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Klaus Lorenz Rattan Lal
Organic Agriculture and Climate Change
Organic Agriculture and Climate Change
Klaus Lorenz • Rattan Lal
Organic Agriculture and Climate Change
Klaus Lorenz CFAES Rattan Lal Center for Carbon Management and Sequestration The Ohio State University Columbus, OH, USA
Rattan Lal CFAES Rattan Lal Center for Carbon Management and Sequestration The Ohio State University Columbus, OH, USA
ISBN 978-3-031-17214-4 ISBN 978-3-031-17215-1 (eBook) https://doi.org/10.1007/978-3-031-17215-1 © Springer Nature Switzerland AG 2023 This work is subject to copyright. All rights are reserved 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 Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
Preface
Humans have increasingly altered and managed terrestrial ecosystems for agricultural land use and food production beginning thousands of years ago. Now, agriculture is the dominant global land use with about 40% of the ice-free land surface used for agricultural practices, and much of cropland has replaced forests, savannas, and grasslands. This has profound effects on the global climate through losses in soil organic carbon (SOC) and emissions of the greenhouse gases (GHGs), carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), as well as on the regional climate by biogeophysical and biogeochemical effects. In 2015, food-system emissions represented 34% of total GHG emissions with the largest contribution from agriculture and land use/land-use change activities (71%). Other than climate impacts, concerns have emerged over the last decades with regard to negative effects of increasing use of synthetic fertilizers and pesticides, and genetically modified organisms (GMOs) often on industrial-scale farms, ranches, and orchards. Increasing concerns regarding the status of the environment and food quality have contributed to an increasing demand for agricultural products produced by organic agriculture (OA) without the use of synthetic fertilizers, pesticides, and GMOs. Currently, about 1.6% of the global agricultural land area is managed by OA practices, and the percentage of land under OA is increasing. In the twentieth century, pioneers such as Rudolf Steiner, Sir Albert Howard, Lady Eve Balfour, Jerome Irving Rodale, and Masanobu Fukuoka developed OA systems in reaction to perceived failures of “conventional” agriculture. However, the net effect of OA on the climate compared to that of conventional practices is uncertain. The SOC stocks may benefit in one OA field from livestock manure application but often at the expense of the SOC stock at another field as livestock manure derived from plant biomass, i.e., atmospheric CO2 may be transferred laterally from another field, and, thus, not contribute to genuine carbon (C) sequestration. Further, the SOC stock may decrease under OA management as tillage is commonly applied for weed control. Worryingly, average crop yields under OA at experimental plots are between 19% and 25% lower than those under conventional management although with a high variability. This would mean that increasing OA production, such as that proposed by the European Green Deal aimed at having 25% of European Union’s agricultural land farmed by OA practices v
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by 2030, needs relatively more land area than that under conventional practices to maintain equal overall yield. This needed additional agricultural area will exacerbate climate change when C-rich tropical rainforests are converted and cultivated to compensate for the OA yield losses. Instead, site-specific OA and conventional practices should be combined to reduce overall climate impacts of agricultural production and food systems. This may include lessen climate impacts of conventional agriculture by replacing some of the synthetic nitrogen (N) fertilizer with less GHGintensive manure and management of biological nitrogen fixation (BNF). Allowing some level of mineral N fertilization would ensure that soils under OA practices are not becoming N-deficient. Enhancing soil health by combining OA with conventional practices may potentially reduce the need for adding climate-negative external inputs. Composite or integrated farming systems combining best OA and conventional practices are promising regarding their ability to reduce energy use and global warming potential (GWP). Modern technologies taking advantage of scientific discoveries should be applied in both OA and conventional systems to reduce climate effects of food production. Conventionalization of OA by increasing adopting features of conventional modes of production based on industrial farming methods can also potentially reduce climate impacts. Regenerative agriculture (RA) combining OA with conventional practices enhances ecological processes which may reduce climate effects of agriculture. Overall, both OA and conventional practices are continuously evolving, and rather than adhesion to fixed sets of practices and principles, climate-positive agricultural practices beyond the conventionalorganic divide should be developed towards site-specific implementation. This book presents an introduction to the history of OA, its recent developments, and its practices and principles. The effects of OA practices on the SOC and soil inorganic carbon (SIC) stocks, and on GHG emissions are discussed subsequently. The often-overlooked biogeophysical and biogeochemical effects of agricultural land use on the climate are also presented. The book concludes with a chapter on how a combination of OA with conventional practices may contribute to lessen the total impact of agriculture and food systems on the global climate. This book is unique as it discusses the contribution of OA to sequestration of atmospheric CO2 in soil and its potential for reducing emissions of GHGs, while also outlining weaknesses of OA and knowledge gaps in the context of climate change. We want to thank all farmers, ranchers, and researchers around the globe who contribute to improving our understanding of the climate impact of agricultural practices as the basis for identifying climate-positive and soil C sequestering practices. This project was supported through funding support to the CFAES Rattan Lal Center for Carbon Management and Sequestration (C-MASC) from the Office of Research of the Ohio State University. Columbus, OH, USA
Klaus Lorenz
Columbus, OH, USA June 2022
Rattan Lal
Contents
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Introduction to Organic Agriculture������������������������������������������������������ 1 1.1 History and Current Organic Agriculture Land Use ������������������������ 2 1.1.1 Early Developments�������������������������������������������������������������� 7 1.1.2 Developments after Second World War�������������������������������� 12 1.1.3 Current Organic Agricultural Land Use�������������������������������� 19 1.1.4 Expansion of Organic Agriculture���������������������������������������� 21 1.2 Practices and Principles�������������������������������������������������������������������� 22 1.3 Conclusions�������������������������������������������������������������������������������������� 30 1.4 Review Questions����������������������������������������������������������������������������� 31 References�������������������������������������������������������������������������������������������������� 31
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Effects of Organic Agriculture on the Soil Carbon Stock�������������������� 39 2.1 Basic Principles of Soil Carbon Sequestration �������������������������������� 40 2.1.1 Soil Carbon �������������������������������������������������������������������������� 40 2.1.2 Soil Carbon Sequestration���������������������������������������������������� 42 2.2 Soil Inorganic Carbon ���������������������������������������������������������������������� 50 2.2.1 Effects of Organic Agriculture Practices on Soil Inorganic Carbon������������������������������������������������������ 53 2.2.2 Soil Inorganic Carbon Stocks under Organic Agriculture�������������������������������������������������������������� 55 2.3 Soil Organic Carbon������������������������������������������������������������������������� 56 2.3.1 Effects of Organic Agriculture Practices on Soil Organic Carbon�������������������������������������������������������� 71 2.3.2 Soil Organic Carbon Stocks Under Organic Agriculture�������������������������������������������������������������� 94 2.4 Net Effect of Organic Agriculture on Soil Carbon Sequestration������������������������������������������������������������������������ 100 2.5 Conclusions�������������������������������������������������������������������������������������� 102 2.6 Review Questions����������������������������������������������������������������������������� 103 References�������������������������������������������������������������������������������������������������� 103
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Organic Agriculture and Greenhouse Gas Emissions�������������������������� 129 3.1 Introduction�������������������������������������������������������������������������������������� 130 3.2 Carbon Dioxide�������������������������������������������������������������������������������� 137 3.2.1 Fossil Fuel Combustion�������������������������������������������������������� 138 3.2.2 Soil Carbon Dioxide Emissions�������������������������������������������� 138 3.3 Methane�������������������������������������������������������������������������������������������� 142 3.3.1 Soil Methane Fluxes ������������������������������������������������������������ 143 3.3.2 Methane Emissions from Livestock Production ������������������ 145 3.3.3 Methane Emissions from Biomass Burning ������������������������ 147 3.4 Nitrous Oxide������������������������������������������������������������������������������������ 147 3.4.1 Soil Nitrous Oxide Emissions���������������������������������������������� 148 3.4.2 Nitrous Oxide Emissions by Livestock Production Systems�������������������������������������������������������������� 156 3.5 The Hidden Carbon Cost of Organic Agriculture Practices�������������� 157 3.6 Conclusions�������������������������������������������������������������������������������������� 163 3.7 Review Questions����������������������������������������������������������������������������� 163 References�������������������������������������������������������������������������������������������������� 164
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Biogeophysical and Biogeochemical Climate Effects of Organic Agriculture���������������������������������������������������������������������������� 177 4.1 Introduction�������������������������������������������������������������������������������������� 178 4.2 Surface Albedo���������������������������������������������������������������������������������� 180 4.3 Land Energy Balance������������������������������������������������������������������������ 183 4.4 Soil Temperature ������������������������������������������������������������������������������ 184 4.5 Evapotranspiration���������������������������������������������������������������������������� 185 4.6 Soil Moisture Regime ���������������������������������������������������������������������� 187 4.7 Soil Erodibility and Erosion������������������������������������������������������������� 189 4.8 Surface Roughness���������������������������������������������������������������������������� 191 4.9 Land-Derived Aerosols �������������������������������������������������������������������� 192 4.10 Conclusions�������������������������������������������������������������������������������������� 195 4.11 Review Questions����������������������������������������������������������������������������� 195 References�������������������������������������������������������������������������������������������������� 196
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Combining Conventional and Organic Practices to Reduce Climate Impacts of Agriculture�������������������������������������������� 201 5.1 Introduction�������������������������������������������������������������������������������������� 202 5.2 Nitrogen Fertilization������������������������������������������������������������������������ 204 5.3 Soil Health���������������������������������������������������������������������������������������� 205 5.4 Integrated Farming���������������������������������������������������������������������������� 207 5.5 Conventionalization of Organic Agriculture ������������������������������������ 207 5.6 Regenerative Agriculture������������������������������������������������������������������ 209 5.7 Agroecology�������������������������������������������������������������������������������������� 211 5.8 Nexus Approach�������������������������������������������������������������������������������� 214 5.9 Conclusions�������������������������������������������������������������������������������������� 215 5.10 Review Questions����������������������������������������������������������������������������� 216 References�������������������������������������������������������������������������������������������������� 216
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Challenges and Opportunities for the Global Food System���������������� 219 6.1 Population Growth and Food Production������������������������������������������ 220 6.2 Urbanization and Food���������������������������������������������������������������������� 222 6.3 Future Research and Developments�������������������������������������������������� 225 6.4 Conclusions�������������������������������������������������������������������������������������� 229 6.5 Review Questions����������������������������������������������������������������������������� 229 References�������������������������������������������������������������������������������������������������� 230
About the Authors
Klaus Lorenz, PhD, is a senior research associate and assistant director of the CFAES Rattan Lal Center for Carbon Management and Sequestration at The Ohio State University (OSU), Columbus, Ohio, USA. He is an experienced soil scientist with research interests in soil organic carbon, and management of soil for climate change adaptation and mitigation. He received a diploma in biology from the University of Freiburg, Germany (1997), and a PhD in agricultural sciences from the University of Hohenheim, Germany (2001). He served as chief soil scientist at the Institute for Advanced Sustainability Studies e.V. in Potsdam, Germany (2011–2014) and as a postdoctoral researcher/research scientist at OSU (2004 to date). He has written books about carbon sequestration in forest and in agricultural ecosystems, soil organic carbon sequestration in terrestrial biomes of the United States, and co-edited books on recarbonization of the biosphere, and on ecosystem services and carbon sequestration in the biosphere. Rattan Lal, PhD, is Distinguished University Professor of Soil Science and director of the CFAES Rattan Lal Center for Carbon Management and Sequestration at The Ohio State University (OSU), Columbus, Ohio, USA, and adjunct professor at the University of Iceland and the Indian Agricultural Research Institute, India. He obtained his BS from Punjab Agricultural University, Ludhiana, India (1963); MS from Indian Agricultural Research Institute, New Delhi, India (1965); and PhD from OSU (1968). He is chair in soil science and Goodwill Ambassador for Sustainability Issues for the Inter-American Institute for Cooperation on Agriculture. Dr. Lal is laureate of the GCHERA World Agriculture Prize (2018), Glinka World Soil Prize (2018), Japan Prize (2019), U.S. Awasthi IFFCO Prize (2019), Arrell Global Food Innovation Award (2020), World Food Prize (2020), and Padma Shri Award (2021). He has authored/co-authored more than 1000 journal articles and more than 550 book chapters, and has written and edited/co-edited more than 100 books.
