands as well as to conserve other carbon-rich soils (Chambers et al. 2016). In India, plantations on degraded lands, returning of residues to the cropping area, and promotion of pulses exist as the potential management practices for the implementation of 4 per mille initiative (Minasny et al. 2017). The successful implementation of this initiative, however, has multifaceted challenges. Constant communication and collaboration between the land managers or farmers, policymakers, marketers, and scientists are required for the implementation and progress of this global aim successfully. Technically, the carbon storage potential of soil is finite. The adoption of recommended management practices by the small landholders and resource-poor farmers of developing nations is crucial due to poor institutional support and inadequate access to the requisite inputs. Moreover, the lacuna in the scientific data due to inadequate research on soil carbon sinks and implications of recommended management practices on croplands and managed ecosystems offer a highly challenging pathway for the achievement of the 4 per mille target (Lal 2016). The existence of inherently low carbon soils, the prevalence of moderate to high rainfall, and high temperature are the major challenges faced by India for the successful implementation of the 4 per mille goal (Minasny et al. 2017).
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Management Practices for Conserving the SOC Pool
Soil, the largest pool of terrestrial carbon, can act as both a sink and a source of carbon. The land-use management practices will determine whether the soil acts as a source or a sink (Lal 2004). In general, land-use practices with minimum disturbance to the soil increase carbon accumulation (Table 3.2). On the contrary, the conversion of pristine forests to cultivated agroecosystems will release large quantities of carbon back into the atmosphere (Kasel and Bennett 2007). However, the establishment of vegetation on barren or fallow agricultural areas would result in a potential increase in the carbon storage capacity of the soil. Practices like minimum or zero tillage, agroforestry, organic farming, cover cropping, and crop rotations contribute to the buildup of organic carbon in the soil (Ramesh et al. 2019). Forest soils play a prominent role in the global cycle of carbon and are recognized as the main sinks of carbon on earth. Nevertheless, forest management practices such as thinning, liming, and unscientific harvesting revealed a reduction in total soil carbon content (Nave et al. 2010). Degradation of forest soil diminishes the total biomass quantity as well as the quality, which eventually results in the degradation of the organic carbon pool. Activities such as deforestation, burning of biomass, shifting cultivation, and forest fires accelerate the emission of carbon from the soil (Lal 2004). Agroforestry systems involving tree elements are reported to positively affect the soil carbon storage potentiality. For instance, the soil organic carbon content of Alnus nepalensis-based agroforestry system increased by 37% as compared to the control (Ramesh et al. 2013). Hübner et al. (2021), based on a meta-analytical study, elucidated that agroforestry systems particularly shelterbelts and agrosilvicultural systems are effective land-use practices to enhance the soil organic carbon stocks, in both topsoil and subsoils. The type of land-use systems, time since land-use change, climate, and previous land management practices influence the amount of soil carbon sequestration by the system (Koul et al. 2011; Feliciano et al. 2018).
Table 3.2 Positive and negative land management practices for soil organic carbon accumulation
Land management practices Perennial pastures or pasture leys Organic amendments Fertilizer Irrigation Green and brown manure Retention of stubble Tillage Erosion Fallowing Agri-chemicals Rotations
Effecta +++ ++ ++ ++ ++ + – – 0 0 to +
+, -, 0 indicates positive, negative, and no effects on soil organic carbon accumulation (Kirkegaard et al. 2007)
a
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Soil management practices such as tillage, mulching, and crop residue management have a significant role in the organic carbon mineralization rates of soil. As compared to intensive tillage, land-use systems with zero tillage or minimum or conservation tillage was reported to have a greater accumulation of organic carbon due to higher physical protection offered to the carbon fractions in the soil (Filho et al. 2002). Moreover, the results of minimum or conservation tillage are highly influenced by the soil as well as site conditions. Mulching and addition of residues reduce evaporation and erosion rates of the soil, thereby providing greater stability to the soil aggregates and resulting in higher soil organic carbon accumulation. Erosion control measures like contour ploughing and terracing and the use of cover crops aid in reducing the loss of carbon from the soil. Carbon input into the soil can also be increased through the addition of organic amendments such as manure, compost, and crop residues (Ramlow et al. 2018; Yu et al. 2021).
3.6
Importance of Soil Organic Carbon
Soil organic carbon determines the quality of the land and its productivity and sustainability status (Stevenson and Cole 1999). SOC has a strong dependency and interaction with vegetation, climate, topography, land use, and soil characteristics (type, texture, and aggregation) (Barua and Haque 2013), which in turn influences the water-holding capacity and soil fertility. The Himalayan region has a diversified profile of SOC due to complex physiographical attributes and wide range in altitudes. Proper management and conservation of soil will reduce CO2 emissions, one of the major drivers of climate change, and fix carbon in the long term (Srinivasarao et al. 2014; Fialho and Zinn 2014). Anthropogenic pressure on the atmosphere, such as fossil fuel combustion, urbanization, land-use change, and industrial emissions, critically leads to a severe global warming. Soil can be a deterministic factor in contributing to future carbon sinks if well utilized and managed (Yam et al. 2021) since soils hold three times more carbon than global vegetation and two times that of the atmosphere (Devi and Sherpa 2019). The conversion of forest land to agriculture severely contributes to the depletion of SOC, which eventually degrades soil health and ecosystem sustainability (Yadav et al. 2018). In addition to climate change mitigation, SOC ensures soil-derived ecosystems requiring carbon-friendly land-use and land management practices (Lorenz and Lal 2015). Also, SOC enhances the growth of useful microorganisms that promote plant growth. Soil, the largest terrestrial carbon pool, needs more advanced studies which have high scope and importance in this era of climate change and land degradation.
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Conclusion
The Indian Himalayas are the sinks of tonnes of carbon through the process of sequestration of carbon across various land-use systems ranging from agroforestry systems to planted forests and natural forests. The variations in the type of forests, the composition of species, systems of land management, and the attributes of climate, viz., temperature, determine the differences in the carbon storage capacity of the soil. India remains a significant contributor to greenhouse gases and is consistently trying to reduce its emissions so as to tap the carbon released into the atmosphere. Soils are the largest terrestrial carbon pools and offer a great opportunity for carbon storage. Considering this, the Indian government also aimed to create an additional carbon sink of 2.5–3 Pg CO2 equivalents through afforestation (Ahirwal et al. 2021). However, the soil may also sometimes act as a carbon source due to improper land management practices like tillage, erosion, and excessive usage of agrochemicals. Therefore, judicious and scientific technologies like conservation agriculture and zero tillage can be adopted to preserve the carbon storage capacity of soil and thus mitigate the impacts of climate change effectively.
References Ahirwal J, Nath A, Brahma B, Deb S, Sahoo UK, Nath AJ (2021) Patterns and driving factors of biomass carbon and soil organic carbon stock in the Indian Himalayan region. Sci Total Environ 770:145292 Babu S, Mohapatra KP, Yadav GS, Lal R, Singh R, Avasthe RK, Das A, Chandra P, Gudade BA, Kumar A (2020) Soil carbon dynamics in diverse organic land use systems in North Eastern Himalayan ecosystem of India. Catena 194:104785 Banerjee SK (2014) Forest soil carbon Stock along an altitudinal gradient in Darjeeling Himalayan Region. Indian Forester 140(8):775–779 Barua AK, Haque SMS (2013) Soil characteristics and carbon sequestration potentials of vegetation in degraded hills of Chittagong, Bangladesh. Land Degrad Dev 24:63–71 Bird MI, Lloyd JJ, Šantrůčková H, Veenendaal E (2001) Global soil organic carbon. In: Schulze E, Heimann M, Harrison S, Holland E, Lloyd J, Prentce IC, Schimel D (eds) Global biogeochemical cycles in the climate system. Academic Press, San Diego, pp 185–200 Buraka T, Elias E, Lelago A (2022) Soil organic carbon and its stock potential in different land-use types along slope position in Coka watershed, Southern Ethiopia. Heliyon 8(8):10261 CEPF (2007) Ecosystem profile: Indo-Burma hotspot, Indo-China region. UK: critical ecosystem partnership fund. Birdlife International, Cambridge Chambers A, Lal R, Paustian K (2016) Soil carbon sequestration potential of US croplands and grasslands: implementing the 4 per thousand initiative. J Soil Water Conserv 71:68–74 Chettri N, Sharma E, Shakya B, Thapa R, Bajracharya B, Uddin K, Oli KP (2010) Biodiversity in the Eastern Himalayas: status, trends and vulnerability to climate change. International Centre for Integrated Mountain Development (ICIMOD), pp 1–28 Chhabra A, Palria S, Dadhwal VK (2003) Soil organic carbon pool in Indian forests. For Ecol Manag 173:187–199 Chisanga K, Bhardwaj DR, Pala NA, Thakur CL (2018) Biomass production and carbon stock inventory of high-altitude dry temperate land use systems in North Western Himalaya. Ecol Process 7(1):1–13
3
Soil Carbon Stock Along an Altitudinal Gradient in the Indian Himalayas
51
Dar JA, Sundarapandian SM (2013) Soil organic carbon stock assessment in two temperate forest types of Western Himalaya of Jammu and Kashmir, India. For Res 3(114):2 Devi SB, Sherpa SS (2019) Soil carbon and nitrogen stocks along the altitudinal gradient of the Darjeeling Himalayas, India. Environ Monit Assess 191:361 Eswaran H, Reich PF, Kimble JM (2000) Global carbon stocks. In: Lal R, Kimble JM, Eswaran H, Stewart BA (eds) Global climate change and pedogenic carbonates. CRC Press, Boca Raton, pp 15–25 Falloon P, Jones CD, Cerri CE, Al-Adamat R, Kamoni P, Bhattacharyya T, Easter M, Paustian K, Killian K, Coleman K, Milne E (2007) Climate change and its impact on soil and vegetation carbon storage in Kenya, Jordan, India and Brazil. Agric Ecosyst Environ 122:114–124 Feliciano D, Ledo A, Hillier J, Nayak DR (2018) Which agroforestry options give the greatest soil and above ground carbon benefits in different world regions? Agric Ecosyst Environ 254:117– 129 Fialho RC, Zinn YL (2014) Changes in soil organic carbon under eucalyptus plantations in Brazil: a comparative analysis. Land Degrad Dev 25:428–437 Filho CC, Lourenco A, Guimaraes MDF, Fonseca ICB (2002) Aggregate stability under different soil management systems in a red Latosol in the state of Parana, Brazil. Soil Tillage Res 65:45– 51 Georgiou K, Jackson RB, Vindušková O, Abramoff RZ, Ahlström A, Feng W, Torn MS (2022) Global stocks and capacity of mineral-associated soil organic carbon. Nat Commun 13(1):1–12 Hübner R, Kühnel A, Lu J, Dettmann H, Wang W, Wiesmeier M (2021) Soil carbon sequestration by agroforestry systems in China: a meta-analysis. Agric Ecosyst Environ 315:107437 IPCC (2007) Climate Change 2007: the physical science basis. Contribution of working group I to the fourth assessment report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge Jobbágy EG, Jackson RB (2000) The vertical distribution of soil organic carbon and its relation to climate and vegetation. Ecol Appl 10(2):423–436 Kasel S, Bennett LT (2007) Land-use history, forest conversion, and soil organic carbon in pine plantations and native forests of south eastern Australia. Geoderma 137:401–413 Keller AB, Borer ET, Collins SL, DeLancey LC, Fay PA, Hofmockel KS, Hobbie SE (2022) Soil carbon stocks in temperate grasslands differ strongly across sites but are insensitive to decadelong fertilization. Glob Chang Biol 28(4):1659–1677 Khan RWA, Shaheen H, Mehmood A, Naseer Awan S (2019) Grazing intensity impacts on soil carbon stocks of Western Himalayan Alpine paddocks. Carbon Manage 10(6):533–540 Kirkegaard J, Kirkby C, Gupta V (2007) Management practices for building soil carbon. CSIRO, Canberra Koul DN, Shukla G, Panwar P, Chakravarty S (2011) Status of carbon sequestration under different land use system in Terai Zone of West Bengal. Environ Int J Sci Technol 6:95–100 Kumar PS, Shukla G, Nath AJ, Chakravarty S (2022) Soil properties, litter dynamics and biomass carbon storage in three-bamboo species of sub-Himalayan region of eastern India. Water Air Soil Pollut 233:12. https://doi.org/10.1007/s11270-021-05477-6 Lal R (2004) Soil carbon sequestration to mitigate climate change. Geoderma 123(1-2):1–22 Lal R (2016) Beyond COP 21: potential and challenges of the “4 per Thousand” initiative. J Soil Water Conserv 71:20–25 Lepcha NT, Devi NB (2020) Effect of land use, season, and soil depth on soil microbial biomass carbon of Eastern Himalayas. Ecol Process 9:65 Lorenz K, Lal R (2015) Managing soil carbon stocks to enhance the resilience of urban ecosystems. Carbon Manage 6(1-2):35–50 Lorenz K, Lal R (2018) Soil carbon stock. In: Carbon sequestration in agricultural ecosystems. Springer, Cham, pp 39–136 Mayer M, Prescott CE, Abaker WEA, Augusto L, Cécillon L, Ferreira GWD, Eesterdal L (2020) Influence of forest management activities on soil organic carbon stocks: a knowledge synthesis. For Ecol Manag 466:118127
52
S. N. Najima et al.
Minasny B, Malone BP, McBratney AB, Angers DA, Arrouays D, Chambers A, Chaplot V, Chen ZS, Cheng K, Das BS, Field DJ, Gimona A, Hedley CB, Hong SY, Mandal B, Marchant BP, Martin M, McConkey BG, Mulder VL, O'Rourke S, Richer-de-Forges AC, Odeh I, Padarian J, Paustian K, Pan G, Poggio L, Savin I, Stolbovoy V, Stockmann U, Sulaeman Y, Tsui CC, Vågen TG, van Wesemael B, Winowiecki L (2017) Soil carbon 4 per mille. Geoderma 292:59– 86 Ming DW (2006) Carbonates. In: Lal R (ed) Encyclopedia of soil science. Taylor & Francis, London Nair PR, Nair VD, Kumar BM, Showalter JM (2010) Carbon sequestration in agroforestry systems. Adv Agron 108:237–307 Nave LE, Vance ED, Swanston CW, Curtis PS (2010) Harvest impacts on soil carbon storage in temperate forests. For Ecol Manag 259:857–866 Pan Y, Richard A, Birdsey, Jingyun F, Richard H, Pekka EK, Werner AK, Oliver L, Phillips et al (2011) A large and persistent carbon sink in the world’s forests. Science 333(6045):988–993 Panwar P, Mahalingappa DG, Kaushal R, Bhardwaj DR, Chakravarty S, Shukla G, Thakur NS, Chavan SB, Pal S, Nayak BG, Srinivasaiah HT, Dharmaraj R, Veerabhadraswamy N, Apshahana K, Suresh CP, Kumar D, Sharma P, Kakade V, Nagaraja MS, Singh M, Das S, Tamang M, Roy AD, Gurung T (2022) Biomass production and carbon sequestration potential of different agroforestry systems in India: a critical review. Forests 13(8):1274. https://doi.org/ 10.3390/f13081274 Parton WJ, Rasmussen PE (1994) Long-term effects of crop management in wheat-fallow: II. CENTURY model simulations. SSSAJ 58:530–536 Pradhan R, Sarkar BC, Manohar A, Shukla G, Tamang M, Vineeta, Bhat JA, Kumar M, Chakravarty S (2022) Biomass carbon and soil nutrient status in urban green sites at foothills of eastern Himalayas: implication for carbon management. CRSUST 4:100168 Rai P, Vineeta, Shukla G, Manohar KA, Bhat JA, Kumar A, Kumar M, Cabral-Pinto M, Chakravarty S (2021) Carbon storage of single tree and mixed tree dominant species stands in a reserve forest-case study of the Eastern Sub-Himalayan Region of India. Landscape 10:435 Ramesh T, Manjaiah KM, Tomar JMS, Ngachan SV (2013). Effect of multipurpose tree species on soil fertility and CO2 efflux under hilly ecosystems of Northeast India. Agrofor Syst 87:1377– 1388 Ramesha T, Bolanb NS, Kirkhamc MB, Wijesekarab H, Kanchikerimath M, Raoe CS, Sandeep S, Rinklebeg J, Oki YS, Choudhurya BU, Wangj H, Tangl C, Wang X, Songm Z, Freeman II OW (2019). Soil organic carbon dynamics: impact of land use changes and management practices: a review. Adv Agron 156, https://doi.org/10.1016/bs.agron.2019.02.001 Ramlow M, Rhoades CC, Cotrufo MF (2018) Promoting revegetation and soil carbon sequestration on decommissioned forest roads in Colorado, USA: a comparative assessment of organic soil amendments. For Ecol Manag 427:230–241 Rathore AC, Kumar A, Tomar JMS et al (2018) Predictive models for biomass and carbon stock estimation in Psidium guajava on bouldery riverbed lands in North-Western Himalayas, India. Agrofor Syst 92:171–182 Ravindernath NH, Somashekhar BS, Gadgil M (1997) Carbon flows in Indian forests. Climate Change 35:297–320 Ravindranath NH, Ostwald M (2008) Carbon inventory methods handbook for greenhouse gas inventory, carbon mitigation and round-wood production projects. Springer, Cham, pp 165–166 Rawat D, Sati SP, Khanduri VP, Riyal M, Mishra G (2021) Carbon sequestration potential of different land use sectors of Western Himalaya. In: Advances in carbon capture and utilization. Springer, Singapore, pp 273–294 Rodríguez Martín JA, Álvaro-Fuentes J, Gonzalo J, Gil C, Ramos-Miras JJ, Grau Corbí JM, Boluda R (2016) Assessment of the soil organic carbon stock in Spain. Geoderma 264:117–125 Roy M, Sarkar BC, Abha K, Shukla G, Vineeta, Nath AJ, Bhat JA, Chakravarty S (2022a) Fuelwood species diversity and consumption pattern in the home gardens from foothills of Indian Eastern Himalayas. Agrofor Syst. https://doi.org/10.1007/s10457-021-00728-1
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Roy M, Sarkar BC, Shukla G, Vineeta, Debnath MK, Nath AJ, Bhat JA, Chakravarty S (2022b) Traditional home gardens and ethnomedicinal plants: insights from the Indian Sub-Himalayan region. Trees Forest People 8:100236. https://doi.org/10.1016/j.tfp.2022.100236 Sarkar BC, Shukla G, Debnath MK, Pala NA, Chakravarty S (2020) Diversity and utilization pattern of homegardens: a case study from Eastern Himalayan region of West Bengal. Indian J Agroforestry 22:31–36 Schlesinger WH (2006) Inorganic carbon and the global C cycle. In: Lal R (ed) Encyclopedia of soil science. Taylor & Francis, London, pp 879–881 Shaheen H, Saeed Y, Abbasi MK, Khalid A (2017) Soil carbon stocks along an altitudinal gradient in different land-use categories in Lesser Himalayan foothills of Kashmir. Eurasian Soil Sci 50(4):432–437 Sheikh MA, Tiwari A, Anjum J, Sarma S (2021) Soil carbon pool and dynamics of different fractions in subalpine temperate coniferous forests of Western Himalaya. Environ Monit Assess 193:756 Shukla G, Chakravarty S (2018) Biomass, primary nutrient and carbon stock in a sub-himalayan forest of West Bengal, India. JFES 34(1):12–23 Shukla G, Koul DN, Chakravarty S (2012) Soil carbon sequestration vis-à-vis soil management. Environ Int J Sci Technol 7:107–122 Shukla G, Biswas R, Das AP, Chakravarty S (2013) Visual qualitative description of a humid tropical foothill forest in Indian eastern Himalayas. Biodiversity 14:1–14 Shukla G, Pala NA, Chakravarty S (2014) Carbon, litter and nutrient status in teak stands of a foothill forest in Indian Eastern Himalayas. J Tree Sci 33(2):24–32 Shukla G, Pala NA, Chakravarty S (2017) Quantification of organic carbon and primary nutrients in litter and soil in a foothill forest plantation of eastern Himalaya. DOI, J For Res. https://doi.org/ 10.1007/s11676-017-0394-7 Singh SK, Pandey CB, Sidhu GS, Sarkar D, Sagar R (2011) Concentration and stock of carbon in the soils affected by land uses and climates in the western Himalaya, India. Catena 87(1):78–89 Singh M, Gupta B, Das SK (2018) Soil organic carbon density under different agroforestry systems along an elevation gradient in north-western Himalaya. Range Manage Agrofor 39(1):8–13 Sleutel S, De Neve S, Hofman G, Boeckx P, Beheydt D, Van Cleemput O, Lemeur R (2003) Carbon stock changes and carbon sequestration potential of Flemish cropland soils. Glob Chang Biol 9(8):1193–1203 Srinivasarao C, Venkateswarlu B, Lal R, Singh AK, Kundu S, Vittal KPR, Patel JJ, Patel MM (2014) Long-term manuring and fertilizer effects on depletion of soil organic carbon stocks under pearl millet-cluster bean-castor rotation in Western India. Land Degrad Dev 25:173–183 Stevenson FJ, Cole MA (1999) Cycles of soils: carbon, nitrogen, phosphorus, sulfur, micronutrients, 2nd edn. Wiley, Hoboken Subba M, Pala NA, Shukla G, Chakravarty S (2018) Study of the variability of home gardens influencing carbon stock under sub-humid tropical zone of West Bengal, India. Indian Forester 144(1):66–72 Tamang M, Chettri R, Vineeta, Shukla G, Bhat JA, Kumar A, Kumar M, Suryawanshi A, CabralPinto M, Chakravarty S (2021a) Stand structure, biomass and carbon storage in Gmelina arborea plantation at agricultural landscape in foothills of Eastern Himalayas. Landscape 10:387 Tamang B, Pala NA, Shukla G, Rashid M, Rather MM, Bhat JA, Masoodi TH, Chakravarty S (2021b) Trees outside forest (TOFs) aids in mitigating global climatic change through carbon sequestration: example from academic institutional landscapes. Acta Ecol Sin. https://doi.org/ 10.1016/j.chnaes.2021.06.007 Thangavel R, Kanchikerimath M, Sudharsanam A, Ayyanadar A, Karunanithi R, Deshmukh NA, Vanao NS (2018) Evaluating organic carbon fractions, temperature sensitivity and artificial neural network modeling of CO2 efflux in soils: impact of land use change in subtropical India (Meghalaya). Ecol Indic 93:129–141 Townsend AR, Vitousek PM, Trumbore SE (1995) Soil organic matter dynamics along gradients in temperature and land use on the island of Hawaii. Ecology 76:721–733
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Vineeta, Sarkar BC, Tamang M, Shukla G, Debnath MK, Nath AJ, Chakravarty S (2022) Floristic diversity and conservation status of large cardamom based traditional agroforestry system along an altitudinal gradient in the Darjeeling Himalaya, India. Agrofor Syst 96:1199–1210 Wei X, Shao M, Gale W, Li L (2014) Global pattern of soil carbon losses due to the conversion of forests to agricultural land. Sci Rep 4:4062 Yadav GS, Das A, Lal R, Babu S, Meena RS, Saha P, Singh R, Datta M (2018) Energy budget and carbon footprint in a no-till and mulch based rice–mustard cropping system. J Clean Prod 191: 144–157 Yadav GS, Kandpal BK, Das A, Babu S, Mohapatra KP, Devi AG, Devi HL, Chandra P, Singh R, Barman KK (2021a) Impact of 28 year old agroforestry systems on soil carbon dynamics in Eastern Himalayas. J Environ Manag 283:111978 Yadav GS, Das A, Babu S, Mohapatra KP, Lal R, Rajkhowa D (2021b) Potential of conservation tillage and altered land configuration to improve soil properties, carbon sequestration and productivity of maize based cropping system in eastern Himalayas, India. Int Soil Water Conserv Res 9:279–290 Yam G, Tripathi OP, Das DN (2021) Modelling of total soil carbon using readily available soil variables in temperate forest of Eastern Himalaya, Northeast India. Geo Ecol Landsc 5(3): 209–216 Yu Y, Zhang Y, Xiao M, Zhao C, Yao H (2021) A meta-analysis of film mulching cultivation effects on soil organic carbon and soil greenhouse gas fluxes. Catena 206:105483 Zomer R, Ustin S, Ives J (2003) Using satellite remote sensing for dem extraction in complex mountainous terrain: landscape analysis of the Makalu Barun National Park of Eastern Nepal. Int J Remote Sens 23(1):125–143
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Impact of Land Uses on Soil Organic Carbon Dynamics in the Indian Himalayan Region Anshuman Das, Gaurav Mishra, Pramod Chand Lakra, Sanjeev Kumar, and Shambhu Nath Mishra
Abstract
Land use contributes to enhance food, fodder and firewood in the society, promoting sustainability and livelihood security. The land use systems also have a vital role in affecting the soil organic carbon (SOC) in order to mitigate and adapt to climate change. Soils are the largest terrestrial reservoir for atmospheric carbon and have the potential to mitigate the effect of global warming. Therefore, an in-depth understanding of changes in the different pools of carbon is necessary for predicting changes in the pattern and magnitude of SOC storage in different land use systems. It also contributes to the adoption of efficient land use planning for sustainable soil management. The SOC sustains the soil physical and biochemical quality. Soil carbon mineralization, carbon sequestration, carbon stabilisation, etc. play a vital role in governing the dynamics of SOC. Thus, dynamics of SOC under various land uses could be a crucial driver in mitigating climate change. Soil aggregates have the potential to accumulate large quantities of SOC, and hence its distribution along with SOC content in aggregates could be a critical factor for its decomposition. Moreover, the quantification of soil carbon stock under various land use systems is a valuable consideration for carbon budgeting. The protection of organic carbon of soil in deeper layers of a particular land use is of critical importance for long-term carbon sequestration as it is less exposed to human-induced changes. Thus, proper knowledge on dynamics of A. Das (✉) · S. Kumar · S. N. Mishra Forest Ecology and Climate Change Division, ICFRE-Institute of Forest Productivity, Ranchi, Jharkhand, India G. Mishra Indian Council of Forestry Research and Education, Dehradun, Uttarakhand, India P. C. Lakra Silviculture Division, ICFRE-Institute of Forest Productivity, Ranchi, Jharkhand, India # The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Mishra et al. (eds.), Soil Carbon Dynamics in Indian Himalayan Region, https://doi.org/10.1007/978-981-99-3303-7_4
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SOC in different land use systems is expected to improve the understanding to conduct suitable land uses and management strategies for the long-term sustainability of the Indian Himalayan region. Keywords
Land uses · Soil organic carbon · Indian Himalayan Region · Climate change
4.1
Introduction
The majority of the Indian Himalayan Mountain region is covered with forest, and the soils there have large levels of organic carbon. The depletion of soil organic carbon (SOC), which has resulted in a falling trend in productivity, has been caused by dramatic changes in climate and land use over the past few decades. The primary indicator of soil quality and environmental sustainability is SOC content (Yadav et al. 2018). It is significant for the global carbon cycle (Lal 2018; Kooch et al. 2020). Despite the significance of SOC for soil quality, one of the biggest concerns regarding the sustainability of ecosystems is its rapid depletion (Yadav et al. 2018). Depending on their level of labilities, the SOC can be classified into labile and non-labile fractions (Sahoo et al. 2019). Among them, management techniques and pedo-climatic conditions have the most significant impact on the labile carbon fractions (Sahoo et al. 2019). Non-labile carbon fractions, on the other hand, are resistive and least impacted by land use management measures (Bayer et al. 2002). As a result, the labile carbon fraction is a reliable predictor of changes in dynamics of SOC brought on by management (Six et al. 2002). The Indian Himalayan Region is spread across 13 Indian States/Union Territories namely Jammu and Kashmir, Ladakh, Uttarakhand, Himachal Pradesh, Arunachal Pradesh, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim, Tripura, Assam and West Bengal (Fig. 4.1). Climate and land use have a significant impact on soil carbon stocks (Lal 2018). These variables (temperature, land use, etc.) control SOC storage in aggregates and interaction of SOC with soil particles, both of which are crucial carbon stabilisation processes (Six et al. 2002). Due to the annual cycle of carbon inputs and varied levels of soil disturbance, stratification of different pools/fractions of SOC is also a frequent phenomenon in many land use systems (Sahoo et al. 2019). SOC is depleted when forest land is turned into farmland (Yigini and Panagos 2016). It is a crucial part of the ecosystem as SOC affects the dynamics of greenhouse gases (Kirschbaum 2000). The biggest portion of the carbon supply on Earth is found in soils (Batjes and Sombroek 1997). There are roughly 1200 Pg of inorganic carbon, mostly in the form of pedogenic carbonates, and about 1500 Pg of organic carbon (Batjes 1996; 1 Pg = 1.1015 g). According to George et al. (1985), soils beneath croplands, temperate woods, and tropical forests can be found up to 1 m deep. According to reports, in the last 20 years, fossil fuel burning has accounted for the remaining three-quarters of anthropogenic carbon dioxide emissions, with land use change, particularly deforestation, accounting for roughly one-fourth (Barnett et al.
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Fig. 4.1 Indian Himalayan Region (Source: National Mission on Himalayan Studies 2023)
2005). According to studies, organic carbon in soil is very susceptible to changes in land use from natural ecosystems like forests or grasslands to agricultural systems, which causes organic carbon to be lost (Paul et al. 1997). By affecting soil respiration and carbon fluxes, changes in land use and vegetation also contribute to the depletion of carbon in the atmosphere (Post and Kwon 2000). India’s Himalayan temperate forests cover a considerable portion of the nation’s territory (Singh 1998). Gupta and Rao (1994) estimated the SOC storage at 24.3 Pg at a mean soil depth of 137 cm based on 48 benchmark soil series. Bhattacharya et al. (2000) refined these estimations from 1800 pedons and reported 63 Pg in 1.5 m soil depth. It is estimated that approximately 67% of the Indian Himalayan glaciers are receding (Miller 2007). Oerlemans (2005) noted that since 1980, the rate of glacial retreat worldwide has dramatically risen, with 142 of the 144 alpine glaciers where the majority of the events between 1900 and 1989 occurred exhibiting a net reduction. As a result, the SOC pool needs to be maintained and increased, especially in the Himalayan region (Bhattacharya et al. 2000). To understand the changes in soil characteristics and carbon fluxes in ecosystems requires quantitative analysis of the dynamics of SOC. The carbon fractions have been classified into active and passive pools based on the SOC's residence period (Chan et al. 2001). The active carbon pool has been defined as the microbial and derivative products that are very active in recycling within a time frame of 5 years, while fractions with considerably longer residence times than the active carbon pool are characterised as the recalcitrant or passive carbon pool. Due to the diverse processes involved in their release and sequestration, these large carbon pools
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significantly contribute to the atmospheric carbon concentration. However, the active carbon pool’s C sink potential is quite limited due to its short residence period (Luo et al. 2003). The passive pool enhances soil quality and production while also adding to the stock of total organic carbon (TOC) (Mandal et al. 2008). Consequently, the passive pool can serve as a reliable indicator of carbon sequestration (Paul et al. 2001). The availability of organic matter and the rate at which it decomposes affect the type and amount of SOC (Krull et al. 2003). For instance, belowground litter with a high lignin concentration takes longer to decompose, which in turn controls the amount of carbon in an active carbon pool (Freschet et al. 2013). The litter decomposition rate is inversely correlated with mean residence time and linearly correlated with turnover rate which further influences SOC lability (Certini et al. 2015).
4.2
Soil Organic Carbon Pools and Dynamics
The changes in SOM content will have an impact on the atmospheric CO2 concentration because the global soil C pool is larger than the sum of the biotic and atmospheric pools. Understanding SOC dynamics is crucial for reducing the negative consequences of climate change as there is evidence pointing to the great potential of soils affected by salt for carbon sequestration (Lal 2004a, b; Setia et al. 2013). The SOC is made up of multiple pools, including active, slow and passive, with varying turnover rates that range from a few months to many hundreds of years (Fig. 4.2).
Fig. 4.2 Interaction between different pools of carbon and factors of soil organic carbon dynamics
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(a) Structural litter pool: This is made up of straw, wood, plant stems and similar components. The C:N ratio fluctuates between 150:1. Lignin content is also higher in this fraction. (b) Metabolic pool: Plant leaves, tree bark, flowers, fruits and animal excrement are all part of it. The ratio of C to N varies from 10 to 25. When this portion breaks down, mineral nitrogen is added. (c) Active soil organic carbon pool: It is a labile type of C that contains leftovers from both fresh plants and animals. The biological functions of soil are connected to this pool. (d) Slow soil organic pool: This phase exists between the active and passive C pools. This is linked to the physical and chemical activity of the soil. (e) Passive soil organic pool: This pool is made up of humus or non-labile type of carbon that is related to climate change and carbon sequestration. This pool is not biologically active.
4.2.1
Total Organic Carbon (TOC)
Organic elements (living and dead) found in soils make up soil organic matter (SOM) (Stevenson 1994). It consists of a huge variety of organic molecules, ranging from simple, organic wastes to intricate, resistant products and microbial biomass (Stevenson 1994). It is assumed that SOM includes 58% carbon since the carbon percentage contained in organic matter represents the total organic carbon (TOC) in the soil.
4.2.2
Particulate Organic Carbon (POC)
The size of the pool components affects the functions and turnover of SOM fractions (Cambardella and Elliot 1992). Physical fractionation systems often divide SOM into three major categories: mineral-associated organic matter (size 53 m), fine particle organic matter (fPOM), and coarse particulate organic matter (cPOM), which contains organic fragments >250 m. POM, which is made up of partially digested organic wastes, is frequently used as a measure of the lability of SOM, with active (labile) carbon pools represented by cPOM and sluggish (less labile) carbon pools by fPOM, respectively (Benbi et al. 2014).
4.2.3
Dissolved Organic Carbon (DOC)
There are numerous sources of dissolved organic carbon (DOC), including plant litter, root exudates, soil humus, and microbial biomass (Bolan et al. 2004). It can be considered as a continuum of organic molecules that pass through a 0.45-m filter and are of different sizes, compositions, and architectures. There is still some uncertainty
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regarding the origin of DOC, despite substantial research on its processes and functions (mostly in forest soils).
4.2.4
Microbial Biomass Carbon (MBC)
The live SOC fraction is represented by microbial biomass carbon (MBC), which has undergone substantial research. MBC is a significant measurable carbon fraction that is incorporated in several multi-pool models of SOC dynamics and is regarded as an estimate of biological activity in soil (Hanson et al. 2000).
4.3
Mechanism of C Stabilisation in Soil
Three mechanisms—chemical, physical, and biological processes—are the key mediators in the stabilisation of carbon. (a) Chemical stabilisation: through physicochemical connection between SOM and soil matrix, chemical stability shields SOC against microbial degradation (e.g. soil clay and silt particles). Clay and silt in the soil can help micro- and macroaggregates produce and protect SOM. However, culture has a tendency to decompose this and release C as CO2. Along with clay concentration, clay varieties (such as 2:1 versus 1:1 versus allophonic clay minerals) also have an impact on how well organic matter is stabilised. (b) By binding to minerals and occluding inside macro- and/or microaggregates, physical stability shields SOM from microbial degradation (Tisdall and Oades 1982). The occlusion would make SOM accessible to microorganisms due to interactions between organominerals and organo-metals (Ghosh et al. 2019; Ghosh et al. 2016). Adsorption on mineral surfaces, complexation, and precipitation are only a few examples of the numerous phenomena involving organo-minerals and organo-metal interactions. These intricate events largely aid in SOM stability (Ghosh et al. 2016).
4.4
Factors Affecting Soil Organic Carbon (SOC) Dynamics
With almost 4.5 times as much carbon stored in soils as there is in terrestrial biomass, soils are one of the most significant carbon sinks. They also represent the most dynamic and unexplored part of the carbon cycle (Jobbagy and Jackson 2000). The size of the SOC pool is influenced by a number of variables that affect carbon decomposition, type of vegetation and NPP (net primary productivity), soil properties, wate content (Ren et al. 2012; Ryan and Law 2005; Tian et al. 2010), temperature sensitivity of carbon, forest fire and land use change (Post and Kwon 2000). Small changes in variables influencing the carbon cycle of soil could have unanticipated effects on the carbon feedback (positive) contributed to the atmosphere because they are one of the largest pools. Additionally, SOC regulates a number of soil physical, biological, and chemical processes that have an impact on
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Fig. 4.3 Factors affecting soil organic carbon dynamics
plant development and sustainability in terrestrial ecosystems (Lal 2004a, b). Soil contains the organic carbon pool which is a heterogeneous mixture of organic compounds and ranges from simple sugars to complex humified materials which, when combined with a variety of soil aggregates, may change from being unstable to stable (Banger et al. 2010). Despite extensive study at many spatiotemporal scales, the balance of the soil carbon pool in relation to the atmosphere is still inadequately represented in contemporary Earth System Models due to their single and interactive effects on biotic and climatic parameters (Karhu et al. 2014). The fundamental regulators of SOC decomposition have traditionally been thought to be environmental variables, especially temperature and moisture, which overstate the contribution of different terrestrial pools to the atmosphere (Carvalhais et al. 2014). The modelling approaches, which have insufficient parameterization of the temperature sensitivity of carbon, microbial utilisation of carbon, and interactions between mineral and organic components, characterise poorly the actual distribution of SOC globally (Carvalhais et al. 2014), in part to explain the uncertainties in predictions (Tang and Riley 2015). There is fluctuation in quantity and quality of various SOC pools on the rate of photosynthetic C addition and their losses through decay. Through breakdown, erosion and leaching, the environment recycles the C in the leaf and root biomass. Consequently, the main factors that affect SOC are climatic factors, soil factors viz. mineral content, clay context, soil texture, soil structure, porosity, soil moisture, soil microbial community, topography and altitude that controls the organic carbon dynamics of soil (Fig. 4.3). The balance of quality and quantity of carbon inputs and carbon outputs from soil determines the
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amount of SOC. Despite study efforts, the mechanisms for stabilising carbon in soil and the variables that control them remain poorly understood.
4.4.1
Climatic Factors
4.4.1.1 Temperature For accurate predictions of the biological cycling of carbon, these groups’ reactions to temperature changes are crucial. Two factors contribute to the strong temperature dependence of biochemical decomposition of SOC: (1) direct effects on enzyme kinetics of enzyme, metabolism of microbes, and molecular properties; and (2) indirect effects on substrate solubility of carbon as well as diffusion (Conant et al. 2011). The extrinsic temperature dependence of carbon decomposition, in contrast to the intrinsic effects, is extremely context-specific and varies with change in climate and soils. The physical and chemical protective mechanisms can impact the temperature sensitivity of SOC breakdown due to soil and climatic constraints: physical protection: SOC contained in aggregates may encounter less microbial activity and a low oxygen environment. Similarly, organic molecules can be resisted from enzymes that are soluble in water due to their intrinsic poor water solubility or hydrophobicity (Spaccini et al. 2002). Inner or outer sphere complexes formations through mineralorganic matter interactions contribute to chemically protecting these complexes from the forces that cause breakdown (Oades 1988). The Arrhenius equation is typically used to describe temperature, a critical rate-determining element in organic carbon decomposition. 4.4.1.2 Rainfall One of the primary abiotic elements affecting the dynamics of SOC under different types of land use, including agriculture, grassland, horticulture and forestry, is rainfall. It directly alters the habitat for plant growth and species diversity, which in turn affects how much aboveground and belowground biomass is produced. Through root-induced protection of organic carbon in soil, increased biomass production has a beneficial effect on storage of organic carbon in soil. It has an indirect impact on biological processes that modify the pH, redox potential, nutrient availability, weathering and mineralogy of the soil (Schuur et al. 2001). Precipitation of acid in soil lowers soil pH, which has an impact on soil biological activity, nutrient availability and, ultimately, SOC sequestration. CO2 is the principal by-product of carbon decomposition, and all CO2 emitted into the atmosphere occurs by microbial decomposition and root respiration. As a diffusion medium for carbon substrates and degradative enzymes, soil moisture indirectly regulates the decomposition of carbon. Reduced soil water layer thickness will impede the diffusion of carbon substrates and extracellular enzymes, reducing the amount of available substrate for reactions at microsites. Excessively wet soil, on the other hand, limits the rate of oxygen transport to reaction
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sites and encourages anaerobic decomposition, which is typically connected to much more gradual degradative enzymatic pathways.
4.4.2
Edaphic Factors
4.4.2.1 Parent Materials The geochemistry of different minerals, the composition and the reactivity of soil are all influenced by the parent material and the degree of weathering. Higher biomass is produced by soils with high nutritional status, which results in greater organic carbon sequestration. The specific surface area along with the charge densities of soils with 1:1 clay minerals (kaolinite), 2:1 clay minerals (montmorillonite), and Fe and Al oxides and hydroxides differs. The variance in the binding strength between the SOC and clay minerals is determined by these clay mineral characteristics. The potential of the soil to store carbon varies among ecosystems and soil types due to mineral and organic matter interaction. The alluvial soils followed by desert soils had the highest soil inorganic carbon concentration, with the highest SOC being found in red soils, alluvial soils and black soils. Because most of the carbon in arid soils is in the form of calcium carbonate, the SIC content was higher than the SOC level (CaCO3). CaCO3 is a more stable carbon source that is less obtainable to soil bacteria. Furthermore, due to high temperatures in arid places, SOC breakdown occurs more quickly than in other regions. Negatively charged soil minerals typically resist organic anions, although binding happens when multivalent cations are present on the exchange complex. 4.4.2.2 Soil Texture The size distribution of the sand, silt and clay-sized particles that help to compose the mineral portion of the soil is referred to as soil texture (Kettler et al. 2001). These size fractions of different minerals interact with soil organic carbon and hold onto soil carbon for a considerable amount of time (Post and Kwon 2000). According to reports, soil texture has a significant impact on the stabilisation of carbon and the rate of SOC sequestration in soils (Lal 2004a, b). Because of their low capacity for protection and low clay content, sandy or sandy to loam soils cannot keep SOC for an extended period of time. According to a study using soil microaggregates, soil organic matter is physically shielded by clay and silt aggregates, protecting it from microbial decomposition and allowing carbon to be sequestered in soils (Skjemstad et al. 1993). Furthermore, according to reports, with increase in clay content, SOM tends to increase based on two mechanisms, which is related with the highest concentrations of SOC found in soils. First off, decomposition is actively hampered by the complexation of organic and clay particles. Second, increased soil clay concentration raises the likelihood of aggregate formation. In a nutshell, macroaggregates significantly protect organic matter against mineralization and microbial use.
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4.4.2.3 Soil Moisture According to Christ and David (1996), soil moisture impacts carbon sequestration and is a key factor in the breakdown of SOC by soil bacteria (Lamparter et al. 2009). The effects of temperature and soil moisture on microbial SOC consumption are additional considerations (Post and Kwon 2000). By increasing soil moisture, an increase in microbial biomass nourishes the soil biota. 4.4.2.4 Soil Structure The term ‘soil structure’ refers to how soil particles are arranged into aggregates or peds, which frequently take on distinctive shapes and are typically found within particular soil horizons. These groupings produce solids and voids in the soil horizons of varying sizes. SOC and soil structure are connected. SOC serves as a binding agent during the development of soil aggregates, and soil aggregate stability is crucial for preserving soil structure (Bronick and Lal 2005). SOC is frequently held in the pore area surrounding aggregates, which helps to stabilise carbon. In some soils, aggregate-associated organic matter, which makes up over half of the total SOC, serves as a significant carbon source (Sarkhot et al. 2007). 4.4.2.5 Porosity The percentage of total soil volume occupied by the pore space is referred to as soil porosity (Nimmo 2004). Pore spaces primarily aid in the flow and accessibility of air or water inside the soil environment. In the soil environment, four types of pore structures have been identified: macropores, the space between macroaggregates, the pore space between microaggregates but within macroaggregates, and the pores within microaggregates. By providing a place for the survival of soil microorganisms, these pores have an impact on soil biodiversity. For instance, bacteria occupy the pores of microaggregates to serve as their home, whereas protozoa, nematodes and fungi live in the pore space between them. Aggregates bind and stabilise SOC produced from microorganisms within soil pores, which affects soil carbon sequestration. 4.4.2.6 Soil Microbial Community Soil organic matter is made up mostly of living microbes and their dead fractions, in addition to any plant or animal remains that may be present in the soil (Hoorman and Islam 2010). The humus, which endures for many years and contributes to the carbon store (long-lived) in soils, is resistant to microbial degradation. The decomposition of soil organic matter is facilitated by soil microorganisms, and the rate of breakdown is influenced by both the kind of soil microorganisms and the type of organic matter sources. One of the methods for lowering SOC turnover and so raising carbon sequestration is to increase the activity of soil fungi (Jastrow et al. 1998). In addition to the humification process, SOM mineralization by soil microbes results in carbon loss. The soil microbial metabolism is assessed by using carbon use efficiency (CUE) (Strickland and Rousk 2010). Low CUE organisms release a greater percentage of carbon from metabolism as CO2 during respiration. Indirectly,
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soil bacteria have an impact on the SOM that is physically protected by promoting soil aggregation, which in turn helps soils stabilise carbon (Six et al. 2006).
4.4.2.7 Topography The ability of landscape for storing carbon in their soil differs depending on the topography, microclimate and parent materials. Due to soil erosion and the redistribution of different sizes of soil particles and organic matter over a landscape, as well as the impact of water distribution on SOC dynamics, topography has an impact on soil carbon budgets (Senthilkumar et al. 2009). At field scales, topography is a major passive soil formation element, which strongly influences the link between SOC and terrain features (Papiernik et al. 2007). 4.4.2.8 Altitude Several factors influence the accumulation and removal of carbon in SOC. Altitude has a large influence on climatic factors particularly temperature and moisture. Regardless of land use, altitudinal variation has a significant impact on carbon content. SOC concentration varies with elevation due to changes in climatic variables with altitude (Choudhury et al. 2016). The total annual rainfall increases with altitude, which further controls soil processes, properties and development and increases biomass production due to improved soil aggregation. Temperature is also affected by altitudinal variation, which influences the rate of SOC accumulation and decomposition in soils (Choudhury et al. 2016).
4.5
Impact of Different Land Uses on Soil Organic Carbon
SOC pools are functionally stable in SOC and have various degradation rates, as demonstrated by Zimmermann et al. (2007). They show that there are three key mechanisms for SOM stability: (1) occlusion within soil aggregates, (2) physicochemical protection via connection with soil minerals and (3) inherent chemical recalcitrance. Depending on their sensitivity, different SOC pools deteriorate at varying rates. SOC sensitivity can be determined by changes in the relative distribution of SOC between pools brought on by changes in land use or land management techniques (John et al. 2005). Forests are the most valuable elements in ecological systems because of the biotic components and carbon they retain in their tissues, which increases with age and growth and contributes to reduce various GHGs and climate change (Nabuurs et al. 2000). Because the carbon deposited in forests has a substantial impact on the pathway for stabilising the climate, the carbon cycle links forests to climate change. Carbon makes up roughly 43–50% of the dry biomass of trees (Negi et al. 2003). Increasing forest production is necessary to address the rising levels of atmospheric CO2 (Mishra et al. 2017). Due to urbanisation and anthropogenic activity in the Himalayas, many elements of the forest ecosystems have been damaged. The main cause of the significant changes in climate is the shrinkage of forest areas as a result of anthropogenic and developmental activity. Therefore, it makes sense to better
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manage forest resources in order to store more carbon. Nearly 19% of India is covered by the Himalayan zones, which have a lot of forest vegetation and contain 33% of the country’s SOC reserves (Bhattacharyya et al. 2008). The vegetation in the western Himalaya ranges from tropical dry deciduous Sal (Shorea robusta) forests in the foothills to timberline. According to Ram et al. (2004), these regions’ predominant forest ecosystems are oak (Quercus leucotichophora) and pine (Pinus roxburghii). Nath et al. (2018) investigated in soil carbon stocks in Barak Valley, Assam, and revealed that accumulation of SOC stock was more in natural forest in comparison to rubber plantation and grassland. There is a loss of 15–50% of SOC over time when a forest is converted to rubber plantations (Li et al. 2015). Similarly, it was also found that when grassland is made from a natural forest, 23% of organic carbon stock in soil is lost (Straaten et al. 2015). The carbon sink in soil may be increased due to biomass when plantation is done in grassland (Lal 2005). As the age of plants and soil depth increase, the relative proportion of non-labile and less-labile carbon increases in SOC stocks in rubber plantations. The recalcitrant pools are less sensitive to oxidation; thus high content of recalcitrant pool indicates relative stability of SOC stocks (Spohn et al. 2016). It was found that the rubber plantations helped in the formation of stable SOC over the long term (Wang et al. 2013). According to Wilson et al. (2008), altering natural land systems to create cultivable agricultural land results in a change in land use that affects SOC (Poeplau and Don 2013). According to Gregorich et al. (2005), converting forest area to arable land resulted in a 20–50% decrease in SOC stocks. According to Zimmermann et al. (2007), forest soils play a significant role in global C sequestration and could serve as a sink for storing atmospheric CO2. As a result of diverse land management techniques including irrigation, tillage and manuring, changes in land usage also have an impact on around 20% of the CO2 emissions that contribute to global warming (Akpa et al. 2016). Singh et al. (2011a, b) investigated the SOC stocks as influenced by different land use and climate in the western Himalayan region. It was found that the land uses within a climatic condition had significant influence on SOC concentration as well as SOC stock in surface and subsurface soil depths. In the Himalaya, agrihorticulture systems are the prevalent land use practises (Yadav et al. 2016). In the Kullu district of Himachal Pradesh, Rajput et al. (2016) studied the effects of five various elevations and the region’s current agroecosystems on biomass and carbon sequestration capacity. Under four elevations with five common land uses—agriculture, agrihorticulture, horticulture, silvipasture and forest—representing a variation in temperature of around 1 °C each, it was found that the agrihorticulture land use system, located in the altitudinal range of 2000–2300 m asl, had the most potential for sequestering carbon, whereas agricultural land use system, located in the altitudinal range of 1100–1400 m asl, had the lowest potential. Fruit-based agrihorticulture had a higher rate of carbon sequestration potential than any combination of woodlands and pastureland. The majority of agricultural crops are managed intensively, which increases biomass output in agricultural land use, but because the produce is harvested and taken from the fields every year, the potential for carbon sequestration is decreased. Greater carbon
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sequestration potential is found in agroforestry systems which follows management practices where biomass is accumulated for a longer period of time. Rajput et al. (2016) reported that sequestration of carbon was highest in agrihorticulture whereas the accumulation of biomass was highest in Forest with respect to silvipasture, agrihorticulture, horticulture and agriculture land uses in Kullu, Himachal Pradesh. On the other hand, carbon mitigation value was found to be lowest in agrihorticulture and highest in agrihortisilviculture among agrihortisilvi, silvipasture, agrisilviculture and agrihorticulture land use system in Solan (Goswami et al. 2014). Singh et al. (2019) reported that the carbon stock comprising vegetation, litter and soil was highest in forest land use among all the land use systems (agriculture, forest, horticulture, grassland, agrisilvicultural, silvopastoral, agrihorticulture, agrihortisilviculture) but higher carbon stock was found in agrihortisilviculture system than agroforestry and agriculture land use system. Soil organic stocks was found to be higher in forest and pastures than agriculture in Uttarakhand (Singh et al. 2011a, b). Similarly, Chisanga et al. (2018) reported that the carbon density was found to be highest in agrihorticulture system and least in barren land among agriculture, barren land, horticulture, agrihortisilviculture, silvipasture and agrihorticulture land use system in Kullu, Himachal Pradesh. Carbon Management Index (CMI) was found to be higher in forest than the other agricultural land uses viz. organic farming, fodder crops, soybean, wheat and barren land in Kumaun region (Kalambukattu et al. 2013). Gosain et al. (2015) reported that among two forest land use systems viz. Oak and Chir Pine, the oak forest was found to have significantly higher carbon stock than the pine forest in Almora, Uttarakhand. On the other hand, among other two forest types composed of Pinus wallichiana and Abies pindrow, higher SOC stock was found in the first one compared to the second in Pahalgam and Ananatnag (Dar and Sundarapandian 2015). Yadav et al. (2017) reported that in the agroforestry system composed of tree Carya illinoinensis and agricultural crops wheat and lentil, the carbon storage was found to be higher in Carya sp. with agricultural crop compared to the agricultural cropping system alone. Krishan et al. (2017) found that the carbon assimilatory capacity was highest in Abies pindrow and lowest in Cedrus deodara due to higher belowground carbon stock in the former in Garhwal region of Uttarakhand. A similar result was found in determining the SOC mitigation density in the southern region of Kashmir (Wani et al. 2014). On the other hand, the total carbon sequestration was found to be highest in Ulmus villosa followed by Albizia procera, Quercus sp., Pinus roxburghii, Alnus nitida, Acacia catechu, Acacia mollissina and least in Eucalyptus tereticornis in Solan (Devi et al. 2013). Mishra et al. (2021) while studying the changes in carbon stocks under plantation and natural forest in West Garo Hills of Meghalaya reported that when the natural forests are converted to plantations, the SOC stock get affected. It was found that the change of SOC stocks was lower in rubber plantation than the forest over chronosequence ages of 0–5 years and 30–40 years old plantations. On the other hand, SOC stocks were higher for tea and cashew nut plantation than the forest whereas it was lower in pineapple and arecanut plantations than the forest. Mishra and Francaviglia (2021) studied the effect of different land uses on soil in Nagaland and reported that
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there is a requirement for best management options for the jhum and plantation land uses in order to increase SOC stocks. They have also reported that there is depletion of nutrient and SOC when continuous jhum cultivation is followed in the long term. It was also reported that most of the soils under different land use systems viz. mulberry, sugarcane, tea and rice-fallow are depleted in exchangeable fractions of potassium covering three districts in Assam (Das et al. 2019a). It was also reported that the forest land use systems have higher potential to supply the subsoil potassium in the long term compared to the rice-fallow land use system in Assam (Das et al. 2019b). Ghosh et al. (2020) observed that the forest land use systems have lower quality of SOC than mulberry, rice-mustard and rice-fallow land use systems of Assam in North-East India. They also reported that the forest land use system was less susceptible to immediate loss of carbon in case of sudden rise in temperature than other land use systems. Thus, the forest land use system has the capability to sequester more SOC than other land use systems which can further help to mitigate climate change. Babu et al. (2020) studied the impacts of land use systems on microbial biomass carbon (MBC) and the dehydrogenase (DHA) activities and reported that during the rainy season, optimal temperature, adequate soil moisture, and a sufficient supply of substrate carbon could have catalysed microbial activity, whereas less soil moisture and low temperature slowed the functions of enzymes and microbes (Xu et al. 2013). According to Sharma et al. (2014), agricultural fields may be more susceptible to soil erosion as a result of the farming methods used, whereas degraded lands may have stabilised through time with less human interference and the emergence of sporadic bushy vegetation. Compared to agricultural and degraded lands, the soils in horticulture systems exhibited larger TOC stocks. Compared to the routine removal of biomass, plantations add a lot of litter to the soil. In surface soils, the pattern of forests > horticulture > degraded lands > agriculture was followed by total carbon (TC), the sum of TOC and IC. However, in terms of TC, forest land use systems were next to degraded areas in the subsurface. The main source of total carbon in degraded soils is inorganic carbon, which rose significantly with depth under waste fields and accounts for higher TC in the lowest depth in this land use system (Wissing et al. 2010).
4.6
Implications of Land Use Change on Soil Carbon Sequestration
The use of the land affects the quantity of carbon that is stored in the soil. The forest systems among the various types of land cover store the most carbon in the soil (Smith 2007). It was believed that forest soils would contain more organic carbon (Sharma et al. 2014). Forest soils experience less soil disturbance, such as tillage, than agricultural systems. Additionally, leaf litter that falls to the ground tends to build up and enrich the soil. Contrarily, due to crop waste clearance, tillage techniques and the addition of minimal biomass to the soil, agricultural production
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systems tend to lose carbon from the soil (Baker et al. 2007). By disrupting the soil’s aggregate protection and exposing the organic matter to soil microorganisms, tillage speeds up the oxidation of organic C. The low organic carbon in cropping systems in the north-eastern Himalayas of India is linked to recurrent soil disturbances, farming along gentle to mild slopes and irregular manuring (Choudhury et al. 2016). Manure additions and leftover biomass are significant sources of organic carbon in agricultural systems, whereas tillage negatively impacts soils’ capacity to store carbon. There is no such disruption on degraded areas, and there are also no outside supplies of organic waste. Despite having the highest inorganic carbon (IC) content, degraded soils exhibited a low level of total organic carbon. Higher organic inputs are present in the forest, horticultural and agricultural land use systems through litter deposition, residue assimilation, or external applications of organic materials. It has been found that the soil’s inorganic C concentration reduces when organic matter is added (Li et al. 2010). The upper layer of the soil profile contains 69% of the carbon in the soil (Singh et al. 2011a, b). The addition of organic matter in the form of leaf litter in a forest or manures in the case of agricultural soils results in high TOC in the higher layers. The same principle applies to degraded lands, albeit less organic matter is added to these soils than in other land use regimes since there is less vegetation on degraded areas varying depending on soil depth.
4.7
Conclusion
Carbon can be stored in soil by converting degraded or barren land into forests or permanent flora. About 180–200 Pg C of the total anthropogenic carbon emissions over the past two centuries has been attributed to the severe loss of SOC to the atmosphere as a result of land conversion from forests to croplands. When forest land is converted to grasslands, more carbon can be stored in them compared to croplands. Temperate grasslands typically retain 331 Mg ha-1 SOC. No matter the land uses, management techniques, climate or types of soil, temperature and moisture are the two most important elements that control SOC dynamics. SOC stocks, fractions and CO2 outflow are all highly associated with temperature and moisture. It is essential to increase SOC sequestration and decrease CO2 emissions to the environment in order to reduce global warming. The sensitive indicators of land use change and management practises in the short term are the active fractions of SOC, such as particulate organic carbon (POC), dissolved organic carbon (DOC) and microbial biomass carbon (MBC), which have a resident time of 1–5 years. They emit more CO2 into the environment at a faster pace as a result of their quick decomposition. These pools have a substantial impact on the processes and functions of the soil, enhancing its health and productivity. Up to a temperate climate, rainfall and soil moisture rise with height and then fall, reaching their lowest levels in upper alpine regions. Although the soil temperature is highest in subtropical climates, it decreases with height. These factors presumably make soil temperature and moisture ideal for temperate forests’ best development, productivity and litter output. The biggest SOC stock buildup in the temperate environment is caused by organo-
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mineral complexes, which are created when the right amount of soil moisture and temperature combine with a high quantity of litter. Although SOC stock is more abundant in forests than in agricultural land uses, agricultural land cannot be spared for forest cover in developing nations like India where the population is large, especially more so in the subtropical zone. In such a situation, land uses like temperate woods and pastures can be thought of as potential carbon sinks. Therefore, in temperate climates, managing pastures and woods may aid in the soil's ability to store atmospheric carbon. By expanding the worldwide soil organic matter stocks, the ‘4 per mille Soils for Food Security and Climate’ initiative, which was unveiled at COP21, hopes to offset around 30% of the greenhouse gas emissions that humans are responsible for on a global scale. This target needs a collaborative approach among farmers, through sustainable forest management, scientists, by the results of innovative researches, and policymakers for their contribution in terms of policies and market regulations. Therefore, the management of forests aimed at improving soil ecosystem services, in contrast to the degradation of soil health and the decline of SOC, can also have positive effects on forest productivity in the eastern Himalayan region of India and worldwide. Farmers, scientists and legislators must work together to achieve this goal through sustainable forest management, creative research findings and their contributions to market and policy rules. As a result, management of forests with focus on enhancing soil ecosystem services, in contrast to the deterioration of soil health and the decline of SOC, can also have a favourable impact on forest productivity worldwide, including India’s eastern Himalayan region.
References Akpa SI, Odeh IO, Bishop TF, Hartemink AE, Amapu IY (2016) Total soil organic carbon and carbon sequestration potential in Nigeria. Geoderma 271:202–215 Babu S, Mohapatra KP, Yadav GS, Lal R, Singh R, Avasthe RK, Das A, Chandra P, Gudade BA, Kumar A (2020) Soil carbon dynamics in diverse organic land use systems in North Eastern Himalayan ecosystem of India. Catena 194:104785 Baker JM, Ochsner TE, Venterea RT, Griffis TJ (2007) Tillage and soil carbon sequestration—what do we really know? Agric Ecosyst Environ 118:1–5. https://doi.org/10.1016/j.agee.2006.05.014 Banger K, Toor G, Biswas S, Sidhu A, Sudhir K (2010) Soil organic carbon fractions after 16 years of applications of fertilizers and organic manure in a Typic Rhodalfs in semi-arid tropics. Nutr Cycl Agroecosyst 86:391–399 Barnett TP, Adam JC, Lettenmaier DP (2005) Potential impacts of a warming climate on water availability in snow dominated regions. Nature 438:303–309 Batjes NH (1996) Total carbon and nitrogen in the soils of the world. Eur J Soil Sci 47:151–163 Batjes NH, Sombroek WG (1997) Possibilities for carbon sequestration in tropical and subtropical soils. Glob Climate Change Biol 3:161–173 Bayer C, Dick DP, Ribeiro GM, Scheuermann KK (2002) Carbon stocks in organic matter fractions as affected by land use and soil management, with emphasis on the no-tillage effect. Ciên Rural 32(3):401–406 Benbi DK, Boparai AK, Brar K (2014) Decomposition of particulate organic matter is more sensitive to temperature than the mineral associated organic matter. Soil Biol Biochem 70:183–192
4
Impact of Land Uses on Soil Organic Carbon Dynamics in the. . .
71
Bhattacharya T, Pal DK, Madal C, Velayuthum M (2000) Organic carbon stock in Indian soil and their geographical distribution. Curr Sci 79:655–660 Bhattacharyya T, Pal DK, Chandran P, Ray SK, Mandal C, Telpande B (2008) Soil carbon storage capacity as a tool to prioritize areas for carbon sequestration. Curr Sci 95(4):482–494 Bolan NS, Adriano DC, de la Luz M (2004) Dynamics and Environmental Significance of Dissolved Organic Matter in Soil. Doctoral dissertation. Regional Institute Limited Bronick CJ, Lal R (2005) Manuring and rotation effects on soil organic carbon concentration for different aggregate size fractions on two soils in northeastern Ohio, USA. Soil Tillage Res 81(2): 239–252 Cambardella CA, Elliot ET (1992) Particulate organic matter changes across a grassland cultivation chronosequence. Soil Sci Soc Am J 56:777–783 Carvalhais N, Forkel M, Khomik M, Bellarby J, Jung M, Migliavacca M, Mu M, Saatchi S, Santoro M, Thurner M, Weber U (2014) Global covariation of carbon turnover times with climate in terrestrial ecosystems. Nature 514(7521):213–217 Certini G, Vestgarden LS, Forte C, Strand LT (2015) Litter decomposition rate and soil organic matter quality in a patchwork heathland of Southern Norway. Soil 1:207–216. https://doi.org/ 10.5194/soil-1-207-2015 Chan KY, Bowman A, Oates A (2001) Oxidizible organic carbon fractions and soil quality changes in an oxic Paleustalf under different pasture leys. Soil Sci 166(1):61–67. https://doi.org/10.1097/ 00010694-200101000-00009 Chisanga K, Bhardwaj DR, Nazir AP, Thakur CL (2018) Biomass production and carbon stock inventory of high-altitude dry temperate land use systems in North Western Himalaya. Ecol Process 7(22):1–13. https://doi.org/10.1186/s13717-018-0134-8 Choudhury BU, Fiyaz AR, Mohapatra KP, Ngachan S (2016) Impact of land uses, agrophysical variables and altitudinal gradient on soil organic carbon concentration of north-eastern Himalayan region of India: soil organic carbon stock of north-eastern Himalayan region. Land Degrad Dev 27:1163–1174. https://doi.org/10.1002/ldr.2338 Christ MJ, David MB (1996) Temperature and moisture effects on the production of dissolved organic carbon in a Spodosol. Soil Biol Biochem 28:1191–1199 Conant RT, Ryan MG, Agren GI et al (2011) Temperature and soil organic matter decomposition rates—synthesis of current knowledge and a way forward. Glob Chang Biol 17:3392–3404 Dar JA, Sundarapandian S (2015) Variation of biomass and carbon pools with forest type in temperate forests of Kashmir Himalaya. Environ Monit Assess 187(2):55. https://doi.org/10. 1007/s10661-015-4299-7 Das A, Biswas DR, Das D, Sharma VK, Das R, Ray P, Ghosh A, Mridha N, Biswas SS (2019a) Assessment of potassium status in soils under different land use systems of Assam. Indian J Agric Sci 89:1077–1081 Das A, Biswas DR, Sharma VK, Ray P (2019b) Soil potassium fractions under two contrasting land use systems of Assam. Indian J Agric Sci 89(8):1340–1343 Devi B, Bhardwaj DR, Panwar P, Pal S, Gupta NK, Thakur CL (2013) Carbon allocation, sequestration and carbon dioxide mitigation under plantation forests of north western Himalaya. Ann For Res 56(1):123–135 Freschet GT, Cornwell WK, Wardle DA, Elumeeva TG, Liu W, Jackson BG, Onipchenko VG, Soudzilovskaia NA, Tao J, Cornelissen JH (2013) Linking litter decomposition of above-and below-ground organs to plant–soil feedbacks worldwide. J Ecol 101(4):943–952 George R, Francis AP, Grima L, Henry AR, Thomas HW (1985) A prospectus for the management of the Long Point ecosystem. Great Lakes Fishery Commission, Ann Arbor, Technical Report No. 43 (WGBR) Ghosh A, Bhattacharyya R, Dwivedi BS, Meena MC, Agarwal BK, Mahapatra P, Shahi DK, Salwani R, Agnihorti R (2016) Temperature sensitivity of soil organic carbon decomposition as affected by long-term fertilization under a soybean based cropping system in a sub-tropical Alfisol. Agric Ecosyst Environ 233:202–213
72
A. Das et al.
Ghosh A, Bhattacharyya R, Dey A, Dwivedi BS, Meena MC, Manna MC, Agnihortri R (2019) Long-term fertilisation impact on temperature sensitivity of aggregate associated soil organic carbon in a sub-tropical inceptisol. Soil Tillage Res 195:104369 Ghosh A, Das A, Das D, Ray P, Bhattacharyya R, Biswas DR, Biswas SS (2020) Contrasting land use systems and soil organic matter quality and temperature sensitivity in North Eastern India. Soil Tillage Res 199:104573 Gosain BG, Negi GCS, Dhyani PP, Bargali SS, Saxena R (2015) Ecosystem services of forests: carbon stock in vegetation and soil components in a watershed of Kumaun Himalaya, India. Int J Ecol Environ Sci 41(3–4):177–188 Goswami S, Verma KS, Kaushal R (2014) Biomass and carbon sequestration in different agroforestry systems of a Western Himalayan watershed. Biol Agric Hortic 30(2):88–96. https://doi. org/10.1080/01448765.2013.855990 Gregorich EG, Rochette P, VandenBygaart AJ, Angers DA (2005) Greenhouse gas contributions of agricultural soils and potential mitigation practices in Eastern Canada. Soil Tillage Res 83(1): 53–72 Gupta RK, Rao DLN (1994) Potential of wastelands for sequestering carbon by reforestation. Curr Sci 66:378–380 Hanson PJ, Edwards NT, Garten CT, Andrews JA (2000) Separating root and soil microbial contributions to soil respiration: a review of methods and observations. Biogeochemistry 48 (1):115–146 Hoorman JJ, Islam R (2010) Understanding soil microbes and nutrient recycling. Fact sheet SAG-16-10, The Ohio State University, Columbus, USA Jastrow JD, Miller RM, Lussenhop J (1998) Contributions of interacting biological mechanisms to soil aggregate stabilization in restored prairie. Soil Biol Biochem 30:905–916 Jobbagy EG, Jackson RB (2000) The vertical distribution of soil organic carbon and its relation to climate and vegetation. Ecol Appl 10:423–436 John B, Yamashita T, Ludwig B, Flessa H (2005) Storage of organic carbon in aggregate and density fractions of silty soils under different types of land use. Geoderma 128(1-2):63–79 Kalambukattu JG, Singh R, Patra AK, Kumar KA (2013) Soil carbon pools and carbon management index under different land use systems in the central Himalaya region. Acta Agric Sci Soil Plant Sci 63:200–205 Karhu K, Auffret MD, Dungait JAJ, Hopkins et al (2014) Temperature sensitivity of soil respiration rates enhanced by microbial community response. Nature 513:81–84 Kettler TA, Doran JW, Gilbert TL (2001) Simplified method for soil particle-size determination to accompany soil-quality analyses. Soil Sci Soc Am J 65:849–852 Kirschbaum MUF (2000) Will changes in soil organic carbon act as a positive or negative feedback on global warming? Biogeochemistry 48:21–51 Kooch Y, Moghimian N, Alberti G (2020) C and N cycle under beech and hornbeam tree species in the Iranian old-growth forests. Catena. https://doi.org/10.1016/j.catena.2019.104406 Krishan R, Tiwari OP, Rana YS, Mishra AK, Sharma CM (2017) Changes in levels of soil carbon and forest floor carbon stocks in the different temperate forests of Garhwal Himalaya. J Cur Res Rev 9(7):5 Krull ES, Baldock JA, Skjemstad JO (2003) Importance of mechanisms and processes of the stabilisation of soil organic matter for modelling carbon turnover. Funct Plant Biol 30(2):207– 222 Lal R (2004a) Soil carbon sequestration impacts on global climate change and food security. Science 304:1623–1627 Lal R (2004b) Soil carbon sequestration in India. Clim Chang 65:277–296 Lal R (2005) Forest soils and carbon sequestration. For Ecol Manag 220:242–258. https://doi.org/ 10.1016/j.foreco.2005.08.015 Lal R (2018) Digging deeper: a holistic perspective of factors affecting soil organic carbon sequestration in agroecosystems. Glob Change Boil 24(8):3285–3301
4
Impact of Land Uses on Soil Organic Carbon Dynamics in the. . .
73
Lamparter A, Bachmann J, Goebel M-O, Woche S (2009) Carbon mineralization in soil: impact of wetting–drying, aggregation and water repellency. Geoderma 150:324–333 Li G, Zhang C, Zhang H (2010) Soil inorganic carbon pool changed in long-term fertilization experiments in north China plain. In: Presented at the 19th World Congress of Soil Science, Soil Solutions for a Changing World, Brisbane, Australia, pp 220–223 Li S, Su J, Liu W, Lang X, Huang X, Jia C, Zhang Z, Tong Q (2015) Changes in biomass carbon and soil organic carbon stocks following the conversion from a secondary coniferous forest to a pine plantation. PLoS One 10:e0135946. https://doi.org/10.1371/journal.pone.0135946 Luo Y, White LW, Canadell JG, DeLucia EH, Ellsworth DS, Finzi A, Lichter J, Schlesinger WH (2003) Sustainability of terrestrial carbon sequestration: a case study in Duke Forest with inversion approach. Glob Biogeochem Cycles 17(1):1021 Mandal B, Majumder B, Adhya TK, Bandopadhyay PK, Gangopadhyay A, Sarkar D, Kundu MC, Gupta S, Choudhury GC, Hazra GC, Kundu S, Samantaray RN, Misra AK (2008) Potential of double-cropped rice ecology to conserve organic carbon under subtropical climate. Glob Chang Biol 14:1–13. https://doi.org/10.1111/j.1365-2486.2008.01627.x Miller R (2007) Melting fast-glaciers in the tropics. Down to Earth, March 31, 44 Mishra G, Francaviglia R (2021) Land uses, altitude and texture effects on soil parameters. A comparative study in two districts of Nagaland, Northeast India. Agriculture 11(2):171 Mishra G, Debnath S, Rawat D (2017) Managing phosphorus in terrestrial ecosystem: a review. Eur J Biol Res 7(3):255–270 Mishra G, Sarkar A, Giri K, Nath AJ, Lal R, Francaviglia R (2021) Changes in soil carbon stocks under plantation systems and natural forests in Northeast India. Ecol Model 446:109500 Nabuurs GJ, Mohren F, Dolman H (2000) Monitoring and reporting carbon stock and fluxes in Dutch forests. Biotechnol Agron Soc Environ 4(4):308–310 Nath AJ, Brahma B, Sileshi GW, Das AK (2018) Impact of land use changes on the storage of soil organic carbon in active and recalcitrant pools in a humid tropical region of India. Sci Total Environ 624:908–917 National Mission on Himalayan Studies (2023) The Indian Himalayan Region. https://nmhs.org.in/ IHR_The_Target_Area.php Negi JDS, Manhas RK, Chauhan PS (2003) Carbon allocation in different components of some tree species of India: a new approach for carbon estimation. Curr Sci 85(11):1528–1531 Nimmo J (2004) Porosity and pore size distribution. In: Encyclopedia of soils in the environment, vol 3. Elsevier, London, pp 295–303 Oades JM (1988) The retention of organic matter in soils. Biogeochemistry 5:35–70 Oerlemans A (2005) Extracting activated signals from 169 glacial records. Science 308:675–677 Papiernik SK, Lindstrom MJ, Schumacher TE, Schumacher JA, Malo DD, Lobb DA (2007) Characterization of soil profiles in a landscape affected by long-term tillage. Soil Tillage Res 93:335–345 Paul EA, Paustian K, Elliott ET, Cole CV (1997) Soil organic matter in temperate agro ecosystems. CRC Press, New York Paul EA, Collins HP, Leavitt SW (2001) Dynamics of resistant soil carbon of Midwestern agricultural soils measured by naturally occurring 14C abundance. Geoderma 104:239–256. https:// doi.org/10.1016/S0016-7061(01)00083-0 Poeplau C, Don A (2013) Sensitivity of soil organic carbon stocks and fractions to different landuse changes across Europe. Geoderma 192:189–201 Post WM, Kwon KC (2000) Soil carbon sequestration and land-use change: processes and potential. Glob Change 6:317–327 Rajput BS, Bhardwaj DR, Pala NA (2016) Factors influencing biomass and carbon storage potential of different land use systems along an elevational gradient in temperate northwestern Himalaya. Agrofor Syst 91:479–486. https://doi.org/10.1007/s10457-016-9948-5 Ram J, Kumar A, Bhatt A (2004) Plant diversity in six forest types of Uttaranchal, Central Himalaya, India. Curr Sci 86:975–978
74
A. Das et al.
Ren W, Tian HQ, Tao B, Huang Y, Pan SF (2012) China’s crop productivity and soil carbon storage as influenced by multifactor global change. Glob Chang Biol 18:2945–2957 Ryan MG, Law BE (2005) Interpreting, measuring, and modeling soil respiration. Biogeochemistry 73:3–27 Sahoo UK, Singh SL, Gogoi A, Kenye A, Sahoo SS (2019) Active and passive soil organic carbon pools as affected by different land use types in Mizoram, Northeast India. PLoS ONE 14(7): e0219969 Sarkhot DV, Comerford N, Jokela EJ, Reeves JB, Harris WG (2007) Aggregation and aggregate carbon in a forested southeastern coastal plain spodosol. Soil Sci Soc Am J 71:1779–1787 Schuur EA, Chadwick OA, Matson PA (2001) Carbon cycling and soil carbon storage in mesic to wet Hawaiian montane forests. Ecology 82(11):3182–3196 Senthilkumar S, Kravchenko AN, Robertson GP (2009) Topography influences management system effects on total soil carbon and nitrogen. Soil Sci Soc Am J 73:2059–2067 Setia R, Gottschalk P, Smith P, Marschner P, Baldock J, Setia D, Smith J (2013) Soil salinity decreased global soil organic carbon stocks. Sci Total Environ 465:267–272 Sharma V, Hussain S, Sharma KR, Arya VM (2014) Labile carbon pools and soil organic carbon stocks in the foothill Himalayas under different land use systems. Geoderma 232:81–87. https:// doi.org/10.1016/j.geoderma.2014.04.039 Singh RL (1998) UP-Himalayas. In: Kayastha SL, Singh KN, Sigh KN (eds) India—a regional geography. National Geographical Society of India, Varanasi Singh H, Pathak P, Kumar M, Raghubanshi AS (2011a) Carbon sequestration potential of IndoGangetic agroecosystem soils. Trop Ecol 52:223–228 Singh SK, Pandey CB, Sidhu GS, Sarkar D, Sagar R (2011b) Concentration and stock of carbon in the soils affected by land uses and climates in the western Himalaya, India. Catena 87(1):78–89 Singh R, Bhardwaj DR, Pala NA, Singh RB (2019) Biomass production and carbon stock potential of natural vegetation, agroforestry and cultivated land use systems along altitudinal gradient in north western Himalaya. Range Manage Agrofor 40(1):94–103 Six J, Conant R, Paul EA, Paustian K (2002) Stabilization mechanisms of soil organic matter: implications for c-saturation of soils. Plant Soil 241:155–176 Six J, Frey SD, Thiet RK, Batten KM (2006) Bacterial and fungal contributions to carbon sequestration in agroecosystems. Soil Sci Soc Am J 70:555–569 Skjemstad JO, Janik LJ, Head MJ, McClure SG (1993) High energy ultraviolet photo-oxidation: a novel technique for studying physically protected organic matter in clay- and silt-sized aggregates. J Soil Sci 44:485–499 Smith P (2007) Land use change and soil organic carbon dynamics. Nutr Cycl Agroecosyst 81:169– 178. https://doi.org/10.1007/s10705-007-9138-y Spaccini R, Piccolo A, Conte P, Haberhauer G, Gerzabek MH (2002) Increased soil organic carbon sequestration through hydrophobic protection by humic substances. Soil Biol Biochem 34(12): 1839–1851 Spohn M, Klaus K, Wanek W, Richter A (2016) Microbial carbon use efficiency and biomass turnover times depending on soil depth-implications for carbon cycling. Soil Biol Biochem 96: 74–81. https://doi.org/10.1016/j.soilbio.2016.01.016 Stevenson FJ (1994) Humus Chemistry: Genesis. John Wiley & Sons, Composition, Reactions Straaten OV, Corre MD, Wolf K, Tchienkoua M, Cuellar E, Matthhews RB, Veldkamp E (2015) Conversion of lowland tropical forests to tree cash crop plantations loses up to one-half of stored soil organic carbon. PNAS 112:9956–9960. https://doi.org/10.1073/pnas.1504628112 Strickland MS, Rousk J (2010) Considering fungal: bacterial dominance in soils—methods, controls, and ecosystem implications. Soil Biol Biochem 42:1385–1395 Tang J, Riley WJ (2015) Weaker soil carbon-climate feedbacks resulting from microbial and abiotic interactions. Nat Clim Chang 5:56–60 Tian H, Chen G, Zhang C, Melillo JM, Hall CA (2010) Pattern and variation of C: N: P ratios in China’s soils: a synthesis of observational data. Biogeochemistry 98:139–151
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Impact of Land Uses on Soil Organic Carbon Dynamics in the. . .