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Chapter 1
Introduction to Organic Agriculture
Contents 1.1 History and Current Organic Agriculture Land Use 1.1.1 Early Developments 1.1.2 Developments after Second World War 1.1.3 Current Organic Agricultural Land Use 1.1.4 Expansion of Organic Agriculture 1.2 Practices and Principles 1.3 Conclusions 1.4 Review Questions References
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Abstract Increasing concerns regarding the status of the environment and food quality contribute to an increasing demand for agricultural products produced by organic agriculture (OA). About 1.6% of the global agricultural land area is currently managed by OA practices. In the twentieth century, pioneers such as Rudolf Steiner, Sir Albert Howard, Lady Eve Balfour, Jerome Irving Rodale and Masanobu Fukuoka developed OA systems in reaction to perceived failures of conventional or nonorganic agriculture. Early types of OA included bio-dynamic, natural, biological, ecological and organic-biological agriculture. The International Federation of Organic Agriculture Movements (IFOAM) provides a definition of modern OA. However, there is no single interpretation of what OA practices and principles entail, and OA production systems continue to evolve. Among common OA practices are fertilization with organic instead of mineral fertilizers, use of natural- derived instead of synthetic plant protection products, and mechanical instead of chemical crop system management. Importantly, OA is the only farming system whose management practices are codified by law in most countries. However, OA is faced with several challenges such as the 19–25% lower crop yield compared to that under conventional or nonorganic practices, the lack of animal and green manure produced on OA farms to satisfy the demand at other OA farms, and lack of plant and animal varieties specifically adapted to OA soil and land-use management
© Springer Nature Switzerland AG 2023 K. Lorenz, R. Lal, Organic Agriculture and Climate Change, https://doi.org/10.1007/978-3-031-17215-1_1
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p ractices. Increased efforts are, thus, needed to improve the contribution of OA systems to environmental health as consumer demand for OA products continues to rise globally. Keywords Land use and land cover change · Organic agriculture land use · Health benefits · Nutritional quality · Crop yield · Industrial agriculture · Rudolf Steiner · Bio-dynamic agriculture · Natural agriculture · Organic-biological agriculture · Sir Albert Howard · Lady Eve Balfour · Edward H. Faulkner · Natural farming · Jerome Irving Rodale · Masanobu Fukuoka · Regenerative agriculture · Organic agriculture standards · Organic agriculture certification · Plant breeding · Principles of modern organic agriculture
1.1 History and Current Organic Agriculture Land Use Humans have altered and managed terrestrial ecosystems for agricultural land use over thousands of years. Profound long-term terrestrial ecosystem changes started about 12,000 years ago with the Neolithic revolution during which hunting and gathering was replaced by domestication of crops and livestock and the establishment of settlements in widely scattered global regions (Larson et al. 2014). Earlier, tropical forests have been altered for at least 45,000 years through techniques ranging from controlled burning of sections of forest to plant and animal management to clear-cutting (Roberts et al. 2017). Agricultural activities are now responsible for a vast majority of ongoing land use related terrestrial ecosystem alterations. Between 1985 and 2013 alone, for example, the global cropland and pasture area has increased by 16.7% (Borrelli et al. 2017). Agriculture is the dominant global land use with about 40% of the ice-free land surface used for agricultural practices, and much of cropland has replaced forests, savannas, and grasslands (Ramankutty et al. 2008). The expansion of the global cropland area is accelerating, and increased by 9% from 2003 to 2019 (Potapov et al. 2021). Half of the new cropland area replaced natural vegetation and tree cover. This chapter begins with an overview on the early history of organic agriculture (OA) in the German- and English-speaking world, and ancient agricultural practices in Asia. This is followed by a discussion on the more recent developments of OA systems since World War II. Then, the current status of OA land use and its potential future area extension is presented. The final chapter section discusses the principles, standards, regulations, certification bodies and labelling systems of OA. Throughout the book, OA will be differentiated from nonorganic or ‘conventional’ agriculture (Sumberg and Giller 2022). Conventional agriculture refers to the dominant system of production in a region (O’Donoghue et al. 2022). The land use and land cover change for agriculture has profound effects on the global climate. For example, soil organic carbon (SOC) has been strongly depleted by agricultural activities with an estimated total SOC debt of 116–135 Pg carbon (C) (1 Pg = 1 Gt = 1015 g) for the top 2-m of soil (Sanderman et al. 2017; Lal 2018). Globally, up to 357 Pg C pre-1850 and 168 Pg C post-1850 may have been released
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by agricultural land-use changes (Erb et al. 2018). Friedlingstein et al. (2021) estimated cumulative carbon dioxide (CO2) emissions from land-use changes of 200 Pg C for 1850–2020. This includes CO2 fluxes from deforestation, afforestation, logging and forest degradation (including harvest activity), shifting cultivation (cycle of cutting forest for agriculture, then abandoning), and regrowth of forests following wood harvest or abandonment of agriculture. Emissions from peat burning and drainage are also considered (Friedlingstein et al. 2021). Methane (CH4) is produced in anaerobic environments under agricultural practices, such as the sediments of wetlands, peatlands, and rice (Oryza sativa L.) paddies as well as by livestock production (Houghton 2014). The net C release through agricultural land use and cover change together with emissions of CH4 and nitrous oxide (N2O) has contributed to increasing atmospheric greenhouse gas (GHG) concentrations and accelerating climate change (Allen et al. 2014). However, climate change also affects agricultural production by some severe negative effects (Porter et al. 2014). Thus, climate change adaptation and mitigation are necessary to sustainably intensify production for meeting the challenge of satisfying the increasing demands for food, feed, fiber and fuel of a growing, more affluent and more animal- products consuming global population (FAO 2017). In the future, the human diet may consist of a higher percentage of food produced by OA as many perceive it as being environmentally friendly, and food produced by OA as being healthier than conventionally produced food (Meemken and Qaim 2018). However, evidence for superior nutritional quality of OA vs. that of conventionally produced food is mixed and further discussed below. The differences between OA and conventionally produced food in terms of environmental effects are also variable. For example, reactive nitrogen (Nr; all chemical species of N except N2) losses from OA production per unit product in the United States of America (USA) are comparable to conventional production while Nr losses from OA beef (Bos taurus Linnaeus, 1758) production were estimated to be higher (Noll et al. 2020). Otherwise, some see a greater potential for climate change mitigation by OA compared to that by conventional practices (Goh 2011). While conventional farming focuses mainly on maximizing yields employing industrialized processes, organic farming is oriented toward the use of natural regulatory processes (Zimmermann et al. 2021). There is a broad spectrum of conventional and organic farming systems. For example, sub-concepts of organic farming may include bio-dynamic farming, advanced organic farming and European Union (EU)-organic farming (Zimmermann et al. 2021). Lord Northbourne coined the term ‘organic farming’ and published a manifesto of OA (Northbourne 1940). In 2020, OA was practiced on only 1.6% of the global agricultural land area but it is a fast-growing land use sector over the last decades (Willer et al. 2022). Only well after 1945 did OA spread to appreciable extent globally with more reliable data on area under OA collected by Forschungsinstitut für biologischen Landbau- International Federation of Organic Agriculture Movements-Stiftung Őkologie & Landbau (FiBL-IFOAM-SOEL) surveys since 1999 (Fig. 1.1; Willer et al. 2022). However, average OA crop yields are between 19% and 25% lower than those under conventional management but with a high variability (Table 1.1; Seufert 2019).
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Fig. 1.1 Temporal changes in global organic agriculture land area (thousand km2) from 1999 to 2020. (Modified from Willer et al. 2022) Table 1.1 Average yield difference (%) between organic and conventional agriculture for different crops (modified from Seufert 2019) Crop species Corn Wheat Soybean (Glycine max L.) Barley (Hordeum vulgare L.) Tomato (Solanum lycopersicum L.) Potato (Solanum tuberosum L.)
% yield difference Minimum −11 −27 −7 −24 −6 −30
Maximum −36 −55 −32 −45 −50 −62
Shennan et al. (2017) argued that yield comparisons must be improved by also including observations at the farm scale in addition to those obtained at small-scale plot experiments. For example, crop OA/conventional yield ratios under commercial practice are reported for cereals in the range 0.40–0.67, grain legumes (pulses) 0.57–0.88, rapeseed (Brassica napus L.) 0.71 and potato (Solanum tuberosum L.) 0.64 in England, France and Sweden (Connor 2022). However, crop yield ratios cannot estimate the relative productivity of OA because they overlook the land that must be maintained in legume crops and pastures to provide the biologically fixed nitrogen (BNF) upon which continuing productivity of OA entirely relies (Connor 2022). Otherwise, in least developed countries OA crop yields may be higher than those under low-input conventional management (Joshi and Piya 2021). What the projected increase in OA production means for environmental performance, delivery of ecosystem services (ESs) by agroecosystems, and sustainability of global agriculture is discussed controversially (Sandhu et al. 2010; Reganold and Wachter 2016; Seufert and Ramankutty 2017; Fess and Benedito 2018; Eyhorn et al. 2019; Kirchmann 2019; Debuschewitz and Sanders 2022). For example, a review of 528 studies performed in the temperate climate region with 2816 pairs
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(OA vs. conventional farming) indicated that across all indicators for the fields of environmental protection and resource conservation, OA management showed advantages over conventional management in 58% of the pairs analyzed (Sanders and Heß 2019). No differences were found for 28%, and in 14% of the comparison pairs, the conventional management was more advantageous. Further, no clear picture was drawn regarding animal welfare. No substantial differences were found between OA and conventional livestock across all animal species and production forms in 46% of the comparison pairs. Specifically, OA management showed advantages in 35% of the pairs, whereas the conventional version performed better in 19% of the pairs. However, very few studies have been found considering animal welfare comprehensively (Sanders and Heß 2019). The species richness and abundance of selected flora and fauna groups in temperate climates was higher under OA practices in 58% of the OA/conventional comparison pairs (Stein-Bachinger et al. 2020). In croplands, benefits of OA (i.e., mechanical weed control, organic fertilization, non-stained seeds, and restricted use of pesticides) on soil microarthropod communities and associated ecosystem functions have been confirmed (Yin et al. 2020). Natural pest control, and plant defenses against herbivores and pathogens may also benefit from OA practices (Krey et al. 2020). Otherwise, Tscharntke et al. (2021) argued that OA has only limited biodiversity benefits due to organic pesticide use and intensification. Non-target organisms may also be affected by OA pesticide use. For example, deltamethrin shaped the evolution of pesticide resistance in non-target aquatic Daphnia magna species (Almeida et al. 2021). A meta-analysis indicated that OA often has positive effects on species richness and abundance, but that its effects are likely to differ between organism groups and landscapes (Bengtsson et al. 2005). This enhancement may benefit soil properties. For example, Birkhofer et al. (2021) reported considerably stronger linkage between soil biota and soil processes for long-term OA than conventional farming. Positive effects of OA on species richness may be expected in intensively managed agricultural landscapes, but not in small-scale landscapes comprising many other biotopes as well as agricultural fields. Tuck et al. (2014) concluded, based on a hierarchical meta-analysis, that OA has large positive effects on biodiversity compared with conventional farming, but that the effect size varies with the organism group and crop studied, and is greater in landscapes with higher land-use intensity. Similarly, a meta-analysis spanning sixty crop types on six continents indicated that OA sites had greater biodiversity than conventional sites with biodiversity gains increasing as field size increased in the landscape (Smith et al. 2020). However, as crop field size increased, yield gaps between OA and conventional farms generally increased, and profitability benefits of OA, for example, in the USA decreased (Smith et al. 2020). Sadras et al. (2020) argued that system boundaries in OA/conventional comparisons are disregarded. Meta-analysis of crop-by-crop yield comparisons does not represent crop productivity under large scale implementation of OA because: (i) export of nutrients from conventional agriculture to OA is ignored; (ii) extrapolating OA yield data from plot- to farm-scale underestimates on-farm pressure by weeds, pests
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and diseases; (iii) more frequent cropping of legumes for N2 fixation in OA; and (iv) less non-legume crops reduces total system food production (Sadras et al. 2020). OA systems require more land because of lower yield (Table 1.1), cause more eutrophication, use less energy, but emit similar amounts of GHGs per unit of food as conventional systems (Clark and Tilman 2017). In contrast, intensive and industrialized systems show the lowest GHG emissions per unit of agricultural production (Bennetzen et al. 2016). The environmental outcomes of OA towards meeting GHG targets are highly variable (Poore and Nemecek 2018). Based on a global meta-analysis, Smith et al. (2019) concluded that sustainability metrics other than crop yield, including greater profitability, are promoted by OA farming systems compared to conventional systems. For example, OA practices may enhance the economic value of some ESs (Sandhu et al. 2008). Economically, OA generally outperform conventional systems largely due to lower production costs and higher market price (Durham and Mizik 2021). However, there is little market for higher priced OA products in developing countries (Giller et al. 2021). Otherwise, in industrialized countries with higher rates of food waste, N surpluses and high meat consumption, strengthening OA may be an integrated way to promote nature-based solutions (NbS) on croplands (Reise et al. 2022). NbS are defined here as locally appropriate, adaptive actions to protect, sustainably manage or restore natural or modified ecosystems in order to address targeted societal challenge(s) – such as climate change mitigation – while simultaneously enhancing human well-being and providing biodiversity benefits (Reise et al. 2022). Debuschewitz and Sanders (2022) emphasized that the polarizing debate of environmental impacts of OA mainly results from the often-binary initial question, i.e., is OA superior to conventional agriculture? Food security should be considered in the assessment of environmental impacts as should be net environmental impacts or possible leakage effects because of lower OA yield levels. Further, the choice of reference units or normative basic assumptions in scientific sustainability assessments should be given greater consideration in the discourse (Debuschewitz and Sanders 2022). Debates about the future are increasing framed in terms of ‘alternative’ agriculture including OA versus ‘conventional’ agriculture (Sumberg and Giller 2022). The notion of conventional agriculture is deeply embedded in discourses that promote alternative agricultures such as OA as well as the scientific literature. However, the category conventional agriculture may have little analytical value but the term conventional agriculture has been weaponized sometimes in the discourse with OA. The focus should be rather on where and how different farming systems can contribute to the sustainability of agriculture (Sumberg and Giller 2022). The current evidence base does not allow a definitive statement on the nutritional and health benefits of dietary intake of food produced by OA (Vigar et al. 2020). Rempelos et al. (2021) summarized results from: (i) dietary intervention studies indicating that OA food consumption substantially reduces pesticide exposure in humans and affects feed intake, growth, hormone balances and immune system responsiveness in animal models; and (ii) human cohort/epidemiological studies reporting significant positive associations between OA food consumption and the lower incidence of a range of diseases including obesity, metabolic syndrome,
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cancer, hypospadias, pre-eclampsia, eczema and middle ear infections in infants. Otherwise, there is little evidence for significant differences in crop macronutrient levels between OA and conventional farming practices (Montgomery and Biklé 2021). In contrast, there is substantial evidence for the influence of different cultivars and farming practices on micronutrient concentrations. More consistent differences between OA and conventional crops include that conventionally grown crops contain greater pesticide levels, whereas OA grown crops contain higher levels of phytochemicals shown to exhibit health-protective antioxidant and anti-inflammatory properties. However, OA tends to rely on tillage for weed control, and this can adversely impact soil life, and thereby mineral uptake and phyto-chemical production (Montgomery and Biklé 2021). In addition, environmental pollutants are also found in food produced by OA (Ramakrishnan et al. 2021). Unintended flow of pollutants into OA food may occur via dairy and farmyard manure, green waste, compost, domestic waste, sludge, and forage grass. These substrates are the richest sources of veterinary antibiotics, pesticides and their residues, pharmaceutical compounds, microplastics, personal care products, and heavy metals (Ramakrishnan et al. 2021). Also, pesticide residues from previous conventional management at a specific site have been found in soil even after 20 years of OA (Riedo et al. 2021).