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Tisdall JM, Oades J (1982) Organic matter and water-stable aggregates in soils. J Soil Sci 33(2): 141–163 Wang Q, Xiao F, He T, Wang S (2013) Responses of labile soil organic carbon and enzyme activity in mineral soils to forest conversion in the subtropics. Ann For Sci 70:579–587. https://doi.org/ 10.1007/s13595-013-0294-8 Wani AA, Joshi PK, Singh O (2014) Estimating soil carbon storage and mitigation under temperate coniferous forests in the southern region of Kashmir Himalayas. Mitig Adapt Strateg Glob Chang 19(18):1179–1194. https://doi.org/10.1007/s11027-013-9466-y Wilson BR, Growns I, Lemon J (2008) Land-use effects on soil properties on the north-western slopes of New South Wales: implications for soil condition assessment. Soil Res 46(4):359–367 Wissing L, Kölbl A, Cao ZH, Kögel-Knabner I (2010) Development of bulk density, total C distribution and OC saturation in fine mineral fractions during paddy soil evolution. In: EGU General Assembly Conference Abstracts, p 3470 Xu W, Yuan W, Dong W, Xia J, Liu D, Chen Y (2013) A meta-analysis of the response of soil moisture to experimental warming. Environ Res Lett 8:044027 Yadav RP, Gupta B, Bhutia PL, Bisht JK (2016) Socioeconomics and sources of livelihood security in Central Himalaya, India a case study. Int J Sust Dev World 23(6):1–9. https://doi.org/10. 1080/13504509.2016.1239233 Yadav RP, Bisht JK, Bhatt JC (2017) Biomass, carbon stock under different production systems in the mid hills of Indian Himalaya. Trop Ecol 58(1):15–21 Yadav GS, Das A, Lal R, Babu S, Meena RS, Saha P, Singh R, Datta M (2018) Energy budget and carbon footprint in a no-till and mulch based rice–mustard cropping system. J Clean Prod 191: 144–157 Yigini Y, Panagos P (2016) Assessment of soil organic carbon stocks under future climate and land cover changes in Europe. Sci Total Environ 557:838–850 Zimmermann M, Leifeld J, Schmidt MWI, Smith P, Fuhrer J (2007) Measured soil organic matter fractions can be related to pools in the RothC model. Eur J Soil Sci 58(3):658–667
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Terrestrial Carbon Stock and Sink Potential of Indian Himalayan Forest Ecosystem: A Tool for Combating Climate Change Anil Kumar, Pawan Kumar, Vimal Chandra Srivastava, Anand Giri, Deepak Pant, and Raj Kumar Verma
Abstract
The terrestrial carbon in the forest system endures in multitude form such as organic and inorganic carbon. The carbon pools in the forest ecosystem exist as the below-ground, above-ground biomass and dead organic matter and play a critical function in maintaining carbon cycle and carbon budget of the terrestrial sphere. The Indian Himalayan Forest Ecosystem (IHFE) stores a significant amount of carbon, which is being affected day by day as a result of mismanaged overexploitation. Therefore, the biomass accumulation potential and carbon sequestration capacity of the forest ecosystem are reducing, and it is a key concern as it may contribute the global warming. Consequently, the current
A. Kumar Forest Ecology and Climate Change Division, Himalayan Forest Research Institute, Shimla, India Forest Research Institute Deemed to be University, Dehradun, Uttarakhand, India P. Kumar Regional Research Centre, Chandsoli, Maharana Pratap Horticultural University, Karnal, Haryana, India V. C. Srivastava Department of Chemical Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India A. Giri (✉) School of Civil and Environmental Engineering, Indian Institute of Technology Mandi, Mandi, HP, India D. Pant Department of Environmental Sciences, Central University of Himachal Pradesh, Dharamshala, India R. K. Verma Forest Ecology and Climate Change Division, Himalayan Forest Research Institute, Shimla, India # The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Mishra et al. (eds.), Soil Carbon Dynamics in Indian Himalayan Region, https://doi.org/10.1007/978-981-99-3303-7_5
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breakdown highlights the fragmented information on carbon sequestration potential in the Indian Himalayan Region (IHR). Previous research has also confirmed a significant contribution of terrestrial carbon pools and potential carbon sinks in the IHR. Nonetheless, this deconstruction also has covered the ecological outlook for conservation and guidelines for estimating the IHR’s carbon stock potential in forest-based mitigation movements in the Himalayan forest ecosystem. Keywords
Carbon stock · Carbon sequestration · IHR · Biomass · Forest ecosystem
5.1
Introduction
The Indian Himalayan mountain ecosystem (IHME) is the lifeline for the people of different Asian countries, such as India, China, Bhutan, Nepal, Pakistan and Afghanistan, and provides a plethora of ecosystem services (Xu et al. 2019; Kumar et al. 2021a, b). The Indian Himalayan region (IHR) is covering 2400 km from west to east (Kumar et al. 2021a, b; Meena et al. 2021) and is one of the noteworthy carbon reservoirs and sensitive provinces throughout the forest ecosystem (Ahirwal et al. 2021). The forest ecosystem at the Indian Himalaya covers 41.5% and is a most significant terrestrial carbon sink component in the mountain province (Upadhyay et al. 2005; Devi et al. 2012; Sati 2014; Kumar et al. 2021a, b). IHR has encountered across 13 states constituting 5.37 lakh km2 area covering 16.2% province of the country (Tripathi et al. 2022). However, 41.5% of areas of the IHR comprise forest cover. The undulate landscapes and various geographical conditions in the provinces adorn peculiar habitats like tropical, subtropical, temperate, subalpine and alpine in different forest types, consequently assembling favourable weather conditions for most dynamic species (Strachey 1853; Singh et al. 2020). The carbon is the consequential element for the sustenance of life on the blue planet and tends to circulate in the form of the carbon flux on the earth’s ecosystem via exchangeable pathways from the atmosphere to the hydrosphere and terrestrial ecosystem (Fig. 5.1) (Hilton and West 2020; Giri et al. 2020). It is an essential nonmetallic and tetravalent element of the earth’s crust and maintains a biogeochemical pathway with multiple interrelated exchangeable forms (Ge 2000; Foley and Smye 2018; Singhal et al. 2022). The carbon travels in the cyclic form and interacts with each ecological hierarchy levels to create an inhabitable ecosystem for the existence of life (Dasgupta and Grewal 2019; Hilton and West 2020). Indeed in terrestrial ecosystem, the carbon storage has been compartmentalized into five major reservoir pools such as the above-ground biomass (AGB), “below-ground biomass (BGB), dead organic matter (DOM) which comprises deadwood, litter and soil organic matter (SOM) (Figs. 5.2 and 5.3). These significant reservoir pools have a considerable amount of organic carbon in the IHFE (Penman et al. 2003; Petrokofsky et al. 2012; Gogoi et al. 2022). The IHFE plays a critical role in carbon
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Fig. 5.1 Carbon flux at various spheres on the earth system
Fig. 5.2 Schematic diagram of different carbon pool in forest ecosystem
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Fig. 5.3 Carbon stock allocation in the states of Indian Himalayan region (ton ha-1)
regulations and the mitigations strategy (Ahirwal et al. 2021). The plant uses CO2 in respiration during photosynthesis and converts it to O2 thereby help to sustain it in the atmosphere (Dusenge et al. 2019). For instance, through photosynthesis, the plants remove CO2 from the atmosphere and store it in organic compounds (Zeng 2008; Wang et al. 2022). After the end and decay of the plants, the carbon in the plant gets stored and mixed with the floor soil in the form of organic carbon (Cotrufo et al. 2015). Earlier decades witnessed that the human activities are responsible for shrinking forest cover at the Indian Himalayan hot spot (Ahmad et al. 2022) thereby causing forest vulnerability, mainly from the illegal harvesting of endemic species, cutting trees for timber purpose, grazing, building road in a fragile region, hydropower project, mining of minerals sources, increasing the urban sprawl in term of a commercial and residential building in the Himalayan states, etc. (Barnard et al. 2001; Kala 2014; Kumar and Katoch 2016; Singh et al. 2020). The forest perturbations in the IHFE, the carbon flux between the carbon reservoir pool and the exchangeable natural carbon cycle have been susceptible in its natural way (Kumari et al. 2022). Consequently, the accumulation of the carbon species (CO, CO2, CH4, and N2O) in the earth’s atmosphere have caused miscellaneous detrimental impacts on the earth’s biogeochemical cycles (Montzka et al. 2011; Mehmood et al. 2020). The carbon enters in the atmosphere mainly through biomass combustion, burning of petrochemicals, transportation, inevitable industrial process, etc. (Martens et al. 2017). The concentrations of major reactive carbon regents (CO, CO2, and CH4) have increased in the atmosphere from some decades due to anthropogenic emissions (Montzka et al. 2011; Giri and Pant 2018). The forest ecosystem alteration in protected areas leads to the disturbance of the carbon flux (Rajeev and Hukum 2020). The consistently altering of forest ecosystem in the IHR requires adequate strategies and approaches for strengthening the forest management procedures and carbon sequestration potential (Negi et al. 2022). This overview
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endeavours to address the significance of the IHFE as a potential carbon sink in terms of capture and storage for combating climate crises in the continent.
5.2
Climate Crisis in the Indian Himalayan Forest Ecosystem
The burgeoning potency of greenhouse gases in the air is a profound concern due to their long-term endurance timescale (Brander and Davis 2012; Goswami et al. 2022). Their concentration has passed to an average extent throughout the globe, subsequently, influencing the natural gaseous cycle. Earlier analyses have figured out the fluctuation in the weather patterns of the entire regions over the decades (Shrestha et al. 2012; Meena et al. 2021). Moreover, various studies inferred that the weather patterns of the IHR regions have also been fluctuated in the last decades (Kotlia et al. 2012). The potency of trace gases in the ambient air has increased, and the mean temperature of the IHR has been accelerated between 0.15 and 0.60 °C in earlier decades (Meena et al. 2021). The temperature of the cold desert has increased, and rain and snowfall have decreased; consequently, the glaciers are shrinking very rapidly, and permafrost has consistently thawed (Shrestha and Aryal 2011; Kanwar and Kuniyal 2022). The observation by the regional community accepted that precipitation patterns, water crisis, low agricultural productivity and a decline in forest resources in the earlier three decades have increased (Vedwan and Rhoades 2001; Negi and Joshi 2002). The average temperature of the Asian landmass, including the Indian Himalayan region, is expected to increase further 2.1 to 2.6 °C by 2050 and 3.3 to 3.8 °C by 2080 if a reasonable effort is not taken thoughtfully (Verma 2021). The carbon content in the Indian Himalayan region differs considerably due to undulated topographic attributes as well as the heterogeneities of the habitats (Sharma et al. 2011; Ahirwal et al. 2021). The forest degradation practices directly fluctuate the frequency of the temperature and precipitation (Sinha and Swaminathan 1991; Kumar and Chopra 2009) and further lays impact on the most sensitive and highly specialized plant species of the IHR (Telwala et al. 2013; Kaur et al. 2022). It’s a known fact that environment gradient plays a crucial role in seed germinations, which may experience vulnerability threats due to change in climate variables (Singh et al. 2013). The local people are also experiencing various consequences of climate change regarding vegetation loss and herbal and water resources scarcity (Vedwan and Rhoades 2001; Negi and Joshi 2002).
5.3
Carbon Stock Potential in IHR
The IHFE is the critical component of the carbon sequestration, which can be intensified in a convenient sink. Various scholars have endeavoured to extensively facilitate the carbon stock opportunity of the IHFE at the distinct regions (Ahirwal et al. 2021; Rawat et al. 2021; Gogoi et al. 2022; Mir et al. 2022). The estimation of carbon budget contribution of IHFE has been quite formidable due to topographic
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constraints (Ahirwal et al. 2021). The organic carbon (OC) and tree carbon density are found to be significantly higher on the northern side as compared to the southern side in the temperate zone of the IHFE (Sharma et al. 2011). The natural forest ecosystems have the most excellent carbon biomass stock (138.5 ± 87.3 C Mg ha1 ), simultaneously, the farmstead forests exhibited the highest soil organic carbon stock (168.8 ± 74.4 C Mg ha-1) in the IHFE (Ahirwal et al. 2021). Intrinsically, the forest carbon biomass potential declines with elevation and encloses unimodal mosaic with height (Liu et al. 2014; Malhi et al. 2017). Sharma et al. (2011) in their study examined the carbon stock allocation in different temperate zone and aspects of the IHFE and demonstrated the tree carbon density (TCD) 291.6 C Mg ha-1 in the moist Cedrus deodara forest ecosystem (NE) and 77.3 C Mg ha-1 in the Quercus oblongata forest ecosystem (SE). Despite this, soil organic carbon was observed 177.5 C Mg ha-1 in the moist Cedrus deodara forest ecosystem (SE) and 40.3 C Mg ha-1 in the Pinus roxburghii forest ecosystem (SW). The total carbon density (SOC + TCD) varied between 118.1 C and 469.1 C Mg ha-1 in Pinus roxburghii forest ecosystem (SW) and moist Cedrus deodara forest ecosystem (NE), respectively. Earlier studies have also highlighted that tree mortality and pest disease in the IHR have increased, and therefore this region is susceptible to various pathological aspects (Vannini et al. 1995; Sangay et al. 2012; Mishra et al. 2015; Sharma 2022; Wani and Qadri 2022). Below, Fig. 5.3 Depicts the potential carbon stock (ton ha-1) in the entire IHFE, and it reveals that Sikkim has the highest carbon stock per hectare. Mizoram, on the other hand, has demonstrated a minimum per hectare carbon stock (FSI 2019). In the recent decade, the IHFE insect pest diseases have also increased. It might be due to instabilities in the environmental gradients of the alpine ecosystem, which affect the Forest health and carbon sequestration potential of IHFE. Moreover, the increasing temperature also affected the plant health in terms of the favourable condition for insect pest disease and overall health of the forest, which consequently led to the loss of vegetation and carbon sequestration potential of the IHR. The indication of increasing temperature in IHR has been observed for five decades; for instance, at various parts of the IHR, agricultural farming has intensified towards apple orchard growth, which indicates temperature accelerating (Singh et al. 2016). However, the links between that acceleration and the mean temperature as well as the deceleration of the precipitation frequency are still uncertain (Wang et al. 2018). Conceptually, the climate variables are the crucial part for plant development including presence of the floral and faunal diversity, and amongst the temperature is the significant environmental factor for seed production, flowering and fruiting development (Dalling et al. 2022). Therefore, the fluctuations in the climate variables may directly influence the soil microbes, essential nutrients and SOC (Luo et al. 2017; Dalling et al. 2022).
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Estimation of Carbon Stock in the IHFE
The carbon stock estimation in the IHFE is challenging due to the physiological attributes of the mountain ecosystem (Wani et al. 2014); however, various scholars have also tried to compute the forest carbon stock at various scales in different altitudinal gradients. The earlier studies have used sample plots and transect methods for computing the carbon stock across the IHFE (Yam et al. 2021; Ahirwal et al. 2021; Gogoi et al. 2022; Haq et al. 2022). Principally, the harvesting, non-harvesting (Gibbs et al. 2007; Joshi et al. 2021) and geospatial tactics (Wani et al. 2015; Dabi et al. 2021; Ahirwal et al. 2021; Bordoloi et al. 2022) have also been employed to compute the AGB and BGB to some extent (Wani et al. 2012). Although, in the non-harvesting method, the DBH and the height of all individual trees in the sample plots of the representative population have been calculated through volume or regression equations (FSI 1996), and in multiple deconstructions, harvesting methods have also been considered (Gairola et al. 2011; Dimri et al. 2018; Vikrant et al. 2022: Gogoi et al. 2022). In addition, branches, woody litter and forest floor samples have been collected from concentric plots (1 × 1 m, 3 × 3 m and 5 × 5 m) for carbon content analysis (Gosain et al. 2015; Krishan et al. 2017). The soil and bulk density samples in earlier studies were randomly collected up to different depths (0–15, 15–30, 30–60 cm, etc.) from the sample site (Yam et al. 2021). Earlier studies have revealed that for computing carbon stocks and carbon sequestration potential in the IHR mainly IPCC-GPG approaches were employed (Penman et al. 2003).
5.5
Principal Drivers of Carbon Loss in the IHR’s
The IHFE these days is highly susceptible because the flux between the reservoir pool and the exchangeable pool of the carbon cycle has been fundamentally altered by human-induced exercises. Increased population, illegal logging, highway construction and hydroelectric project are taking place in the IHR (Chandy et al. 2012: Kumar and Katoch 2016). Furthermore, the pasture, exploitation of RET species (Kumar et al. 2021a, b) and forest degradation practice at the provinces of IHR are the most sensitive issues nowadays and have tended to result in vegetation loss (Singh et al. 2016). The IHFE is one of the significant terrestrial carbon sinks (Gogoi et al. 2022). In addition, plants absorb CO2 during photosynthesis and release O2, which enables them to stabilize atmospheric CO2 (Whitmarsh and Govindjee 1999). Carbon is preserved in plants and soil as organic material (Gougoulias et al. 2014). Nowadays, scaling up human perturbations, such as deforestation, has exponentially degraded the topsoil humus (Greipsson 2011) and has altered the habitat of highly specialized species. The highway and hydropower project construction in the Himalayan forest zone might cause landslides and soil erosion amongst forest and non-forest land (Chandy et al. 2012; Kumar and Katoch 2016). Moreover, the conversion of forest land to agricultural uses has an impact on the potential carbon stock (Sharma et al. 2014).
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According to Gogoi et al. 2022, Jhum land stored 289 MgCO2 ha-1, whereas tropical evergreen forest stored 373 Mg C ha-1 (= 1366 MgCO2 ha-1). The findings demonstrate that shifting farming (Jhum) has even less carbon stock potential than the natural evergreen forest ecosystem, even though forest fires remove the stored carbon in the wood, therefore expanding the concentration of carbon in the ambient air (Sannigrahi et al. 2020). It is an opportune span to compensate for forest manipulation activities before it is too late to meet the Paris Agreement goal of restricting global warming to less than 2 °C above pre-industrial levels.
5.6
Future Carbon Management Technology
Human activities must be renounced to maintain the concentration of carbon dioxide and the earth’s heat budget cycle. As a rough estimate, 0.96 billion tons of CO2 annually is removed from the atmosphere (Naddaf 2023). The trend of abolishment will consistently increase at the pace of time (https://www.nature.com/articles/d41 586-023-00180-4). Hence, scaling-up carbon dioxide removal technology ought to be invented to capture CO2 from the atmosphere (Giri et al. 2020) and keep it on land, sea, geological formations or products—for instance, reforestation, biochar and
Carbon Component in the Forest ecosystem
Above -ground Biomass
Soil organic matter
Below-ground Biomass
Deadwood
Duff and root decomposition Wood product in service Floor Off site land fill Stem wood Stem bark Snag Foliage Branches Large woody debris Litter biomass
Fig. 5.4 Carbon allocation in various forms at the forest system
Dead organic matter
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bioenergy with carbon capture and storage (BECCS) (Sharma et al. 2021; Goswami et al. 2021; Smith et al. 2023) (Fig. 5.4). An initial executive international contemporary report titled “The State of Carbon Dioxide Removal” (https://www. stateofcdr.org), demonstrated that carbon dioxide removal (CDR) technology removes more than 2 billion tons of carbon dioxide from the earth’s atmosphere annually, albeit this is not adequate to meet the Paris Agreement Goals (PAG) (Smith et al. 2023; Naddaf 2023). There is an obligation to constrain forest deception and devise a robust configuration for forest conservation in the IHR. At COP 26, India set preferred target to ameliorate the consequences of climate change in order to meet concern targets by 2030, such as expanding nonfossil energy output by 500GW, limiting nonrenewable energy by 50%, minimizing carbon emissions by 1 billion and reducing carbon emissions intensity by 45% (https://pib.gov.in/ PressReleasePage.aspx?PRID=1795071Z). While in COP 27, India has a commitment and approaches towards reaching net zero by 2070. Therefore afforestation, to an extensive extent, preservation of forest land and endemic species in the province, will strengthen to meet the PAG of determining global warming to less than 2 °C above pre-industrial temperature (MoEFCC 2022). However, to encounter the climate goals, the government must also increase investment in carbon dioxide removal technologies (Naddaf 2023). Furthermore, more work and documentation are required to fill gaps and strengthen long-term monitoring networks in the various zones of the IHFE in order to fully comprehend the consequences of human manipulation in the vegetation patterns and carbon stock potential. In addition, long-term monitoring sites are consistent with global guidelines, such as the Global Observation Research Initiative in Alpine Environments GLORIA (Pauli et al. 2015), such research will focus on the unknown implications of climate change on vegetation in the IHFE (Fig. 5.5).
5.7
Challenges for Future Investigation
A uniform composition throughout this contemplation has been the low enthusiasm in the foreseen responses of floral diversity by the pace of climate change in the Indian Himalayan forest ecosystem due to a lack of empirical demonstrations. Understanding how consistently changing climate will impact forest carbon stock and forest functional traits is one of the most challenging phenomenon in modelling the absolute carbon flux of the IHR. IHFE has varied topographic features that appeal to considerable attention from more studies in the progressive specialized convention. Due to topographic features and cost constraints, most carbon studies in the Indian Himalayan forests ecosystem have been performed on small scales and at approachable places. However, more extensive provinces like cold desert regions, temperate forests, and alpine pastures are still unexplored. Long-term monitoring sites are compatible with global protocol, i.e. Global Observation Research Initiative in Alpine Environments GLORIA, and are well suited to experimental work on alpine vegetation to understand functional traits, a biotic and biotic attraction and forest vulnerability by the pace of climate change (Pauli et al. 2015). More
Fig. 5.5 Carbon dioxide capture and storage technique
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information is also needed about the carbon stock potential of individual and dominant tree species in the IHFE at extensive extent. The principal rationale of the research also needs to be considered, like most tree species and province in the IHR which play a crucial role in carbon stock potential and the predominant principal factor accountable for influencing the soil organic carbon or crucial soil macro- and micronutrient capacities influenced by particular human manipulation due to diverse physical attributes; hence there need to be appropriate strategies at regional scales to figure out a suitable carbon sink in the IHFE. Secondly, there is also the need to consider function traits in IHFE. How will these functional traits appropriately be considered, and how much do climate changes influence them? Various other studies on global warming on the earth system have successfully provided insight into the increasing greenhouse gases in the atmosphere, indicating climate change due to increasing human-induced activities. However, in the case of floral diversity, predicting how projected future climates, including changes in climate parameters, will alter the carbon stock potential, and recruitment patterns of Himalayan vegetation in terms of succession patterns are not a straightforward task. Such studies need adequate time to conclude possible climate-related changes in rates of forest traits and productivity by the pace of climate which are still unknown, despite GLORIA protocol long-term monitoring sites (Pauli et al. 2015) to represent vulnerable conditions in the cold desert region and the REDD+ Strategy (Angelsen 2009), for forest carbon sequestration in various forest type in the IHR, which will have had mark a new era for strengthening the Indian Himalayan ecological research in term forest diversity and function using Global Forest Carbon database (ForC) (Anderson-Teixeira et al. 2016, 2018) by the pace of climate change.
References Ahirwal J, Nath A, Brahma B, Deb S, Sahoo UK, Nath AJ (2021) Patterns and driving factors of biomass carbon and soil organic carbon stock in the Indian Himalayan region. Sci Total Environ 770:145292 Ahmad M, Batish DR, Singh HP (2022) Biodiversity status, issues, and challenges: trees and shrubs. In: Biodiversity in India: status, issues and challenges. Springer, Singapore, pp 45–59 Anderson-Teixeira KJ, Wang MM, McGarvey JC, LeBauer DS (2016) Carbon dynamics of mature and regrowth tropical forests derived from a pantropical database (T rop F or C-db). Glob Chang Biol 22(5):1690–1709 Anderson-Teixeira KJ, Wang MM, McGarvey JC, Herrmann V, Tepley AJ, Bond-Lamberty B, LeBauer DS (2018) ForC: a global database of forest carbon stocks and fluxes. Ecology 99(6): 1507 Angelsen A (ed) (2009) Realising REDD+: national strategy and policy options. CIFOR, Bogor Barnard PL, Owen LA, Sharma MC, Finkel RC (2001) Natural and human-induced landsliding in the Garhwal Himalaya of northern India. Geomorphology 40(1-2):21–35 Bordoloi R, Das B, Tripathi OP, Sahoo UK, Nath AJ, Deb S, Tajo L (2022) Satellite based integrated approaches to modelling spatial carbon stock and carbon sequestration potential of different land uses of Northeast India. Environ Sustainability Indicators 13:100166 Brander M, Davis G (2012) Greenhouse gases, CO2, CO2e, and carbon: what do all these terms mean. Econometrica, White Papers
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Chandy T, Keenan RJ, Petheram RJ, Shepherd P (2012) Impacts of hydropower development on rural livelihood sustainability in Sikkim, India: community perceptions. Mt Res Dev 32(2): 117–125 Cotrufo MF, Soong JL, Horton AJ, Campbell EE, Haddix ML, Wall DH, Parton WJ (2015) Formation of soil organic matter via biochemical and physical pathways of litter mass loss. Nat Geosci 8(10):776–779 Dabi H, Bordoloi R, Das B, Paul A, Tripathi OP, Mishra BP (2021) Biomass, carbon stock and soil physicochemical properties in plantation of East Siang district, Arunachal Pradesh, India. Environ Challenges 4:100191 Dalling J, Cernusak LA, Chen YY, Slot M, Sarmiento C, Zalamea PC (2022) Effect of climate change on regeneration of plants from seeds in tropical wet forests. In: Plant regeneration from seeds. Academic Press, Cambridge, pp 157–168 Dasgupta R, Grewal DS (2019) Origin and early differentiation of carbon and associated lifeessential volatile elements on earth. Deep Carbon 5:4–39 Devi B, Bhardwaj DR, Panwar P, Pal S, Gupta NK, Thakur CL (2012) Carbon allocation, sequestration and carbon dioxide mitigation under plantation forests of north western Himalaya, India. Ann For Res 56(1):123–135 Dimri S, Baluni P, Sharma CM (2018) Carbon dynamics in Quercus semecarpifolia (Kharsu Oak) and Quercus floribunda (Moru Oak) Forests of Garhwal Himalaya, India. Proc Natl Acad Sci 88(3):1157–1168 Dusenge ME, Duarte AG, Way DA (2019) Plant carbon metabolism and climate change: elevated CO2 and temperature impacts on photosynthesis, photorespiration and respiration. New Phytologist 221(1):32–49 Foley BJ, Smye AJ (2018) Carbon cycling and habitability of Earth-sized stagnant lid planets. Astrobiology 18(7):873–896 FSI (1996) Volume equations for forests of India, Nepal and Bhutan: Forest Survey of India, Ministry of Environment and Forests FSI (2019) Carbon Stock in India’s Forests India. State of Forest Report, 2019, vol 1. http://fsi.nic. in/isfr19/vol1/chapter9pdf Gairola S, Sharma CM, Ghildiyal SK, Suyal S (2011) Live tree biomass and carbon variation along an altitudinal gradient in moist temperate valley slopes of the Garhwal Himalaya (India). Curr Sci 100:1862–1870 Ge G (2000) The group 14 elements: carbon, silicon, germanium. Main Group Chem 3:76 Gibbs HK, Brown S, Niles JO, Foley JA (2007) Monitoring and estimating tropical forest carbon stocks: making REDD a reality. Environ Res Lett 2(4):045023 Giri A, Pant D (2018) Carbon management and greenhouse gas mitigation. In: Reference module in materials science and materials engineering. Elsevier, Amsterdam, pp 312–335 Giri A, Sharma V, Thakur S, Sharma T, Kumar A, Pant D (2020) Engineering of microbial carbonic anhydrase for enhanced carbon sequestration. In: Chemo-biological systems for CO2 utilization. CRC Press, Boca Raton, pp 91–105 Gogoi A, Ahirwal J, Sahoo UK (2022) Evaluation of ecosystem carbon storage in major forest types of Eastern Himalaya: implications for carbon sink management. J Environ Manag 302:113972 Gosain BG, Negi GCS, Dhyani PP, Bargali SS, Saxena R (2015) Ecosystem services of forests: carbon Stock in vegetation and soil components in a watershed of Kumaun Himalaya, India. Int J Ecol Environ Sci 41(3-4):177–188 Goswami M, Pant G, Mansotra DK, Sharma S, Joshi PC (2021) Biochar: a carbon negative technology for combating climate change. Adv Carbon Capture Util 2021:251–272 Goswami M, Kumar V, Kumar P, Singh N (2022) Prediction models for evaluating the impacts of ambient air pollutants on the biochemical response of selected tree species of Haridwar, India. Environ Monit Assess 194(10):696 Gougoulias C, Clark JM, Shaw LJ (2014) The role of soil microbes in the global carbon cycle: tracking the below-ground microbial processing of plant-derived carbon for manipulating carbon dynamics in agricultural systems. J Sci Food Agric 94(12):2362–2371
5
Terrestrial Carbon Stock and Sink Potential of Indian Himalayan. . .
89
Greipsson S (2011) Restoration ecology. Jones & Bartlett Learning, Burlington Haq SM, Rashid I, Calixto ES, Ali A, Kumar M, Srivastava G, Khuroo AA (2022) Unravelling patterns of forest carbon stock along a wide elevational gradient in the Himalaya: implications for climate change mitigation. For Ecol Manag 521:120442 Hilton RG, West AJ (2020) Mountains, erosion and the carbon cycle. Nat Rev Earth Environ 1(6): 284–299 Joshi VC, Negi VS, Bisht D, Sundriyal RC, Arya D (2021) Tree biomass and carbon stock assessment of subtropical and temperate forests in the Central Himalaya, India. Trees Forests People 6:100147 Kala CP (2014) Deluge, disaster and development in Uttarakhand Himalayan region of India: Challenges and lessons for disaster management. Int J Disaster Risk Reduct 8:143–152 Kanwar N, Kuniyal JC (2022) Vulnerability assessment of forest ecosystems focusing on climate change, hazards and anthropogenic pressures in the cold desert of Kinnaur district, northwestern Indian Himalaya. J Earth Syst Sci 131(1):1–16 Kaur D, Tiwana AS, Kaur S, Gupta S (2022) Climate change: concerns and influences on biodiversity of the Indian Himalayas. In: Climate change: impacts, responses and sustainability in the Indian Himalaya. Springer International Publishing, Cham, pp 265–281 Kotlia BS, Ahmad SM, Zhao JX, Raza W, Collerson KD, Joshi LM, Sanwal J (2012) Climatic fluctuations during the LIA and post-LIA in the Kumaun Lesser Himalaya, India: evidence from a 400 y old stalagmite record. Quat Int 263:129–138 Krishan R, Tiwari OP, Rana YS, Mishra AK, Sharma CM (2017) Changes in levels of soil carbon and forest floor carbon stocks in the different temperate forests of Garhwal Himalaya. J Cur Res Rev 9(7):5 Kumar V, Chopra AK (2009) Impact of climate change on biodiversity of India with special reference to Himalayan region-An overview. J Appl Nat Sci 1(1):117–122 Kumar D, Katoch SS (2016) Environmental sustainability of run of the river hydropower projects: a study from western Himalayan region of India. Renew Energy 93:599–607 Kumar A, Shashni S, Kumar P, Pant D, Singh A, Verma RK (2021a) Phytochemical constituents, distributions and traditional usages of Arnebia euchroma: a review. J Ethnopharmacol 271: 113896 Kumar M, Kumar A, Kumar R, Konsam B, Pala NA, Bhat JA (2021b) Carbon stock potential in Pinus roxburghii forests of Indian Himalayan regions. Environ Dev Sustain 23(8):12463–12478 Kumari R, Kumar A, Saikia P, Khan ML (2022) Vulnerability assessment of the Indian Himalayan forests in terms of biomass production and carbon sequestration potential in changing climatic conditions. In: Handbook of climate change mitigation and adaptation. Springer, Cham, pp 147–161 Liu Y, Yu G, Wang Q, Zhang Y, Xu Z (2014) Carbon carry capacity and carbon sequestration potential in China based on an integrated analysis of mature forest biomass. Sci China Life Sci 57:1218–1229 Luo Z, Feng W, Luo Y, Baldock J, Wang E (2017) Soil organic carbon dynamics jointly controlled by climate, carbon inputs, soil properties and soil carbon fractions. Glob Chang Biol 23(10): 4430–4439 Malhi Y, Girardin CA, Goldsmith GR, Doughty CE, Salinas N, Metcalfe DB, Silman M (2017) The variation of productivity and its allocation along a tropical elevation gradient: a whole carbon budget perspective. New Phytol 214(3):1019–1032 Martens JA, Bogaerts A, De Kimpe N, Jacobs PA, Marin GB, Rabaey K, Verhelst S (2017) The chemical route to a carbon dioxide neutral world. ChemSusChem 10(6):1039–1055 Meena NK, Gaury PK, Mahajan AK (2021) The climatic and anthropogenic influences on Himalayan glacial and non-glacial lakes. In: Quaternary climate change over the Indian subcontinent, vol 21. Routledge, London Mehmood I, Bari A, Irshad S, Khalid F, Liaqat S, Anjum H, Fahad S (2020) Carbon cycle in response to global warming. In: Environment, climate, plant and vegetation growth. Springer, Cham, pp 1–15
90
A. Kumar et al.
Mir AH, Dad JM, Singh B, Kamili AN (2022) Passive restoration considerably improved the community structure, soil health and carbon stock in the Pine forests of Kashmir Himalaya, India. Ecol Eng 176:106535 Mishra T, Singh B, Gill PK (2015) Ectropis deodarae and fungal pathogen: a potential threat to Cedrus deodara in the Himalayan forestry. Int J Agric Sci Res 4(7):146–149 MoEFCC (2022) India’s long-term low-carbon development strategy. Ministry of Environment, Forest and Climate Change, Government of India Montzka SA, Dlugokencky EJ, Butler JH (2011) Non-CO2 greenhouse gases and climate change. Nature 476(7358):43–50 Naddaf M (2023) Carbon capture nets 2 billion tonnes of CO2 each year-but it’s not enough. Nature. https://www.nature.com/articles/d41586-023-00180-4 Negi GS, Joshi V (2002) Drinking water issues and development of spring sanctuaries in a mountain watershed in the Indian Himalaya. Mt Res Dev 22(1):29–31 Negi VS, Pathak R, Dhyani V, Durgapal M, Joshi RK, Bhatt ID (2022) Land restoration in the Himalayan Region: steps towards biosphere integrity. Land Use Policy 121:106317 Pauli, H., Gottfried, M., Lamprecht, A., Niessner, S., Rumpf, S., Winkler, M., Grabherr, G. (2015). The GLORIA field manual–standard multi-summit approach, supplementary methods and extra approaches. Austrian Academy of Sciences & University of Natural Resources and Life Sciences, Vienna Penman J, Gytarsky M, Hiraishi T, Krug T, Kruger D, Pipatti R, Wagner F (2003) Good practice guidance for land use, land-use change and forestry Petrokofsky G, Kanamaru H, Achard F, Goetz SJ, Joosten H, Holmgren P, Wattenbach M (2012) Comparison of methods for measuring and assessing carbon stocks and carbon stock changes in terrestrial carbon pools. How do the accuracy and precision of current methods compare? A systematic review protocol. Environ Evid 1(1):1–21 Rajeev J, Hukum S (2020) Carbon sequestration potential of disturbed and non-disturbed forest ecosystem: a tool for mitigating climate change. Afr J Environ Sci Technol 14(11):385–393 Rawat D, Sati SP, Khanduri VP, Riyal M, Mishra G (2021) Carbon sequestration potential of different land use sectors of Western Himalaya. Adv Carbon Capture Util 2021:273–294 Sangay D, Edwin D, Michael JW, Dal BC, Thomas K (2012) Himalayan dwarf mistletoe (Arceuthobium minutissimum) and the leafy mistletoe Taxillus kaempferi on blue pine (Pinus wallichiana) in Bhutan. J Agric Extens Rural Dev 4(9):217–220 Sannigrahi S, Pilla F, Basu B, Basu AS, Sarkar K, Chakraborti S, Roy PS (2020) Examining the effects of forest fire on terrestrial carbon emission and ecosystem production in India using remote sensing approaches. Sci Total Environ 725:138331 Sati VP (2014) Mountain ecosystems. In: Towards sustainable livelihoods and ecosystems in mountain regions. Springer, Cham, pp 115–121 Sharma N (2022) Pathogenic diseases of a wonder plant-Seabuckthorn in Garhwal Himalayas and their biocontrol. EduBubs Publishing House, New Delhi Sharma CM, Gairola S, Baduni NP, Ghildiyal SK, Suyal S (2011) Variation in carbon stocks on different slope aspects in seven major forest types of temperate region of Garhwal Himalaya, India. J Biosci 36(4):701–708 Sharma V, Hussain S, Sharma KR, Arya VM (2014) Labile carbon pools and soil organic carbon stocks in the foothill Himalayas under different land use systems. Geoderma 232:81–87 Sharma T, Bhardwaj R, Bhardwaj R, Giri A, Pant D, Nadda AK (2021) Progresses in bioenergy generation from CO2: mitigating the climate change. Adv Carbon Capture Util 2021:297–312 Shrestha AB, Aryal R (2011) Climate change in Nepal and its impact on Himalayan glaciers. Reg Environ Chang 11:65–77 Shrestha UB, Gautam S, Bawa KS (2012) Widespread climate change in the Himalayas and associated changes in local ecosystems. PLoS One 7(5):e36741 Singh RP, Prasad PV, Reddy KR (2013) Impacts of changing climate and climate variability on seed production and seed industry. Adv Agron 118:49–110
5
Terrestrial Carbon Stock and Sink Potential of Indian Himalayan. . .
91
Singh N, Sharma DP, Chand H (2016) Impact of climate change on apple production in India: a review. Curr World Environ 11(1):251 Singh L, Singh H, Singh S (2020) Managing natural resources and environmental challenges in the face of urban sprawl in Indian Himalayan City of Jammu. J Indian Soc Remote Sens 48(8): 1139–1147 Singhal S, Gupta M, Alam MS, Javed MN, Ansari JR (2022) Carbon allotropes-based nanodevices: graphene in biomedical applications. In: Nanotechnology. CRC Press, Boca Raton, pp 241–269 Sinha SK, Swaminathan MS (1991) Deforestation, climate change and sustainable nutrition security: a case study of India. In: Tropical forests and climate. Springer, Dordrecht, pp 201–209 Smith SM, Geden O, Nemet G, Gidden M, Lamb WF, Powis C, Bellamy R, Callaghan M, Cowie A, Cox E, Fuss S, Gasser T, Grassi G, Greene J, Lück S, Mohan A, Müller-Hansen F, Peters G, Pratama Y, Repke T, Riahi K, Schenuit F, Steinhauser J, Strefler J, Valenzuela JM, Minx JC (2023) The state of carbon dioxide removal, 1st edn. MCC, Berlin. https://www.stateofcdr.org Strachey H (1853) Physical geography of western Tibet. J R Geogr Soc Lond 23:1–69 Telwala Y, Brook BW, Manish K, Pandit MK (2013) Climate-induced elevational range shifts and increase in plant species richness in a Himalayan biodiversity epicentre. PLoS One 8(2):e57103 Tripathi AK, Pandey PC, Sharma JK, Triantakonstantis D, Srivastava PK (2022) Climate change and its impact on forest of Indian Himalayan region: a review. Climate Change 2022:207–222 Upadhyay TP, Sankhayan PL, Solberg B (2005) A review of carbon sequestration dynamics in the Himalayan region as a function of land-use change and forest/soil degradation with special reference to Nepal. Agric Ecosyst Environ 105(3):449–465 Vannini A, Cecca D, Monaci L, Anselmi N (1995) Main tree pathogens of western Himalayan forests in Nepal: description and risk of introduction. EPPO Bull 25(3):455–461 Vedwan N, Rhoades RE (2001) Climate change in the Western Himalayas of India: a study of local perception and response. Clim Res 19(2):109–117 Verma O (2021) Climate change and its impacts with special reference to India. In: Water, cryosphere, and climate change in the Himalayas. Springer, Cham, pp 39–55 Vikrant KK, Chauhan DS, Rizvi RH (2022) Assessment of agroforestry area and its carbon storage potential along altitudes of Tehri Garhwal District, Uttarakhand, in North-Western Indian Himalaya. In: Climate change. Springer, Cham, pp 243–263 Wang L, Tian F, Wang Y, Wu Z, Schurgers G, Fensholt R (2018) Acceleration of global vegetation greenup from combined effects of climate change and human land management. Glob Chang Biol 24(11):5484–5499 Wang R, Mattox CM, Phillips CL, Kowalewski AR (2022) Carbon sequestration in turfgrass–soil systems. Plants 11(19):2478 Wani ZA, Qadri M (2022) Exploring the endophytic fungi of Himalayan Pinus sp. In: Endophyte biology. Apple Academic Press, New York, pp 65–80 Wani AA, Joshi P, Singh O, Pandey R (2012) Carbon sequestration potential of Indian forestry land use systems: a review. Wetlands 354:182–187 Wani AA, Joshi PK, Singh O, Bhat JA (2014) Estimating soil carbon storage and mitigation under temperate coniferous forests in the southern region of Kashmir Himalayas. Mitig Adapt Strateg Glob Chang 19:1179–1194 Wani AA, Joshi PK, Singh O (2015) Estimating biomass and carbon mitigation of temperate coniferous forests using spectral modeling and field inventory data. Eco Inform 25:63–70 Whitmarsh J, Govindjee JA (1999) The photosynthetic process. Concepts in photobiology: photosynthesis and photomorphogenesis. Springer, New York, pp 11–51 Xu J, Badola R, Chettri N, Chaudhary RP, Zomer R, Pokhrel B, Pradhan R (2019) Sustaining biodiversity and ecosystem services in the Hindu Kush Himalaya. In: The Hindu Kush Himalaya assessment. Springer, Cham, pp 127–165 Yam G, Tripathi OP, Das DN (2021) Modelling of total soil carbon using readily available soil variables in temperate forest of Eastern Himalaya, Northeast India. Geol Ecol Landsc 5(3): 209–216 Zeng N (2008) Carbon sequestration via wood burial. Carbon Balance Manag 3(1):1–12
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Conservation Agriculture for Soil Health and Carbon Sequestration in the Indian Himalayan Region Ashish Rai, Sumit Tripathi, Ayush Bahuguna, Sumit Rai, Jitendra Rajput, Anshu Gangwar, Rajeev Kumar Srivastava, Arvind Kumar Singh, Satish Kumar Singh, Dibyanshu Shekhar, Rahul Mishra, Eetela Sathyanarayana, and Supriya Pandey
A. Rai (✉) · A. Gangwar · A. K. Singh Krishi Vigyan Kendra Parsauni, East Champaran, Dr Rajendra Prasad Central Agricultural University, Pusa, Bihar, India S. Tripathi Department of Soil Science and Agricultural Chemistry, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh, India A. Bahuguna Department of Agriculture Chemistry and Soil Science, Ch. Chhotu Ram (PG) College, Muzaffarnagar, Uttar Pradesh, India S. Rai · S. Pandey Centre for Environmental Assessment and Climate Change, GB Pant National Institute of Himalayan Environment, Almora, India J. Rajput Division of Agricultural Engineering, ICAR-Indian Agricultural Research Institute, New Delhi, India R. K. Srivastava Directorate of Seed and Farms, TCA Dholi, Dr Rajendra Prasad Central Agricultural University, Pusa, Bihar, India S. K. Singh Department of Plant Breeding and Genetics, Dr. Rajendra Prasad Central Agriculture University, Pusa, Bihar, India D. Shekhar Krishi Vigyan Kendra Jale Darbhanga, Dr Rajendra Prasad Central Agricultural University, Pusa, Bihar, India R. Mishra ICAR-Indian Institute of Soil Science, Bhopal, Madhya Pradesh, India E. Sathyanarayana Department of Soil Science and Agricultural Chemistry, Agricultural College, Palem, PJTSAU, Hyderabad, India # The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Mishra et al. (eds.), Soil Carbon Dynamics in Indian Himalayan Region, https://doi.org/10.1007/978-981-99-3303-7_6
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Abstract
Mountains the most significant agroecosystems that directly or indirectly support human life. The areas surrounding the hills are abundant in biodiversity and have enormous potential for sustaining Indian agriculture. It has been widely recognised that the ecological fragility and sensitivity of the Himalayas to climatic aberrations, topography, peculiar geographical features, and some of the particular identified problems, which may be soil loss, runoff, steep slopes, acidity of soils, and loss of soil nutrients, form it a very distinct region as opposed to plains in terms of socioeconomic situation. Conventional agriculture was one of the best aspects of food production during the green revolution and after India gained its independence for securing food and nutrition through intensive agricultural practices, but on the flip side, it has simultaneous effects on resource degradation and soil biodiversity. The need for food and fodder, an ever-growing population, the preservation of soil biodiversity, declining soil health, climate change, the use of unbalanced fertilisers, and decreased farm profitability all call for a paradigm shift in the agriculture sector. On the other hand, increasing the intensity of the hillside agriculture system without implementing any conservation measures greatly increases the likelihood of disastrous conditions. Conservation agriculture has long been known to improve soil health and sustain agricultural production systems by reducing environmental footprints. Between the atmosphere and the lithosphere, numerous biological and physical processes are regulated by soils. An integral aspect of soil that promotes agricultural sustainability is soil health. However, each measurement of a specific soil health parameter is always tied to a unique set of circumstances. A fundamental concern in maintaining soil health to feed an expanding population is resource conservation. Climate change is a topic of discussion on a worldwide scale in the current globalisation context. The greenhouse effect is best for life but only up to a point beyond which it becomes dangerous. Due to urbanisation, changes in land use, cropping patterns, and other factors, human influences on climate change go beyond the range of natural fluctuation. Climate change in the soil system is significantly influenced by carbon regulation in the soil. The rate of organic matter decomposition is accelerated by an increase in mean annual temperature, which affects aggregate stability, water storage capacity, and nutrient balance— all of which are crucial for healthy soil structure, soil fertility, productivity, and sustainability. In actuality, soil bacteria break down organic materials, but a change in temperature regime may change the microbial population. Keywords
Climate change · Carbon sequestration · Conservation agriculture · Himalaya · Soil health · Soil quality
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Introduction
The Himalayan mountains take up about 18% of India’s total geographical area and are home to 40% of the endemic species found only in India. About 4% of India’s total population resides in the Himalayan states, and they rely heavily on agriculture, animal husbandry, and horticulture for their livelihoods (Himalayan Resources 2012). The health of the hill determines the health of the plains, so it is especially important to maintain, repair, and enhance the hill and mountain ecosystems. More than 95% of soils in the Himalayas are acidic because basic cations have been leached away by the regular heavy rain. Because of intensive natural resource mining and continued deterioration of natural resources (soil, water, and vegetation) under conventional agricultural systems, the future of farm output and food security is in jeopardy (Yadav et al. 2021). However, climate change, resource degradation, soil erosion, and land fragmentation pose major threats to the region’s biodiversity, agriculture, environment, and way of life in the Himalayan mountain. Many of the region’s indigenous peoples have stayed put in their home countries despite the fact that they employ effective methods for preserving their natural resources. Increasing demands from the world’s populace have resulted in a shift toward more intensive farming practices. In the rainfed hill zones, marginal mechanisation is typically the result of difficult terrain, small holdings, and low economic position among farmers (Malik et al. 2018). Adding crop leftovers, which can add organic matter, nutrients, and other soil-binding cations that help in the development of soil micro- and macroaggregates, is one strategy that can help conservation agriculture (CA) reverse the trend of degradation to a larger extent. As a result, conservation agriculture (CA) based on minimum tillage/no-till system is an option to reconcile agriculture with its environment and overcome the imposed limits of climate change and spiralling input prices to maintain the production system in a sustainable fashion under different land situations (Yadav et al. 2021). More specifically, RCTs that make use of locally available resources are those that boost resource or input-use efficiency and provide immediate, observable, and quantifiable economic benefits such as lower production costs, less need for water, fuel, and labour, and the timely establishment of crops that produce higher yields (Jayaraman et al. 2021). The benefits of conservation agriculture for soil health and carbon sequestration in the Indian Himalayan region are illustrated in great depth in this chapter.
6.2
Concerning the Effects of Climate Change and Global Warming on Agricultural Practices
Greenhouse gas (GHG) emissions have been rising due to human interference in both agricultural and natural ecosystems, reducing environmental quality. Tillage, intercultural techniques, irrigation, manure application, and the use of chemical fertilisers are all examples of agricultural operations that result in the emission of GHGs into the atmosphere and have profoundly negative consequences for the
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ecosystem. Fossil fuel combustion for energy use in agriculture is a significant source of greenhouse gas emissions (Tjandra et al. 2016; Ashoka et al. 2017). As a result, slowing the rate of climate change necessitates lessening the production of GHGs from agricultural and related activities (Liu et al. 2016; Meena and Meena 2017). In addition, the cost of production is four to five times higher than it would be with no-till (NT) farming over the same time period, and resource and energy intensive practices have a high carbon footprint, especially of GHGs (Tubiello et al. 2015). The global energy budget has increased by 10 times since the beginning of the twentieth century (Tandon and Singh 2009; Pratibha et al. 2015). Traditional agricultural practices include burning or removing crop waste and repeatedly tilling the soil to create a fine seed bed, all of which contribute to an increase in greenhouse gas emissions (Kuotsu et al. 2014). A lot of power is used up by the agricultural machines because of the farm management procedures (Pishgar-Komleh et al. 2012). By emitting carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), the energy used in agricultural processes contributes to global warming (Ntinas et al. 2017; Yadav et al. 2017a, b). Therefore, it is critical to reduce the associated CF and boost EUE in agricultural productivity. It is important to evaluate the GWP of agricultural production techniques, quantify emissions of GHGs, and think about adopting appropriate mitigation strategies with minimal energy use in cropping systems in order to feed the world’s expanding population (Gunady et al. 2012). Therefore, slowing the rate of climate change and solving the related environmental issues could be aided by determining the exact amount of carbon (C) emission and energy consumption in an agroecosystem, particularly from the rice-based systems. The public and policymakers will benefit from this evaluation as well, as it will increase environmental awareness and streamline the process of identifying and promoting environmentally beneficial innovations (Meena and Yadav 2014; Xue et al. 2016). Due to human thirst for development and unsustainable resource management, the land resource and other natural resources are deteriorating at an alarming rate. These will have a negative impact on environmental sustainability and overall ecological stability on a global scale, as well as on the structure of ecosystems and the services they provide. Soil organic carbon (SOC) pools that directly or indirectly link with food-soil-climate security will rise as a result of C capture through the process of C sequestration (Kumar et al. 2013). For effective land management, it is essential to focus on soil organic matter (SOM) and carbon (C). The most effective mitigation technique across ecosystems is the use of modern, cutting-edge methods for managing soil carbon. Management of soil carbon needs actions that increase the soil’s carbon content, rather than depleting its existing carbon or nutrient stores. Land use systems need to be sustainable and environmentally friendly if we’re going to put a stop to the deterioration of our planet’s surface. Continuous research and development is required to build up a database of information about C dynamics, which will aid in visualising the effects of soil C changes on atmospheric C. Additionally, this data helps with terrestrial C management and adapting to and mitigating the effects of climate change. In light of the foregoing, a thorough and in-depth discussion has been made on the role of soil C
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sequestrations in achieving the goal of a sustainable environment and maintaining overall ecological stability through various land use practices.
6.3
A Decrease in Soil Carbon as a Result of Intensive Cropping
After initial cultivation, intensive agriculture has a significant potential to lower the level of carbon in the soil in a relatively short amount of time; however, the extent to which this potential is realised varies depending on the ecosystem and the management practices that are in place, such as the soil cover, the climatic and edaphic characteristics, and the farming practices (Poeplau et al. 2011; Cusack et al. 2012). It is well-known that unsustainable agricultural intensification and a change in the pattern of land use from natural system to intensive agricultural system management can deplete the soil carbon pool (Guo and Gifford 2002). Since forever, the widespread issue of depleted SOC stocks has come from intensive farming without regard for system sustainability. Intense farming has reduced the amount of organic carbon in most agricultural soils by 30–75% compared to their pre-farming SOC flow. Soil carbon losses of 41–55 Pg C are estimated for the world’s croplands (Paustian et al. 1995). In spite of the fact that Smith et al. (2008) reported a loss of more than 40 Pg C from the world’s soils as a result of human agriculture, at a rate of roughly 1.6 Pg C per year-1 to the atmosphere during the 1990s, scientists are optimistic that the soils may be restored (Smith et al. 2008). However, Lal (2013) noted that extended intense farming is predicted to lessen soil C stock by 0.1–1.0% per year. Depending on factors such as soil cover, climate, edaphic qualities, and farming practices, the soil C level can be reduced significantly by intensive agriculture in a short amount of time after beginning cultivation (Poeplau et al. 2011; Cusack et al. 2012). According to multiple sources (Guo and Gifford 2002), soil C pools have been depleted due to unsustainable agricultural intensification and a shift from natural to intensive land use patterns.
6.4
Role of Carbon Sequestration
SOC stock is a measure of soil health and quality that plays a crucial role in ensuring the long-term viability of an agroecosystem (Veni et al. 2020). Meanwhile, most of the SOC pool of the world’s agricultural areas has been depleted due to the continuation of unsustainable agricultural techniques under intensive farming. Good soil health and C content at varying soil depths, depending on the crop, are guaranteed by the perennial plants covering the soil’s surface (Table 6.1). It is the nature of growth, root morphology and physiology, leaf morphology, climate, soil texture, structure, and aggregation, the dominant cropping system, and agronomic interventions that determine the C sequestration potential and the amount of organic C returned by crop plants. Soil health can be improved and atmospheric CO2 levels lowered by increasing SOC pools through agricultural practices (Lal et al. 1999; Bronick and Lal 2005; Lal 2002; Ashoka et al. 2017). There are two distinct types of
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Table 6.1 Carbon sequestration potential of different land use systems in the Himalayan region Location/ study site Central Himalaya, Tarai region
Land use practice Dalbergia sissoo Populus deltoides, Mangifera indica
Indian Himalayas Doon valley, Uttarakhand
Bhimal (Grewia optiva) Bamboo (Dendrocalamus strictus)
4
Kwalkahad watershed, Himachal Pradesh
5
Almora, Uttarakhand Dehradun, Uttarakhand Uttarakhand
Eight land use (agriculture, agrisilviculture, agri-horticulture, agri-silvi-horticulture, agrihorti-silviculture, silvi-pasture, grassland, abandoned land Pecan nut and wheat system
S. No. 1
2 3
6 7
C sequestration potential 2.73 Mg C ha1 year-1 2.75 Mg C ha1 year-1 1.43 Mg C ha1 year-1 0.63–0.81 Mg C ha-1 year-1 49.1 Mg C ha1 (4-year-old plantation) 15 Mg ha-1
1.67 Mg C hayear-1 0.96 Mg C ha1 year-1 1.62 Mg C ha1 year-1 1
Guava (Psidium guajava) Poplar and wheat agroforestry system
References Kanime et al. (2013)
Verma et al. (2014) Subbulakshmi et al. (2020) Goswami et al. (2014)
Yadav et al. (2017a, b) Rathore et al. (2018) Chauhan et al. (2010)
carbon sequestration in soil: the former, in the form of organic C, is viewed favourably by farmers, while the latter, in the form of inorganic carbon (CaCO3), is generally viewed negatively (Meena and Meena 2017). SOC can be increased through agricultural practices that either boost OM inputs or reduce breakdown of SOM and oxidation of SOC (Singh et al. 2008; Jat et al. 2009; Prasad et al. 2006). Soil carbon and nitrogen can be increased in a variety of farming systems by decreasing the amount of time spent tilling and keeping the residues (Lal and Kimble 1997). Using organic amendments, conservation tillage (such reduce tillage-RT and no-till-NT), and crop rotation can all boost soil organic carbon levels.
6.5
Conservation Agriculture
Energy use in tillage accounts for about 30 percent of the energy used in crop cultivation (Lal 2004; Singh et al. 2008). Using intense tillage increases greenhouse gas emissions, which is directly tied to the use of fossil fuels for energy (Yadav et al. 2017a, b; Soni et al. 2013). Therefore, a significant shift is needed in agricultural management, one that emphasises conservation efficiency, high EUE, and low GHG emissions for cleaner, safer food production. Reduced energy consumption and greenhouse gas emissions are two benefits of using conservation agriculture
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(CA)-based agro-techniques including no-till (NT), residue retention (mulching), and other similar practices (Lal 2004). Soil erosion, compaction, aggregate breakdown, loss of organic matter, leaching of nutrients, and other processes that are exacerbating in the face of extremes in weather and management practices can all be prevented through the use of a set of management practices known as CA (Hobbs et al. 2008; Dalal et al. 2011; Sinha et al. 2019; Somasundaram et al. 2020). The pace at which carbon is released into the atmosphere is slowed because the organic materials stored in this way are degraded slowly, and many of the materials are integrated into the surface soil layer. Soil becomes a carbon sink because of the amount of carbon that is sequestered there (Dalal et al. 2011; Page et al. 2020; Somasundaram et al. 2018, 2020). This has the potential to have far-reaching implications in our efforts to curb GHG emissions from farming activities and avert the worst effects of climate change. Beneficial effects of CA on soil include enhanced aggregation, reduced compaction, increased organic matter and carbon content at the soil’s surface, moderated soil temperature, and reduced weed growth. Cost savings from using CA include time and energy savings, an increase in output through better timing of seeding and planting, a lessening of pest and disease incidence from increased biological diversity, and a decrease in greenhouse gas emissions.
6.6
Principles of Conservation Agriculture
The soil C pool could be harmed by conventional tillage, which leads to greater erosion and a weakening of the soil’s underlying structure. When compared to traditional tillage methods, conservation tillage significantly reduces surface runoff, as well as soil and water erosion, while also shielding the land from the effects of precipitation (Fig. 6.1). The primary instruments of C sequestration with a conservation tillage strategy are the improvement of soil micro-aggregation, the deeper placement of SOC in lower horizons, and the reversal of soil-degrading processes (Lal and Kimble 1997). The hills of India provide a wealth of biodiversity and have great potential for supporting farming of all kinds (including horticulture and livestock). The Himalayas have long been a source of worry due to their ecological susceptibility and fragility in the face of climate anomalies, as well as the everincreasing demand for land to raise more food. Almost two-thirds of the Himalayan workforce is involved in subsistence agriculture, which provides only enough food to sustain the region’s rapidly expanding population for five to 6 months per year. The hilly region is distinct from the plains economically and socially due to its topography, peculiar geographical features. Natural vegetation, fertile soil, forests, meadows, lakes, and snow-capped mountain peaks are only few of their many natural treasures. The perennial streams that sustain the plains originate in the hills. For the hills and the people who live there to advance more quickly, all of these resources must be put to good use. Because of the region’s varying agroclimatic conditions, NW Himalayas is suitable for cultivating a wide range of crops. The growth of agriculture and its supporting industries had a significant impact on
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Fig. 6.1 Principle and approaches of conservation agriculture
the hills and their subsequent prosperity. Although agriculture is a key industry in the North West Hill (NWH) region, a lack of modernization in this sector may be shown through indicators like low adoption of contemporary technology, low use of fertilisers, and slow economic growth. Inadequate investments in system- and location-based technologies are major contributors to this sluggish expansion.
6.7
Characteristic and Problems of Hill Farming
Traditional farming in NWH is often a low-input, low-output practice used mostly for sustenance. Most hill farmers still use antiquated methods that limit their agricultural output. The energy, feed, water, and non-timber goods provided by forests are also vital to hill farming. The human and livestock population has increased, and so has the area under cultivation; nevertheless, fields have become more dispersed and are located on marginal soils, and overgrazing and the excessive harvesting of trees for use as building materials and animal feed continue to be problems (Fig. 6.2). It’s ironic that the hill people aren’t as self-sufficient as they were a century ago. Nearly all of the NWH’s farmland relies on rainwater for its sustenance. There is a severe lack of accessibility, and oftentimes vital infrastructure is not present. Because of the extreme weather and other obstacles, farming is extremely difficult in this area. The principal natural challenges that afflict sustained agriculture in the hills are excessive/meagre rainfall, relatively low temperature, poor and shallow soils, and soil erosion in terms of loss of fertile top soil. Growing conditions are severely constrained by height and aspect, which reduces warmth and sunlight. Spreading hill
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Injudicious Agricultural Development
Atmospheric CO2
Temperature
Degradation by Different Means
Management of Population load
Fig. 6.2 Possible consequences and problems of hill farming
farming into previously uncultivated areas can have devastating effects on ecosystems by reducing biodiversity and depleting natural resources like soil fertility and organic matter. Rainfall, land sloping, slope length, vegetation cover density, and management techniques are all contributors to soil erosion. One of the most damaging factors is the widespread use of erosion-prone farming methods. Uncontrolled growth in agriculture is clearing more and more land every year. Extreme soil erosion occurs when heavy rains are followed by rapid runoff down a long slope. The effect is worsened with higher slopes. Sometimes the force of the collision is great enough to reveal the bedrock beneath the surface. The growth of agriculture in this region is currently hampered by soil erosion, poverty, and a lack of water. Extreme weather events and general climate change pose a serious threat to people’s capacity to make a living in the mountains. Many households who are at risk of food insecurity are also particularly exposed to weather shocks and climatic dangers. The uplands present a challenging agricultural environment that requires careful management. The threat of degradation and stress to the agile hill environment is accelerated by population growth above a certain threshold and poor resource management (Lal 2001) (Table 6.2).
6.8
Potential of Conservation Agriculture in Hills
Successful in meeting production targets, the conventional or traditional form of agriculture through intensive agricultural methods has nonetheless resulted in the degradation of agricultural resources. The rising cost of puts and other field operations has pushed up output prices. Large-scale migration to the plains or major cities in search of economic opportunity has further diminished the availability of agricultural labour. A paradigm shift is required in agriculture due to the many
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Table 6.2 SOC stock in representative forest soil in Indian Himalayan regions Eastern Himalayas
North Western and Central Himalayas
Region Sikkim
Forest type –
West Bengal hills Darjeeling
Tropical moist deciduous forest: East Himalayan temperate forest: East Himalayan subalpine forest
Darjeeling
Altitudinal gradient from 155 to 3500 m in Darjeeling Himalayan region only under foliage cover
Jammu and Kashmir
Moist temperate forest
Jammu and Kashmir
Northern temperate forests
Remark The carbon stock under forest cover of South and West Sikkim combined is 213.39 million tons Increased soil carbon stocks (257.02–527.79 MgC ha-1), SOC stocks (152.55–398.88 MgC ha-1), and soil nitrogen stocks (15.10–32.38 MgN ha-1) Subalpine/alpine and high altitude (2500–3500 m and 2000–2500 m) forest sites showed the highest soil organic carbon in the top soil layer (0–15 cm) (59.8 and 58.2 g/kg, respectively) With increasing soil depth, a declining trend in soil organic carbon was seen Low carbon stocks were found in Pinus wallichiana (PW) and Abies pindrow (AP) forest, ranging from 50.37 to 55.38 Mg C ha-1 Pinus wallichiana (PW), Betula utilis, Cedrus deodara (CD), Abies pindrow (AP), and Picea smithiana (PS) (BU) In PS and BU forest types, the mean SOC stock levels ranged from 46.211.84 Mg ha-1 to 67.09 1.23 Mg ha-1at 0–30 cm depth, respectively
References Gangopadhyay et al. (2020)
Devi and Sherpa (2019)
Banerjee (2014)
Dar and Sundarapandian (2013)
Dar and Sahu (2017)
(continued)
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Table 6.2 (continued) Region Ladakh
Forest type Croplands as well as grasslands in Indus and Nubra Valley
Ladakh
From forest of different altitudes
Uttarakhand
Forests having Shorea robusta (sal), Pinus roxburghii (chir), Quercus leucotrichophora (banj oak), Cedrus deodara (deodar), Pinus wallichiana (kail), Picea smithiana and Abies pindrow (silver fir and spruce)
Himachal Pradesh
Moist alpine forests, tropical dry deciduous forests (Himalayan moist temperate forests, Himalayan dry temperate forests, subalpine, tropical dry deciduous forests
Remark Total SOC storage was found 37.95 t ha-1 and 43.94 t ha-1, respectively. SOC storage of grasslands of Indus and Nubra Valley has been estimated to be about 40.23 t ha-1 and 46.9 t ha1 respectively Soil organic carbon (SOC) content and storage increased significantly with the increase in the altitude The highest SOC stock was found above 2501 m elevation (138.37 Mg ha-1), followed by soils at elevations between 2001 and 2500 m (115.00 Mg ha-1), 83.10 Mg ha-1 in soils having elevations between 1501 and 2000 m, 58.31 Mg ha-1 in soils having elevations between 1001 and 1500 m, 55.90 Mg ha-1 in soils having elevations between 501 and 1000 m, and the lowest S Maximum pool was in the soils under moist Alpine Scrub (73.26 tons/ha) followed by Himalayan moist temperate forests (55.20 tons/ha), Himalayan dry temperate forests (47.61 tons/ha), and
References Acharya et al. (2012)
Charan et al. (2012)
Gupta et al. (2018)
Panwar and Gupta (2013)
(continued)
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Table 6.2 (continued) Region
North Eastern Himalayas
Assam, Manipur, Meghalaya, Nagaland, Sikkim and Tripura
Forest type
–
Remark subalpine forests (45.67 tons/ha), and the least was under tropical dry deciduous forests (36.04 tons/ha) A total of 339.8 Tg SOC stocks was estimated. The SOC content as percentage of total geographical area was highest in Sikkim followed by Nagaland, Manipur, Meghalaya, Assam, and Tripura
References
Chaudhary et al. (2000)
challenges and constraints that it faces, including a growing population, rising demands for food, feed, and fodder, a changing climate, the emergence of novel parasites, stagnating per capita income, and the introduction of stringent new trade regulations at the international level. Hill farmers will have to make the transition from subsistence farming to commercial crop production if they want to survive. The need for better agricultural technologies to boost soil and water conservation and crop yields has grown in recent years in response to rising population and declining agricultural land. Scienceimproved technologies that are optimal for the hill people’s agro-social-economic situation should be developed. There is a significant risk of degradation associated with intensifying hill farming without conservation. CA in the hill farming systems must be different from CA in the plains in managing the different production systems because the varied agro-climatic conditions of hills confer a unique benefit and competitive edge over a plain region. Therefore, CA can show to be an invaluable instrument in directly addressing concerns like extensive resource degradation, low production costs, high profitability, and increased competitiveness in agriculture. As an alternative to both conventional and organic farming, CA is gaining popularity around the globe. It has been quickly spreading in recent years and is now practised in more than 50 nations across all ecologies (including semiarid Mediterranean regions) on every continent (Kassam and Friedrich 2009). CA systems are becoming increasingly important in helping resource-poor farmers in Africa, Asia, and Latin America meet their own unique issues, such as those posed by climate change, dwindling labour supplies, rising energy prices, and fluctuating global temperatures. As well as the obvious economic benefits of boosting agricultural output, there are also important social benefits for mountainous areas to consider. There is a need to evaluate the viability of CA systems in rainfed hilly
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areas, which are typically single cropped during the Kharif season, in contrast to irrigated production systems in the plain regions, where CA techniques were investigated extensively in the context of the second crop in the season. It has been noted that some high-rainfall areas show promise for CA adoption, but relevant methods still need to be developed. Farms and ecosystems alike will benefit from conservation agriculture.
6.9
Conservation Agriculture Practices for Hill Farming
6.9.1
Conservation Tillage
By minimising soil compaction and retaining more of the soil’s natural moisture, conservation tillage can cut soil loss in half (Fig. 6.3). When using zero tillage, seeds are sown onto soil that has not been tilled since the previous crop was harvested. The crop can save as much as a million litres of water per hectare by germinating in soil that still has moisture from the preceding crop. Time and money savings aren’t the only benefits of conservation tillage for hill farmers. The practice is also well-suited to the area’s delicate ecosystems and the region’s dismal economic and social climate. The benefits of conservation tillage (mulch plus zero/minimum tillage) in hills under both rainfed and irrigated conditions have been established through field experiments at CSK Himachal
Management of Social Issues Augmentation of Soil Carbon Pool
Agroecosystem StabilityIncrease in
Nutrient Recycling for Soil Fertility
Enhance Bio-diversity Above &Below Hike in Global
Rational Conservation Approaches to RestoreDegraded Hill Lands for Human Welfare
Develop Restorative Land Use Plant/Soil
Consequencesof the
Soil and Water Conservation Adopt Sound Approaches to Check Erosion
Fig. 6.3 Rational conservation approaches to restore natural resources
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Pradesh Agricultural University, Palampur (India). Grain yield from wheat grown using conservation tillage in the hills of north-west India was comparable to, or even higher than, grain yield from wheat grown using conventional tillage, which included this material at sowing. There is no need to worry about decreased output if NWH adopts reduced tillage. It helps reduce expenditures, boosts organic matter and water retention in soil, and conserves resources. Reduced tillage conditions are ideal for soy-lentil and soy-wheat combinations (Singh et al. 2008).
6.9.2
Selection of Crops/Varieties
Choosing a lucrative crop and high-yielding varieties are essential components of conservation agriculture, and there is a lot of room for improvement in productivity and financial returns in the north-west hills. High-yielding crop varieties, such as pulses and oilseeds, are helpful in challenging environments due to their unique traits, such as indeterminate growth habit, excessive foliage and flower production, and non-synchronous maturation. Amaranthus, buckwheat, horse gram, finger millet, and barnyard millet are all better suited to marginal soils when grown as superior cultivars. However, in a favourable setting, larger returns can be obtained from growing input-responsive crop varieties with higher yields, such as rice, wheat, and maize. Varied crops have vastly different root systems, water needs, absorption capacities, growth patterns, and canopies. Infrastructure, accessible input technologies, traditional knowledge and experience of previous performance and limitations, governmental decisions, and domestic and market needs all play a role in determining which crop (or crops) will be grown. Water-scarce regions can benefit from the selection of crops with increased water usage efficiency, robust root development, and rapid seedling vigour. In areas where farmers have limited access to other resources, such as synthetic N fertilisers, these nitrogen-efficient cultivars could be very helpful. Selecting N-efficient varieties, which can extract more N from soil at reduced availability, will boost yield in these areas.
6.9.3
Sowing Method
The method of sowing is essential for achieving the desired plant population per unit area, which in turn is necessary for obtaining the potential yield of crop. The hills have a preference for the broadcast sowing approach. This method may be speedier and require less energy, but it usually results in damaged seeds, inconsistent germination, and stunted plant growth. Contrarily, line sowing not only facilitates intercultural activities but also increases germination by placing seeds in the moist zone.
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Seed Priming
Seed priming refers to the practice of soaking seeds for a set amount of time in water prior to planting. Seeds can better endure moisture stress and continue the germination process if they are primed prior to planting in soil with inadequate moisture levels. However, the type of seed and soil moisture content affect the response to the priming process. Overnight soaking of seeds improves germination, increases plant vigour and drought resistance, accelerates flowering and harvest, and increases yield in rainfed regions. Priming seeds evenly with H2O (hydro-priming) for 18–24 h is a simple, low-cost, and ecologically friendly practice that has been shown to improve seed germination, seed yield, and yield components in a variety of crops (Soleimanzadeh 2013).
6.9.5
Remunerative Cropping Systems and Intercropping
Subsistence farming, including the use of traditional cropping techniques and mixed cropping that have developed over the centuries to fulfil rising domestic food demands, plays a significant role in the NWH highlands. Natural resources, local eating patterns, and socioeconomic situations have all played significant roles in shaping them. However, without a temporal/spatial design, the relative yield stability of these conventional systems is low, increasing the likelihood of crop failures. It is important to find water-wise crops that can outperform conventional ones in locations where rainfall is restricted or where water is scarce. Higher waterdemanding crops should generally be left out of crop production systems unless reliable access to irrigation can be guaranteed. More money can be made using 1-year cropping sequences based on crops like maize, soybeans, and June-seeded rice in the rainy hills of Uttarakhand than with the conventional 2-year cropping sequences that have traditionally been used. Legumes like soybeans, lentils, and peas planted in the right order can increase profits and boost soil quality. Therefore, these cropping methods can enhance the commercial viability of hill farming. The maizeradish-onion, maize-toria-potato, maize-toria+gobhi sarson, and maize-gobhi sarson cropping systems have been more profitable for farmers in Himachal Pradesh than the maize-wheat system (Chaudhary et al. 2000).
6.9.6
Integrated Nutrient Management
The only method to reduce production costs is to increase input-use efficiency by adopting environmentally friendly technologies like the use of organic manures, crop rotation, integrated pest control, crop residues for organic carbon buildup, etc. Synergistically replacing some inorganic fertilisers with locally available organic sources of nutrients such as manures, green manures, crop residues, biofertilisers, etc. is called integrated nutrient management and is necessary due to the high cost of fertilisers and the Josses of fertiliser elements leading to environmental pollution and
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unsustainable crop production. Organic sources not only give nutrients but also enhance the physical state and biological health of soil, which in turn increases the availability of both applied and native nutrients.
6.9.7
Mulching
Mulching stops water from evaporating from the soil and keeps the soil at a more manageable temperature by acting as a barrier between the soil and the air. It is wellknown that mulching benefits in location with little rainfall by retaining moistures in the soil profile. Both types of organic matter are found in hilly areas. Mulch can be made from a wide variety of materials, such as pine needles, oak leaves, lantana leaves, crop debris, or even plastic sheets.
6.9.8
Contour Farming
The up-and-down method of cultivation is widely used in mountainous regions. This method makes it easier for precipitation to pick up speed, which increases runoff and soil erosion. Cultural operations that are carried out over a slope, on the other hand, create furrows that produce natural ridges that accumulate runoff water and so decrease soil erosion. The resulting counter ridges create numerous little barriers in the runoff’s route, greatly enhancing the area’s detention capacity. It will give rainwater more time to soak into the ground after it falls. Additionally, there is a significant decrease in both the volume and speed of runoff water. Counter tillage increases crop yields because the furrows it creates soak up and store water that would otherwise be lost. Soil erosion can be reduced through the widespread use of terrace development and the construction of retaining walls made of stone or vegetative barriers.