1.1.1 Early Developments Conventional or industrial agriculture methods were developed since the late nineteenth century, and became more widespread until after World War II, particularly with the breakthrough of the Green Revolution (Borlaug 2007). For example, synthetic nitrogen (N) fertilizer inputs to global croplands increased since the late 1930s and particularly the early 1960s (Ren et al. 2020). Industrial agriculture is highly resource and energy intensive, but also highly productive. Thus, pre-industrial agriculture without intensification by synthetic fertilizer, pesticide and organism inputs can be regarded as a simple type of pre-modern OA. The development of modern OA methods was strongly facilitated in reaction to the perceived failures of conventional or industrial agriculture, especially due to enhanced soil degradation, poor food quality, and the decay of rural social life and traditions (Barton 2018). In response to these challenges, the OA movement emerged in Europe in English- and German-speaking countries already during the late nineteenth/early twentieth century (Vogt 2007). The use of mineral fertilizers, pesticides and machinery was regarded as either a cause of or a solution to environmental problems. Specifically, neglect of organic manuring by conventional practices was perceived by some as a major concern. Establishing the concepts for OA was influenced by the knowledge of biologically oriented agricultural science, the visions of ‘Life Reform’ and ‘Food Reform’ movements, and an interest in farming systems of the Far East (Vogt 2007). For example, the new discipline agricultural bacteriology focused on bacteria in soil, manure, silage and milk. A biological concept of soil fertility was developed focusing on the community of soil organisms, the dynamics of soil organic matter
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(SOM), and the relations between plant roots and soil. This concept recommended feeding the soil organisms by organic fertilization, i.e., by rotted organic material and green manuring. Thus, OA practices aimed at intensification of farming practices by biological and ecological means (Vogt 2007). German-Speaking World The development of OA was influenced by the German ‘Life Reform’ movement (Vogt 2007). The movement called for a ‘natural way of living’ consisting of vegetarian diets, physical training, natural medicine and going back to the land. However, OA did not become a key part of the urban ‘Life Reform’ movement because any vegetarian nutrition played a more important role than high-quality OA food (Vogt 2007). Similarly, Far Eastern farming systems were admired by early OA pioneers but had almost no practical influence on OA in Europe. However, the Far East played a key role in the development of OA by presenting a model of a sustainable society based on gardening and farming (Vogt 2007). Related to OA in German-speaking countries is bio-dynamic agriculture based on the esoteric-occult world view Anthroposophy, a philosophy introduced by the Austrian philosopher Rudolf Steiner (Steiner 1924). Anthroposophy postulates the existence of an objective, intellectually comprehensible spiritual world, accessible to human experience. In a series of lectures, Steiner presented an alternative vision of agriculture based on this philosophy. He was the first to propose the concept of the farm as an organism in which all the component parts – the soil minerals, organic matter (OM), microorganisms, insects, plants, animals, and humans – interact to create a coherent whole (Stockdale et al. 2001). However, Steiner did not present a complete concept in his lectures but subsequently farmers and researchers together developed Steiner’s guidelines, and in 1927 the trademark Demeter was introduced for food produced in bio-dynamic farming systems (Gerber and Hoffmann 1998). Bio-dynamic agriculture uses mystical formulations as, for example, herbal preparations added to manure are supposed to pull cosmic forces from the universe and channel them into the soil (Barton 2018). However, there are no clear scientific data supporting the efficacy of bio-dynamic preparations (Chalker-Scott 2013). Bio- dynamic practices include also using lunar calendars for planting, managing and harvesting (Chalker-Scott 2013). However, there is no scientific evidence for any causal relationship between lunar phases and plant physiology (Mayoral et al. 2020). Despite this thoroughly unscientific approach, bio-dynamic agriculture is now practiced in many countries (Stockdale et al. 2001). However, Steiner’s belief that mineral fertilizers decrease food quality could not be proven (Kirchmann 2019). Further, bio-dynamic agricultural systems depend somehow on restoring soil nutrients by cosmic forces and not on the need to return nutrients to the soil. Thus, it may work at best only for crops that thrive in low nutrient soils. The term biodynamic is often used by farmers without the practice of a closed system with no outside inputs as originally envisioned by Steiner (Barton 2018). No agricultural system is or has ever been a closed nutrient loop (Amundson 2022). In fact, none of the four essential aspects of bio-dynamic agriculture – its concept of nature, its characteristic preparations, the notion of a farm as a living organism and individuality, and the
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intimate, ‘personal relation’ to nature – have been incorporated into ‘modern’, science-based OA (Vogt 2007). Other types of OA, i.e., natural, biological, ecological and organic-biological agriculture, were also developed during the twentieth century in German-speaking countries (Rusch 1968; Vogt 2007). For example, the science-based natural agriculture focused on the biological concept of soil fertility, and on soil cultivation including careful composting, conservation tillage, green manuring, rock powder fertilization and mulching (Vogt 2007). Natural agriculture included a healthful vegetarian diet, gardening, fruit growing and farming without animals. However, despite the initial refusal, pioneers of natural agriculture accepted a small number of animals and developed the first concepts of appropriate animal husbandry such as high-quality fodder, grazing on pastures and a high standard of hygiene. Similarly, technology was generally rejected but compromises had to be made in the use of agricultural machines with the development of small-scale and intermediate agricultural technology suited to OA and gardening (Vogt 2007). Organic-biological agriculture was grounded in a movement initiated shortly after Steiner of agricultural reform centered around Christian concepts of land stewardship and preservation of family farms (Ziechaus-Hartelt 1991). Self-sufficiency and economic viability of farms are the key principles of organic-biological agriculture, with soil fertility maintained through crop rotation and careful management and use of animal manures (Stockdale et al. 2001). English-Speaking World The origins of OA in the English-speaking world can be traced back to India where Sir Albert Howard and Sir Robert McCarrison were working in the early twentieth century (Vogt 2007). In fact, Howard has been identified by Barton (2018) as the preeminent figure in the founding of OA. The bio-dynamic agriculture movement based on Rudolf Steiner’s lectures also provided some input (Barton 2018). In fact, Sir Albert Howard and Sir George Stapledon were influenced by some of the agricultural ideas of Rudolf Steiner but did not adopt them (Stockdale et al. 2001). While working in India, Howard developed an aerobic composting technique known as the ‘Indore Process’ (Howard 1935). By this process, various types of plant residues are converted into humus. Long, shallow pits are established, and OM is placed in the pits in layers alternating with layers of dung, ashes, etc.; frequent watering is essential, and aeration must be promoted by maintaining a loose condition and by turning the heaps. Conditions in the heaps are favorable for the fermenting action of fungi and bacteria, and within 3 months the material is reduced to humus ready for application to soil (Howard 1935). Howard also emphasized that the health of soil, plants, animals and humans are interrelated. The idea of a healthy soil arose, at least in part, from the OA movement in Europe in the early twentieth century (Powlson 2020), A humus-rich soil was regarded as the key to successful farming and soil fertility as the precondition for healthy plants and animals (Howard 1940). Also working in India, McCarrison studied the relationships among soil fertility, food quality and human nutrition (Vogt 2007). Specifically, he defined the ‘Wheel of Health’, consisting of soil, plants, animals and humans because properly
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composted organic residues will create a fertile soil, on which strong plants will grow, offering a healthy diet for humans and animals (McCarrison 1936). In the U.K., Friend Sykes and Newman Turner, under the influence of OA concepts from German-speaking countries, developed an organic soil management concept (Vogt 2007). It emphasized no-till soil cultivation, organic soil cover, green manuring and ley farming. Further, Sir George Stapledon examined establishment and cultivation of diverse grass turf, breeding of grassland plants and improvement of food quality (Vogt 2007). Stapledon’s work with alternate husbandry systems, Howard’s work on the role of OM in soils and composting, and McCarrison’s work linking human health and nutrition together strongly influenced the work of Lady Eve Balfour (Stockdale et al. 2001). In 1939, she initiated the Haughley Experiment (1939–1969) to study the links between the way food is produced, food quality and human health at the whole farm level (Balfour 1976). The Haughley Experiment was the first long-term OA experiment. Balfour also founded the British organic farming association, i.e., ‘The Soil Association’ (Vogt 2007). However, Balfour’s claim that artificial fertilizers speed up the rate at which SOM is exhausted was later refuted (Kirchmann 2019). In the USA, ‘The Friends of the Land’, a group of scientists studying soil protection, landscape development and ecology, promoted a sustainable way of farming to prevent erosion (Vogt 2007). Wind erosion was a serious problem at the beginning of the twentieth century, especially in the Great Plains (‘Dust Bowl’). Among the people with an important influence on the early OA movement in the USA was politician and part-time farmer Edward H. Faulkner (Faulkner 1943). He favored a ‘trash mulch system’ combining a surface layer of organic residues with no-till soil cultivation to prevent soil erosion. The novelist Louis Bromfield experimented with sustainable farming, and his Malabar Farm in Ohio became a showpiece of OA practices (Bromfield 1949). Further, the Rodale family was inspired by Howard’s and Balfour’s ideas emphasizing the role of healthy, fertile soil for the production of healthy crops and livestock, and the link with human health and nutrition (Merrill 1983). In summary, British, imperial, European and North American pioneers were laying the foundation for OA before it spread around the world during the twenty- first century into a global phenomenon (Barton 2018). Ancient Farming Practices in Asia Farming cultures of Asia were admired by pioneers of the early OA movement because of their perceived sustainability over centuries and millennia (Vogt 2007). However, before industrial agriculture, humans in Asia did not always practice sustainable agriculture, i.e., agriculture practiced in a manner that did not deplete the soil and enabled more or less permanent cultivation (Barton 2018). Many ancient farmers – except those cultivating in river systems – practiced slash and burn, or if they had no shortage of land, nomad and pastoral settlers simply moved from plot to plot in search of fresh soil fertility. In the early modern era, most of the land surface of the world still exhibited this type of agriculture, with many Asian farmers practicing intensive farming. Letting the ground lay fallow and applying manure to tilled land enabled continued cultivation. Yet even these approaches may not all fall
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under “sustainable” practices because they did not always maintain soil fertility over long periods. For example, in central Asia, grazing cleared tree cover. Then farmland was established, and finally invasions by Mongols and others decimated many populations, leaving the soil depleted of nutrients, unsuitable for crops, and open to erosion. In some cases, continued deforestation reduced rainfall, making agriculture difficult or impossible (Barton 2018). Despite the contested view that before the industrial age almost all farmers practiced sustainable agriculture or OA by default (Barton 2018), many OA pioneers aimed at transferring Asian farming concepts to European agriculture. They were influenced by reports on voyages to Asian countries that focused on agriculture, such as that of Franklin H. King in the early twentieth century (King 1911). Over several millennia, many farmers in Asia used pre-industrial agriculture practices without intensification by synthetic fertilizer, pesticide and organism inputs. This is regarded by some as a simple type of pre-modern OA. For example, Japanese, Korean, and Chinese farmers kept their land productive for an extended period of time (King 1911). Their farming practices included: (i) double, triple, and even quadruple cropping; (ii) runoff harvesting; (iii) crop species selected for maximum water-use efficiency; (iv) soil management practices to reduce evaporation; (v) intercropping to plant new crops between rows of still developing ones; transplanting to improve land-use efficiency; and (vi) high numbers of poultry but low numbers of ‘coarse food transformers’ (pigs [Sus domesticus Erxleben, 1777], sheep [Ovis aries Linnaeus, 1758], and goats [Capra hircus Linnaeus, 1758]) per unit of land. Extreme diligence was employed by the farmers in recycling organic materials and making use of BNF. Specifically, all products harvested from the land, after having been used for food, feed, fuel, or fabric eventually found their way back to the farm fields (King 1911). In India, the farmer toiled under the warrior and priestly caste (Barton 2018). Indians burned dried cattle dung for fuel leaving few nutrients returned to the soil. Because villagers did not compost human waste and return it to the fields, British imperial officials noticed a ring of verdant growth around villages where villagers deposited sewage. Before industrial fertilizers, farmers in India survived by planting varieties of wheat (Triticum aestivum L.) and other crops that flourished with low nutrients. Some consider this as a variant of sustainable farming, but whether it can be described as some type of OA is questionable (Barton 2018). Sir Robert McCarrison studied the health and physique of the Hunza tribesmen living at India’s north-west frontier in the early twentieth century (Vogt 2007). He discovered the meaning of nutrition for health: their nearly vegetarian diet consisted mainly of whole grains, vegetables, fruits and milk products; meat and alcohol did not play a major role. His findings opened a new perspective for medicine: to examine the conditions that determine one’s health, rather than simply to cure diseases (Vogt 2007). Overall, the practical influence of Asian farming systems on OA was limited (Vogt 2007). For example, from the beginning, OA preferred aerobic composting instead of the anaerobic methods used in Asia. Efforts to mimic wetland rice farming – starting cereal plants in small beds and then transplanting the young plants to
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large fields – failed. Only a few local projects in the 1950s and 1960s attempted to re-cycle municipal organic waste from households, factories and sewage treatment plants to use them as fertilizers. Nowadays, fertilization with sewage sludge is forbidden for OA farmers because of contamination by heavy metals and other harmful substances. The replacement of water closets by composting toilets, a goal during organic farming’s pioneer period, was never achieved. Finally, a vegetarian diet was not in accordance with Asian habits (Vogt 2007).