6.9.9
Protected Cultivation of Vegetables at High Altitudes
It is more cost-effective to cultivate high-value crops like out-of-season vegetables, vegetable seeds, tropical fruits, medicinal herbs, and other plants in the hills than in the lowlands. Vegetables like peas, cucumbers, cauliflower, Brinjal, ginger, tomatoes, beans, radishes, carrots, and more can be grown “off-season” in Himachal Pradesh and Uttarakhand thanks to the region’s distinct “ecological niche” and improved marketing infrastructure. Vegetables grown on the hills are harvested at a time when they are not available in the traditional plain area, making off-season vegetable cultivation more lucrative. The term “protected cultivation methods” refers to a method of farming in which the immediate environment of the plants is carefully managed to meet the specific needs of the species being cultivated. A green home is merely a house that has had its roof replaced with transparent film or glass to allow sunlight to enter and promote plant growth. The greenhouse’s temperature
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rises because the sun’s heat is unable to escape. In colder climates, a natural increase in greenhouse air temperature is used to successfully cultivate crops. But in summertime due to the aforementioned issue, ventilation is essential to keep the temperature within the structure well below 30–35 °C (Singh and Sirohi 2004).
6.9.10 Water Harvesting and Recycling In mountainous areas, natural depressions can collect rainwater and reuse it to irrigate crops during drought. Although there are many benefits to water collection, doing it on a communal scale has its drawbacks. Soybean and wheat grain yields in the light soils in the mid hills of NWH were significantly boosted in comparison to rainfed conditions after supplemental irrigation using captured rainwater was applied. Supplemental watering of both crops resulted in a significant reduction in the cost per unit of water used. The residents in the Shivalik foothills of India have seen an improvement in their standard of living thanks to the increased accessibility of water. Dairy farming developed as a result of the surplus of forage because of the subsequent rise in milk output and the practice of stall feeding of animals. Most dairy farms are run by women, and more economic independence has resulted in better childcare, higher rates of education for girls, and more milk sales. Since more money was available, more resources could be put into crop cultivation, increasing output.
6.9.11 Conservation Contour Terracing (CCT) This is an important strategy for enhancing soil health and productivity. For effective resource management, a significant area may be designated as a CCT and built using the cut and fill method of land along the contour line according to the slopes.
6.9.12 Farm Mechanisation When compared to farming on the flat Indo-Gangetic plain, the stepped, marginal, and uneven fields, undulating geography, lack of skilled human resources, inadequate facilities for machine repair and maintenance, and inadequate local manufacturing facilities pose significant challenges for agricultural mechanisation in CA practices in the hills. When it comes to maximizing agricultural power utilisation, decreasing the need for manual labour, and lowering biomass tradeoffs, the CA in hill agriculture in the Himalayan region offers huge unrealised potential. There is significant future potential for reducing net energy consumption and increasing resource productivity under the CA system (Sims and Kienzle 2015). Many mountainous areas of India, especially the eastern Himalayas, saw heavy rainfall that exacerbated the preexisting weed problems. One of the most effective ways to reduce the overall cost of cultivation and get a head start on eliminating weeds is with the help of a mechanical weeder.
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Effect of Conservation Agriculture on Soil Health
6.10.1 Effect on Soil Physical Properties 6.10.1.1 Soil Aggregation, Aggregate Stability, and Soil Structure The stability of soil aggregates describes how well the soil can withstand environmental and anthropogenic disturbances. Aggregate size, total organic carbon content, and aggregate water stability all correlate moderately to highly with one another (Liu et al. 2019). Most crop residues are left on the soil surface once CA techniques are implemented, enhancing soil aggregation and aggregate stability. It also prevents particles near the surface from being eroded by splashing water. Soil aggregation and aggregate stability are aided by CA, which is characterised by little or no tillage and the retention of crop residue (Li et al. 2011). A sufficient amount of soil cover is necessary for CA because of the vital roles it plays in water retention, plant availability, and aggregate stability (Palm et al. 2014). Improved soil micropore content means better water retention and less loss of moisture through evaporation (Kassam et al. 2009; Palm et al. 2014). Tillage is a management method that has a major impact on both the topsoil and the subsoil (the rooting zone) structure of the soil. Vertisols in New South Wales, Australia, were studied by Hulugalle et al. (2004), who found that avoiding tillage and traffic when the soil was wet reduced structural damage to the soil. According to Gwenzi et al. (2009), reducing tillage operations on Zimbabwe’s Alfisols led to considerable increases in mean weight diameter (MWD) and water-stable aggregates (WSA). Soil structure is improved by crop rotation because of the return of agricultural residues, which alters the soil environment through the formation and dispersion of bio-pores and the dynamics of microbial communities (Ball et al. 2005). Despite the beneficial effects of cover crops on soil fertility, the heavy machinery used to sow and harvest the crop has been shown to degrade the structure of the field (Hulugalle et al. 2017a, b). 6.10.1.2 Soil Moisture Soil cover with crop leftovers and mulches is an important part of the CA’s strategy to save water. Crop residues left in the field improve infiltration and water retention. Mulches prevent the soil’s surface from freezing or thawing and considerably lessen surface evaporation, which is especially helpful in tropical and subtropical regions (Kodzwa et al. 2020). Lower surface evapo-transpiration losses due to surface residue cover (Jat et al. 2011) and increased soil moisture available to the standing crop are the primary mechanisms by which conservation agriculture reduces irrigation water use by 20–30% (Verhulst et al. 2010). 6.10.1.3 Soil Temperature The soil’s temperature is a key ephemeral physical feature that controls its physical, chemical, and biological activities, all of which have an impact on crop development and growth (Buchan 2000). It also affects the mechanisms involved in the exchange of gases between the atmosphere and the ground. Zero-tillage (ZT) soils with residue retention have the potential to have much lower surface-layer soil temperatures
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during the day in the summer as compared to conventionally tilled soils (Johnson and Hoyt 1999; Oliveira et al. 2001; Liebig et al. 2004; Malecka et al. 2012). Researchers have found that crop residue and other types of surface mulches affect soil temperature through altering the volumetric heat capacity, thermal conductivity, and thermal diffusivity of the soil (He et al. 2010).
6.10.1.4 Water Infiltration Total soil macropores and tillage techniques that change soil macropores through influencing the settling and consolidation of soil particles over time were found to be strongly and positively connected with hydraulic soil behaviour (Rasse et al. 2000). With more macropores created by zero tillage, hydraulic conductivity was greater than in conservation tillage (McGarry et al. 2000; Eynard et al. 2004). Because CA improves soil porosity and hydraulic conductivity with minimal soil disturbance, infiltration rates are increased (Mrabet 2007). Particularly useful in arid or semiarid climates, cover crops that are mulched over can increase water uptake and decrease evaporation from the soil surface. We found that the zero-till method resulted in a higher rate of infiltration than the conservation-till method (Liebig et al. 2004; Bhushan et al. 2007). Because of the increased infiltration rate brought on by rain, more soil water is made available in thick textured soils by CA techniques in no-till systems (Mrabet 2007). On the other hand, several studies have shown that no-till results in worse infiltration and hydraulic conductivity than regular tillage (Castellini et al. 2019). In a nutshell, CA lessens the rate of evaporation, runoff, and soil erosion caused by crop residue while increasing hydraulic conductivity and infiltration. Saturated and unsaturated hydraulic conductivities were found to be greater under zero-tillage circumstances than under conservation tillage, as reported by Azooz and Arshad (1996). Soil pore organisation and increased macropore continuity may account for the large increase in hydraulic conductivity observed in tilled plots compared to their unworked counterparts (Bhattacharyya et al. 2006). 6.10.1.5 Bulk Density of Soil Soil’s mass per unit volume is expressed as its bulk density (BD). A lower BD indicates a more permeable soil, which in turn allows for greater water infiltration. To add to that, it will help roots expand more rapidly than in soil with a higher BD. Soil compaction can be measured, in part, by its bulk density. For the most part, as soil is dug deeper, its BD will rise. As a result of leaving a lot of crop residue on the soil’s surface, conservation tillage dramatically alters the soil’s properties, particularly in the first few centimetres (Thomas et al. 2007; D’Haene et al. 2008). Plough pan forms under the furrow slice when conventional farming methods are used repeatedly because BD is higher in this horizon than CA. Soil compaction is mitigated gradually over time through the use of CA techniques, which reduce the intensity of tillage activities. Soil BD drops in CA, which may be attributable to improved aeration, root development, aggregation, and biomass (Salem et al. 2015). Bennett et al. (2017) found an increase in BD when wheel traffic occurred on the grey Vertisols of Auscott, Warren, Australia, despite row spacing or traffic system. The topsoil was the only place where growth was much higher. Soil BD was also
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dramatically reduced when legumes were incorporated via crop rotations rather than monocultures. Soil BD is significantly affected by residue retention in the first 10 cm of soil, although this effect is attenuated at deeper soil depths (10–20 cm) (BlancoCanqui and Lal 2007). Since the soil in no-till systems is not broken up by cultivation, it has a higher bulk density. Soil porosity increases in no-till systems may result from the incorporation of organic matter (from crop leftovers or cover crops) and the lack of or reduced disturbance of the soil (Alam et al. 2014). Soil bulk density (BD) is primarily affected by practices like tillage and residue retention at the surface. Infiltration is the process by which water percolates downward into the soil, which is a useful measure of soil quality (Thierfelder and Wall 2010). Infiltration rate, measured in millimetres per hour, is the rate at which water permeates the soil (Morgan 2009). This quality of soil is affected by the clay mineralogy and the quantity of sand, silt, and clay present in the soil. Water drains quickly through sandy soil because of its huge pore spaces, but it takes longer to drain through clayey soil due to the latter’s abundance of microscopic pores. Infiltration can be affected by the crop and soil management strategies implemented by altering the soil structure, surface sealing or crusting, and the soil organic matter. Very little crop residue is left as a result of poor management practices, which decreases the organic matter content of the soil and results in a weak soil structure. These soils don’t drain as well as others that have a better structure. The ability of Vertisols to retain water is aided by their fine texture and healthy soil structure (Vervoort et al. 2006). It has been observed that conservation agriculture (CA) measures help keep water in the soil or make it percolate more effectively (Morgan 2009).
6.10.2 Soil Chemical Properties 6.10.2.1 Soil Organic Matter Indicative of soil quality, SOM is crucial to soil fertility, productivity, and long-term viability (Chivenge et al. 2007). It keeps the soil aggregated and stable, and it gives crops the nutrients they need to grow. In most cases, SOM and nutrient availability are increased by CA practices by growing green manure or cover crops (GMCs) and retaining agricultural leftovers as surface mulch rather than burning them. Soil organic carbon levels typically shift in tandem with agronomic management approaches that affect production and the amount of crop residues returned to the soil (Campbell et al. 2001). The amount of residue applied affects the amount of organic carbon (SOC) in the soil. Since the rate of decomposition is higher in the semiarid tropics, a greater quantity of residue would be required to cause a shift in SOC under those conditions. This is clear from the abundance of high-quality manure and the gradual increase in SOC due to green manure application (Blaise 2006). When farmers in California go from conventional to conservation tillage, the soil isn’t disturbed nearly as much; therefore fewer greenhouse gas emissions from the crop are produced. Long-term field tests in CA found that keeping agricultural wastes on the soil’s surface increased organic carbon. Crop wastes, which are rich in
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carbon and nutrients, can be retained at the soil’s surface to boost OC levels through CA. Soil quality, OC, aggregation, conservation of soil, evaporation, and soil structure are all enhanced by no-till farming. Over the course of 11 years, organic matter (SOM) increased by 14% with no-tillage and by 3.3% with conventional tillage (Mrabet 2007). Soil organic carbon (SOC) levels tend to rise when crops rotated with legumes and no-till techniques are used.
6.10.2.2 Soil Nitrogen The distribution, mineralisation, transformation, and recycling of soil nutrients are all influenced by conservation tillage, crop residue management, and crop rotation (Verhulst et al. 2010). A greater amount of residue addition and input of nutrientcontaining organic material to the soil can boost soil organic carbon under CA techniques, which in turn can have a major effect on plant nutrient availability. As a result, plant nutrients are made more accessible and nutrient-rich soils are enhanced by how crop wastes are handled after harvest (Pheap et al. 2019). For nitrogen (N), while CA may increase overall N storage, it may reduce the amount of N that is available to plants, especially in the early stages of CA’s implementation, necessitating additional N fertiliser treatments to sustain output (Sithole and Magwaza 2019). As more agricultural residues are fed to the soil, the soil’s N mineralisation rate drops while the N immobilisation rate rises under CA (Page et al. 2020). 6.10.2.3 Soil Phosphorus Mrabet (2007) reported that with no-tillage, crop wastes are applied directly to the soil surface, causing less soil disturbance and resulting in less phosphate and potassium loss. As a result, nutrients like phosphorus and potassium were more concentrated near the soil’s surface than in tilled soil because P stratification in the soil is seen under various tillage systems, with the zero-tillage system being linked to a higher concentration of P due to preferential movement of P in the soil (Dorneles et al. 2015). Further, under CA, there is a greater concentration of P on the surface soil because of the incorporation of crop residues and fertiliser P with little P losses due to water erosion. As a result of bigger P addition from residue decomposition being kept on the soil surface, zero-tillage plots have a 15% higher total P content in the topsoil (5 cm) than conservation tillage plots. The reduction of soil erosion, the accumulation of labile forms of P derived from the presence of organic residues in the soil, and the effect of OM negative charges maintaining freely available phosphate are also benefits of no-tillage and reduced tillage over conservation tillage in terms of P availability. 6.10.2.4 Soil Potassium Concentration of potassium (K) in the top 5 and 25 cm of soil were 1.65 and 1.43 times higher for permanent bed planting with residue retention compared to CT, respectively. When comparing zero tillage to conservation tillage, Du Preez et al. (2001) found higher K levels, albeit this effect diminished with depth. Roldan et al. (2007) found that crop rotation had no influence on K concentrations.
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Comparatively, in conservation tillage, the available nutrients are reduced since the stover/straw is absorbed into the deep soil layer, resulting in quick breakdown and maybe also leaching of mineralised minerals in much deeper soil layers. Chelating these nutrients with organic matter in undisturbed soil improves soil nutrient status over a range of soil depths (Borie et al. 2006; Singh et al. 2014), ultimately leading to an overall higher NPK status. Similarly, Borie et al. (2006) and Wang et al. (2014) found that N, P, and K were all more available in the soil as a result of CA practices, while Malhi et al. (2011) found that P was more available, and Du Preez et al. (2001) found that K was more available.
6.10.2.5 Secondary and Micronutrients of the Soil The surface soil under no-tillage was found to have considerably more exchangeable Ca, Mg, and K than the ploughed soil, as reported by Rahman et al. (2008). Biochemical decomposition of organic crop leftovers at the soil surface is crucial as a nutritional material for the soil microbes, and it also improves the soil’s ability to provide and cycle nutrients. In comparison to conservation tillage, zero tillage with residue retentions typically results in increased micronutrient (Zn, Fe, Cu, and Mn) concentrations near the soil surface (Franzluebbers and Hons 1996). However, Govaerts et al. (2007) found that PB planting considerably increased the concentration of extractable Zn in the 0–5 cm layer compared to conservation tillage with full residue retention, while having no effect on the concentration of extractable Fe, Mn, or Cu. Du Preez et al. (2001) and Franzluebbers and Hons (1996) both reported findings that were consistent with each another.
6.10.3 Soil Microorganisms The greater accumulation of soil organic carbon under CA methods is mostly attributable to the elimination of tillage and the retention of residue. The organic carbon in CA system soils provide a food source for soil microorganisms, which in turn affects the growth of those microbes and, ultimately, the bacteria spread (Page et al. 2020). As the world’s population continues to rise at an alarming rate, so too are the associated food demands. Meeting these rising needs will require innovative approaches to soil management that preserve and boost biodiversity in order to increase food production. When compared to uncultivated soils and/or less disturbed soil, soils that have been subjected to intensive cultivation over extended periods of time have lower levels of microbial biodiversity. The foundational ideas and methods of CA have been extensively researched and have the ability to achieve the objective of safe productivity while also maintaining or sustaining soil biodiversity (Holland 2004). Soil fauna and flora, both harmful and helpful, undergo dramatic changes when tillage, crop residue, and crop rotation practices are altered (Anderson 2003). High levels of tillage have a corrosive effect on microbial diversity (Kladivko 2001; Jinbo et al. 2007). Climate, location, and both below- and aboveground environmental circumstances are primary determinants of the effect of soil tillage on microbiological parameters of soil.
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6.10.3.1 Soil Microbial Biomass Carbon (SMBC) The living component of SOM, microorganisms, is a sensitive indicator of shifts in soil processes/management practices and has connections to soil nutrient and energy dynamics (Lupwayi et al. 2012; Wright et al. 2008). Aggregate formation and breakdown may be affected by the quantity and persistence of binding agents, both of which are affected by soil tillage (Six et al. 2000; Somasundaram et al. 2018). Crop yields can be increased by the application of CA-based management methods because they reduce soil disturbance, which in turn stimulates soil microbial biomass and increases its metabolic rate (Hungria et al. 2009). The mean annual MBC was found to be highest in the ZT with residue and lowest in the CT without residue, as reported by Dong et al. (2009) and Silva et al. (2010), also observed that MBC and microbial biomass nitrogen were consistently higher (by up to 100%) under NT than CT. Soil microbial biomass (SMB) is thought to be primarily regulated by the rate of organic C input from crop biomass. The SMB has a high turnover rate in comparison to the total soil organic matter and so represents the soil’s capacity to store and cycle nutrients (C, N, P, and S) (Dick 1992; Carter et al. 1999). Higher levels of MBC and N were seen in plots where residue management was used, as opposed to plots where the tillage system was used (Spedding et al. 2004). When compared to conventionally tilled cotton, reduced tillage in Texas silt loams increased soil microbial biomass C by 11% as reported by Wright et al. (2008). Coupling values for the expansion of N-containing soil microorganism biomass were 62%. Also, compared to cultivating cotton alone, the C content of the soil microbial biomass increased when maize and cotton were rotated. Increased soil aeration, cooler and wetter conditions, less temperature and moisture swings, and higher carbon content in surface soil are the primary causes of the beneficial impacts of zero tillage and residue retention on soil microbial populations (Doran 1980). Motta et al. (2007) found that in cotton-based systems on silty loam in Alabama, USA, microbial biomass C in the surface layers was much higher with conservation tillage than with conventional tillage. 6.10.3.2 Enzymatic Activities of the Soil Enzymes in soil were often employed as a proxy for soil quality because of their central function in decomposing organic materials and recycling nutrients (Dick 1992; Velmourougane and Sahu 2013). Tillage, crop rotation, and residue management are just a few examples of management strategies that could have an impact on soil enzyme activities (Acosta-Martinez et al. 2003, 2004a, b) and found that surface-layer enzyme activity was significantly enhanced in conservation tillage systems. Due to the vertical distribution of organic residues and microbial activity, CA-based tillage increases enzymatic activities in the soil profile, positively altering soil enzymes that play a significant role in the catalysation of reactions obligatory for organic matter decomposition and nutrient cycling, as well as involved in energy transfer, improvement of environmental quality, and crop productivity (Dick 1992). Zero tillage increases dehydrogenase and phosphatase activity in the top 5 cm of soil, according to research by Roldan et al. (2007), while conservation tillage does not. Soil dehydrogenase enzyme activity was also shown to be 62% greater when using
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the permanent bed planting approach as opposed to the conservation tillage method. Acid phosphatase activities were higher in the treatment that combined organic residues with zero tillage, as observed by Hota et al. (2014). Mankolo et al. (2012) found that conservation tillage with cover crop rotation and the application of poultry manure had a favourable effect on all of the enzyme activities. As noted by Hota et al. (2014), when organic residues were included into a no-till system, acid phosphatase activities were higher than in systems managed with conventional tillage and no residue. The problem in the Himalayan regions may be solved with the help of conservation agriculture because it may eventually lead to greater carbon sequestration in the soil and better long-term soil health in the Himalayas. Therefore, conservation agriculture will bring even more benefits in the future, especially in hill regions.
6.11
Conclusion
It is evident that million farms in Himalayan region face the challenge of climate change head-on, and we are demanding more than ever from agriculture. It is not a simple challenge to provide more food for a growing population, improve the incomes of individuals working along the food chain, and maintain our soil and water resources with care. Climate-smart agriculture is the solution to all of these issues. It is a strategy for discovering new methods to adapt and thrive in the face of climate change. It is built on interdependent objectives: increasing agricultural productivity and incomes sustainably and equitably, helping the food system and livelihood become more resilient, and reducing greenhouse gas emissions from agriculture of all types and sizes can become more climate-smart by identifying and promoting sustainable farming practices and tools that use inputs more efficiently and effectively to grow more from less and by creating markets where farmers can sell any surplus and buy what they need. The impact of climate change on our food system is both a challenge and an opportunity to innovate and adapt. Researchers, legislators, scientists, and farmers must collaborate to provide our farmers with the technological policy and investment answers they require most.
References Acharya S, Charan G, Singh N, Srivastava RB (2012) Soil organic carbon sequestration of cold desert Ladakh. Range Manage Agrofor 33(1):79–82 Acosta-Martinez V, Zobeck TM, Gill TE, Kennedy AC (2003) Enzyme activities and microbial community structure in semiarid agricultural soils. Biol Fertil Soils 38(4):216–227 Acosta-Martinez V, Upchurch DR, Schubert AM, Porter D, Wheeler T (2004a) Early impacts of cotton and peanut cropping systems on selected soil chemical, physical, microbiological and biochemical properties. Biol Fertil Soils 40(1):44–54 Acosta-Martinez V, Zobeck TM, Allen V (2004b) Soil microbial, chemical and physical properties in continuous cotton and integrated crop–livestock systems. Soil Sci Soc Am J 68(6): 1875–1884
6
Conservation Agriculture for Soil Health and Carbon Sequestration in. . .
117
Alam MD, Islam M, Salahin N, Hasanuzzaman M (2014) Effect of tillage practices on soil properties and crop productivity in wheat-mungbean-rice cropping system under subtropical climatic conditions. Sci World J 2014:437283 Anderson TH (2003) Microbial eco-physiological indicators to asses soil quality. Agric Ecosyst Environ 98(1-3):285–293 Ashoka P, Meena RS, Gogoi N, Kumar S, Yadav GS, Layek J (2017) Green nanotechnology is a key for eco-friendly agriculture. J Clean Prod 142:4440 Azooz RH, Arshad MA (1996) Soil infiltration and hydraulic conductivity under long-term no-tillage and conventional tillage systems. Can J Soil Sci 76(2):143–152 Ball BC, Bingham I, Rees RM, Watson CA, Litterick A (2005) The role of crop rotations in determining soil structure and crop growth conditions. Can J Soil Sci 85(5):557–577 Banerjee SK (2014) Forest soil carbon stock along an altitudinal gradient in Darjeeling Himalayan region. Indian Forester 140(8):775–779 Bennett JM, Roberton SD, Jensen TA, Antille DL, Hall J (2017) A comparative study of conventional and controlled traffic in irrigated cotton: I. Heavy machinery impact on the soil resource. Soil Tillage Res 168:143–154 Bhattacharyya R, Prakash V, Kundu S, Gupta HS (2006) Effect of tillage and crop rotations on pore size distribution and soil hydraulic conductivity in sandy clay loam soil of the Indian Himalayas. Soil Tillage Res 86(2):129–140 Bhushan L, Ladha JK, Gupta RK, Singh S, Tirol-Padre A, Saharawat YS, Pathak H (2007) Saving of water and labor in a rice–wheat system with no-tillage and direct seeding technologies. Agron J 99(5):1288–1296 Blaise D (2006) Yield, boll distribution and fibre quality of hybrid cotton (Gossypium hirsutum L.) as influenced by organic and modern methods of cultivation. J Agron Crop Sci 192(4):248–256 Blanco-Canqui H, Lal R (2007) Impacts of long-term wheat straw management on soil hydraulic properties under no-tillage. Soil Sci Soc Am J 71(4):1166–1173 Borie F, Rubio R, Rouanet JL, Morales A, Borie G, Rojas C (2006) Effects of tillage systems on soil characteristics, glomalin and mycorrhizal propagules in a Chilean Ultisol. Soil Tillage Res 88(1-2):253–261 Bronick CJ, Lal R (2005) Manuring and rotation effects on soil organic carbon concentration for different aggregate size fractions on two soils in northeastern Ohio, USA. Soil Tillage Res 81(2): 239–252 Buchan GD (2000) Soil temperature regime. In: Smith KA, Mullins ED (eds) Soil and environmental analysis physical methods. Marcel Dekker, New York, pp 539–594 Campbell CA, Selles F, Lafond GP, Zentner RP (2001) Adopting zero tillage management: impact on soil C and N under long-term crop rotations in a thin Black Chernozem. Can J Soil Sci 81(2): 139–148 Carter MR, Gregorich EG, Angers DA, Beare MH, Sparling GP, Wardle DA, Voroney RP (1999) Interpretation of microbial biomass measurements for soil quality assessment in humid temperate regions. Can J Soil Sci 79(4):507–520 Castellini M, Fornaro F, Garofalo P, Giglio L, Rinaldi M, Ventrella D, Vonella AV (2019) Effects of no-tillage and conventional tillage on physical and hydraulic properties of fine textured soils under winter wheat. Water 11(3):484 Charan G, Bharti VK, Jadhav SE, Kumar S, Angchok D, Acharya S, Kumar P, Srivastava RB (2012) Altitudinal variations in soil carbon storage and distribution patterns in cold desert high altitude microclimate of India. Afr J Agric Res 7(47):6313–6319 Chaudhary JB, Thakur RC, Bhargava M, Sood RD (2000) Production potential and economics of maize (Zea mays)-based crop sequences on farmers’ fields. Indian J Agron 45(2):232–235 Chauhan SK, Sharma SC, Beri V, Yadav S, Gupta N (2010) Yield and carbon sequestration potential of wheat (Triticum aestivum)-poplar (Populus deltoides) based agri-silvicultural system. Indian J Agric Sci 80(2):129–135
118
A. Rai et al.
Chivenge PP, Murwira HK, Giller KE, Mapfumo P, Six J (2007) Long-term impact of reduced tillage and residue management on soil carbon stabilization: implications for conservation agriculture on contrasting soils. Soil Tillage Res 94(2):328–337 Cusack DF, Chadwick OA, Hockaday WC, Vitousek PM (2012) Mineralogical controls on soil black carbon preservation. Glob Biogeochem Cycles 26:2 D’Haene K, Vermang J, Cornelis WM, Leroy BL, Schiettecatte W, De Neve S, Hofman G (2008) Reduced tillage effects on physical properties of silt loam soils growing root crops. Soil Tillage Res 99(2):279–290 Dalal RC, Allen DE, Wang WJ, Reeves S, Gibson I (2011) Organic carbon and total nitrogen stocks in a Vertisol following 40 years of no-tillage, crop residue retention and nitrogen fertilisation. Soil Tillage Res 112(2):133–139 Dar DA, Sahu P (2017) Assessment of soil organic carbon stock in five forest types of Northern Kashmir and Himalaya. Int J Theor Appl Sci 10(1):86–92 Dar JA, Sundarapandian SM (2013) Soil organic carbon stock assessment in two temperate forest types of Western Himalaya of Jammu and Kashmir, India. For Res 3(114):2 Devi SB, Sherpa SSSS (2019) Soil carbon and nitrogen stocks along the altitudinal gradient of the Darjeeling Himalayas, India. Environ Monit Assess 191:1–18 Dick RP (1992) A review: long-term effects of agricultural systems on soil biochemical and microbial parameters. Agric Ecosyst Environ 40(1-4):25–36 Dong W, Hu C, Chen S, Zhang Y (2009) Tillage and residue management effects on soil carbon and CO2 emission in a wheat–corn double-cropping system. Nutr Cycl Agroecosyst 83(1):27–37 Doran JW (1980) Soil microbial and biochemical changes associated with reduced tillage. Soil Sci Soc Am J 44(4):765–771 Dorneles EP, Lisboa BB, Abichequer AD, Bissani CA, Meurer EJ, Vargas LK (2015) Tillage, fertilization systems and chemical attributes of a Paleudult. Sci Agric 72:175–186 Du Preez CC, Steyn JT, Kotze E (2001) Long-term effects of wheat residue management on some fertility indicators of a semi-arid Plinthosol. Soil Tillage Res 63(1-2):25–33 Eynard A, Schumacher TE, Lindstrom MJ, Malo DD, Kohl RA (2004) Wettability of soil aggregates from cultivated and uncultivated Ustolls and Usterts. Soil Res 42(2):163–170 Franzluebbers AJ, Hons FM (1996) Soil-profile distribution of primary and secondary plantavailable nutrients under conventional and no tillage. Soil Tillage Res 39(3-4):229–239 Gangopadhyay S, Bhattacharyya T, Banerjee S (2020) Forest soil carbon in relation to elevation in Sikkim. Proc Indian Natl Sci Acad 86(4):1331–1339 Goswami S, Verma KS, Kaushal R (2014) Biomass and carbon sequestration in different agroforestry systems of a Western Himalayan watershed. Biol Agric Hortic 30(2):88–96 Gunady MG, Biswas W, Solah VA, James AP (2012) Evaluating the global warming potential of the fresh produce supply chain for strawberries, romaine/cos lettuces (Lactuca sativa), and button mushrooms (Agaricus bisporus) in Western Australia using life cycle assessment (LCA). J Clean Prod 28:81–87 Guo LB, Gifford RM (2002) Soil carbon stocks and land use change: a meta analysis. Glob Chang Biol 8(4):345–360 Gupta MK, Panwar VP, Manoj K (2018) Carbon sequestration: organic carbon stock in the soils along with elevation gradient under different land uses in Uttarakhand State. Indian Forester 144(2):139–145 Gwenzi W, Gotosa J, Chakanetsa S, Mutema Z (2009) Effects of tillage systems on soil organic carbon dynamics, structural stability and crop yields in irrigated wheat (Triticum aestivum L.)– cotton (Gossypium hirsutum L.) rotation in semi-arid Zimbabwe. Nutr Cycl Agroecosyst 83(3): 211–221 He J, Li H, Kuhn NJ, Wang Q, Zhang X (2010) Effect of ridge tillage, no-tillage, and conventional tillage on soil temperature, water use, and crop performance in cold and semi-arid areas in Northeast China. Soil Res 48(8):737–744 Himalayan Resources (2012). Retrieved from https://chimalaya.org/2012/08/27/himalayanresources-issuesand-challenges
6
Conservation Agriculture for Soil Health and Carbon Sequestration in. . .
119
Hobbs PR, Sayre K, Gupta R (2008) The role of conservation agriculture in sustainable agriculture. Philos Trans R Soc B Biol Sci 363(1491):543–555 Holland JM (2004) The environmental consequences of adopting conservation tillage in Europe: reviewing the evidence. Agric Ecosyst Environ 103(1):1–25 Hota R, Jena AK, Narayana KL (2014) Effect of inorganic and organic amendments on yield of cocoyam (Colocasia esculenta), and on soil properties. World J Agric Res 2(2):70–81 Hulugalle NR, Nehl DB, Weaver TB (2004) Soil properties, and cotton growth, yield and fibre quality in three cotton-based cropping systems. Soil Tillage Res 75(2):131–141 Hulugalle NR, Weaver TB, Finlay LA (2017a) Fallow soil evaporation in a grey Vertisol under contrasting wheat stubble management practices in cotton cropping systems. Soil Tillage Res 165:41–45 Hulugalle NR, Weaver TB, Finlay LA (2017b) Soil structure in permanent beds under irrigated cotton-based cropping systems in a Vertisol. Soil Tillage Res 165:107–112 Hungria M, Franchini JC, Brandao-Junior O, Kaschuk G, Souza RA (2009) Soil microbial activity and crop sustainability in a long-term experiment with three soil-tillage and two crop-rotation systems. Appl Soil Ecol 42(3):288–296 Jat ML, Gathala MK, Ladha JK, Saharawat YS, Jat AS, Kumar V, Gupta R (2009) Evaluation of precision land leveling and double zero-till systems in the rice–wheat rotation: water use, productivity, profitability and soil physical properties. Soil Tillage Res 105(1):112–121 Jat ML, Malik RK, Saharawat YS, Gupta R, Mal B, Paroda R (2011) Regional dialogue on conservation agriculture on South Asia: proceedings and recommendations Jayaraman S, Dalal RC, Patra AK, Chaudhari SK (eds) (2021) Conservation agriculture: a sustainable approach for soil health and food security: conservation agriculture for sustainable agriculture. Springer, Cham Jinbo Z, Changchun S, Shenmin W (2007) Dynamics of soil organic carbon and its fractions after abandonment of cultivated wetlands in northeast China. Soil Tillage Res 96(1-2):350–360 Johnson AM, Hoyt GD (1999) Changes to the soil environment under conservation tillage. Hortic Technol 9(3):380–393 Kanime N, Kaushal R, Tewari SK, Raverkar KP, Chaturvedi S, Chaturvedi OP (2013) Biomass production and carbon sequestration in different tree-based systems of Central Himalayan Tarai region. For Trees Livelihoods 22(1):38–50 Kassam A, Friedrich T (2009) Nutrient management in conservation agriculture: a biologicallybased approach to sustainable production intensification. In Proc. 7th Conservation Agric. Conf Kassam A, Friedrich T, Shaxson F, Pretty J (2009) The spread of conservation agriculture: justification, sustainability and uptake. Int J Agric Sustain 7(4):292–320 Kladivko EJ (2001) Tillage systems and soil ecology. Soil Tillage Res 61(1-2):61–76 Kodzwa JJ, Gotosa J, Nyamangara J (2020) Mulching is the most important of the three conservation agriculture principles in increasing crop yield in the short term, under sub humid tropical conditions in Zimbabwe. Soil Tillage Res 197:104515 Kumar R, Rawat KS, Singh J, Singh A, Rai A (2013) Soil aggregation dynamics and carbon sequestration. J Appl Nat Sci 5(1):250–267 Kuotsu K, Das A, Lal R, Munda GC, Ghosh PK, Ngachan SV (2014) Land forming and tillage effects on soil properties and productivity of rainfed groundnut (Arachis hypogaea L.)–rapeseed (Brassica campestris L.) cropping system in northeastern India. Soil Tillage Res 142:15–24 Lal R (2001) Potential of desertification control to sequester carbon and mitigate the greenhouse effect. Clim Chang 51(1):35–72 Lal R (2002) Soil carbon dynamics in cropland and rangeland. Environ Pollut 116(3):353–362 Lal R (2004) Soil carbon sequestration impacts on global climate change and food security. Science 304(5677):1623–1627 Lal R (2013) Climate–resilient agriculture and soil organic carbon. Indian J Agron 58(4):440–450 Lal R, Kimble JM (1997) Conservation tillage for carbon sequestration. Nutr Cycl Agroecosyst 49(1):243–253
120
A. Rai et al.
Lal R, Follett RF, Kimble J, Cole CV (1999) Managing US cropland to sequester carbon in soil. J Soil Water Conserv 54(1):374–381 Li LL, Huang GB, Zhang RZ, Bill B, Guangdi L, Kwong YC (2011) Benefits of conservation agriculture on soil and water conservation and its progress in China. Agric Sci China 10(6): 850–859 Liebig MA, Tanaka DL, Wienhold BJ (2004) Tillage and cropping effects on soil quality indicators in the northern Great Plains. Soil Tillage Res 78(2):131–141 Liu Q, Liu B, Ambus P, Zhang Y, Hansen V, Lin Z, Xie Z (2016) Carbon footprint of rice production under biochar amendment–a case study in a Chinese rice cropping system. GCB Bioenergy 8(1):148–159 Liu M, Han G, Zhang Q (2019) Effects of soil aggregate stability on soil organic carbon and nitrogen under land use change in an erodible region in Southwest China. Int J Environ Res Public Health 16(20):3809 Lupwayi NZ, Lafond GP, Ziadi N, Grant CA (2012) Soil microbial response to nitrogen fertilizer and tillage in barley and corn. Soil Tillage Res 118:139–146 Malecka I, Blecharczyk A, Sawinska Z, Dobrzeniecki T (2012) The effect of various long-term tillage systems on soil properties and spring barley yield. Turk J Agric For 36(2):217–226 Malhi SS, Nyborg M, Goddard T, Puurveen D (2011) Long-term tillage, straw management and N fertilization effects on quantity and quality of organic C and N in a Black Chernozem soil. Nutr Cycl Agroecosyst 90(2):227–241 Malik SH, Kumar K, Kumar A (2018) Agricultural sustainability in North-Western Himalayan Region: issues and challenges Mankolo R, Reddy C, Senwo Z, Nyakatawa E, Sajjala S (2012) Soil biochemical changes induced by poultry litter application and conservation tillage under cotton production systems. Agronomy 2:187–198 McGarry D, Bridge BJ, Radford BJ (2000) Contrasting soil physical properties after zero and traditional tillage of an alluvial soil in the semi-arid subtropics. Soil Tillage Res 53(2):105–115 Meena H, Meena RS (2017) Assessment of sowing environments and bio-regulators as adaptation choice for clusterbean productivity in response to current climatic scenario. Bangladesh J Bot 46(1):241–244 Meena RS, Yadav RS (2014) Phenological performance of groundnut varieties under sowing environments in hyper arid zone of Rajasthan, India. J Appl Nat Sci 6(2):344–348 Morgan RPC (2009) Soil erosion and conservation. Wiley, Hoboken Motta AC, Wayne Reeves D, Burmester C, Feng Y (2007) Conservation tillage, rotations, and cover crop affecting soil quality in the Tennessee valley: particulate organic matter, organic matter, and microbial biomass. Commun Soil Sci Plant Anal 38(19-20):2831–2847 Mrabet R (2007) Conservation agriculture in Morocco: a research review. In: The Proceedings of the International Workshop on Conservation Agriculture for Sustainable Land Management to Improve the Livelihood of People in Dry Areas, pp 183–208 Ntinas GK, Neumair M, Tsadilas CD, Meyer J (2017) Carbon footprint and cumulative energy demand of greenhouse and open-field tomato cultivation systems under Southern and Central European climatic conditions. J Clean Prod 142:3617–3626 Oliveira JCM, Timm LC, Tominaga TT, Cassaro FAM, Reichardt K, Bacchi OOS, Câmara GDS (2001) Soil temperature in a sugar-cane crop as a function of the management system. Plant Soil 230(1):61–66 Page KL, Dalal RC, Reeves SH, Wang WJ, Jayaraman S, Dang YP (2020) Changes in soil organic carbon and nitrogen after 47 years with different tillage, stubble and fertiliser management in a Vertisol of north-eastern Australia. Soil Res 58(4):346–355 Palm C, Blanco-Canqui H, DeClerck F, Gatere L, Grace P (2014) Conservation agriculture and ecosystem services: an overview. Agric Ecosyst Environ 187:87–105 Panwar VP, Gupta MK (2013) Soil organic carbon pool under different forest types in Himachal Pradesh. Int J Farm Sci 3(2):81–89
6
Conservation Agriculture for Soil Health and Carbon Sequestration in. . .
121
Paustian K, Elliott ET, Peterson GA, Killian K (1995) Modelling climate, CO2 and management impacts on soil carbon in semi-arid agroecosystems. Plant Soil 187(2):351–365 Pheap S, Lefevre C, Thoumazeau A, Leng V, Boulakia S, Koy R, Tivet F (2019) Multi-functional assessment of soil health under Conservation Agriculture in Cambodia. Soil Tillage Res 194: 104349 Pishgar-Komleh SH, Ghahderijani M, Sefeedpari P (2012) Energy consumption and CO2 emissions analysis of potato production based on different farm size levels in Iran. J Clean Prod 33:183–191 Poeplau C, Don A, Vesterdal L, Leifeld J, Van Wesemael BAS, Schumacher J, Gensior A (2011) Temporal dynamics of soil organic carbon after land-use change in the temperate zone–carbon response functions as a model approach. Glob Chang Biol 17(7):2415–2427 Prasad R, Shivay YS, Kumar D, Sharma SN (2006) Learning by doing exercise in soil fertility-a practical manual for soil fertility. IARI, New Delhi Pratibha G, Srinivas I, Rao KV, Raju BMK, Thyagaraj CR, Korwar GR, Srinivasarao C (2015) Impact of conservation agriculture practices on energy use efficiency and global warming potential in rainfed pigeonpea–castor systems. Eur J Agron 66:30–40 Rahman MH, Okubo A, Sugiyama S, Mayland HF (2008) Physical, chemical and microbiological properties of an Andisol as related to land use and tillage practice. Soil Tillage Res 101(1-2): 10–19 Rasse DP, Smucker AJ, Santos D (2000) Alfalfa root and shoot mulching effects on soil hydraulic properties and aggregation. Soil Sci Soc Am J 64(2):725–731 Rathore AC, Kumar A, Tomar JMS, Jayaprakash J, Mehta H, Kaushal R, Alam NM, Gupta AK, Raizada A, Chaturvedi OP (2018) Predictive models for biomass and carbon stock estimation in Psidium guajava on bouldery riverbed lands in North-Western Himalayas, India. Agrofor Syst 92:171–182 Roldan A, Salinas-Garcia JR, Alguacil MM, Caravaca F (2007) Soil sustainability indicators following conservation tillage practices under subtropical maize and bean crops. Soil Tillage Res 93(2):273–282 Salem HM, Valero C, Muñoz MÁ, Rodríguez MG, Silva LL (2015) Short-term effects of four tillage practices on soil physical properties, soil water potential, and maize yield. Geoderma 237: 60–70 Silva AP, Babujia LC, Franchini JC, Souza RA, Hungria M (2010) Microbial biomass under various soil-and crop-management systems in short-and long-term experiments in Brazil. Field Crop Res 119(1):20–26 Sims B, Kienzle J (2015) Mechanization of conservation agriculture for smallholders: issues and options for sustainable intensification. Environments 2(2):139–166 Singh B, Sirohi NPS (2004) Protected cultivation of vegetables in India: problems and future prospects. In: International Symposium on Greenhouses, Environmental Controls and In-house Mechanization for Crop Production in the Tropics 710, pp 339–342 Singh KP, Prakash V, Srinivas K, Srivastva AK (2008) Effect of tillage management on energy-use efficiency and economics of soybean (Glycine max) based cropping systems under the rainfed conditions in North-West Himalayan Region. Soil Tillage Res 100(1-2):78–82 Singh RK, Kumar DP, Singh P, Solanki MK, Srivastava S, Kashyap PL, Arora DK (2014) Multifarious plant growth promoting characteristics of chickpea rhizosphere associated Bacilli help to suppress soil-borne pathogens. Plant Growth Regul 73(1):91–101 Sinha AK, Ghosh A, Dhar T, Bhattacharya PM, Mitra B, Rakesh S, Menzies NW (2019) Trends in key soil parameters under conservation agriculture-based sustainable intensification farming practices in the Eastern Ganga Alluvial Plains. Soil Res 57(8):883–893 Sithole NJ, Magwaza LS (2019) Long-term changes of soil chemical characteristics and maize yield in no-till conservation agriculture in a semi-arid environment of South Africa. Soil Tillage Res 194:104317
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Six JΑΕΤ, Elliott ET, Paustian K (2000) Soil macroaggregate turnover and microaggregate formation: a mechanism for C sequestration under no-tillage agriculture. Soil Biol Biochem 32(14):2099–2103 Smith P, Martino D, Cai Z, Gwary D, Janzen H, Kumar P, Smith J (2008) Greenhouse gas mitigation in agriculture. Philos Trans R Soc B Biol Sci 363(1492):789–813 Soleimanzadeh H (2013) Effect of seed priming on germination and yield of corn. Int J Agric Crop Sci 5(4):366–369 Somasundaram J, Lal R, Sinha NK, Dalal R, Chitralekha A, Chaudhary RS, Patra AK (2018) Cracks and potholes in vertisols: characteristics, occurrence, and management. Adv Agron 149: 93–159 Somasundaram J, Sinha NK, Dalal RC, Lal R, Mohanty M, Naorem AK, Chaudhari SK (2020) No-till farming and conservation agriculture in South Asia–issues, challenges, prospects and benefits. Crit Rev Plant Sci 39(3):236–279 Soni P, Taewichit C, Salokhe VM (2013) Energy consumption and CO2 emissions in rainfed agricultural production systems of Northeast Thailand. Agric Syst 116:25–36 Spedding TA, Hamel C, Mehuys GR, Madramootoo CA (2004) Soil microbial dynamics in maizegrowing soil under different tillage and residue management systems. Soil Biol Biochem 36(3): 499–512 Subbulakshmi V, Kaushal R, Tomar JMS, Alam NM, Jayparkash J, Mehta H, Gupta AK, Rathore AC, Chaturvedi OP, Mishra PK (2020) Biomass and carbon stock estimation in woody grass (Dendrocalamus strictus L.) in Doon Valley, India Tandon SK, Singh S (2009) Energy balance in conservation agriculture and conventional farming: a comparison. In: Proceedings of 4th world congress on conservation agriculture, pp 4–7 Thierfelder C, Wall PC (2010) Rotation in conservation agriculture systems of Zambia: effects on soil quality and water relations. Exp Agric 46(3):309–325 Thomas GA, Dalal RC, Standley J (2007) No-till effects on organic matter, pH, cation exchange capacity and nutrient distribution in a Luvisol in the semi-arid subtropics. Soil Tillage Res 94(2): 295–304 Tjandra TB, Ng R, Yeo Z, Song B (2016) Framework and methods to quantify carbon footprint based on an office environment in Singapore. J Clean Prod 112:4183–4195 Tubiello FN, Cóndor-Golec RD, Salvatore M, Piersante A, Federici S, Ferrara A, Prosperi P (2015) Estimating greenhouse gas emissions in agriculture: a manual to address data requirements for developing countries. Estimating greenhouse gas emissions in agriculture: a manual to address data requirements for developing countries Velmourougane K, Sahu A (2013) Impact of transgenic cottons expressing cry1Ac on soil biological attributes. Plant Soil Environ 59(3):108–114 Veni VG, Srinivasarao C, Reddy KS, Sharma KL, Rai A (2020) Soil health and climate change. In: Climate change and soil interactions. Elsevier, Amsterdam, pp 751–767 Verhulst N, Govaerts B, Verachtert E, Castellanos-Navarrete A, Mezzalama M, Wall P, Sayre KD (2010) Conservation agriculture, improving soil quality for sustainable production systems. In: Advances in soil science: food security and soil quality. CRC Press, Boca Raton, pp 137–208 Verma A, Kaushal R, Alam NM, Mehta H, Chaturvedi OP, Mandal D, Tomar JMS, Rathore AC, Singh C (2014) Predictive models for biomass and carbon stocks estimation in Grewia optiva on degraded lands in western Himalaya. Agrofor Syst 88:895–905 Vervoort RW, Minasny B, Cattle SR (2006) The hydrology of Vertosols used for cotton production: II. Pedotransfer functions to predict hydraulic properties. Soil Res 44(5):479–486 Wang Q, Lu C, Li H, He J, Sarker KK, Rasaily RG, Mchugh ADJ (2014) The effects of no-tillage with subsoiling on soil properties and maize yield: 12-year experiment on alkaline soils of Northeast China. Soil Tillage Res 137:43–49 Wright AL, Hons FM, Lemon RG, McFarland ML, Nichols RL (2008) Microbial activity and soil C sequestration for reduced and conventional tillage cotton. Appl Soil Ecol 38(2):168–173 Xue JF, Pu C, Liu SL, Zhao X, Zhang R, Chen F, Zhang HL (2016) Carbon and nitrogen footprint of double rice production in Southern China. Ecol Indic 64:249–257
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Yadav GS, Lal R, Meena RS, Datta M, Babu S, Das A, Saha P (2017a) Energy budgeting for designing sustainable and environmentally clean/safer cropping systems for rainfed rice fallow lands in India. J Clean Prod 158:29–37 Yadav RP, Bisht JK, Bhatt JC (2017b) Biomass, carbon stock under different production systems in the mid hills of Indian Himalaya. Trop Ecol 58(1):15–21 Yadav GS, Babu S, Layek J, Singh R, Das R, Das A (2021) Conservation agriculture in the North Eastern Himalayan Eco-Region of India. In: Conservation agriculture: a sustainable approach for soil health and food security. Springer, Singapore, pp 223–237
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Establishing Linkages of Soil Carbon Dynamics with Microbes Mediated Ecological Restoration of Degraded Ecosystems in Indian Himalayan Region Supriya Pandey, Sumit Rai, Anand Singh Bisht, and Ashish Rai
Abstract
The Himalayan region is one of the planet’s most distinctive mountain ecosystems as a result of its geography, altitude, and biological diversity. Mountain ecosystems throughout the world are being affected by overuse of resources, widespread land conversion, and climate change. Despite their rich biodiversity and diverse ecosystems, mountains are facing an increasing pressure from land conversion, industrialization, and climate change. Between 2000 and 2025, food production in developing nations, now estimated at 1223 million metric tonnes (Mt), should increase by 778 million Mt, or 2.5% annually, to fulfill the demands of an expanding population and an anticipated change in diet. SOC is regarded as the most important indicator of soil quality and agricultural sustainability. Focusing on improving soil quality and agronomic productivity per unit area through an increase in the soil organic carbon pool provides the most additional advantages among all the others. Adopting suggested management techniques on arable lands and degraded soils would improve soil quality. Cropland deterioration is accelerated by increased agricultural activity, and restoration has been controlled by modifying the vegetation on the land. However, little is known about the crucial microbiome that fuels the degradation of organic materials linked to plants during vegetation regeneration. Ecological rehabilitation of deteriorated areas has gradually increased public awareness and sparked widespread concern around the
S. Pandey · S. Rai (✉) · A. S. Bisht Centre for Environment Assessment and Climate Change, G.B. Pant National Institute of Himalayan Environment, Almora, India A. Rai Krishi Vigyan Kendra, Parsauni East Champaran, Dr. Rajendra Prasad Central Agricultural University, Pusa, Bihar, India # The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Mishra et al. (eds.), Soil Carbon Dynamics in Indian Himalayan Region, https://doi.org/10.1007/978-981-99-3303-7_7
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world. Thus, this chapter will focus on the role of microbes and their functioning in enhancing SOC and in the restoration of the degraded agricultural ecosystems. Keywords
Soil carbon · Microbes · Ecological restoration · Deterioration · Rehabilitation
7.1
Introduction
Understanding the global pattern of land degradation is crucial because land degradation has emerged as one of the most critical environmental issues that human society is now dealing with. Ecological restoration efforts strive to establish the bare necessities for creating dependable biological communities and ecological processes that can deliver a variety of ecosystem services. Mountainous ecosystems offer a variety of crucial ecosystem commodities and services. In India and throughout the world, land conversion and degradation are highly important environmental issues. Despite their rich biodiversity and diverse ecosystems, mountains are facing an increasing pressure from land conversion, industrialization, and climate change (Kanwal et al. 2019). Land conversion’s causes, patterns, and effects are all intricately linked. Land conversion can be caused by a variety of factors, including population, individual preferences, legislation, development activities, and economic factors. These factors also have a significant impact on environmental deterioration. Growing population, rising food consumption, and developmental needs put a pressure on the conversion of forests to agricultural land. The microbial stoichiometry, nutrient activity, and soil organic carbon (SOC) supply may all be significantly impacted by the conversion of forests (Zhao et al. 2022). The loss or removal of land cover contributes to this category of land degradation by allowing organic materials and sensitive soil to be washed or blown away. Similar impacts, such as decreased land productivity, may result from salinization. For a very long time, restoring degraded land has been a top priority. In 1980, India introduced the Society Forestry initiative in an effort to reclaim waste and damaged land as well as to satisfy global biomass demands. The Indian Himalaya is made up of 59 million ha of land, of which 7.3 million ha are community lands, 13.5 million ha are government forests, and 1.2 million ha are private agricultural holdings that have been abandoned. One of the world’s biodiversity hotspots, the Himalayas, is threatened by land degradation. The main ecological concern today is the stabilization of the atmosphere’s rising CO2 concentration. Since soil is the greatest organic carbon sink on the planet, sequestering atmospheric carbon in the soil through plantbased photosynthesis is a feasible approach for reducing global warming. The local, national, regional, and global components of sustainable development all emphasize the importance on the rehabilitation of degraded lands in the tropics. The sustainable regeneration of a damaged landscape necessitates the adaptation of multiple land uses, including agriculture, tree planting, and protected landscape regions. The global C cycle, atmospheric chemistry, radioactive forcing, and ecosystem services
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are all moderated by the world’s soils, a vast reservoir of reactive carbon; hence, soil C sequestration is crucial for keeping global warming within 2°C. Soil carbon management will therefore become a more crucial approach over the ensuing decades due to its numerous additional advantages as a sustainable response to climate change (Singh et al. 2020) Like other mountain ecosystems, the IHR’s inhabitants rely significantly on local natural resources and primary sector production from activities like agriculture, forestry, cattle, and others as a source of livelihoods. Due to the dependence of an ever-increasing population on limited resources, the lack of practical technology to address mountain-specific challenges, and the increased production to fulfill demand, resources are being depleted along with farmers’ marginalization, which ultimately leads to poverty (Samal et al. 2003). The area is under developed despite having abundant biological and cultural resources. Numerous studies conducted in the area, which focused on development interventions or efforts, show the unscientific exploitation of resources that is causing environmental deterioration, according to report published on 2022, Forest Survey report 2021 reported increase of 2261 km2 in the total forest and tree cover of the country in last 2 years, state forest report claims that the difference in forest cover in last 2 years would accurately represent changes on the ground. In India and around the world, land conversion and degradation are major environmental issues. Land conversion has a number of interconnected causes, trends, and effects. Land conversion has effects including environmental deterioration that are generally attributed to factors like population, human preferences, legislation, development activities, and economic concerns (Navarro-Pedreño et al. 2021). The pressure to use forests for agriculture is largely a result of the expanding population and needs for development. Since the early 1980s, restoration of degraded soil has been a top priority. India introduced the Social Forestry Programme in 1980, followed by the more participative Joint Forest Management (JFM) program, to reclaim degraded and waste land and to meet biomass demand (Sundar 2017). A total of 59 million ha of land make up the Indian Himalaya, of which 7.3 million ha are degraded community lands, 13.5 million ha are degraded government forests, and 1.2 million ha are private agricultural fields that have been abandoned. In the uplands, the effects of soil degradation are felt locally as a lack of food and fodder, as well as far away in the Indo-Gangetic lowlands where floodings damage crops, properties, and human life. Various anthropogenic activities cause the imbalance in environmental conditions, thus leading to the dominance of humans over the Earth’s natural resources. The lands, agricultural fields, and the groundwater all get contaminated by the regular use of toxic chemicals like organo-phosphorus, toluene, benzene, organo-chlorides, neo-nicotenoids, polycyclic aromatic hydrocarbons (PAHs), and DDT. All these factors play an important role in land and soil depletion that ultimately leads to crop and yield decrease. There are several conventional techniques (chemical treatment process) available to treat some of these chemicals; however, due to their cost and end products that are in turn toxic, these techniques fail to completely eradicate these chemicals (Juwarkar et al. 2014). Thus, urgency for
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developing new technologies that are cost-effective and eco-friendly is pressing. Despite the fact that physical and chemical approaches have been practiced for decades, they still suffer from several drawbacks. These include high processing costs, increased requirements of reagents, and the undesirable generation of secondary pollutants (Dangi et al. 2019). In this context, microbes have tremendous potential to cater to the need and holds hope for environmental protection, management, and ecorestoration (Hatti-Kaul et al. 2007; Azadi and Ho 2010). One of the best considered technologies to treat these toxic chemicals is the process of bioremediation or the biological remediation. Biological remediation in the form of microbe-based treatment is one of the costeffective, eco-friendly, and socially acceptable way to remove pollutants such as heavy metals (Iravani and Varma 2020), pesticides (Rodríguez et al. 2020), and hydrocarbons (Ławniczak et al. 2020) from the environment. Thus, bioremediation may work as an alternative to restore the balance and create a clean environment to live, as well as one of the most effective tools to manage a polluted site or an area. The use of microorganisms is considered as the best, easy, and the most costeffective manner to clean up a contaminated area (Sharma et al. 2019). Such microorganisms have a metabolic pathway where they utilize the contaminant as a source of food and energy and hence detoxify the contaminated area or a site. Microbes make use of heavy metals and trace elements as terminal electron acceptors from which they acquire the needed energy to detoxify metals via enzymatic and nonenzymatic processes (Dixit et al. 2015).
7.2
Impact of Vegetation Type on Carbon Storage
Vegetation is the only source of carbon for the soil in terrestrial ecosystems. From local to national, regional, and global perspectives of sustainable development, rehabilitation of degraded lands in the tropics is vital (Coleman et al. 2019). According to the Special Report on Climate Change and Land of IPCC, one of the world’s biodiversity hot places, the Himalaya, is threatened by land degradation. Local land degradation may result from the expansion and intensification of biomass production, such as by irrigation, fertilizer additions, or monoculture energy crops. Inadequate land management intensification results in salinization from irrigation and other types of land degradation. When afforestation and reforestation take place on previously degraded land, there are opportunities to restore and rehabilitate areas with potential significance. Since soils are the world’s greatest organic carbon sink, it is possible to avoid global warming by sequestering atmospheric carbon in soils through plant-based photosynthesis. Inadequate soil management and changes in land use result in annual carbon dioxide losses between 0.7 and 2.1 Pg C (Houghton et al. 2012). Land use change includes changes to other types of land cover, such as intensifying agricultural management or other changes in the farming system. The combination of social, institutional, and environmental factors results in changes in land use and cover. Conversion of natural grassland and forest to agriculture might cause the loss of up to 40% of native C stocks (Yellajosula et al.
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Table 7.1 Significant patterns of land use distribution in the Indian Himalayan region (adapted from: NRSC 2010; FSI 2011) States/regions Jammu and Kashmir Himachal Pradesh Uttarakhand Sikkim West Bengal hills Meghalaya Assam hills Tripura Mizoram Manipur Nagaland Arunachal Pradesh India
Geographical areas (km2) 222,236
Agricultural land cover 4.7
Presence of area under Wastelands Forests 64.6 9.6
55,673 53,483 7,096,743 3149 22,429 15,322 10,486 21,081 22,327 16,579 88,743 3,287,263
14.5 12.5 16.1 43.5 48.2 10.5 29.6 21.2 7.3 38.4 3.5 55.8
56.9 30.1 50.3 2.2 44.2 56.6 12.2 19.3 58.0 50.7 21.9 20.2
25.8 44.8 45.0 68.7 69.5 79.8 67.4 83.0 75.8 80.5 81.3 20.6
2020). According to research, losses of soil organic carbon (SOC) brought on by deforestation resulted in a 7.7% decline in soil carbon in tropical forests (from 164.0 to 151.3 Pg C) between 1990 and 2007 (Scharlemann et al. 2014). Substantial changes in the climate and land use over the past few decades have contributed to SOC depletion and a decreasing trend in productivity, related to how the tropical climate region of the Indian Himalayan mountain range is largely covered in forest as shown in Table 7.1 and has high levels of organic carbon in its soils. It is important to point out that the C stock in the Indian subtropical Himalayas is significantly impacted by plant species and cropping. SOC concentrations in soil were higher in forested than in cultivated areas. However, at a deeper soil depth, SOC reserves were higher in cultivated soils than in forest soils (1.5 m). The enhanced subsurface SOC in cultivated soil may be caused by the faster movement of dissolved organic carbon into deeper layers in cultivated soils than in forest soils. According to data on greenhouse gas emissions, global carbon emissions from fossil fuels have significantly increased since 1900. About 78% of the global increase in greenhouse gas emissions from 1970 to 2011 was caused by emissions from the burning of fossil fuels and industrial operations. Since 1970, CO2 emissions have increased by about 90%. The second-largest factors have been land use changes, deforestation, and agriculture. These activities may become a carbon sink instead of a net emitter in order to stop the trend of climate change. The soil on agricultural and forestry land may take up carbon from the atmosphere by adopting regenerative techniques. Research estimates predict that croplands alone will store between 18 and 37 billion tonnes of carbon over the next 20 years (Zomer et al. 2017).
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Indian Himalayan Region: SOC Pools
There are 13 Indian states/union territories that make up the 2500-km-long Indian Himalayan Region, including Jammu and Kashmir, Ladakh, Uttarakhand, Himachal Pradesh, Arunachal Pradesh, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim, Tripura, Assam, and West Bengal. Due to the significant percentage of tribal residents in each district, tribal districts include Arunachal Pradesh, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim, and Tripura. Forests have a crucial role in tribal economies, societies, and cultures. The tribal population depends heavily on forests as a source of food and income. According to Forest Survey of India (FSI), shown in Table 7.2, there was a 55 km2 total decline in forest cover in tribal districts. Considering soil inorganic (SIC) and soil organic (SOC) carbon pools, soils contain the majority of terrestrial carbon. Lal (2004) estimates that soils contain an average carbon pool of 2500 Pg. In particular, the top 1 m of soil contains around 1200–1600 Pg (1 Pg = 1015 g) of SOC and 695–930 Pg of SIC. The amount of carbon (C) in soil dominates both the global biotic C pool and the global atmospheric C pool (Batjes 1996). The soil microbiology, flora, climate, and altitude of the Himalayan region are some of the strongest predictors of SOC stocks (Matus et al. 2014). For soil fertility, productivity, and a reduction in CO2 emission to the atmosphere, SOC must be preserved. It has been noticed that by using appropriate land management techniques, a significant portion of the soil carbon loss (about 66–90 Pg C) can be recovered (Lal 2004). Increasing forage production through land management strategies including fertilization, irrigation, and intersowing of grasses and legumes is essential for improving carbon storage. Other land management practices include growing and recycling more biomass. According to research, natural grasslands have low soil C sequestration, but when compared to arable land, grasslands have higher SOC variability. Processes like Table 7.2 Total soil organic carbon stocks in Indian Himalayan region with stock in tons per ha given in parentheses (FAO 2021) S. No. 1 2 3 4 5 6 7 8 9 10 11 12 13
State/union territories Arunachal Pradesh Assam Himachal Pradesh Manipur Meghalaya Mizoram Nagaland Sikkim Tripura Uttarakhand West Bengal Jammu and Kashmir Ladakh
SOC 560,298 (84.34) 156,042 (55.12) 105,937 (68.60 111,708 (67.30) 108,014 (63.37) 95,961 (53.85) 82,115 (67.03) 30,944 (92.62) 43,304 (56.08) 166,847 (68.65) 92,889 (55.19) 152,772 (71.43) 12,987 (57.12)
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active rhizo-deposition favor C storage in grasslands, and due to earthworm activity, macroaggregate formation is enhanced, which stabilizes SOC. Continuous addition of organic matter from plants to the soil and its turnover through microbial activity maintain ecosystem carbon pool balance (Stuart Chapin et al. 2009). However, extensive logging, illegal logging, and the encouragement of agricultural activities have changed carbon cycling and have contributed significantly to carbon dioxide emissions into the atmosphere (Ahirwal et al. 2022). Even after 34 years of rubber cultivation, the establishment of plantations in a natural forest of northeast India decreased SOC stock by 67.4 Mg C ha-1 (Nath et al. 2018). Scientists are interested in understanding the mechanism and factors impacting SOC storage because of the significant losses and partial recovery of SOC stock as a result of land use change. SOC is made up of distinct fractions with varying stability and turnover rates (Chan et al. 2001; Rovira et al. 2010). A change in climate with altitude affects the type and productivity of vegetation as well as the amount and turnover of soil organic matter (SOM) via controlling soil water balance, soil erosion, and deposition processes. Urbanization and the conversion of grasslands to crops typically involve removing vegetation and diminishing surface cover, which undermines the soil and accelerates erosion, including the loss of organic carbon. This is especially obvious in arid regions where deterioration is more severe due to the dry character of grassland ecosystems, in addition to conversion to agriculture. According to Ojima et al. (1994), “regressive” land management (i.e., increasing grazing levels from 30 to 50% removal of vegetation) led to a net loss of soil carbon after 50 years, with the greatest losses occurring in warm grasslands. In contrast, sustainable management (i.e., light grazing) led to a net increase in soil carbon. Thus, grassland ecosystems have the potential to be net C sources if they are overused in terms of consumption of plant biomass. Given that good management can sustain or enhance soil C sequestration and help to mitigate the increase in atmospheric CO2, management strategies that either increase or decrease soil C storage might have a significant impact on the global C budget. The ability to increase C storage in grasslands is also highly regarded for global-scale revegetation initiatives that attempt to prevent land degradation and restore damaged lands, particularly in dry regions. The grasslands in the Indian Himalayan Region (IHR), which represent around 33% of India’s SOC stocks (Bhattacharyya et al. 2008), cover wide climate gradients and provide a number of products and services, including acting as an atmospheric C sink. Soil Organic carbon stock of Indian Himalayan region is shown in Fig. 7.1. This is particularly significant for the Kashmir Himalaya, where alpine grasslands, permanent pastures, and other grazing areas cover 5.23% of the area and represent the dominating landscape component. In fact, the Kashmir Himalaya alone represents up nearly 77% of the 171,464 km2 of alpine grassland in the Indian Himalaya (Lal et al. 1991). However, the majority of these grasslands are threatened by anthropogenic factors such as globalization, urbanization, invasive alien species, and climate change. The realization of recreational facilities, which basically involves shifting
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Fig. 7.1 Soil Organic carbon stock of Indian Himalayan regions (ISRIC 2016)
from pasture use to non-pasture tourism activities, has also badly encroached into grasslands. The government began this practice in the early 1970s when the tourism industry in the Kashmir Valley began to boom. Since then, it has spread throughout the entire region, and many priceless meadows that were once summer pastures for both local and migratory animals are now renowned for their recreational appeal. Despite the fact that few authors have discussed the effects of non-pasture activities on the biodiversity of grasslands (Dad and Khan 2010; Dad and Reshi 2015), there is essentially no information on SOC stocks in the various grassland ecosystems of the Kashmir Himalaya. This practice has slightly understated the importance of grasslands, which is much greater than currently acknowledged and includes issues like C sequestration, social cohesion, and local economies. It is also severely constrained by the fact that Himalayan ecosystems, with their massive carbon stocks and capacity for climate mitigation, are among the most sensitive to climate change and are crucial players in the global carbon cycle (Yang et al. 2007). The Indian Himalayan Region is a rich source of SOC since significant areas of the Himalayan Mountains are covered with various forest kinds. A Global Soil Information System called “soil grids” with a 250 m resolution was issued by ISRIC (International Soil Reference Information Centre)—World Soil Information, making possible to collect soil data for the entire Himalaya region. The output from the IHR’s SOC data is shown in Fig. 7.1.
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7.3.1
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Forest as Carbon Sinks in Indian Himalayan Regions
The forest cover has a significant role in avoiding soil erosion, land degradation, as well as maintaining ecological balance and environmental stability, due to the fragility of hilly terrain and vulnerability to land degradation. The difference in forest cover between two evaluations made back-to-back represents the actual change on the ground reported in Table 7.3. The positive changes include an increase in vegetation, which can be attributed to conservation efforts, afforestation efforts, improved protection measures in plantations as well as in traditional forest areas, growth of trees outside of forest, etc. In addition to the change from forest to non-forest and vice versa, the positive changes also include the change from forest to non-forest. Forest cover has been reduced as a result of harvesting, shifting farming, biotic pressure, development activities, etc. The interpretational variations in classifications also apply to regions where the forest cover was either lost due to snow cover, the effects of shadows cast by hills, or low tree reflectivity as a result of leaf fall, among other factors. As per the Indian State forest report, Arunachal Pradesh (257 km2), Manipur (249 km2), Nagaland (235 km2), Mizoram (186 km2), and Meghalaya (73 km2) are the states with the greatest loss of forest cover. The shifting of cultivation, the cutting of trees, natural disasters, anthropogenic pressure, and development activities may be responsible for the decline in forest cover and the state of the forest canopy (Kumari et al. 2019). The most abundant element, carbon, is necessary for all known living beings. The carbon cycle is made up of a series of processes allowing for life forms to exist and survive on the planet. Sources and sinks are another way to consider the carbon cycle. Sources and sinks are the two components of the cycle that add and remove carbon from the atmosphere, respectively. The sun’s energy that enters the Earth’s atmosphere is in part reflected back into the space, with greenhouse gases absorbing and radiating the remainder. The carbon cycle’s sources and sinks help to control the amount of greenhouse gases in the atmosphere and to maintain the equilibrium the CO2 concentrations in the sources and sinks must be equal. The three biggest sinks are the oceans, forests, and terrestrial soils. Around one-fourth of the carbon that humans release to the atmosphere may be removed by the seas and forests, respectively. The concentration of greenhouse gases has increased during the past 1.5 centuries as a result of the increased human activity, primarily the combustion of fossil fuels and deforestation. All around the world, the environment and the quality of life are now seriously threatened by climate change. Forests are crucial in preventing and adapting to climate change and according to a report of American forests can be considered to be a carbon source if it releases more carbon than it absorbs and as a carbon sink. More carbon is stored and sequestered by forests than any other terrestrial ecosystem, and they also operate as a natural restrictions strategy on climate change. Forest carbon stock in 2021 under different pools and changes with respect to previous assessment of 2019 (in million tons) is shown in Table 7.4. Global interest in carbon sequestration by forests is high since it is a relatively low-cost method of reducing
13
12
4 5 6 7 8 9 10 11
2 3
S. No. 1.
States Arunachal Pradesh Assam Himachal Pradesh Manipur Meghalaya Mizoram Nagaland Sikkim Tripura Uttarakhand West Bengal Jammu and Kashmir Ladakh
2
22
9 7 8 11 4 4 13 1
3 12
No. of hill districts 16
222,236
22,223
22,327 22,429 21,081 16,579 7098 10,486 53,483 721
19,295 55,673
Geographical area 83,746
2
4155
905 560 157 1272 1102 647 5055 721
981 3163
Very dense forest 21,058
512
8117
6228 9160 5715 4449 1551 5212 12,768 682
5473 7100
Moderately dense forest 30,176
Table 7.3 Forest cover area in Indian Himalayan states (in km2) (FAO 2021)
1758
9115
9465 7326 11,948 6530 688 1863 6482 947
6446 5180
Open forest 15,197
2272
21,387
16,598 17,046 17,820 12,251 3341 7722 24,305 2350
12,900 15,443
Total 66,431
1.35
39.15
74.340485 75.999822 84.531094 73.894686 47.069597 73.641045 45.444347 74.62
66.856699 27.73876
Percentage of GA 79.324386
18
29
-249 -73 -186 -235 -1 -4 2 -18
-107 9
Change in forest cover with respect to IFR (2021) -257
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Table 7.4 Forest carbon stock under different pools and changes with respect to previous assessment (in million tons) (FAO 2021) Component Above ground biomass Below ground biomass Dead wood Litter Soil Total
Carbon stock in forests in 2021 2319.90
Carbon stock in forest in 2019 2,257
Net change in carbon stock 63.4
Annual change in C stock 31.7
718.9
700.8
18.1
9.1
47.7 107.3 4010.2 7204
35.8 127.9 4003.6 7124.6
11.9 -20.6 6.6 79.4
6 -10.3 3.3 39.7
climate change. India’s forests are diverse, which makes them resistant to climate change and a productive carbon sink.
7.3.2
Agriculture and Carbon Sequestration in Indian Himalayan Regions
A report by Egan and Price (2017) on mountain ecosystem services and climate change states that the mountain ecosystems, which make up about 22% of the Earth’s geographical surface, are home to millions of people who rely mostly on agriculture for their living stability. For most IHR inhabitants, agriculture has been their main source of income. The Himalayan agroecosystem is known for its vulnerability, marginality, inaccessibility, and lack of infrastructure (roads, electricity, irrigation facilities, etc.). Despite these obstacles, the Himalayan agricultural system has endured for years, providing all of the food needed for households. However, the Himalayan agriculture is currently under pressure from a number of social, economic, and environmental factors, including land fragmentation, small and unprofitable landholdings per family, increased rural migration, dwindling labor supply, higher production costs, lack of financial resources, and climate change, among others. FAO (2021) study on the impact of disasters and crises on agriculture and food security states that several disturbances, including flooding, landslides, drought, wildfires, and overexploitation of resources, are occurring as a result of climate change. Increased agricultural land abandonment is the result. The traditional kind of agriculture in the Himalayas has been “family farming,” which focuses on producing food for families and local consumers (Schroeder 1985). Significant soil carbon stores have been depleted as a result of agriculture’s growth throughout the centuries, especially in recent decades. A potential method of reducing the rising CO2 concentration in the atmosphere is through the expanded
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Fig. 7.2 Biological carbon sequestration (source: Biological Carbon Sequestration by Climate Adaptation Science Centers 2022)
carbon sequestration (CS) capacity of agricultural soils, which are among the planet’s greatest carbon repositories. Biological carbon sequestration is shown in Fig. 7.2. Furthermore, this technique helps to improve biodiversity, reduce desertification and erosion, and improve the quality of the soil, crops, and environment. In addition to lowering agricultural yields, land degradation frequently lowers the carbon content of agroecosystems and may lower biodiversity. Determining what significant synergies exist in the field of soil carbon sequestration is crucial. The ability of agricultural fields and forests to absorb carbon dioxide from the atmosphere is referred to as carbon sequestration in the agricultural industry. Through photosynthesis, trees, plants, and crops absorb carbon dioxide, which is then stored as carbon in biomass of trunks, branches, foliage, roots, and soils of trees (Patil and Kumar 2017). Forests and stable grasslands are referred to as carbon sinks because they have the capacity to store considerable amounts of carbon in their vegetation and root systems for long periods of time. Climate, soil type, crop or vegetation cover, management techniques, and other elements all affect how well agricultural areas can sequester carbon. The addition of carbon from decomposing plant matter and carbon losses from respiration, the decomposition process, and soil disturbances caused by both natural and human activity all affect how much carbon is retained in soil organic matter (Trumbore 1997). Farmers may be able to slow down or perhaps stop the loss of carbon from their crops by using agricultural techniques that favor carbon sequestration while causing the least amount of soil disturbance.
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Rhizospheric Microbes and Carbon Sequestration
Since the beginning of industrial revolution, carbon dioxide concentration in the atmosphere has been rising alarmingly. Global environmental changes are brought about by increasing emission of greenhouse gases (GHGs). According to greenhouse gas emission data among various GHGs, CO2 is key one accounting for 65% of total GHGs emission. Carbon sequestration is the effective method to increase soil carbon storage through soil carbon sequestration. An essential link between ecosystems’ above- and below-ground parts is provided by soil microorganisms. They are the key players in the carbon sequestration process of terrestrial ecosystems (Jacoby et al. 2017). The main carbon source in soil is plant organic matter through plant inputs in the form of shoot and root litter that serve as an additional carbon source for soil organisms in addition to root exudation (Hoffland et al. 2020). As shown in Fig. 7.3 by respiration, soil microbes mineralize the majority of freshly fixed carbon, but they also help in the preservation of SOM by turning over and recycling biomass (Mambelli et al. 2011; Miltner et al. 2012; Throckmorton et al. 2012). According to estimates, up to 80% of the organic carbon in soil is formed by nonliving microbial biomass (Liang and Balser 2011). In large part, the molecular resynthesis or transformation of chemicals by microbes into substances that seem to stay in soil is responsible for the stabilization of some molecules in soil (Gleixner 2013). Although it is now widely known that microbially produced carbon inputs to soil are a significant source of SOM, it is still unclear how different microbiological components affect soil carbon storage. Various cellular fractions
Fig. 7.3 The primary processes that soil microorganisms mediate in the terrestrial carbon cycle (adapted from Prosser 2007)
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of microbes in soil are expected to contribute differentially to carbon storage based on variable turnover rates and consequently different retention durations (Singh et al. 2020). Therefore, it is necessary to ascertain the connection between soil carbon turnover and microbial macromolecular structure (Pandey et al. 2021a, b). Rootdriven carbon is a significant flux in the terrestrial carbon cycle and is essential for soil health, ecosystem function, and carbon sequestration (Pausch and Kuzyakov 2018). Recent research has revealed that interactions between roots and rhizomicroorganisms are the primary source of SOC (Treseder and Holden 2013; Cheng et al. 2014).
7.4.1
Microbial Strategies and Carbon Sequestration
Transferring organic carbon directly from the plant to the subsurface carbon pool, changing the rate of SOC turnover, (Tefs and Gleixner 2012; Keymer et al. 2017), and regulating SOC from biomass and SOC secretion by microorganisms, roots can have a significant impact on soil carbon sequestration (Clemmensen et al. 2013). Additionally, rhizo-microorganisms have an impact on SOC breakdown and sequestration through the soil microbes’ uptake of nutrients (Pausch and Kuzyakov 2018). SOC sequestration is regulated by competition and symbiosis between roots and soil microorganisms (Kuzyakov and Xu 2013). Soil microbes are also known to play a significant role in the succession of plant communities and to affect carbon sequestration (Bardgett and van der Putten 2014; Morriën et al. 2017). The relationships between the amount of microbial biomass, microbial community structure, microbial byproducts, and soil characteristics such texture, clay mineralogy, pore size distribution, and aggregate dynamics control the microbial contribution to C sequestration. The physical and chemical characteristics of the soil, such as moisture, pH, temperature, atmospheric CO2 concentration, and nitrogen and phosphorus concentrations, all have an impact on the ability of roots to sequester carbon (Rukshana et al. 2013; Cheng et al. 2014; Song et al. 2018). In order for microbially derived organic matter (MOM) to accumulate in soil, there must be a balance between how quickly microbiological products are produced and how quickly they decompose through the following: 1. The microbial growth efficiency (MGE), which measures how effectively substrates are incorporated into microbial biomass and byproducts 2. The level of protection provided by the soil structure for microbial biomass 3. The rate at which microbial byproducts are broken down by other microorganisms (Hoover and Heath 2015). In addition to being connected to the transfer of nutrients and energy between plants and soil organisms, root-associated microbial food webs also promote plant growth (Wardle et al. 2004; de Boer et al. 2006). The primary organisms that break down plant-derived carbon are fungi and bacteria, and it is well-known that fungal and bacterial decomposers have various niches depending on the complexity of the
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substrate (de Boer et al. 2006). In fact, a number of bacteria, particularly those from the Burkholderiaceae or Pseudomonadaceae families, have been linked to the quick assimilation of plant carbon produced from the roots (Vandenkoornhuyse et al. 2007; Philippot et al. 2013). However, other investigations have shown that both symbiotic and saprophytic fungi play a substantial role in the consumption of root-derived carbon (Drigo et al. 2010; Balasooriya et al. 2014). Most significantly, the quick belowground transfer of plant carbon has been associated with arbuscular mycorrhizal fungi (AMF). According to estimates, AMF can use up to 20% of photoassimilates, making mycorrhizal hyphal turnover a significant pathway for C input into SOM (Godbold et al. 2006). Greater fungal abundance is related to greater C storage, and bacterial and fungal abundances in soils are correlated with C sequestration potential (Malik et al. 2016). Since fungi have higher microbial growth efficiency than bacteria, the production of microbial biomass and byproducts will be higher in soils where fungi dominate the microbial population. So, for every unit of substrate consumed, fungaldominated communities will retain more carbon in their biomass and release less carbon dioxide. Since fungal products are more chemically resistant to decay and are preferentially protected from decomposition through their interactions with clay minerals and soil aggregates, MOM degradation will be slower in soils where fungus predominate (Six et al. 2006). Agricultural practices that encourage fungal dominance will improve soil C sequestration. The overall C uptake by plants is greatly increased by mycorrhizal interaction. The transfer of photosynthates from the host plants to the AM fungal intraradical hyphae and then to extraradical hyphae before release to the soil matrix is a well-known method by which AMF sequester C in soil (Solaiman 2014). AM fungi have an indirect impact on C sequestration in soils and cause a 4–20% drain of carbon from the host plant to their hyphae (Jakobsen and Rosendahl 1990). They directly affect soil C sequestration by increasing the number and turnover of extraradical hyphae in the bulk soil and rhizosphere. The total amount of hyphal biomass produced, the amount of time it takes for accumulated hyphal biomass to decompose, and the role these fungi play in stabilizing the development of soil aggregates will affect how much C is sequestered by soil by AM fungi (Treseder and Allen 2000).
7.4.2
The Significance of Bacterial and Fungal Diversity in the Soil Ecosystem of the Himalayas and Methods for Restoring Degraded Soil
Both bacteria and fungi play crucial roles in the establishment of plant communities and are significant mediators of biogeochemical processes. Both bacteria and fungi are crucial to the functioning of ecosystems, and understanding how they recover from severe perturbations is crucial to understanding how ecosystems as a whole grow. Many anthropogenic activities that reduce soil fertility and productivity contribute to the global problem of land degradation. Deforestation, inefficient
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agricultural methods (heavy tillage, imbalanced fertilization, inadequate irrigation, and chemical inputs in the form of pesticides or fertilizers), and industrialization are the main drivers of land degradation. Plant diversity and soil ecosystem are connected by microorganisms that control the carbon and nitrogen cycles in the soil ecosystem. Similar to this, the microbial community structure of the soil around plant roots is influenced by plant diversity. Microorganisms use the root exudates of plants as a resource for growth and development. Due to the abundant nutrition sources, the rhizosphere supports a diverse range of microorganisms. Suyal et al. (2015) used an unculturable approach to investigate the diversity of soil bacteria in the rhizosphere of Phaseolus vulgaris from the Western Indian Himalaya. They discovered that soil bacteria, the most numerous and diverse group of microorganisms in soil, play a crucial role in the establishment of sustainable plant communities, nutrient cycling, and soil structure. In order to adapt to changes in environmental factors like soil pH, nutrient contents, and vegetation type, soil bacterial communities have evolved various strategies shown in Fig. 7.4. Due to this, the composition and abundance of soil bacterial communities are considered crucial indicators of soil quality (Schloter et al. 2018),
Vegetation
Organic Matter
Depth
Soil Environment Affecting Microbe diversity
Light
pH
Sailinity
Temperature
Moisture
Fig. 7.4 Soil Environment influencing diversity of microorganisms
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particularly in the context of land degradation and restoration. Following restoration, a variety of vegetation patterns affect the nutrients and soil microbes in the soil (Liu et al. 2021). Several researches have examined the succession of soil bacterial species in the recent years. In contrast to slurry manure fertilization, Rashid et al. (2014) found that applying solid cattle manure to sandy soil increased organic matter, nitrogen, pH, microbial biomass, and soil fauna. In semiarid regions with deteriorated soil, application of municipal garbage improved soil microbial activity. In addition to these experiments, the Himalayan region’s deteriorated soil was improved by using wheat straw and poultry manure (Khaliq and Abbasi 2015). In the degraded alpine steppe in Northern Tibet, Wang et al. (2021) reported improved ecological restoration treatments in plant and soil microbial diversity. They also investigated how the improved soil microbial diversity might help the biological communities in the degraded alpine steppe for the development of better ecological functions. Donhauser and Frey (2018) described the huge amount of undiscovered microbial diversity found in alpine permafrost soils as well as studies of climate change in alpine habitats that revealed changes in microbial community structures and function in response to warming and changed soil moisture. According to Sharma et al. (2019), seabuckthorn trees improve other forests and boost soil microorganisms, which improve soil biodiversity and assist preserve and restore fragile ecosystems.
7.5
Conclusion
Today’s world faces major issues with carbon management and land restoration. Although there have been several land restoration initiatives in the Himalaya and throughout the tropics, the outcomes have frequently fallen short of expectations due to inefficient technology, plans, and execution techniques. The sustainable regeneration of degraded landscapes is required, according to the FAO State of the World’s Forests 2016 report, to accommodate a variety of land uses, including agriculture, tree plantations, and protected landscape regions. Up to one-third of CO2 emissions are absorbed by healthy ecosystems including forests, mangroves, and peatlands, acting as carbon sinks. In order to feed the world’s rising population, healthy soils can store more nutrients and grow plants of greater quality. Microbial carbon storage in the rhizosphere is a potential enormous, if ephemeral, carbon store that affects plant health, production, and disease through regulating rhizosphere bacterial activity under stress. Our understanding of the soil processes involved in the formation and decomposition of SOM is still very limited, which results in a lack of consensus knowledge regarding microbial trophic interactions and the flow of carbon through terrestrial ecosystems, despite the soil organic carbon pool’s relatively large size and temporal sensitivity and its importance in maintaining agricultural productivity and reducing atmospheric CO2 levels. As a result, a revision of the root-associated microbial food web is necessary.
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References Ahirwal J, Gogoi A, Sahoo UK (2022) Stability of soil organic carbon pools affected by land use and land cover changes in forests of eastern Himalayan region, India. Catena 215:106308 Azadi H, Ho P (2010) Genetically modified and organic crops in developing countries: a review of options for food security. Biotechnol Adv 28(1):160–168 Balasooriya WK, Denef K, Huygens D, Boeckx P (2014) Translocation and turnover of rhizodeposit carbon within soil microbial communities of an extensive grassland ecosystem. Plant Soil 376(1):61–73 Bardgett RD, Van Der Putten WH (2014) Belowground biodiversity and ecosystem functioning. Nature 515(7528):505–511 Batjes NH (1996) Total carbon and nitrogen in the soils of the world. Eur J Soil Sci 7(2):151–163 Bhattacharyya T, Pal DK, Chandran P, Ray SK, Mandal C, Telpande B (2008) Soil carbon storage capacity as a tool to prioritize areas for carbon sequestration. Curr Sci 95:482–494 Biological Carbon Sequestration by Climate Adaptation Science Centers (2022). https://www.usgs. gov/media/images/biological-carbon-sequestration Chan KY, Bowman A, Oates A (2001) Oxidizible organic carbon fractions and soil quality changes in an oxic paleustalf under different pasture leys. Soil Sci 166(1):61–67 Cheng W, Parton WJ, Gonzalez-Meler MA, Phillips R, Asao S, McNickle GG, Brzostek E, Jastrow JD (2014) Synthesis and modeling perspectives of rhizosphere priming. New Phytol 201(1): 31–44 Clemmensen KE, Bahr A, Ovaskainen O, Dahlberg A, Ekblad A, Wallander H, Stenlid J, Finlay RD, Wardle DA, Lindahl B (2013) Roots and associated fungi drive long-term carbon sequestration in boreal forest. Science 339(6127):1615–1618 Coleman JL, Ascher JS, Bickford D, Buchori D, Cabanban A, Chisholm RA, Chong KY, Christie P, Clements GR, Dela Cruz TEE, Dressler W (2019) Top 100 research questions for biodiversity conservation in Southeast Asia. Biol Conserv 234:211–220 Dad JM, Khan AB (2010) Floristic composition of an alpine grassland in Bandipora, Kashmir. Grassl Sci 56(2):87–94 Dad JM, Reshi ZA (2015) Influence of environmental and anthropogenic factors on the species distribution in alpine rangelands of Figurez valley, Kashmir, India. Trop Ecol 56(3):335–346 Dangi AK, Sharma B, Hill RT, Shukla P (2019) Bioremediation through microbes: systems biology and metabolic engineering approach. Crit Rev Biotechnol 39(1):79–98 De Boer W, Kowalchuk GA, Van Veen JA (2006) ‘Root-food’ and the rhizosphere microbial community composition. New Phytol 170:3–6 Dixit R, Malaviya D, Pandiyan K, Singh UB, Sahu A, Shukla R, Singh BP, Rai JP, Sharma PK, Lade H, Paul D (2015) Bioremediation of heavy metals from soil and aquatic environment: an overview of principles and criteria of fundamental processes. Sustainability 7(2):2189–2212 Donhauser J, Frey B (2018) Alpine soil microbial ecology in a changing world. FEMS Microb Ecol 94(9):99 Drigo B, Pijl AS, Duyts H, Kielak AM, Gamper HA, Houtekamer MJ, Boschker HT, Bodelier PL, Whiteley AS, Veen JAV, Kowalchuk GA (2010) Shifting carbon flow from roots into associated microbial communities in response to elevated atmospheric CO2. PNAS 107(24):10938–10942 Egan PA, Price MF (2017). Mountain ecosystem services and climate change: a global overview of potential threats and strategies for adaptation FAO (2021) The impact of disasters and crises on agriculture and food security FSI (2011) Atlas Forest types of India, Forest Survey of India, Ministery of Environment Forest & Climate Change Gleixner G (2013) Soil organic matter dynamics: a biological perspective derived from the use of compound-specific isotopes studies. Ecol Res 28(5):683–695 Godbold DL, Hoosbeek MR, Lukac M, Cotrufo MF, Janssens IA, Ceulemans R, Polle A, Velthorst EJ, Scarascia-Mugnozza G, De Angelis P, Miglietta F (2006) Mycorrhizal hyphal turnover as a dominant process for carbon input into soil organic matter. Plant Soil 281(1):15–24
7
Establishing Linkages of Soil Carbon Dynamics with Microbes. . .
143
Hatti-Kaul R, Törnvall U, Gustafsson L, Börjesson P (2007) Industrial biotechnology for the production of bio-based chemicals–a cradle-to-grave perspective. Trends Biotechnol 25(3): 119–124 Hoffland E, Kuyper TW, Comans RN, Creamer RE (2020) Eco-functionality of organic matter in soils. Plant Soil 455(1):1–22 Hoover CM, Heath LS (2015) A commentary on ‘Mineral soil carbon fluxes in forests and implications for carbon balance assessments’: a deeper look at the data. GCB Bioenergy 7(2): 362–365 Houghton RA, House JI, Pongratz J, Van Der Werf GR, Defries RS, Hansen MC, Le Quéré C, Ramankutty N (2012) Carbon emissions from land use and land-cover change. Biogeosciences 9(12):5125–5142 Iravani S, Varma RS (2020) Bacteria in heavy metal remediation and nanoparticle biosynthesis. ACS Sustain Chem Eng 8(14):5395–5409 ISRIC (2016) world soil information, https://www.isric.org/explore/wise-databases Jacoby R, Peukert M, Succurro A, Koprivova A, Kopriva S (2017) The role of soil microorganisms in plant mineral nutrition—current knowledge and future directions. Front Plant Sci 8:1617 Jakobsen I, Rosendahl L (1990) Carbon flow into soil and external hyphae from roots of mycorrhizal cucumber plants. New Phytol 115(1):77–83 Juwarkar AA, Misra RR, Sharma JK (2014) Recent trends in bioremediation. In: Geomicrobiology and biogeochemistry. Springer, Berlin, pp 81–100 Kanwal MS, Mukherjee S, Joshi R, Rai S (2019) Impact assessment of changing environmental and socioeconomical factors on crop yields of central Himalaya with emphasis to climate change. Environ Ecol 37(1B):324–332 Keymer A, Pimprikar P, Wewer V, Huber C, Brands M, Bucerius SL, Delaux PM, Klingl V, von Roepenack-Lahaye E, Wang TL, Eisenreich W (2017) Lipid transfer from plants to arbuscular mycorrhiza fungi. elife 6:e29107 Khaliq A, Abbasi MK (2015) Improvements in the physical and chemical characteristics of degraded soils supplemented with organic–inorganic amendments in the Himalayan region of Kashmir, Pakistan. Catena 126:209–219 Kumari R, Banerjee A, Kumar R, Kumar A, Saikia P, Khan ML (2019) Deforestation in India: consequences and sustainable solutions. For Degrad Around World 2019:1–18 Kuzyakov Y, Xu X (2013) Competition between roots and microorganisms for nitrogen: mechanisms and ecological relevance. New Phytol 198(3):656–669 Lal R (2004) Soil carbon sequestration impacts on global climate change and food security. Science 304(5677):1623–1627 Lal JB, Gulati AK, Bisht MS (1991) Satellite mapping of alpine pastures in the Himalayas. Int J Remote Sens 12(3):435–443 Ławniczak Ł, Woźniak-Karczewska M, Loibner AP, Heipieper HJ, Chrzanowski Ł (2020) Microbial degradation of hydrocarbons—basic principles for bioremediation: a review. Molecules 25(4):856 Liang C, Balser TC (2011) Microbial production of recalcitrant organic matter in global soils: implications for productivity and climate policy. Nat Rev Microbiol 9(1):75–75 Liu M, Li X, Zhu R, Chen N, Ding L, Chen C (2021) Vegetation richness, species identity and soil nutrients drive the shifts in soil bacterial communities during restoration process. Environ Microbiol 13:411–424 Malik AA, Chowdhury S, Schlager V, Oliver A, Puissant J, Vazquez PG, Jehmlich N, Von Bergen M, Griffiths RI, Gleixner G (2016) Soil fungal: bacterial ratios are linked to altered carbon cycling. Front Microbiol 7:1247 Mambelli S, Bird JA, Gleixner G, Dawson TE, Torn MS (2011) Relative contribution of foliar and fine root pine litter to the molecular composition of soil organic matter after in situ degradation. Org Geochem 42(9):1099–1108 Matus F, Rumpel C, Neculman R, Panichini M, Mora ML (2014) Soil carbon storage and stabilisation in andic soils: a review. Catena 120:102–110
144
S. Pandey et al.
Miltner A, Bombach P, Schmidt-Brücken B, Kästner M (2012) SOM genesis: microbial biomass as a significant source. Biogeochemistry 111(1):41–55 Morriën E, Hannula SE, Snoek LB, Helmsing NR, Zweers H, De Hollander M, Soto RL, Bouffaud ML, Buée M, Dimmers W, Duyts H (2017) Soil networks become more connected and take up more carbon as nature restoration progresses. Nat Commun 8(1):1–10 Nath AJ, Brahma B, Sileshi GW, Das AK (2018) Impact of land use changes on the storage of soil organic carbon in active and recalcitrant pools in a humid tropical region of India. Sci Total Environ 624:908–917. https://doi.org/10.1016/j.scitotenv.2017.12.199 Navarro-Pedreño J, Almendro-Candel MB, Zorpas AA (2021) The increase of soil organic matter reduces global warming, myth or reality? Science 3(1):18 NRSC (2010) Wasteland Atlas of India, 2005-06. National Remote Sensing Centre, Department of Space, Government of India, 291 Ojima DS, Galvin KA, Turner BL (1994) The global impact of land-use change. Bioscience 44(5): 300–304 Pandey D, Savio N, Rai S, Pandey S (2021a) Restoration of soil microbiota for promoting climate resilient ecosystems in the Himalayan region. ENVIS Bull Himalayan Ecol 29:90 Pandey S, Rai S, Pandey D (2021b) Soil microbial strategies for Himalayan ecosystem restoration. ENVIS Bull Himalayan Ecol 29:85 Patil P, Kumar AK (2017) Biological carbon sequestration through fruit crops (perennial crops— natural “sponges” for absorbing carbon dioxide from atmosphere). Plant Arch 17(2):1041–1046 Pausch J, Kuzyakov Y (2018) Carbon input by roots into the soil: quantification of rhizodeposition from root to ecosystem scale. Glob Chang Biol 24(1):1–12 Philippot L, Raaijmakers JM, Lemanceau P, Van Der Putten WH (2013) Going back to the roots: the microbial ecology of the rhizosphere. Nat Rev Microbiol 11(11):789–799 Prosser JI (2007) Microorganisms cycling soil nutrients and their diversity. In: Modern soil microbiology. CRC Press, New York, pp 237–261 Rashid MI, de Goede RG, Nunez GAC, Brussaard L, Lantinga EA (2014) Soil pH and earthworms affect herbage nitrogen recovery from solid cattle manure in production grassland. Soil Biol Biochem 68:1–8 Rodríguez A, Castrejón-Godínez ML, Salazar-Bustamante E, Gama-Martínez Y, SánchezSalinas E, Mussali-Galante P, Tovar-Sánchez E, Ortiz-Hernández M (2020) Omics approaches to pesticide biodegradation. Curr Microbiol 77(4):545–563 Rovira P, Jorba M, Romanyà J (2010) Active and passive organic matter fractions in Mediterranean forest soils. Biol Fertil Soils 46(4):355–369 Rukshana F, Butterly CR, Xu JM, Baldock JA, Tang C (2013) Soil organic carbon contributes to alkalinity priming induced by added organic substrates. Soil Biol Biochem 65:217–226 Samal PK, Palni LMS, Agrawal DK (2003) Ecology, ecological poverty and sustainable development in Central Himalayan region of India. Int J Sustain Dev World Ecol 10(2):157–168 Scharlemann JP, Tanner EV, Hiederer R, Kapos V (2014) Global soil carbon: understanding and managing the largest terrestrial carbon pool. Carbon Manage 5(1):81–91 Schloter M, Nannipieri P, Sørensen SJ, van Elsas JD (2018) Microbial indicators for soil quality. Biol Fertil Soils 54(1):1–10 Schroeder RF (1985) Himalayan subsistence systems: indigenous agriculture in rural Nepal. Mt Res Dev 5:31–44 Sharma A, Singh V, Sharma A, Negi N (2019) Seabuckthorn a new approach in ecological restoration of Himalayan ecosystem: a review. Int J Che Stud 7:1219–1226 Singh AP, Singh SK, Rai S, Kumar M (2020) Soil carbon dynamics in relation to soil surface management and cropping system. In: Carbon management in tropical and sub-tropical terrestrial systems. Springer, Singapore, pp 159–172 Six J, Frey SD, Thiet RK, Batten KM (2006) Bacterial and fungal contributions to carbon sequestration in agroecosystems. Soil Sci Soc Am J 70(2):555–569
7
Establishing Linkages of Soil Carbon Dynamics with Microbes. . .
145
Solaiman ZM (2014) Contribution of arbuscular mycorrhizal fungi to soil carbon sequestration. In: Mycorrhizal fungi: use in sustainable agriculture and land restoration. Springer, Berlin, pp 287–296 Song W, Tong X, Zhang J, Meng P, Li J (2018) How a root-microbial system regulates the response of soil respiration to temperature and moisture in a plantation. Pol J Environ Stud 27(6): 2749–2756 Stuart Chapin F, McFarland J, David McGuire A, Euskirchen ES, Ruess RW, Kielland K (2009) The changing global carbon cycle: linking plant–soil carbon dynamics to global consequences. J Ecol 97(5):840–850 Sundar B (2017) Joint forest management in India–an assessment. Int For Rev 19(4):495–511 Suyal DC, Yadav A, Shouche Y, Goel R (2015) Diversified diazotrophs associated with the rhizosphere of Western Indian Himalayan native red kidney beans (Phaseolus vulgaris L.). Biotech 5(4):433–441 Tefs C, Gleixner G (2012) Importance of root derived carbon for soil organic matter storage in a temperate old-growth beech forest–evidence from C, N and 14C content. For Ecol Manag 263: 131–137 Throckmorton HM, Bird JA, Dane L, Firestone MK, Horwath WR (2012) The source of microbial C has little impact on soil organic matter stabilisation in forest ecosystems. Ecol Lett 15:1257– 1265 Treseder KK, Allen MF (2000) Mycorrhizal fungi have a potential role in soil carbon storage under elevated CO2 and nitrogen deposition. New Phytol 147(1):189–200 Treseder KK, Holden SR (2013) Fungal carbon sequestration. Science 339(6127):1528–1529 Trumbore SE (1997) Potential responses of soil organic carbon to global environmental change. PNAS 94(16):8284–8291 Vandenkoornhuyse P, Mahé S, Ineson P, Staddon P, Ostle N, Cliquet JB, Francez AJ, Fitter AH, Young JPW (2007) Active root-inhabiting microbes identified by rapid incorporation of plantderived carbon into RNA. PNAS 104(43):16970–16975 Wang C, Wang S, Wu B, Wei M, Rong X, Li Y, Du D (2021) Ecological restoration treatments enhanced plant and soil microbial diversity in the degraded alpine steppe in Northern Tibet. Land Degrad Dev 32(2):723–737 Wardle DA, Bardgett RD, Klironomos JN, Setala H, Van Der Putten WH, Wall DH (2004) Ecological linkages between aboveground and belowground biota. Science 304(5677): 1629–1633 Yang Y, Mohammat A, Feng J, Zhou R, Fang J (2007) Storage, patterns and environmental controls of soil organic carbon in China. Biogeochemistry 84(2):131–141 Yellajosula G, Cihacek L, Faller T, Schauer C (2020) Soil carbon change due to land conversion to grassland in a semi-arid environment. Soil Syst 4(3):43 Zhao R, He M, Yue P, Huang L, Liu F (2022) Linking soil organic carbon stock to microbial stoichiometry, carbon sequestration and microenvironment under long-term forest conversion. J Environ Manag 301:113940 Zomer RJ, Bossio DA, Sommer R, Verchot LV (2017) Global sequestration potential of increased organic carbon in cropland soils. Sci Rep 7(1):1–8
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Harnessing Soil Ecosystem Services for Achieving Soil-Based SDGs in Indian Himalaya Deepa Rawat, Debaaditya Mukhopadhyay, Vinod Prasad Khanduri, Bhupendra Singh, Manoj Kumar Riyal, and Sarswati Prakash Sati
Abstract
The soil is well-known to offer and regulate a wide range of ecosystem services and play a significant role in supporting human life. The 17 Sustainable Development Goals (SDGs) adopted in the United Nations general assembly in September 2015 have also reinforced the importance of various soil functions, ecosystem services, carbon sequestration by soil, prevention of soil degradation, and their influence on life on earth and global climate change. Although soils are not clearly mentioned in the SDGs, a few SDGs are closely related to the characteristics and functions of soil. Among the SDGs defined and approved in general assembly of UN in 2015, eight directly or indirectly include soil functions. The Indian Himalaya is an important region in terms of global significance due to its enriched ecological and sociocultural diversity and vast range of ecosystem services for the very existence of humanity. The better and improved soil ecosystem services provided by different land uses of this region directly feed into the realisation and achievement of the soil-related SDGs of the United Nations. However, the soil ecosystem services provided by Indian Himalaya are under remarkable pressure due to the rapid growth in human population, uncontrolled urbanisation, developmental activities, increase in agricultural activities, climate change, and the related changes in land use and land cover. Various studies conducted in this part of country indicated a general decline in forest cover area and an increasing trend both in fragmentation of forest cover and D. Rawat (✉) · V. P. Khanduri · B. Singh · M. K. Riyal · S. P. Sati College of Forestry, VCSG Uttarakhand University of Horticulture and Forestry, Tehri Garhwal, Uttarakhand, India D. Mukhopadhyay ICFRE-Rain Forest Research Institute, Jorhat, Assam, India # The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Mishra et al. (eds.), Soil Carbon Dynamics in Indian Himalayan Region, https://doi.org/10.1007/978-981-99-3303-7_8
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in the built-up areas, barren areas and croplands in recent years. This observation entails the degradation of ecosystems and the decrease in the potential for the sustainable flow of ecosystem services from this region. In view of these facts, this chapter aims to provide a systematic review of the soil ecosystem services provided by various land uses (from existing literature) and their ultimate sustainable management in order to achieve soil-related SDGs in Indian Himalayan ecosystem. Keywords
Soil · Indian Himalaya · Ecosystem services · SDGs · Land uses
8.1
Introduction
Ecosystem services (ESs) are all the benefits that humans derive from an ecosystem (Hassan et al. 2005) which includes supplying, regulating, sustaining, and cultural services provided by an ecosystem. Ecosystem services have also been described as the result of interaction between ecosystem’s biotic and abiotic elements (Singh 2002) and pertains the circumstances and procedures by which ecosystems and the species that inhabit them support and realise human life (Lawton and Daily 1997). They are the elements of nature that may be consumed, enjoyed, or employed for the benefit of people (Boyd et al. 2006). Food, fibre, fresh air, water supplies, carbon sequestration, and a variety of recreational opportunities are just a few of the essential services that terrestrial ecosystems offer to individuals and society. The local ESs are mostly characterised according to how they impact people’s well-being (Mondal and Zhang 2018). Future changes in socioeconomic conditions, land cover, land use regulations, biodiversity, and climate will affect the sustainable availability of ESs. Not only the residents of this region but also a sizeable portion of the world’s population are critically dependent on the Himalayan mountains for various categories of ESs. Therefore, it is vital to understand the roles and values of these ecosystems while taking into account the direct, indirect, and existence advantages (Negi and Agarwal 2006). The Sustainable Development Goals (SDGs), often referred to as the Global Goals, have been established by a global agreement to eradicate poverty, preserve all that makes the world habitable, and ensure that everyone lives are in peace and prosperity, both now and in the future. In order to address the overwhelming factual evidence that the world needs a significantly more sustainable approach, the SDGs were formally endorsed by all UN member states in 2015 for the period 2016–2030. Their aims offer a well-studied framework that is politically acceptable, scientifically sound, and intuitive to the general public. The SDGs provide us with the best opportunity to ensure the essential cooperation and alignment, as we adopt global strategies to ensure a healthy and prosperous future for ourselves and for future generations. The 17 goals (Table 8.1) are all closely related, despite the fact that they are all accompanied by targets and indicators. Globally, we need to use the SDGs to
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Table 8.1 Summary of UN’s 17 Sustainable Development Goals linked to 5 areas of critical importance (5Ps)
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• People - No Poverty (Goal 1) - Zero Hunger (Goal 2) - Good Health and Well-Being (Goal 3) - Quality Education (Goal 4) - Gender Equality (Goal 5) - Clean Water and Sanitation (Goal 6) • Planet - Climate Action (Goal 13) - Life Below Water (Goal 14) - Life on Land (Goal 15) • Prosperity - Affordable Clean Energy (Goal 7) - Decent Work and Economic Development (Goal 8) - Industry, Innovation, and Infrastructure (Goal 9) - Reduce Inequalities (Goal 10) - Sustainable Cities and Communities (Goal 11) - Responsible Consumption and Production (Goal 12) • Peace and Partnerships - Peace, Justice, and Strong Institutions (Goal 16) - Partnerships for the Goals (Goal 17)
emphasise how the objectives are interconnected and to promote particular, teamwork-based efforts that produce several positive results for a common goal. The SDGs, which were officially adopted by the UN General Assembly in September 2015 and cover the years from 2016 to 2030, are part of the document “Transforming our World: The 2030 Agenda for Sustainable Development”, which outlines the goals, guiding principles, and commitments for a more sustainable environment for all. All scientific fields create knowledge that is relevant to the SDGs, including soil science. The key areas of focus mentioned in most sustainability-related reports do not include soil; however, a focused and pragmatic discussion is needed regarding the potential role of soil science in cross- and intercross research that contributes to achieving the SDG’s (Bouma and McBratney 2013). Accordingly, the focus has now been pragmatically shifted towards soil functions to understand how they affect food security, freshwater availability, climate change, biodiversity, and energy conservation (Bouma 2014). The increased emphasis on the relevance of science for society has led to a multidisciplinary approach. Thus, the emphasis on ecosystem services in relation to one of the most significant natural resources, viz. soil, would give the needed broader focus needed for achieving SDGs (Bouma 2014). Such an endeavour will be especially vital in future years as the SDGs are created and, more importantly, implemented. The main contact between the atmosphere, hydrosphere, lithosphere, and biosphere is the soil, which is also known as the skin of the earth. Therefore, many ESs are influenced by soil (Bouma 2010; Dominati et al. 2014), and several researchers pointed out that soil resources are extremely beneficial for human well-being (Amundson et al. 2015; Banwart 2011). Production of food, water and
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climate regulation, energy production, and biodiversity are just a few of the ESs that are dependent on healthy soils (Haygarth and Ritz 2009; Grêt-Regamey et al. 2017; McBratney et al. 2014; Volchko et al. 2013). Soil needs necessarily to be considered in ESs assessments (Huber and Kurzweil 2012; Dominati et al. 2010), and the importance of soils in this regard has been emphasised in several research (Adhikari and Hartemink 2016; Bouma 2014; Bouma et al. 2012; Haygarth and Ritz 2009; Hewitt et al. 2015; Robinson et al. 2013). In six case studies, Bouma (2015) strongly argued for the need to include soil in ESs evaluations highlighting the importance of soil and the use of soil information. In order to measure and quantify soils’ contributions to ESs, the ES community often refers to them as “natural capital stocks” (Hewitt et al. 2015; Robinson et al. 2009, Robinson et al. 2013). The ability of a particular form of soil to function within unmanaged or managed ecosystem boundaries was described by a working committee of the American Soil Science Society in 1995. This definition has highlighted the versatility of soils and their chemical, physical, and biological characteristics. The ability of soils to provide ESs is mainly influenced by their functions, and each specific soil function can be thought to contribute in some way to ESs (Bouma 2014). For more than a century, the soil science community has worked to understand how soil systems work, and recently closely related ideas such as soil quality indicators, soil health, and soil protection have also been established (Doran 2002; Karlen et al. 2003; Wienhold et al. 2004). While the policy was not ultimately implemented, the European Commission’s soil protection strategy (EC 2006) was a significant effort that raised awareness of the idea of soil functions among a wider audience and put it on the political scene. The strategy (EC 2006) identified seven functions of soil: 1. 2. 3. 4. 5. 6. 7.
Production of food and biomass, storage Filtering and transformation of compounds Habitats for living beings and genomic pools Cultural and physical surroundings Source of raw materials, carbon pool An archive of geological and archaeological heritage Natural environments for living beings and gene pools
Therefore, the soil security framework can be seen as one soil-related element in the broader ES strategy established by MEA (2005). The roles of soils in ESs were highlighted in the United Nations sustainable development goals for 2015–2030 in goal 15, “. . . .to protect, restore and promote sustainable use of terrestrial ecosystems. . .”.
8.2
SDGs Related to Soil Functions
The prudent use of natural resources is essential to the sustainability of human society. In addition to providing basic human requirements such as food and clean water and air, soils also play a significant role in supporting biodiversity. The
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Table 8.2 List of Ecosystem services related to soil functions and SDGs defined by European Commission (EC 2006)
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Ecosystem services 1 Provision of food, wood, and fibre 2 Provision of raw materials 3 Provision of support for human infrastructures and animals 4 Flood mitigation 5 Filtering of nutrients and contaminants 6 Carbon storage and greenhouse gas regulation 7 Detoxification and the recycling of wastes 8 Regulation of pests and disease populations 9 Recreation 10 Aesthetics 11 Heritage values 12 Cultural identity
sustainability of soil in the globalised world of the twenty-first century depends not only on management decisions made by farmers, foresters, and land planners but also on political choices regarding rules and regulations, marketing, and subsidies, with public perceptions being the most crucial factor (Keesstra et al. 2016). The United Nations Convention to Combat Desertification (UNCCD) also mentions soils but only in the context of drylands. The Rio + 20 conference on sustainable development held in 2012 in Rio de Janeiro stated that, while some improvement has been made, there is still significant global land and soil degradation and continued rapid depletion of rich soil resources, which limits the capacity for food production. We should therefore “strive to achieve a land degradation-neutral world in the context of sustainable development”, as stated in the Rio + 20 sustainable development conference (Töpfer et al. 2013). This agreement was expanded during the subsequent process of setting the SDGs, which was accepted by the UN General Assembly in September 2015 (Table 8.1). The goals 1, 4, 5, 8–11, 16, and 17 are examples of goals that are primarily socioeconomic in nature, but other goals are firmly focused on the biophysical system, in which soils play a significant part (e.g. goals 2, 3, 6, 7, 12–15). These two spheres together define human life and are mutually dependent, and socioeconomic factors must be taken into account while achieving goals with an ecological emphasis. Activities of farmers and foresters will be crucial for maintaining the environment, but urban growth also has a significant impact on local land use (Keesstra et al. 2016). The SDGs pose a significant challenge for global citizens and their different policy domains. The scientific world has a duty to provide all stakeholders with knowledge that enables them to make wise decisions. It is crucial to understand that most of SDGs have no specific link to soils. Instead, soils provide broader ecosystem services, which are the “benefits to society that ecosystems deliver”, and require collaboration between other professions (De Groot et al. 2002; Dominati et al. 2014; Robinson et al. 2013). Almost all land-related SDGs benefit, either directly or indirectly, from ecosystem services. Considering the seven soil functions as outlined by the European Commission (EC 2006) is an effective approach to think about how soil contributes to multidisciplinary studies on ecosystem services (Tables 8.2 and 8.3). As a result, an operational sequence is established, starting with the SDGs and
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Table 8.3 The seven soil functions (SFs) as defined by the European Commission (EC 2006) 1 2 3 4 5 6 7
Biomass production, including agriculture, and forestry Storing, filtering and transforming nutrients, substances, and water Biodiversity pool, such as habitats, species, and genes Physical and cultural environment for humans and human activities Source of raw material Acting as carbon pool Archive of geological and archaeological heritage
moving on to the main ecosystem services and how the soils can contribute to their improvement.
8.3
Soils of Indian Himalaya
The ecosystem of mountains is very fragile from the topographic, climatic, geological, and demographic points of view (Biswas and Mukherjee 2001). The Himalayan mountain ecosystem covers a large area equal to about 16.2% of India, which forms the northern Union territories (Jammu & Kashmir, Ladakh, Uttarakhand, Himachal Pradesh) and north-eastern states (Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim, and Tripura). The Himalayas, being youngest mountain range, were uplifted about 60–70 million years ago, and due to soil acidity, low cation exchange capacity, erosion, etc., the soils of this region are less fertile (Sen et al. 1997). Despite this, the Himalayan ecosystem provides great offsite benefits as it regulates drought, floods, and aquifer recharge for the adjacent lowlands. These hillside ecosystems are also rich in biodiversity, have great productive potential, and control the hydrology of the river basins. Soil plays an important role in these ecosystems and is strongly altered by landforms (Sawhney et al. 2000). The variation in soil due to different factors of soil formation, viz. relief, altitude, and slope is generally dominant in hilly regions (Gupta and Chera 1996). The variation in soil of Himalayan region has mainly been associated with land use and altitude (Walia et al. 1999). The Northwestern Himalayan tract covers an area of about 33.12 M ha, which is mainly categorised into three discrete landform types, viz. Greater Himalaya, Lesser Himalayas, and Siwaliks. The soils of greater Himalaya in the high ranges remain mostly covered with permanent snow cover and the gentle to moderate slopes and intermountain valleys possess a very thin soil cover with A-C soil profile and rock outcrops. The soils of this region have been characterised as TypicEutrocryepts, TypicCryorthents, Cryorthents, and Cryorthids at different places (Dhir 1971; Sehgal 1973; Walia et al. 1999; Yadav and Prasad 2005). The soils of lesser Himalaya cover 1.75 M ha (31.5%). These soils are considered extremely inconsistent in relation to the vegetation, geographical environment, and geology of the area (Sidhu et al. 1997; Rana et al. 2000; Walia et al. 1999; Singh et al. 1993, 2004). They are characterised as well to extremely drained, shallow to deep, loamy-skeletal,
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sandy, coarse-loamy, fine loamy, and non-calcareous/calcareous. In terms of soil reaction, they are slightly acidic to neutral on higher areas and slightly alkaline to neutral on the lower hills. They also possess high to very high organic carbon content owing to dense vegetation cover. These soils are classified as Typic/Dystric Eutrochrepts, Lithic/Typic Udorthents, Typic Udifluvents, Typic Hapludalfs, and Typic Hapludolls (Kaistha and Gupta 1994; Kirmani et al. 2013). The Siwaliks are a thin extended range of northwest and southeast lower hills of the Himalayan region, in the altitude range of 750–1200 m. The northern slopes, in particular, are abundantly forested, and the lower parts are generally levelled. The southern slopes are mostly barren, steep, and unproductive. The soil in fairly steep or in steeply sloping ridges generally belongs to Lithic and Typic Ustorthents (Entisols), the moderate slopes of peaks are Typic Dystrudepts (Inceptisols), and fallow slope soils mainly belong to Lithic and Typic Udorthents (Entisols) along with Typic Dystrudepts (Inceptisols). In the river valleys, the soils are deep and present gentle or moderately steep slopes. These soils also have high drainage capacity and low nutrient retention capacity due to high sand content. They are derived from sandstone (Typic Ustipsamments) or quartzite/mica (Typic Dystrudepts) and are developed on alluvium or colluviums (Sidhu and Surya 2014). The soils in north-eastern region are Acrisols. These soils are also highly weathered, are acidic, have low base saturation ( forest > agriculture ≥ horticulture
Forests with high undisturbed forest, moderately disturbed and degraded
Lichi
Soil fertility
Primary productivity
It was found that the S, B, Zn, and Mo were most common yield limiting nutrients in litchi under lower northern Himalayas of India
In terms of soil physicochemical properties, soils were having good fertility status in the study sites
Primary productivity
Shorea robusta
Carbon sequestration, soil fertility
The Q. leucotrichophora–based agroforestry system and forest store large amounts of carbon in tree biomass and soil
Primary productivity
Carbon sequestration
Quercus leucotrichophorabased agroforestry systems
Highest total organic carbon (TOC) was recorded in forest soils followed by horticultural systems, whereas the least was observed in degraded and agricultural systems while inorganic carbon (IC) decreased in the sequence of: degraded lands > forest > agriculture ≥ horticulture. The study highlights the impact of erosion on dynamics of soil carbon and its partitioning and suggests the need to promote better carbon sequestering land use systems towards conservation of top carbon rich soil and promoting sustainability in hill ecosystems particularly in Himalayas
Carbon sequestration
The study indicated that moderate level disturbance promotes better carbon sequestration rates, tree density, and the survival of seedlings. A degraded oak forest is expected to recover at a slower rate than an undisturbed forest after a clear cutting because of soil deterioration and slow responses of trees with depleted photosynthetic surfaces
–
Primary productivity
Carbon sequestration
Quercus leucotrichophora (banj oak)
(continued)
Savita et al. (2020)
Kongkham et al. (2021)
Kumar et al. (2021)
Hussain et al. (2019)
Pandey et al. (2020)
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Location
Himachal Pradesh
S. No.
10.
Table 8.5 (continued) Vegetation type –
Land use
– Soil erosion
–
Supporting
Soil-related ecosystem services Regulatory The data indicated that about 22% of total gross area of the state has annual soil loss less than 5 t ha-1, and this can be termed as very well within the tolerance limit. As recommended by the authors, this area does not require any specific soil conservation measures but improved land and crop production technologies need to be adopted for improving the productivity on sustainable basis
Highlights of the study
Sidhu and Yadav (2016)
References
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Pseudomonas, Stenotrophomonas, Serratia, and Acinetobacter (Salwan et al. 2010). Similar to microorganism variability, changes in land use have also been found to affect the population and abundance of soil macroorganisms in the Himalayan area. The conversion of primary forests to rubber plantations in Tripura resulted in the dominance of the exotic-endogeic Pontoscolex corethrurus earthworms. The changes in functional status were also observed from being endogenic under primary forest ecosystem and endo-anecic/endo-epigeic in plantations (Chaudhuri et al. 2008).
8.5
Challenges and Opportunities for Advancing Soil-Related SDGs in Himalayan Region
Being one of the faster-growing economies, India efficiently contributes to global food security and is capable of meeting sustainable development goals. The concept of ecosystem services is a key model to link the functioning of ecosystems with wellbeing of humans (Fisher et al. 2009). However, with the economic growth, India is facing the challenge of feeding the ever increasing population of the country (Das et al. 2022). On the other hand, even as the requirement of ecosystem services is increasing, the anthropogenic activities are constantly affecting this flow of services. Soil, the most important component of the earth ecosystem, is a vital, nonrenewable, and non-infinite natural resource that can perform many ecosystem services, such as food supply, nutrient supply, gaseous exchange, water filtration, and carbon store (Mishra et al. 2022). The degradation of natural resources owing to demographic factors, the reduction in forest covers and biodiversity, and global warming are some of the serious challenges. The degradation of farmland not only involves the impairment of soil (FAO and ITPS 2015) but also leads to the loss of wild species biodiversity (Dainese et al. 2019). Apart from the disturbances from harvesting the fodder and wood, changes in traditional land uses, forest fires, and climate change, the commercial exploitation of the Himalayan ecosystem by infrastructure development projects and dam constructions has been the main cause of forest and land degradation in this area (Thadani et al. 2014; Sati et al. 2020; Rawat et al. 2020a, b). The recent example of horrific subsidence of Joshimath land, due to the movement of underground material in January 2023, can be ascribed to various reasons among which the increased developmental activities, like dams and unplanned residential construction, have contributed to the generation of debris and have changed the flow of water. Earthquakes, soil compaction, and soil erosion are also some of the common causes of this type of subsidence (Bagheri-Gavkosh et al. 2021; The Indian express 2023). The surface run-off has also been reported to increase due to conversion of forest land for expansion of agriculture and high-intensity rainfalls (Tiwari 2000, Rawat et al. 2022a, b). The changes resulting in decreased water discharge either have completely dried the natural springs or made them seasonally functioning (Tiwari and Joshi 2014; Vashisht and Sharma 2007; Vashisht and Bam 2013; Tambe et al. 2012; Valdiya and Bartarya 1989). Soil erosion is one of the prominent contributors of land degradation in the Himalayan region and the foothills
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that promotes land degradation (Sati et al. 2020; Rawat et al. 2020a, b, 2021). The frequent soil erosion in slopes not only washes away the nutrients from the top layer, but the accumulation of organic carbon is also hampered leading to lowered productivity in the region (Kaur et al. 2021). Future strategies need to be focussed on the judicial management of natural resources and using available resources of nutrient in soils more effectively and efficiently for sustaining the productivity of land, especially in steep slopes of Himalaya (Singh et al. 1992; Tomar et al. 2022). The soils of Himalayan region have been reported to be deficient in nutrients like nitrogen, phosphorus, calcium, magnesium, sulphur, zinc, boron, and molybdenum (Prajapati et al. 2021; Sidhu and Surya 2014); therefore the balance between nutrient requirements of plants and available nutrients in the soil is necessary to maintain the fertility, prevent land degradation, and sustain productivity of agriculture and horticulture based land uses (Rawat et al. 2016; Srivastava et al. 2015, 2016; Rawat et al. 2022a, b; Savita et al. 2016; Kumar et al. 2020). Due to the lack of an efficient master plan on land use policy and legislation, the challenges associated with Himalayan ecosystem degradation and sustaining soil ecosystem services remain so far unresolved. The restoration of degraded ecosystems in Indian Himalayan regions is needed to be accomplished by interlinking various land uses like agriculture, agroforestry, waste lands, primary forests, and plantations to the policy making and implementation (Gibbs and Salmon 2015; Berendse et al. 2015) for achieving the soil-related sustainable development goals. Therefore, setting the conservation and landscape functionality in Himalayan land uses should be addressed to maintain synergy and trade-offs between various ecosystem services at a spatiotemporal scale (Brown 2004). A few strategies that can be adopted for the development of soil-related ecosystem services and realizing the sustainable development goals in the Indian Himalayan regions include: • The ecological degradation owing to human activities should be reversed in lower Himalayan regions by land shaping, bunding, reforestation, terracing, etc. • At higher altitudes, rehabilitation measures like afforestation should be implemented to reduce run-off and erosion in skeletal and shallow soils of steep slopes. • To reduce further degradation of soil, run-off, water scarcity integrated approach for watershed development should be implemented. • Monitoring the effect of climate change on soils, soil carbon, and length of growing season. • More research and studies on hydrology, watershed development, and groundwater discharge should be strengthened and conducted. • Awareness programmes to disseminate the importance of soil and its conservation should be implemented at administrative level.
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Conclusion
A refined approach towards sustainable forest and agriculture management to cut down land degradation, enhance carbon sequestration in soil, and improve primary productivity without jeopardising natural resources of the Himalayan ecosystem can considerably contribute to meet the United Nations Sustainable Development Goals in this area. To do this, the majority of applied soil research in the Himalayan region may be summarised in terms of how they relate to certain SDGs, along with which ecosystem services and related soil functions are crucial. By addressing a much wider audience, this new framework linking SDGs, ecosystem services, and soil functions would open the door for the scientific community to make more pertinent contributions to current important global and regional ecosystems assessments related to land and soils in Indian Himalayas. Overall, we should recognise that nature itself has provided services, and human efforts should be guided by the awareness that each ecosystem has its perspective and boundaries. Sustainable development can only be achieved by taking the ecosystem processes, feedbacks, and thresholds into consideration.
References Adhikari K, Hartemink AE (2016) Linking soils to ecosystem services—a global review. Geoderma 262:101–111 Amundson R, Heimsath A, Owen J, Yoo K, Dietrich WE (2015) Hillslope soils and vegetation. Geomorphology 234:122–132 Andrews SS, Karlen DL, Cambardella CA (2004) The soil management assessment framework: a quantitative soil quality evaluation method. Soil Sci Soc Am J 68(6):1945–1962 Assembly UNG (2015) Transforming our world: the 2030 agenda for sustainable development Bagheri-Gavkosh M, Hosseini SM, Ataie-Ashtiani B, Sohani Y, Ebrahimian H, Morovat F, Ashrafi S (2021) Land subsidence; a global challenge. Sci Total Environ 778:146193. https://doi.org/10. 1016/j.scitotenv.2021.146193 Banwart S (2011) Save our soils. Nature 474(7350):151–152 Barrios E (2007) Soil biota, ecosystem services and land productivity. Ecol Econ 64(2):269–285 Berendse F, van Ruijven J, Jongejans E, Keesstra S (2015) Loss of Plant Species Diversity Reduces Soil Erosion Resistance. Ecosystems 18: 881–888. https://doi.org/10.1007/s10021-015-9869-6 Bhattacharyya R, Pandey AK, Gopinath KA, Mina BL, Bisht JK, Bhatt JC (2016) Fertilization and crop residue addition impacts on yield sustainability under a rainfed maize–wheat system in the Himalayas. Proc Natl Acad Sci India Sect B Biol Sci 86(1):21–32 Biswas TD, Mukherjee SK (2001) Textbook of soil sciences. Tata McGraw-Hill Education, New York Bouma J (2010) Implications of the knowledge paradox for soil science. Adv Agron 106:143–171 Bouma J (2014) Soil science contributions towards sustainable development goals and their implementation: linking soil functions with ecosystem services. J Plant Nutr Soil Sci 177(2): 111–120 Bouma J (2015) Reaching out from the soil-box in pursuit of soil security. Soil Sci Plant Nutr 61(4): 556–565 Bouma J, McBratney A (2013) Framing soils as an actor when dealing with wicked environmental problems. Geoderma 200:130–139
164
D. Rawat et al.
Bouma J, Stoorvogel JJ, Sonneveld WMP (2012) Land evaluation for landscape units. In: Huang PM, Li Y, Summer ME (eds) Handbook of soil science. CRC, Boca Raton, pp 34-1–34-22 Boyd J, Banzhaf S (2007) What are ecosystem services? The need for standardized environmental accounting units. Ecol Econ 63(2–3):616–626 Brevik EC, Calzolari C, Miller BA, Pereira P, Kabala C, Baumgarten A, Jordán A (2016) Soil mapping, classification, and pedologic modeling: history and future directions. Geoderma 264: 256–274 Brown G (2004) Mapping Spatial Attributes in Survey Research for Natural Resource Management: Methods and Applications. Soc Nat Resour 18:(1)17-39. https://doi.org/10.1080/ 08941920590881853 Chaudhuri PS, Nath S, Paliwal R (2008) Earthworm population of rubber plantations (Hevea brasiliensis) in Tripura, India. Trop Ecol 49(2):225 Costanza R, d’Arge R, de Groot R, Farberk S, Grasso M, Hannon B, Limburg K, Naeem S, O’Neill RV, Paruelo J, Raskin RG, Suttonkk P, van den Belt M (1997) The value of the world’s ecosystem services and natural capital. Nature 387:253 Daily GC (1997) Introduction: what are ecosystem services. Nature’s services: Societal dependence on natural ecosystems, 1(1) New Haven: Yale University Press Daily GC, Söderqvist T, Aniyar S, Arrow K, Dasgupta P, Ehrlich PR, Walker B (2000) The value of nature and the nature of value. Science 289(5478):395–396 Dainese M et al (2019) A global synthesis reveals biodiversity-mediated benefits for crop production. Sci Adv 5:eaax0121. https://doi.org/10.1126/sciadv.aax0121 Das A, Lyngdoh D, Ghosh PK, Lal R, Layek J, Idapuganti RG (2018) Tillage and cropping sequence effect on physico-chemical and biological properties of soil in eastern Himalayas, India. Soil Tillage Res 180:182–193 Das BS, Wani SP, Benbi DK, Muddu S, Bhattacharyya T, Mandal B, Santra P, Chakraborty D, Bhattacharyya R, Basak N, Reddy NN (2022) Soil health and its relationship with food security and human health to meet the sustainable development goals in India. Soil Security 8:100071. https://doi.org/10.1016/j.soisec.2022.100071 De Groot RS, Wilson MA, Boumans RM (2002) A typology for the classification, description and valuation of ecosystem functions, goods and services. Ecol Econ 41(3):393–408 De Groot RS, Fisher B, Christie M, Aronson J, Braat L, Haines-Young R, Ring I (2010) Integrating the ecological and economic dimensions in biodiversity and ecosystem service valuation. In: The economics of ecosystems and biodiversity (TEEB): ecological and economic foundations. Routledge, London, pp 9–40 Dhir RP (1971) Micromorphology of some soils of the North Western Himalayas. J Indian Soc Soil Sci 19(2):179–184 Dixon RK (1994) Carbon pools and flux of global forest ecosystems. Science 265(5169):171–171 Dominati E, Patterson M, Mackay A (2010) A framework for classifying and quantifying the natural capital and ecosystem services of soils. Ecol Econ 69(9):1858–1868. https://doi.org/10. 1016/j.ecolecon.2010.05.002 Dominati E, Mackay A, Green S, Patterson M (2014) A soil change-based methodology for the quantification and valuation of ecosystem services from agro-ecosystems: a case study of pastoral agriculture in New Zealand. Ecol Econ 100:119–129 Doran JW (2002) Soil health and global sustainability: translating science into practice. Agric Ecosyst Environ 88(2):119–127 EC (2006) European Commission-thematic strategy for soil protection. EC, Brussel Faber JH, Van Wensem J (2012) Elaborations on the use of the ecosystem services concept for application in ecological risk assessment for soils. Sci Total Environ 415:3–8 FAO and ITPS (2015) Status of the World’s Soil Resources (SWSR); Main Report; Food and Agriculture Organization of the United Nations and Intergovernmental Technical Panel on Soils, Rome, Italy. Available online: ftp://ext-ftp.fao.org/nr/Data/Upload/SWSR_MATTEO/ Main_report/Pdf/web_Soil_Report_Main_001.pdf
8
Harnessing Soil Ecosystem Services for Achieving Soil-Based SDGs in. . .
165
Fisher B, Turner RK, Morling P (2009) Defining and classifying ecosystem services for decision making. Ecol Econ 68(3):643–653 Gangwar P, Alam SI, Bansod S, Singh L (2009) Bacterial diversity of soil samples from the western Himalayas, India. Can J Microbiol 55(5):564–577 Gibbs HK, Salmon JM (2015) Mapping the world's degraded lands. Appl Geogr 57:12–21. https:// doi.org/10.1016/j.apgeog.2014.11.024 Gogoi A, Ahirwal J, Sahoo UK (2022) Evaluation of ecosystem carbon storage in major forest types of eastern Himalaya: implications for carbon sink management. J Environ Manag 302:113972 Grêt-Regamey A, Sirén E, Brunner SH, Weibel B (2017) Review of decision support tools to operationalize the ecosystem services concept. Ecosyst Serv 26:306–315 Gupta SK, Chera RS (1996) Soil characteristics as influenced by slope aspects in middle Siwaliks. Agropedology 6:43–48 Hassan RR, Scholes AN (eds) (2005) Ecosystems and human well-being: current state and trends, vol 1. Findings of the condition and trends working group of the Millennium Ecosystem Assessment. Island Press, Washington, DC Haygarth PM, Ritz K (2009) The future of soils and land use in the UK: soil systems for the provision of land-based ecosystem services. Land Use Policy 26:S187–S197 Hewitt A, Dominati E, Webb T, Cuthill T (2015) Soil natural capital quantification by the stock adequacy method. Geoderma 241:107–114 Houghton RA, House JI, Pongratz J, Van Der Werf GR, Defries RS, Hansen MC, Ramankutty N (2012) Carbon emissions from land use and land-cover change. Biogeosciences 9(12): 5125–5142 Huber S, and Kurzweil A (2012) Guide municipal soil management Hussain S, Sharma V, Arya VM, Sharma KR, Rao CS (2019) Total organic and inorganic carbon in soils under different land use/land cover systems in the foothill Himalayas. Catena 182:104104 IUSS (2014) World Reference Base for Soil Resources 2014. International Soil Classification System for Naming Soils and Creating Legends for Soil Maps. World Soil Resources Reports 106. FAO, Rome Jha MN, Gupta MK, Saxena A, Kumar R (2003) Soil organic carbon store in different forests of India. Indian Forester 129(6):714–724 Joshi AK, Joshi PK (2019) Forest ecosystem services in the central Himalaya: local benefits and global relevance. Proc Natl Acad Sci India Sect B Biol Sci 89(3):785–792 Kaistha BP, Gupta RD (1994) Morphology and characteristics of a few Entisols and Inceptisols of North-Western Himalayan region. J Indian Soc Soil Sci 42(1):100–104 Karlen DL, Ditzler CA, Andrews SS (2003) Soil quality: why and how? Geoderma 114(3–4): 145–156 Kaur T, Sehgal SK, Singh S, Sharma S, Dhaliwal SS, Sharma V (2021) Assessment of seasonal variability in soil nutrients and its impact on soil quality under different land use systems of lower Shiwalik foothills of Himalaya, India. Sustainability 13(3):1398 Keesstra SD, Bouma J, Wallinga J, Tittonell P, Smith P, Cerdà A, Fresco LO (2016) The significance of soils and soil science towards realization of the United Nations sustainable development goals. Soil 2(2):111–128 Kirmani NA, Wani MA, Sofi JA (2013) Characterization and classification of Alfisols under lesser Himalayan temperate region. Agropedology 23(2):118–121 Kongkham B, Khanduri VP, Rawat D, Singh B, Riyal M, Ahmad T (2021) Community structure, regeneration status, carbon sequestration potential and soil properties in Shivalik Sal forests of Uttarakhand, India. Adv Biores 12(4):206–215 Kumar S, Singh B, Rawat D, Singh AP, Tewari S (2020) Physico-chemical properties of soil and productivity of lentil (Lens culinaris medic.) and wheat (Triticum aestivum L.) under existing agri-horticulture system in mid hills of Uttarakhand Himalaya. J Tree Sci 39(2):24–32 Kumar S, Bijalwan A, Singh B, Rawat D, Yewale AG, Riyal MK, Thakur TK (2021) Comparison of carbon sequestration potential of Quercus leucotrichophora–based agroforestry systems and natural Forest in central Himalaya, India. Water Air Soil Pollut 232(9):1–16
166
D. Rawat et al.
Lal R (2015) Restoring Soil Quality to Mitigate Soil Degradation. Sustainability 7(5):5875–5895. https://doi.org/10.3390/su7055875 Lavelle P, Decaëns T, Aubert M, Barot S, Blouin M, Bureau F, Rossi JP (2006) Soil invertebrates and ecosystem services. Eur J Soil Biol 42:S3–S15 Lawton JH, Daily GC (1997) Nature’s services. Societal dependence on natural ecosystems. Island Press, Washington, DC, p 392. ISBN 1-55963-475-8 hbk), 1 55963 476 6 (soft cover. In Animal conservation forum 1998 Feb (Vol. 1, no. 1, pp. 75-76). Cambridge University Press, 01, 75 McBratney A, Field DJ, Koch A (2014) The dimensions of soil security. Geoderma 213:203–213 MEA (2005) Ecosystems and human Well-being: current state and trends. Millennium ecosystem assessment, Global assessment reports. Island Press, Washington, DC Meena VS, Mondal T, Pandey BM, Mukherjee A, Yadav RP, Choudhary M, Pattanayak A (2018) Land use changes: strategies to improve soil carbon and nitrogen storage pattern in the mid-Himalaya ecosystem, India. Geoderma 321:69–78 Mishra G, Debnath S, Rawat D (2017) Managing phosphorus in terrestrial ecosystem: a review. Eur J Biol Res 7:255–270 Mishra G, Sulieman MM, Kaya F, Francaviglia R, Keshavarzi A, Bakhshandeh E, Rawat D (2022) Machine learning for cation exchange capacity prediction in different land uses. Catena 216: 106404 Mondal PP, Zhang Y (2018) Research progress on changes in land use and land cover in the western Himalayas (India) and effects on ecosystem services. Sustainability 10(12):4504 National Research Council, Geographical Sciences Committee (2014) Advancing land change modeling: opportunities and research requirements. National Research Council, Washington, DC Negi GCS, Agarwal DK (2006) Measuring and valuing ecosystem services: Himalayan mountain context. Current Sci 91(5):573 Palm C, Sanchez P, Ahamed S, Awiti A (2007) Soils: a contemporary perspective. Annu Rev Environ Resour 32:99–129 Pandey A, Arunachalam K, Thadani R, Singh V (2020) Forest degradation impacts on carbon stocks, tree density and regeneration status in Banj oak forests of central Himalaya. Ecol Res 35(1):208–218 Pant M, Negi GC, Kumar P (2017) Macrofauna contributes to organic matter decomposition and soil quality in Himalayan agroecosystems, India. Appl Soil Ecol 120:20–29 Pereira APDA, Andrade PAMD, Bini D, Durrer A, Robin A, Bouillet JP, Cardoso EJBN (2017) Shifts in the bacterial community composition along deep soil profiles in monospecific and mixed stands of Eucalyptus grandis and Acacia mangium. PLoS One 12(7):e0180371 Peterson GD, Carpenter SR, Brock WA (2003) Uncertainty and the management of multistate ecosystems: an apparently rational route to collapse. Ecology 84(6):1403–1411 Phalan B, Onial M, Balmford A, Green RE (2011) Reconciling food production and biodiversity conservation: land sharing and land sparing compared. Science 333(6047):1289–1291 Pielke RA Sr, Pitman A, Niyogi D, Mahmood R, McAlpine C, Hossain F, de Noblet N (2011) Land use/land cover changes and climate: modeling analysis and observational evidence. Wiley Interdiscip Rev Clim Chang 2(6):828–850 Porter J, Costanza R, Sandhu H, Sigsgaard L, Wratten S (2009) The value of producing food, energy, and ecosystem services within an agro-ecosystem. AMBIO J Hum Environ 38(4): 186–193 Prajapati A, Pachauri S, Srivastava P, Pathak A, Rawat D (2021) Status of some extractable macroand micro-nutrients in soils of Tehri Garhwal district of Uttarakhand. Pantnagar J Res 19(2):171 Qazi N (2020) Hydrological functioning of forested catchments, central Himalayan region, India. For Ecosyst 7:63 Rai A, Saha SP, Manvar T, Bhattacharjee A (2022) A shotgun approach to explore the bacterial diversity and a brief insight into the glycoside hydrolases of Samiti lake located in the eastern Himalayas. J Genet Eng Biotechnol 20(1):1–11
8
Harnessing Soil Ecosystem Services for Achieving Soil-Based SDGs in. . .
167
Rana KPC, Walia CS, Sidhu GS, Singh SP, Velayutham M, Sehgal J (2000) Soils of Jammu and Kashmir for optimizing land use, vol 62. NBSS Publ, Nagpur, p 71 Rawat D, Singh, AP, Bhatt SC, Supriya (2016) Impact of resource conservation technologies and fertilizer doses on rice under Mollisols of Uttarakhand. Advances in Life Sciences 5(5):1652– 1657 Rawat D, Khanduri VP, Sati SP, Ahmad T, Riyal M, Mishra P (2020a) Impact of forest fire on soil quality and resilience potential: a review. ADRRI J Agric food Sci 4(6 (4)):59–81 Rawat M, Arunachalam K, Arunachalam A, Alatalo JM, Kumar U, Simon B, Pandey R (2020b) Relative contribution of plant traits and soil properties to the functioning of a temperate forest ecosystem in the Indian Himalayas. Catena 194:104671 Rawat D, Sati SP, Khanduri VP, Riyal M, Mishra G (2021) Carbon sequestration potential of different land use sectors of Western Himalaya. In: Advances in carbon capture and utilization. Springer, Singapore, pp 273–294 Rawat D, Mishra P, Ray S, Warnakulasooriya HHF, Sati SP, Mishra G, Abotaleb M (2022a) Modeling of rainfall time series using NAR and ARIMA model over western Himalaya, India. Arab J Geosci 15(23):1–26 Rawat D, Mukhopadhyay D, Mishra G, Bijalwan A (2022b) Soil nitrogen dynamics and Management in Agroforestry Systems for ecological sustainability. In: Land degradation neutrality: achieving SDG 15 by Forest management. Springer, Singapore, pp 381–403 Robinson DA, Lebron I, Vereecken H (2009) On the definition of the natural capital of soils: a framework for description, evaluation and monitoring. Soil Sci Soc Am J 73:1904–1911 Robinson DA, Lebron I, Ryel RJ, Jones SB (2010) Soil water repellency: a method of soil moisture sequestration in pinyon–juniper woodland. Soil Sci Soc Am J 74(2):624–634 Robinson DA, Hockley N, Cooper DM, Emmett BA, Keith AM, Lebron I, Robinson JS (2013) Natural capital and ecosystem services, developing an appropriate soils framework as a basis for valuation. Soil Biol Biochem 57:1023–1033 Robinson DA, Fraser I, Dominati EJ, Davíðsdóttir B, Jónsson JOG, Jones L, Clothier BE (2014) On the value of soil resources in the context of natural capital and ecosystem service delivery. Soil Sci Soc Am J 78(3):685–700 Rogan J, Chen D (2004) Remote sensing technology for mapping and monitoring land-cover and land-use change. Prog Plan 61(4):301–325 Saha D, Kukal SS, Bawa SS (2012) Soil organic carbon stock and fractions in relation to landuse and soil depth in degraded Shiwalik of lower Himalayas. Land Degrad Dev 25(5):407–416 Saha D, Kukal SS (2015) Soil structural stability and water retention characteristics under different land uses of degraded lower Himalayas of north-West India Land Degrad. Dev 26(2015):263– 271. https://doi.org/10.1002/ldr.2204 Salwan R, Gulati A, Kasana RC (2010) Phylogenetic diversity of alkaline protease-producing psychrotrophic bacteria from glacier and cold environments of Lahaul and Spiti, India. J Basic Microbiol 50(2):150–159 Sandhu HS, Wratten SD, Cullen R (2010a) Organic agriculture and ecosystem services. Environ Sci Pol 13(1):1–7 Sandhu HS, Wratten SD, Cullen R (2010b) The role of supporting ecosystem services in conventional and organic arable farmland. Ecol Complex 7(3):302–310 Sati SP, Sharma S, Sundriyal YP, Rawat D, Riyal M (2020) Geo-environmental consequences of obstructing the Bhagirathi River, Uttarakhand Himalaya, India. Geomat Nat Haz Risk 11(1): 887–905 Savita S, Krishnappa R, Ngangom B, Devi MT, Mishra G, Rawat D, Srivastava PC (2016) Diagnosis and recommendation integrated system (DRIS) approach on nutritional diagnosis in fruit crops-a review. J App Nat Sci 8(4):2337–2345 Savita B, Srivastava PC, Verma SM, Rawat D, Rangappa K, Raghupathi HB, Rymbai H (2020) Multivariate diagnosis of nutrient imbalances in different yield categories of litchi in north Indian lower Himalayas. Indian J Hortic 77(4):640–646
168
D. Rawat et al.
Sawhney JS, Verma VK, Jassal HS (2000) Soilphysiographic relationship in southeastern sector of submontane tract of Punjab. Agropedology 10(1):6–15 Sehgal JL (1973) Studies of some soils in the NW Himalayas and the highlands of India. Geoderma 9(1):59–74 Sen TK, Nayak DC, Singh RS, Dubey PN, Maji AK, Chamuah GS, Sehgal J (1997) Pedology and Edaphology of Bem: hmark AcH soils of north-eastern India. J Indian Soc Soil Sci 45(4): 782–790 Sharma E, Rai SC, Sharma R (2001) Soil, water and nutrient conservation in mountain farming systems: case-study from the Sikkim Himalaya. J Environ Manag 61(2):123–135 Sidhu GS, Surya JN (2014) Soils of North-Western Himalayan eco-system and their land use, constraints, productivity potentials and future strategies. Agropedology 24(01):1–19 Sidhu GS, Rana KPC, Sehgal J, and Velayutham M (1997) Soils of Himachal Pradesh for optimizing land use. NBSS publ. 57. (soils of India series). National Bureau of Soil Survey & Land use Planning, Nagpur, India, 44 p + 2 sheets soil map (1:50,000 scale) Sidhu GS, Yadav RP (2016) Soil Degradation in North-West Himalayas (NWH): A Case Study of Himachal Pradesh. In: Bisht J, Meena V, Mishra P, Pattanayak A (eds) Conservation Agriculture. Springer, Singapore. https://doi.org/10.1007/978-981-10-2558-7_15 Singh S (2002) Balancing the approaches of environmental conservation by considering ecosystem services as well as biodiversity. Curr Sci 82(11):1331–1335 Singh SP (2007) Himalayan forest ecosystem services incorporating in national accounting, vol 9. Central Himalayan Environment Association (CHEA), Nainital, Uttarakhand. Waldorf compound, Nainital, Uttarakhand, India Consul Printers. Uttarakhand: Nainital Singh K, Sharma PD, Bhandari AR (1992) Land capability classes and management needs for sustained productivity in semi-arid regions of North-West Himalayas. Agropedology 2:51–57 Singh K, Tripathi D, and Tomar KP (1993) Pedogenesis and taxonomy of soils in topo-sequence of Central Himalayas Singh SP, Ram J, Walia CS, Sachdev CB, Dhankar RP, Rana KPC, Gajbhiye KS (2004) Soils of Uttar Pradesh for optimizing land use, vol 68. NBSS Publ, New Delhi, pp 1–91 Smit E, Bakker PA, Bergmans H, Bloem J, Griffiths BS, Rutgers M, Glandorf DC (2012) General surveillance of the soil ecosystem: an approach to monitoring unexpected adverse effects of GMO's. Ecol Indic 14(1):107–113 Srivastava PC, Rawat D, Pachauri SP, Shrivastava M (2015) Strategies for enhancing zinc efficiency in crop plants. In: Nutrient use efficiency: from basics to advances. Springer, New Delhi, pp 87–101 Srivastava A, Rawat KS, Bhatt SC, Rawat D, Srivastava PC (2016) Degradation of AM nitrification inhibitor in soil of subtropical region. Commun Soil Sci Plant Anal 47(17):1961–1966 Swinton SM, Lupi F, Robertson GP, Hamilton SK (2007) Ecosystem services and agriculture: cultivating agricultural ecosystems for diverse benefits. Ecol Econ 64(2):245–252 Tambe S, Kharel G, Arrawatia ML, Kulkarni H, Mahamuni K, Ganeriwala AK (2012) Reviving dying springs: climate change adaptation experiments from the Sikkim Himalaya. Mt Res Dev 32(1):62–72 Thadani R, Singh V, Shahabuddin G (2014) MEETING REPORT: Forests of the Western Himalaya. Curr Sci 107(8):1225–1226 The Indian Express (2023) Joshimath crisis: what is land subsidence and why does it happen? https://indianexpress.com/article/explained/explained-climate/joshimath-what-is-land-subsi dence-and-why-does-it-happen-8370817/ Tiwari PC (2000) Land-use changes in Himalaya and their impact on the plains ecosystem: need for sustainable land use. Land Use Policy 17(2):101–111 Tiwari PC, Joshi B (2014) Environmental changes and their impact on rural water, food, livelihood, and health security in Kumaon Himalaya. Int J Urban Reg Stud Contemp India 1(1):1–12 Tomar JMS, Kumar R, Kaushal R, Kar SK, Mehta H, Chaturvedi OP (2022) Soil conservation measures improve vegetation development and ecological processes in the Himalayan slopes. Trop Ecol 64:1–9
8
Harnessing Soil Ecosystem Services for Achieving Soil-Based SDGs in. . .
169
Töpfer K, Müller A, Weigelt J (2013) Governing the transformation of soils must urgently be improved. Rural 21 47(3):6–8 Valdiya KS, Bartarya SK (1989) Diminishing discharges of mountain springs in a part of Kumaun Himalaya. Curr Sci 58(8):417–426 Vashisht AK, Bam B (2013) Formulating the spring discharge-function for the recession period by analyzing its recession curve: a case study of the Ranichauri spring (India). J Earth Syst Sci 122(5):1313–1323 Vashisht AK, Sharma HC (2007) Study on hydrological behaviour of a natural spring. Curr Sci 69: 837–840 Volchko Y, Norrman J, Bergknut M, Rosén L, Söderqvist T (2013) Incorporating the soil function concept into sustainability appraisal of remediation alternatives. J Environ Manag 129:367–376 Walia CS, Rana KPC, Sidhu GS, Mahapatra SK, and Lal T (1999) Characterisation and classification of some soils of Ladakh region for land use. Agropedology (India) Wall DH (ed) (2004) Sustaining biodiversity and ecosystem services in soils and sediments, vol 64. Island Press, Washington, DC Warr B, Ayres R (2004) Accounting for soils: towards an integrated sustainability and productivity assessment for soils. INSEAD, CMER, Fontainbleau, pp 1–11 Weber T (2007) Ecosystem services in Cecil County’s green infrastructure. The Conservation Fund, Arlington, VA Wienhold BJ, Andrews SS, Karlen DL (2004) Soil quality: a review of the science and experiences in the USA. Environ Geochem Health 26(2):89–95 Yadav J, Prasad J (2005) Characteristics of some typical pedons from Leh. Ann Arid Zone 44(2) Yadav GS, Das A, Babu S, Mohapatra KP, Lal R, Rajkhowa D (2021) Potential of conservation tillage and altered land configuration to improve soil properties, carbon sequestration and productivity of maize based cropping system in eastern Himalayas, India. Int Soil Water Conserv Res 9(2):279–290 Zhang W, Ricketts TH, Kremen C, Carney K, Swinton SM (2007) Ecosystem services and dis-services to agriculture. Ecol Econ 64(2):253–260
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AFOLU Sectors of North East India and Their Potential for Soil Carbon Storage Kingshuk Modak, Nibedita Guru, Gaurav Mishra and Abhishek Jangir
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Abstract
Agriculture, Forestry, and Other Land Use (AFOLU) sectors, within terrestrial ecosystems, may have implications on carbon (C) emission and storage capability. Diversification of forests to other land use sectors is considered as one of the most important factors for C emissions. But, due to the increase in population, unsustainable productivity, and livelihood issues, many of the forest areas are under threat of conversion to other land use sectors. Land-use change activities (LUCs) are another source of anthropogenic C emissions, and deforestation is the major one accounting for 10–12% of C emission. The North-East (NE) region of India, which is a biodiversity hotspot due to the richness of natural resources, can be considered as one of the most important regions for the carbon storage. During the last few decades, the NE region of India had faced rapid changes in land use pattern, especially due to settled plantation systems. Permanent plantations systems, like tea gardens, rubber plantations, which are having 40–50 years of growth period, can become C sinks over a long-term basis. Tea cultivation in NE India has come a long way since its first cultivation by Robert Bruce in 1823. It was first started in Assam, but nowadays it can find in all the states of NE India. Similarly, rubber cultivation is another land use sector, which can store carbon both in above and below ground parts. Earlier rubber cultivation was confined to Tripura, but nowadays it can be seen in Assam, Meghalaya, and Nagaland. These
K. Modak · N. Guru Forest Ecology and Climate Change Division, ICFRE-Rain Forest Research Institute, Jorhat, Assam, India G. Mishra (✉) Indian Council of Forestry Research and Education, Dehradun, Uttarakhand, India A. Jangir ICAR—National Bureau of Soil Survey and Land Use Planning, RC, Udaipur, India # The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Mishra et al. (eds.), Soil Carbon Dynamics in Indian Himalayan Region, https://doi.org/10.1007/978-981-99-3303-7_9
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land use sectors, having enormous soil C storage capability, provide economic resilience for the small farmers. These settled land use sectors in NE India are adopted to generate the additional income, but can also serve as potential reservoirs of additional C storage. So, keeping the above facts in mind, this chapter deals with the potential of AFOLU sectors of NE India for C storage and their contribution toward Reducing Emissions from Deforestation and Forest Degradation (REDD+). Keywords
Land uses · Tea · Rubber · Jhum · North East India · Carbon stock
9.1
Introduction
The Agriculture, Forestry, and Other Land Use (AFOLU) sector plays a pivotal role in providing food security and ecosystem services for sustainable human development. In fifth assessment report of the Inter-Governmental Panel on Climate Change (IPCC), the term AFOLU was first used to bifurcate the anthropogenic source of greenhouse gas (GHG) emission (IPCC 2014) into two parts, i.e., Agriculture and Land Use, Land Use Change, and Forestry (LULUCF). Globally, the AFOLU sectors contribute to 24% of total GHG emission (Kumar and Aravindakshan 2022) (Fig. 9.1). Although the developing countries account for 1/3rd of GHG emission from these sectors, India contributes 8% only. From 1970 to 2018, the GHG emission increased from 746.5 to 3375 million metric tons CO2 equivalent (MtCO2e) primarily due to substantial rise in industrialization and agricultural intensification (Climate Watch 2020). The United Nations Framework Convention on Climate Change (UNFCCC) recently reported that agriculture sector produces 14.36% of the nation’s total emission. Unsustainable agricultural activities (like crop residue burning, intensive tillage, paddy cultivation), enteric fermentation, and improper soil management are the main sources of C footprint from Indian agriculture (Sinha and Tripathi 2021). Although deforestation, forest fire, and shifting cultivation have been designated sources of C emission, the LULUCF sector acts as a potential net C sink rather than a source. The third biennial update report of Ministry of Environment, Forests, and Climate Change, Government of India, indicated that this sector helps in accrual of 330.76 Mt. of CO2, which accounts for 15% of total carbon dioxide (CO2) loss from all sectors (MoEFCC 2021). The forestry and agricultural sectors are human-centric dynamic land use. Unsustainable developmental activities may also cause ecosystem degradation in terms of decline in crop productivity and soil quality apart from soil C loss. Under the present scenario, the land use transformation is driven by certain factors such as increased population pressure, strive for monetary benefits, change in food production pattern, eating habits, and climate change (CC) (Fróna et al. 2019; Mora et al. 2020). The impact of CC is grossly visible around the world. Negative feedback of CC on agriculture and forest is a potential threat to food security and ecosystem functions,
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Fig. 9.1 Sources of CO2 emissions globally (Tubiello 2014)
respectively (Tubiello et al. 2014; Singh et al. 2020). The magnitude of alteration of land use may often vary in between and within the countries due to spatial and temporal variation in CC drivers. The south-Asian countries (like India, Bangladesh, and Nepal) are predominantly dependent on agriculture and forest for their means of support and source of revenue (Shrestha et al. 2021). In the last few decades, forest ecosystem has been posing a serious threat to indiscriminate mining of natural resources in India. Natural forests are witnessing severe stress like human encroachment, conversion to agriculture land use, indiscriminate timber extraction, and also paving way for developmental activities such road, infrastructure, and hydropower projects. Eventually, in the future, this potential net C sink could turn into significant C source due to fragmentation of land areas, decline in net productivity, and conversion into small patches (Kumari et al. 2019; Talukdar et al. 2020). Indian soils have low appetite for C (Mandal et al. 2007). Being a tropical nation with high temperature and heavy rainfall in most of its region, the C-capturing capacity of these soils is conditioned by climate and poor land management practices and limited by various soil type. The North-east region of India is endowed with species richness and diversity and is considered as one of the 12 biodiversity hotspots around the world (Choudhury et al. 2013). According to Forest Survey of India, this region constitutes one-fourth forest cover in just 7.98% of the total geographical area of the country (ISFR 2021). Due to population explosion and to meet livelihood, the forests are converted to produce crop. Such unsustainable
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management is not only depleting region’s rich biodiversity but also declining soil quality and SOC status. Therefore, C centric management should be carried out for sustaining optimum productivity and maintaining critical C level in agriculture and forest lands. Thus, mitigation policies in agricultural and forest lands to tackle CC are a win-win strategy. C plantation through AFOLU sector can be an eco-friendly and cost-effective way to maintain critical C concentration in India soils and thereby reduce the impact of CC. Smith et al. (2014) suggested three principle mitigation opportunities within AFOLU consisting of one or more of these strategies: prevention or reduction of GHG emissions by conservation of existing vegetation and soil C pools that would otherwise be lost into atmosphere; enhancing the sequestration capacity of terrestrial C sink and thereby reducing atmospheric CO2 concentration; substitution of fossil fuel by renewable source of energy and need-based change in lifestyle, food habits, wood consumption, and reduction in wastage of food may also play a crucial role in improving assimilating soil C. In this chapter, some high soil C sink land uses, which have potential to improve NE soil health and also contribute to Reducing Emissions from Deforestation and Forest Degradation (REDD+), are discussed elaborately.