1.1.2 Developments after Second World War Some of Rudolf Steiner’s thoughts and ideas on how Anthroposophy could inform agricultural practices were shared in Ehrenfried Pfeiffer’s book ‘Bio-Dynamic Farming and Gardening’, published in 1938 (Paull 2011). However, only a limited number of copies of Steiner’s lectures were available before 1963 when those were finally printed (Vogt 2007). Another major issue hindering the more widespread adoption of bio-dynamic agriculture was that pre-World War II, its development occurred predominantly in eastern parts of Germany. Thus, Western Germany’s farms required a change of biodynamic farming practice and concepts after Germany’s division post-World War II. In fact, bio-dynamic agriculture was subsequently closely associated with OA by integration of scientific-biological knowledge. The environmental protection and sustainable farming had a more prominent role for bio-dynamic agriculture during the 1980s and 1990s. Concepts of animal husbandry were also developed, and efforts were initiated to breed cultivars adapted to organic farming conditions. A more recent development is the combination of agricultural with social work at bio-dynamic farms by integrating handicapped, mentally impaired and drug-addicted people, and people with educational problems (Vogt 2007). Science-Based Organic Agriculture The science-based types of OA were further developed in Germany and Switzerland after World War II (Vogt 2007). While different names (biological or ecological agriculture) were given, more important was that key principles of the ‘Life Reform’ movement such as vegetarianism, farming without animals, back-to-the-land concept and recycling of municipal organic wastes were abandoned. In fact, biological or ecological agriculture were closer to the mainstream of agriculture, society and politics. Knowledge about biologically stabilized soil structure, rhizosphere dynamics and systems ecology were also integrated into OA. Further, ecological technologies concerning soil management, plant cultivation and appropriate animal husbandry were developed (Vogt 2007). The original background of organic- biological agriculture using the concept of nature as a cycle of living particles was also abandoned during the 1970s (Rusch 1968). Rusch’s statement that mineral fertilizer is not a normal, physiological adapted and natural form of plant nutrition degenerating food quality was refuted (Kirchmann 2019). Instead, science-based
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concepts of natural and biological agriculture were adopted, and both merged to become today’s OA. While preservation of rural life was a policy topic during the 1950s and 1960s, environmental protection came into focus during the 1980s and 1990s (Vogt 2007). Between 1950 and 1980, the OA movement became more and more globalized and increasingly integrated with an environmental movement that emphasized a link between ecology and human health, informing a new emphasis on air pollution, water pollution, and the protection of wildlife (Barton 2018). One the most important voices of the environmental movement in the 1970s was E.F. Schumacher who learned his environmental awareness from the OA movement and served as president of the Soil Association in the U.K. The links between OA and a new phase of the environmental movement, in the U.K. as in most of the industrialized world, were further strengthened during the 1980s (Barton 2018). In the USA, more criticism towards OA was raised during the period from the 1940s to the 1970s, resulting in little support from academic and conventional agriculturists (Barton 2018). However, doubt and pessimism regarding conventional agriculture did also rise, particularly, in relation to Rachel Carson’s book ‘Silent Spring’ documenting the adverse environmental effects caused by the indiscriminate use of pesticides (Carson 1962). Pesticide pollution continues to be a major concern in the USA as today an estimated 2.46 million km2 of agricultural land is at risk of pesticide pollution by more than one active ingredient (Tang et al. 2021). Globally, pesticides of all types pose a clear hazard to soil invertebrates (Gunstone et al. 2021). Several key figures supported the acceptance of natural farming methods in the USA (Barton 2018). Among key personalities were Henry Wallace, Secretary of Agriculture; William Albrecht, Professor of Soil Science, University of Missouri; and Aldo Leopold, Professor of Game Management, University of Wisconsin. However, the greatest effect on raising awareness for OA among the public in North America had Jerome Irving Rodale as he was mainly responsible for bringing the ideas of Howard to the North American public (Barton 2018). After the early 1970s, OA was more widely adopted by industrial growers and farmers in the USA (Wiggins and Nandwani 2020). OA did rise post-World War II in German-speaking countries, the U.K. and the USA. This was also the case in Japan based on the work by the OA pioneer Masanobu Fukuoka (Nandwani and Nwosisi 2016). Fukuoka’s vision of ‘natural farming’ is based on four principles which comply with the natural order and lead to the replenishment of nature’s richness: (i) no cultivation (ploughing or turning of the soil), (ii) no chemical fertilizer or prepared compost, (iii) no weeding by tillage or herbicide, and (iv) no dependence on chemicals (Sumberg 2022). There are also many individual farmers and gardeners who practice according to OA protocols in many other global regions (Barton 2018). India was far behind in the adoption of OA due to several reasons but has now achieved rapid growth becoming one of the largest organic producers in the world (Das et al. 2020). After the 1980s, the integration of OA – already an international movement – into government policy and certification standards began. Driven by increasing consumer demand in the USA, for
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example, the United States Department of Agriculture (USDA) launched an organic certification scheme with organic farmers that gross less than $5000 from sales of organic products exempt from the certification requirement (Wiggins and Nandwani 2020). Certification schemes in Europe and other major markets followed, leading to initiatives by the United Nations for the harmonization of organic certification through multilateral agencies. During the 1990s, the United Nations stepped in to resolve the regulatory fragmentation creating a global market for organic goods (Barton 2018). Scientific Progress Progress in OA was increasingly made on soil management, crop and livestock production practices aside improvements on economic and policy levels. For example, after three decades of research and development, improved weed prevention techniques have become available (Niggli 2007). These include adapted crop rotations and seedbed preparations as well as efficient and effective mechanical and thermal weed control. Manuring techniques have also been improved, in particular, driven by the necessity to reduce N losses by leaching and gaseous emissions. A major outcome of research and development activities are higher nutrient efficiencies of the entire manure and slurry supply chain from livestock to plant uptake. Similar efficiency gains were achieved in modern composting techniques. Another recent development is improved use of cover crops in OA rotations, either as catch crop to ‘catch’ the available N or as green cover crop to improve nutrition of the subsequent main crop. In fact, productive, stockless OA systems are now possible (Schmidt et al. 1999). A wealth of knowledge on fertility-building crops suitable for OA has also been collated, particularly, for crops with a self-sustaining N supply. Phosphorus (P) is another limiting nutrient aside N and potassium (K), and some progress has been made towards providing sufficient P supply to OA systems (Niggli 2007). However, more P and K are generally removed with products from OA cropping systems than applied with fertilizer (Möller et al. 2018; Watson and Stockdale 2019). Otherwise, a meta-analysis of European studies indicated that OA farms had a surplus of 45 kg N ha−1 year−1, a balanced P budget of 0 kg P ha−1 year−1, and a deficit of −12 kg K ha−1 year−1 (Reimer et al. 2020). While arable and mixed farms faced more severe nutrient shortages than dairy/beef farms, vegetable farms often had problems with nutrient surpluses. The actual nutrient demand of OA farms must be assessed with regards to geographical location, budgeting method, and farm type, and soil data should always be incorporated (Reimer et al. 2020). Local soil characteristics need to be considered in parallel with potential new avenues for sourcing nutrients (Sapinas and Abbott 2020). Using non-renewable nutrient sources in OA such rock phosphate is discussed controversially (Watson and Stockdale 2019). Thus, P and K recycling on OA farms is needed (Niemiec et al. 2020). While various types of recycled P fertilizers are under discussion, contamination linked to P fertilization (copper [Cu], zinc [Zn], chrome [Cr], mercury [Hg], and cadmium [Cd]; organic pollutants) must also be addressed (Möller et al. 2018). As studies on some OA systems in Europe indicate, however, allowable P inputs must also be
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revised to improve long-term P supply (Cooper et al. 2018). Importantly, many OA farms are unsustainable in the long term without importing nutrients (Watson and Stockdale 2019). Shallow tillage (< 25-cm soil depth) continues to be widely used in OA to control weeds and to reduce disturbance of soil animals and microorganisms associated with the deep mixing of soil horizons (Niggli 2007). However, reduced tillage practices are increasingly promoted to improve sustainability and productivity of both OA and conventional agricultural systems. Reduced tillage and, in particular, shallow non-inversion tillage showed some promise for improving soil health in OA systems while minimizing impacts on yields (Cooper et al. 2016). However, reducing tillage intensity in OA systems consistently results in more weeds. Similarly, no-till (NT) practices may enhance soil health on OA farms but problems associated with weeds, nutrient cycling and other issues must be resolved to improve crop performance towards a wider adoption of NT OA rotations (Carr et al. 2013). Instead of continuous-NT systems, rotational-NT systems are more common under OA practices where tillage is not used when growing specific crops but is employed when growing other crops (Briar et al. 2019). Weed management under OA practices has generally been improved (Niggli 2007). This is based on refined tillage techniques together with well-designed crop rotations, various mulching techniques, and gains in knowledge on physical weed control. In contrast, less progress has been made on the self-regulation of crop diseases and insect pests. Thus, healthy soils are not necessarily associated with healthy plants as originally envisioned by Howard (1940). Pest prevention strategies including management and manipulation of habitats, however, shows some promise to control pests (Niggli 2007). Specifically, insect pest populations on OA fields are reduced due to increased biodiversity and abundance of beneficial predators, and changes in plant nutrient contents. Further, Blundell et al. (2020) reported that plants managed by OA practices are less attractive to insect pests, and OA managed soils and microbial communities may contribute to plant resistance to insects. In contrast, Nyamwasa et al. (2020) showed that OA practices can also attract soil insect crop pests, and it may be necessary to manage the laying of insect eggs by targeting key attractants. Sensitive crops like grapes (Vitis vinifera L.), apples (Malus domestica Borkh., 1803), some berries, and most of the very challenging greenhouse vegetables can now also be grown following OA principles (Niggli 2007). Improvements have also been made regarding OA livestock production. For example, rotating livestock frequently through paddocks such that plants are uniformly grazed but left with significant residual biomass and time for regrowth are critical for maintaining dense, productive swards in OA pasture management (Jackson et al. 2019). Further, OA livestock husbandry is increasingly addressing ethologically appropriate housing and free-range systems (Niggli 2007). However, holistic concepts of livestock health still face severe problems, and research started only in the 1990s. Van Wagenberg et al. (2017) emphasized that more data are needed to assess differences in sustainability between OA and conventional livestock production systems. Preliminary results indicated that OA systems had higher income per animal
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or full-time employee, lower impact on biodiversity, lower eutrophication and acidification potential per unit land, equal or lower likelihood of antibiotic resistance in bacteria and higher beneficial fatty acid levels in cow milk (van Wagenberg et al. 2017). Gaudaré et al. (2021) provided a first global comparison highlighting differences between OA and conventional farming on animal productivity, feeding strategy and feed use efficiency in dairy cattle, pigs (Sus Linnaeus, 1758 spp.) and poultry. The animal productivity was 12% lower under OA. Organic dairy cattle were fed with a lower proportion of concentrate and food-competing feed than in conventional systems. The overall feed-use efficiency was 14% lower under OA (−11 and −47% for organic dairy cattle and poultry broilers, respectively). However, there was a 46% lower human-food vs. animal-feed competition in organic dairy cattle (Gaudaré et al. 2021). Scientific progress towards improving OA in the USA is increasing as many public and private universities have created and devoted research and education directly addressing OA (Wiggins and Nandwani 2020). Further, many NGOs are also contributing to improve OA practices. There is some convergence between OA and regenerative agriculture (RA; Schreefel et al. 2020). Robert Rodale (1983) defined RA as ‘one that, at increasing levels of productivity, increases our land and soil biological production base. It has a high level of built-in economic and biological stability. It has minimal to no impact on the environment beyond the farm or field boundaries. It produces foodstuffs free from biocides. It provides for the productive contribution of increasingly large numbers of people during a transition to minimal reliance on non-renewable resources’. A central tenet of RA is that these practices increase the flow of sugars from plant roots, and that this can be accomplished by maximizing rates of photosynthesis (Prescott et al. 2021). There is, however, no legal or regulatory definition of RA nor has a widely accepted definition emerged in common usage (Newton et al. 2020). The Rodale Institute (2014) published a white paper on Regenerative Organic Agriculture (ROA). Aim of this type of OA is to maximize C fixation while minimizing the loss of C once returned to the soil, reversing the greenhouse effect. ROA: (i) takes advantage of the natural tendencies of ecosystems to regenerate when disturbed, (ii) is marked by tendencies towards closed nutrient loops, (iii) greater diversity in the biological community, fewer annuals and more perennials, and (iv) greater reliance on internal rather than external resources. It is aligned with agroecology with some of the ROA practices similar to those of OA such as crop rotation and compost application. However, no agricultural system is a closed nutrient loop (Amundson 2022). Recently, the case was also made for ROA in improving human health (Moyer et al. 2020). The Regenerative Organic Certification is a holistic agriculture certification encompassing pasture-based animal welfare, fairness for farmers and workers, and robust requirements for soil health and land management (https:// regenorganic.org/wp-content/uploads/2021/02/ROC_ROC_STD_FR_v5.pdf). To achieve ROA certification, an entity must hold USDA organic certification or an equivalent formally recognized by the National Organic Program.