9.2
SOC Stock Under Tea Plantation of NE India
Tea (Camellia sinensis) is one of the principal plantation crops in north-east region (NER) of India. Tea cultivation was initiated in 1823 by Englishman Robert Bruce in Assam, and later it spread through different north-east states. Since then, tea industry has become the backbone of states’ economy and contributed to socioeconomic upliftment of indigenous farmers and local communities. In NER region of India, tea gardens account for 18.5% and 3.4% of agricultural and total land areas, respectively and generate employment to about 1 million daily-waged labors (Choudhary et al. 2019). Assam is the front runner in tea production among north-eastern states and contributes to 51% of the country’s total tea production (Das and Mishra 2020). According to a report published by the Tea Board of India (2022), Assam produced 771 million kg (Mkg) of tea out of 1343.06 Mkg of total production in 2021. Tea is a woody perennial evergreen cash crop with a huge potential to store C in its biomass and soil (Kumar and Nair 2011). Recent trend indicates adoption of tea cultivation in native forest lands or established agricultural fields by the small-scale farmers for economic benefits (Deka and Goswami 2021). Since tea is a permanent settlement, accurate quantification of SOC stock in this intensively managed plantation is essential to evaluate the soil quality for better understanding of soil C dynamics under short and long-term scenarios. Several studies have suggested that tea root system forms a unique microenvironment in the rhizosphere region due to release of root exudates, organic acids, and management practices (Kamau et al. 2008). Phukan et al. (2018) estimated that tea crops can assimilate 1243.8–2526.7 kg CO2 ha-1 year-1 in its biomass. The assimilated CO2 is converted to labile C compounds (low-molecular-weight organic acids, amino acids, flavonoids, and sugar) and secreted in tea rhizosphere. This labile organic C constitutes ~5.9–8.6%
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of assimilated CO2 and may increase SOC by 44–48 kg ha-1 year-1 in tea cultivated soils (Pramanik and Phukan 2020). Seasonal pruning of branches and leaves to promote fresh flush of leaves also stimulated SOC accumulation. Climatic factors directly govern the SOC accumulation and loss by changing soil microbial community and fluctuation in soil moisture and temperature regime. Besides this, tea bushes and shade trees (Albizia odoratissima, A. chinensis, A. procera) minimize SOC depletion by preventing soil erosion caused due to beating action of rain (Zhang et al. 2013). Furthermore, topography and climate also have a significant role in tea production in term of biomass and leaf quality. Several scientific research findings reported that long-term tea plantation had a positive change in SOC stock (Table 9.1). In the Barak Valley of Assam, Kalita et al. (2016) reported that soil under tea agroforestry holds 101.19 Mg ha-1 OC up to 1 m depth. Besides this, multistoried plantation including alder, tea, and black pepper showed 8% substantial increase in SOC stock in comparison to other agroforestry systems prevalent in NER (Saha et al. 2012). Application of phosphatic fertilizer in tea gardens also enhances SOC concentration by improving formation and stability of microaggregates through physical stabilization and microbial inaccessibility (Misra 2018). On the other hand, addition of nitrogenous fertilizer improves conversion of biomass with high C: N to humus with low C: N in tea-growing soil, thereby improving the lability of SOC. A pre-monsoon study on SOC dynamics up to 80 cm soil depth was carried out in Silcoorie tea estate in Assam (Harongbam 2014). The SOC concentration was maximum at the surface (1.61%) and depleted with increasing depth. Similar result was also observed in several tea estates of Tripura where on an average SOC concentration depleted by 71.4% in subsurface soil in comparison with surface soil (Choudhury et al. 2013). Pruning litters, dropping from shade trees, and preferential stabilization of root-derived C might have attributed to increased SOC content in surface soil layers. Mishra et al. (2021) studied the variation in SOC stock in tea plantation under different age groups in Meghalaya. They reported that over 40-year chrono sequence SOC stock under baseline climatic scenario was maximum in case of 10–15 -yearsold plantation (94.3 Mg C ha-1) and thereafter got stabilized in 30–40-years-old plantation (84 Mg C ha-1) with minimum SOC content (74 Mg C ha-1) in 20–25years-old plantation. On the other hand, in Assam, Kalita et al. (2016) reported 35.7, 32.2, 45.4 and 32.1 Mg C ha-1 SOC stock under 5–10, 10–15, 20–25 and 25–30years-old plantations, respectively, but did not observe any significant trend. Gogoi et al. (2016) carried out seasonal soil sampling to study the impact of moisture and temperature on OC in tea-growing soil. They reported that SOC concentration increased by 37.8% during winter in comparison with monsoon season. High temperature with favorable soil moisture in monsoon season might have enhanced SOC loss. Furthermore, tea plantation also showed to sustain under abrupt climate change (ACC) scenario. A simulation study done in Meghalaya showed that tea-growing soils contain 10–15% more SOC than soil under forest prior to conversion (Mishra et al. 2021). Thus, adoption of tea crop by conversion of forest can be a viable option to sustain soil quality, mitigate ACC, and simultaneously generate livelihood for local small-scale farmers.
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Table 9.1 Soil organic carbon (SOC) stock under different land uses in North-East India
Place Forest Subtropical wet hill forest Mawphlang, Meghalaya Mixed-oak Forest, Manipur Natural forest, Senapati District, Manipur Bamboo forest, Chandipur, Hailakandi Forest, Barapani, Meghalaya Bamboo forest, Imphal, Manipur Dipterocarpus forests in Karimganj district, Assam Tropical rainforest, Assam
Soil depth (cm)
SOC (%)
SOC stock (Mg ha-1)
0–30
5.90
70.80
0–10
4.40
60.72
0–10
1.20
Reference Arunachalam and Arunachalam (2000) Supriya Devi and Yadava (2009) Binarani and Yadava (2010) Laskar et al. (2012)
0–30
0.53
21.15
0–30 0–30
1.92 1.62
56.45 63.36
0–100
1.40
141.13
0–20
2.41
–
0–15 0–15 0–30 0–100
2.30 5.25 2.75 –
– – 52.74 129.46
Adhikari and Bhattacharyya (2015) Chatterjee et al. (2016) Vashum et al. (2016) Sahoo et al. (2019) Nath et al. (2021)
0–30 0–30
2.02 1.91
– 58.45
Dutta et al. (2010) Saha et al. (2012)
0–20
1.55
–
Gogoi et al. (2016)
0–30 0–30
1.28 1.66
49.72 62.75
Mon district, Nagaland Tura district, Meghalaya Rubber Agartala, Tripura,
0–30 0–30
2.47 2.44
73.62 87.84
Kalita et al. (2016) Mishra and Sarkar (2020) Mishra et al. (2019) Mishra et al. (2021)
0–30
1.99
93.10
Unakoti districts, Tripura Barak valley, Assam Kolasib district, Mizoram
0–100 0–100 0–45
1.18 – 1.09
176.74 97.00 61.27
Mizoram, NER
0–30
2.02
76.96
Ri-Bhoi district, Meghalaya Tura district, Meghalaya
0–30 0–30
1.34 1.46
43.41 54.63
Tura district, Meghalaya
0–30
1.94
71.58
Forest, Nagaland Ukhrul, Manipur Forest, Mizoram Karbi Anglong district, Assam Tea Terai region, Assam Tea based multistoried AFS, Barapani, Meghalaya Tea-based agroforestry, Golaghat district, Assam Barak Valley, Assam Tura district, Meghalaya
Saha et al. (2012) Thokchom and Yadava (2014) Debajit et al. (2014)
Mandal and Islam (2010) Choudhary et al. (2016) Nath et al. (2018) Lungmuana et al. (2019) Manpoong and Tripathi (2019) Mishra et al. (2020a, b) Mishra and Sarkar (2020) Mishra et al. (2021)
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Additionally, in permanent settlements like tea, aged bushes are replaced by young ones, which also prevent C loss through tree felling. Therefore, tea plantation conserves C in biomass and soil for a longer time period in terrestrial ecosystem and hence, provides a way in Reducing Emissions from Deforestation and Forest Degradation (REDD+) when combined with suitable agroforestry system.
9.3
SOC Stock Under Rubber Plantation of NE India
Rubber trees (Hevea brasiliensis) were introduced in Asia from Rio Tapajo’z region of Amazon basin by Sir Henry Wickam (Dijkman 1951). Due to increasing demand and commercial importance of natural rubber, this tree species is cultivated in many tropical countries (Venkatachalam et al. 2013). In addition to this, policymakers are gaining interest as scientific research documented that rubber plantations have tremendous potential in restoring degraded lands, conserving SOC stock, and mitigating CC (Brahma et al. 2016). In India, rubber was first introduced in 1913 by the Britishers in Cachar district of Assam (Guha 2012). However, commercial cultivation of rubber started in late 1980s in NER with tremendous increase in adoption among the tribal communities of Tripura, Assam, and Meghalaya (Viswanathan 2006). India is the six largest producers of natural rubber globally with 6.94 million tonnes of produce in 2017–18 (NRP 2019). According to Rubber Board of India, the NE region is one hub of rubber production of the country with 6.05% of total production in 18.62% of total land area (Viswanathan and Bhowmik 2021). Although the NE states are a non-traditional belt for rubber production, suitable agro-climate and its wide local and international demand have encouraged private and public sectors to cultivate rubber in this region (Raj and Dey 2008; Majumder et al. 2014). Tripura is the leading producer of natural rubber among north-east states and second in rank after Kerala in India. In the recent times, it has been estimated that area under rubber plantation may increase fourfold by 2050 through conversion of traditional agricultural fields and secondary forest (Fox et al. 2012). This transition might have a widespread adverse effect on soil moisture regime, SOC dynamics, energy balance, ecological processes and cause biodiversity loss (Hu et al. 2008; Li et al. 2008; Guardiola-Claramonte et al. 2010). Additionally, conversion of forest to rubber gardens may incur up to 19% loss in soil C from initial stock (de Blécourt et al. 2013). Despite these harmful environmental consequences, numerous studies showed that rubber trees have huge potential to sequester C in its woody biomass and rehabilitate degraded soil (Rew et al. 2012; Brahma et al. 2017). In Assam, Brahma et al. (2018) estimated that the above-ground biomass (AGB) and below-ground biomass (BGB) in 35–40-years-old rubber was 376.9 and 23.9 kg per tree. They reported that cultivated rubber (286.1 Mg ha-1) had nearly two times more biomass than jungle rubber (147 Mg ha-1) with 143.1 Mg ha-1 sequestered C. They also stated that clear felling of mature trees led to loss of 135 Mg C ha-1 from AGB. Hence, they recommended to go for selective felling of 20% of tree from plantation age of 35 years and replanting it every 2 years. Choudhury et al. (2016)
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studied the changes in SOC stock up to 100 cm soil depth in different-aged rubber stand in Tripura. The study revealed that SOC stock increased by 9.9% with concurrent increase in tree C density from 177.06 (in 5 years) to 194.82 t C ha-1 (in 10 years). Another study was conducted to estimate the biomass C in Hevea stand of different age group in Barak valley, Assam (Brahma et al. 2016). The total C stored in biomass was estimated as 16.0, 50.29, 69.59, and 105.73 Mg C ha-1 in 5–10, 10–20, 20–30, and 30–40 years old rubber plantation, respectively. Mishra et al. (2020b) also reported that rubber plantation can store more SOC in recalcitrant pool than forest soil. Numerous studies have stated that SOC stock increased with age of rubber plantation (Wauters et al. 2008; Maggiotto et al. 2014) (Table 9.1). In Tripura, after a 20-year period, the C stock in soil profile of rubber garden improved by 14–57%, which accounted for 34 Mg ha-1 SOC accumulated (Mandal and Islam 2010). Similarly, in a chrono sequence study, Nath et al. (2018) recorded that SOC stock increased by 22.6% from 6- to 34-year-old rubber stands in Barak valley, Assam. Evaluation of SOC fractions revealed that the very labile (CVL, 31.7 Mg ha-1) and labile (CL, 30.8 Mg ha-1) SOC pools were higher in 6-yearsold plantation, whereas less labile (CLL, 33.2 Mg ha-1) and non-labile (CNL, 53.8 Mg ha-1) SOC pools were higher under 34-years-old plantation. The recalcitrant C (CVL+CL) fraction constituted 41–67% of SOC under rubber plantation. Presence of tannin and waxy compounds in the rubber leaf litter might have a positive priming effect on recalcitrant SOC fraction (Kraus et al. 2003; Wigati et al. 2014). Additionally, mature rubber trees have deep root system (Maeght 2014). Microbial inaccessibility, low oxygen availability at lower depth, and inherent chemical recalcitrant nature of root-derived C might also contribute to formation of stable SOC (Modak et al. 2019). In another study, Mishra and Sarkar (2020) found that labile and recalcitrant C were ~ 51.2% and 9% more in rubber plantation in comparison to jhum lands in Tura district of Meghalaya. In Mizoram, Lungmuana et al. (2019) observed that microbial biomass C (MBC) significantly contributed to SOC in rubber gardens. This indicates that the microbial biota was under less stress prompting less CO2 loss in the form of respiration and better assimilation of substrate C in their biomass. Thus, they suggested that conversion of jhum lands to permanent rubber plantations can restore soil biological heath in those NE regions where shifting cultivation is predominant. Therefore, long-term rubber plantation in jhum and degraded forest lands can facilitate formation of stable SOC, mitigate CC, and also provide livelihood security. However, monoculture of rubber in NE states like Tripura, Assam, and Meghalaya has changed the demographic scenario of these agrarian states (Debbarma and Debbarma 2018). Decline in biodiversity and natural resources with expanding rubber monoculture has compelled the local communities to encroach into undisturbed natural forest. Hence, it is important to spread local awareness to adopt rubber-based agroforestry to maintain sustainability of land and check indiscriminate utilization of forest resources (Majumder et al. 2014).
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SOC Stock Under Shifting Cultivation of NE India
Shifting cultivation, also known as jhum cultivation, is a slash-and-burn agricultural practice by local communities in North-East India (Zodinpui et al. 2016). It has been in practice for centuries and became a cultural identity to indigenous tribal communities. Till date, jhuming provides food and livelihood security to deprived people in rural landscape. The practice involves clearing and burning of mature natural forest to cultivate for some years and subsequently migrate to clear new forest lands. Over the years, the practice was thought to be sustainable and environment-friendly when the rotation cycle was 15–20 years. But due to excessive population pressure, shortage of lands, and strict government measures, the Jhumias are compelled to reduce the rotation cycles to 2 –3 years only (Thong et al. 2018). Hence, the time offered is not sufficient enough for regeneration of vegetation and restoration of initial soil fertility in these fallow lands promoting soil degradation (Punitha et al. 2018). It is more likely a continuous cycle where a forest land is converted to jhum land and then to degraded land. Scientific research also supported that slash-and-burn cultivation may improve soil C and nutrient status temporarily but has a negative impact on soil in the long term due to leaching and run-off (Arunachalam 2002). Substantial decrease in fallow land period in Nagaland, NE India, from 3 to 1 year has drastically deteriorated SOC stock and altered soil quality (Bhuyan 2019). Temjen et al. (2022) had observed significant increase in SOC from 2.88 to 3.94% with increase in fallow duration from 3 to 12 years in jhum lands of Mokokchung district, Nagaland. Lack of anthropogenic disturbances, improved litter addition, and slower decomposition rate improved soil structural stability and OC. In Mizoram, Lungmuana et al. (2018) also reported that the surface soil (0–10 cm) has highest C stock after 21 years of fallow period. Another study conducted in Khawrihnim village, Mizoram, showed that SOC concentration in natural forest increased post jhuming from 2.22 to 2.24% and then decreased to 2.25% in 0–10 cm soil layers (Zodinpuii et al. 2016). Such temporary improvement in SOC status might be attributed due to deposition of charred material after burning, but SOC gradually declined as period of cropping increased. The labile C fractions like microbial biomass C (MBC) are also influenced by soil moisture and OC (Devi and Yadava 2006). In Manipur, a comparative study between jhum and forest lands revealed that MBC declined more in winter than in rainy season with simultaneous decrease in SOC in burnt site (Binarani and Yadava 2010). Positive correlation between soil moisture and microbial activity and increased vegetation growth during wet season might have contributed to higher substrate availability, which enhances microbial population. Comparatively higher SOC stock was also reported in Karbi Anglong district of Assam after 15–20 years of fallow land compared to 5–8 years fallow (Nath et al. 2021). The recalcitrant C concentration significantly increased by 155% in 0–15 cm soil layers after fallow period of 15–20 years. Development of dense vegetation, reduced soil loss through run-off, and gradual stabilization of rootderived C might have stimulated steady buildup of OM. Soil aggregate analysis
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study showed that macroaggregate proportion was higher than meso- and microaggregates in jhum and fallow lands of Assam, NER (Laskar et al. 2021). Moreover, macroaggregate contributed more to SOC stock in comparison to mesoand microaggregate fractions. The SOC stock improved by 4–20% with increase in duration of fallow from 2 to 20 years. Therefore, they concluded that decline in proportion of macroaggregate fraction after shifting cultivation is the major factor behind loss of SOC stock. Vashum et al. (2016) reported that undisturbed primary forest has enormous potential to sequester SOC than secondary forest, which is subjected to continuous jhum cultivation. But secondary forest also showed to improve soil quality and OC buildup when fallow period is extended to a longer duration. Modeling of SOC stock under shifting cultivation in Nagaland indicated that under baseline and future CC scenario, the SOC loss decreased by 0.40 and 0.50 t ha-1 year-1, respectively, in different jhum sites (Mishra et al. 2019). However, plantation crops like tea and rubber can stimulate and improve SOC stock significantly in jhum lands under abrupt CC scenarios (Mishra et al. 2020a, b). Despite negative consequences on environment, it is virtually impossible to prevent jhum cultivation due to involvement of large number of small-scale farmers (about 4.43 lakhs local farming families) (Paul et al. 2017). On the other hand, monoculture of jhuming is not sustainable. Hence, integrated farming systems such as horticulture and horti-silviculture-based IFS and agroforestry should be promoted up to nullify its undesirable effects (Punitha et al. 2018; Chatterjee et al. 2021). Traditional agroforestry systems (AFSs), which are already prevalent in NE Indian, also need further improvement in land management practices to maximize its positive impact on soil quality and socioeconomic life of farming communities. Multipurpose trees such as Alnus nepalensis, Michelia oblonga, and Parkia roxburghii were found to be suitable bio-ameliorant for degraded soils in hilly terrain of North-East India (Ramesh et al. 2013). Due to constant leaf litter fall and extensive root system, these tree species in the long term can increase soil aggregate stability by 24%, OC by 96.2% and decrease erosion ratio by 39.5% (Saha et al. 2012). In recent times, AFSs have become an integral to maintain a steady supply of natural resources, manage degraded lands, and sustain ecosystem services (Saha et al. 2007). About 7.85 million ha area of degraded lands were rehabilitated by adopting various agroforestry models (Wasteland Atlas of India 2000). Multistoried AFS (alder + tea + black pepper + agricultural crops between the tree rows) and silvihorti-pastoral (alder + pine apple + fodder grasses) systems reported to improve the SOC concentration by 1.17–1.65 times in degraded Alfisol of Meghalaya in comparison with natural forest (Saha et al. 2012). Home-garden agroforestry is another viable option, which is socially, economically, and ecologically more suited to village ecosystem of NER (Sahoo 2009). This multistoried AFS is a mixture of several tree, horticultural species, and agricultural crops resembling a forest-like composition and structure having a capacity to store higher SOC stock than jhum lands (Singh and Sahoo 2021).
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181
SOC Stock Under Forests of NE India
The forest soils are less prone to anthropogenic disturbances due to less cultural operations and hence, maintain a healthy microbial population, adequate nutrients, and an important SOC sink. The tropical forest holds 37% of global terrestrial C (Houghton 1996). Poor management can transform this long-term SOC sink into potential C source and influence C cycle of the environment. Assessment of SOC not only evaluates the soil fertility and productivity but also provides information on sequestration and emission potential of forest soil under abrupt CC and unsustainable management. Demographic pressure had led to change in land use, which affected SOC pools significantly. The NER of India is known for its diverse forest ecosystem with one-third of the country’s biodiversity (Chatterjee et al. 2006). The region experiences higher rainfall compared to other parts resulting in greater vegetative growth. As vegetation is one of the major sources to enrich C in soil (Fang et al. 2015), this region provides suitable environments for C storage (Table 9.1). Now with the ever-changing CC, the forest soil health of this region is gaining much importance. Therefore, quantification and information on nature of SOC fractions dominant in these soils will provide a vivid knowledge in changes in SOC fluxes under future CC scenarios. Choudhury et al. (2013) observed that SOC stock under dense forest was higher (>2.5%) than that of cultivated system (1.45–1.69%). Another study in east Khasi and Jaintia hilly region showed that dense forest had higher SOC storage than open forest and agroforestry systems (Hinge et al. 2019). Apart from land use, elevation and aspect influence rainfall and temperature, which create a regional microclimate and cause variation in SOC stock. Mishra et al. (2020a, b) reported that SOC stock increased by 21 and 20% with rise in elevation from 500 to 1000 masl in Mon and Zunheboto district of Nagaland. Similarly, Choudhury et al. 2016 estimated that SOC increased from 1.65 to 3.53% with increase in altitude from 250 to 3500 masl. Higher elevation led to cooler temperature, which might have retarded the SOC mineralization rate (López-Vicente et al. 2009). Thus, higher SOC accumulation in Sikkim among the other North-East Indian states under the influence of lower temperature was justified by Choudhury et al. (2013). Additionally, altitudinal rise also causes appreciable increase in precipitation that promotes better phytobiomass production, soil formation, enhances clay concentration and soil aggregation under wetter climate (Sinoga et al. 2012). Furthermore, lack of human-induced severe interference (like shifting cultivation) and enhanced vegetation growth in higher altitude of NER might have assisted accumulation of finer soil separates and stimulated SOC buildup (Choudhury et al. 2016). In Mizoram, study on SOC fractions revealed that active and recalcitrant C pools were more in forest than agroforestry, cultivated lands, and plantations (Sahoo et al. 2019). Moreover, the active C pools (CVL and CL) were 42.4% more than recalcitrant pools (CLL and CNL) and contributed about 60% total OC stock in forest soil. This suggests that despite these forest soils acting as significant recalcitrant C sink, change in land use and unsustainable management practices could lead to loss of C from labile pool. The labile SOC pools like MBC also show a positive correlation
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with soil temperature, soil moisture regime, air temperature, light intensity, and litter thickness in dense forest and gap areas (Sanford 1989; Falloon et al. 2011; Fekete et al. 2016). In the subtropical hill forest of Mawphlang, Shillong, Arunachalam and Arunachalam (2000) reported that MBC contribution to SOC ranged between 2.15 and 3.41%. They also stated that microbial population declined during winter and improved in rainy season. Low temperature, less vegetation growth, and water stress might lead to lower MBC in winter. Urban sacred forest also has crucial role in SOC storage (Anjali et al. 2020). As these forests are protected from human interference, the soil underlying the forest has high C storage potential and aids in CC mitigation (Moradi and Shabanian 2022). Devi et al. (2021) reported that the SOC stock was highest in Enchey Monastery sacred grove (EMS, 97.64 Mg C ha-1) followed by subtropical forest (107.84 Mg C ha-1) and Deorali Chorten Monastery sacred grove (DMS, 118.70 Mg C ha-1) in Sikkim. This trend in SOC might be due to high species richness, tree density, presence of conifer leaf litter in the upper soil layer in EMS. Furthermore, high soil and air temperature in DMS site increased litter decomposition rate and thereby reduced SOC density. SOC stabilization has a positive correlation with texture and soil mineralogy (Laskar et al. 2012; Adhikari and Bhattacharyya 2015). The SOC turnover time in the subsoil is higher in clayey soil of Bakrihawar, Assam, than in sandy soils in the hills of Chandipur (Laskar et al. 2012). It has been reported that soil clay can bind 90% SOC by formation of SOM-clay complex (Sparks 2003). Under similar climatic condition in virgin forest land of foothills of Karbi Hill range, Assam, an investigation revealed that SOC stabilization was more in forest lands than cultivated fields due higher occurrence of Fe/Al oxide (Adhikari and Bhattacharyya 2015). Higher proportion of aromatic hydrocarbon in comparison to aliphatic C in these forest soils stimulated more SOC stabilization by aggregate formation due to their strong affinity for Fe oxides/Al oxides (Feller and Beare 1997). Soil C storage through commercially important species like bamboo plantation is a suitable option to gain both economic profit and ripe environmental benefits. In Manipur, a study showed that bamboo plantation holds 5.2% more SOC than broadleaf Dipterocarpus forest (Thokchom and Yadava 2017). The findings also revealed that broadleaf forest emitted more CO2 into the atmosphere in comparison to bamboo ecosystems. This indicates that apart from natural forest, plantation forest like bamboo not only acts as SOC sink but also contributes less to atmospheric CO2 concentration. Temperature sensitivity study of SOC revealed that forest soils are invulnerable to abrupt temperature rise than managed systems (mulberry plantation and agricultural systems) (Ghosh et al. 2020). High C mineralization of forest soil at 35 °C was observed due to increased reaction rate and solubility of tannin and lignin like substances (Davidson et al. 2012). However, higher recalcitrance nature of C in forest soil also contributed to low proportion of C mineralization to total SOC than other managed land uses. The study indicated that natural forests have low-quality soil C, which has higher stability than managed systems. Hence, natural forest should be protected to sustain C balance and for CC mitigation.
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Conclusions
The AFOLU sector is one the most effective approaches to make India net-zero C footprint nation. C plantation through long-term permanent settlements (like tea, rubber), agroforestry, and plantation forest can augment soil environment in terms of quality, fertility, and C status. This sector is vital to create a large terrestrial C sink through rehabilitation of degraded forest, checking shifting cultivation, adopting soil and moisture conservation strategies, and simultaneously mitigating climate change. Although India contributes to only 8% of anthropogenic C emissions in comparison to 25% of C emission globally, Indian forest resources are more stabilized. Also, improvement in forest cover especially in NER India is cumbersome due to increasing demand for food among growing population and competition between different land uses for economic gains. Therefore, agroforestry, homestead gardens are promising land-based mitigation approaches to sustain soil fertility, enhance crop productivity in agricultural lands, improve tree cover, and ultimately contribute to SOC sink. However, such a land-related mitigation is challenging in NER as it requires development of stringent policies, political support, and good coordination for its implementation. Nevertheless, if such integrated management policies can be executed, positive results in terms of food security, resource conservation, emission reduction, and enhanced SOC sink can be achieved effectively.
References Adhikari G, Bhattacharyya KG (2015) Correlation of soil organic carbon and nutrients (NPK) to soil mineralogy, texture, aggregation, and land use pattern. Environ Monit Assess 187(11):735 Anjali K, Khuman YSC, Sokhi J (2020) A review of the interrelations of terrestrial carbon sequestration and urban forests. AIMS Environ Sci 7(6):464–485 Arunachalam A (2002) Dynamics of soil nutrients and microbial biomass during first year cropping in an 8-year jhum cycle. Nutr Cycl Agroecosyst 64(3):283–291 Arunachalam A, Arunachalam K (2000) Influence of gap size and soil properties on microbial biomass in a subtropical humid forest of North-East India. Plant Soil 223(1–2):187–195 Bhuyan R (2019) Review notes on shifting cultivation in Northeast India amidst changing perceptions. Dhaulagiri J Sociol Anthr 13:90–95 Binarani RK, Yadava PS (2010) Effect of shifting cultivation on soil microbial biomass C, N and P under the shifting cultivations systems of Kangchup Hills, Manipur, North-East India. J Exp Sci 1:10 Brahma B, Nath AJ, Das AK (2016) Managing rubber plantations for advancing climate change mitigation strategy. Curr Sci 110:2015–2019 Brahma B, Sileshi GW, Nath AJ, Das AK (2017) Development and evaluation of robust tree biomass equations for rubber tree (Hevea brasiliensis) plantations in India. For Ecosyst 4(1): 1–10 Brahma B, Nath AJ, Sileshi GW, Das AK (2018) Estimating biomass stocks and potential loss of biomass carbon through clear felling of rubber plantations. Biomass Bioenergy 115:88 Chatterjee S, Saikia A, Dutta P, Ghosh D, Pangging G, Goswami AK (2006) Biodiversity significance of North East India. WWF, New Delhi, pp 1–71 Chatterjee D, Kumar R, Kuotsu R, Deka BC (2016) Validation of traditional weed control method through common salt application in the hill region of Nagaland. Curr Sci 25:1459–67
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Chatterjee D, Kuotsu R, Ray SK, Patra MK, Thirugnanavel A, Kumar R, Deka BC (2021) Preventing soil degradation in shifting cultivation using integrated farming system models. Arch Agron Soil Sci 68:1–17 Choudhary BK, Majumdar K, Datta BK (2016) Carbon sequestration potential and edaphic properties along the plantation age of rubber in Tripura, Northeastern India. Curr World Environ 11(3):756 Choudhary BK, Majumdar K, Datta BK (2019) Status of soil organic carbon and nutrient pools in tea plantation ecosystem of Tripura, India. In: Recent trends in biodiversity conservation and bio-resource utilisation, pp 143–160 Choudhury BU, Mohapatra KP, Das A, Das PT, Nongkhlaw L, Fiyaz RA, Munda GC (2013) Spatial variability in distribution of organic carbon stocks in the soils of North East India. Curr Sci 1:604–614 Choudhury BU, Fiyaz AR, Mohapatra KP, Ngachan S (2016) Impact of land uses, agrophysical variables and altitudinal gradient on soil organic carbon concentration of North-Eastern Himalayan region of India. Land Degrad Dev 27(4):1163–1174 Climate Watch (2020) GHG emissions. World Resources Institute, Washington, DC. https://data. worldbank.org/indicator/EN.ATM.GHGT.KT.CE?locations=IN Das A, Mishra RR (2020) Compound annual growth (CAGR) rate of fresh tea leaf (Camellia sinensis) production in Assam: a statistical approach. SSRN 3728002 Davidson EA, Samanta S, Caramori SS, Savage K (2012) The dual arrhenius and michaelis–menten kinetics model for decomposition of soil organic matter at hourly to seasonal time scales. Glob Chang Biol 18(1):371–384 de Blécourt M, Brumme R, Xu J, Corre MD, Veldkamp E (2013) Soil carbon stocks decrease following conversion of secondary forests to rubber (Hevea brasiliensis) plantations. PLoS One 8(7):e69357 Debajit R, Nepolion B, Das AK (2014) Assessment of aboveground and soil organic carbon stocks in Dipterocarpus forests of Barak valley, Assam, Northeast India. Int J Ecol Environ Sci 40(1): 29–40 Debbarma A, Debbarma A (2018) Perspectives on rubber monoculture in Tripura, North-East India. Int J Ecol Environ Sci 44(1):27–31 Deka N, Goswami K (2021) Economic sustainability of organic cultivation of Assam tea produced by small-scale growers. Sustain Prod Consum 26:111–125 Devi NB, Yadava PS (2006) Seasonal dynamics in soil microbial biomass C, N and P in a mixedoak forest ecosystem of Manipur, North-East India. Appl Soil Ecol 31(3):220–227 Devi NB, Lepcha NT, Mahalik SS, Dutta D, Tsanglao BL (2021) Urban sacred grove forests are potential carbon stores: a case study from Sikkim Himalaya. Environ Chall 4:100072 Dijkman MJ (1951) Hevea, Thirty years of research in the Far East. Hevea, thirty years of research in the Far East Dutta R, Stein A, Smaling EMA, Bhagat RM, Hazarika M (2010) Effects of plant age and environmental and management factors on tea yield in Northeast India. Agron J 102(4): 1290–1301 Falloon P, Jones CD, Ades M, Paul K (2011) Direct soil moisture controls of future global soil carbon changes: an important source of uncertainty. Glob Biogeochem Cycles 25:3 Fang XM, Chen FS, Wan SZ, Yang QP, Shi JM (2015) Topsoil and deep soil organic carbon concentration and stability vary with aggregate size and vegetation type in subtropical China. PLoS One 10(9):e0139380 Fekete I, Varga C, Biró B, Tóth JA, Várbíró G, Lajtha K, Kotroczó Z (2016) The effects of litter production and litter depth on soil microclimate in a central European deciduous forest. Plant Soil 398(1):291–300 Feller C, Beare MH (1997) Physical control of soil organic matter dynamics in the tropics. Geoderma 79(1–4):69–116 Fox J, Vogler JB, Sen OL, Giambelluca TW, Ziegler AD (2012) Simulating land-cover change in montane mainland Southeast Asia. Environ Manag 49(5):968–979
9
AFOLU Sectors of North East India and Their Potential for Soil Carbon Storage
185
Fróna D, Szenderák J, Harangi-Rákos M (2019) The challenge of feeding the world. Sustainability 11(20):5816 Ghosh A, Das A, Das D, Ray P, Bhattacharyya R, Biswas DR, Biswas SS (2020) Contrasting land use systems and soil organic matter quality and temperature sensitivity in north eastern India. Soil Tillage Res 199:104573 Gogoi S, Mishra G, Deka AK (2016) Soil nutrient dynamics in tea agroforestry ecosystem of Golaghat district of Assam, India. Agric Sci Dig Res J 36(3):185–190 Guardiola-Claramonte M, Troch PA, Ziegler AD, Giambelluca TW, Durcik M, Vogler JB, Nullet MA (2010) Hydrologic effects of the expansion of rubber (Hevea brasiliensis) in a tropical catchment. Ecohydrology 3(3):306–314 Guha A (2012) Medieval and early colonial Assam: society, polity, economy Harongbam N (2014) Assessment of soil fertility status in Silcoorie tea estate, Assam, north East India. Int J Curr Res 6(12):10851–10854 Hinge G, Surampalli RY, Goyal MK (2019) Effects of land use and soil management on soil quality in India’s Northeastern Himalayas. J Environ Eng 145(4):04019007 Houghton RA (1996) Terrestrial sources and sinks of carbon inferred from terrestrial data. Tellus B Chem Phys Meteorol 48(4):420–432 Hu H, Liu W, Cao M (2008) Impact of land use and land cover changes on ecosystem services in Menglun, Xishuangbanna, Southwest China. Environ Monit Assess 146(1):147–156 IPCC (2014) Summary for policymakers. In: Field CB, Barros VR, Dokken DJ, Mach KJ, Mastrandrea MD, Bilir TE, Chatterjee M, Ebi KL, Estrada YO, Genova RC, Girma B, Kissel ES, Levy AN, MacCracken S, Mastrandrea PR, White LL (eds) Climate change 2014: impacts, adaptation, and vulnerability. Part A: global and sectoral aspects. Contribution of working group II to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, New York, NY, pp 1–32 ISFR (2021) India state of forest report 2021. Forest Survey of India, Ministry of Environment and Forest, Dehradun. http://fsi.nic.in/forest-report-2021 Kalita RM, Das AK, Nath AJ (2016) Assessment of soil organic carbon stock under tea agroforestry system in Barak Valley, North East India. Int J Ecol Environ Sci 42(2):175–182 Kamau DM, Spiertz JHJ, Oenema O (2008) Carbon and nutrient stocks of tea plantations differing in age, genotype and plant population density. Plant Soil 307(1):29–39 Kraus TE, Dahlgren RA, Zasoski RJ (2003) Tannins in nutrient dynamics of forest ecosystems-a review. Plant Soil 256(1):41–66 Kumar BM, Aravindakshan S (2022) Carbon footprints of the Indian AFOLU (agriculture, forestry, and other land use) sector: a review. Carbon Footprints 1:7 Kumar BM, Nair PR (2011) Carbon sequestration potential of agroforestry systems: opportunities and challenges Kumari R, Banerjee A, Kumar R, Kumar A, Saikia P, Khan ML (2019) Deforestation in India: consequences and sustainable solutions. In: Forest degradation around the world. IntechOpen, London, pp 1–18 Laskar AH, Yadava MG, Ramesh R (2012) Radiocarbon and stable carbon isotopes in two soil profiles from Northeast India. Radiocarbon 54(1):81–89 Laskar SY, Sileshi GW, Pathak K, Debnath N, Nath AJ, Laskar KY, Das AK (2021) Variations in soil organic carbon content with chrono sequence, soil depth and aggregate size under shifting cultivation. Sci Total Environ 762:143114 Li H, Ma Y, Aide TM, Liu W (2008) Past, present and future land-use in Xishuangbanna, China and the implications for carbon dynamics. For Ecol Manag 255(1):16–24 López-Vicente M, Navas A, Machin J (2009) Effect of physiographic conditions on the spatial variation of seasonal topsoil moisture in Mediterranean soils. Soil Res 47(5):498–507 Lungmuana S, Choudhury BU, Saha S, Singh SB, Das A, Buragohain J, Dayal V, Dutta SK (2018) Impact of postburn jhum agriculture on soil carbon pools in the north-eastern Himalayan region of India. Soil Res 56(6):615–622
186
K. Modak et al.
Lungmuana S, Singh SB, Choudhury BU, Saha S, Hnamte V (2019) Transforming jhum to plantations: effect on soil microbiological and biochemical properties in the foot hills of north eastern Himalayas, India. Catena 177:84–91 Maeght JL (2014) Effects of climate variability on shallow and deep root growth of mature rubber (Hevea brasiliensis) and teak (Tectona grandis) trees in South-East Asian plantations Maggiotto SR, Oliveira DD, Marur CJ, Stivari SMS, Leclerc M, Wagner-Riddle C (2014) Potential carbon sequestration in rubber tree plantations in the northwestern region of the Paraná state, Brazil. Acta Sci Agron 36:239–245 Majumder A, Datta S, Choudhary BK, Majumdar K (2014) Do extensive rubber plantation influences local environment? A case study from Tripura, Northeast India. Curr World Environ 9(3):768 Mandal D, Islam KR (2010) Soil carbon sequestration under rubber plantations in North-East India. In: Climate change and food security in South Asia. Springer, Dordrecht, pp 433–444 Mandal B, Majumder B, Bandyopadhyay PK, Hazra GC, Gangopadhyay A, Samantaray RN, Kundu S (2007) The potential of cropping systems and soil amendments for carbon sequestration in soils under long-term experiments in subtropical India. Glob Chang Biol 13(2):357–369 Manpoong C, Tripathi SK (2019) Soil properties under different land use systems of Mizoram, North East India. J Appl Nat Sci 11(1):121–125 Mishra G, Sarkar A (2020) Studying the relationship between total organic carbon and soil carbon pools under different land management systems of Garo hills, Meghalaya. J Environ Manag 257:110002 Mishra G, Jangir A, Francaviglia R (2019) Modeling soil organic carbon dynamics under shifting cultivation and forests using RothC model. Ecol Model 396:33–41 Mishra G, Giri K, Jangir A, Francaviglia R (2020a) Projected trends of soil organic carbon stocks in Meghalaya state of Northeast Himalayas, India. Implications for a policy perspective. Sci Total Environ 698:134266 Mishra G, Sarkar A, Das J (2020b) Changes in soil organic carbon lability along the altitudinal variations in three land use types of Meghalaya, India. Environ Sustain 3(3):325–331 Mishra G, Sarkar A, Giri K, Nath AJ, Lal R, Francaviglia R (2021) Changes in soil carbon stocks under plantation systems and natural forests in Northeast India. Ecol Model 446:109500 Misra TK (2018) Tea management: option for carbon sequestration monocultural ecosystem. Assam Rev Tea News 107(3):20–25 Modak K, Ghosh A, Bhattacharyya R, Biswas DR, Das TK, Das S, Singh G (2019) Response of oxidative stability of aggregate-associated soil organic carbon and deep soil carbon sequestration to zero-tillage in subtropical India. Soil Tillage Res 195:104370 MoEFCC (2021) India: third biennial update report to the United Nations framework convention on climate change. Ministry of Environment, Forests and Climate Change, Government of India, New Delhi. https://unfccc.int/documents/268470 Mora O, Le Mouël C, de Lattre-Gasquet M, Donnars C, Dumas P, Réchauchère O, Marty P (2020) Exploring the future of land use and food security: a new set of global scenarios. PLoS One 15(7):e0235597 Moradi A, Shabanian N (2022) Land-use change in the Zagros forests and its impact on soil carbon sequestration. Environ Dev Sustain 1:1–16 Nath AJ, Brahma B, Sileshi GW, Das AK (2018) Impact of land use changes on the storage of soil organic carbon in active and recalcitrant pools in a humid tropical region of India. Sci Total Environ 624:908–917 Nath PC, Nath AJ, Reang D, Lal R, Das AK (2021) Tree diversity, soil organic carbon lability and ecosystem carbon storage under a fallow age chrono sequence in North East India. Environ Sustain Indicators 10:100122 NRP (2019) National Rubber Policy, Department of Commerce Ministry of Commerce & Industry Government of India. https://commerce.gov.in/hi/wpcontent/uploads/sites/2/2020/02/ NTESCL637038876015166279_National-Rubber-Policy-2019
9
AFOLU Sectors of North East India and Their Potential for Soil Carbon Storage
187
Paul S, Tripathi AK, Burman RR, Panggam M, Ray SK, Kalita N, Singh AK (2017) Jhum cultivation and its consequences on forest and environment in eastern Himalayan tract of India: a participatory assessment. Range Manag Agrofor 38(1):121–126 Phukan M, Savapondit D, Hazra A, Das S, Pramanik P (2018) Algorithmic derivation of CO2 assimilation based on some physiological parameters of tea bushes in North-East India. Ecol Indic 91:77–83 Pramanik P, Phukan M (2020) Potential of tea plants in carbon sequestration in North-East India. Environ Monit Assess 192(4):1–10 Punitha P, Ansari MA, Pandey DK, Ram D, Datt S, Sharma PK, Prakash N (2018) Shifting cultivation in North East India: social dimension, cross cultural reflection and strategies for improvement. Indian J Agric Sci 88(6):811–819 Raj S, Dey S (2008) Agrometeorological perspective. Climate Change & Food Security, 149 Ramesh T, Manjaiah KM, Tomar JMS, Ngachan SV (2013) Effect of multipurpose tree species on soil fertility and CO2 efflux under hilly ecosystems of Northeast India. Agrofor Syst 87(6): 1377–1388 Rew EE, Pascal TT, Beatrice AF, Eneke B (2012) Simulation of the impacts of three management regimes on carbon sinks in rubber and oil palm plantation ecosystems of South-Western Cameroon. J Ecol Nat Environ 4(6):154–162 Saha R, Tomar JMS, Ghosh PK (2007) Evaluation and selection of multipurpose tree for improving soil hydro-physical behavior under hilly eco-system of North East India. Agrofor Syst 69:239– 247 Saha R, Chaudhary RS, Somasundaram J (2012) Soil health management under hill agroecosystem of North East India. Appl Environ Soil Sci 2012(696174):1–9 Sahoo UK (2009) Traditional home gardens and livelihood security in North-East India. J Food Agric Environ 7(2):665–670 Sahoo UK, Singh SL, Gogoi A, Kenye A, Sahoo SS (2019) Active and passive soil organic carbon pools as affected by different land use types in Mizoram, Northeast India. PloS One 14(7): e0219969 Sanford RL (1989) Fine root biomass under a tropical forest light gap opening in costa rica. J Trop Ecol 5(2):251–256 Shrestha A, Anwar MP, Islam AM, Gurung T, Dhakal S, Tanveer A, Ikram NA (2021) Weed science as a new discipline and its status in some South Asian universities and colleges: examples from Bangladesh, Bhutan, Nepal and Pakistan. CABI Rev 2021:1 Singh SL, Sahoo UK (2021) Tree species composition, diversity and soil organic carbon stock in homegardens and shifting cultivation fallows of Mizoram, Northeast India. Vegetos 34(1): 220–228 Singh RK, Sinha VSP, Joshi PK, Kumar M (2020) Modelling agriculture, forestry and other land use (AFOLU) in response to climate change scenarios for the SAARC nations. Environ Monit Assess 192(4):1–18 Sinha S, Tripathi P (2021) Trends and challenges in valorization of food waste in developing economies: a case study of India. Case Studies Chem Environ Eng 4:100162 Sinoga JDR, Pariente S, Diaz AR, Murillo JFM (2012) Variability of relationships between soil organic carbon and some soil properties in Mediterranean rangelands under different climatic conditions (south of Spain). Catena 94:17–25 Smith P, Bustamante M, Ahammad H, Clark H, Dong H, Elsiddig EA, Haberl H, Harper R, House J, Jafari M, Masera O (2014) Agriculture, forestry and other land use (AFOLU). In: Climate change 2014: mitigation of climate change. Contribution of working group III to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, pp 811–922 Sparks DL (2003) Environmental soil chemistry. Elsevier, Amsterdam Supriya Devi L, Yadava PS (2009) Aboveground biomass and net primary production of semievergreen tropical forest of Manipur, North-Eastern India. J For Res 20:151–5
188
K. Modak et al.
Talukdar NR, Ahmed R, Choudhury P, Barbhuiya NA (2020) Assessment of forest health status using a forest fragmentation approach: a study in Patharia Hills reserve Forest, Northeast India. Model Earth Syst Environ 6(1):27–37 Tea Board India (2022). www.teaboard.gov.in/pdf/State_wise_Month_wise_tea_production_2022 Temjen W, Singh MR, Ajungla T (2022) Effect of shifting cultivation and fallow on soil quality index in Mokokchung district, Nagaland, India. Ecol Process 11(1):1–16 Thokchom A, Yadava PS (2014) Soil CO2 flux in the different ecosystems of north East India. Curr Sci 1:99–105 Thokchom A, Yadava PS (2017) Biomass and carbon stock along an altitudinal gradient in the forest of Manipur, Northeast India. Trop Ecol 1:58(2) Thong P, Pebam R, Sahoo UK (2018) A geospatial approach to understand the dynamics of shifting cultivation in Champhai district of Mizoram, North-East India. J Indian Soc Remote Sens 46(10):1713–1723 Tubiello FN (2014) Agriculture, forestry, and other land use–AFOLU. Working Group III contribution to IPCC Fifth Assessment Report Tubiello FN, Salvatore M, Cóndor Golec RD, Ferrara A, Rossi S, Biancalani R, Flammini A (2014) Agriculture, forestry and other land use emissions by sources and removals by sinks. Rome Vashum KT, Kasomwoshi T, Jayakumar S (2016) Soil organic carbon sequestration potential of primary and secondary forests in Northeast India. Int Acad Ecol Environ Sci 6(3):67–74 Venkatachalam P, Geetha N, Sangeetha P, Thulaseedharan A (2013) Natural rubber producing plants: an overview. Afr J Biotechnol 12:12 Viswanathan PK (2006) A comparative study of smallholder rubber and rubber integrated farm livelihood Systems in India and Thailand, report of the post-doctoral research study submitted to the Asian Institute of Technology (AIT), Bangkok Viswanathan P, Bhowmik I (2021) Compatibility of institutional architecture for rubber plantation development in north East India from a comparative perspective of Kerala Wasteland Atlas of India (2000) Ministry of rural development. Govt. of India and National Remote Sensing Agency, Hyderabad Wauters JB, Coudert S, Grallien E, Jonard M, Ponette Q (2008) Carbon stock in rubber tree plantations in Western Ghana and Mato Grosso (Brazil). For Ecol Manag 255(7):2347–2361 Wigati S, Maksudi M, Latief A (2014) Analysis of rubber leaf (Hevea brasiliensis) potency as herbal nutrition for goats. Proceedings of the 16th AAAP animal science congress, vol 2, p 497–500 Zhang JC, Zhang QH, Lin SX (2013) Different ecological regions in Guizhou king bird tea and tea quality soil characteristics correlation studies. Guangdong Agric Sci 40(8):60–63 Zodinpuii B, Lalnuntluanga, Lalthanzara H (2016) Impact of shifting cultivation on soil organic carbon in hilly terrain of Mizoram, India. Sci Vision 16(3):135–143
Soil Microbial Carbon Pools as an Indicator of Soil Health in Different Land Use Systems of Northeast India
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Lungmuana, Ramchhanliana Hauchhum, and Paul Lalremsang
Abstract
Soil contains the largest pool of terrestrial carbon, and research on soil carbon sequestration potential and its decomposition dynamics becomes a paramount importance. The quality and quantity of soil organic carbon are the key to soil health to dictate productivity of agro ecosystems. The north-eastern Indian hills consist of fragile ecosystems, which are prone to land degradation. Land use systems dominated in the region include traditional agroforestry, terrace cultivation, shifting agriculture, etc., involving deforestation and loss of phytomass, which can drastically affect the soil within a short period of time. Soil carbon can be divided into active and passive pools, and the active pools are more sensitive to soil management, disturbances, and even climate change and act as a sensitive indicator. The active carbon pool is linked with microbial-mediated fractions like microbial biomass carbon, soil respiration, and soil enzyme activities. These microbial-mediated fractions by virtue of its sensitivity act as an indicator to land use and land cover change. Thus, understanding the response of microbiological properties to land use management is crucial for any initial changes in the soil properties and in turn crop productivity. In this chapter, we reviewed the past research works carried out in the North Eastern Hill (NEH) region where soil-labile and microbial-associated C pool properties were used as an indicator of soil health changes due to several land use systems.
Lungmuana (✉) ICAR-RC-NEH Region, Mizoram Centre, Kolasib, Mizoram, India R. Hauchhum Mizoram University, Aizawl, Mizoram, India P. Lalremsang North Eastern Hill University, Tura, Meghalaya, India # The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Mishra et al. (eds.), Soil Carbon Dynamics in Indian Himalayan Region, https://doi.org/10.1007/978-981-99-3303-7_10
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Keywords
Soil health · Soil microbial properties · Slope · Indicator · Productivity
10.1
Introduction
Information and mechanism regarding soil carbon (C) mineralization and stabilization had become a topic of interest and importance in the recent past due to the global climate change scenario. It has been reported that soil being the largest reservoir of terrestrial carbon pool can offset carbon dioxide emission if properly managed (Batjes 2014). Due to the above reasons, there have been a number of studies across the globe in understanding the carbon below- and above-ground biomass, CO2 emission, and carbon sequestration. The C sequestration potential of soil may however depend on several factors and management such as climate and land use types. Soil organic carbon (SOC) itself is regarded as the most important indicator of soil quality determining the physiochemical and microbial characteristics of soil (Kirschbaum 2000). Thus, soil carbon sequestration besides dictating the productivity of agricultural system holds the key for offsetting increasing CO2 and a regulator of climate change. Soil organic matter (SOM) is a very complex component where organic plant debris, litters, and inorganic constituents of the soil interplay in various degrees and stages (Poeplau and Don 2013). The capacity of a soil to store C is controlled mainly by the quantity and quality of input biomass and its decomposition rate. The decomposition of organic matter native or added depends on the proliferation and activity of soil microbes. Based on the degree of C stabilization in soil, the SOC can be classified into labile pools, regarded as the most sensitive indicator of management and where most of the initial decomposition and regulation take place (Haynes 2005). The second C pool is passive or recalcitrant and stable in nature, where microbial activity is less representing more storage of soil C. The microbial activity is responsive to labile pool representing a nexus between organic and inorganic pool and outflow of nutrient to other pathways. A soil labile C pool is extremely sensitive, providing energy for the microbes, and reflects small changes in soil organic matter through soil enzyme activities (Lungmuana et al. 2019). The North-eastern or Eastern Himalayan Region (NEHR) of India consists of hills and intermountain valleys rich in biodiversity. Recently, due to diverse land use systems such as shifting cultivation led deforestation leading to phytomass loss, its ecosystem remains fragile. Land use and land cover have a significant consequence on the soil organic carbon, and that is reflected through microbial properties, which are linked to the most labile part of OM (Choudhury et al. 2016; Lungmuana et al. 2019). The changes in aggregated associated C and recalcitrant C pools may take time when natural or secondary forests are converted to permanent cultivation (Ramesh et al. 2019). Thus, studies on soil microbial C changes in the region are important to determine the initial changes in soil health. In this chapter, we focus on the dynamics of microbial associated C pools due to several land use and land cover
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changes in the NEH region and their responses to management practices as an indicator of soil health.
10.2
Labile Carbon and Soil Microbial Activities
The labile C pool represents a smaller fraction of the total OC compared to the recalcitrant pool (Duval et al. 2018). The labile C pools are considered the most sensitive in understanding the SOM transformation and thus, act as an important indicator of soil health (Blair et al. 1995). Labile C has higher turnover rates due to which it is easy to detect the SOM changes and acts as source of energy for soil microbes to determine the biological activity of soil. In turn, the more biologically active the soil, the more will be plant available nutrients through mineralization. Labile C pools represent an organic and a pathway through microbial activity between fresh residues and stabilized OM (Benbi et al. 2012). Some of the labile C commonly used are microbial biomass C, dissolved OC, and microbial properties associated with labile C pools such as soil basal respiration and soil enzyme activities. Alteration in soil environment caused by soil management results in soil microbes responding to produce extracellular enzymes and other by-products. Thus, in this process, enzyme activity in the soil influences the biological properties and nutrient cycling to maintain soil health (Sharma et al. 2022). The decomposition of organic matter and nutrient cycling are significantly influenced by soil microbial activities. Soil microbial characteristics, including microbial biomass, metabolic quotient, soil respiration, and enzymatic properties, have been linked to the operation of soil ecological processes and nutrient cycling, according to studies reported by Jiang et al. (2009). The soil microbial biomass is directly related to the soil organic matter and serves as a labile reservoir of plantavailable nutrients (Smith and Paul 1990). A crucial soil component, soil microbial biomass serves as both a source and a sink for nutrients that are available to plants and catalyzes their changes in the soil. The release of excess inorganic nutrients into the soil occurs as a result of the microbial biomass carbon in the soil assimilation of complex organic substrates for energy and biomass carbon. When compared to soil organic matter, microbial biomass comprises a very tiny standing stock of nutrients; as a result, it is referred to as a living component of soil organic matter (Jenkinson and Ladd 1981). Due to its function in nutrient dynamics, decomposition, and the physical stabilization of soil aggregates, soil microbial biomass is a significant factor in determining the quality of soil (Franzlueebber et al. 1994). According to Kaiser et al. (1992), microbial activity and biomass are strongly correlated with the physical and chemical characteristics of the soil. They are also thought to be an early indicator of changes in soil’s physical and chemical characteristics brought on by soil management practices and environmental stress as a result of changing land use (Moore et al. 2000). Thus, quantitative measurement of soil microbial biomass is considered to be an important step and tool to understand and predict long-term changes in soil
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characteristics. Fallow phase is considered to be an important factor that alters the soil microbial parameters that reflect the soil nutrient availability.
10.3
Factors Affecting Soil Microbial Properties
The quality of soil depends on physicochemical factors including its natural composition and modifications caused by humans on its management system (Abbott and Murphy 2003). The presence of soil microbes and enzyme activity enhance the rate of reaction at which plant residues decompose and release plant-available nutrients (Balezentiene 2012). It is therefore used as an indicator of soil management depending on the intensity of disturbance, inherent soil nutrient, and OM status and other biotic factors. But abiotic elements like temperature, moisture, soil pH, and aeration are crucial in determining how quickly soil microbes proliferate (Zhou et al. 2005) (Fig. 10.1). Chemical reaction rates double with every 10 °C increase in temperature; however, enzymatic reaction rates grow until the pH is optimal and then decline (Tabatabai 1994). Chatterjee et al. (2019) studied the impact of temperature in soil under different land use of Nagaland on labile C and microbial properties and reported that increasing temperature from 36 °C to 42 °C increased the MBC and MBN while there was a reduction in the dissolved organic matter (DOM). Similarly, dehydrogenase and acid phosphatase activity increased from ambient to elevated temperature, while the acid phosphatase decreased after 36 °C while dehydrogenase activity increased after 36 °C to 42 °C. The amount of soil microbial biomass and enzyme activity are determined in part by the moisture content of the soil. Studies from several tropical regions showed that soil MB exhibited a high value during the rainy season (increased soil moisture), as opposed to the dry season (decreased soil moisture) (Devi and Yadava 2006; Iqbal et al. 2010; Patel et al. 2010). Warm and humid conditions during the rainy season speed up the decomposition of the litter because microbial activity and
Fig. 10.1 Schematic diagram showing factors affecting soil microbial proliferation
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decomposition are at their height during this time, increasing the microorganisms’ ability to immobilize nutrients (Usman et al. 2000; Devi and Yadava 2010). The highest levels of microbial biomass are reported in India’s humid subtropical forest (Arunachalam and Arunachalam 2000) and dry tropical deciduous forest (Singh et al. 1989) in summer and winter, respectively. This suggests that microbial biomass is greatly influenced by the species composition, location, elevation, and pattern of rainfall at the site. According to previous research, a 10% soil moisture reduction decreased the activities of urease, protease, and β-glucosidase, while a 21% soil moisture reduction decreased urease, protease, β-glucosidase, and acid phosphatase activities, but had no discernible effects on alkaline phosphatase activity (Sardans and Penuelas 2005). The overall impact of changes in climatic circumstances on enzyme activity depends on how they affect both enzyme production and turnover. It is challenging to isolate the impact of a single abiotic factor on a specific soil enzyme due to the intricacy of interactions between many climatic conditions and soil characteristics (Steinweg et al. 2013). The pH of the soil has a significant impact on the makeup of the microbial population (Grosso et al. 2016; Yang et al. 2017). According to Turner (2010), the soil pH exerts a significant influence on enzyme conformation, absorption on solid surfaces, ionization, and substrate solubility, which suggests that the variation in pH stability of enzymes was caused by various sources that contributed to enzyme activity and its adsorption. High H+ and OH- ion concentrations tend to break down the ionic and hydrogen bonds necessary to keep the enzyme in its active shape, which results in a loss of biological activity (Pavani et al. 2017). According to Shi et al. (2008), soil OM had a beneficial indirect effect that offsets the detrimental impact of soil pH on urease and phosphatase activity. The water and nutrient condition of the soil can both be impacted by soil texture, which then affects the microorganisms’ habitat and metabolic activity (Naveed et al. 2016). Soil aeration influences the soil properties and soil reaction, and these reactions facilitate the breaking down of OM. Further, soil microbial activity and biochemical processes effectively control the availability and movement of vital plant nutrients, which are significantly influenced by soil aeration. Correspondingly, aeration enhances air permeability, thereby improving soil oxygen content and increased the activity of soil enzymes (Niu et al. 2012). Additionally, prior research has demonstrated that synthetic soil aeration can enhance the root zone environment, raise soil enzyme activity, and encourage nutrient uptake, hence encouraging plant growth and fruit production and enhancing soil quality (Li et al. 2015).
10.4
Land Use Change and Soil Organic Carbon
Due to changes in biomass, shifting cultivation in the NEH region of India and other land uses may modify the SOC stock and soil quality. Studies conducted in the northeast revealed a decrease in SOC when forests were converted to shifting cultivation and established agriculture (Singh et al. 2018; Choudhury et al. 2016). Previous research has shown that shift from a natural forest to agricultural land has
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Table 10.1 Impact of fallow length on soil organic carbon
5.42–11.25 (mg g-1)
Fallow length (Years) 1, 3, 6, 10, 14, 21 and 23 2, 4, 6, 11 and 15
0.77–1.39 (mg g-1)
1,3 and 6
1.46–2.14 (mg g-1) (unburnt-Mizoram) 1.22–1.82 (mg g-1) (burntMizoram) 1.70–2.85 (mg g-1) (unburnt-Nagaland) 1.63–2.16 (mg g-1) (burntNagaland) 0.54–0.65 (mg g-1)
5, 10 and 15
3 and 7
1.40–1.96 (mg g-1)
2 and 7
119.10–141.85 (mg ha-1)
1–2, 5–8 and 15–20
Soil organic carbon 19.1–30.22 (mg g-1)
5, 10 and 15 5, 10 and 20 5, 10 and 20
Response with fallow Increase with fallow length Increase with fallow length Increase with fallow length Increase with fallow length Increase with fallow length Increase with fallow length Increase with fallow length Increase with fallow length Decrease with fallow length Decrease with fallow length
Reference Lungmuana et al. (2017) Haripal and Sahoo (2013) Reza et al. (2014) Saplalrinliana et al. (2016)
Binarani et al. (2009) Sahoo et al. (2019) Nath et al. (2021)
significantly reduced both the labile and recalcitrant percentage of soil organic C (Haynes 2005; Wei et al. 2013). The dynamics of SOC can be strongly influenced by a number of variables, including past land use, climate, vegetation type, and management techniques (Lal 2008). The length of fallow period in shifting cultivation has significant impact on SOC and analyses of earlier studies indicate increased SOC with respect to increase in the number fallow ages (Table 10.1). The increment amount of SOC from 2 to 15 years fallow was 51.82% (Haripal and Sahoo 2013), 44.60% from 1 to 6 years fallow (Reza et al. 2014), 16.92% from 3 to 7 years fallow (Binarani et al. 2009), and 36.79% from 1 to 23 years fallow (Lungmuana et al. 2017). Longer fallow periods may have higher SOC values due to the creation and progress of vegetative cover, which results in the accumulation of soil organic matter, a reduction in runoff loss, and a consequent buildup of SOC (Seyum et al. 2019). In addition, the greater contribution of root exudates from the plant communities in longer fallow acts as source of nutrients for soil microbes enhancing the rate of decomposition of organic matter (Hauchhum and Tripathi 2019). On the contrary, Sahoo et al. (2019) observed a reduction of 28.5% SOC from current jhum to 7 years fallow and a 10.5% drop of SOC from 1–2 fallow to 15–20 years fallow (Nath et al. 2021). Furthermore, the SOC content decreased significantly after burning, and the extent of the decrease ranges from 17.3% to 22% both (Saplalrinliana et al. 2016). The reduction in SOC concentration with fallow length may be the result of post burning effect as burning vegetation biomass enriched the SOC mainly at the top soil (Nath et al. 2021). Higher topsoil temperature due to
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burning also enhanced the decomposition rates of organic matter, and the limited incorporation of litter materials was also responsible for the decline in SOC (Saplalrinliana et al. 2016). Studies revealed greater SOC levels up until the second year, fallow land that had been idle for a longer length (more than 15 years) with higher SOC content was more susceptible to burning loss. This could be a result of increasing the amount of heating and burning at higher temperatures since more biomass has accumulated during the prolonged fallow period (Tawnenga and Tripathi 1997). Land use and land cover change is one of the major factors that significantly affect the SOC pool that relies on the rate of input (plant residues) and rate of output (SOC and nitrogen mineralization) of soil organic matter as a result of changes in land management practices and vegetation development (Dawson and Smith 2007; Poeplau and Don 2013).
10.5
Land Use Change and Soil Microbial Biomass
Numerous studies on soil microbial biomass including microbial biomass carbon (MBC) and nitrogen (MBN) in the fallow period following shifting cultivation in different states in Northeast India revealed that the longer fallow phase has a significantly high amount of MBC and MBN as compared to the shorter fallow phase. Lungmuana et al. (2017) found the total amount of MBC (491–992.8 mg kg-1) from 1, 3, 6, 10, 14, 21, and 23 years of fallow length from Kolasib district, Mizoram, where the amount was higher with increasing fallow period and SOC. Hauchhum and Tripathi (2017) also recorded higher values of MBC and MBN within 2, 5, and 10 years of fallow length in the Aizawl district, Mizoram. Similarly, Saplalrinliana et al. (2016) examined the effect of fallow length (5, 10, and 20 years) on MBC and MBN and reported that the total value of MBC ad MBN significantly increased as the number of fallow lengths increased. In addition, several studies also reported an increasing trend in the value of MBC and MBN from the short fallow to long fallow phase (Ralte et al. 2005; Jia et al. 2005; Haripal and Sahoo 2013) (Fig. 10.2). The steady rise in soil microbial biomass that occurs with an extension of the fallow period points to enrichment of soil organic matter status during secondary succession. The key driver in the development of soil microbial biomass includes plant species, vegetation cover, and soil organic matter (Tscherko et al. 2005). Thus, undisturbed forests or lengthening the number of fallow periods would increase the accumulation of forest litter and fine roots, thereby increasing the amount of root exudates that provide energy for soil microbial function, leading to increase in the size of soil microbial pool. On the other hand, frequent burning activity of slashed biomass in short fallow alters the soil physicochemical properties. Consequently, the number of soil microbial population substantially reduced due to the burning effect as well as the loss of soil moisture and soil organic carbon. Previous research discovered a positive relationship between soil moisture and microbial biomass because more soil moisture encourages microbial activity, which in turn boosts microbial biomass (Patel et al. 2010; Yang et al. 2010). Similarly, soil organic
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Fig. 10.2 (a) Slashed vegetation for burning and cultivation. (b) Cultivation after burning
carbon content has a positive association with soil microbial biomass (Reza et al. 2011; Lungmuana et al. 2017; Hauchhum and Tripathi 2017), and the ratio of soil organic carbon and microbial biomass reflects the availability of nutrient substrates to soil microbes (Dinesh et al. 2003). On the other hand, soil microbial biomass relatively depends not only on the quantity of available plants but also on the type and quality of plants (Jia et al. 2005), indicating that the early regenerating plants in fallow land largely determine the quality of soil organic matter, which in turn will affect the soil microbial biomass. Furthermore, the continual exudates released by the early colonizing plants have a large impact on the soil microbial activity and as a result, increase the microbial biomass (Hauchhum and Tripathi 2019, 2020). Alder tree (Alnus nepalensis), a traditional agroforestry system practiced in Nagaland, can increase the SOC through symbiotic N fixing with actinomycetes (Frankia), thereby increasing soil nutrients, MBC, and potentially mineralizable N compared to traditional jhum and natural forest (Kalidas-Singh et al. 2021). Traditional agroforestry systems such as tree bean (Parkia trimoriana) and Alnus nepalensis increase fixed atmospheric N, which increases biomass accumulation and improves soil health. Lungmuana et al. (2019) have investigated the effect of forest conversion to different land use such as current jhum and plantations like teak, arecanut, and rubber and found that there is less significant difference among the studied soil nutrients (available N, P, and K). However, in this study, there was a significant difference in the microbial properties where MBC, MBN, and basal respiration (μg g-1 h-1) were significantly higher in forest and plantation compared to current jhum, which mainly was attributed to the higher SOC content. Similarly, there was evidence of soil-labile C pool and MBC under leguminous agroforestry compared to other land uses even upto 1 m depth (Ansari et al. 2022).
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Fig. 10.2 (continued)
10.6
Land Use Change and Soil Enzyme Activity
Enzyme activity in the soil is sensitive marker of the health of the microbial community and the environment. It demonstrates changes in soil abiotic and biotic components brought on by human activity, as well as dynamics of soil organic matter (Trasar-Cepeda et al. 2008). The influence of changes in land use and management methods on soil health can be assessed by measuring the enzyme activity of the soil (Acosta-Martínez et al. 2007; Pandey et al. 2014; de Medeiros et al. 2015). Moreover, the activity of enzymes depends on the soil microbial population (Kourtev et al. 2002), vegetation (Sinsabaugh et al. 2002), physiochemical properties (Amador et al. 1997), disturbance, and vegetation succession (Tscherko et al. 2005). Studies from the different regions indicate that enzyme activities are greatly affected by land use change (Acosta-Martínez et al. 2007), tillage (Acosta-Martinez and Tabatabai 2001), and cropping systems (Ekenler and Tabatabai 2002). Specific enzyme activities have been evaluated and compared in soils with various organic matter contents and have been recognized as straightforward indices of soil quality. Dehydrogenase activity is sensitive to external factors and is mainly used as an ecotoxicological indicator. Due to its intracellular presence in all living microbial cells, soil enzyme plays a significant part in the transformation of organic carbon, and their activity levels are used as a measure of total microbial activity (Bielinska et al. 2014; Rana et al. 2021). Phosphatases are the driving force for the transformation of organic phosphorus compounds into inorganic phosphates, which are an available form of this element to plants and soil organisms. The activity of the phosphatase enzyme is involved in phosphorus cycling and has also been reported to
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be governed by soil microclimate, soil organic carbon, and the availability of phosphorus in the soil (Hamman et al. 2008). Alkaline phosphatase is a measure of the pH of the soil, whereas acid phosphatase is mostly released by plant roots and fungi (Bielinska et al. 2014). The availability of urease in soil indicates nitrogen transformation and generally use as a measure of nitrogen cycling and transformation (Rana et al. 2021). Proteases indicate the rate of mineralization of organic nitrogen compounds in soil (Jesmin et al. 2022). Widely used in the evaluation of soil quality under various management activities is ß-glucosidase activity (Saviozzi et al. 2001). Evaluation of enzyme activity provides quantitative data on the chemistry of the soil, rates of nutrient mineralization, and buildup of organic matter. Thus, abiotic factors such as temperature, moisture, soil pH, and oxygen content have an impact on the activity of soil enzymes, and the physicochemical makeup of organic matter and its position in the soil strata have a significant impact on the rate of growth of soil microorganisms (Zhou et al. 2005). Studies reported that fallow length, vegetation succession, and restoration of abandoned land have positive impacts on the soil enzyme activities, which are attributed mainly due to the soil organic carbon accumulation. Soil OC also increases other nutrient and gives the energy required for microbial transformation. Thus, N-fixing trees such as Alnus nepalensis improve soil health and increase phosphatase enzyme activity compared to natural forest and jhum (Kalidas-Singh et al. 2021). A significant increase in soil phosphatase and dehydrogenase enzyme activity upto 1 m soil depth was also exhibited by Parkia roxburghii agroforestry compared to non-legume agroforestry systems (Ansari et al. 2022), suggesting that soil microbes are responsible for soil nutrient enrichment through N fixation by legumes. The response of soil enzyme activities in different jhum fallow length was listed in Table 10.2. Higher organic matter content means a greater supply of substrate that acts as a source of energy and enhances the soil microbes and hence, greater enzyme activity (Hauchhum and Tripathi 2020). These soil microbes are directly responsible and play a vital role in soil nutrient cycling and improved restoration of vegetation. Studies also reveal the strong correlation between the volume of microbial biomass and soil enzyme activities, hence, as the soil microbial biomass increased in longer fallow length that positively increases the soil enzyme activity (Saplalrinliana et al. 2016; Lungmuana et al. 2017; Hauchhum and Tripathi 2020).
10.7
Conclusion
The increase in microbial activities like microbial biomass and enzyme activities in longer vegetation fallow, forests, and less-intensely managed plantation compared to shorter fallow phase or intensified forms of agriculture was due to higher quantity of accumulated litters. The decomposition of OM regulated soil nutrient availability resulting in higher activity of soil microbes and soil enzymes. However, due to the metabolism of soil microbes, soil nutrients status may not show the significant difference, but, on the contrary, significant change can be observed in the microbial activities as it is more sensitive to environmental alteration. The frequent burning
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Table 10.2 Effect of fallow length in different soil enzyme activity Fallow length (Years) 2, 4, 6, 11, 15
Enzyme response with fallow length Increase
5, 20 5, 10, 15
Increase Decrease
1, 3, 6, 10, 14, 21, 23 5, 20 5, 10, 15
Increase
5, 10, 15
Increase
2, 5, 10
Increase
1, 3, 6, 10, 14, 21, 23 5, 20 1, 5, 10
Increase
2, 4, 6, 11, 15
Increase
1, 3, 6 5, 10, 15
Increase Increase
1, 3, 6, 10, 14, 21, 23 2, 5, 10
Increase Increase
5, 20 1, 5,10
Increase Increase
2, 5, 10
Increase
1, 3, 6, 10, 14, 21, 23 1, 5, 10
Increase
Protease
5, 10, 15
Increase
Cellulase
5, 20 2, 4, 6, 11, 15
Increase Increase
Phosphatase
2, 4, 6, 11, 15
Increase
Soil enzyme Amylase
Arylsulphatase
ß-glucosidase
Dehydrogenase
Acid phosphatase
Increase Decrease
Increase Increase
Increase
Reference Haripal and Sahoo (2013) Deka et al. (2019) Saplalrinliana et al. (2016) Lungmuana et al. (2017) Deka et al. (2019) Saplalrinliana et al. (2016) Saplalrinliana et al. (2016) Hauchhum and Tripathi (2017) Lungmuana et al. (2017) Deka et al. (2019) Hauchhum and Tripathi (2020) Haripal and Sahoo (2013) Reza et al. (2014) Saplalrinliana et al. (2016) Lungmuana et al. (2017) Hauchhum and Tripathi (2017) Deka et al. (2019) Hauchhum and Tripathi (2020) Hauchhum and Tripathi (2017) Lungmuana et al. (2017) Hauchhum and Tripathi (2020) Saplalrinliana et al. (2016) Deka et al. (2019) Haripal and Sahoo (2013) Haripal and Sahoo (2013) (continued)
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Table 10.2 (continued) Soil enzyme Urease
Fallow length (Years) 2, 4, 6, 11, 15
Enzyme response with fallow length Increase
Alkaline phosphatase
1, 3, 6, 10, 14, 21, 23
Increase
Reference Haripal and Sahoo (2013) Lungmuana et al. (2017)
practice in shifting cultivation or intensifying agriculture creates a stressed environment and hinders the functions of certain microbe and enzyme activities suggesting that soil microbial-labile C and activities as enzyme can be successfully used as a quick indicator of land use change in the region. Fragile ecosystem of north eastern India, rapid land use changes due to the introduction of monoculture plantations involving deforestation lead to a decline in soil health and function. Thus, soil-labile C pools and microbial activities can successfully be used as an early indicator of soil health.