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Haller et al. (2020) called for more basic and applied research to improve the environmental performance of OA. For example, active substances that are not in line with the requirements of modern plant protection are still used in OA due to a lack of alternatives. This includes the use of copper sulfate as a fungicide, and that of organic insecticides with a broad spectrum of action and corresponding effects also on non-target organisms. Widespread insecticides used in OA include natural pyrethrin, derived from chrysanthemum (Chrysanthemum L.), and azadirachtin from the Asian neem tree (Azadirachta indica A. Juss., 1830; Tscharntke et al. 2021). Copper has been shown to have negative effects on some soil invertebrates (Gunstone et al. 2021). The long-term effects of sulfur addition to OA systems are also uncertain (Hinckley et al. 2020). Importantly, data on the use of permitted plant protection products in OA are scanty. For example, copper is widely used by Mediterranean OA growers in Europe with annual application limits not always respected (Katsoulas et al. 2021). The allowed use of copper, sulfur or mineral oils contradicts the aspiration of OA to be free from toxic, non-renewable chemicals. Thus, there is an urgent need to research alternatives (Katsoulas et al. 2021). Overall, little is known about pesticide use practices on OA fields (Larsen et al. 2021). There is insufficient knowledge about the benefits and functionality of important ES (e.g., the role of soil microbiomes) in relation to yield formation and stability (Haller et al. 2020). Specifically, the partnership between OA farmers’ practical knowledge and scientific research can provide innovations for the further development of OA. In summary, important research areas for OA are: (i) digitalization, (ii) plant protection and breeding, (iii) optimal nutrient management and soil fertility, and (iv) increasing efficiency and resolving conflicts in animal husbandry (Haller et al. 2020). Shennan et al. (2017) argued that all farming systems including OA cropping systems fall along gradients between the three philosophical poles industrial, agrarian, and ecological. Different systems will be appropriate in different contexts. The authors found considerable evidence for environmental and social benefits of OA cropping systems. However, comparing realistic OA with conventional systems may be the basis for identification of “best” management systems. Increased investment in OA and ecologically based cropping systems research and extension would be needed to improve cropping systems (Shennan et al. 2017). Since the early 2000s, an increasing number of research papers on OA have been published mirroring the increased interests of producers and policymakers, and also the increased consumer demand for food produced by OA practices (Aleixandre et al. 2015). The main research issues were linked to the relationship between OA and biodiversity, the possibility that enhance or reduce the nutritional value of OA plant foods, OA as a global food supply, the agronomic and environmental implications and impact, the sustainability of agricultural systems, and the innovation in the conversion to OA. Thus, OA has become an emerging field of research, and scientific cooperation across borders are becoming increasingly important (Aleixandre et al. 2015). Wiggins and Nandwani (2020) summarized research priorities on innovative techniques that may improve OA systems, particularly, in the USA. This includes
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OA vertical gardening with the potential advantages of reducing disease problems by being elevated from the soil surface, by increasing the air circulation through the foliage, and making it easier to detect pests. Another innovation for OA may be the application of biofertilizers consisting of living microorganisms to increase soil fertility and crop production. Further, soil-less aeroponic OA systems may have the advantages of growing vertically and horizontally depending on space availability. Other potential advantages of OA aeroponics include the ability to extend growing seasons, and reduce pest and disease thresholds (Wiggins and Nandwani 2020). Aquaponic and hydroponic systems replacing soil substrates with water or nutrient solutions to grow plants have been especially popular among operations adopting the USDA OA certification (Gunderson et al. 2018). Olowe and Somefun (2020) synthesized more than 1100 papers presented at the last four IFOAM Organic World Congresses. Contributions from research areas such as agronomy, socio-economics, and organic livestock dominated the conferences at the expense of organic aquaculture, policy issues, health and safety of OA products, and standards and certification. Overall, more research addressed the production phase of the value chains on most commodities than the phase involving processing, distribution, and consumption. Olowe and Somefun (2020) recommended that inter- and transdisciplinary research projects should be commissioned to explore the potential of these identified and largely overlooked research areas in solving global challenges in the organic food and OA sector. Research in OA should also use the potential of on-farm research more widely and systematically to co-design solutions with farmers and advisors (Reckling and Grosse 2022). On-farm research is an emerging field aiming to transform global agriculture by involving farmers and associated actors in the design and evaluation of farming systems (Lacoste et al. 2022). “Living collaborations” with farmers and other actors can help to co-design diversified OA cropping systems (Reckling and Grosse 2022). Animal- or Livestock-Free Organic Agriculture Another recent development is livestock-free or animal-free OA (Hall and Tolhurst 2007). Stock-free OA excludes any animal by-products during the whole cultivation process. First farms in Europe have started to follow the stock-free OA principles (Jürkenbeck and Spiller 2020). These bio-veganic farms are currently small-scale, and mainly grow fruits and vegetables. The Biocyclic Vegan Standard excludes animal production and animal products from the entire agricultural production chain (Biocyclic-Vegan Network 2018). Of high priority is the constant rise in soil fertility by increasing SOM or humus content. This is achieved by using mature compost or biocyclic humus soil together with green manuring and mulching. All materials used for the production of biocyclic humus soil should be of plant origin (Biocyclic- Vegan Network 2018). The Vegan Organic Network (VON) based in the United Kingdom explains that ‘Veganic’ is a combination of two words ‘vegan’ and ‘organic’ (Seymour and Utter 2021). It’s a guarantee that food is grown in an organic way with only plant-based fertilizers, encouraging functional biodiversity so pesticides are not necessary. No chemicals, no genetically modified organism (GMO)
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and no animal byproducts in any part of the chain is used (Seymour and Utter 2021). However, animals contribute to the composting process, any soil-based agricultural production depends on the activity of soil animals, and soil biological processes are particularly important in supporting crop protection and productivity in OA systems (Yang et al. 2018; Jernigan et al. 2020). Further, some crops must be pollinated by insects. Thus, a pure ‘animal-free’ soil-based OA production is not possible. Also, a vegan diet appears incompatible with OA (Barbieri et al. 2021).
1.1.3 Current Organic Agricultural Land Use FiBL (‘Research Institute of Organic Agriculture’) and IFOAM – Organics International conduct an annual survey on the global status of OA (Willer et al. 2022). Basic data on OA systems worldwide were compiled in reports since 1999. According to the latest survey from 2022 summarizing data from 190 countries for the year 2020, the area under OA, number of producers and retail sales continued to grow, and reached new highest values (Fig. 1.1). In total, 0.749 million km2 or about 1.6% of the world’s agricultural land area was managed by OA practices in 2020 including in-conversion areas (Table 1.2). This area was about 4.1% more than the area under OA in 2019. Australia had half of the world’s certified OA farmland in 2020 with an OA area covering 0.357 million km2. Strong absolute increases in OA acreage compared to 2019 were reported for Argentina (+21.3%), Uruguay (+27.9%) and India (+15.6%). The second and third largest OA areas were reported for Argentina and Uruguay (0.037 and 0.027 million km2, respectively). Many countries reported an increase in the OA farmland area. In total, about one quarter of the world’s OA area was located in developing countries. Aside agricultural land under Table 1.2 Certified area (million km2) under organic agriculture including in-conversion areas worldwide for selected countries in the year 2020 (based on data reported in Willer et al. 2022) Countries Australia Argentina Uruguay India France Spain China United States of America Italy Germany Canada Brazil World
Million km2 0.357 0.045 0.027 0.027 0.025 0.024 0.024 0.023 0.021 0.017 0.014 0.013 0.749
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OA, 0.105 million km2 of non-agricultural land were dedicated in 2020 to other OA activities including areas for wild collection, beekeeping, aquaculture, forest and non-agricultural land grazing areas. However, data on aquaculture and forest may not be accurate as many countries do not report non-agricultural organic areas (Willer et al. 2022). The 2020 survey data on OA had some limitations (Willer et al. 2022). For example, for some countries either no current data were available or provided data were incomplete while for other countries no data were available at all. In Brazil, OA is a relatively new development compared to English- and German-speaking countries (da Costa et al. 2017). Over two-thirds of the global OA area was grassland/grazing area in 2020 with an increase by 4% compared to 2019 (Table 1.3). Arable cropland covered 18% of the total OA area in 2020, increasing by 1% compared to 2019. Cereals, green fodder from arable land, oilseeds, dry pulses, vegetables and textile crops were important arable crops in OA systems. Permanent crops covered about 7% of the OA area with the important crops coffee (Coffea arabica L.), olives (Olea europaea L.), nuts, coconut (Cocos nucifera L.), grapes, and fruits (Willer et al. 2022).
Table 1.3 Certified area (km2) under organic agriculture land use differentiated by important crop group categories in the year 2020 (based on data reported in Willer et al. 2022) Land use Arable crops
Arable crops total Permanent crops
Permanent crops total Permanent grassland
Crop group Cereals Plants harvested green Oilseeds Dry pulses Textile crops Fallow land, crop rotation Fresh vegetables and melons Medicinal and aromatic plants Olives (Olea europaea L.) Nuts Coffee (Coffea arabica L.) Permanent crops other Grapes (Vitis vinifera L.) Cocoa (Theobroma cacao L.) Coconut (Cocos nucifera L.) Fruit, tropical and subtropical Fruit of temperate climate zones
Area km2 50,885 32,178 17,951 7783 6179 4733 4216 2555 131,402 8950 7491 7449 5659 4984 3845 2942 2925 2563 52,383 508,026
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1.1.4 Expansion of Organic Agriculture Muller et al. (2017) suggested that OA can only contribute to providing sufficient food for the global population in 2050 and simultaneously reduce environmental impacts if OA is implemented in a well-designed food system in which animal feeding rations, i.e., reduced animal numbers and animal product consumption, and food wastage are addressed. Importantly, OA needs also to adopt a more open position towards new technologies, and should address social, economic and governance issues besides environmental performance (Muller et al. 2019). In Europe, OA is regarded by some as an environmentally-friendly practice that needs to be further developed. As part of the European Green Deal, the European Commission aims to boost the development of the OA area with the goal of 25% of EU’s agricultural land farmed by OA practices by 2030 (Montanarella and Panagos 2021). The associated loss in crop yields due to lower OA crop yields may be compensated by increased imports of agricultural products from non-EU regions undercutting EU farming standards (Fuchs et al. 2020; Seufert 2019). Thus, increasing land under OA in the EU may cause environmental damages elsewhere, essentially offshoring environmental damage to other nations. It is also unclear whether OA or conventional farming with landscape diversification is more effective and cost- effective from the viewpoint of crop production and the maintenance of biodiversity in Europe (EASAC 2022; Tscharntke et al. 2021). Some argue that the share of OA should expand dramatically over the next century to reduce the environmental impact of global food production (Crowder and Illan 2021). Aside the difficulty of addressing the yield gap associated with this expansion, Barbieri et al. (2021) question whether N limitation may prevent rapid expansion of OA worldwide. Specifically, farmers would need to increase the reliance on production of legume crops that naturally fix N2, and would likely need to more broadly integrate crop production and animal husbandry to generate enough animal manure to provide a local source of N to OA systems. Nevertheless, OA could reach 20% of global cropland cover without a major redesign of agricultural systems. However, further expansion would require a dramatic redesign of global agricultural systems to ensure a tighter coupling between livestock and crop production, reduction in food waste, and potentially sourcing N from human wastewater and conventional manure. This growth in OA acreage would also need to be accompanied by major shifts in human diets, i.e., farms would need to increasingly shift away from production of cereals and livestock towards increased production of fruits and vegetables. Legumes would also become considerably more common to allow for sufficient N availability in farmed soils within crop rotations (Barbieri et al. 2021). To continue to sustainably feed the world and mitigate environmental harm, a mix of conventional, agro-ecological, regenerative and OA agricultural systems is needed (Crowder and Illan 2021; Giller et al. 2021).
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1.2 Practices and Principles OA has a framework of principles, standards, regulations, certification bodies and labelling systems (Løes and Adler 2019). However, there is no single interpretation of what OA practices and principles entail as what OA means is seen differently by the various actors including consumers, producers, theorethicians and regulators (Seufert et al. 2017). Importantly, OA is the only farming system whose management practices are codified by law in many countries including clear standards, inspection and certification procedures (Padel 2019). In contrast, conventional agriculture is generally not codified including in law (Sumberg and Giller 2022). Initially, the first OA standards were set by the private sector and groups of farmers. In the year 2021, 76 countries had fully implemented organic regulations, 20 countries had regulations not fully implemented, and 13 countries were of drafting legislation (Willer et al. 2022). The organic standard refers to worldwide standards and certification issues in the organic food sector (https://organicstandard.com/). However, efficiency is often not addressed in OA certification systems which means that the scarcity of productive arable land is not considered a limiting resource for future food production (Linderholm et al. 2020). Certification of OA is also largely restricted to banning synthetic agrochemicals, resulting in limited benefits for biodiversity (Tscharntke et al. 2021). However, OA certification is a new theme in the scientific literature (Brito et al. 2022). About 71% of the reviewed articles related OA certification to social and governance issues, while 29% related it to technical production issues. Researchers based in the USA and Italy were the ones who published the most on OA certification (Brito et al. 2022). The world’s first association dedicated to the advocacy of OA, the Australian Organic Farming and Gardening Society (AOFGS) founded in 1944 in Sydney, Australia, adopted Northbourne’s terminology of ‘organic farming’ (Paull 2015). However, the use of the terms ‘organic farming’ and ‘OA’, and their associated practices in Australia, long predate the development of OA standards and certification which were introduced during the 1980s (Paull 2013). Founded in 1972, IFOAM provides a definition for OA that is based on four principles from which OA grows and develops (IFOAM 2019). The commonly cited definition is: “OA is a production system that sustains the health of soils, ecosystems and people. It relies on ecological processes, biodiversity and cycles adapted to local conditions, rather than the use of inputs with adverse effects. OA combines tradition, innovation and science to benefit the shared environment and promote fair relationships and a good quality of life for all involved.” OA is also defined by government regulations in at least 76 countries while voluntary OA standards may prevail in the remaining countries where OA is known to be practiced (Willer et al. 2022). For example, Australia has an entirely voluntary domestic market, with no government regulation beyond generic ‘truth in labelling’ provisions within Australian consumer law (Rousset et al. 2015). Fourty-nine OA standards are affiliated worldwide with the IFOAM standard (IFOAM 2018), and some also with the Codex Alimentarus. The governmental and private standards are quite similar (Meekem and Qaim 2018), and OA
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practices and regulations also do not differ substantially among countries. The Codex Alimentarus was set up by the Food and Agriculture Organization (FAO) and the World Health Organization (WHO) in 2001 (Seufert et al. 2017). In contrast to OA, conventional agriculture is seldom conceptualized, probed, problematized or defined (Sumberg and Giller 2022). OA is assumed by some to be a holistic and ambitious effort to achieve sustainable development (Løes and Adler 2019). However, several important sustainability outcomes of OA such as biodiversity and soil fertility are not directly addressed in most OA standards (Tscharntke et al. 2021; Padel 2019). Questions persist about the sustainability of OA soil fertility management practices (Sapinas and Abbott 2020). Overall, OA standards provide only weak support for key indicators of sustainability (Ascui et al. 2019). Among voluntary standard-setting organizations and the IFOAM standard, for example, very little collection of verifiable data on sustainability outcomes of OA does occur. Nevertheless, sustainability claims go well beyond the exclusion of synthetic chemicals and GMOs. Well-specified means of verification for sustainability outcomes of OA are often missing. This assurance gap creates the risk of consumer backlash. Thus, Ascui et al. (2019) recommended either to withdraw unsupported sustainability claims or to introduce reforms that would be able to support sustainability claims beyond the exclusion of synthetic chemicals and GMOs. There is also a need to provide more evidence regarding the impact of OA principles and practices on sustainability outcomes (Padel 2019). The main differences between OA and conventional arable farming practices have been generalized and summarized by Boone et al. (2019). With regards to fertilization, mainly organic manure is applied under OA whereas conventional farmers apply high amounts of mineral fertilizers in addition to organic fertilizers. Maintaining the SOM stock is a very important aim of OA practices, but not among the highest priorities under conventional practices. While compost is often applied to soils managed by OA practices, it is used only to a limited degree in conventional agriculture. OA practices include limited use of natural and non-chemically treated mineral fertilizers. In contrast, conventional practices are characterized by intensive use of mineral fertilizers which are mainly chemically treated natural products. OA farmers apply naturally derived plant protection products, and conventional farmers apply synthetically produced plant protection products. Crops are managed mainly mechanically in OA while those are managed mainly chemically in conventional arable farming (Boone et al. 2019). In OA, soil structure, fertility, and weeds are managed by crop rotations, high density planting, multiple tillage options, cover crops, organic amendments and fertilizers, and pesticides that are approved for certified organic production (Jernigan et al. 2020). OA standards involve activities that are prohibited or restricted, and other activities that are required or recommended (Meekem and Qaim 2018). Important among recommended activities are balanced crop rotations including legumes, recycling of nutrients (e.g., through mixed farming), and the use of organic fertilizers. While conventional crop rotations have been simplified over the last 50 years, OA is thought to promote crop diversification (Barbieri et al. 2017). For example, OA crop rotations are 15% longer, and result in higher diversity and more even crop species
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distribution. Drivers of this improvement are higher abundance of temporary fodders, catch and cover crops to the detriment of cereals. This increased complexity of OA crop rotations may enhance ES provision to agroecosystems (Barbieri et al. 2017). Thus, under a scenario of 100% conversion of current global cropland to OA systems, drastic changes in types of crops grown would occur (Barbieri et al. 2019). For example, the harvested area would decrease by 31%, with primary cereals (wheat, rice and maize [Zea mays L.]) compensated by an increase in the harvested areas with temporary fodders (+63%), secondary cereals (+27%) and pulses (+26%) compared with the conventional situation. In total, energy production from croplands would be 27% lower, and major adaptations of human diets and animal husbandry would be needed under this scenario. However, more realistic than a 100% would be a 15–20% conversion to OA practices (Barbieri et al. 2019). OA is based on crop varieties that were bred for the conventional sector and consequently lack important traits required under OA production conditions. For example, years of conventional plant breeding under high-nutrient environments developed crop varieties that are poor at optimizing use of limited nutrients (Li et al. 2018). Further, crop varieties bred for conventional farming systems produce low yields when grown in SOC-poor soils without synthetic fertilizers (Montgomery and Biklé 2021). Thus, adapted and efficient breeding strategies need to be designed to breed modern resistant and tolerant OA crop varieties that produce high yields under OA practices (Fess and Benedito 2018; Le Campion et al. 2020). Both OA and locally adapted crop varieties should be grown (Meekem and Qaim 2018). Erosion control should be among measures to improve fertility of soils managed by OA practices. Pest and weed control are only possible through mechanical, biological and/or thermic measures. Prohibited are the use of synthetic fertilizers, synthetic pesticides, GMOs and sewage sludge. In livestock production, the animals must be fed with organic fodder, preferably from the same farm. A major limitation in organic livestock production is, however, the severe shortage of organic feed (Ramakrishnan et al. 2021). Animals must also be provided with enough space, and access to pasture or outdoor areas. Not allowed in OA livestock production systems is the use of growth hormones, the prophylactic administration of antibiotics, and also not GMOs (Meekem and Qaim 2018). In the late 1990s, breeding and selection programs for OA crops begun but for many crops no OA-specific breeding programs have been initiated (Rempelos et al. 2021). However, plant breeding has recently been invigorated by the introduction of gene editing technologies to facilitate more targeted breeding for traits that are also desirable in OA systems, such as introducing traits from crop wild relatives for disease resistance and drought tolerance (Nawaz et al. 2020). For example, clustered randomly interspaced palindromic repeats (CRISPR) techniques involve creating proteins to recognize a specific deoxyribonucleic acid (DNA) sequence in a target plant genome, bind to it, and cut it. Then, the plant cell itself repairs the break in a way that alters the original genomic sequence and, often, leaves no transgenic material in the resulting plant. Some argue that gene editing is a more targeted and specific form of mutagenesis which is a traditional breeding technique making use of spontaneous mutations. Gene-edited crops are indistinguishable from those bred
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traditionally. However, the OA community in Canada and the United States of America is reaffirming and deepening boundaries to GMOs in response to arguments made by proponents of gene editing. Importantly, what distinguishes acceptable levels of human intervention in plant genomes, and the compatibility of both new and established breeding methods with OA are unclear (Nawaz et al. 2020). Overall, CRISPR and other biotechnological breeding strategies are regarded as incompatible with OA standards (Fess and Benedito 2018). There is no single OA system as the different schools of OA introduced in the previous sections differ in their practices and principles (Table 1.4; Kirchmann et al. 2008). However, all of them prohibit the use of synthetic fertilizers and pesticides. Biodynamic agriculture aims to manage channeling of cosmic forces into food to enhance spiritual development of mankind. In contrast, the school of OA based on the work of Balfour and Howard places the connection between soil fertility and human health, and the management of soil humus in the center. The biological OA practices apply nature’s principles and aim to enhance humification and humus formation (Kirchmann et al. 2008). Table 1.4 Development, principles and practices for different types of organic agriculture (use of synthetic fertilizers and pesticides is generally excluded; modified from Chalker-Scott 2013; Kirchmann et al. 2008) Type Emergence Principles 1920s Channeling of forces into Biological food is essential for the dynamic spiritual development of (biodynamic) mankind (Rudolf Steiner) Non-visible matter acts in soil, crops and animals, and the forces related to it can be managed Life can be influenced by application of compounds controlling spiritual forces in soils and plants Food enriched with spiritual powers could help mankind develop spiritually and reach complete intuition
Practices Production of compounds consisting of mixtures of minerals, wild plants and animal organs Application of humus and silica compounds to transfer forces into soils and crops Application of compost compounds prepared from animal manure to transfer forces via manure into soils and crops Biodynamic preparations that involve alchemy and homeopathy Lunar and astrological calendars for planting, managing and harvesting Stones used for channeling cosmic energy and radiant fields Burning of pests and weeds (pest ashing) Sensitive testing (including biocrystallization or morpho-chromatography) Each farm is a closed entity Return of nutrients present in toilet and a self-sustaining unit wastes is prohibited Only natural means and methods Only natural products can be used contain curing and saving forces for mankind (continued)
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Table 1.4 (continued) Type Emergence Principles 1930s Close relationship between Organic (Lady soil fertility and human Eve Balfour, Sir health Albert Howard) Physiological and spiritual wellbeing of man has its roots in soil Soil humus is the most significant natural reserve and the most fundamental component of a life-giving principle Plant nutrient supply through soluble fertilizers is a fatal error Synthetic fertilizers speed up the rate at which soil organic matter is exhausted Food quality is important for human health 1950s Application of nature’s Biological principles organic Holistic view of nature agriculture incorporating both wanted (Hans-Peter and unwanted properties Rusch) Process of humus formation is a sign of fertility and more important than the material itself Humification is the greatest biological regulation known to nature Humus is a manifestation of the biological achievement Let nature take its course