References Abbott LK, Murphy DV (2003) Soil biological fertility: a key to sustainable land use in agriculture. Springer Science & Business Media, Dordrecht Acosta-Martinez V, Tabatabai MA (2001) Enzyme activities of a lime agricultural soil. Biol Fert Soil 31(1):85–91 Acosta-Martínez V, Mikha MM, Vigil MF (2007) Microbial communities and enzyme activities in soils under alternative crop rotations compared to wheat-fallow for the central great plains. Appl Soil Ecol 37(1–2):41–52 Amador JA, Glucksman AM, Lyons JB, Gorres JH (1997) Spatial distribution of soil phosphatase activity within a riparian forest. Soil Sci 162:808–825 Ansari MA, Choudhury BU, Mandal S, Jat SL, Meitei CB (2022) Converting primary forests to cultivated lands: long-term effects on the vertical distribution of soil carbon and biological activity in the foothills of eastern Himalaya. J Environ Manag 301:113886 Arunachalam A, Arunachalam K (2000) Influence of gap size and soil properties on microbial biomass in a subtropical humid forest of North-East India. Plant Soil 233:185–193 Balezentiene L (2012) Hydrolases related to C and N cycles and soil fertility amendment: responses to different management styles of agro ecosystems. Pol J Environ Stu 21:1153–1159 Batjes NH (2014) Projected changes in soil organic carbon stocks upon adoption of recommended soil and water practices in Teh upper Tana River catchment, Kenya. Land Degrad Devel 25: 278–287 Benbi DK, Brar K, Toor AS, Singh P, Singh H (2012) Soil carbon pools under poplar based agroforestry, rice-wheat and maize-wheat cropping in semiarid India. Nutr Cycl Agroecosyst 92:107–118 Bielinska EJ, Futa B, Mocek-Plóciniak A (2014) Soil enzymes as bioindicators of soil quality and health. Libropolis Scientific 550 Publishers Society, Lublin Binarani RK, Yaava PS, Ibechoubi L (2009) Soil organic carbon and soil microbial biomass under the shifting cultivation systems of Kangchup hills Manipur, North-East India. Int J Eco Environ Sci 35:261–266 Blair GJ, Lefroy RDB, Lisle L (1995) Soil carbon fractions based on their degree of oxidation and the development of a carbon management index. Aust J Agric Res 46:1459–1466
10
Soil Microbial Carbon Pools as an Indicator of Soil Health in. . .
201
Chatterjee D, Kuotsu R, Ao M, Saha S, Ray SK, Ngachan SV (2019) Does rise in temperature adversely affect soil fertility, carbon fractions, microbial biomass and enzyme activities under different land uses? Curr Sci 116:2014–2054 Choudhury BU, Fiyaz AR, Mohapatra KP, Ngachan S (2016) Impact of land uses, agrophysical variables and altitudinal gradients on soil organic carbon concentration of North-Eastern Himalayan region of India. Land Degrad Devel 27:1163–1174 Dawson JJC, Smith P (2007) Carbon losses from soil and its consequences for land-use management. Sci Tot Environ 382:165–190 de Medeiros EV, Notaro KA, de Barros JA, Moraes WS, Silva AO, Moreira KA (2015) Absolute and specific enzymatic activities of sandy entisol from tropical dry forest, monoculture and intercropping areas. Soil Till Res 145:208–215 Deka J, Thakuria D, Khyllep A, Ahmed G (2019) Isolation and functional characterization of beneficial bacteria associated with roots of Thysolaena maxima and rhizospheric soil enzyme activities in Jhum agriculture. Curr Agri Res J 7:189–200 Devi NB, Yadava PS (2006) Seasonal dynamics in soil microbial biomass C, N and P in a mixedoak forest ecosystem of Manipur, North-East India. Appl Soil Ecol 31(3):220–227 Devi NB, Yadava PS (2010) Influence of climate and litter quality on litter decomposition and nutrient release in sub-tropical forest of Northeast India. J For Res 21(2):143–150 Dinesh R, Chaudhadhuri GS, Ganeshmurthy AN, Dye C (2003) Changes in soil microbial indices and their relationships following deforestation and cultivation in wet tropical forests. Appl Soil Ecol 24:17–26 Duval ME, Galantini JA, Martínez JM, Limbozzi F (2018) Labile soil organic carbon for assessing soil quality: influence of management practices and edaphic conditions. Catena 171:316–326 Ekenler M, Tabatabai MA (2002) ß-Glucosaminidase activity of soils: effect of cropping systems and its relationship to nitrogen mineralization. Biol Fert Soils 36:367–376 Franzlueebber AJ, Hons FM, Zuber DA (1994) Seasonal changes in soil microbial biomass and mineralizable C and N in wheat management systems. Soil Biol Biochem 26:1469–1475 Grosso F, Bååth E, Nicola F (2016) Bacterial and fungal growth on different plant litter in mediterranean soils: effect of C/N ratio and soil pH. Appl Soil Ecol 108:1–7 Hamman ST, Burke IC, Knapp EE (2008) Soil nutrients and microbial activity after early and late season prescribed burns in a sierra nevada mixed conifer forest. For Ecol Manag 256:367–374 Haripal K, Sahoo S (2013) Physicochemical and biochemical reclamation of oil through secondary succession. Open J Soil Sci 3:235–243 Hauchhum R, Tripathi SK (2017) Rhizosphere effects of Melocannabaccifera on soil microbial properties under different fallow phases following shifting cultivation. Int J Plant Soil Sci 17:1– 9 Hauchhum R, Tripathi SK (2019) Carbon and nitrogen differences in rhizosphere soil of annual plants in abandoned lands following shifting agriculture in Northeast India. Nut Cyc Agroecosyst 113:157–166 Hauchhum R, Tripathi SK (2020) Impact of rhizosphere microbes of three early colonizing annual plants on improving soil fertility during vegetation establishment under different fallow periods following shifting cultivation. Agric Res 9:213–221 Haynes RJ (2005) Labile organic matter fractions as central components of the quality of agricultural soils. Adv Agron 85:221–268 Iqbal J, Hu R, Feng M, Lin S, Malghani S, Ali IM (2010) Microbial biomass, and dissolved organic carbon and nitrogen strongly affect soil respiration in different land uses: a case study at three gorges reservoir area, South China. Agri Ecosys Environ 137:294–307 Jenkinson DS, Ladd JN (1981) Microbial biomass in soil: measurement and turnover. In: Paul EA, Ladd JN (eds) Soil biochemistry, 5th edn. Marcel Dekker, New York, NY, pp 415–471 Jesmin T, Margenot AJ, Mulvaney RL (2022) A comprehensive method for casein-based assay of soil protease activity. Comm Soil Sci Plant Anal 53:507–5200
202
Lungmuana et al.
Jia GM, Cao J, Wang C, Wang G (2005) Microbial biomass and nutrients in soil at the different stages of secondary forest succession in Ziwulin, Northwest China. For Ecol Manag 217:117– 125 Jiang JP, Xiong YC, Jiang HM, Ye DY, Song YJ, Li FM (2009) Soil microbial activity during secondary vegetation succession in semiarid abandoned lands of loess plateau. Pedosphere 19: 735–747 Kaiser EA, Mueller T, Joergensen RG, Insam H, Heinemever O (1992) Evaluation of methods to estimate the soil microbial biomass and the relationship with soil texture and organic matter. Soil Biol Biochem 18:95–108 Kalidas-Singh S, Bora IP, Thakuria D, Changkija S, Puyam A, Khwairakpam L (2021) The comparative soil fertility in traditional and alder-based shifting cultivation of varied fallow lengths in eastern Indian Himalayas. Soil Sci Plant Nut 67:681–692 Kirschbaum MUF (2000) Will changes in soil organic carbon act as a positive or negative feedback on global warming? Biogeochemistry 48:21–51 Kourtev PS, Ehrenfeld JG, Häggelom M (2002) Exotic plant species alter the microbial community structure and function in the soil. Ecology 83:3152–3166 Lal R (2008) Sequestration of atmospheric CO2 in global carbon pools. Energy Environ Sci 1:86– 100 Li Y, Jia ZX, Niu WQ, Wang JW, Zhang MZ (2015) Effect of postinfiltrationsoil aeration at different growth stages on growth and fruitquality of drip-irrigated potted tomato plants (Solanum lycopersicum). PLoS One 10:e0143322 Lungmuana, Singh SB, Vanthawmliana, Saha S, Dutta SK, Rambuatsaiha, Singh AR, Boopathi T (2017) Impact of secondary forest fallow period on soil microbial biomass carbon and enzyme activity dynamics under shifting cultivation in North Eastern Hill region, India. Catena 156:10– 17 Lungmuana, Singh SB, Choudhury BU, Vanthawmliana, Saha S, Hnamte V (2019) Transforming jhum to plantations: effect on soil microbiological and biochemical properties in the foot hills of north eastern Himalayas, India. Catena 177:84–91 Moore JM, Klose S, Tabatabai MA (2000) Soil microbial biomass carbon and nitrogen as affected by cropping systems. Biol Fert Soils 31:200–210 Nath PC, Nath AJ, Reang D, Rattan L, Das AK (2021) Tree diversity, soil organic carbon lability and ecosystem carbon storage under different fallow age chronosequence in North East India. Environ Sus Indic 10:100–122 Naveed M, Herath L, Moldrup P, Arthur E, Nicolaisen M, Norgaard T, Ferre TPA, de Jonge LW (2016) Spatial variability of microbial richness and diversity and relationships with soil carbon, texture and structure across an agricultural field. Appl Soil Ecol 103:44–55 Niu W, Zang X, JiaZ SH (2012) Effects of rhizosphere ventilationon soil enzyme activities of potted tomato under different soil water stress. Clean Soil Air Water 40:225–232 Pandey D, Agrawal M, Bohra JS (2014) Effects of conventional tillage and no tillage permutations on extracellular soil enzyme activities and microbial biomass under rice cultivation. Soil Till Res 136:51–60 Patel KK, Nirmal-Kumar JI, Nirmal-Kumar R, Kumar-Bhoi R (2010) Seasonal and temporal variation in soil microbial biomass C, N and P in different types land uses of dry deciduous forest ecosystems of Udaipur, Rajasthan, Western India. Appl Ecol Environ Res 8:377–390 Pavani G, Chandrasekhar RP, Padmaja G, Naveen KB (2017) Effect of soil temperature, moisture and pH on soil L-glutaminase activity. Int J Curr Micro Appl Sci 6(8):3081–3087 Poeplau C, Don A (2013) Sensitivity of soil organic carbon stocks and fractions to different landuse changes across Europe. Geoderma 192:189–201 Ralte V, Pandey HN, Barik SK, Tripathi RS, Prabhu SD (2005) Changes in microbial biomass and activity in relation to shifting cultivation and horticultural practices in subtropical evergreen forest ecosystem on North-East India. Acta Oecol 28:163–172 Ramesh T, Bolan NS, Kirkham MB, Wijesekara H, Kanchikerimath M, Rao CS, Sandeep S, Rinklebe J, Ok YS, Choudhury BU, Wang H, Tang C, Wang X, Song Z, Freeman OW
10
Soil Microbial Carbon Pools as an Indicator of Soil Health in. . .
203
(2019) Soil organic carbon dynamics: impact of land use changes and management practices: a review. Adv Agron 156:1–107 Rana MA, Mahmood R, Ali S (2021) Soil urease inhibition by various plant extracts. PLoS One 16: e0258568 Reza SK, Baruah U, Sarkar D, Dutta DP (2011) Influence of slope positions on soil fertility index, soil evaluation factor and microbial biomass indices in acid soil of humid subtropical India. Ind J Soil Conser 39:44–49 Reza SK, Baruah U, Nath DJ, Sarkar D, Gogoi D (2014) Microbial biomass and enzyme activity in relation to shifting cultivation and horticultural practices in humid subtropical North-Eastern Region. Range Manag Agrofor 35:78–84 Sahoo UK, Singh SL, Gogoi A, Knye A, Sahoo SS (2019) Active and passive soil organic carbon pools as affected by different land use types in Mizoram, Northeast India. PLoS One 14(7): e0219969 Saplalrinliana H, Thakuria D, Changkija S, Hazarika S (2016) Impact of shifting cultivation on litter accumulation and properties of Jhum soils of north East India. J Ind Soc Soil Sci 64:402–413 Sardans J, Penuelas J (2005) Drought decreases soil enzyme activity in a mediterranean Quercus ilex L. Forest Soil Biol Biochem 37:455–461 Saviozzi A, Levi-Minzi R, Cardelli R, Riffaldi R (2001) A comparison of soil quality in adjacent cultivated, forest and native grassland soils. Plant Soil 233:251–259 Seyum S, Taddese G, Mebrate T (2019) Land-use land cover changes on soil carbon stock in the Weshem watershed, Ethiopia. For Res Eng Int J 3:24–30 Sharma S, Singh P, Angmo P, Satpute S (2022) Total and labile pools of organic carbon in relation to soil biological properties under contrasting land-use systems in a dry mountainous region. Carbon Manage 13:352–371 Shi ZJ, Lu Y, Xu ZG, Fu SL (2008) Enzyme activities of urban soils underdifferent land use in the Shenzhen city, China. Plant Soil Environ 54(8):341–346 Singh JS, Raghubanshi AS, Singh RS, Srivastava SC (1989) Microbial biomass acts as a source of plant nutrients in dry tropical forest and savanna. Nature 338:499–500 Singh SL, Sahoo UK, Kenye A, Gogoi A (2018) Assessment of growth, carbon stock and sequestration potential of oil palm plantations in Mizoram, Northeast India. J Environ Prot 9: 912–931 Sinsabaugh RL, Carreiro MM, Repert DA (2002) Allocation of extracellular enzymatic activity in relation to litter composition, N deposition, and mass loss. Biogeochemistry 60:1–24 Smith JL, Paul EA (1990) The significance of soil microbial biomass estimation. In: Magusar F, Gantar M (eds) Perspectives in microbial ecology. Sloven Society for Microbiology, Ljubljana, pp 357–396 Steinweg JM, Dukes JS, Paul EA, Wallenstein MD (2013) Microbial responses to multifactor climate change: effects on soil enzymes. Front Micro 4:146. https://doi.org/10.3389/fmicb. 2013.00146 Tabatabai MA (1994) Soil enzymes. In: Weaver RW, Angle JS, Bottomley PS, Bezdicek D, Smith S, Tabatabai A, Wollum A (eds) Methods of soil analysis: microbiological and biochemical properties. Soil Science Society of America, Madison, WI, pp 775–833 Tawnenga SU, Tripathi RS (1997) Evaluating second year cropping on jhum fallows in Mizoram, North-Eastern India: soil fertility. J Biosci 22:615–625 Trasar-Cepeda C, Leirósb MC, Gil-Sotres F (2008) Hydrolytic enzyme activities in agricultural and forest soils. Some implications for their use as indicators of soil quality. Soil Biol Biochem 40: 2146–2155 Tscherko D, Hammesfahr U, Zeltner G, Kandeler E, Bocker R (2005) Plant succession and rhizosphere microbial communities in a recently deglaciated alpine terrain. Basic Appl Ecol 6:36–383 Turner BL (2010) Variation in pH optima ofhydrolytic enzyme activities in tropicalrain forest soils. Appl Environ Micro 76(19):6485–6493
204
Lungmuana et al.
Usman S, Singh SP, Rawat YS, Bargali SS (2000) Fine root decomposition and nitrogen mineralization pattern in Quercus leucotrichophora and Pinus roxburghii forest in central Himalaya. For Ecol Manag 131:191–199 Wei X, Shao M, Gale WJ, Zhang X, Li L (2013) Dynamics of aggregate-associated organic carbon following conversion of forest to cropland. Soil Biol Biochem 57:876–883 Yang K, Zhu J, Zhang M, Yan Q, Sun OJ (2010) Soil microbial biomass carbon and nitrogen in forest ecosystems of Northeast China: a comparison between natural secondary forest and larch plantation. J Plant Ecol 3:175–182 Yang Y, Li X, Liu J, Zhou Z, Zhang T, Wang X (2017) Bacterial diversity as affected by application of manure in red soils of subtropical China. Biol Fert Soils 53:639–649 Zhou QH, Wu ZB, Cheng SP, He F, Fu GP (2005) Enzymatic activities in constructed wetlands and di-n-butyl phthalate (DBP) biodegradation. Soil Biol Biochem 37:1454–1459
Bamboo Resources in Karbi Anglong District of Assam and Their Role in Soil Carbon Management
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Pator Singnar, Panna Chandra Nath, Arun Jyoti Nath, and Ashesh Kumar Das
Abstract
Bamboo being an important and subsistence non-timber forest product (NTFP) is meeting various commercial, social, environmental, and rural economical perspectives. India is one of the largest reserves of bamboo in the world with 145 species belonging to 23 genera. The diversity and growing stock of bamboo are very rich in the North-Eastern region of India, which represents about 66% of the growing stock of bamboo represented by 78 species belonging to 19 genera. Karbi Anglong district is very rich in forest bamboo resource with more than six species found in this region. The commonly found forest bamboo species are Dendrocalamus hamiltonii, Melocanna baccifera, Schizostachyum dullooa, Pseudostachyum polymorphum, Bambusa pallida, Gigantochloa parvifolia, etc. The soil organic carbon (SOC) content varied across the soil layer for different forest bamboo stands with a range of 0.65–1.46%, 0.56–1.93%, 0.66–1.61%, and 0.61–2.04% for P. polymorphum, M. baccifera, S. dullooa, and D. hamiltonii, respectively. The SOC stock from 0 to 100 cm soil layer depth was found highest for P. polymorphum forest (131.77 ± 5.66 Mg ha-1) followed by S. dullooa forest (128.70.12 ± 3.85 Mg ha-1), D. hamiltonii forest (127.44 ± 3.05 Mg ha-1), and M. baccifera forest (118.62 ± 3.82 Mg ha-1). The SOC density (118.62–131.77 Mg ha-1) computed in the study falls within the worldwide range for bamboo ecosystem 70–200 Mg ha-1. Therefore, forest bamboos in Karbi Anglong district provide an important opportunity for soil carbon sink management. Keywords
SOC · Correlation matrix · Carbon pool · REDD+ P. Singnar · P. C. Nath (✉) · A. J. Nath · A. K. Das Department of Ecology and Environmental Science, Assam University, Silchar, Assam, India # The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Mishra et al. (eds.), Soil Carbon Dynamics in Indian Himalayan Region, https://doi.org/10.1007/978-981-99-3303-7_11
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Introduction
Bamboo being the important and subsistence non-timber forest product (NTFP) is meeting various social, commercial, environmental, and rural economical perspectives (Blowfield et al. 1996; Rao 1998; Sundriyal et al. 2002); belongs to the subfamily Bambusoideae of the grass family Poaceae (Graminae) and has about 75 genera with over 1250 species on the globe (Sharma 1982; Soderstrom and Ellis 1988). It grows from the tropical to the temperate regions of the world with a bumpy distribution depending on the altitude, annual precipitation, conditions of the soil, and temperature (FSI 2017), covering about 31.5 million hectare of land surface, which is equivalent to 0.8% of the total forested area of the globe (FAO 2010; Song et al. 2011). Bamboo represents one of the world’s greatest natural and renewable resources and is called as “the poor man’s timber” to the Indian natives; it is “the friend of the people” to the Chinese and “the brother” of the Vietnamese (Banik 2000) and also known as green gold, cradle to coffin timber (FSI 2017). In India, 125 indigenous bamboo species and 11 exotic bamboo species belonging to 23 genera are reported with principal genera including Arundinaria, Bambusa, Chimonobambusa, Dendrocalamus, Dinochloa, Gigantochloa, etc. and are naturally growing roughly across all parts of the country excluding Kashmir (FSI 2017). In India, nearly 15.69 million hectare area is estimated to be the total bamboo-bearing area (pure, dense, and scattered bamboo stands are 0.06, 4.05, and 9.14 m. ha., respectively) with Northeastern states having 5.41 million hectare bamboo-bearing area (FSI 2017). Bamboo, extremely a diverse plant that easily adapts to different climatic and soil conditions, can play a vital role in poverty alleviation, carbon sequestration, as well as in soil and water conservation or in land rehabilitation (Ben-zhi et al. 2005). It offers humankind a variety of products for daily needs and also a protective habitat function (Ben-zhi et al. 2005). It is an important aspect of several natural and agricultural ecosystems, which provide crucial ecosystem services to consumers in developed and developing countries like food and raw materials (provisioning services). Bamboo also regulates the flow of water, helps in erosion control on slopes and along riverbanks due to the action of water, and is also important in treating wastewater. It offers as a catalyst culminating windbreak in shelterbelts and helps in protection against storms (regulating services) (Yipping et al. 2010). The poor and rural people may be retrogressively hit by the effects of climate change; therefore, action plans for adaptation need to be customized to their situation (UNFCCC 2007). Bamboo forests can be used comprehensively in rehabilitating degraded and prone-to-degradation hillsides, riverbanks, and catchment areas and have represented a promising and quick result (Ben-zhi et al. 2005). Karbi Anglong district is very rich in forest bamboo resource with more than six species found in this region. The commonly found forest bamboo species are Bambusa pallida Munro, Dendrocalamus hamiltonii Nees, Gigantochloa parvifolia (Brandis ex Gamble) T.Q. Nguyen, Melocanna baccifera (Roxb.) Kurz., Pseudostachyum polymorphum Munro, Schizostachyum dullooa (Gamble) R.B. Majumdar, etc. Whereas, Bambusa tulda is the most commercially cultivated bamboo species
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throughout the district. Limited research and associated uncertainties with resolutions prevent a robust assessment of carbon stocks for most bamboo species. Review of current allometric equations revealed the need of more work in developing equations to predict biomass carbon for most bamboo species (Yuen et al. 2017). Moreover, no study has been done on the biomass, carbon stock, carbon sequestration potential in the district. Therefore, the present study was aimed with the objectives to estimate phytosocial and carbon sequestration potentials of selected Bamboo species in the Karbi Anglong district.
11.2
Materials and Methods
The Karbi Anglong district is located in the central part of Assam, North east India (NEI), with its headquarters in Diphu. This is the largest district and is one of the 33 administrative districts of Assam with main inhabitants of the district being the Karbi community. Main forest types of the region are: tropical: semi-evergreen forest, moist: deciduous forest, dry: deciduous forest, and subtropical: moist evergreen forest. The Karbis (indigenous group of the district), in their various day-today purposes, use >05 species of bamboo, of which the prominent are Bambusa tulda Roxb. and B. balcooa Roxb. (Sil borua) in the plains and Dendrocalamus hamiltonii Nees et Arn. ex Munro in the hills (Teron and Borthakur 2011). Among the village bamboo species, B. tulda is the most preferred bamboo by the local peoples of this region. Forests dominated by each of the bamboos were identified, and two each from clump-forming and non-clump-forming bamboos were selected for the present study based on their occurrence and socioeconomy in the village livelihoods (Singnar et al. 2021). Among the selected species, the thin-walled bamboos include S. dullooa, P. polymorphum and M. baccifera and dominate the forest bamboo species of NEI, whereas D. hamiltonii is the only thick-walled bamboo species. For the estimation of soil physicochemical parameters, samples of soil were collected at different depths (0–10, 10–30, 30–60, and 60–100 cm) of vertical soil profile using soil corer of 5.5 cm diameter. Triplicate samples were collected from each layer, and two samples from each layer were mixed to make a composite sample for analysis of different physicochemical properties, and another was used for the bulk density (BD) determination. The BD samples were air-dried, preprocessed for dirt removal, and kept in hot air oven at 105 °C until a constant weight was gained and BD was calculated (Al-Shammary et al. 2018; Nath et al. 2022). SOC was estimated following Walkley and Black wet oxidation method (Walkley and Black 1934). Bouyoucos Hydrometer method (Bouyoucos 1962) was followed for the texture analysis of the soil of the selected bamboo stands. Waterholding capacity (WHC) of soil for different bamboo forests was determined by Keen’s box method (Keen and Raczkowski 1921; Nath et al. 2022). The pH of the soil samples was measured by a pH meter (Thomas 1996; Kabala et al. 2016).
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Results
Soil BD of S. dullooa stand ranges from 1.28 to 1.57 Mg m-3 with minimal at top of the layers and gradually increases with depth, whereas, for M. baccifera stands, the value varies from 1.36 to 1.64 Mg m-3, which varies significantly across soil depths. The range of soil BD recorded for P. polymorphum stand was from 1.33 to 1.77 Mg m-3 with values significantly varying across the soil depths ( p < 0.01). For D. hamiltonii forest, the mean soil BDs of 0–10, 10–30, 30–60, and 60–100 cm depth were 1.26, 1.57, 1.67, and 1.79 Mg m-3, respectively, with values significantly varying across the soil depths ( p < 0.05). Percent sand was the most dominant across all the soil depths for S. dullooa stand, which varies from 52.72 to 62.24% followed by silt (22.00–25.75%) and clay (13.89–25.28%) (Table 11.1). However, percent clay was more than that of silt at the depths of 30–60 and 60–100 cm. The soil of D. hamiltonii forest represented the percent sand, silt, and clay in similar trend that was found at S. dullooa stand. WHC of soil ranges from 30.86 to 32.49% for P. polymorphum stand and from 35.51 to 37.81% for S. dullooa forest and is significantly not different across the different soil layers. However, WHC of M. baccifera soil varied from 30.11 to 33.75% and from 35.95 to 37.78% for D. hamiltonii stand, which was significantly different across the soil layer depths ( p < 0.01). There is a slightly higher pH value in M. baccifera stands (5.13–6.19), and it decreases with the increasing soil depth (Table 11.1). The mean SOC was recorded to be decreasing for all the forest bamboos with soil depth. The highest SOC (2.04%) was recorded for D. hamiltonii stand at the top layer (0–10 cm) of soil, whereas the lowest value was recorded for M. baccifera stand at 60–100 cm soil layer (0.56%). SOC across the soil layer for different forest bamboo stands ranged as 0.65–1.46, 0.56–1.93, 0.66–1.61, and 0.61–2.04% for P. polymorphum, M. baccifera, S. dullooa, and D. hamiltonii stands, respectively. The SOC stock up to 100 cm soil depth was found to be the highest for P. polymorphum forest (131.77 ± 5.66 Mg C ha-1) followed by S. dullooa forest (128.70 ± 3.85 Mg C ha-1), D. hamiltonii forest (127.44 ± 3.05 Mg C ha-1), and M. baccifera forest (118.62 ± 3.82 Mg C ha-1) (Table 11.2). The SOC proportion of 0–10 cm depth to total SOC stock ranged between 18.69 and 24.17% for M. baccifera stand, 13.89–20.76% for P. polymorphum stand, 15.75–21.48% for D. hamiltonii stand, and 15.08–17.12% for S. dullooa stands with the mean contribution of 22%, 17%, 18%, and 16%, respectively. The proportion of 60–100 cm depth was the highest for the soil of all the selected forest bamboo stands with 29%, 31%, 31%, and 30% for M. baccifera, P. polymorphum, S. dullooa, and D. hamiltonii stand, respectively (Fig. 11.1). Pearson’s correlation (two-tailed) was performed between the soil physicochemical parameters and SOC (%) for all the selected four forest bamboos. For S. dullooa forest, SOC (%) of the soil was highly negative correlated with BD (r = -0.88, p < 0.01) and clay% (r = -0.97, p < 0.01) while it was significantly positive correlation with the sand% (r = 0.93, p < 0.01). For M. baccifera forest, SOC (%) of the soil was negatively correlated with the BD and clay%, whereas it showed significantly positive correlation with the sand%. Significant negative correlation
Depth (cm) 0–10 10–30 30–60 60–100 0–10 10–30 30–60 60–100 0–10 10–30 30–60 60–100 0–10 10–30 30–60 60–100
Sand (%) 35.95 ± 0.66 32.67 ± 0.66 29.76 ± 0.24 24.64 ± 0.27 64.67 ± 0.67 60.00 ± 0.23 56.67 ± 0.56 50.24 ± 0.12 62.24 ± 1.37 56.67 ± 0.67 54.72 ± 0.16 52.72 ± 0.11 46.00 ± 0.18 45.33 ± 0.67 42.67 ± 0.67 35.33 ± 0.65
Silt (%) 37.03 ± 0.67 34.00 ± 0.11 26.91 ± 0.58 23.69 ± 0.67 25.33 ± 0.65 27.03 ± 0.62 24.00 ± 0.12 24.43 ± 0.62 23.87 ± 0.81 25.75 ± 0.67 22.00 ± 1.15 22.00 ± 0.08 27.33 ± 0.67 32.00 ± 1.15 25.33 ± 1.33 18.00 ± 0.24
Values are mean ± standard error. BD bulk density, WHC water holding capacity
D. hamiltonii
S. Dullooa
M. baccifera
Bamboo species P. polymorphum
Clay (%) 27.03 ± 0.67 33.33 ± 0.67 43.33 ± 0.67 48.67 ± 0.66 10.00 ± 0.14 12.97 ± 0.66 19.33 ± 0.65 25.33 ± 0.67 13.89 ± 0.67 17.59 ± 0.67 23.28 ± 1.15 25.28 ± 0.13 26.67 ± 0.65 22.67 ± 0.67 32.00 ± 1.15 46.67 ± 0.66
Table 11.1 Soil physicochemical properties at different depths for four forest bamboo stands BD (Mg m-3) 1.33 ± 0.04 1.62 ± 0.07 1.71 ± 0.06 1.77 ± 0.10 1.36 ± 0.02 1.55 ± 0.02 1.59 ± 0.02 1.64 ± 0.03 1.28 ± 0.02 1.39 ± 0.05 1.41 ± 0.12 1.57 ± 0.04 1.26 ± 0.17 1.57 ± 0.08 1.67 ± 0.09 1.79 ± 0.04 WHC (%) 31.38 ± 0.36 30.86 ± 0.28 31.98 ± 0.69 32.49 ± 0.61 30.11 ± 0.56 30.93 ± 0.45 32.32 ± 0.15 33.75 ± 0.59 35.51 ± 1.45 37.69 ± 1.13 37.81 ± 1.54 36.76 ± 0.97 35.95 ± 1.55 36.05 ± 1.59 37.57 ± 1.94 37.78 ± 1.15
pH 5.98 ± 0.08 5.17 ± 0.04 5.11 ± 0.04 4.96 ± 0.04 6.19 ± 0.08 5.67 ± 0.08 5.26 ± 0.06 5.13 ± 0.07 5.64 ± 0.13 5.56 ± 0.08 5.47 ± 0.05 5.23 ± 0.04 5.40 ± 0.13 4.93 ± 0.06 5.18 ± 0.03 5.16 ± 0.02
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Table 11.2 Soil organic carbon (SOC) density of soil at different depths for four forest bamboo stands Bamboo species P. polymorphum
M. baccifera
S. Dullooa
D. hamiltonii
Depth (cm) 0–10 10–30 30–60 60–100 Total (0–100 cm) 0–10 10–30 30–60 60–100 Total (0–100 cm) 0–10 10–30 30–60 60–100 Total (0–100 cm) 0–10 10–30 30–60 60–100 Total (0–100 cm)
SOC (%) 1.46 ± 0.05 0.82 ± 0.05 0.80 ± 0.07 0.65 ± 0.07 1.93 ± 0.06 0.75 ± 0.03 0.61 ± 0.02 0.56 ± 0.03 1.61 ± 0.02 1.23 ± 0.06 0.87 ± 0.01 0.66 ± 0.02 2.04 ± 0.05 1.21 ± 0.08 0.80 ± 0.11 0.61 ± 0.04
SOC Stock (Mg C ha-1) 22.45 ± 0.97 28.14 ± 0.73 40.13 ± 1.92 41.05 ± 2.15 131.77 ± 5.66 25.56 ± 0.71 27.48 ± 1.52 31.07 ± 0.82 34.49 ± 1.14 118.62 ± 3.82 20.67 ± 0.22 32.87 ± 0.82 35.79 ± 0.42 39.37 ± 1.33 128.70 ± 3.85 23.31 ± 0.81 31.69 ± 1.51 34.19 ± 1.72 38.25 ± 1.73 127.44 ± 3.05
Values are mean ± standard error
was also recorded for SOC (%) of the soil of D. hamiltonii and P. polymorphum forest with BD and clay% while significant positive correlation was noticed with the sand% of the soil for both the species. During the present study, no significant correlation was recorded between the WHC (%) and SOC (%) for the forest bamboo species (Tables 11.3, 11.4, 11.5 and 11.6).
11.4
Discussion
The selected forest bamboo species during the present study were D. hamiltonii, S. dullooa, M. baccifera, and P. polymorphum. Selected stands were unmanaged, undisturbed, or less disturbed natural bamboo forests. The soil physicochemical parameters studied for the four forest bamboo species were recorded significantly different with the depth of the soil. The distribution pattern of sand, silt, and clay fraction with soil profile was the same for all the four forest bamboo stands selected during the present study. The BD, pH, and SOC (%) recorded for M. baccifera stand during the present study were comparable with the reported values (1.14 g cm-3, 5.78 g cm-3, and 1.37 g cm-3, respectively) from Barak Valley, NE India, for the same species (Nandy 2001). The observed reduced BD at the surface layer under studied bamboo forests of Karbi Anglong resembled the ability of the soils’ function
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Fig. 11.1 Contribution of different soil layers to the SOC stock (0–100 cm) of the soil collected from the selected forest bamboo stands. (a) M. baccifera forest, (b) P. polymorphum forest, (c) S. dullooa forest, and (d) D. hamiltonii forest Table 11.3 Pearson’s correlation (two-tailed) among the soil physicochemical parameters for M. baccifera forest Parameters SOC% BD (g cm-3) Clay% Silt% Sand% WHC% a
SOC% 1 -0.929a -0.753a 0.166 0.806a -0.331
BD (g cm-3)
Clay%
Silt%
Sand%
WHC%
1 0.810a -0.254 -0.846a 0.552
1 -0.572 -0.976a 0.705b
1 0.379 -0.463
1 -0.672b
1
Significant at the 0.01 level (two-tailed) b Significant at the 0.05 level (two-tailed)
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Table 11.4 Pearson’s correlation (two-tailed) among the soil physicochemical parameters for S. dullooa forest Parameters SOC% BD (g cm-3) Clay% Silt% Sand% WHC%
SOC% 1 -0.878a -0.969a 0.533 0.939a -0.176
BD (g cm-3)
Clay%
Silt%
Sand%
WHC%
1 0.838a -0.423 -0.832a -0.023
1 -0.646b -0.920a 0.240
1 0.294 0.005
1 -0.303
1
a
Significant at the 0.01 level (two-tailed) b Significant at the 0.05 level (two-tailed) Table 11.5 Pearson’s correlation (two-tailed) among the soil physicochemical parameters for D. hamiltonii forest Parameters SOC% BD (gcm-3) Clay% Silt% Sand% WHC% a
SOC% 1 -0.927a -0.648b 0.518 0.751a -0.054
BD (g cm-3)
Clay%
Silt%
Sand%
WHC%
1 0.815a -0.693b -0.893a 0.219
1 -0.969a -0.954a 0.154
1 0.850a -0.122
1 -0.179
1
Significant at the 0.01 level (two-tailed) Significant at the 0.05 level (two-tailed)
b
Table 11.6 Pearson’s correlation (two-tailed) among the soil physicochemical parameters for P. polymorphum forest Parameters SOC% BD (g cm-3) Clay% Silt% Sand% WHC% a
SOC% 1 -0.751a -0.841a 0.799a 0.881a -0.119
BD (g cm-3)
Clay%
Silt%
Sand%
WHC%
1 0.756a -0.742a -0.753a 0.075
1 -0.992a -0.978a 0.222
1 0.944a -0.212
1 -0.232
1
Significant at the 0.01 level (two-tailed)
to structural support for aeration, fine root production, and movement of watersoluble nutrients sustaining plants’ growth (Kaushal et al. 2020). It is also helpful to sustain porosity of the soil for better microbial metabolic activity, thereby inducing recalcitrant soil carbon storage. This had also increased the soil pH in the surface layer of vertical soil profile due to decomposition of organic materials, releasing organic acids at the humus layer. SOC density range (118.62–131.77 Mg C ha-1) observed at the present study was within the worldwide range for bamboo ecosystem 70–200 Mg C ha-1 (Yuen et al. 2017). SOC of the forest bamboo stands was recorded to be very high,
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indicating its significance for assessment of total ecosystem biomass carbon and function as an important terrestrial carbon pool. SOC stock up to 30 cm depth (50.59–55 Mg C ha-1) in the present study was comparable with the reported value from the same depth of 57.3 t ha-1 for village bamboos in North East India (Nath et al. 2009); 53.28 Mg ha-1 in M. baccifera stand from Mizoram, North-East India (Devi et al. 2018) but higher than the reported value of 38.8 Mg ha-1 in B. tulda stand from Mizoram, North-East India (Devi et al. 2018). The SOC stock reported for Phyllostachys bambusoides stand was 92 Mg C ha-1 (Isagi et al. 1993). The significant negative correlation of SOC and BD could be attributed to increased organic matter and subsequent mulching in the top soil and their reciprocal change with the increasing soil depth (Zhang et al. 2015). The recorded SOC value was lower than the reported value of 110.37–125.03 Mg C ha-1 (up to 30 cm) for non-degraded mixed Oak forest in Kumaon Himalaya (Chaturvedi and Melkania 2013); 188.80 Mg C ha-1 up to 90 cm soil depth for Tectona grandis plantations in West Bengal, India (Banerjee and Prakasam 2013) but comparable with the reported value of 43.81–53.47 Mg C ha-1 (up to 30 cm) for degraded mixed pine forest in Kumaon Himalaya (Chaturvedi and Melkania 2013). In the district, bamboo is not only a part of rural and cultural component but, it also had in service relating to soil conservation, ecosystem stability and acts as one of the lager carbon sink catalysts (Nath et al. 2015). Forests dominated by bamboos in the district are expected to represent a crucial role in mitigating the future impact of climate change as bamboo is regarded an ideal plant to have more carbon sequestration potentials within a short period of time due to its fast growth (Song et al. 2011). However, a majority of the shifting cultivable lands occupied by forest bamboo species were converted to degraded lands due to reduction in Jhum cycles (Sarkar et al. 2020; Nath et al. 2021). Therefore, partnership with local communities could be beneficial for conservation of the studied bamboo species for their management. Moreover, these four bamboo species could also be introduced to the degraded lands of the district for further benefits in climate change mitigation of the programs like REDD+ and restoration of the degraded lands.
11.5
Conclusion
Karbi Anglong district holds great forest bamboo resource; however, this resource has been degraded in recent years due to unsustainable harvest and land use conversion. The significant contribution of SOC stock in the selected forest bamboo stands indicates that these species can be considered for climate change mitigation projects. The bamboo forests represented by four species in Karbi Anglong, Northeast India, can help in restoration of degraded land and contribute toward REDD+ for the benefit of local comminities as most of these bamboo forests are managed by them.
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References Al-shammary AAG, Kouzani AZ, Kaynak A et al (2018) Soil bulk density estimation methods: a review. Pedosphere 28:581–596 Banerjee SK, Prakasam U (2013) Biomass carbon pool and soil organic carbon sequestration in Tectona grandis plantations. Indian For 139:797–802. https://doi.org/10.36808/if%2F2013% 2Fv139i9%2F37178 Banik RL (2000) Silviculture and field-guide to priority bamboos of Bangladesh and South Asia. Government of the People’s Republic of Bangladesh, Bangladesh Forest Research Institute, Chittagong, p 82 Ben-zhi Z, Mao-yi F, Jin-zhong X et al (2005) Ecological functions of bamboo forest: research and application. J For Res 16:143–147. https://doi.org/10.1007/BF02857909 Blowfield M, Boa E, Chandrashekara UM (1996) The role of bamboos in village based enterprise. In: Bamboo, people and the environment, vol 4. International Network of Bamboo and Rattan, Wangjing, pp 10–21 Bouyoucos GH (1962) Hydrometer method improved for making particle size analyses of soils. Agron J 54:464–465 Chaturvedi S, Melkania U (2013) Soil organic carbon stock in mixed oak and mixed pine forest of Kumaon Himalaya. Indian For 139:218–221 Devi AS, Singh KS, Lalramnghinglova H (2018) Aboveground biomass production of Melocanna baccifera and Bambusa tulda in a sub-tropical forest in Lengpui, North-East India. Int Res J Environ Sci 7:23–28 FAO (2010) Global forest resources assessment 2010: main report. Food and agricultural Organization of the United Nations, Rome, pp 30–32 FSI (2017) India State of Forest Report 2017. Forest survey of India (FSI), Ministry of Forest, Environment and Climate Change. Government of India, Dehradun, pp 57–66 Isagi Y, Kawahara T, Kamo K (1993) Biomass and net production in a bamboo Phyllostachys bambusoides stand. Ecol Res 8:123–133 Kabala C, Musztyfaga E, Galka B et al (2016) Conversion of soil pH 1:2.5 KCl and 1:2.5 H2O to 1.5 H2O: conclusions for soil management, environmental monitoring, and international soil databases. Pol J Environ Stud 25:647–653 Kaushal R, Singh I, Thapliyal AK et al (2020) Rooting behaviour and soil properties in different bamboo species of western Himalayan foothills. India Sci Rep 10:4966. https://doi.org/10.1038/ s41598-020-61418-z Keen AB, Raczkowski H (1921) The relation between the clay content and certain physical properties of a soil. J Agric Sci 11:441–449 Nandy S (2001) Studies on the ecology of Muli bamboo—Melocanna baccifera (Roxb.) Kurz. In Barak Valley, North-East India. M. Phil thesis, Department of Ecology, Assam University, Silchar, Assam, India Nath AJ, Das G, Das AK (2009) Above ground standing biomass and carbon storage in village bamboos in north East India. Biomass Bioenergy 33:1188–1196. https://doi.org/10.1016/j. biombioe.2009.05.020 Nath AJ, Lal R, Das AK (2015) Managing woody bamboos for carbon farming and carbon trading. Glob Ecol Conserv 3:654–663. https://doi.org/10.1016/j.gecco.2015.03.002 Nath PC, Nath AJ, Reang D et al (2021) Tree diversity, soil organic carbon lability and ecosystem carbon storage under a fallow age chronosequence in north East India. Environ Sustain Indicators 10:100122. https://doi.org/10.1016/j.indic.2021.100122 Nath PC, Sileshi GW, Ray P et al (2022) Variations in soil properties and stoichiometric ratios with stand age under agarwood monoculture and polyculture on smallholder farms. Catena 213: 106174. https://doi.org/10.1016/j.catena.2022.106174 Rao IVR (1998) Bamboo for sustainable development: an agenda for action. INBAR Magazine 6: 35–39
11
Bamboo Resources in Karbi Anglong District of Assam and Their Role in. . .
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Sarkar R, Bora AK, Sarma T (2020) Spatial distribution pattern of jhum cultivation and land use land cover status in Amri block of Karbi Anglong district, Assam. PalArch's J Archaeol 17: 2317–2323 Sharma YML (1982) Some aspects of bamboos in Asia and the Pacific, FAO Regular Programme. No. Rapa 57, Bangkok, p 56 Singnar P, Sileshi GW, Nath A et al (2021) Modelling the scaling of belowground biomass with aboveground biomass in tropical bamboos. Trees For People 3:100054. https://doi.org/10.1016/ j.tfp.2020.100054 Soderstrom TR, Ellis RP (1988) The woody bamboos (Poaceae: Bambusoideae) of Sri Lanka: a morphological-anatomical study. Smithsonian contributions of botany, no. 72. Smithsonian Institution Press, Washington, DD, pp 30–36 Song X, Zhou G, Jiang H et al (2011) Carbon sequestration by Chinese bamboo forests and their ecological benefits: assessment of potential, problems, and future challenges. Environ Rev 19: 418–428. https://doi.org/10.1139/a11-015 Sundriyal RC, Upreti TC, Varuni R (2002) Bamboo and cane resource utilization and conservation in the Apatani plateau, Arunachal Pradesh, India: implications for management. J Bamboo Ratt 1:205–246 Teron R, Borthakur SK (2011) Traditional uses of bamboos among the Karbis, a hill tribe of India. J Am Bamboo Soc 25:43–49 Thomas GW (1996) Soil pH and soil acidity. In: Methods of soil analysis. Part 3—chemical methods. SSSA Book Series, Madison, Wisconsin, p 475 UNFCCC (2007) Climate change impact, vulnerabilities and adaptation in developing countries. http://unfccc.int/resource/docs/publications/impacts.pdf Walkley A, Black IA (1934) An examination of Degtjareff method for determining soil organic matter and a proposed modification of the chronic acid titration method. Soil Sci 37:29–38 Yipping L, Yanxia L, Buckingham K et al (2010) Bamboo and climate change mitigation: a comparative analysis of carbon sequestration. INBAR technical report no. 32, Beijing, China, p 47 Yuen JQ, Fung T, Ziegler AD (2017) Carbon stocks in bamboo ecosystems worldwide: estimates and uncertainties. For Ecol Manag 393:113–138. https://doi.org/10.1016/j.foreco.2017.01.017 Zhang H, Zhuang S, Qian H et al (2015) Spatial variability of top sol organic carbon in the Moso bamboo forests of southern China in association with soil properties. PLoS One 10:e0119175. https://doi.org/10.1371/journal.pone.0119175
Land Use Change and Its Impacts on Soil Carbon Dynamics in Mizoram, Northeast India
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Jitendra Ahirwal, Uttam Thangjam, and Uttam Kumar Sahoo
Abstract
Mizoram is among the seven-sister states of northeast India and shows the most diverse land use in northeast India. Though vegetation is the major land cover in the state, it experiences rapid land use and land cover change that have a direct impact on the ecosystem function and soil carbon storage. To combat these land use changes, Mizoram adopted a new land use policy in 2011 that focused on the utilization of forest land and replacing shifting cultivation with settled farming. We identified major land uses (natural forest, plantation, agriculture, agroforest, grassland, and home garden) and reviewed the carbon storage potential of different land uses and how these pools are affected by the land use change in Mizoram. We show that soil carbon storage varied with the soil depth and was found highest in agricultural land. However, the impact of land use and land cover change on soil carbon stock was maximum on the plantation system and minimum on the home garden. We recommend carrying out a large number of field studies on different land uses to develop soil carbon map of Mizoram. Keywords
Agriculture · Forest · Land use change · Plantation · Soil carbon
J. Ahirwal · U. Thangjam · U. K. Sahoo (✉) Department of Forestry, School of Earth Sciences and Natural Resources Management, Mizoram University Aizawl, Aizawl, Mizoram, India # The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Mishra et al. (eds.), Soil Carbon Dynamics in Indian Himalayan Region, https://doi.org/10.1007/978-981-99-3303-7_12
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Introduction
Mizoram is one of the northeastern states of India. The name Mizoram is derived from the term “Mizo” generally used to describe the natives of the state or the people of the hills and “Ram” means land; therefore, Mizoram is the land of the Mizo people. Mizoram is among the seven-sister states of northeast India and is located in the southernmost region of northeast India. It is a landlocked state flanked by three neighboring states, Manipur in the northeast, Tripura in the northwest, and Assam in the north. Internationally the state is bounded by Myanmar in the east and Bangladesh in the west and is located within geographical coordinates 21° 58′— 24° 35’ N and 92° 15′—93° 29′ E (Fig. 12.1). Total area of the state is 21,084 km2 and 722 km international boundaries with Myanmar and Bangladesh. More than 80% of the geographical area of the state is hilly terrain. The altitude ranges from 152 to 2210 m above the mean sea level. The average height of the hills is 900 m, and the highest peak is Phawngpui (Blue Mountain) at a height of 2210 m. The marvelously green hills are steep and separated by rivers that flow either to the north (Tlawng and Tuirail) or south (Kaladan) creating deep gorgeous between the hill ranges. The climate of Mizoram is moderate, and the average temperature of the area is 22.48 °C, which varies from 11° to 21 °C during winter and from 20° to 30 °C during summer. Mizoram receives heavy rainfall with an average between 2500 mm and 3000 mm per year and is mostly brought by the southwest monsoon (from May to September). Mizoram is the second least populated state of India having a total
Fig. 12.1 Map of the Mizoram state showing the elevation gradient
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population of 1,205,974 in 2021–22 (UIDAI 2022). About 80% of the population depends on agriculture for their livelihood, and the majority of them are practicing shifting cultivation (Zothansanga and Beingachhi 2019). An exponential increase in population, land use change, and deforestation are among the major barriers to providing food security to all. Both land use change and reduction in jhum (local name for shifting cultivation) cycles alter soil fertility and often rendered crop productivity that is in turn responsible for lesser crop production and increased poverty. Owing to the predominant hilly terrain and lack of viable livelihood alternatives, about 0.3 million of the Mizo population engaged in jhum cultivation, which leads to the loss of approximately 600 km2 of natural forests. Moreover, deforestation in hilly regions leads to soil erosion and ecological disturbance at a greater rate. Therefore, several developmental initiatives are urgently needed to open new opportunities and provide alternative sustainable livelihood options to the major workforce in Mizoram and reduce the jhum cultivation practices. After recognizing a full-fledged state, Mizoram introduced a new land use policy in 1987 to control jhum cultivation on a modest scale in the selected blocks. In addition to financial assistance, integrated farming, sericulture, and cottage industries were also provisioned to improve rural livelihood. In 2002, a new land use policy was replaced by Mizoram Intodelhna Programme (MIP) to provide selfsufficiency, food security, and better livelihood for the cultivator as a whole by providing financial assistance to all the families. The main aim of MIP was the upliftment of the rural poor, especially the shifting cultivators, but it could not make any headway toward future sustainability as the assistance is very less, and frequent changes in the program lead to confusion and worst implementation. Mizoram adopted a new land use policy in 2011 that focused on the utilization of forest land and replacing shifting cultivation with settled farming (Bose 2019). This also emphasizes the need for sustainable farming that can provide adequate food and economic benefits to local farmers without land degradation. The major objectives of the new land use policy are to (1) keep 60% of the land in Mizoram under rain forest, (2) halt the destructive jhum farming and assist the farmers to engage in sustainable economic farming, and (3) to improve economies of the farmers and non-farming population through sustainable farming and microenterprises. Moreover, it focuses on land reclamation, regeneration of natural resources such as forests and biodiversity, and promotion of horticulture, plantation, animal husbandry, and fishery for employment and income generation. Considering social, ecological, and political concerns, understanding the role of soil carbon in mitigating multiple problems associated with global change has largely been focused on recent years. At the same time, a balance between anthropogenic activities and terrestrial carbon reserve is highly disturbed due to land use change, climate change, and land management (Beillouin et al. 2022). Growing scientific evidence shows that human activities have increased global warming, which could have vital feedback on land emissions and loss of soil carbon pool (Smith 2008). According to an estimate, soils have lost 40–90 Pg C globally due to cultivation and disturbance that mainly occurred in tropical regions (Smith 2008). A
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meta-analysis of 74 publications across the globe (Guo and Gifford 2002) reported that soil C declined substantially after land use change and mainly from forest to crop (-42%), pasture to crop (-59%) while increased after crop was converted to a secondary forest (+53%). In another meta-analysis on the impact of land use change on soil organic carbon (SOC) particularly in tropical land (Don et al. 2011), conversion of primary forest into cropland (-25%) and perennial crops (-30%) was reported, while these losses are reversed to some extent if agricultural land is afforested (+29%) or under cropland fallow (+32%). A comprehensive review and meta-analysis of carbon storage in a different plant-based ecosystem in the Indian Himalayan Region (IHR) show that plantations store a maximum amount of SOC (168.8 Mg C ha-1), but differences are insignificant when compared to SOC storage in forests, agroforest, and herbaceous vegetation cover ecosystems (Ahirwal et al. 2021b). Both the regional and global studies show decline in the SOC pool due to land use change. Thus, sustainable management of different land uses and soil C has become a priority for soil sustainability. In this chapter, we primarily focus on assessing the carbon sequestration potential of major land uses and how land use and land cover change alter the carbon budget of different land uses of Mizoram. For this, we identified major land uses and reviewed the carbon storage potential of different land uses and how these pools are affected by the land use change.
12.2
Major Land Use and Carbon Stock in Mizoram
Mizoram has the most versatile land use patterns in northeast India and is mostly covered by hilly terrain. The lands of the state are mainly occupied by vegetation including forests and plantations and remain barren or jhum fallows followed by human settlement, water bodies, and agricultural land (Table 12.1, Fig. 12.2). Total area of the state is recorded as 21,084 km2, of which vegetation is dominant and covers 85.96% of the total area followed by barren land that may include unfertile marginal land and then buildup area for human settlement. A closer view of the different land use, viz. natural forest, plantation, agriculture, agroforest, shifting cultivation (jhum), homegarden, grassland, and human settlement in Mizoram is shown in Fig. 12.3.
Table 12.1 Land use pattern of Mizoram state
Land use Agriculture land Water bodies Buildup area Barren land Vegetation cover Total
Area (km2) 18.082 36.652 441.497 2462.412 18126.044 21084.689
Area (%) 0.085 0.174 2.093 11.678 85.967
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Fig. 12.2 Land use and land cover (LULC) map of the Mizoram state
12.2.1 Natural Forests India State of Forest report 2021 shows the total forest cover of India is 713,789 km2, which is 21.75% of the total geographical area. In Mizoram, an area of 17,820 km2, which is 84.53% of the total geographical area of the state, is under forest cover (ISFR 2021). According to the report, Mizoram has an area of 157 km2 of very dense forest (0.74%), 5718 km2 of moderately dense forest (27.11%), and an area of 11,948 km2 of open forest (56.68%). Mizoram has a diverse range of forests that
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Fig. 12.3 Different land uses: (a) natural forest, (b) plantation, (c) agriculture land, (d) agroforest, (e) shifting cultivation (Jhum land), (f) homegarden, (g) grassland, and (h) human settlement in Mizoram
include six major forest types based on the latest classification viz., tropical wet evergreen forests, montane subtropical forests, temperate forests, bamboo forests, Quercus forests, and jhum land (Singh et al. 2002). Tropical wet evergreen forests are usually grown up to an altitude of 900 m and are mostly found in the western part of the state. These forests have a diverse range of tree species, of which Castanopsis tribuloides, Calliandra umbrosa, Albizia lebbeck, Litsea monopetala, Mesua ferrea, Saraca indica, and Sycopsis griffithiana are dominant. Montane subtropical forests are mostly found between the altitudes of 900 and 1500 m in the eastern fringes areas, which are bordering Myanmar. Plants such as Oroxylum indicum, Quercus oblongata, Helicia excelsa, Schima wallichii, and Syzygium claviflorum are dominant in these forests. The temperate forests are found in a few areas of Mizoram above 1600 m elevation. Species such as Quercus floribunda, Rhododendron arboretum, Castanopsis tribuloides, Helicia excelsa, Quercuso blongata, and Duabanga grandiflora are dominant in these forests. Quercus forests occur in both subtropical and temperate regions of the state. The dominant species in these forests are Quercus griffithii, Lithocarpus elegans, Quercus serrata, and Quercus lineata. Bamboo forests are almost everywhere in the state, and Mizoram is commonly known as Bamboo Queen. The diverse range of bamboo species was present in these forests; however, Bambusa tulda is the most common (Gogoi et al. 2022). Soil organic carbon concentration in the natural forests of Mizoram was reported at an average of 40.66 ± 16.52 Mg C ha-1 (n = 20) with a maximum of 77.09 Mg C ha-1 and a minimum of 11.90 Mg C ha-1 in top 0–15 cm of soil depth (Fig. 12.4). Studies also reported SOC stock for the different depths such as 0–10 cm, 10–20 cm, 20–30 cm, and 0–45 cm. Here we collected another dataset comprising SOC stock of 0–45 cm depth in natural forests and found 55.81 ± 12.02 Mg C ha-1 (40.75–77.69 Mg C ha-1, n = 5). SOC stock in different forests of Mizoram is largely varied. For example, SOC stock in temperate (178.91 Mg C ha-1), tropical
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Fig. 12.4 Soil organic carbon stock at 0–15 and 0–45 cm depth in different land use of Mizoram. AG agriculture, AGF agroforestry, HG home gardens
wet evergreen forest (161.61 Mg C ha-1), montane subtropical (147.06 Mg C ha-1), and Quercus forest (123.41 Mg C ha-1) shows variation in SOC stock up to 45 cm depth (Gogoi et al. 2022). Tropical semi-evergreen forests of Mizoram sequester 18.28 Mg C ha-1 in top 0–10 cm soil (Sharma et al. 2018) while a natural forest of Mizoram store 24.50 Mg C ha-1 in 0–15 cm, 16.52 Mg C ha-1 in 15–30 cm, and 11.71 Mg C ha-1 in 30–45 cm (Kenye et al. 2019).
12.2.2 Plantation New Land Use Policy in Mizoram introduces the plantation of different timber and fruit-yielding trees on marginal land that can be beneficial to local farmers as well as the restoration of degraded shifting cultivation lands. Oil palm, teak, orange, pineapple rubber, and areca nut plantations are dominant among others in Mizoram. Although the plantation of different tree species is a major cause of diversity loss, it is largely practiced to increase the economy of the landholders. In some parts of northeast India, field observation shows that plantation can increase biodiversity and help sequester carbon in biomass and soils that can be comparable to a natural forest of the area (Gogoi et al. 2021). Moreover, plant growth on shifting cultivation land helps recuperate soil quality and SOC sequestration in Mizoram (Ahirwal et al. 2022b). It is estimated that the plantation of different tree species potentially requesters 8.42–42.52 Mg C ha-1 in 0–15 cm of soil (n = 15) while in 0–45 cm of soil, it can sequester up to 31.93 ± 5.21 Mg C ha-1(n = 17) in Mizoram (Fig. 12.4).
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Fig. 12.5 Percentage changes in SOC stock (0–45 cm) from forest to other land use and land cover in Mizoram. AG agriculture, AGF agroforestry, HG home gardens
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A review of the literature shows varied SOC stock under different plantations in Mizoram. For example, teak plantation sequesters 20.57 Mg C ha-1 and oil palm plantation sequesters 17.29 Mg C ha-1 in 0–15 cm of soil (Kenye et al. 2019). In addition, SOC stock in the plantation forest of Mizoram was reported at 210.7 Mg C ha-1 in the top 100 cm of soils (Singh and Sahoo 2015). Oil palm plantation as monoculture, mixed, or in agroforestry system has been largely carried out in the last two decades in Mizoram. Along with the economic benefits to stakeholders, these plantations are proven useful to recuperate soil quality and accretion of SOC. After 11 years of oil palm plantation in Mizoram, SOC stock was reported at 30.55 Mg C ha-1 in 0–40 cm of soil (Singh et al. 2018c). SOC stock in other plantations (0–45 cm) such as arecanut (44.52 Mg C ha-1), coffee (33.38 Mg C ha-1), mango (16.00 Mg C ha-1), oil palm (36.73 Mg C ha-1), orange (39.49 Mg C ha-1), pine (26.05 Mg C ha-1), and teak (44.66 Mg C ha-1) was also reported a substantial amount of carbon in Mizoram (Singh et al. 2018a). Land use change from natural forest to plantation has a significant impact on the SOC stock, and particularly in Mizoram (n = 17), about 43% of the SOC stock was declined in 0–45 cm of soils (Fig. 12.5).
12.2.3 Agriculture Land The total agricultural land in the state is 1808 hectares, which is 0.09% of the total area of Mizoram. The lesser area for agriculture was mainly due to the hilly terrain where locals mostly practice shifting cultivation instead of permanent agriculture. About 90% of the population depends on agriculture as the main source of livelihood. Depending on the fertility of the soils, crops are generally grown for 1–2 years on the same land and then shifted to other lands. Wet rice cultivation, sugarcane, maize, ginger, and mustard are the major crops among others in Mizoram. Since agriculture is periodic, carbon sequestration in agricultural soil largely depends on land management and crop types. An average of the five studies carried out in
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Mizoram show SOC stock at 41.96 ± 13.08 Mg C ha-1 that ranged from 26.10 to 56.80 Mg C ha-1 in 0–15 cm of soils and 43.25 ± 6.69 Mg C ha-1 in 0–45 cm of soils (Fig. 12.4). Agriculture expansion in natural forests results in loss of SOC stock in many parts of the world (Ahirwal et al. 2021a; Guo and Gifford 2002). Likewise, in Mizoram, the conversion of forests to agriculture results in an approximately 22% decline in SOC stock (Fig. 12.5).
12.2.4 Agroforestry Agroforestry is a land use management that integrates trees or shrubs around crops or pasture land. It is recognized globally as an option for sustainable land use management because it provides a range of ecosystem goods and services including carbon sequestration, soil fertility, and nutrient cycling (Nair et al. 2009). A global metaanalysis of 427 databases shows that the agroforestry system stores an average of 126 Mg C ha-1 in the top 1 m of soils, which is about 19% higher than that of the cropland or pasture (Shi et al. 2018). Authors also opined that agroforestry could store 5.3 × 109 carbon in soils of 944 M ha of land mainly distributed in tropical and subtropical regions globally. In Mizoram, the top 0–15 cm of soils store an average of 17.53 ± 5.59 Mg C ha-1 and 0–45 cm of soils store 52.52 ± 1.66 Mg C ha-1 (Fig. 12.4). It is observed that in comparison to the natural forests, soils of the agroforestry system sequester about 6% lesser SOC stock (Fig. 12.5). A study of oil palm cultivation in an agroforestry system (maize, turmeric, and pineapple) and its impact of soil carbon sequestration in Mizoram reported higher SOC under co-cultivation of oil palm and maize (36.70 Mg C ha-1) in 0–30 cm of soils (Ahirwal et al. 2022b). It is recommended to grow oil palm in an agroforestry system not only to increase the economies of the farmers and stakeholders but also to provide ecological services such as carbon sequestration (Ahirwal et al. 2022b; Khasanah et al. 2020).
12.2.5 Grassland Grasslands are among the major land uses across the globe and cover approximately 25% of the land surface that potentially store 12% of terrestrial carbon stock (Ontl and Janowiak 2017). In Mizoram, grassland occupies comparatively lesser land cover than forest and agriculture and is mainly located at higher altitudes. Likewise, only three studies reported SOC stock in grassland that ranged from 26.59 to 55.19 Mg C ha-1 in 0–45 cm of soils (Fig. 12.4). However, when forests converted to grassland, SOC stocks were reduced up to 35% (Fig. 12.5). Stability of SOC in grassland shows lesser active carbon pool and sequesters 26.76 Mg C ha-1 (0–45 cm), which is lesser than the other major lands uses in Mizoram (Sahoo et al. 2019). Another study determining the SOC stock in grassland reported 16.09 Mg C ha-1 in the top 15 cm of soils (Kenye et al. 2019). Loss of soil carbon may impact numerous ecosystem functions such as reducing water-holding capacity
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and soil fertility while increasing wind and water erosion. Therefore, the management of carbon must focus on reducing soil disturbance, which can be achieved by reduced tillage and increasing vegetation cover (Ontl and Janowiak 2017).
12.2.6 Home Gardens Home gardens are one of the ancient land use patterns and are very common in northeast India. These gardens are a vital source of rare genetic resources and provide grounds for plant biodiversity conservation comprising woody, ornamental, fruits and vegetables, and medicinal plants (Thangjam et al. 2022). Given the need for food security for locals, every garden is unique in terms of food production, species composition, nutrients, market value, and site management (Galhena et al. 2013). Besides several socioeconomic services, home gardens provide numerous ecological benefits such as a site for animal husbandry, reduction of soil erosion and nutrient losses in hilly areas, carbon sequestration, and offset of greenhouse gas emissions (Eyzaguirre and Linares 2010; Jeeceelee and Sahoo 2022). Studies conducted in Mizoram to assess the potential role of the home garden in SOC sequestration show an average of 24.15 ± 7.49 Mg C ha-1 in 0–15 cm soils (n = 5) and 59.09 ± 17.85 Mg C ha-1 in 0–45 cm of soil (n = 8) (Fig. 12.4). Exceptionally, SOC stock increased by 6% when natural forests were converted to the home garden (Fig. 12.5) that may be attributable to manure application due to animal and proper management of soils to increase fertility of the home garden. A study conducted to assess variation in SOC stock based on the age and size of the home garden reported small home gardens (154.68 Mg C ha-1) and old-age home gardens (258.43 Mg C ha-1) sequester more SOC stock compared to large and young-age home garden in Mizoram (Singh and Sahoo 2015). In another field study carried out in Mizoram, SOC stock in home garden was reported at 183.42 Mg C ha1 in the top 1 m of soils, which is much greater than the shifting cultivation (Singh and Sahoo 2021). While assessing SOC stock in major land uses of Mizoram, soils of home gardens sequester 19.95 Mg C ha-1 (0–15 cm), 17.54 Mg C ha-1 (15–30 cm), 13.36 Mg C ha-1 (30–45 cm) in different soil depths (Kenye et al. 2019).
12.3
Jhum Cultivation: Challenges and Opportunities
Shifting cultivation also known as slash-and-burn agriculture (locally known as Jhum) is a form of agricultural practice that involves land clearing by slashing and burning a piece of land and then framing on the same land until the loss of soil fertility. Jhum is a traditional agricultural practice of the ethnic communities living in hilly regions of the entire northeast India. It may also be described as a traditional cultivation practice of rotating land for temporary farming that helps maximize the utilization of land in hilly terrain (Bose 2019). It is cyclic and, when land becomes unfertile for further cultivation, left for natural succession, and cropping plots will be
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shifted for cultivation (Lal 2017). The cycle begins with the slashing and burning of vegetation to convert the forest into cultivated land. Further, cultivation is carried out for a period of one or more years, followed by a fallow period that may be extended to 5–20 years. This fallow period allows the soil to recover naturally and regain nutrients and organic matter. However, it also causes land degradation, deforestation, and biodiversity loss, therefore remains debatable on socioeconomic–cultural– environmental nexus (Ahirwal et al. 2022a). Recent statistics on jhum cultivation show that about 198.5 km2 (0.94%) of the total land of Mizoram is under jhum cultivation (Zothansanga and Beingachhi 2019). Jhum cultivation is one of the major sources of food, and most of the population depends on jhum for livelihood.
12.3.1 Soils of Jhum Land Jhum cultivation is well known to aggravate several issues related to soil sustainability such as health and function. Soil degradation in terms of nutrient loss, SOC depletion, and erosion are the major issues that arise due to continuous changes in land use from forest to jhum and jhum to other land use (Mishra and Francaviglia 2021). Therefore, land use change has a direct impact on the soil quality and sustainability of soils in this region. Unlike, in different parts of the state and overall northeast India, jhum cultivation is one of the simplest options for cultivation that also help sanitize soil, reduce weed growth and soil pathogen, and unlock the nutrients bound in biomass (Wapongnungsang et al. 2021). Loss of soil fertility and crop productivity in Mizoram is the greatest matter of concern to both the local population and the government. It is reported that soils of jhum land are acidic and poor in nutrients, soil carbon, and microbial biomass. To overcome this problem, several field studies were carried out in the state. For example, a study was carried out to explore the response of the fallow period and application of indigenous soil microbe and rock phosphate on soil fertility and crop productivity in Mizoram (Wapongnungsang et al. 2021). The results show that jhum significantly increased the soil pH, P, and N levels while decreasing soil C, microbial biomass C, and organic matter in both 10 and 15 years of fallow land. Moreover, the synergistic effect of rock phosphate and microbial inoculation improves soil biochemical properties and maximizes rice grain yield and productivity. Another study was carried out on the effect of fertilizers on the growth and yield of the maize variety called mimpui under different jhum cycles (Hnamte et al. 2016). As the burning reduces the soil nutrients, this study aims to optimize the balance between jhum cycle and fertilizer application to enhance soil fertility and crop growth. Different levels of NPK fertilizer application were studied in 2, 3, and 5 years of jhum cycle, and significant growth and yield of maize were recorded under fertilizer application. Also, different periods of jhum had an impact on the growth and yield of maize where the longest jhum cycle was highly productive. The study suggests that a 5-year jhum cycle with a lower rate of fertilizer application (80: 40:20 NPK kgha-1) may be adopted in poor soil nutrient content and acidic soil in Mizoram. Changes in soil fertility in terms of nutrients, pH, and carbon were
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assessed on young (6 years) and old (20 years) jhum fields in response to different management activities such as slashing and burning of vegetation, cropping period, and intervening fallow period between first and second year cropping (Tawnenga and Tripathi 1997). The results show that jhum declined soil pH, C, and N but elevates P, cations, whereas soil fertility declined along the cropping age.
12.3.2 Carbon Storage Potential of Jhum Cultivation System Soils can act as one of the most important and largest sinks of carbon and subsequently reduce atmospheric carbon concentration (IPCC 2019). However, maintaining soil as a carbon sink is very complex and only be achieved through proper management activities. SOC is one of the most recognized soil quality indicators and is largely used to assess the sustainability of many agroecosystems or land converted from forest to agriculture (Majumder et al. 2008). Studies carried out in Mizoram to assess carbon storage in soils of jhum land reported SOC concentration in the range of 1.34–2.90% in top 0–15 cm of soils, which is lesser than the natural forest of the area (Ahirwal et al. 2022a; Singh et al. 2018b; Yinga et al. 2020). Data collected from the literature on SOC stock in jhum land varied largely among the similar soil depth and different soil depths. For example, an average of nine studies reporting SOC stock in the top 15 cm of soils in jhum land is 23.07 ± 10.0 Mg C ha-1 while the minimum value is 11.67 Mg C ha-1 and maximum at 38.71 Mg C ha-1 (Fig. 12.4). For the larger soil depth (0–45 cm), the SOC stock increased and ranged between 14.91 and 56.93 Mg C ha-1 with an average of 32.40 ± 12.93 Mg C ha-1 (n = 8). Though the potential of jhum land to sequester soil C may vary among the ages of revegetation and period of jhum cycle, it remains increasing with the age preferably up to 10–20 years but remains lesser than the natural forests.
12.4
Case Studies
A large number of studies were carried out to study the impact of land use change on the soil carbon stock in different land uses of Mizoram. Here, we discuss two classic examples of field studies that show changes in SOC stock due to land use and land cover change. First, a study was conducted in eight major land uses of Mizoram, viz. natural forests, oil palm plantation, teak plantation, bamboo plantation, shifting cultivation, wet rice cultivation, home gardens, and grassland to assess changes in SOC stock due to land use change (Kenye et al. 2019). Since natural forests cover major land use, it is essential to investigate the impact of anthropogenic land use change or other disturbance patterns that may affect carbon stock. The authors collected a total of 120 soil samples from three depths (0–15, 15–30, and 30–45 cm) and eight land uses and analyzed them for SOC concentration, fine earth fraction, and bulk density to calculate SOC stock. Change in SOC stock due to land use conversion was calculated as the difference between SOC stock of the
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Fo re s O il t pa lm Te Sh a Ba k ift in m bo W gc u o et ric ltiv e c atio ul n H tiva om tio n eg ar de ns G ra ss la nd
Fig. 12.6 Changes in soil organic carbon concentration (%) and stock (Mg C ha-1) down to 45 cm soils in different land uses of Mizoram
SOC concentration (%)
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previous land use, i.e., natural forest and present land use. The significant difference between the SOC stocks of the different land uses was confirmed using an analysis of variance. The soil was acidic and sandy loam in textural class. The major soil types were Typic Udorthents, Typic Dystrochrepts, Typic Hapludults, Umbric-Dystrochrepts, Humic Hapludults and across the study area. The average bulk density of the top 45 cm soils was recorded the highest in natural forests (0.68 g cm-3) and lowest in shifting cultivation land (0.42 g cm-3) that show lesser compaction in soils across the land uses. Among the different land uses, natural forests showed the highest SOC concentration in each of the soil depths and highest in topsoil (0–15 cm) at 3.74% followed by 2.70% in 15–30 cm and 1.79% in 30–45 cm. Unlike, bamboo forests had lowest SOC concentration of 1.25% (0–15 cm) > 1.10 (15–30 cm) > 0.56% (30–45 cm) (Fig. 12.6). Since natural forests remain undisturbed to a large extent, carbon cycle in forests maintains an appropriate balance between land and atmosphere. Moreover, in an old-age forest, higher above- and below-ground biomass contributes a substantial amount of carbon into the soils through decomposition. In contrast, lesser carbon concentration in bamboo plantations may be because of the younger age of the plantation exhibiting lesser biomass. Bamboo plantation in the state is largely carried out on shifting cultivation lands, for that large piece of land was fired that substantially reduced microbial population and carbon stock. SOC concentration showed an inverse relation with soil depth across land uses. Soil carbon storage is mainly controlled by the balance between the rate of carbon input through photosynthesis and its release through autotrophic and heterotrophic
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respiration (Chapin et al. 2011). Carbon stored via above-ground biomass, belowground biomass, and litter in soils is highly dependent on vegetation cover and climatic conditions (Fontaine et al. 2007). However, in similar climatic conditions, carbon storage is mainly governed by plant traits. Therefore, land use change leads to alter vegetation cover that in turn changes carbon storage in soils. SOC stock (0–45 cm soil) in different land use varied slightly and was found highest in natural forests (52.74 Mg C ha-1). SOC stock in other studied land uses was found in the order of home garden (50.85 Mg C ha-1) > wet rice cultivation (46.21 Mg C ha1 ) > teak plantation (44.66 Mg C ha-1) > oil palm plantation (36.73 Mg C ha1 ) > bamboo plantation (29.83 Mg C ha-1) > shifting cultivation (27.87 Mg C ha1 ) > grassland (27.68 Mg C ha-1) (Fig. 12.6). SOC stock highly depends on the soil texture, i.e., particles size having Tropical wet evergreen (TWE) forest > Montane subtropical forest > Quercus forest > bamboo forest > jhum land. Temperate forests store the highest amount of SOC stock, which may be attributable to the larger canopy cover at a higher elevation and lesser soil disturbance. In contrast, jhum land is frequently disturbed by human activities that resulted in lower SOC stock. The study also showed that the conversion of TWE forest to jhum land reduces SOC stock by 65.3%. Changes in SOC stock were highest when temperate forests were converted to jhum land (69.1%) (Fig. 12.7). Overall, the average reduction in SOC stock was higher due to the conversion of natural forests to jhum land (58%). The number of studies carried out in northeast India also reported a decline in SOC stock, i.e., 30.8% in Nagaland (Mishra and Francaviglia 2021), 63.5% in the eastern Himalayas (Gogoi et al. 2022), 56.5% in Mizoram (Sahoo et al. 2019), and 38% in the rainforest for northeast India (Gogoi et al. 2020) after natural forest was converted to jhum cultivation. Authors highlighted that land use and land cover change significantly reduced the SOC stock of the major forests in Mizoram, and the magnitude of changes in SOC was highest when temperate forests were brought under shifting cultivation.
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Summary and Future Perspectives
Mizoram has diverse land use patterns, and each land use has a different potential to store soil carbon. Accelerated land use change has a significant impact on the soil carbon stock; thus, proper management of land use is essential to prevent carbon losses and sequester more carbon into the soil. Our data synthesis shows that among the major land uses of Mizoram, natural forest sequesters higher soil carbon compared to other land use, but it also depends on the soil depth of measurement. In addition, the conversion of natural forest to other land use reduces the SOC stock, whereas the plantation system substantially reduces the SOC stock among other land uses such as agroforestry, jhum land, agriculture, home gardens, and grassland. A review of the literature identifies that a lesser number of studies were carried out to assess carbon storage in grassland and agroforestry compared to natural forest and plantation systems. Therefore, we recommend carrying out a large number of studies across the diverse land use to assess SOC stock and quantify changes in SOC due to land use change that can help to prepare baseline data on SOC stock and assist to develop carbon management strategies in Mizoram.
References Ahirwal J, Kumari S, Singh AK, Kumar A, Maiti SK (2021a) Changes in soil properties and carbon fluxes following afforestation and agriculture in tropical forest. Ecol Indic 123:107354. https:// doi.org/10.1016/j.ecolind.2021.107354 Ahirwal J, Nath A, Brahma B, Deb S, Sahoo UK, Nath AJ (2021b) Patterns and driving factors of biomass carbon and soil organic carbon stock in the Indian Himalayan region. Sci Total Environ 770:145292. https://doi.org/10.1016/j.scitotenv.2021.145292 Ahirwal J, Gogoi A, Sahoo UK (2022a) Stability of soil organic carbon pools affected by land use and land cover changes in forests of eastern Himalayan region, India. Catena 215:106308. https://doi.org/10.1016/J.CATENA.2022.106308 Ahirwal J, Sahoo UK, Thangjam U, Thong P (2022b) Oil palm agroforestry enhances crop yield and ecosystem carbon stock in Northeast India: implications for the United Nations sustainable development goals. Sustain Prod Consum 30:478–487. https://doi.org/10.1016/J.SPC.2021. 12.022 Beillouin D, Cardinael R, Berre D, Boyer A, Corbeels M, Fallot A, Feder F, Demenois J (2022) A global overview of studies about land management, land-use change, and climate change effects on soil organic carbon. Glob Chang Biol 28:1690–1702. https://doi.org/10.1111/GCB.15998 Bose P (2019) Oil palm plantations vs. shifting cultivation for indigenous peoples: analyzing Mizoram’s new land use policy. Land Use Policy 81:115–123. https://doi.org/10.1016/J. LANDUSEPOL.2018.10.022 Chan KY, Bowman A, Oates A (2001) Oxidizible organic carbon fractions and soil quality changes in an oxic paleustalf under different pasture leys. Soil Sci 166:61–67. https://doi.org/10.1097/ 00010694-200101000-00009 Chapin FS, Matson PA, Vitousek PM (2011) Principles of terrestrial ecosystem ecology, 2nd edn. Springer, New York, NY Don A, Schumacher J, Freibauer A (2011) Impact of tropical land-use change on soil organic carbon stocks—a meta-analysis. Glob Chang Biol 17:1658–1670. https://doi.org/10.1111/j. 1365-2486.2010.02336.x
12
Land Use Change and Its Impacts on Soil Carbon Dynamics in Mizoram,. . .
233
Eyzaguirre PB, Linares OF (2010) Home gardens and agrobiodiversity. In: Smithsonian books, Washington, DC Fontaine S, Barot S, Barré P, Bdioui N, Mary B, Rumpel C (2007) Stability of organic carbon in deep soil layers controlled by fresh carbon supply. Nature 450:277–280. https://doi.org/10. 1038/nature06275 Galhena DH, Freed R, Maredia KM (2013) Home gardens: a promising approach to enhance household food security and wellbeing. Agric Food Secur 2:1–13. https://doi.org/10.1186/20487010-2-8/TABLES/3 Gogoi A, Sahoo UK, Saikia H (2020) Vegetation and ecosystem carbon recovery following shifting cultivation in Mizoram-Manipur-Kachin rainforest eco-region, Southern Asia. Ecol Process 9:1. https://doi.org/10.1186/s13717-020-00225-w Gogoi A, Ahirwal J, Sahoo UK (2021) Plant biodiversity and carbon sequestration potential of the planted forest in Brahmaputra flood plains. J Environ Manag 280:111671. https://doi.org/10. 1016/j.jenvman.2020.111671 Gogoi A, Ahirwal J, Sahoo UK (2022) Evaluation of ecosystem carbon storage in major forest types of eastern Himalaya: implications for carbon sink management. J Environ Manag 302:113972 Guo LB, Gifford RM (2002) Soil carbon stocks and land use change: a meta analysis. Glob Chang Biol 8:345–360. https://doi.org/10.1046/j.1354-1013.2002.00486.x Hnamte L, Lalrammawia C, Gopichand B (2016) Effect of NPK fertilizer on growth and yield of maize under different jhum cycles in Mizoram. Sci Vis 16:59–67 IPCC (2019) Climate change and land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems. https://doi.org/10.4337/9781784710644.00020 ISFR (2021) India state of forest report 2021 (ISFR). Forest Survey of India, Dehradun, p 31 Jeeceelee L, Sahoo UK (2022) Mizo homegardens promote biodiversity conservation, nutritional security and environmental development in Northeast India. Acta Ecol Sin 42:520–528. https:// doi.org/10.1016/J.CHNAES.2021.12.005 Kenye A, Kumar Sahoo U, Lanabir Singh S, Gogoi A (2019) Soil organic carbon stock of different land uses of Mizoram, Northeast India. AIMS Geosci 5:25–40. https://doi.org/10.3934/geosci. 2019.1.25 Khasanah N, van Noordwijk M, Slingerland M, Sofiyudin M, Stomph D, Migeon AF, Hairiah K (2020) Oil palm agroforestry can achieve economic and environmental gains as indicated by multifunctional land equivalent ratios. Front Sustain Food Syst 3:122. https://doi.org/10.3389/ FSUFS.2019.00122 Lal R (2017) Encyclopedia of soil science, 3rd edn. CRC Press, Boca Raton, FL. https://doi.org/10. 1081/E-ESS3 Majumder B, Mandal B, Bandyopadhyay PK (2008) Soil organic carbon pools and productivity in relation to nutrient management in a 20-year-old rice-berseem agroecosystem. Biol Fertil Soils 44:451–461. https://doi.org/10.1007/S00374-007-0226-6/METRICS Mishra G, Francaviglia R (2021) Land uses, altitude and texture effects on soil parameters. A comparative study in two districts of Nagaland, Northeast India. Agric 11:171. https://doi.org/ 10.3390/AGRICULTURE11020171 Mishra G, Sarkar A (2020) Studying the relationship between total organic carbon and soil carbon pools under different land management systems of Garo hills, Meghalaya. J Environ Manag 257:110002. https://doi.org/10.1016/J.JENVMAN.2019.110002 Nair PKR, Kumar BM, Nair VD (2009) Agroforestry as a strategy for carbon sequestration. J Plant Nutr Soil Sci 172:10–23. https://doi.org/10.1002/JPLN.200800030 Nath AJ, Brahma B, Sileshi GW, Das AK (2018) Impact of land use changes on the storage of soil organic carbon in active and recalcitrant pools in a humid tropical region of India. Sci Total Environ 624:908–917. https://doi.org/10.1016/j.scitotenv.2017.12.199 Ontl T, Janowiak M (2017) Grassland and carbon management, glob biogeochem cycles. https:// doi.org/10.1029/2007GB002952
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Rovira P, Vallejo VR (2002) Labile and recalcitrant pools of carbon and nitrogen in organic matter decomposing at different depths in soil: an acid hydrolysis approach. Geoderma 107:109–141. https://doi.org/10.1016/S0016-7061(01)00143-4 Sahoo UK, Singh SL, Gogoi A, Kenye A, Sahoo SS (2019) Active and passive soil organic carbon pools as affected by different land use types in Mizoram, Northeast India. PLoS One 14:1–16. https://doi.org/10.1371/journal.pone.0219969 Sharma SB, Singh SN, Lalruatfela R (2018) Tree diversity and carbon stocks of Hmuifang forest, Mizoram. Int J Res Biosci 7:87–99 Shi L, Feng W, Xu J, Kuzyakov Y (2018) Agroforestry systems: meta-analysis of soil carbon stocks, sequestration processes, and future potentials. L Degrad Dev 29:3886–3897. https://doi. org/10.1002/LDR.3136 Singh SL, Sahoo UK (2015) Soil carbon sequestration in homegardens of different age and size in Aizawl district of Mizoram, Northeast India. NeBIO 6:12–17 Singh SL, Sahoo UK (2021) Tree species composition, diversity and soil organic carbon stock in homegardens and shifting cultivation fallows of Mizoram, Northeast India. Vegetos 34:220– 228. https://doi.org/10.1007/S42535-021-00194-1/METRICS Singh NP, Singh KP, Singh DK (2002) Flora of Mizoram, 1st edn. Botanical Survey of India, Dehradun Singh SL, Sahoo UK, Gogoi A, Kenye A (2018a) Effect of land use changes on carbon stock dynamics in major land use sectors of 1262–1285. https://doi.org/10.4236/jep.2018.912079 Singh SL, Sahoo UK, Gogoi A, Kenye A (2018b) Effect of land use changes on carbon stock dynamics in major land use sectors of Mizoram, Northeast India. J Environ Prot 9:1262–1285. https://doi.org/10.4236/JEP.2018.912079 Singh SL, Sahoo UK, Kenye A, Gogoi A (2018c) Assessment of growth , carbon stock and sequestration potential of oil palm plantations in Mizoram , Northeast India. J Environ Prot 9: 912–931. https://doi.org/10.4236/jep.2018.99057 Smith P (2008) Land use change and soil organic carbon dynamics. Nutr Cycl Agroecosystems 81: 169–178. https://doi.org/10.1007/S10705-007-9138-Y/METRICS Tawnenga US, Tripathi RS (1997) Evaluating second year cropping on jhum fallows in Mizoram, North- Eastern India: soil fertility. J Biosci 22:615–625. https://doi.org/10.1007/BF02703399/ METRICS Thangjam U, Thong P, Sahoo UK, Ahirwal J, Malsawmkima B, Hrahsel L (2022) Tree species diversity in relation to site quality and home gardens types of North-East India. Agrofor Syst 96: 187–204. https://doi.org/10.1007/S10457-021-00715-6/METRICS UIDAI (2022) Unique identification authority of India, Government of India [WWW Document]. https://uidai.gov.in/en/. Accessed 14 Nov 2022 Wapongnungsang, Ovung EY, Upadhyay KK, Tripathi SK (2021) Soil fertility and rice productivity in shifting cultivation: impact of fallow lengths and soil amendments in Lengpui, Mizoram Northeast India. Heliyon 7:e06834. https://doi.org/10.1016/J.HELIYON.2021.E06834 Yinga OE, Kumar KS, Chowlani M, Tripathi SK, Khanduri VP, Singh SK (2020) Influence of landuse pattern on soil quality in a steeply sloped tropical mountainous region, India. Arch Agron Soil Sci 68:852–872. https://doi.org/10.1080/03650340.2020.1858478 Zothansanga D, Beingachhi B (2019) The new land use policy: a panacea for shifting cultivation in Mizoram. Senhri J Multidiscip Stud 4:21–29. https://doi.org/10.36110/sjms.2019.04.01.003
Vegetation and Recalcitrant Soil Carbon Recovery Along an Age Chronosequence of Jhum Fallows in North East India
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Panna Chandra Nath, Arun Jyoti Nath, and Ashesh Kumar Das
Abstract
Jhum (local name for shifting cultivation) is one of the oldest and dominant land uses in North East India. Jhum cultivation is sustainable for efficient resource use if left undisturbed for over 15 years, during which its soil and vegetation can substantially be recovered to their original form (before slashing). However, increased human population pressure coupled with reduced acreage of available land has tremendously reduced the fallow period, adversely affecting soil nutrients storage and stability in the absence of established cover. Further, the reduced fallow period affected the reduction in recalcitrant soil carbon stock and productivity of the soil. Due to the scarcity of work on how successive Jhum fallows can influence vegetation vis-a-vis recalcitrant soil carbon pool, the present study aimed to estimate the (1) rate of vegetation carbon recovery and (2) recalcitrant soil carbon recovery along an age chronosequence of Jhum fallows. The results revealed that tree density increased with an increase in fallow age and vegetation carbon and recalcitrant carbon pools. The natural forest (control) harbored 1075 trees ha-1 with 83.37 Mg ha-1 of recalcitrant soil organic carbon stock. The computed recalcitrant carbon storage under the 1, 2, 5, 8, and 15-year old fallows was 16.37 Mg C ha-1, 17.52 Mg C ha-1, 57.71 Mg C ha-1, 61.46 Mg C ha-1, and 69.67 Mg C ha-1, respectively. No trees were found established up to 2-year-old Jhum fallows. However, tree density at 5-year-old fallows was 310 trees ha-1 and increased to 1060 trees ha-1 after 15 years of abandonment. The study thus recommends retaining a long Jhum fallow period to attain a nearequilibrium recalcitrant soil and vegetation carbon recovery.
P. C. Nath (✉) · A. J. Nath · A. K. Das Department of Ecology and Environmental Science, Assam University, Silchar, Assam, India # The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Mishra et al. (eds.), Soil Carbon Dynamics in Indian Himalayan Region, https://doi.org/10.1007/978-981-99-3303-7_13
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Keywords
Agroforestry · Biomass carbon · Fallow lands · Recalcitrant SC
13.1
Introduction
Shifting cultivation, also called “slash-and-burn agriculture,” “swidden,” and “rotational bush fallow agriculture,” is commonly called “Jhum” in India. It is practiced in the wet tropics and is the oldest farming system globally and still represents the dominant land use in the mountainous regions of South and Southeast Asia (Ramakrishnan 1992; Borah et al. 2018). Practicing Jhum cultivation involves clearing mountainous land by cutting the vegetation (tree or bushes), leaving the biomass in situ for drying, and finally burning it to produce charred material for soil fertility enrichment (Nath et al. 2016; Borah et al. 2018). Shifting cultivation provides subsistence for 200–300 million people across 64 developing countries (Mertz et al. 2009; Li et al. 2014). The system is sustainable, maintains ecosystem balance, and produces a satisfactory yield on a long-term basis, but reduction in the duration of the fallow period, from 20 (Borah et al. 2018) to 3–5 years (Nath et al. 2016), has jeopardized the ecological balance of the age-old system. Moreover, with the ever-increasing population pressure for food and other victuals, the low-productivity land-use system has become a significant threat to the remaining forested areas. The population-driven abrupt decline in the Jhum cycle has aggravated the risks of soil erosion, nutrient loss, and declines in productivity, reduction in biodiversity and essential ecosystem services. Indeed, the shortening of the fallow period has also set in motion the vicious cycle that can lead to irreversible degradation of soil and disintegration of the native ecosystems (Nath et al. 2015). Shifting agriculture is also an integral part of the social customs for the peoples of hill districts of North-East India (NEI) (Borah et al. 2018) and is practiced on 1.5 M ha (Roy et al. 2012). Thus, natural forests are under continuous threat because of new shifting farms. The attendant loss of vegetation and soil organic carbon (SOC) stock and short duration of fallowing also accelerate numerous ecosystem disservices. Therefore, short fallow management can succeed only with the scenario that soil quality can be restored by massive inputs of the above- and below-ground biomass and sequestration of SOC. However, an in-depth understanding is lacking regarding the ecosystem resilience of such a system. Therefore, a fallow age chronosequence was selected from 1 to 15 years old to study whether or not tree species diversity and ecosystem carbon stock can be restored to the equilibrium level comparable to that under the native forest over 15 years. The specific objective of the study was to estimate the (1) rate of vegetation carbon recovery and (2) recalcitrant soil carbon recovery along an age chronosequence of Jhum fallows in the Karbi Anglong district of Assam.
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Materials and Method
Karbi Anglong, the study district, falls under the Himalayan foothills and is one of the hill districts of Assam, NEI. Geographically the district consists of ~76% of its total (10, 434 km2) geographical area under forest cover with average annual rainfall and temperature of 1500 mm and 28.6 °C, respectively (Nath et al. 2021). Moreover, 65% of the total population of the district (9.56 × 105) was supported by 70% of land under shifting cultivation situated on hilly terrains (GoA 2016; Nath et al. 2021). Based on the initial survey and subsequent verification from the landowners, we selected five shifting cultivation fallows: Fallow 1 (shifting fallow 1-year-old), Fallow 2 (shifting fallow 2-year-old), Fallow 5 (shifting fallow 5-year-old), Fallow 8 (shifting fallow 8-year-old), and Fallow 15 (shifting fallow 15-year-old), besides an adjacent natural forest (control) for studying the vegetation and recalcitrant carbon recovery pattern across the sites. To estimate the physiognomic structure, 10 quadrats of 0.1 ha were laid over each age chronosequence of fallow lands and the natural forest (control). All the trees (≥10 cm circumference at breast height) found in the quadrats were counted, and their DBH (diameter at breast height) were measured for the estimation of biomass. All tree species were recorded with their vernacular names and confirmed by Teron and Borthakur (2009) and Nath et al. (2021). To estimate the biomass, we used Nath et al. (2019) equation (AGBest = 0.18D2.16 × 1.32; D is the diameter at breast height), and the default value of 0.47 was used to extract the biomass carbon stock (Andreae and Merlet 2001; McGroddy et al. 2004). All the data collected were subjected to Shapiro–Wilk and Levene’s test for the homogeneity of variances. The impact of fallow age chronosequence was tested from the means values compared using least significance difference (LSD). Tukey’s honestly significant difference (HSD) was used to compare the means at 0.05 level. Tree density within the laid quadrats was multiplied with a multiplication factor of 10 to extrapolate the data on a per hectare basis. The tree density of each species was multiplied by the biomass carbon content of the concerned species to obtain the biomass carbon content in megagram (Mg) per hectare. Fallow age chronosequences and the control site were evaluated for the diversity using the Shannon–Wiener diversity index (Shannon and Weaver 1963) and species richness (Margalef 1958). Composite and core soil samples were collected from 0 to 100 cm soil profile from each laid quadrat. Collected soil samples were processed for bulk density and soil organic carbon (SOC) estimation following Al-Shammary et al. (2018) and Nath et al. (2022), respectively. SOC and SOC pools (i.e., carbon under active and passive pools) were estimated using the wet combustion method (Walkley and Black 1934) and modified Walkley and Black method (Chan et al. 2001). For calculation of the recovery rate (increment) of vegetation and soil carbon, Fallow 1 was considered as the base year from which the subsequent increment was measured. Recalcitrant SC stock of Fallow 1 was subtracted from the subsequent fallows to get the actual stock during the fallowing period, and the annual recovery rate was measured using the following formula:
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Annual increment =
ContentðFÞ - ContentðIÞ Age of the system
ð1Þ
where F is the final year whose increment is to be calculated; I is the initial studied year from which the difference is to be calculated.
13.3
Results
Nearly 20–30% of the shifting fallows in the Karbi Anglong district were reported by the farmers to have an abandonment period of ≥15 years. In sustenance of the growing demand for an increase in population, the fallow period has drastically reduced to almost 5 years in maximum cases as reported by the land use owners. In the present study, no outgrowth of trees had been observed for the fallow 1 and 2 years. However, the same was observed to have outgrowth of tree saplings as soon as the land was abandoned after cultivation. Tree species diversity, richness, and the total number of species were found in the range of 0.93–2.01, 0.61–1.92, and 4–31, respectively, for the Fallow 5, 8, and 15 years. The control site (natural forest) had the highest diversity (3.71), richness (5.25), and per hectare the total number of tree species (63) (Fig. 13.1).
Fig. 13.1 Diversity of tree species at age chronosequence and land use transition from natural forest to shifting fallow. Fallow 1–15 (shifting fallow 1–15 years of age)
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Tree density (stems ha–1)
1400 1200
R2 = 0.973 Adj.R2 = 0.963
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F value = 96.081 p < 0.001
1000 800 600 400 200 0
0
0 Fallow 1
Fallow 2
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a Fallow 15
Control & Land use chronosequence
a Natural forest
Fig. 13.2 Tree density at age chronosequence and land use transition comparing natural forest (control) to shifting fallow. Fallow 1–15 (shifting fallow 1–15 years of age); different letters represent significant mean difference at 0.05 level as per LSD test
In the absence of any trees, the density remained 0 (zero) at 1- and 2-year-old fallows; however, with an increase in the age of the fallow, the tree density had increased to 1060 trees ha-1, which was near equivalent to the tree density of the natural forest (1075 trees ha-1). The least tree density was observed in the Fallow 5 (310 trees ha-1) and had a significant positive increment with the increase in age of the fallow period (R2 = 0.97, Adj. R2 = 0.96). The mean tree density represented a significant difference with the increase in the age of the fallow lands up to fallow 15 (F value = 96.08, p < 0.001) (Fig. 13.2). At the control site, the SOC was found to be 130.01 Mg ha-1, and it ranged between 94.92 and 126.98 Mg ha-1 at Fallow 1–15 years of age, provided the least was at the Fallow 1. The recalcitrant soil organic carbon was estimated at 83.37 Mg ha-1 at the control site. The highest (69.67 Mg ha-1) and the lowest (16.37 Mg ha-1) recalcitrant soil organic carbon was respectively found at Fallow 15 and Fallow 1. The SOC and recalcitrant soil organic carbon showed a significant shift of increment toward that contained in the control site with the increase in the fallow age (F value = 1038.28, p < 0.001) (Fig. 13.3). Fallow 1 represented 0 (zero) increment in tree recovery, vegetation carbon, SOC, and recalcitrant carbon. Fallow 15 and Fallow 5 represented the highest (151 stems ha-1) and the lowest (62 stems ha-1) tree density recovery. Vegetation carbon and recalcitrant soil carbon increments were observed within the range of 6.0–11.4 Mg ha-1 year-1 and 0.6–8.2 Mg ha-1 year-1, respectively, with fallow 5 having significantly the highest increment (F value = 57.65 and 58.76 respectively, p < 0.0001). Significantly, the highest (8.2 Mg ha-1 year-1) and lowest
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Soil organic carbon stock (Mg ha–1)
240 140 Active SC
Recalcitrant SC
120 100
c
80
b
b
a
60 40 d
d
20 0 Fallow 1
a
c
c
b
d
Fallow 2
Fallow 5
Fallow 8
Fallow 15
Natural forest
Control & Land use chronosequence
Fig. 13.3 Distribution of active (F value = 1038.282, p < 0.001) and recalcitrant (F value = 229.328, p < 0.001) soil carbon at age choronosequence and land use transition comparing natural forest (control) to shifting fallow. Fallow 1–15 (shifting fallow 1–15 years of age); SC (soil organic carbon); different letters under same color regime (each carbon pool) represent significant mean difference at 0.05 level as per Tukey’s HSD test Table 13.1 Rate of trees and recalcitrant soil carbon recovery along age chronosequence of Jhum fallow Land use Fallow 1 Fallow 2 Fallow 5 Fallow 8 Fallow 15 F value P value
Tree recovery (Stems hayear-1) 0 (0)a
Vegetation carbon (Mg ha-1 year-1) 0 (0)a
Recalcitrant SC (Mg ha1 year-1) 0 (0)a
0 (0)a
0 (0)a
0.6 (0.2)a
62 (5)c
6.0 (1.0)b
8.2 (1.5)c
145 (7)b
11.4 (1.9)c
5.6 (0.5)b
151 (14)b
6.2 (1.2)b
3.6 (0.3)b
362.18 35%), intermediate (15% > CV 35%) and low (CV < 15%). Our findings from the CV analysis suggest that SOC has a semi-homogeneous geographical distribution, which may be related to variations in the research area’s topography, farming and management methods and land use. A soil property like SOC is a stochastic variable supported by the continuation of the soil formation processes and the change in the climate, as demonstrated by Jena et al. (2022) and Moharana et al. (2022). As a result, it is essential to use contemporary statistical procedures to survey the geographical variability in SOC. In the calibration and validation data sets, the frequency distribution of the SOC concentrations is shown in Fig. 18.2. Histograms and probability densities are displayed using bars and curves, respectively. The locations of the particular sample sites along the SOC content range are displayed on the rug plots’ X-axis. The SOC content values appear to follow a normal distribution, as seen by their bell-shaped distribution. The distribution was not made more normal by the transformations (log and square root). As a result, the prediction models were fitted using the original SOC values. In addition, unlike the traditional regression models used in this work, the machine learning model did not require the data to have a normal distribution. Before fitting the predictive models to the observed data, a test of spatial autocorrelation was carried out using the Global Moran’s I test to prevent the problems
n 850 595 255
Minimum 0.190 0.270 0.190
Maximum 4.910 4.910 4.210
Mean 2.188 2.206 2.143
SD standard deviation, SE standard error, CV coefficient of variation
Data set Total Calibration Validation
SE 0.032 0.037 0.058
Median 2.040 2.060 2.040
Table 18.2 Descriptive statistics of soil organic carbon in the northeast Himalayan region of India SD 0.920 0.914 0.932
CV 42.039 41.444 43.476
Skewness 0.275 0.325 0.171
Kurtosis -0.638 -0.612 -0.717
18 Digital Mapping of Soil Organic Carbon Using Legacy Data in the. . . 331
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Fig. 18.2 Soil organic carbon (SOC) content distribution in the calibration and validation data set as represented by the histogram, density plot and rug plot. Vertical dashed lines represent the mean values
associated with spatial autocorrelation (Moran 1950). Significant spatial autocorrelation was not present in the geographical pattern. Figure 18.3 displays the linear correlations between SOC and the predictor factors. Elev and CNBL both had favourable correlations with SOC (r = 0.44 and 0.46, respectively). Previous studies have shown a relationship between vegetation, topographic factors and the amount of SOC (Moharana et al. 2022). Topographic factors affect the composition of SOC, vegetation cover, soil characteristics and water retention. In the research area, there was a low association between the aspect and SOC (r = 0.04). This was similar to the result of investigations by Lamichhane et al. (2021) and Mahmoudzadeh et al. (2020). Emadi et al. (2020) earlier noted the positive connection of SOC with CNBL and elevation in our investigation. Our findings also showed a negative association between SOC and the TWI, which was
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Fig. 18.3 Correlation analysis between covariates and organic carbon in the study area of the northeast Himalayan region of India
in contrast to the findings of Schwanghart and Jarmer (2011), but similar to those of Falahatkar et al. (2016). This unfavourable outcome could have been caused by the high vegetation density and low TWI at the high-elevation regions with little human activity (Falahatkar et al., 2016). The research of Li (2010) has demonstrated the substantial relationships of topography characteristics with SOC (elevation r = 0.46, slope r = 0.43 and TWI r = 0.20).
18.4.2 Evaluation of Prediction Models By computing statistical measures such as the coefficient of determination (R2), Lin’s concordance correlation coefficient (CCC), mean error (ME) and root mean square error, the performance of the MLR, RF and cubist models was assessed
334 Table 18.3 Goodness-offit and error statistics of model for predicting soil organic carbon in the study area of the northeast Himalayan region of India
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Model MLR RF Cubist
Data set Calibration Validation Calibration Validation Calibration Validation
R2 0.256 0.230 0.935 0.305 0.265 0.218
CCC 0.407 0.365 0.910 0.498 0.448 0.396
RMSE 0.788 0.818 0.332 0.834 0.786 0.829
ME 0.001 0.062 0.002 0.103 0.012 0.067
Fig. 18.4 Predicted vs. observed parameters of soil organic carbon by various models in the study area of the northeast Himalayan region of India
(RMSE). Table 18.3 displays the statistics for the prediction models’ goodness-of-fit and errors employed in this investigation. The observed and predicted SOC concentrations for each of the three models are shown in Fig. 18.4. With R2cal = 0.935 and R2val = 0.305, the RF model produced the best prediction results, closely followed by the MLR, which had R2cal = 0.256 and R2val = 0.230. In comparison with previous models, the RF model has lower RMSE and mean absolute error (MAE). The RF model has the best ability to predict SOC in India’s northeastern Himalayas. The CCC value of 0.498 was seen in the RF model, overall in the validation data set, suggesting high agreement between the predicted and observed values. The average ME values were quite near to zero, which suggests that overall forecasts were impartial. Figure 18.4 further supports the efficacy of the RF models by demonstrating a moderate correlation between the anticipated and measured K percentages. Because the RF is a more reliable technique than the MLR, these data show that RF performed somewhat better than the MLR and cubist. These findings generally concur with those of da Chagas et al. (2016) and Pahlavan-Rad et al. (2020), who found that the RF was superior to the MLR for predicting clay, sand, infiltration and soil organic carbon. Due to the data-driven nature of the RF and MLR, discrepancies between the current findings and those of earlier research may be attributed to the interaction of local agricultural practises, soil type and climate. The findings from the previous publications suggest that accuracy plots can aid in
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visualising the efficacy of local uncertainty prediction and that traditional error measures may be deceptive. The accuracy of the RF, MLR and cubist models based on error matrices has not been compared in any studies to our knowledge. Although further research is necessary to determine the causes of this present trend, it may have something to do with the fact that, unlike the RF, the MLR performs a linear fitting after partitioning the data according to a predetermined criterion. The values centred on the mean were overestimated by both the cubist and MLR models, while the lower and higher values of the various soil attributes were underestimated. This supports past research that showed machine learning models like the cubist and random forest tended to overestimate low values and underestimate high values (Mahmoudzadeh et al. 2020). The intricacy of soil property fluctuations and soil formation conditions in the particular topography is demonstrated by the comparatively high RMSE values in this study. The discrepancy between the RMSE values for the training and validation sets shows that the analysed attributes were overstated by the MLR and cubist models.
18.4.3 Importance of Environmental Variables CNBL, LDC, LS, NDVI, Slp, TRI and VD were the covariates in the MLR model that were most important for predicting OC using the stepwise model, whereas other covariates were removed (Table 18.4). The comparative relative variable importance plots given in Figure 18.5 show that the RF chose more variables than the MLR and cubist models did. One of the primary benefits of the RF model over the MLR model is that the former provides an assessment of the relative relevance of the covariates in the model, in contrast to the MLR model, which maintains the model through stepwise selection only with highly correlated predictive variables (Chagas et al. 2016). Even though there may be relationships between the predictive variables and soil, the RF model avoids removing them (Akpa et al., 2014). The order of the most crucial factors in the RF model for predicting OC was CNBL > elevation > VD > StH > RSP. The most crucial variables for using the cubist model to predict the variance of OC were CNBL, TRI, Slp, RSP, LS and elevation. In a study conducted in the Zehak County in this region, Pahlavan-Rad and Akbarimoghaddam (2018) discovered that the CNBL and elevation were the most crucial covariates for the prediction of soil qualities. The CNBL was the most significant factor for OC prediction for both the RF and cubist models, followed by the other topography and vegetation factors. In the Himalayan region, gravitational potential energy gradients Table 18.4 Results of the stepwise multiple linear regression models relating soil organic carbon to environmental covariates Parameters OC
Significant predictors -0.236 + 0.00191 × CNBL +0.104007 × LDC-0.03483 × LS + 1.61030 × NDVI +1.64460 × Slp-0.037727 × TRI + 0.00122 × VD
Intercept Significant
pValue 2.2e16
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Fig. 18.5 Importance variables in predicting soil organic carbon by various models in the study area of the northeastern Himalayan region of India
in the terrain cause soil sediments to flow and gather in lower elevation regions. Elements are transported by these topography-driven erosional processes from higher elevations, where OC concentrations are often lower, to lower elevations, where OC concentrations are typically higher (Jena et al. 2022).
18.4.4 Spatial Prediction of SOC Large discrepancies between the forecasts are shown in Fig. 18.6, which depicts the spatial predictions of OC made by various models. Although the two models’
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Fig. 18.6 Distribution of soil organic carbon predicted by various models in the study area of the northeastern Himalayan region of India
cross-validation accuracy metrics were comparable, the RF model forecasts more closely matched the spatial pattern of OC we anticipated in the research area. The OC in the research area appears to be underestimated by the MLR forecasts. All of the maps for the prediction models displayed abrupt and gradual shifts throughout the research region. In the MLR, RF, and cubist models, the predicted OC ranged from 0.79 to 3.79%, 0.86 to 3.80% and 0.038 to 3.261%, respectively. It is impossible to decide which model is the most accurate without independently confirming these predictions; however, we selected the RF model as the best because the cross-validation accuracy metrics were similar and the spatial forecasts visually matched our perception of the terrain. The spatial patterns of SOC in all models are reasonable, with large values in the study area’s western region, which is dominated by forest and covered in dense vegetation, and with minor values in its eastern regions, which have soils subject to significant erosion and shifting cultivation. In the Himalayan condition, low-elevation cultivable fields appear to be more uncertain than high-elevation cultivable lands. This can be explained by the variation in the management techniques used on the more intensively farmed regions (Jena et al. 2022). The covariates used in these predictive models may not have adequately accounted for the management aspects that may have contributed to the spatial heterogeneity in SOC content levels in these downstream farmed regions. The high-elevation areas are less actively farmed, which may have less impact due to management and because the terrain features have a stronger hold over them. SOC concentrations are the outcome of the balance between carbon imports and outputs in
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soils; a number of variables, including local characteristics like vegetation and topography and environmental conditions, affect this equilibrium (Sahoo et al. 2019). According to Pahlavan-Rad et al. (2020), topography was the most significant covariate influencing the distribution of SOC in our study.
18.5
Conclusion
A lot of work has been done in the past to increase the accuracy of SOC assessment using statistical techniques because soil organic carbon is one of the most crucial soil characteristics. In the northeastern Himalayan area of India, this study examined SOC fluctuations with a spatial precision of 30 m. In comparison with the other ML algorithms examined, the RF model demonstrated the best performance in forecasting SOC at the regional level. However, given that the MLR, RF, and cubist models all perform similarly, we advise that all the three models be calibrated before using the best results to forecast target soil properties spatially in different geographical contexts. Based on the validation samples, the RF had better R2 and RMSE values for the prediction of OC than did the MLR and cubist. The accurate prediction of regional variation of OC at both a national scale and a detailed level depends on the integration of RF approaches with currently known high-resolution soil formative environmental variables. In general, many soil and environmental experts and land managers in the northeastern Himalayan region find value in fine-resolution soil maps. As a result, given that the agroecological zone varies considerably throughout the northeastern Himalayan region of India, we advise using the comparison approach used in this study area to map the SOC in other regions of India.
References Akpa SI, Odeh IO, Bishop TF, Hartemink AE (2014) Digital mapping of soil particle-size fractions for Nigeria. Soil Sci Soc Am J 78:1953–1966 Arrouays D, Grundy MG, Hartemink AE et al (2014) Global Soil Map: toward a fine-resolution global grid of soil properties. Adv Agron 125:93–134 Ben-Dor E (2002) Quantitative remote sensing of soil properties. In: Advances in agronomy. Academic, Cambridge, MA, pp 173–243 Bray RH, Kurtz LT (1945) Determination of total, organic, and available forms of phosphorus in soils. Soil Sci 59:39–46 Breiman L (2001) Random forests. Mach Learn 45:5–32 da Chagas CS, de Carvalho Junior W, Bhering SB, Calderano Filho B (2016) Spatial prediction of soil surface texture in a semiarid region using random forest and multiple linear regressions. Catena 139:232–240. https://doi.org/10.1016/j.catena.2016.01.001 Dharumarajan S, Hegde R, Janani N, Singh SK (2019) The need for digital soil mapping in India. Geoderma Reg 16:e00204 Dokuchaev VV (1883) Russian Chernozems (Russkii Chernozems). In: Israel program for scientific translations, Jerusalem, translation from Russian by N. Kaner (1967). US Department of Commerce, Springfield, VA
18
Digital Mapping of Soil Organic Carbon Using Legacy Data in the. . .
339
Emadi M, Taghizadeh-Mehrjardi R, Cherati A, Danesh M, Mosavi A, Scholten T (2020) Predicting and mapping of soil organic carbon using machine learning algorithms in Northern Iran. Remote Sens 12:2234. https://doi.org/10.3390/rs12142234 Falahatkar S, Hosseini SM, Ayoubi S, Salmanmahiny A (2016) Predicting soil organic carbon density using auxiliary environmental variables in northern Iran. Arch Agron Soil Sci 62:375– 393 FAO, ITPS (2020) Global soil organic carbon map V1.5. Technical report. FAO, Rome Grimm R, Behrens T, Marker M, Elsenbeer H (2008) Soil organic carbon concentrations and stocks on Barro Colorado island-digital soil mapping using random forests analysis. Geoderma 146:102–113 Guo P-T, Li M-F, Luo W et al (2015) Digital mapping of soil organic matter for rubber plantation at regional scale: an application of random forest plus residuals kriging approach. Geoderma 237– 238:49–59. https://doi.org/10.1016/j.geoderma.2014.08.009 Hanway JJ, Heidel H (1952) Soil analysis methods as used in Iowa state college soil testing laboratory. Iowa Agric 54:1–31 Hartemink AE, Hempel J, Lagacherie P et al (2010) Global soil map. Net–a new digital soil map of the world. In: Digital soil mapping. Springer, Cham, pp 423–428 Hengl T, de Jesus JM, Mac Millan RA et al (2014) Soil grids 1 km—global soil information based on automated mapping. PLoS One 9:e105992 Hengl T, Heuvelink GB, Kempen B et al (2015) Mapping soil properties of Africa at 250 m resolution: random forests significantly improve current predictions. PLoS One 10:e0125814 Jackson ML (1973) Soil chemical analysis. Prentice Hall of India Private Limited, New Delhi Jena RK, Bandyopadhyay S, Pradhan UK et al (2022) Geospatial modelling for delineation of crop management zones using local terrain attributes and soil properties. Remote Sens 14:2101 Jenny H (1941) Factors of soil formation, vol 52. McGraw Hill, New York, p 415 Lagacherie P, Baret F, Feret J-B et al (2008) Estimation of soil clay and calcium carbonate using laboratory, field and airborne hyperspectral measurements. Remote Sens Environ 112:825–835 Lal R (2009) Challenges and opportunities in soil organic matter research. Eur J Soil Sci 60:158– 169 Lamichhane S, Adhikari K, Kumar L (2021) Use of multi-seasonal satellite images to predict SOC from cultivated lands in a montane ecosystem. Remote Sens 13:4772 Li Y (2010) Can the spatial prediction of soil organic matter contents at various sampling scales be improved by using regression kriging with auxiliary information? Geoderma 159:63–75 Liaw A, Wiener M (2002) Classification and regression by random forest. R News 2:18–22 Lin LI (1989) A concordance correlation coefficient to evaluate reproducibility. Biometrics 45:255– 268 Lindsay WL, Norvell WA (1978) Development of a DTPA soil test for zinc, iron, manganese, and copper. Soil Sci Soc Am J 42:421–428 Liu F, Zhang G-L, Song X et al (2020) High-resolution and three-dimensional mapping of soil texture of China. Geoderma 361:114061 Mahmoudzadeh H, Matinfar HR, Taghizadeh-Mehrjardi R, Kerry R (2020) Spatial prediction of soil organic carbon using machine learning techniques in western Iran. Geoderma Reg 21: e00260 McBratney AB, Santos MM, Minasny B (2003) On digital soil mapping. Geoderma 117:3–52 Mikkonen HG, van de Graaff R, Clarke BO et al (2018) Geochemical indices and regression tree models for estimation of ambient background concentrations of copper, chromium, nickel and zinc in soil. Chemosphere 210:193–203 Minasny B, Hartemink AE (2011) Predicting soil properties in the tropics. Earth Sci Rev 106:52–62 Minasny B, McBratney AB, Malone BP, Wheeler I (2013) Digital mapping of soil carbon. Adv Agron 118:1–47 Mishra G, Giri K, Jangir A, Francaviglia R (2020) Projected trends of soil organic carbon stocks in Meghalaya state of Northeast Himalayas, India. Implications for a policy perspective. Sci Total Environ 698:134266
340
P. C. Moharana et al.
Moharana PC, Dharumarajan S, Kumar N et al (2022) Modelling and prediction of soil organic carbon using digital soil mapping in the Thar Desert region of India. J Indian Soc Soil Sci 70: 86–96 Moran PA (1950) Notes on continuous stochastic phenomena. Biometrika 37:17–23 Mulder VL, De Bruin S, Schaepman ME, Mayr TR (2011) The use of remote sensing in soil and terrain mapping—a review. Geoderma 162:1–19 Niang MA, Nolin MC, Jégo G, Perron I (2014) Digital mapping of soil texture using RADARSAT2 polarimetric synthetic aperture radar data. Soil Sci Soc Am J 78:673–684 Pahlavan-Rad MR, Akbarimoghaddam A (2018) Spatial variability of soil texture fractions and pH in a flood plain (case study from eastern Iran). Catena 160:275–281 Pahlavan-Rad MR, Dahmardeh K, Hadizadeh M et al (2020) Prediction of soil water infiltration using multiple linear regression and random forest in a dry flood plain, eastern Iran. Catena 194: 104715 Prasad AM, Iverson LR, Liaw A (2006) Newer classification and regression tree techniques: bagging and random forests for ecological prediction. Ecosystems 9:181–199 R Core Team (2019) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. http://www R-project org/ Ratnayake RR, Karunaratne SB, Lessels JS et al (2016) Digital soil mapping of organic carbon concentration in paddy growing soils of Northern Sri Lanka. Geoderma Reg 7:167–176 Sahoo UK, Singh SL, Gogoi A et al (2019) Active and passive soil organic carbon pools as affected by different land use types in Mizoram, Northeast India. PLoS One 14:e0219969 Sanchez PA, Ahamed S, Carré F et al (2009) Digital soil map of the world. Science 325:680–681 Schwanghart W, Jarmer T (2011) Linking spatial patterns of soil organic carbon to topography—a case study from South-Eastern Spain. Geomorphology 126:252–263 Soil Survey Staff (1999) Soil taxonomy. A basic system of soil classification for making and interpreting soil surveys, 2nd edn. USDA, US Government Print Office, Washington, DC Subbiah BV, Asija GL (1956) A rapid procedure for the estimation of available nitrogen in soils. Curr Sci 25:259–260 Taghizadeh-Mehrjardi R, Minasny B, Sarmadian F, Malone BP (2014) Digital mapping of soil salinity in Ardakan region, Central Iran. Geoderma 213:15–28 Taghizadeh-Mehrjardi R, Nabiollahi K, Kerry R (2016) Digital mapping of soil organic carbon at multiple depths using different data mining techniques in Baneh region, Iran. Geoderma 266: 98–110 Walkley A, Black IA (1934) An examination of the Degtjareff method for determining soil organic matter, and a proposed modification of the chromic acid titration method. Soil Sci 37:29–38 Wilding LP, Dress LR (1983) Spatial variability and pedology. In: Pedogenesis and soil taxonamy: concepts and interactions. Elsevier, Amsterdam, pp 83–166 Zhao M-S, Rossiter DG, Li D-C et al (2014) Mapping soil organic matter in low-relief areas based on land surface diurnal temperature difference and a vegetation index. Ecol Indic 39:120–133
Advanced Techniques in Estimating Soil Erosion and Associated Carbon Loss in the Himalayan Region
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Suresh Kumar, K. R. Sooryamol, Anu David Raj, Justin George Kalambukattu, and Sankar Mariappan
Abstract
Soil erosion (SE) is a major concern for ecosystem services and food security for the global community. Climate change, unsustainable land management practices, abandoning cultivable agricultural land, deforestation, and steep slope are the prime factors that worsen the soil erosion status. Soil erosion and associated carbon (C) loss is one of the prime threats for sustainability of hilly and mountainous terrain. Identification, monitoring, and quantification of soil erosion are highly required for sustainable management of hilly and mountainous ecosystem. Advanced techniques such as process-based erosion models and radiotracer-based environmental markers provide a deep insight into the soil erosion and associated carbon loss from a landscape. Nowadays, remote sensing (RS) and geographic information system (GIS) techniques aid in developing better understanding and synoptic coverage of inaccessible hilly and mountainous terrain with economically viable route. Integrated multidimensional approaches using advanced techniques could provide sustainability in hilly and mountainous environment with minimum degradation. In this perspective, various advanced techniques to estimate soil erosion and associated carbon loss will be the core of discussion in this chapter. S. Kumar (✉) Agriculture, Forestry and Ecology Group, Indian Institute of Remote Sensing, Indian Space Research Organization (ISRO), Dehradun, Uttarakhand, India e-mail: [email protected] K. R. Sooryamol · S. Mariappan Indian Institute of Soil and Water Conservation (ICAR-IISWC), Dehradun, Uttarakhand, India A. David Raj · J. G. Kalambukattu Agriculture and Soils Department, Indian Institute of Remote Sensing, Indian Space Research Organization (ISRO) , Dehradun, Uttarakhand, India e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Mishra et al. (eds.), Soil Carbon Dynamics in Indian Himalayan Region, https://doi.org/10.1007/978-981-99-3303-7_19
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Keywords
Soil erosion and sediment loss modelling · Enrichment ratio · Soil carbon loss · Radio-isotopes methods (137 Caesium) · Climate change · Himalayan region
19.1
Introduction
Soil is a dynamic, multifunctional, and nonrenewable resource, which is under the threat of erosion for a long time, and has reached a critical limit for ecosystem services around the world. Reports on world population growth indicate the significance of the term food security, because maintaining and augmenting adequate food supply depend on productive land. Over the centuries, people have modified large areas of the natural landscape for agricultural purposes, settlements, livestock activities, and developmental processes. However, the consequences of overexploitation of soil resources resulted in soil erosion, land degradation, productivity loss of all natural ecosystems, and decreased food security. Soil erosion by water/wind, deterioration of soil quality, and continued loss of natural vegetation are the major processes that cause land degradation, whose costs range from 40 to US$490 billion globally (Sartori et al. 2019). The soil erosion process begins with the detachment of soil particles by the generation of surface runoff that is followed by transportation and deposition within the landscape or in the streams. The spatial extent of erosion causes various on-site and off-site problems. All these processes are influenced by multiple factors such as the intensity of rainfall, soil properties, slope variations, ground cover, transit capability of eroding agent, and runoff velocity. Regions susceptible to erosion are situated across the arid, semiarid, and subhumid regions, as well as agricultural lands and mountainous terrains including the Himalayan region. Among the 15% of the degraded land around the world, the highest was reported from Asia (37%). India is one of the tropical countries that have extreme soil erosion rates with an average soil loss of 16.4 tha-1 yr-1 (Dhruvanarayana and Babu 1983). However, the tolerable erosion rate is 4.5–11.2 tha-1, and 39% of the area is under an erosion rate higher than 10 tha-1 yr-1. About 53% of the total geographical area in India is under the threat of slight to severe soil erosion and other forms of land degradation. Estimated values of land degradation in the country range from 53 to 188 Mha. According to a recent analysis by Bhattacharyya et al. (2015), around 147 Mha of land in India has degraded soil. By restoring 26 Mha of damaged land in 2030, India hopes to achieve land degradation neutrality as part of the Fourteenth Meeting of the Conference of Parties (COP14). Erosion intensity is one of the factors that cause approximately 5–50% of productivity loss. The amount of soil nutrients lost due to erosion ranges from 5.37 to 8.40 million tonnes, which reduces the supply of food grain by 30–40 million tonnes annually. The productivity loss of major rainfed crops such as cereals, oilseeds, and pulses in the country accounts for about 111.3 billion in terms of money (Kar et al. 2022). According to Food and Agriculture Organization (2017), soil erosion in agricultural lands could result in a financial loss
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of US$400 billion annually. Continuous decline or loss of soil productivity can cause land abandonment and desertification. The Himalayan regions are geologically unstable, young, and highly prone to soil erosion. The conversion of natural slopes into gentle slopes and agricultural terraces was the traditional farming system in the Himalayas. The topography of this region is a controlling factor in the soil erosion process. The direct proportionality of soil loss and slope steepness on cultivated and uncultivated soil is the best example, even though the effect is more visible on cultivated land. However, the lack of proper maintenance of land, slope degradation, and intensive tillage practices ultimately resulted in accelerated soil erosion, landslide vulnerability, soil organic carbon (SOC) loss, and land degradation with the changing climate scenarios. Nearly 39% area of the Indian Himalayan region (IHR) had an erosion of more than 40 t ha-1 yr-1 (Mandal and Sharda 2011). In the northeastern Himalayas, approximately 3.0 Mha of land is severely affected by erosion due to shifting cultivation of the total degraded lands (4.60Mha). An average of 17% of the northwestern Himalayas exceeds the erosion rates of 40 tha-1 yr-1. Singh and Gupta (1982) reported that the annual soil loss from the Himalayas is 28.2 t ha-1 yr-1. Mandal and Sharda (2011) estimated that the critical tolerance limit of the Indian Himalayas is 12.5 Mg ha-1 yr-1. Soil and parent material in the lower Shivalik Hills (Uttarakhand) of northern India is vulnerable to runoff associated with the torrential monsoonal rainfall, contributing to higher sediments production by landslips and breaking down of field bunds and terraces due to oversaturation of side slope and riser of terraced fields. Approximately 25% of the dissolved load deposited into the world’s oceans due to erosion is transported from the Himalayan and Tibetan Region. Increased runoff from the land surface reduces the water storage capacity and infiltration ability of the soil. Loss of nutrient-rich topsoil results in the decline in essential plant nutrients, organic matter, and thus the soil depth. Removal, redistribution, and deposition of soil organic carbon along with soil cause an imbalance between stored soil organic carbon and carbon input in a region. Studies on the erosion from the Himalayan region revealed that its deposition at Bengal Fan acts as a net global carbon sink (Galy et al. 2007). The deposition of eroded sediment is the key factor of off-site problems such as siltation and sedimentation in the rivers and reservoirs, eutrophication, water quality deterioration, and risk for the aquatic life systems. Degraded soils can no longer support the natural growth and the presence of soil biota until they are restored.
19.2
Soil Erosion
Soil erosion is the process of removal of soil particles due to the erosive power of rainfall and runoff. It removes nutrient-rich fertile topsoil; thus, it is considered as a major environmental, social, and economic threat around the globe. Soil erosion induced by water is considered as the major form of erosive agent in most areas around the world. Hilly and mountainous terrains are highly affected by water
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erosion. Various erosion-causing factors like rainfall, runoff, and processes including detachment, transport, and deposition are discussed in this section.
19.2.1 Processes and Factors The process of soil erosion is triggered as a consequence of water in the form of rain splash or surface runoff. Both these agents have enough potential to remove soil particles. Consequently, soil erosion by water is associated with rainfall events. Due to the energy of rainfall, soil particles detach from one place to another; eventually, surface runoff or flow detaches and transports the soil particles. Therefore, the process of soil erosion can be considered as a two-stage process, that is, detachment and transportation. However, one more phase deposition is also associated with them, depending on the transportation potential of the agents involved in removal of soil (Morgan 2005). Primarily, the kinetic and potential energy of raindrop and runoff is governing the soil erosion process. Indeed, soil hydrology also plays a major role in determining the soil erosion process and associated other processes. The hydrological processes such as infiltration, saturation, and hydraulic conductivity play a role in generating water flow and surface runoff, which depends upon the type of soil textural class; sandy soils have higher infiltration followed by silt and clay. However, clay soil can store more water compared with sandy soils. Mechanism of generating runoff is described by Horton (1945), who stated that, if the rainfall intensity is higher than the infiltration capacity, then surface runoff will occur (called infiltration excess runoff). Accordingly, if the soil gets saturated and then the runoff happens, it is referred as saturation excess runoff. There are various forms of soil erosion such as splash, sheet, rill, and gully, which indicate advancing erosive processes as the amount of rainfall gets increased. The momentum of rainfall (rain drop) causes the splash erosion or soil particles to remove. The energy required to remove soil from its original location depends upon the geometric size and mass of the soil particles. As the rainfall increases, it forms sheets of flow and soil also gets removed or transported through this flow. The runoff water flows into small depressions in the surface and generates rills in the surface, while the small rills advance to form small to large gullies. They can transport huge mass of soil through these continuous depressions. The occurrence of various soil erosion processes is controlled by erosiongoverning factors. In case of water erosion (soil erosion through water), water (raindrop and runoff) is considered as the primary driving factor of soil erosion. This factor is termed as rainfall erosivity factor that depends on the amount and intensity of rainfall. Apart from rainfall, surface runoff also has the capability to detach and transport the soil particles. Soils have an inherent capacity to resist the physical damage exerted on the soil, called soil erodibility. Hence, it is defined as the resistivity of the soil to detach or transport. The erodibility depends on infiltration capacity, organic matter content, aggregate stability, and soil texture. The presence of higher organic contents in soil exhibits higher aggregate stability and higher resistance to soil erosion. Topography is another important factor that controls the
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spatial variation of soil erosion. Thus, especially in hilly and mountainous terrains, soil erosion has emerged as a major environmental concern. Slope steepness is the major topographical factor affecting soil erosion. The erosion would normally be expected to increase as the slope increases and vice versa, because the slope determines the velocity of surface runoff or transport of soil mass. The effects of vegetation cover are another important erosion controlling factor that can regulate hazardous erosion. Vegetation acts as a buffer/ protective layer between the atmosphere and soil. The aboveground biomass such as leaf and stems absorbs and dissipates the energy of falling raindrop. In addition, belowground biomass such as root also prevents the removal of soil particles from surface layers. Apart from this, artificial conservation practices such as bench terraces, contour farming, mulching, and check dams reduce soil erosion and massive soil movement due to rainfall. The upcoming section (Sect. 19.2.4) will provide more insights into soil and water conservation measures.
19.2.2 Erosion and Deposition Processes Erosion and deposition are on-site and off-site consequences of soil erosion process (Figs. 19.1 and 19.2). This process is depending upon the erosive power of the agent (water) and the topographical characteristics. Soil redistribution is the term used to represent both the processes. Indeed, some places can reach equilibrium of soil
Fig. 19.1 Process of soil redistribution (erosion, deposition, and net and gross erosion) and soil carbon movement in a typical hillslope
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Fig. 19.2 (a) On-site (severely eroded hillslope) and (b) off-site (deposition in reservoir) effects of soil erosion processes Fig. 19.3 Erosion and deposition from a typical hillslope—A valley region in Harsil, Uttarakhand, India Eroded hillslope
Sediment deposition
erosion and deposition process. The concept of soil redistribution provides the idea about eroded, noneroded, deposition or equilibrium spots/location of a watershed/ catchment. A typical hillslope with convex slope usually exhibits high erosion, while concave slope promotes deposition (Fig. 19.1). Typically, watersheds located in valley regions are the highest deposition zone, as the water, transporting huge soil masses, can eventually deposit as its energy gets dissipated. Simultaneously, hillslope positions are considered as the eroding zones. Fig. 19.3 shows a highly eroded and deposited wide valley in the Himalayas. The perception of soil redistribution brings the concept of net and gross erosion. While considering a system (typically closed), net and gross erosion has more importance. The soil particles removed or lost from their primary position by an erosive agent are considered as gross erosion, and the total mass of soil particles reaching a surface is gross deposition. Net erosion is the difference in soil mass before and after an event, that is, the difference between all the particles leaving and arriving the surface. For example, when considering a watershed, the sediment yield
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at the outlet of a watershed can be considered as the net erosion for the watershed. Figure 19.1 illustrates the concept of sediment redistribution and gross and net erosion. In general, the rate of gross erosion should be higher than the rate of net erosion. Typically, the Revised Universal Soil Loss Equation (RUSLE) (Kalambukkkattu et al. 2021) model estimates gross soil erosion, while processbased/physically based Soil & Water Assessment Tool (SWAT) (Sooryamol et al. 2022) and Agricultural Policy/Environmental eXtender (APEX) (David Raj et al. 2022) models estimate sediment yield at each Hydrological Response Unit (HRU)/ Subarea and proved efficient in hilly and mountainous regions of the Himalayas. The spatial and temporal soil redistribution rates are very much vital, due to their strong relation with soil organic carbon distribution (Doetterl et al. 2016). Soil organic carbon (SOC) is the principal terrestrial organic carbon pool (FAO et al. 2009). The quantity of SOC that is dispersed by soil erosion worldwide, principally due to water erosion, is calculated to be between 0.3 and 5 Gt C y-1. It affects the soil organic carbon variability and eventually food security. Evaluating the interactions between soil erosion and C dynamics exhibits various challenges as the erosion rates change spatially and temporally. Hence, instead of gross erosion, net erosion measurement and estimations are much required for identifying soil carbon distribution. Thus, the concept of sediment loss will provide the soil organic carbon dynamics in a watershed or hillslope.
19.2.3 Sediment Loss Sediment loss is the effect of soil erosion process occurring as a result of rainfall and runoff agents, while sedimentation refers to the buildup of eroded soil particles that are deposited in drainage systems, on certain ground surfaces, or in bodies of water or wetlands after being transported through runoff from their source of origin. Sediment loss arises when water flow slows and eroded material that is being conveyed by the water falls out of the water column onto the surface. Raindrops break the agglomeration between soil particles and disperse them, which is how sediment/soil particles are produced when rainfall events take place. Sheet erosion occurs when water is applied to the surface in thin, continuous sheets, displacing the soil particles. Rill erosion happens when the water’s surface flow creates channels, and the moving water separates soil granules from the sides and the bottoms of the newly formed rills. When rills enlarge and combine with others to form channels due to the geography of a landscape, ephemeral or concentrated-flow erosion occurs. The most severe type of water erosion that occurs on farmland is gully erosion, which is caused when concentrated-flow erosion persists over time. The sediment loss is not only an on-site issue but also a major off-site issue in reservoirs, riverbeds, and cultivation sites. The sediments of waterway’s beds, banks, and floodplains have been carried there by the flow of water from higher positions in the catchment. Even though erosion and sedimentation are normal processes, improper land use and management in the catchments and physical damage to a waterway’s banks or channels can speed up these processes and cause changes in the channel.
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There are several erosion models to estimate the rate of various soil erosion processes. The Universal Soil Loss Equation (USLE) is the primary one used to estimate the sheet and rill form of soil movement (erosion) down a constant slope using rainfall energy as the erosive force performing on the soil (Wischmeier and Smith 1978). While the GIS-interfaced RUSLE is the mostly used soil erosion models around the globe. Like the USLE, the RUSLE also estimates soil erosion due to sheet and rill only. Hence, routing of sediments from one place to another is absent in these models. Conversely, the Modified Universal Soil Loss Equation (MUSLE) uses storm-based runoff volumes and runoff peak flows to simulate erosion and sediment yield (Williams 1995). The use of runoff variables rather than rainfall erosivity as the driving force enables the MUSLE to estimate sediment yields for individual storm events. Various physically based models such as SWAT (Arnold et al. 1998), Environmental Policy Integrated Climate (EPIC) (Williams 1995), and APEX (Gassman et al. 2009) have the capability to predict the sediment yield from the watershed. The sediment yield received at the outlet of watershed can be considered as the sediment loss from the watershed. Although this does not provide the source of sheet and rill, it can provide net erosion rates instead of gross erosion, which can deliver more insights into soil organic carbon dynamics.
19.2.4 Soil Erosion Conservation Measures Uninterrupted soil erosion induced by rainfall and runoff causes permanent damages to soil ecosystem and environmental water resources. For a nation to be socially, environmentally, and economically sustainable, soil and water management and conservation are extremely important. The term “soil conservation” refers to a group of practices designed to stop or slow down soil erosion, preserve soil fertility and productivity, and improve soil health. It affects increasing soil water storage, lowering running water velocity, and providing enough plant cover to protect the soil from raindrop impact. Measures for preserving the soil’s physicochemical qualities, erosion management, and ultimately soil organic carbon content can all be achieved through soil conservation. The best way to prevent erosion is to use appropriate land management techniques that can safeguard the topsoil, stop splash, sheet, and rill soil erosion, and preserve soil quality. The two main types of soil conservation measures are agronomic or biological and mechanical or structural (Fig. 19.4). Although only agronomic practices and soil management are necessary for soil conservation, mechanical practices serve as a support. Agronomic controls are affordable, simple to implement, and friendly to the environment. However, agronomic practices are better suited in regions with low rainfall and low slope. The main goals of mechanical soil erosion control procedures are to slow down runoff and give time for water to sink into the soil or infiltrate. The choice of measurements also depends on the steepness and length of the slope. Agronomic measures, in general, are a type of land management that does not require a lot of engineering or earthmoving to level off or change the slope. The primary methods of soil conservation used in hilly and mountainous environments
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Fig. 19.4 Classification of major soil conservation measures
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Fig. 19.5 Plants for supporting (a) risers of terraces and (b) agroforestry
are contour farming systems. In contour farming, rows of crops are planted across the slope, among other methods, slowing the flow of water. With a slope of less than 10%, soil erosion can be effectively avoided or reduced. In regions with steep slopes, runoff may concentrate in furrows and seriously harm the soil through extreme rainfall events. Another crucial strategy is conservation tillage, which uses mechanical operations such as sod seeding (no tillage) or minimum tillage in place of heavy tillage. Major agronomic soil conservation strategies include crop placement, crop choice, crop pattern, crop rotation, cover cropping, organic management, and agroforestry. (Fig. 19.5). Mulches serve to reduce the impact of raindrops on soil by acting as a barrier between the soil and the atmospheric agents.
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Bench terraces
Stone patching on the riser
Field bund
Trenching
Fig. 19.6 Conservation practices adopted in various regions of the Himalayas
The main purpose of mechanical soil conservation strategies (Fig. 19.6) is to slow down runoff and its velocity. Thus, designing and building the structures need engineering expertise. The majority of the structures are expensive and require ongoing maintenance. The most popular mechanical technique for conserving soil in steep and mountainous areas is the terrace. A terrace is a mound that is constructed across a slope to stop soil erosion and flow. As far back as 4000 years ago, Peruvians built terraces out of patched stone (Kohnke and Bertrand 1959). Simple agronomic treatments are insufficient in locations with steep slopes and very erosive rainfall; therefore, mechanical/structural interventions could stop the soil erosion. In order to preserve the soil and allow for water infiltration, bench terraces are widely used in steep and very erosive terrains. Bench terraces are the construction of series of levelled at appropriate intervals which run across the slope by cutting and filling the slope supported by risers. Stones, grass, bricks, and pebbles can all act as supports for these risers. Mechanical measures include, among other things, contour bunds, intermittent terraces, ridging and tied ridging, stop-wash lines, contour trenching, grassed rivers, and diversion drains.
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Measurement and Modelling of Soil Erosion and Sediment Loss
Measuring the quantity of soil lost from a plot under various measured rainfall, soil, and crop conditions, plot experiments have been the primary method of quantifying soil erosion at a site. Indeed, a common practice is to assess soil erosion rate using soil erosion models. A reasonably straightforward modelling strategy combines data on terrain, climate, land use, and soil type, placing emphasis on “accelerated erosion” brought on by human landscape exploitation, particularly in agriculture. Accelerated erosion causes rates of erosion to increase 10- to 100-fold above background “normal” values, which roughly correspond to the rates of soil formation (Montgomery 2007). Such an approach has a lot of issues because it implies that erosion occurs uniformly. Therefore, extrapolating erosion measured at the plot or field scale to the entire landscape will overestimate the real amount. Field erosion occurs at amounts that are significantly lower than what the models had predicted. The necessity to calibrate models and the conclusion that “it is not sure that the model will have a strong predictive quality if the event lies beyond the range of calibration events” were both significant sources of concern. Model parameters are frequently set to the values that are inappropriate for the location under consideration, which results in models that are frequently incorrectly calibrated. Commonly used methods for measuring soil erosion rate and amount are described as follows: 1. Runoff plot methods: Erosion rates over extensive areas are usually measured using experimental plots, which are typically 22.1 m × 2 m in size. Plot measurements are a helpful tool in research on rill and inter-rill erosion as well as in the comparisons of the relative differences between various land uses and agricultural techniques. In order to create a plot area and drive runoff and eroded material into a collector for soil erosion evaluation, runoff plot systems require artificial boundaries. Runoff plots are sensitive, time-tested dynamic techniques for studying soil erosion. The Universal Soil Loss Equation (USLE) and the Revised Universal Soil Loss Equation (RUSLE) were developed mostly using these method. Most erosion models, especially those derived from the widely used USLE, are based on the findings of plot experiments. In fact, it is the main way of evaluating soil erosion in the United States (National Research Council 1986). Occasionally, models have been evaluated using actual field-scale data. The effectiveness of monitoring programs at the regional scale can greatly benefit from methods of erosion assessment at the field size. However, since runoff plot methods’ artificial borders change the natural runoff pattern, they may not accurately reflect natural runoff and soil erosion conditions and are not ideal for assessments of soil erosion under undisturbed field circumstances. 2. Field-scale measurement: Estimates of soil erosion at the field size should be based on volumetric measurements of gullies, rills, and transient gullies. Rill lengths can be calculated using a tape measure, a map, and an aerial shot or by pacing. By sampling, cross-sectional areas are determined (such as every 10 m along the channel). The sampling interval is determined by the survey’s
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objectives and the level of accuracy and precision needed. Another consideration is that field measurement can be done quickly, again depending on the level of specificity needed. It can be as small as the area where a tractor wheels, or it can be as large as the wider landscape, which is frequently arbitrarily defined as a sampling transect, a soil landscape, or an administrative region. It can also be as small as the area of a field that directly contributes runoff, or it can be as large as the area of a field where erosion occurs. Erosion pins: Despite significant limitations in soil erosion measurements, erosion pins are still often utilized. When assuming a bulk density of 1.2 g cm3 , the error in an erosion pin approach is often at the 3–5 mm (0.12–0.20 inch) level, which is corresponding to 36–60 t ha of soil erosion, making it insensitive for the majority of crucial soil erosion measurements in agricultural or forested areas. Development of contour plotting frame methods: However, technologies like contour plotting frames and laser scanners have had trouble working in areas with vegetation because they can only be used for small plots of at most a few square meters. Volumetric methods also do not provide samples for analysis; therefore, they miss information about the properties of the eroded soil, such as its nutrient content. Mesh-bag (MB) field method: The mesh-bag (MB) field method has been used for assessing soil erosion for some time (Hsieh 1992). The MB approach, which is dynamic, includes placing small nylon mesh sheets, like those measuring 20 × 20, in a plot to sample the distribution of eroded soil following one or more runoff events. The vegetation immediately beneath the bags is removed, putting the nylon mesh sheets in close touch with the contour of the bare ground. This arrangement allows water but very little dirt to seep underneath the bag. Mesh bags are collected after one or more runoff episodes, and the dirt on and within the sheets is gathered for study. Only the original soil surface is marked by MB, allowing for easy sampling of the eroded soil’s redistribution. The amount of soil erosion is measured by the weight of the eroded dirt and the area of the bags. Radionuclides from the fallout: Radionuclides have been employed as tracers to identify soil erosion and deposition, such as the caesium-137 (137Cs) approach. The employment of 137Cs as a tool for mapping and calculating the amounts of erosion and deposition was highly anticipated. These tracer approaches have been effectively used in several studies that assess soil erosion and deposition in natural environments, despite their limitations (Walling and He 1997, 1999). The fallout radionuclide techniques have been used to calculate the rates of soil erosion and deposition over quite extended periods of time (i.e., currently approx. 60 years). Due to sensitivity and background noise issues, they are not appropriate for direct or specific soil erosion events. The researchers need to fulfill the assumptions underlying with this method for the reliable soil erosion estimation. Measurement of sediment at watershed scale : Measurements of meteorological variables, runoff, and sediment loss are much required data for experimental micro-watershed. A weir civil structure with a stage-level recorder (selfrecording) is required to record measurements of surface runoff and sediments.
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Pasta Micro Watershed : 57 ha : North-western Lesser Himalayas Elevation : 835 to 1374 m Climate : Humid subtropical Land use/ cover : Forest (Sal), Agriculture (Maize & Rice) Soil texture : Sandy loam Area Region
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Fig. 19.7 Instrumented (gauging station) Pasta micro-watershed
To keep track of meteorological information, an automatic weather station (AWS) needs to be set up in the watershed. For the modelling, daily rainfall data are used. The sampled surface runoff water collected in the sediment tank can be used to calculate the daily loss of sediment from the watershed. To collect runoff water carrying sediments, a 1.5-m steel pipe with holes at 10–15-cm interval, commencing after 5 cm (base), is attached in the middle of a weir civil structure and connected to the sediment tank through a steel pipe. Figure 19.7 shows a watershed observatory (surface runoff and sediment yield measurement) installed by the Indian Institute of Remote Sensing at Sitla Rao watershed (Pasta micro-watershed) of the northwestern Lesser Himalayas. In order to estimate sediments on a daily basis, 2 L of the sampled runoff water containing sediments collected in the tank can be extracted and brought to the soil laboratory. The highpressure filter unit is used to filter the samples that are transported to the laboratory. Following that, dried filtrate sediments are stored in an oven set to 60 °C (24 h). Electronic balances can be used to weigh the material, and mg/liter measurements of sediment content are taken. Sediment is then kept in storage and to be analyzed for soil carbon using a CHNS analyzer; thus, the sediments are examined for total soil carbon and nitrogen loss. 8. Estimates of sediment yield: Rivers do not correspond to hillslope erosion. This is a result of sediment storage between fields and watercourses and nonfield sources such riverbank erosion. It has been extensively studied how to budget the sources and sinks of silt within a catchment. Another method of estimating sediment output is by deposition in dams and retention ponds. Both the strategies have room for large errors. A significant study gap in soil erosion, particularly at larger field scales, has been the absence of field soil erosion data. Our ability to comprehend, model, and foresee soil erosion in agricultural and wild lands is severely constrained by this gap (Nearing et al. 2000).
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19.3.1 Soil Erosion Models Soil erosion models aim to mathematically describe the three major stages involved in erosion, namely soil particles’ detachment, their transportation, and their subsequent deposition on land surfaces. Most of the soil erosion models could simulate splash, sheet, and rill erosion processes occurring in different landscapes. Based on the data requirement, the processes involved, and their complexities, erosion models are generally grouped into three categories, namely empirical, conceptual, and physical process–based models. Empirical models, also referred to as statistical models, are the most widely used category of erosion models globally. These are formulated based on the simple statistical/empirical relationship between the observed values and the various erosion-causing factors, by making use of a large set of observations/experimental data from the field plots. These are known for their simplicity, comparatively low data requirement, and reduced computational complexities compared with other categories but do not describe any erosion process. They are sometimes referred to as black box models, as the mechanism and processes involved are not clearly defined. Wischmeier and Smith (1965) developed the first empirical soil erosion model widely known as the Universal Soil Loss Equation (USLE) making use of extensive field plot observations across the United States. Even though they are referred to as black box type of models addressing only sheet and rill erosion processes, the USLE along with its further improved versions such as the Modified Universal Soil Loss Equation (MUSLE) and the Revised Universal Soil Loss Equation (Renard et al. 1997) is the most widely used empirical model. Physical process–based models primarily represent the fundamental physical processes occurring during erosion in the form of mathematical equations and are based on the mass and energy conservation laws. They represent distinct soil erosion components and their complex mutual interactions, including their spatial and temporal variability, utilizing continuity equations. These models involve several assumptions and are capable of simulating erosion on a daily or an event basis for longer timescales based on the data availability. Such models are widely employed for the identification of critical source area due to their spatially distributed nature and can provide better simulation accuracies compared with empirical models when properly calibrated and parameterized. These characteristics help the user to understand processes involved in erosion and runoff generation in a much better way. These models can accurately simulate the impact of changes in various factors such as climate, land use/land cover, topography, and plant growth. In addition to simulating erosion processes, they can predict the associated sediment and nutrient losses from catchments. However, these models suffer from the very high data requirement and are computationally intensive, thus limiting their widespread adoption by researchers and land managers. Physical models are also referred as white box models owing to the use of mathematical expressions for defining various
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erosion processes and their mechanisms. Limburg Soil Erosion Model (LISEM), Kinematic Erosion (KINEROS) model, Water Erosion Prediction Project (WEPP), GIS interface for WEPP model (GeoWEPP), Areal Nonpoint Source Watershed Environment Response Simulation (ANSWERS), etc. are some of the most widely used physical process–based models. Conceptual models represent a transition between empirical and physical models and are based on spatially lumped forms of water and soil conditions. They primarily use the concept of unit hydrographs to predict sediment yields mainly at catchment scales of differing magnitudes. Such models make use of catchment parameters in a spatially averaged form for estimating runoff and loss of sediments for the entire catchment area. They represent overall processes occurring in a catchment without addressing specific details pertaining to various interactions happening between erosion processes, which the physical models are capable of providing. These group of models needs parameterization and calibration using observed runoff and sediment load data and are known to represent reality in a much better way. Such models are known for their ability to predict the consequence of land use changes (both quantitative and qualitative), with a moderate spatially distributed data requirement. Morgan–Morgan–Finney (MMF) model, modified MMF, Soil & Water Assessment Tool (SWAT), Agricultural Policy/Environmental eXtender (APEX), Agricultural Non-Point-Source Pollution Model (AGNPS), etc. are some of the widely explored conceptual models. The detailed description of the abovementioned model categories and some of the widely adopted erosion models are provided in Kumar and Kalambukattu (2022). Nearing et al. (2005) provided the comprehensive information of model capabilities and comparisons of different models with respect to rainfall and land cover in two different study areas, while Borrelli et al. (2021) conducted a comprehensive review of global soil erosion modelling and statistical analysis.
19.3.2 Sediment Loss Prediction Models Sediment loss prediction is a vital aspect of erosion modelling studies, as it affects fertility status, crop performance, and downstream ecosystem characteristics. Sediment loss is the most visible and easily identifiable characteristic with which impact of erosion could be observed and analyzed. Sediment loss is confined to not only the removal of soil particles from the top layers of soil, but also the associated loss of various nutrients including soil organic carbon, nitrogen, phosphorus, etc., thus causing deleterious effects on soil quality. Most of the conceptual and physical process–based models mentioned in the earlier sections are capable of sediment and nutrient loss prediction at varying temporal and spatial scales. The different spatial scales on which these models operate range from plot, hillslopes, farm, and watershed, whereas the temporal scales may vary from event-based, daily, monthly, seasonal and annual scales. Some of the most widely used models for sediment loss prediction are SWAT, APEX, AGNPS, WEPP, GeoWEPP, and ANSWERS. Another physical process–based erosion model, Environmental Policy Integrated
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Climate (EPIC) has also been widely used to generate estimates of soil loss, loss of nutrients (nitrogen and phosphorus), and change in soil organic carbon under various croplands across the United States. A detailed description of the model use is given in Potter et al. (2006). These models simulate sediment and nutrient loss, by incorporating a large diverse set of input parameters pertaining to soil and topography, crop growth parameters, weather and climate, tillage and conservation practices, nutrient/manure applications, etc., in the form of various interrelated processes represented by physical equations. Outputs from most of these models are widely used for identification of erosion hotspots, source areas of nutrient loss, and pollutants at catchment/watershed scale for better management and conservation of natural resources aimed at sustainable development.
19.4
Soil Erosion and Carbon Dynamics
19.4.1 Soil Erosion, Carbon Loss, and Nutrients Loss The soil productivity of the Himalayan regions is low and highly unstable due to low concentration of available soil nutrients and organic carbon contents. Soil nutrients and carbon stored are redistributed within the watershed or deposited in the larger river systems or exported outside the catchment along with the runoff water and soil particles. Nitrogen (N), phosphorous (P), and potassium (K) are the significant crop growth nutrients concentrated in the surface layer that are lost by the erosion processes. Each of them has a different correlation with runoff and soil loss due to the difference in their characteristics such as solubility, mobility, and affinity to get adsorbed on soil particles. However, in general, higher runoff and soil loss will lead to higher nutrient mobilization and loss. Approximately 5.37–8.4 MT of plant nutrients are lost from soils in India due to water erosion every year. Intensive agricultural practices (especially for wheat and rice) cause nutrient imbalance. Around nine nutrient elements (N, P, K, S, B, Ca, Fe, Mn, and Zn) in Indian soils have been listed as deficient during the period of 1950–2006 (Bhattacharyya et al. 2015). Eroded soils contain three times less nutrients left in the remaining soil. One ton of fertile surface soil averages 1–6 kg of nitrogen. However, after erosion, an average of 0.1–0.5 kg per ton nitrogen is found in the soil (Meena et al. 2017). Nutrients transported further down to the fluvial system through sediments, and runoff water alone is enough to cause serious global problem such as decline in the quality of the water bodies receiving these effluents and further economic and environmental consequences. Dynamic redistribution of SOC can happen because of water erosion and tillage practices. Arguably, soil erosion causes about 0.6–1.5 Gt of carbon sequestration and approximately 1 Gt of carbon emission annually. Burial of transported SOC below plough depth is protected from mineralization, and thus, C remains undisturbed in the depositional sites. Erosion-induced breakage of aggregates containing SOC releases labile organic carbon and gets easily mineralized, and about 20–30% of transported SOC is emitted into the atmosphere (Lal 2005). Spatial redistribution
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Table 19.1 Some selected studies regarding the soil erosion–induced carbon loss in India Sl. No. 1
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Objective Soil erosion and associated nutrient loss (C) How and why erosion modifies carbon storage in low-input agriculture Sediment loss and associated nutrient loss
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Carbon loss estimation method Sediment measurement
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Steady-state C and erosion model Enrichment ratio
Arc-APEX/ watershed gauging station Radionuclide (137Cs isotope) Runoff plot
Carbon amplification ratio Sediment measurement
Source Mishra et al. (2022) Mariappan et al. (2021) Kumar et al. (2021) Mandal et al. (2019) Kothyari et al. (2004a, b)
of SOC is related to landscape positions; the low levels of SOC can be found at highmid-slope (eroding sites) and the highest at low positions (depositional sites), and thus. the eroded material is enriched with SOC compared to the original soil. Erosion-induced SOC loss can accelerate the erosion as the soil loses its ability to incorporate organic carbon and produce more stable aggregates. In India, SOC stocks were reported to be depleted at a rate of 0.5% due to topsoil erosion. A watershed-based study by Kumar et al. (2021) to model surface runoff, sediment yield, and nutrient loss using Agricultural Policy Environmental eXtender (APEX) from the Lesser Himalayan landscape with spatial and nonspatial data sets estimated a loss of 0.49 to 0.5 kgha-1 of total carbon (TC) and 0.16 to 01.7 kgha-1 of total nitrogen on a daily basis with an average daily runoff of 19.58 mm. Table 19.1 describes the soil erosion–induced carbon loss studies conducted in the Himalayas.