Soil application of soluble salts does not fulfil crop demand Supply is not synchronized with crop growth Nutrient losses are inevitable and high from artificial fertilizers compared with organic manures because the organic but not the artificial fertilizer is adapted to the turnover in soil
Practices Increase and maintain soil organic matter contents to guarantee soil health
Only composted organic materials should be applied to soil to maintain soil fertility
Natural soil layering should not be disturbed to achieve normal humus formation Soil tillage should be kept to a minimum to avoid disorder
Organic manures and composts can only be used as surface cover as both are not suitable for the root zone Synthetic fertilizers cannot be used
(continued)
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Table 1.4 (continued) Type Emergence Principles Sustain and enhance the Modern organic 1970s health of soil, plant, animal, agriculture human and planet (IFOAM)
Practices Exclusion of synthetic compounds including water-soluble synthetic fertilizers Use of natural means and methods only Avoid using fertilizers, pesticides, animal drugs and food additives with potential adverse health effects Produce high-quality, nutritious food that contributes to preventive health care and well-being Adapt management practices to Production is based on local conditions ecological processes and Reduce inputs by reuse recycling Recycle and manage materials and Fit the cycles and ecological balance in nature energy efficiently Establish habitats, and maintain the genetic and agricultural diversity be maintained All involved in production, processing, trade or consumption should protect and benefit the environment Build on relationships that Manage resources in socially and ecologically just ways ensures fairness with Contribute to a sufficient supply of regards to the common good quality food and other environment and life products opportunities Ensure life conditions of animals respecting their physiology, natural behavior and well-being Manage organic agriculture Science is necessary to ensure that organic agriculture is healthy, safe in a precautionary and and ecologically sound responsible manner to Valid solutions are also based on protect the health and practical experience, accumulated well-being of current and future generations and the wisdom and traditional and indigenous knowledge environment Adopt appropriate technologies by transparent and participatory processes
The four IFOAM principles for modern OA will be presented in more detail in the following section (IFOAM 2019). The principle of health states that OA should sustain and enhance the health of soil, plant, animal, human and planet as one and indivisible (Table 1.3). Soil health, in particular, is considered a cornerstone of OA (Tully and McAskill 2020). However, effects of OA practices on soil health are
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debatable (Roper et al. 2018, 2019; van Es and Karlen 2019). In practice, OA should avoid the use of fertilizers, pesticides, animal drugs and food additives that may have adverse health effects on organisms and ecosystems. High-quality, nutritious food that contributes to preventive health care and well-being should be produced by OA. According to the principle of ecology, OA should be based on living ecological systems and cycles, work with them, emulate them and help sustain them. Thus, OA management should be adapted to local conditions as ecological cycles are site-specific. Inputs should be reduced by reuse, and materials and energy recycled and managed efficiently. Habitats should be established, and the genetic and agricultural diversity be maintained. All involved in OA production, processing, trade or consumption should protect and benefit the environment. The principle of fairness emphasizes that OA should build on relationships that ensures fairness with regards to the common environment and life opportunities. Resources should be managed in socially and ecologically just ways. Further, management of life conditions of animals should respect their physiology, natural behavior and well-being. The principle of care highlights that OA should be managed in a precautionary and responsible manner to protect the health and well-being of current and future generations and the environment. While efficiency and productivity can potentially be increased by OA, the incomplete understanding of agriculture and ecosystems necessitates critical review of existing methods and new technologies. Aside scientific knowledge, however, practical experiences should be considered towards adopting appropriate technologies by transparent and participatory processes (IFOAM 2019). These key goals of modern OA have been lauded by some but Kirchmann et al. (2008) also questioned whether OA is able to achieve them. For example, soil health is not the only determining factor for crop health as exemplified by the formation of natural toxins in crops. Other reasons for concern are related to ecological processes and recycling. Like conventional agriculture, OA is man-made, and, in any case, the not naturally occurring conversion of natural land to agricultural use and its management is a drastic change. Also, manure is applied to soils under OA resulting in enhancement of process beyond levels occurring in natural soils. Whether OA can contribute to a sufficient supply of good quality food and other products is uncertain because of lower average crop yields for OA systems. Further, the contribution of OA to food security may be lower due to its 15% lower temporal stability per unit crop yield compared to conventional agriculture (Knapp and van der Heijden 2018). Questions arise also regarding animal husbandry according to natural behavior because domesticated animals differ in their behavior from natural or wild species (Kirchmann et al. 2008). It is questionable whether traditional knowledge which may include occult practices can be regarded as being of similar value as scientific knowledge. Thus, Kirchmann et al. (2008) raised concerns that OA principles may exclude other potentially superior solutions to achieve food security. Principles and specific requirements of OA regulations affect also the contribution of OA systems to public goods. Public goods can be defined as goods or services that society wants its citizens to have access to but which are normally not tradeable and non-excludable (Jespersen et al. 2017). However, there are currently
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no specific requirements, for example, in the EU, OA Regulation regarding resource efficiency including energy, climate change mitigation, and contribution to nature and biodiversity. In Denmark, the contributions of OA farms to the public goods ‘Nature and Biodiversity’, ‘Human Health and Welfare’, and ‘Animal Health and Welfare’ are mainly positive compared to those of conventionally managed farms. In contrast, the effects of OA on the public goods ‘Environment’ and ‘Energy and Climate’ are mixed with some positive and some negative effects. However, some OA requirements and practices cause dilemmas. For example, more space per animal and outdoor access improves the public goods ‘Animal Health and Welfare’ but has negative effects on the public goods ‘Environment’, and ‘Energy and Climate Change’. Such dilemmas should be solved to strengthen OA as an integrated policy measure supporting jointly the contribution to several public goods (Jespersen et al. 2017). Haller et al. (2020) emphasized that despite the legal framework and clearly defined cultivation guidelines, there is a lack of clearly defined minimum requirements and standards in important environmental areas of OA. For example, there are currently no minimum requirements for OA crop rotations (e.g., minimum number of crop rotation elements, integration of legumes, management of cover or catch crops or the degree of soil cover of open arable land during winter). Moreover, there are no binding requirements for minimum portions of ecological priority areas. On permanent OA grassland, binding standards on the frequency and periods of use are necessary to effectively promote biodiversity (Haller et al. 2020). Standards for certified OA production and processing prefer natural products while avoiding processing and, in particular, chemical processes (Løes and Adler 2019). For example, many recycled fertilizers are not allowed in OA, and farmers are often dependent on the use of animal and green manure from non-OA or conventional farms to maintain soil fertility (He 2019; Watson and Stockdale 2019). OA farmers import certified nutrient sources originating from conventional agriculture including animal manures, meat- and bone-meal, organic fertilizers, feedstuff and straw (Sadras et al. 2020). However, OA has a certain interest in recycling, resource utilization and renewable resources that may also contribute to a further development of circular economy and bioeconomy. Also, sustainable agriculture should: (i) replace finite by renewable resources, (ii) utilize all appropriate materials from society as sources for food, feed or fertilizers, and (iii) source all inputs as locally as possible, from renewable resources where harvesting is within the limits of a sustained production. Further, nutrients and OM need to be recycled back to OA soil to maintain soil fertility (Sapinas and Abbott 2020). The relatively poor performance of OA systems in recycling weakens the importance of OA for the development of a better resource utilization which will reduce environmental impacts from food production. Thus, Løes and Adler (2019) called for a revision of the regulations for OA production to soften restrictions regarding recycling and better utilization of valuable resources. Agroforestry, i.e., the intentional combination of trees and shrubs with crops or livestock has been recently proposed to be combined with OA practices to improve environmental outcomes (Wilson and Lovell 2016). Beneficial effects of combining agroforestry with OA practices may be related to reductions in soil loss, GHG
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emissions and nutrient leaching. Also, OA agroforestry systems may contribute to the conservation of biodiversity and have beneficial effects on livestock. Another potential advantage is the increased resilience of perennial polyculture systems such as agroforests to perturbations, and cultural benefits such aesthetics. However, both agroforestry and OA adoption has been low due to barriers such as expense of establishment, landowner’s lack of experience with trees, and the time and knowledge required for management (Wilson and Lovell 2016). Animal welfare is among the central principles in OA (Kabir 2019). Animals must be provided high-quality feed, adequate space, fresh air, natural light, exercise, access to outdoors, amongst others. Moreover, tail, teeth, and beak trimmings are condemned in OA. Organic livestock production standards are sets of requirements that describe what practices can be considered organic. The most common organic standards for animal production, handling, and product processing requirements are the EU Organic Standard for Livestock Production, the USDA Standard, and the IFOAM Standard for Animal Husbandry (Kabir 2019). The OA standards generally address various aspects of OA production such as general farm production requirements and conversion periods, crop production requirements and requirements for the collection of wild products, animal production requirements (including beekeeping), processing and handling requirements, social justice requirements, and labeling requirements. The requirements commonly found in OA standards are in the Common Objectives and Requirements of Organic Standards (COROS). However, not all OA standards cover all of those areas, e.g., some OA standards do not cover animal production or address social justice. Further, some OA standards cover additional or more detailed areas, such as aquaculture or mushroom production. The IFOAM Standard is an example of a standard covering all of the above areas (Kabir 2019).
1.3 Conclusions The global land area under OA practices is increasing driven by increasing consumer demand for OA products which are perceived as being more environmentally friendly than those produced by conventional practices. About a century ago, various disciplines of OA were introduced in several global regions by different thought leaders, and interest in OA particularly increased with the environmental movement in the second half of the twentieth century. OA is now practiced on about 1.6% of the global agricultural land area. The beneficial effects of OA are based on the omission of use of mineral fertilizers and synthetic pesticides, and the use of more diverse crop rotations, cover crops and animal manure. Soil biological processes are regarded as the foundation for sustaining OA productivity. Importantly, a site- specific humus or SOC stock contributes to the success of OA practices. However, primary soil C inputs are also lower because of 19 to 25% lower OA yields and, together with tillage for weed control, this may result in lower steady-state equilibrium SOC stocks compared to those under conventional practices. Other challenges
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are how to satisfy the demand for OA manure, and the gap in plants specifically bred for favorable performance under OA soil and land-use management practices. These are some of the major challenges that must be addressed to support a more widespread adoption of OA to feed an increasing global population. Further, adoption of OA practices is facilitated by price premiums for products, is codified by law in many countries and continues to evolve. However, there may be little market for higher priced OA products in developing countries. Long-term field experiments in all major global growing regions are a valuable source to improve OA versus those of conventional soil and land-use management practices.