19.4.2 Climate Change and Soil Erosion Global soil erosion threat is expected to rise as a result of climate change. According to measured and simulated statistics, this may cause soil erosion to increase by 5–95% and average annual runoff rates to increase by 30–40% in high latitudes. The amount and intensity of rainfall determine soil detachment and transport, and the projected climate change is expected to significantly enhance rainfall erosivity. Rainfall amount and frequency are less important factors in erosion than rainfall intensity. As a result, a brief, but intense rainfall event may result in significant soil erosion. By lowering macro-porosity and water infiltration rates, changes in the water and temperature regimes may have an impact on the soil structure. Soil erosion can be exacerbated by climate change–related changes in surface soil properties as
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crusting, surface sealing, and compaction. To adapt to climate change, changes in land use, crop variety, tillage techniques, plant species, and vegetation cover are anticipated to have an impact on soil erodibility and soil aggregate stability. Climate change is correlated with soil formation due to its strong influence on the factors affecting the soil formation processes such as vegetation, soil organisms, landscape characteristics, parent material, and soil management. Leaching of dissolved chemicals and bases (Ca2+, Mg2+, and Na+) due to increased rainfall can cause acidification. Changes in soil chemical processes such as reaction rates, diffusion, and solubility of salts can happen due to small changes in soil temperature. Soil physical properties such as shrink-swell and freeze-thaw, biological properties such as organic matter decomposition, and microbial activity processes may be affected by the change in soil temperatures and alter the soil structure. Highly intensive rainfall over a soil with weak structural properties results in accelerated topsoil loss and exposure of the horizons beneath with reduced structural development (BlancoCanqui and Lal 2010). Due to the Himalayas’ exceptional sensitivity to heavy rainfall and flood events during the monsoon seasons, the shift in the erosive force of rainfall and soil erosion because of climate change is a major problem of concern. The summer monsoon is responsible for more than 80% of the yearly rainfall in the central Himalayas. Westerlies winds primarily affect areas in the far west and east, and 60–80% of the annual precipitation falls on the eastern and western Himalayas during the summer monsoon. This changing rainfall gradient during intense storms due to climate change affects erosion during extreme rainfall events. Developmental activities like road and infrastructure constructions in these areas will destabilize hillslopes even more. The Himalayas and mountain-peak areas have more than 10 or even more extreme rainfall days during summer season. Extreme rainfall events on a landscape with rugged terrain and poor soil quality will lead to accelerated soil erosion and mass transport of sediment through fluvial systems. These infrequent, intense rainfall events may account for a significant portion of the total erosion (Bookhagen 2010). Studies on the Lesser Himalayan region’s watersheds conducted under various future scenarios reveal that the monsoonal rains are variable, and their potential strengthening in the future raises the possibility of rainfall erosivity and soil loss. The average rainfall erosivity of the downscaled precipitation data for the 2020s, the 2050s, and the 2080s may increase from 546 to 693.8 and to 701 m t/ ha/cm. Further, the average annual soil loss may increase from 20.33 to 28.38% in the future under the scenarios from the base period (Gupta and Kumar 2017).
19.4.3 Climate Change and Soil Carbon Loss The region’s climate variables, such as temperature and precipitation, affect how SOC is stored, specifically soil water content and temperature. Since soil organic matter decomposes more quickly at higher soil temperatures, aggregate stability and soil organic C storage may decline. A rise in temperature of 3 °C is predicted to result in an 8% increase in carbon dioxide (CO2) emissions and a decrease in soil organic C
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concentration of roughly 11% in the surface soil (up to 30 cm soil depth). An increase in soil organic carbon can result from increased water content due to higher growth of vegetation. Aboveground and belowground biomass decomposition enriches the soil with organic carbon and improves aggregate stability. Ultimately, the preferential removal of labile organic carbon by the dynamic changes in climate may result in the reduction of soil C pools. Expected high-intensity rainfall can redistribute SOC and topsoil and expose the soil horizon to degradation of soil structure, which in turn accelerates the erosion and soil carbon loss. The range of SOC lost by erosion in the surface layer of moderately and severely eroded soils can be as much as 19–51% for Mollisols and 15–65% for Alfisols (Zhang et al. 2015). The combined effect of climate change and erosion can decrease the SOC stocks in the soil and thus the soil quality. Nearly 40% of the SOC stocks of the soils around the world is stored by the forests. The eastern and western Himalayan zones contribute 33% of the SOC reserve of the country due to the thick forest covers in these regions. Deciduous forests in the Indian Himalayas have a carbon stock of 2.64 Pg C in the top 1 m of soil (Chhabra et al. 2003; Longbottom et al. 2014). SOC concentration of surface soils of the northeastern Himalayan regions ranges from 085 to 356%. Essential nutrients to support rain-fed agricultural systems are mainly depending on the soil organic matter pools of the Himalayan soils. SOC in the Himalayas is vulnerable to changes in precipitation, altitude, and temperature. The abundance of moisture has a bigger impact on SOC stock sensitivity in the Indian Himalayas than temperature, and the average annual precipitation has a greater impact on SOC than altitude. The Himalayas are also the source of the Ganges and Indus Rivers, which are among the major contributors of sediment and related terrestrial organic matter to the world’s oceans because of significant erosion rates. With changing climate variables (precipitation and temperature) brought on by climate change, a large-scale destabilization of soil organic matter is anticipated in the Himalayas. This destabilization will affect net primary production (NPP), which equalizes soil carbon losses and rates of turnover/decomposition of SOC. Through transit and deposition, soil erosion decreases plant productivity and the SOC pool. Large-scale landslides that are caused by significant rainfall events in the Himalaya and Trans-Himalaya destabilize slope material and remove it, which promotes rapid flow if slopes are not stabilized by organic content and thick forests. Changes in annual temperature and precipitation can boost CO2 emissions to the atmosphere by increasing soil respiration. An abnormality in the intensity, quantity, and length of a monsoon shower could have an impact on SOC dynamics on a regional level either by causing an increase in vegetation because more water is available or by speeding up soil erosion. The potential effects of climate change on carbon cycling in the area are as follows: Increasing water availability at high altitudes will probably increase SOC storage, but extremely large increases in precipitation may destabilize hillslope SOC stocks and probably result in greater SOC mineralization at lower altitudes and in river basins (Longbottom et al. 2014; Choudhury et al. 2015).
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19.4.4 Uncertainty in Soil Erosion and Carbon Loss Soil erosion and associated soil carbon loss can vary between different land uses, slopes, erosion phases, soil properties, climatic factors, and tillage practices. It may cause variation in their magnitude and intensity at local, regional, and global scales. Soil erosion could be a major perturbation in the terrestrial cycle of carbon. A debate over the effect of erosion on atmospheric carbon points out that the accelerated decomposition of the eroded SOC during detachment and transport can be a net source of CO2, but on depositional sites, deep burial of SOC reduces the decomposition and acts as a sink of carbon. Complexity in erosion processes such as detachment, transportation, and sedimentation may affect a better understanding of the fate of eroded materials. The major challenges in evaluating the relations between soil erosion and C dynamics can result from the use of various methods. The use of bounded or unbounded experimental plot to study runoff, erosion, and associated carbon fluxes with respect to rainfall events may help to understand the soil erosion events and processes, but their implication to natural conditions or landscape scale is questionable. Thus, the erosion rates obtained from such plots are relevant only to plots of the used size and the conditions of the monitoring site. Applications beyond the limits of these studies may possibly erroneous. Modelling of erosion and soil carbon loss may be a better way to obtain more reliable results. Models can overcome the restrictions of both plot studies and monitoring, but they are controlled by the representation of processes and by its parameterization. There are a number of models for estimating erosion and associated carbon loss such as numerical, empirical, and process-based models. Difficulties in modelling also exist due to data availability, model efficiency, and model reliability. Each of them may differ in their principle, concepts, attributes, parameter estimation, location, scale, and performance under different conditions. Ultimately, all models have empirical bases, and the model performance depends on how well this empirical basis represents soil erosion processes. Even though the models are calibrated, errors can happen and affect the simulation to some extent (Parsons 2019; Doetterl et al. 2016).
19.5
Soil Carbon Models
In the view of carbon sequestration as a negative emission technology, it is significant to manage soil carbon pool. Carbon in soils shows complexity due to its high spatial and temporal variability. Accurate quantification of carbon sequestration potential and its dynamics is an effective way to understand the management of soil carbon stocks. Traditional ways of field experiments are laborious, costly, and time-consuming. Now models are being extensively used for simulation and prediction of soil carbon changes. Several models from simple empirical formulations to complex biogeochemical processes were developed. Most of the models estimate soil organic carbon (SOC) dynamics by compartmentalization. The multicompartment models categorize organic matter into conceptual pools and
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presumptively presume that first-order kinetics governs the degradation of organic matter. Decomposition is defined as a continuous quality equation in models with a continuum structure, and some of these models are very complicated. The Rothamsted Carbon (RothC) (Coleman and Jenkinson 1996), EPIC (Williams 1990), and CENTURY (Parton et al. 1987), among others, are some of the most used process-based models for simulating C dynamics in soil–plant systems by considering the impact of different biotic and abiotic variables.
19.6
Soil Organic Carbon Status, Soil Quality, and Soil Ecosystem Services
Soil organic carbon is the net balance between soil carbon input and carbon output. The capacity of global soils to store organic carbon in the top 1 m was estimated to be nearly 1500–2400 Gt C (5500–8800 Gt CO2), (Smith et al. 2020), which is much greater than the atmospheric pool and biotic pool. Changes in soil organic carbon can affect soil quality itself due to the influence on the other physical, chemical, and biological properties of the soil. Since the soil acts as the largest terrestrial C pool, about 90% of total greenhouse gas (GHG) mitigation potential can be achieved through the proper sequestration of SOC in soil. The SOC stocks from global agricultural land is valued to be 2 to 3 Gt C yr-1 from the top 1 m, which efficiently offsets 20–35% of global anthropogenic GHG emissions. Through cultivation, around 140–150 Gt C (510–550 Gt CO2) has been lost since the onset of agriculture. Assessments of global soil C sequestration potential vary greatly; then, the latest studies estimate an annual technical potential of 2–5 Gt CO2 yr-1. The SOC stocks in Indian soils, distributed from the surface to an average depth of 44–186 cm, are estimated to be 24.3 Pg. The organic C pool of Indian forest soils is 6.8 Pg C in the top 1 m. Carbon stock in the Indian Himalayan region (IHR) varies with land use, such as bamboo forest (25.8 Mg C ha-1), tea plantation (158 Mg C ha-1), temperate forest (112–205 Mg C ha-1), and some major forest types (59–170 Mg C ha-1) in the western Himalayas and prevailing climatic conditions (Rice et al. 2021). The concept of soil quality describes the ability of soil to perform various soil ecosystem functions. Soil quality can be used to assess soil condition because of changes in soil properties (physical, chemical, and biological properties) and management practices. High soil organic matter and soil organic carbon concentration are general characteristics of soils in better condition or soils in a state of higher soil quality or soils with higher productivity. Thus, soil organic carbon is widely considered as an indicator of soil quality. In addition to providing plant nutrients, boosting cation exchange capacity, enhancing soil aggregation and water retention, and promoting soil biological activity, SOC is crucial for many soils’ ecosystem functions. Soil organic carbon concentration changes can affect the health of the soil environment. Aggregates are formed by soil particles coalescing around binding agents that are produced by organic components. SOC enhances aggregation, and stable aggregates protect SOC and promote a long-term storage. Improved microporosity and water infiltration because of stable aggregate production can promote
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soil microbial activity, which affects the transformation and availability of nutrients, organic matter, and soil resilience and health. Increased soil aggregate stability may have an impact on near-surface soil processes that affect water infiltration and runoff, such as splash detachment, surface sealing, and crusting. Depending on the texture of the soil, 1 g of C can retain between 1 and 10 g of plant-available water. For medium-textured soils with a bulk density of 1.25 Mg m-3, an average 1% increase in SOC may result in a 12.5-mm increase in the available water in the top 20 cm of the soil profile. Thus, water retention capability is another advantage of SOC. Water retention and absorption in the soil matrix are improved by organic C. SOC accounts for 58% of soil organic matter, making it the primary soil component. Organic matter can react with cations and organic pollutants because it frequently has a net negative charge and a large specific surface area (i.e., pesticides and herbicides). By absorbing and filtering pollutants in runoff, this property will lessen nonpoint source pollution and enhance water quality. A higher content of SOC will result in higher fertilizer use efficiency (FUE). SOC-induced improvements in soil properties can enhance soil productivity, resulting in more sustained crop production (Blanco-Canqui et al. 2013).
19.7
Radio-Isotopes Methods of Soil Carbon Estimation
The movement of soil carbon from local carbon cycle depletes soil fertility. Estimating and understanding its redistribution is crucial to sustaining soil organic carbon in the region and maintaining soil quality. Lateral distribution of SOC can be estimated using suitable modelling and analytical tools at the landscape scale. A more sophisticated approach to estimate soil carbon is the radio-isotopes methods. Since soil erosion favors the loss of both elements, radio-isotopes inventories can be used to track the mobility of soil and related carbon on a landform. Atoms that have different numbers of neutrons in their nucleus, but the same atomic number are called isotopes. Some isotopes are stable over long periods of time and retain their atomic structure. However, some are radioactively volatile and emit alpha and beta particles or gamma rays as they decay into other elements. Some radio-isotopes are observed in soil, while others are created unnaturally by nuclear reactions (often referred to as fallout radionuclides [FRNs]) after nuclear accidents like the recent accident at Fukushima Daiichi in Japan or atmospheric thermonuclear testing in the 1960s. Every “parental” radio-isotope eventually breaks down into one or more stable isotopes that are “daughters” and are exclusive to the parent. Rocks and soil naturally contain radium and uranium radioactive isotopes. Radiocarbon and potassium are typically found in trace concentrations in organic compounds. For successful stabilization of soil organic matter, about 90% of the carbon in soil is chemically bonded to soil mineral particles like clay and metal oxides. These bonds make up stable aggregates and allow for the chemical and physical preservation of carbon. Breakdown of aggregates and separation of soil particles, followed by sediment movement and deposition, are the steps in soil erosion. Preferential removal of the low-density organic colloids due to erosion has a strong influence
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on the state and dynamics of SOC. Radioactive isotopes such as 137Cs are strongly and rapidly adsorbed on mineral and organo-mineral soils, and further redistribution over time in the concentrations of these isotopes in soil is possible only through physical movement of soil minerals such as erosion or deposition by water, tillage, and wind. Thus, the radio-isotopes have traditionally been used to trace the movement of soil and assessing long-term erosion rates due to their relatively long halflife time. The information on the long-term spatial pattern of soil redistribution can help to study the effect of erosion on the spatial distribution of soil nutrients such as carbon, nitrogen, and phosphorus and the erosion-induced SOC dynamics within the field. The most used radio-isotopes in soil erosion studies are caesium-137 (137Cs), lead-210 (210Pb), beryllium-7 (7Be), and plutonium-239 + 240 (239 + 240Pu) (Sankar et al. 2018). Even though the use of radio-isotopes to assess erosion and associated carbon loss in India is in its initial stage, 137Cs-based assessment of erosion-induced soil organic carbon loss was conducted in the Lower Himalayas (Doon Valley) and found a strong relationship between 137Cs and SOC content of the soil due to the selective displacement of clay particles and SOC during erosion process. The technique showed to be more accurate for examining the relationship between erosion and carbon in various erosion phases in sloped agricultural fields of the northwestern Himalayas (Mandal et al. 2019).
19.8
A Case Study: Soil Erosion–Induced Carbon Loss in a Watershed of Northwestern Lesser Himalayas
The distribution of soil organic carbon is highly depending on the spatial and temporal distribution of soil erosion. This is preferably quite high in hilly and mountainous terrain. The erosive power of rainfall, runoff, and topographical characteristics plays a major role in determining the carbon distribution. In the Himalayas, a highly fragile and eroded region, SOC distribution is varying significantly due to high erosion. Hence, here, we are demonstrating the soil organic carbon loss induced from water erosion in a watershed of the Lesser Himalayas. The common methodology adopted for the studies is illustrated in Fig. 19.8.
19.8.1 Study Area The study area located in the Indian Lesser Himalayas, part of the northwest Himalayan region. The average annual rainfall in the study area is 2200 mm, and average annual temperature ranges from 15.8 to 33.3 °C. The elevation of the study area varies from 835 to 1374 m (Fig. 19.9a, b). Soils in the study area are resultant from the alluvium parent material. Soils have a dominant sandy loam to loam texture. The land use/land cover of the study area is dominated by cropland (rice, maize, and mustard), forest (Sal-Shorea Robusta), and scrub land (Fig. 19.9c). The watershed is divided into five soil physiographic units comprising of slope/topography and land use/land cover (Fig. 19.9d).
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Fig. 19.8 Commonly adopted methodology for soil erosion–induced carbon loss
19.8.2 Materials and Methods The amount of sediment yield at the watershed outlet or sediment loss/net erosion from entire watershed is required for estimating soil erosion–induced carbon loss. The SWAT model was used to predict sediment loss from the watershed based on Hydrological Response Units (HRUs). The HRU is characterized by unique soil, slope, and land cover characteristics. Hence, the SWAT model–generated HRU is considered as the basic unit for assessing the erosion-induced carbon loss. The average carbon loss from the various HRUs was considered as the carbon content of soil. The model was calibrated and validated with watershed gauging station installed at the outlet of watershed (Sooryamol et al. 2022). It provides the sediment yield value at the outlet of the watershed. Carbon erosion was calculated using the following formula (Mandal et al. 2019):
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Fig. 19.9 Elevation map (a), slope map (b), land use/land cover map (c), and soil unit map (d) of the study area
C erosion kg ha - 1 yr - 1 =
SE × SOC × CAR × 1000 100
ð19:1Þ
The carbon erosion was estimated using soil erosion (SE) from the soil physiographic unit (from HRUs), organic carbon in original soil (SOC), and organic carbon in the sediment (Eq. 19.1). CAR =
Organic carbon in the sediment Organic carbon in the soil
ð19:2Þ
where CAR is the carbon amplification ratio, defined as the ratio of the organic carbon in the sediment to the organic carbon in the original soil (Eq. 19.2). Here erosion is considered as sediment loss from the watershed. For estimating the SOC, a total 50 surface and subsurface soil samples were collected and analyzed using Walkley and Black method. Likewise, a total of 48 event-based sediment samples collected from the outlet of watershed were analyzed in the CHNS analyzer for total carbon (TC) determination in sediment, and later the correction factor proposed by Kumar et al. (2019) was used to convert TC value to total SOC. Average values of this sediment samples were used for estimating organic carbon in the sediment at the outlet. Soil physiographic unit wise CAR was derived using the available data.
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19.8.3 Main Findings The main findings of the study are described in Table 19.2 and Fig. 19.10. The soil organic carbon of the study area varies from 0.67 to 2.44%. Scrub land exhibits the lowest, while maize and moderately dense forest exhibit high organic carbon contents. Less cover with highly erodible sloping land is responsible for the lowest carbon content in scrub land, whereas fertilizer application (maize field) and vegetation cover with inputs from litter (forest) contributed high carbon content. The carbon content in the sediment varied from 0.074 to 3.41% with a mean and standard deviation of 1.54 and 0.72, respectively. The lowest carbon amplification ratio was found in maize field (0.63) and forest (0.69) due to the frequent addition of carbon to soil (fertilizer and litter), while the highest amplification ratio was found in scrub land with a value of 2.30. The paddy field exhibits an amplification ratio of 1.25. Table 19.2 Soil-physiographic unit/soil-landscape unit wise sediment loss and erosion-induced carbon loss Soil unit HS12 HS14 HS21 HS23 HS24
Land use/land cover Scrub land Maize Forest Paddy Maize
SOC in soil (%) 0.67 2.44 2.24 1.23 0.96
SOC in Sediment (%) 1.54 1.54 1.54 1.54 1.54
CAR 2.30 0.63 0.69 1.25 1.60
Fig. 19.10 Spatial distribution of soil carbon erosion rate
Sediment loss (tha-1 yr-1) 42.8 30.2 20.1 24.0 30.3
Carbon erosion (kg ha-1 yr-1) 658.8 465.1 310.2 369.1 466.6
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Mandal et al. (2019) also observed a carbon amplification ratio from 2.54 to 2.96 in Doon Valley region. Based on the severity of erosion, soil type, slope steepness, and land cover, the amplification ratio showed significant variations. The sediment/soil loss from the watershed was predicted using the SWAT model. HRU-based sediment loss was averaged to find out the sediment loss of each soil map unit (Sooryamol et al. 2022). The highest average soil loss was observed from scrub land (42.8 t ha-1 yr-1), followed by maize field (30.2 t ha-1 yr-1) and paddy (24.0 t ha-1 yr-1). The lowest soil loss was observed from Sal Forest with a value of 20.1 t ha-1 yr-1. The carbon erosion from the watershed varied from 310.2 to 658.8 kg ha-1 yr-1. Forest land cover exhibits the lowest loss of soil organic carbon (310.2 kg ha-1 yr-1) due to good cover and continues addition of organic matter through litter. Apart from this, less soil erosion also acts as a major reason for lower carbon erosion. Highest carbon erosion was obtained from scrub land with a value of 658.8 kg ha-1 yr-1. Less cover and highly erodible soil contributes higher soil erosion and carbon erosion. Maize field showed a carbon erosion range of 465.1–466.6 kg ha-1 yr-1 and paddy field a value of 369.1 kg ha-1 yr-1 (Table 19.1; Fig. 19.7). The average carbon erosion from the watershed amounted to 454 kg ha-1 yr-1 (Rainfall– 2200 mm). Similarly, Boix-Fayos et al. (2009) also reported 200 kg ha-1 yr-1 of carbon erosion from a Mediterranean catchment with 583-mm rainfall. Sitaula et al. (2004) also reported a value of 256 kg ha-1 yr-1 from Hindu Kush Himalayan region, whereas Mandal et al. (2019) observed the highest average carbon erosion rate of 383.8 kg ha-1 yr-1 in Doon Valley region with an average rainfall of 1625 mm.
19.9
Conclusions
Soil erosion is an ecological and socioeconomical threat as it reduces the soil quality by the loss of soil carbon and nutrients; degrades the land and environmental quality; decreases crop yield production; and leads to food security threats. Among the degradative processes, it is the most widespread form of soil degradation. Every year, erosion transports around 75 Gt of topsoil and a significant amount of nutrients. This degradation process is highly relevant in hilly and mountainous terrains, especially in the Himalayan region. Climate change and steep slope along with unsustainable land management practices further enhance the soil erosion and associated carbon loss that may severely affect food security in the region. Soil erosion affects all aspects of soil quality or soil health. Several researches stated that soil erosion could be a strong carbon source or sink. Roughly 20–30% of the eroded C is mineralized, and approximately 0.7–1.2 Pg C yr-1 is released into the atmosphere. In the hilly and mountainous landscape, when a natural toposequence is turned into cropland, soils of the hillslope will reduce organic carbon by mineralization. Complexities in the Himalayan terrain and erosion processes require advanced estimation methods of soil erosion and associated carbon loss in the region. Processbased soil erosion models can simulate event-based erosion with a fine temporal and
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spatial resolution. A wide range of soil erosion models exist to simulate erosion and sediment transport and associated carbon loss. The choice of a suitable model structure relies heavily on the function that the model needs to serve. The most widely applied soil loss models are the USLE and the RUSLE. Other widely applied models are as follows: Morgan–Morgan–Finney model (MMF), Water Erosion Prediction Project (WEPP), Kinematic Runoff and Erosion Model (KINEROS), Agricultural Non-Point Source Pollution (AGNPS), Areal Nonpoint Source Watershed Environment Response Simulation (ANSWERS), and Chemicals, Runoff and Erosion from Agricultural Management Systems (CREAMS). Incorporating geographic information system (GIS) interface to model for a better and accurate prediction of erosion and associated nutrient loss was a revolutionary change in the soil erosion modelling. Soil & Water Assessment Tool (Arc-SWAT), Agricultural Policy Environmental eXtender (Arc-APEX), and Geo-WEPP are some of the models interfaced with GIS. The RothC and the CENTURY models can be used to simulate soil erosion and the accompanying carbon dynamics. The employment of numerous distinct techniques has helped to overcome the challenges in experimentally determining the spatial patterns of erosion rates owing to discrete or episodic events, tracers as proxies such as natural or fallout radionuclides (FRNs) for longterm and short-term soil redistribution by tracking the pathways of mobilized soil. Apart from this, radio-isotopes tracer technique is also used to calibrate and validate these soil erosion and carbon models. Thus, integration of available advanced techniques could enhance the efficiency of adaptation and mitigation measures and deliver sustainable hilly and mountainous ecosystem.
References Arnold JG, Srinivasan R, Muttiah RS et al (1998) Large area hydrologic modeling and assessment part I: model development. J Am Water Resour Assoc 34:73–89. https://doi.org/10.1111/j. 1752-1688.1998.tb05961.x Bhattacharyya R, Ghosh B, Mishra P et al (2015) Soil degradation in India: challenges and potential solutions. Sustainability 7:3528–3570. https://doi.org/10.3390/su7043528 Blanco-Canqui H, Lal R (2010) Climate change and soil erosion risks. In: Principles of soil conservation and management. Springer, Dordrecht, pp 513–536 Blanco-Canqui H, Shapiro CA, Wortmann CS et al (2013) Soil organic carbon: the value to soil properties. J Soil Water Conserv 68:129A. https://doi.org/10.2489/jswc.68.5.129a Boix-Fayos C, de Vente J, Albaladejo J et al (2009) Soil carbon erosion and stock as affected by land use changes at the catchment scale in Mediterranean ecosystems. Agric Ecosyst Environ 133:75–85. https://doi.org/10.1016/j.agee.2009.05.013 Bookhagen B (2010) Appearance of extreme monsoonal rainfall events and their impact on erosion in the Himalaya. Geomatics Nat Hazards Risk 1:37–50. https://doi.org/10.1080/ 19475701003625737 Borrelli P, Alewell C, Alvarez P et al (2021) Soil erosion modelling: a global review and statistical analysis. Sci Total Environ 780:146–494. https://doi.org/10.1016/j.scitotenv.2021.146494 Chhabra A, Palria S, Dadhwal VK (2003) Soil organic carbon pool in Indian forests. For Ecol Manag 173(1–3):187–199
19
Advanced Techniques in Estimating Soil Erosion and Associated Carbon. . .
369
Choudhury BU, Fiyaz AR, Mohapatra KP et al (2015) Impact of land uses, agrophysical variables and altitudinal gradient on soil organic carbon concentration of north-eastern Himalayan region of India. Land Degrad Dev 27:1163–1174. https://doi.org/10.1002/ldr.2338 Coleman K, Jenkinson DS (1996) RothC-26.3—a model for the turnover of carbon in soil. In: Powlson DS, Smith P, Smith JU (eds) Evaluation of soil organic matter models using existing long-term datasets. Springer, Heidelberg, pp 237–246 David Raj A, Kumar S, Sooryamol KR (2022) Modelling climate change impact on soil loss and erosion vulnerability in a watershed of Shiwalik Himalayas. Catena 214:106–279. https://doi. org/10.1016/j.catena.2022.106279 Dhruvanarayana VV, Babu R (1983) Estimation of soil erosion in India. J Irrig Drain Eng 109(4): 419–434 Doetterl S, Berhe AA, Nadeu E et al (2016) Erosion, deposition and soil carbon: a review of process-level controls, experimental tools and models to address C cycling in dynamic landscapes. Earth Sci Rev 154:102–122. https://doi.org/10.1016/j.earscirev.2015.12.005 FAO et al (2009) Harmonized World soil database v1.1. FAO, Rome. http://www.fao.org/ docrep/018/aq361e/aq361e.pdf. Accessed 28 September 2022 Food and Agriculture Organization (2017) Voluntary guidelines for sustainable soil management. Food and Agriculture Organization of the United Nations, Rome Galy V, France-Lanord C, Beyssac O, Faure P, Kudrass H, Palhol F (2007) Efficient organic carbon burial in the Bengal fan sustained by the Himalayan erosional system. Nature 450(7168): 407–410 Gassman PW, Williams JR, Wang X, Saleh A, Osei E, Hauck L, Izaurralde R, Flowers J (2009) The agricultural policy environmental EXtender (APEX) model: an emerging tool for landscape and watershed environmental analyses. CARD Tech Rep 41:113 Kalambukkkattu JG, Kumar S, Hole RM (2021) Geospatial modelling of soil erosion and risk assessment in Indian Himalayan region—a study of Uttarakhand state. Environmen Adv 4:100039. https://doi.org/10.1016/j.envadv.2021.100039 Gupta S, Kumar S (2017) Simulating climate change impact on soil erosion using RUSLE model— a case study in a watershed of mid-Himalayan landscape. J Earth Syst Sci 126(3):1–20 Horton RE (1945) Erosional development of streams and their drainage basins; hydrophysical approach to quantitative morphology. Geol Soc Am Bull 56:275. https://doi.org/10.1130/00167606(1945)56[275:edosat]2.0.co;2 Hsieh YP (1992) A meshl-bag method for field assessment of soil erosion. J Soil Water Conserv 47(6):495–499 Kar SK, Kumar S, Sankar M et al (2022) Process-based modelling of soil erosion: scope and limitation in the Indian context. Curr Sci 122(5):533. https://doi.org/10.18520/cs/v122/i5/ 533-541 Kohnke H, Bertrand AR (1959) Soil conversation. McGraw, New York, p 298 Kothyari BP, Verma PK, Joshi BK, Kothyari UC (2004a) Rainfall–runoff-soil and nutrient loss relationships for plot size areas of Bhetagad watershed in central Himalaya, India. J Hydrol 293(1–4):137–150 Kothyari BP, Verma PK, Joshi BK et al (2004b) Rainfall–runoff-soil and nutrient loss relationships for plot size areas of Bhetagad watershed in central Himalaya, India. J Hydrol 293(1–4): 137–150. https://doi.org/10.1016/j.jhydrol.2004.01.011 Kumar S, Ghotekar YS, Dadhwal VK (2019) C-equivalent correction factor for soil organic carbon inventory by wet oxidation, dry combustion and loss on ignition methods in Himalayan region. Journal of Earth System Science 128:1–10 Kumar S, Kalambukattu JG (2022) Modeling and monitoring soil erosion by water using remote sensing satellite data and GIS. In: Bhunia GS, Chatterjee U, Lalmalsawmzauva K, Shit PK (eds) Anthropogeomorphology. Geography of the physical environment. Springer, Cham Kumar S, Singh RP, Kalambukattu JG (2021) Modeling daily surface runoff, sediment and nutrient loss at watershed scale employing ARC-Apex model interfaced with GIS: a case study in lesser
370
S. Kumar et al.
Himalayan landscape. Environ Earth Sci 80(15):1–17. https://doi.org/10.1007/s12665-02109791-4 Lal R (2005) Soil erosion and carbon dynamics. Soil Tillage Res 81:137–142. https://doi.org/10. 1016/j.still.2004.09.002 Longbottom TL, Townsend-Small A, Owen LA et al (2014) Climatic and topographic controls on soil organic matter storage and dynamics in the Indian Himalaya: potential carbon cycle–climate change feedbacks. Catena 119:125–135. https://doi.org/10.1016/j.catena.2014.03.002 Mandal D, Sharda VN (2011) Assessment of permissible soil loss in India employing a quantitative bio-physical model. Curr Sci:383–390 Mandal D, Giri N, Srivastava P et al (2019) 137Cs–a potential environmental marker for assessing erosion-induced soil organic carbon loss in India. Curr Sci 117(5):865 Mariappan S, Hartley IP, Cressey EL et al (2021) Soil burial reduces decomposition and offsets erosion-induced soil carbon losses in the Indian Himalaya. Glob Chang Biol 28:1643–1658. https://doi.org/10.1111/gcb.15987 Meena NK, Gautam R, Tiwari P et al (2017) Nutrient losses in soil due to erosion. J Pharmacogn Phytochem SP1:1009–1011 Mishra PK, Rai A, Abdelrahman K et al (2022) Land degradation, overland flow, soil erosion, and nutrient loss in the eastern Himalayas, India. Land 11(2):179. https://doi.org/10.3390/ land11020179 Montgomery DR (2007) Soil erosion and agricultural sustainability. Proc Natl Acad Sci 104 (33):13268–13272 Morgan RPC (2005) Soil Erosion and conservation, 3rd edn. Blackwell Publishing, Oxford. X + 304 pp. F29.95, paperback. ISBN 1-4051-1781-8 National Research Council (1986) Soil conservation: assessing the National resources inventory, vol 1. The National Academies Press, Washington, DC. https://doi.org/10.17226/647 Nearing MA, Romkens MJ, Norton LD et al (2000) Measurements and models of soil loss rates. Science 290:1300–1301. https://doi.org/10.1126/science.290.5495.1300b Nearing MA, Jetten V, Baffaut C et al (2005) Modeling response of soil erosion and runoff to changes in precipitation and cover. Catena 61:131–154. https://doi.org/10.1016/j.catena.2005. 03.007 Parsons AJ (2019) How reliable are our methods for estimating soil erosion by water? Sci Total Environ 676:215–221. https://doi.org/10.1016/j.scitotenv.2019.04.307 Parton WJ, Schimel DS, Cole CV et al (1987) Analysis of factors controlling soil organic matter levels in Great-Plains grasslands. Soil Sci Soc Am J 51:1173–1179. https://doi.org/10.2136/ sssaj1987.03615995005100050015x Potter SR, Andrews S, Atwood JD et al (2006) Model simulation of soil loss, nutrient loss, and change in soil organic carbon associated with crop production. US Department of Agriculture, Natural Resources Conservation Service, Washington DC. https://www.nrcs.usda.gov/Internet/ FSE_DOCUMENTS/nrcs143_013138.pdf. Accessed 29 Sept 2022 Renard KG, Foster GR, Weesies GA (1997) Predicting soil erosion by water: a guide to conservation planning with the revised universal soil loss equation (RUSLE). United States Department of Agriculture, Washington DC Rice CW, Pires CB, Lin J et al (2021) Soil organic carbon assessment methods. In: Soil health series, vol 38–51. American Society of Agronomy, Madison, WI. https://doi.org/10.1002/ 9780891189831.ch3 Sankar M, Green SM, Mishra PK, Snöälv JTC, Sharma NK, Karthikeyan K, Quine TA (2018) Nationwide soil erosion assessment in India using radioisotope tracers 137 Cs and 210 Pb. Curr Sci 115(3):388–390 Sartori M, Philippidis G, Ferrari E et al (2019) A linkage between the biophysical and the economic: assessing the global market impacts of soil erosion. Land Use Policy 86:299–312. https://doi. org/10.1016/j.landusepol.2019.05.014
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Advanced Techniques in Estimating Soil Erosion and Associated Carbon. . .
371
Singh DR, Gupta PN (1982) Assessment of siltation in Tehri reservoir. In: Proceedings of the international symposium on hydrological aspects of mountainous watersheds, vol 66. University of Roorkee, Roorkee, p VIII60 Sitaula B, Bajracharya R, Singh B et al (2004) Factors affecting organic carbon dynamics in soils of Nepal/Himalayan region—a review and analysis. Nutr Cycl Agroecosyst 70:215–229. https:// doi.org/10.1023/b:fres.0000048474.85331.7d Smith P, Soussana JF, Angers D et al (2020) How to measure, report and verify soil carbon change to realize the potential of soil carbon sequestration for atmospheric greenhouse gas removal. Glob Chang Biol 26(1):219–241 Sooryamol KR, Kumar S, Regina M et al (2022) Modelling climate change impact on soil erosion in a watershed of north-western lesser Himalayan region. J Sediment Environ 7:125–146. https:// doi.org/10.1007/s43217-022-00089-4 Walling DE, He Q (1997) Use of fallout 137cs in investigations of overbank sediment deposition on river floodplains. Catena 29:263–282. https://doi.org/10.1016/s0341-8162(96)00072-0 Walling DE, He Q (1999) Improved models for estimating soil erosion rates from cesium-137 measurements. J Environ Qual 28:611–622. https://doi.org/10.2134/jeq1999. 00472425002800020027x Williams JR (1990) The erosion-productivity impact calculator (EPIC) model: a case history. Phil Trans R Soc Lond B 329:421–428. https://doi.org/10.1098/rstb.1990.0184 Williams JR (1995) The EPIC model. In: Singh VP (ed) Computer models of watershed hydrology. Water Resources Publications, Highlands Ranch, pp 909–1000 Wischmeier WH, Smith DD (1965) Predicting rainfall-erosion losses from cropland east of the Rocky Mountains: guide for selection of practices for soil and water conservation. Agricultural Research Service, U.S. Dept of Agriculture in Cooperation with Purdue Agricultural Experiment Station, Washington, DC Wischmeier WH, Smith DD (1978) Predicting rainfall erosion losses: a guide to conservation planning. U.S. Dept. of Agriculture, Washington, DC Zhang JH, Wang Y, Li FC (2015) Soil organic carbon and nitrogen losses due to soil erosion and cropping in a sloping terrace landscape. Soil Res 53:87. https://doi.org/10.1071/sr14151
Soil Carbon Pools in Different Land Use Systems in the Indian Himalayan Region and Their Role in Climate Change Mitigation and Ecological Sustainability
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Shilky, Ratul Baishya, and Purabi Saikia
Abstract
Increasing anthropogenic disturbances in the Indian Himalayan mountains including forest degradation for extractive and intensive agriculture and fulfilling livelihood securities of local communities have become a major source of soil degradation and carbon (C) stock depletion in the region. The low-temperature conditions are prevalent in high-altitude mountain ecosystems, resulting in a reduced rate of litter decomposition and the addition of higher carbon values. Soil organic matter (SOM) substantially impacts productivity and resilience, improves soil quality, increases fertilizer input efficiency, reduces soil erosion and sedimentation, and reduces nonpoint source pollution in important terrestrial ecosystems. The increased total organic carbon (TOC) content in forest soil results from a considerable annual addition of organic matter (OM) in the form of leaf litter, which stays in the soil owing to the unavailability of disturbance and lack of annual tillage as in the case of agroecosystems. Trees are one of the world’s most cost-effective carbon sinks. Restoring tree cover through forest conservation and planting trees as a nature-based solution help in terms of carbon benefits and mitigating the risks and challenges of climate change. Assessing the soil quality of the Indian Himalayan regions (IHRs), especially the soil carbon pool, is critical for establishing future strategies for restoration and enhancing economic and ecological sustainability in the IHRs.
Shilky · P. Saikia (✉) Department of Environmental Sciences, Central University of Jharkhand, Ranchi, India e-mail: [email protected] R. Baishya Department of Botany, University of Delhi, Delhi, India # The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Mishra et al. (eds.), Soil Carbon Dynamics in Indian Himalayan Region, https://doi.org/10.1007/978-981-99-3303-7_20
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Keywords
Soil organic matter · Total organic carbon · Climate change · Sustainable ecosystem management
20.1
Introduction
The Indian Himalayan regions (IHRs) are represented by a forested landscape covering around 42% of the geographical area and account for one-third of India’s forest cover (Negi et al. 2019). However, the IHR’s significant reliance on forest resources, frequent forest fires, shifting agricultural practices, and land use changes (LUCs) have resulted in unprecedented forest degradation and biodiversity loss (Chakraborty et al. 2018). Furthermore, due to a large number of glaciers and glacial lakes, this region is very much prone to climate change (Sharma and Goyal 2020). The IHR’s principal land use system comprises forest, agriculture, horticulture, agrisilviculture, silvopasture, agri-horticulture, agri-horti-silviculture, and grassland (Singh et al. 2018). The vivid variation in altitude produces various patterns of vegetation types in the IHRs, including alluvial grasslands, subtropical forests, conifer mountain forests, and alpine meadows, which support significant prospects of carbon sequestration compared with other widespread regions of the country comprising specific types of vegetation (Rawat et al. 2021). The Himalayan dry temperate forests have a better ability to sequester carbon in comparison with the Himalayan moist temperate forests, subalpine forests, and montane wet temperate forests (Kumari et al. 2022). Increasing anthropogenic disturbances in the IHRs including forest degradation for intensive agriculture and fulfilling livelihood securities of native residents have become a major source of soil degradation and carbon stock depletion in the region (Kalambukattu et al. 2013). Long-term removal of carbon dioxide (CO2) from the atmosphere is made possible by sequestering carbon in the soil, which is a critical factor in decreasing the global warming rate (Gupta and Sharma 2011). However, activities involving land use changes (LUC) are regarded as one of the major causes of C loss from soil and vegetation with a significant impact on nitrogen (N) dynamics (Friedlingstein et al. 2019). Long-term use of extractive and intensive agricultural practices and the transformation of natural ecosystems like forests and grasslands to croplands and pasture lands cause erosion and deplete the soil organic carbon (SOC) pool over time (Lal 2004). SOC is an important part of the agroecosystem due to its function in the dynamics of greenhouse gases (GHGs) (Kirschbaum 2000). Forests fix more carbon than croplands or grasslands and have a higher C density (Zhou et al. 2011), and they can operate as a net carbon sink, absorbing 1.1 ± 0.8 pentagrams of C per year (Pan et al. 2011). The ability of a forest to store carbon depends on its type, its age, and the size class of the trees, with mature trees acting as long-term carbon pool repositories because they are more resilient (Day et al. 2014). The effects of altitude and climate on soil carbon storage predominated over plant type and landform at higher altitudes (>1700 m a.s.l.) (Rajput et al. 2015). However,
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Table 20.1 SOC in various land use systems of the Indian Himalayan regions Land use types At the depth of 50 cm Degraded lands Forests Horticulture Agriculture At the depth of 100 cm Plantation forests Agroforests Forests Herbaceous vegetation Tea plantation
Soil organic carbon (Mg C ha-1)
Sources
36.3 ± 4.40 47.5 ± 2.49 42.4 ± 2.92 35.1 ± 3.51
Sharma et al. (2014)
168.8 ± 74.4 162.3 ± 55.2 154.5 ± 72.9 134.1 ± 25.5 152.67 ± 9.98
Ahirwal et al. (2021)
Kalita et al. (2019)
the influence of the landform and the type of vegetation, whether naturally occurring like forests or artificially created like agriculture, outweighed the influence of the climate at lower altitudes (900–1700 m a.s.l.) (Martin et al. 2010). The conversion of native secondary forests to either settled or shifting agriculture has a significant negative impact on soil C loss because secondary forests can also store a good amount of C (Mukul et al. 2016). India stores ~15% of the CO2 emitted by fossil fuels per annum (Singh et al. 2010). Studies on various land use systems along an elevational gradient in the northwestern Himalayas reveal that orchards had the highest aboveground biomass (AGB) (75.64 Mg ha-1), while cereal cultivation had the highest belowground biomass (BGB) estimates (23.60 Mg ha-1) (Rajput et al. 2015). Similarly, the mean live tree total biomass density (TBD) and live tree total carbon density (TCD) in the moist temperate forests of the Garhwal Himalayas were 356.8 ± 83.0 Mg ha-1 and 178.4 ± 41.5 Mg C ha-1, respectively (Gairola et al. 2011). The highest CO2 mitigation potential was observed at an altitudinal range of 1900 to 2200 m (7.81 Mg ha-1 yr-1), while the highest C density of both soil and plant was at an altitudinal range of 1300–1600 m (90.88 Mg ha-1) (Rajput et al. 2015). However, in the eastern Himalayan forests, the total AGB variation is 279.25 ± 3.04 to 15.35 ± 7.38 Mg ha-1, whereas the total BGB varied from 144.76 ± 8.10 to 9.85 ± 4.82 Mg ha-1 and the total carbon content varied from 195.03 ± 2.32 to 11.59 ± 5.61 Mg C ha-1 (Rai et al. 2018) (Table 20.1).
20.2
Major Soil Carbon Pools
Soil organic matter (SOM) substantially impacts productivity and resilience advantages such as improved soil quality, increased fertilizer input efficiency, reduced soil erosion and sedimentation, and reduced nonpoint source pollution in important terrestrial ecosystems (Dahal and Bajracharya 2012). It is an important driver of ecosystem sustainability, and changes in SOM quality can occur in both total and active or labile C pools (Blair et al. 1995). The increased total organic
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carbon (TOC) content in forest soil results from a considerable annual addition of organic matter in the form of leaf litter, which stays in the soil owing to the unavailability of disturbance and lack of annual tillage as in the case of agroecosystems (Kalambukattu et al. 2013). The most common types of soil inorganic carbon (SIC) are carbonate minerals, found in lithogenic or pedogenic soil sources or generated when soil is formed (Blair et al. 1995). In dry and semiarid regions, this process is the primary method of SIC sequestration (Lal 2008), and the SIC pool contains roughly 950 Pg C (Eswaran et al. 2000). The function of SIC in reducing atmospheric CO2 and sequestration processes has not received much attention (Lal 2008), while soil organic carbon (SOC) is potentially a larger sink for atmospheric CO2 in the terrestrial pool and provides information on soil fertility and production (Sahoo et al. 2019). In agroecosystem soils, the SOC pool is severely depleted, especially in those that have experienced extensive damage from rapid erosion and other processes like salinization and nutrient depletion and need to be managed in an extractive manner (Köchy et al. 2015). The effects of tillage on the SOC pool vary depending on the type of soil; in some types of soil, it encourages decomposition by bringing organic carbon to the surface and promoting mineralization, while it dilutes SOC in the topsoil as a result of soil mixing between the subsurface and the surface layers (Renwick et al. 2004). The soil quality and production decline due to the depletion of the SOC pool (Lal 1999). Some soils have lost up to 30–35 Mg C ha-1; their root zone SOC content is below the critical/ threshold range of 1.5–2.0% (Lal et al. 2015), while in some severely degraded agricultural soils SOC concentration is less than 0.1% (Schnitzer and Monreal 2011). SOC is made up of several pools, including active, slow, and passive ones, with turnover rates that range from months to centuries (Silveira et al. 2008). The majority of the fresh plant and animal by-products, also referred to as the labile form of C, that make up the active SOC pool degrade within weeks to years and are associated with a lot of biological activities (Blair et al. 1995). The more quickly responsive forms of SOC, such as particulate organic C, water-soluble C, easily mineralizable C, quickly extractable C, carbohydrates, and microbial biomass C, are included in the labile C pool (Blair et al. 1995; Haynes 2005). The labile SOC pools are better indicators of soil quality, while the nonlabile SOC pools contribute to the indication of TOC stocks that remain in the soil for a longer period (Vieira et al. 2007; Chan et al. 2001). The nonlabile form of carbon, also known as humus or the passive SOC pool, could take several hundreds of years to decompose due to its lack of biological activity and low food supply for soil organisms (Haubensak et al. 2002). The slow SOC pool is located between the active and passive SOM and is typically composed of humus, which is relatively stable over time. Compared with active pools, slow SOM is more resistant to deterioration, and it may take several years to completely deteriorate (Schnitzer and Monreal 2011). Subsoil SOC saturation may be quite low, even though SOC concentrations in surface soils are typically higher than those at deeper depths (Kell 2012).
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Impacts of Land Use Change in Soil Carbon Pools
Regional trends in the Himalayan forest cover show that the IHRs are experiencing significant forest degradation (Ahirwal et al. 2021). For instance, the forest cover loss in the Garhwal Himalayas is 0.27% from 1998 to 2014 (Batar et al. 2017), while the primary forest cover loss in Sikkim Himalaya is 16% from 1990 to 2013. Similarly, the Western Himalayas lost 1115 km2 between 2011 and 2015 (Prasad 2019), and the Eastern Himalayas lost 5% of its forest cover and 32 km2 of statemanaged reserve forests from 2013 to 2017 (Sheth et al. 2020). The Himalayan foothills have been subjected to diverse anthropogenic pressures such as shifting agriculture, uncontrolled fire, agriculture, monoculture, plantation expansion, construction of dams, and fuelwood collection (Chitale and Behera 2019; Saikia et al. 2017). Since carbon stocks are dynamic, changes in land use, land use management, and climate have a significant impact on carbon stocks and their dynamics (Sakrabani and Hollis 2006). In the IHRs, LUC is particularly prevalent and causes a high rate of C mineralization in addition to higher soil CO2 emissions (Mishra et al. 2021). Intensive agricultural practices negatively impact the soil, such as the quick mineralization of SOC, leading to extra C conversion into soil air, raising atmospheric CO2 levels, and decreasing the soil C storage (Bhattacharya et al. 2016). Arable agriculture depletes soil carbon by removing a significant portion of photosynthetically fixed carbon and returning less plant litter due to the disruption of soil aggregates caused by agroforestry practices, which results in poor biological decomposition of OM, accelerated erosion, and removal of C-rich surface soil (Janzen 2006). The amount of soil microbial biomass increases when litter is added to the soil (Jin et al. 2010), and litter cover indirectly aids in moisture storage, hence increasing microbial activity (Feng et al. 2009). Degraded lands have poor microbial growth because there is not enough newly added organic matter to provide the energy substrate (C) that bacteria need to grow (Fontaine et al. 2007). In addition, land use and vegetation modifications also affect soil respiration and carbon fluxes, which reduce the amount of carbon in the atmosphere (Post and Kwon 2000). With proper crop management, more organic carbon may be stored in the soil, which will serve as a basis for reducing GHG emissions, improving crop production, and stabilizing yields (Pan et al. 2009). A well-developed deep root system, foliage cover, and litterfall result in a higher accumulation of organic matter in forest ecosystems as compared to agricultural land use (Choudhury et al. 2014). Furthermore, intensive agriculture heavily relies on agrochemicals, conventional tillage, farm machinery, and land use change to increase crop yield, which results in poor SOC and a sizable loss of biodiversity (Gardi et al. 2013). Changes in land use from natural ecosystems, like forests or grasslands, to agricultural systems are particularly prone to causing losses in SOC (Lal 1999). Agricultural soils have a high SOC storage level because dissolved organic carbon is moved by tillage and irrigation water application (Martin et al. 2010). Furthermore, hilltop soils with Quercus, Cedrus, and Rhododendron forests have superior carbon storage in the topmost layers at a depth of 0.3 m in comparison with comparable agricultural soils (Martin et al. 2010). Under identical land use conditions, the total carbon storage in soils on side slopes with a 25–33%
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slope gradient was significantly higher than the storage on slopes with an 8–15% gradient (Martin et al. 2010). Land use and vegetation changes contribute to carbon depletion in the atmosphere affecting soil respiration and carbon fluxes (Post and Kwon 2000). SOC in Mizoram’s natural forest ranged from 132.7 Mg C ha-1 in temperate forest to 44.2 Mg C ha-1 in jhum land at the soil depth of up to 30 cm, while it is also in the surface soil of the temperate forest (77.1 Mg C ha-1) and lowest in jhum land (23.8 Mg C ha-1) (Ahirwal et al. 2022). Land use and soil management techniques significantly influence the amount of microbial biomass in a pool (Kalambukattu et al. 2013). Therefore, the loss of soil organic carbon is strongly influenced by the shrinkage of forest areas (Lal 2002). The amount of carbon lost from the soil is attributed to LUC because the side slopes with significant land use changes had much higher carbon losses (20%) than the other land units, which indicates that changing land cover has a significant impact on climate in this physiographic context (Martin et al. 2010).
20.4
Role of Soil Carbon Pools in Climate Change Mitigation and Ecological Sustainability
Soil has a high capacity to store carbon and is the primary source of organic carbon for terrestrial systems on the Earth (Belay-Tedla et al. 2009). Depending on land use and the appropriate management practices, soil can also act as a source of various GHGs like CO2, methane (CH4), and nitrous oxide (N2O) or sink of CO2 and CH4 (Lal 1999). SOC is also regarded as a crucial indicator of soil fertility and environmental sustainability because the entire soil carbon pool, at a depth of 1 m, is ~2.68 times the biotic (560 Pg) stocks and 1.71 times the atmospheric (867 Pg) stocks (Lal 2018). Carbon and nitrogen sequestration in soil significantly reduces climate change (Gupta and Sharma 2011). It is critical to protect, maintain, and store SOC to address climate change, rising atmospheric CO2 concentration, and food insecurity issues (Rawat et al. 2021) because a 0.47-ppm increase in CO2 is equivalent to a 1-Pg decrease in the SOC storage (Rawat et al. 2021). Besides, soils are crucial carbon sinks globally as the top 1 m of soils stores between 1500 and 2400 Gt C (Sanderman et al. 2017). LUC is responsible for the estimated loss of 156 Pg C from soils worldwide during the past 150 years (Houghton 2003). Soil can operate as a carbon sink, and modest changes in the SOC pool could have large effects on the atmospheric concentration of CO2 (Guo and Gifford 2002). Labile carbon pools significantly impact soil health due to nutrient availability and microbiological transformations despite making up a small portion of the total carbon (Haubensak et al. 2002). Labile C pools are excellent markers of minute changes because of their quick turnover rates, which contribute to the flux of CO2 between soils and the atmosphere (Xia et al. 2010). In contrast, the nonlabile pool is a more stable and recalcitrant fraction of SOC that forms organic–mineral complexes with soil minerals and decomposes gradually through microbial activity (Wiesenberg et al. 2010).
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Sustainable Soil Management Practices
The National Action Plan on Climate Change (NAPCC) regarded IHRs as an essential ecoregion for preserving the nation’s ecological integrity as it is the storehouse of about 44% of India’s total forest biomass (FSI 2019). Therefore, the National Mission for Sustaining the Himalayan Ecosystem (NMSHE) was established with one of the main goals being to improve the carbon sink capacity of the Himalayan ecosystems (Ahirwal et al. 2021). According to the Kyoto Protocol, reforestation is vital to creating a soil C pool in terrestrial ecosystems (Lal 2008). Restoring tree cover through forest conservation and planting trees as a nature-based solution help in terms of carbon benefits and also help in mitigating the risks and challenges of climate change because trees are one of the world’s most affordable carbon sinks (Palmer 2021). Combining fruit trees with other multipurpose tree species, which can store carbon, has emerged as a viable option to reduce CO2 levels and protect the livelihood of nearby marginal farmers (Rawat et al. 2021). It has been shown that even small-scale conversion of agricultural fields to forests causes a considerable adjustment in the C budget (Dou et al. 2013). Because poor soil conditions make it difficult for natural regeneration, native tree species of tropical forests are less tolerant of soil degradation (Bhattacharya et al. 2016). Therefore, it is a common practice to use a selected few tolerant, fast-growing, exotic tree species, like Eucalyptus, Pinus, and Acacia, to restore damaged agricultural fields (Marliana and Rühe 2014). Trees that help with N fixation, like Acacia sp., are beneficial to the health of the soil, and therefore, the use of such plants is encouraged for this purpose (Cramer et al. 2010). Initiatives for reforestation may alter the amount of carbon in the microbial biomass of the soil at a depth of 0–20 cm (Liu et al. 2012). Different forestry practices, such as the length of the crop rotation and the timing of thinning, can alter the amount of carbon stored in vegetation (Baishya and Barik 2015). Similarly, agricultural management impacts organic matter turnover and soil feedback to global climate change (Singh and Benbi 2018). Moreover, several management techniques have also been recommended for improving soil C sequestration, including crop residue recycling, no-till farming, cover crop planting, improved nutrient management, and agricultural intensification (Powlson et al. 2011). Conservation tillage and agroforestry systems are thought to have significant potential for enhancing SOC storage in agricultural soils (Luo et al. 2010). Agro-management methods have been widely regarded as a promising solution for mitigating global climate change and addressing soil infertility (Srivastava et al. 2016). However, extensive use, harsh topography, climatic circumstances, and agricultural growth in the Himalayan ecosystem resulted in plant and soil degradation (Palni et al. 2001). Organic inputs play a crucial role in maintaining the soil C pool by replacing the SOC stock depleted by detrimental agricultural practices (Bhattacharya et al. 2016). However, the soil system can operate as one of the best sinks for capturing and subsequently reducing the concentrations of atmospheric GHGs, mainly CO2, and this is only possible through effective land use–specific C sequestration methods (Mujuru et al. 2013). Although soil stores C throughout the entire depth of its profile (Harper and Tibbett 2013), more than half of the SIC and SOC stocks are reported in
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subsoil layers below 0.3 m–1.0 m depth (Batjes 1996). Therefore, by implementing appropriate soil management practices, it may be possible to increase C sequestration within soil profiles (Rumpel 2014). Since mineral soils contain more than half of the forest SOC supply, belowground litter inputs in particular should be regulated in forests (Buchholz et al. 2014). However, it is unclear whether root litter input or macro-faunal activity is the main mechanism causing C sequestration in a stable form in mineral soil (Vesterdal et al. 2013). On the other hand, use changes, biomass removal, application of soil amendments, soil texture, plant species mix, frequent cutting, and climate conditions are the major factors that influence SOC sequestration capability in grasslands (Ammann et al. 2007), and grasslands have a higher potential for SOC sequestration than croplands (Lal et al. 2015).
20.6
Recommendations and Future Research Prospects
• Labile carbon pools appear to be more sensitive to land use than the soil’s innate characteristics. Therefore, appropriate management plans must be devised for the areas to stop deforestation, restore damaged soils, and establish more resilient agricultural systems. • SOC stock is vital for avoiding climate crises and the cycling of carbon. The highest SOC stock is found in the temperate forest of the eastern Himalayan region, which is greatly influenced by LULC, and this effect is exacerbated by the conversion of temperate forests to jhum land. Therefore, alternatives to jhum cultivation methods could be encouraged in the area to maintain the carbon stock. • There may be opportunities to create synergies between adaptation and mitigation efforts and potential nonclimate benefits in natural forests, agroforests, and other herbaceous ecosystems. • The most obvious way to stop the release of carbon into the atmosphere is to fix it in trees since forests serve as net carbon sinks. Proper scientific intervention may increase the capacity of forests to sequester carbon as some natural forests frequently store carbon at rates that are significantly below their natural rates. • Even though the biomass and carbon stocks of the IHRs have been the subject of several scientific investigations from the eastern to western extensions, there is a need to create methodologies for precise quantification rather than the traditional time-consuming approach. • We recommend a further study in the IHRs to boost their carbon sequestration potential by initiating restoration efforts. • It may be possible to lessen the effects of climate change and improve the soil and vegetation carbon pool of IHRs by identifying the Himalayan tree species with better carbon sequestration potential and introducing them in their natural habitat.
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Conclusion
The increased flux of CH4, N2O, and CO2 is the outcome of changing and intensifying land use to meet the requirements of the fast-rising human population. Increased biomass burning, soil cultivation, and an increase in animal populations have all been linked to this higher flux. Although considering the CO2 concentration and temperature, the IHRs appear to have a higher potential than other warm regions for increasing carbon sequestration in the vegetation and soils. The amount of CO2 in the atmosphere and the entire global carbon cycle could change even with minor changes in the SOC pool because soil stores three times as much carbon as the global atmospheric carbon pool and twice as much as the global biotic carbon pool. Increasing SOC, ensuring its depth-wise distribution, and stabilizing it within stable micro-aggregates are the main objectives of the carbon sequestration strategy to safeguard the carbon from microbial processes that might otherwise lose it through the decomposition of organic matter. A critical component of such a strategy is the application of best management practices. This is especially important for tree systems where the carbon stocks must be increased to preserve them for a longer period. In addition, it highlights the variations in the ability of various forest types to sequester carbon, making it possible to conserve and eventually reduce global carbon emissions for forest types with higher carbon sequestering potential and prolonged rotation periods. However, the low-temperature conditions prevalent in the Himalayan forests due to the high altitude may result in a reduced litter decomposition rate, contributing to greater carbon levels. Soil quality assessment of the IHRs, especially the soil carbon pool, is critical for establishing future strategies for restoration and enhancing economic and ecological sustainability in the IHRs.
References Ahirwal J, Nath A, Brahma B, Deb S, Sahoo UK, Nath AJ (2021) Patterns and driving factors of biomass carbon and soil organic carbon stock in the Indian Himalayan region. Sci Total Environ 770:145292 Ahirwal J, Gogoi A, Sahoo UK (2022) Stability of soil organic carbon pools affected by land use and land cover changes in forests of eastern Himalayan region, India. Catena 215:106308 Ammann C, Flechard CR, Leifeld J, Neftel A, Fuhrer J (2007) The carbon budget of newly established temperate grassland depends on management intensity. Agric Ecosyst Environ 121(1–2):5–20 Baishya R, Barik SK (2015) Ecosystem level carbon and net primary productivity of an old-growth and a regenerating humid tropical forest of north-eastern India. Int J Plant Environ 1(1):85–98 Batar AK, Watanabe T, Kumar A (2017) Assessment of land-use/land-cover change and forest fragmentation in the Garhwal Himalayan region of India. Environments 4(2):34 Batjes NH (1996) Total carbon and nitrogen in the soils of the world. Eur J Soil Sci 47(2):151–163 Belay-Tedla A, Zhou X, Su B, Wan S, Luo Y (2009) Labile, recalcitrant, and microbial carbon and nitrogen pools of a tallgrass prairie soil in the US Great Plains subjected to experimental warming and clipping. Soil Biol Biochem 41(1):110–116
382
Shilky et al.
Bhattacharya SS, Kim KH, Das S, Uchimiya M, Jeon BH, Kwon E, Szulejko JE (2016) A review of the role of organic inputs in maintaining the soil carbon pool of the terrestrial ecosystem. J Environ Manag 167(1):214–227 Blair GJ, Lefroy RD, Lisle L (1995) Soil carbon fractions based on their degree of oxidation, and the development of a carbon management index for agricultural systems. Aust J Agric Res 46(7):1459–1466 Buchholz T, Friedland AJ, Hornig CE, Keeton WS, Zanchi G, Nunery J (2014) Mineral soil carbon fluxes in forests and implications for carbon balance assessments. GCB Bioenergy 6(4): 305–311 Chakraborty A, Joshi PK, Sachdeva K (2018) Capturing forest dependency in the central Himalayan region: variations between oak (Quercus spp.) and pine (Pinus spp.) dominated forest landscapes. Ambio 47(4):504–522 Chan KY, Bowman A, Oates A (2001) Oxidizible organic carbon fractions and soil quality changes in an oxicpaleustalf under different pasture leys. Soil Sci 166(1):61–67 Chitale V, Behera MD (2019) How will forest fires impact the distribution of endemic plants in the Himalayan biodiversity hotspot? Biodivers Conserv 28(8):2259–2273 Choudhury BU, Fiyaz AR, Mohapatra KP, Ngachan S (2014) Impact of land uses, agrophysical variables and altitudinal gradient on soil organic carbon concentration of north-eastern Himalayan region of India. Land Degrad Dev 27(4):1163–1174 Cramer MD, Van Cauter A, Bond WJ (2010) Growth of N2-fixing African savanna acacia species is constrained by below-ground competition with grass. J Ecol 98(1):156–167 Dahal N, Bajracharya RM (2012) Effects of sustainable soil management practices on distribution of soil organic carbon in upland. Agricultural soils of mid-hills of Nepal. Nepal J Sci Technol 13(1):133–141 Day M, Baldauf C, Rutishauser E, Sunderland TC (2014) Relationships between tree species diversity and above-ground biomass in central African rainforests: implications for REDD. Environ Conserv 41(1):64–72 Dou H, Jiang G, Stott P, Piao R (2013) Climate change impacts population dynamics and the distribution shift of moose (Alces alces) in the Heilongjiang Province of China. Ecol Res 28(4): 625–632 Eswaran H, Reich PF, Kimble JM, Beinroth FH, Padmanabhan E, Moncharoen P (2000) Global carbon stocks. In: Lal R, Kimble JM, Eswaran H, Stewart BA (eds) Global climate change and pedogenic carbonates. Taylor, and Francis Publishing, Delhi, pp 15–25 Feng W, Zou X, Schaefer D (2009) Above-and belowground carbon inputs affect seasonal variations of soil microbial biomass in a subtropical monsoon forest of Southwest China. Soil Biol Biochem 41(5):978–983 Fontaine S, Barot S, Barré P, Bdioui N, Mary B, Rumpel C (2007) Stability of organic carbon in deep soil layers controlled by fresh carbon supply. Nature 450(7167):277–280 Friedlingstein P, Jones MW, O'sullivan M, Andrew RM, Hauck J, Peters GP et al (2019) Global carbon budget 2019. Earth Syst Sci Data 11(4):1783–1838 FSI (2019) India state of forest report. Forest Survey of India, Ministry of Environment, Forest and Climate Change, Government of India, Dehradun Gairola S, Sharma CM, Ghildiyal SK, Suyal S (2011) Live tree biomass and carbon variation along an altitudinal gradient in moist temperate valley slopes of the Garhwal Himalaya (India). Curr Sci 100(12):1862–1870 Gardi C, Jeffery S, Saltelli A (2013) An estimate of potential threat levels to soil biodiversity in EU. Glob Chang Biol 19(5):1538–1548 Guo LB, Gifford RM (2002) Soil carbon stocks and land use change: a meta-analysis. Glob Chang Biol 8(4):345–360 Gupta MK, Sharma SD (2011) Sequestrated carbon: organic carbon pool in the soils under different forest covers and land uses in the Garhwal Himalayan region of India. Int J Agric For 1(1): 14–20
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Soil Carbon Pools in Different Land Use Systems in the Indian. . .
383
Harper RJ, Tibbett M (2013) The hidden organic carbon in deep mineral soils. Plant Soil 368(1): 641–648 Haubensak KA, Hart SC, Stark JM (2002) Influences of chloroform exposure time and soil water content on C and N release in forest soils. Soil Biol Biochem 34(11):1549–1562 Haynes RJ (2005) Labile organic matter fractions as central components of the quality of agricultural soils: an overview. Adv Agron 85:221268 Houghton RA (2003) Revised estimates of the annual net flux of carbon to the atmosphere from changes in land use and land management 1850–2000. Tellus B 55(2):378–390 Janzen HH (2006) The soil carbon dilemma: shall we hoard it or use it? Soil Biol Biochem 38(3): 419–424 Jin H, Sun OJ, Liu J (2010) Changes in soil microbial biomass and community structure with addition of contrasting types of plant litter in a semiarid grassland ecosystem. J Plant Ecol 3(3): 209–217 Kalambukattu JG, Singh R, Patra AK, Arunkumar K (2013) Soil carbon pools and carbon management index under different land use systems in the central Himalayan region. Acta Agric Scand B Soil Plant Sci 63(3):200–205 Kalita RM, Das AK, Nath AJ (2019) Role of smallholder tea growers in carbon sink management. Curr Sci 116(9):1560–1566 Kell DB (2012) Large-scale sequestration of atmospheric carbon via plant roots in natural and agricultural ecosystems: why and how. Philos Trans R Soc B: Biol Sci 367(1595):1589–1597 Kirschbaum MU (2000) Will changes in soil organic carbon act as a positive or negative feedback on global warming? Biogeochemistry 48(1):21–51 Köchy M, Hiederer R, Freibauer A (2015) Global distribution of soil organic carbon–part 1: masses and frequency distributions of SOC stocks for the tropics, permafrost regions, wetlands, and the world. Soil 1(1):351–365 Kumari R, Kumar A, Saikia P, Khan ML (2022) Vulnerability assessment of Indian Himalayan forests in terms of biomass production and carbon sequestration potential in changing climatic conditions. In: Lackner M, Sajjadi B, Chen WY (eds) Handbook of climate change mitigation and adaptation, 3rd edn. Springer Nature, Switzerland AG, pp 147–161 Lal R (1999) Soil management and restoration for C sequestration to mitigate the accelerated greenhouse effect. Prog Environ Sci 1(4):307–326 Lal R (2002) Soil carbon dynamics in cropland and rangeland. Environ Pollut 116(3):353–362 Lal R (2004) Soil carbon sequestration to mitigate climate change. Geoderma 123(1–2):1–22 Lal R (2008) Carbon sequestration. Philos Trans R Soc B: Biol Sci 363(1492):815–830 Lal R (2018) Digging deeper: a holistic perspective of factors affecting soil organic carbon sequestration in agroecosystems. Glob Chang Biol 24(8):3285–3301 Lal R, Negassa W, Lorenz K (2015) Carbon sequestration in soil. Curr Opin Environ Sustain 15: 79–86 Liu Y, Wei X, Guo X, Niu D, Zhang J, Gong X, Jiang Y (2012) The long-term effects of reforestation on soil microbial biomass carbon in sub-tropic severe red soil degradation areas. For Ecol Manag 285:77–84 Luo Z, Wang E, Sun OJ (2010) Soil carbon change and its responses to agricultural practices in Australian agro-ecosystems: a review and synthesis. Geoderma 155:211 Marliana SN, Rühe F (2014) Post-reforestation vegetation development on abandoned highland fields in Java, Indonesia. For Ecol Manag 328:245–253 Martin D, Lal T, Sachdev CB, Sharma JP (2010) Soil organic carbon storage changes with climate change, landform and land use conditions in Garhwal hills of the Indian Himalayan mountains. Agric Ecosyst Environ 138(1–2):64–73 Mishra U, Hugelius G, Shelef E, Yang Y, Strauss J, Lupachev A et al (2021) Spatial heterogeneity and environmental predictors of permafrost region soil organic carbon stocks. Sci Adv 7(9): eaaz 5236
384
Shilky et al.
Mujuru L, Mureva A, Velthorst EJ, Hoosbeek MR (2013) Land use and management effects on soil organic matter fractions in Rhodic Ferralsols and Haplic Arenosols in Bindura and Shamva districts of Zimbabwe. Geoderma 209:262–272 Mukul SA, Herbohn J, Firn J (2016) Tropical secondary forests regenerating after shifting cultivation in the Philippines uplands are important carbon sinks. Sci Rep 6(1):1–12 Negi VS, Pathak R, Rawal RS, Bhatt ID, Sharma S (2019) Long-term ecological monitoring on forest ecosystems in Indian Himalayan region: criteria and indicator approach. Ecol Indic 102: 374–381 Palmer L (2021) How trees and forests reduce risks from climate change. Nat Clim Chang 11:374– 377 Palni LMS, Maikhuri RK, Rao KS (2001) Conservation of the Himalayan agroecosystems: issues and priorities. In: Economy of Uttarakhand: profile and dynamics of change. Anamika publishers, New Delhi, pp 135–176 Pan G, Zhou P, Li Z, Smith P, Li L, Qiu D et al (2009) Combined inorganic/organic fertilization enhances N efficiency and increases rice productivity through organic carbon accumulation in a rice paddy from the tai Lake region, China. Agric Ecosyst Environ 131(3–4):274–280 Pan Y, Birdsey RA, Fang J, Houghton R, Kauppi PE, Kurz WA et al (2011) A large and persistent carbon sink in the world’s forests. Science 333(6045):988–993 Post WM, Kwon KC (2000) Soil carbon sequestration and land-use change: processes and potential. Glob Chang Biol 6(3):317–327 Powlson DS, Whitmore AP, Goulding KW (2011) Soil carbon sequestration to mitigate climate change: a critical re-examination to identify the true and the false. Eur J Soil Sci 62(1):42–55 Prasad S (2019) Diminishing forest area in the Western Himalaya: apprehensions for the loss of vital biodiversity. Curr Sci 116(2):170 Rai S, Pandey A, Badola HK (2018) Biomass and carbon stock estimation across the timberline of Khangchendzonga National Park, Eastern Himalaya, India. Taiwania 63(4):311–320 Rajput BS, Bhardwaj DR, Pala NA (2015) Carbon dioxide mitigation potential and carbon density of different land use systems along an altitudinal gradient in North-Western Himalayas. Agrofor Syst 89(3):525–536 Rawat D, Sati SP, Khanduri VP, Riyal M, Mishra G (2021) Carbon sequestration potential of different land use sectors of Western Himalaya. In: Pant D, Kumar NA, Pant KK, Agarwal AK (eds) Advances in carbon capture and utilization. Springer, Singapore, pp 273–294 Renwick WH, Smith SV, Sleezer RO, Buddemeier RW (2004) Comment on “managing soil carbon”(ii). Science 305(5690):1567–1567 Rumpel C (2014) Opportunities and threats of deep soil organic matter storage. Carbon Manag 5(2): 115–117 Sahoo UK, Singh SL, Gogoi A, Kenye A, Sahoo SS (2019) Active and passive soil organic carbon pools as affected by different land use types in Mizoram, Northeast India. PloS One 14(7): e0219969 Saikia P, Deka J, Bharali S, Kumar A, Tripathi OP, Singha LB, Dayanandan S, Khan ML (2017) Plant diversity patterns and conservation status of eastern Himalayan forests in Arunachal Pradesh, Northeast India. For Ecosyst 4:28 Sakrabani R, Hollis J (2006) Predicting changes in soil organic carbon in different land uses for England and Wales under current and future climatic conditions using CENTURY 5. In: Abstracts 18th World congress of soil science. International Union of Soil Sciences (IUSS), USA, synthesis, modeling, and applications of disciplinary soil science knowledge for soilwater-plant-environment systems paper pp 70–5 Sanderman J, Hengl T, Fiske GJ (2017) Soil carbon debt of 12,000 years of human land use. Proc Natl Acad Sci 114(36):9575–9580 Schnitzer M, Monreal CM (2011) Quo vadis soil organic matter research? A biological link to the chemistry of humification. Adv Agron 113:143–217 Sharma A, Goyal MK (2020) Assessment of the changes in precipitation and temperature in Teesta River basin in Indian Himalayan region under climate change. Atmos Res 231:104670
20
Soil Carbon Pools in Different Land Use Systems in the Indian. . .
385
Sharma V, Hussain S, Sharma KR, Arya VM (2014) Labile carbon pools and soil organic carbon stocks in the foothill Himalayas under different land use systems. Geoderma 232:81–87 Sheth C, Datta A, Parashuram D (2020) Persistent loss of biologically-rich tropical forests in the Indian eastern Himalaya. Silva Fenn 54:1–16 Silveira ML, Comerford NB, Reddy KR, Cooper WT, El-Rifai H (2008) Characterization of soil organic carbon pools by acid hydrolysis. Geoderma 144(1–2):405–414 Singh P, Benbi DK (2018) Soil organic carbon pool changes in relation to slope position and landuse in Indian lower Himalayas. Catena 166:171–180 Singh SP, Singh V, Skutsch M (2010) Rapid warming in the Himalayas: ecosystem responses and development options. Clim Dev 2(3):221–232 Singh R, Bhardwaj DR, Pala NA, Kaushal R, Rajput BS (2018) Soil microbial characteristics in sub-tropical agro-ecosystems of North Western Himalaya. Curr Sci 115(10):1956–1959 Srivastava P, Singh R, Tripathi S, Singh H, Raghubanshi AS (2016) Soil carbon dynamics and climate change: current agro-environmental perspectives and future dimensions. Energy Ecol Environ 1(5):315–322 Vesterdal L, Clarke N, Sigurdsson BD, Gundersen P (2013) Do tree species influence soil carbon stocks in temperate and boreal forests? For Ecol Manag 309:4–18 Vieira FCB, Bayer C, Zanatta JA, Dieckow J, Mielniczuk J, He ZL (2007) Carbon management index based on physical fractionation of soil organic matter in an acrisol under long-term no-till cropping systems. Soil Tillage Res 96(1–2):195–204 Wiesenberg GL, Dorodnikov M, Kuzyakov Y (2010) Source determination of lipids in bulk soil and soil density fractions after four years of wheat cropping. Geoderma 156(3–4):267–277 Xia XU, Xiaoli C, Yan Z, Yiqi LUO, Honghua R, Jiashe W (2010) Variation of soil labile organic carbon pools along an elevational gradient in the Wuyi Mountains, China. J Res Ecol 1(4): 368–374 Zhou L, Dai L, Wang S, Huang X, Wang X, Qi L et al (2011) Changes in carbon density for three old-growth forests on Changbai Mountain, Northeast China: 1981–2010. Ann For Sci 68(5): 953–958