1.4 Review Questions 1. Describe the early developments in OA and compare them with the history of conventional agriculture 2. Contrast and compare the different early types of OA 3. Summarize the major common OA principles and practices 4. Compare the environmental, economic and social repercussions of OA with those of conventional agriculture 5. What are the major challenges for modern conventional agriculture vs. those of modern OA and how can those be addressed? 6. How can global food and nutritional security be improved? 7. Develop and describe a hybrid conventional-organic agriculture system
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Stockdale EA, Lampkin NH, Hovi M et al (2001) Agronomic and environmental implications of organic farming systems. Adv Agron 70:261–327 Sumberg J (2022) Future agricultures: the promise and pitfalls of a (re)turn to nature. Outlook Agric 51:3–10. https://doi.org/10.1177/00307270221078027 Sumberg J, Giller KE (2022) What is ‘conventional’ agriculture? Soil Secur 32:100617. https:// doi.org/10.1016/j.gfs.2022.100617 Tang FHM, Lenzen M, McBratney A, Maggi F (2021) Risk of pesticide pollution at the global scale. Nat Geosci 14:206–210. https://doi.org/10.1038/s41561-021-00712-5 Tscharntke T, Grass I, Wanger TC, Westphal C, Batáry P (2021) Beyond organic farming – harnessing biodiversity-friendly landscapes. Trend Ecol Evol. https://doi.org/10.1016/j. tree.2021.06.010 Tuck SL, Winqvist C, Mota F et al (2014) Land-use intensity and the effects of organic farming on biodiversity: a hierarchical meta-analysis. J Appl Ecol 51:746–755. https://doi. org/10.1111/1365-2664.12219 Tully KL, McAskill C (2020) Promoting soil health in organically managed systems: a review. Org Agric 10:339–358. https://doi.org/10.1007/s13165-019-00275-1 Van Es HM, Karlen DL (2019) Reanalysis validates soil health indicator sensitivity and correlation with long-term crop yields. Soil Sci Soc Am J 83:721–732. https://doi.org/10.2136/ sssaj2018.09.0338 Van Wagenberg CPA, de Haas Y, Hogeveen H et al (2017) Animal board invited review: comparing conventional and organic livestock production systems on different aspects of sustainability. Animal 11(10):1839–1851. https://doi.org/10.1017/S175173111700115X Vigar V, Myers S, Oliver C et al (2020) A systematic review of organic versus conventional food consumption: is there a measurable benefit on human health? Nutrients 12:7. https://doi. org/10.3390/nu12010007 Vogt G (2007) The origins of organic farming. In: Lockeretz W (ed) Organic farming: an international history. CABI, Wallingford, pp 9–29 Watson C, Stockdale EA (2019) Maintaining soil fertility and health in organic crop cultivation. In: Köpke U (ed) Improving organic crop cultivation. Burleigh Dodds, Cambridge, pp 61–85. https://doi.org/10.19103/AS.2017.0029.03 Wiggins Z, Nandwani D (2020) Innovations of organic agriculture, challenges and organic certification in the United States. Sustain Agric Res 9:50–57. https://doi.org/10.5539/sar.v9n3p50 Willer H, Trávníček J, Meier C, Schlatter B (eds) (2022) The world of organic agriculture. Statistics and emerging trends 2022. Research Institute of Organic Agriculture (FiBL)/IFOAM – Organics International, Frick/Bonn Wilson MH, Lovell ST (2016) Agroforestry – the next step in sustainable and resilient agriculture. Sustainability 8:574. https://doi.org/10.3390/su8060574 Yang G, Wagg C, Veresoglou SD, Hempel S, Rillig MC (2018) How soil biota drive ecosystem stability. Trends Plant Sci 23:1057–1067. https://doi.org/10.1016/J.TPLANTS.2018.09.007 Yin R, Siebert J, Eisenhauer N, Schädler M (2020) Climate change and intensive land use reduce soil animal biomass via dissimilar pathways. elife 9:e54749. https://doi.org/10.7554/ eLife.54749 Ziechaus-Hartelt C (1991) Bioland – ein Verband entwickelt sich. Bioland 2:13–14 Zimmermann B, Claß-Mahler I, von Cossel M et al (2021) Mineral-ecological cropping systems – a new approach to improve ecosystem services by farming without chemical synthetic plant protection. Agronomy 11:1710. https://doi.org/10.3390/agronomy11091710
Chapter 2
Effects of Organic Agriculture on the Soil Carbon Stock
Contents 2.1 Basic Principles of Soil Carbon Sequestration 2.1.1 Soil Carbon 2.1.2 Soil Carbon Sequestration 2.2 Soil Inorganic Carbon 2.2.1 Effects of Organic Agriculture Practices on Soil Inorganic Carbon 2.2.2 Soil Inorganic Carbon Stocks under Organic Agriculture 2.3 Soil Organic Carbon 2.3.1 Effects of Organic Agriculture Practices on Soil Organic Carbon 2.3.2 Soil Organic Carbon Stocks Under Organic Agriculture 2.4 Net Effect of Organic Agriculture on Soil Carbon Sequestration 2.5 Conclusions 2.6 Review Questions References
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Abstract The soil carbon (C) stock is comprised of the soil inorganic carbon (SIC) and the soil organic carbon (SOC) stock. A site-specific steady state equilibrium soil C stock evolves under natural conditions depending on the balance between soil C inputs (plant residues) and losses (decomposition, erosion, leaching). The SIC stock is perceived as being less dynamic than the SOC stock with uncertain effects of organic agriculture (OA) on SIC sequestration rate, and not the focus of agricultural soil and land-use management. In contrast, the SOC stock receives increasing attention due to its importance for the global climate and soil health. However, increases in the SOC stock may also alter the greenhouse gas (GHG) balance and this must be addressed in the assessment of soil C sequestration practices to mitigate climate change. The historical loss of SOC due to the conversion of natural ecosystems to agroecosystems provides an opportunity to use soil and land-use management practices to partially replenish lost SOC stocks. Topsoil (0–15 cm depth) SOC stocks have been shown to increase under OA management by 1.98–3.50 Mg C ha−1 compared to nonorganic management. But the addition of exogenous C (e.g., with
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manure) for this improvement and SOC sequestration for climate change adaptation and mitigation may be important. Compared to nonorganic management, topsoil SOC sequestration rates did either not differ or were 0.29–0.45 Mg C ha−1 year−1 higher under OA, respectively. However, assessments of SOC sequestration and stocks for the entire rooted soil profile are scanty but needed to fully address long- term effects of agricultural management on SOC. Lower primary soil C inputs due to lower OA yields and higher losses by tillage compared to conventional no-tillage (NT) system may result in lower steady state equilibrium SOC stocks in OA systems. There is some evidence that root C allocation is higher under OA than that under nonorganic management. More agricultural soils will be managed in the future by OA driven by increasing consumer demand. The net effects of increased soil and land-use management for OA on the global soil C stocks must be critically assessed also in relation to long-term field experiments to support the design of climate-smart and climate resilient agroecosystems. Therefore, the objectives of this chapter are to describe in detail what processes and practices result in changes in SIC and SOC stocks and sequestration in soils under OA management. Keywords Soil carbon sequestration · Soil inorganic carbon · Soil organic carbon · Climate change mitigation · Greenhouse gases · Turnover time · Temperature increase · Soil properties · Soil health · Recommended management practices · Carbon dioxide removal · Natural climate solution · Pedogenic carbonates · Soil organic carbon persistence · Plant roots · Rhizodeposition · Microbial necromass · Mineral-associated organic matter · Particulate organic matter · Soil and land-use management
2.1 Basic Principles of Soil Carbon Sequestration 2.1.1 Soil Carbon Agricultural practices including both conventional agriculture and organic agriculture (OA) affect the soil carbon (C) stock comprised of the soil inorganic carbon (SIC) and the soil organic carbon (SOC) stocks (Lorenz and Lal 2018). Historically, converting natural ecosystems for agricultural uses has caused losses from the SOC stock in the order of 116–135 Pg C (1 Pg = 1 Gt = 1015g) from the top 2-m of soil (Sanderman et al. 2017; Lal 2018). It is useful to note that 1 Pg C yields 3.66 Pg of carbon dioxide (CO2), and that this is equivalent to a concentration change of ∼2.124 ppm in the atmospheric CO2 (Ballantyne et al. 2012). The historical SOC losses indicate a hypothetical though highly impractical upper bound for restoring SOC stocks through adjustments in soil and land-use management (Powlson et al. 2022). Nolan et al. (2021) used the silo conceptualizations of terrestrial C storage centered on refilling past C losses from land use change and land management. In contrast, Janzen et al. (2022) suggested that what matters
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in projecting SOC change is not past losses but future C inputs. They argued for a re-orientation in emphasis from soil processes towards a wider ecosystem perspective, starting with photosynthesis and net primary production (NPP). Based on this approach, the maximally achievable rate of C sequestration in arable lands globally may be in the order of 0.1–0.2 Pg C year−1 (Janzen et al. 2022). Minasny et al. (2022) discovered: (i) many uncertainties in Janzen et al.’s back-of-the envelope calculation, (ii) the calculation was not regarded robust because the parameters were pragmatically determined, and (iii) current NPP estimates cannot be used to estimate future SOC stock storage potential. This chapter provides a general overview on the basic principles of soil C sequestration, and on SIC and SOC dynamics. This is followed by a discussion on the effects of key OA practices on sequestration and stocks of SIC and SOC. The final section presents the net effects of OA on soil C sequestration. Depending on differences in agricultural management practices, SOC losses continue after initial land conversion of natural ecosystems as the aim of agronomic production is to maximize plant productivity and increase the capture and removal of photosynthetically fixed C from a site with harvestable products (extractive agriculture) while SOC sequestration is not focus of farm management (Amelung et al. 2020). Further, accelerated erosion rates by agricultural activities such as soil tillage result also in removal of SOC from a site, its redistribution over the landscape and C export to aquatic ecosystems (Doetterl et al. 2016). Thus, SOC in a soil at a given time is the result of a complex inheritance linked to the functioning and use of soil over several hundreds or thousands of years (Basile-Doelsch et al. 2020). However, already millennia ago, Virgil established the link between C’s darkening hue and the fertility of land (Janzen 2015). Thus, preserving and replenishing SOC-rich soil organic matter (SOM) has been the underlying aim of conservation agriculture (CA) for a long time, and is an important strategy for addressing climate change (Bohoussou et al. 2022; Xiao et al. 2021; Crowther et al. 2019). The SOC stock may comprise 47% of the climate change mitigation potential for agriculture and grasslands (Bossio et al. 2020). Less well studied than SOC is the other principal soil C form in agricultural soils, i.e., carbonate-C, inorganic C or SIC (Lorenz and Lal 2018; Monger et al. 2015). The SIC stock consists mainly of carbonates and bicarbonates. Whether SIC has changed historically by initial land conversion of natural ecosystems for agriculture, and subsequently by agricultural soil and land-use management practices is a matter of debate (Sanderman 2012). An et al. (2019) reported little to mixed evidence of land-use effect on SIC while also noting shallow sampling depths of many studies and inventories. For example, Kim et al. (2020a) reported that SIC stocks to 7.3-m depth were reduced under rainfed-cropland and even more so under irrigated cropland compared to those under native vegetation. Thus, agricultural practices can fundamentally alter the SIC cycle but in comparison to SOC, it is generally thought that SIC is much more ‘stable’ and less sensitive to perturbations (Lal and Kimble 2000; Monger et al. 2015). However, changes in SIC stocks can be more than one order of magnitude larger than those in SOC stocks (Kim et al. 2020a). Nevertheless, preserving and replenishing the SIC stock is not among the aims of CA although
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carbonates influence soil microbial activity, the rate of SOM mineralization, soil pH, adsorption-desorption processes, and soil cementation (Ming 2006; Garcia et al. 2018). For example, the presence of CaCO3 in soil is important for acidity buffering, aggregate formation and stabilization, organic matter (OM) stabilization, microbial and enzyme activities, nutrient cycling and availability, and water permeability and plant productivity (Raza et al. 2020). The presence of CaCO3 may alter water retention through changes in effective soil texture, and via alteration of soil structure and pores (Bagnall et al. 2022). There may also exist a previously unrecognized SOC stabilization mechanism associated with carbonates (Heckman et al. 2021). In Earth’s history, global weathering of minerals and rocks has had long-term effects on atmospheric CO2 levels. Specifically, long-term stabilization of C in organic and mineral substrates may take place through interactions involving glycoproteins, melanin, extracellular polymeric substances, and formation of secondary minerals and mineraloids (Finlay et al. 2020). Thus, the dynamics of both SIC and SOC must be better understood to remove atmospheric CO2 and transfer it into terrestrial pools. Soils in humid climates have potential to increase storage of SOC, and those in arid and semiarid climates have potential to store both SOC and SIC through adoption of judicious land use and science-based management practices (Lal et al. 2021).
2.1.2 Soil Carbon Sequestration Buringh (1984) provided estimates on the SOC content of major soil orders and land uses, and on losses by clearing of forests for grassland or cropland. Subsequently, the first incidence of the terms “soil”, “carbon” and “sequestration” being used together to present a concept, occurred in the year 1991 (Thornley et al. 1991). Thus, “soil C sequestration” is a relatively new concept (Feller and Bernoux 2008), and soils have never been harnessed at large scale for the purpose of sequestering C (Guenet et al. 2021). Most definitions of C sequestration refer simply to the removal of CO2 from the atmosphere and storage in organic forms in plants, plant residues and soil (Olson et al. 2014; Chenu et al. 2019). However, “soil C sequestration” as a concept should not be restricted to quantification of soil C storage or the CO2 balance. Specifically, agriculture contributes also to the emissions of other greenhouse gases (GHGs), i.e., nitrous oxide (N2O) and methane (CH4; Smith et al. 2008). In fact, all GHG fluxes must be computed at the plot level in C-CO2 or CO2 equivalents (CO2e or CO2eq), and as many as possible GHG emission sources and sinks across the soil-plant system should be incorporated (Feller and Bernoux 2008). The CO2e is the concentration of CO2 that would cause the same level of radiative forcing (RF) as a given type and concentration of GHG. It is based on the 100-year global warming potential GWP100 metric. The GWP100 represents the time-integrated climate forcing (perturbation to the Earth’s balance between incoming and outgoing energy) due to a one-off pulse emission of one Mg of a GHG over the 100 years following
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its emission, relative to the corresponding impact of a one Mg pulse emission of CO2 (Allen et al. 2016). The GWP100 values on a mass basis for CO2, CH4 and N2O are 1, 28, and 265, respectively, according to IPCCs Fifth Assessment Report (AR5; https://www.ipcc.ch/report/ar5/syr/). Soil C sequestration for a specific agroecosystem, in comparison with a reference system, should be considered as the result – for a given period of time and fraction of space – of the net balance of all GHGs, computing all emissions sources at the soil-plant-atmosphere interface (Feller and Bernoux 2008). Soil C sequestration refers, therefore, to GHGs, expressed in equivalent C–CO2, stored in the soil and originating from the atmosphere while C storage is C stored in the soil irrespective of its origin. Specifically, in some cases the increase in agroecosystem SOC stock does not imply a removal of CO2 from the atmosphere but a transfer from one pool to another. This is the case, for example when manure or other exogenous organic material are added to the soil of an agroecosystem (Schlesinger 2000; Powlson et al. 2011). Meaningful increases in C sequestration at one farm or region must occur without simultaneous reductions in SOC at another location from where the organic material is transported from (Amelung et al. 2020). Thus, organic C inputs into soil must be produced on-site, e.g., by enhancing crop production and green manure, and not transferred from one terrestrial location to another (e.g., manure). The SOC storage implies an increase in the SOC stock whereas SOC sequestration assumes a net removal of atmospheric CO2 (Chenu et al. 2019). However, SOC storage and SOC sequestration should not be confused with soil C storage and sequestration as agricultural soils may contain also SIC in the form of carbonates. Further, soil C sequestration in the global agroecosystem area only occurs when the net balance of all GHGs is negative irrespective of the lateral transfer and addition of exogenous C produced from atmospheric CO2 within the global agroecosystem area. For example, an increase in the SOC stock may also be associated with an increase in labile SOC. This may promote the release of mineral N and, if this N is not taken up by plants, result in increased N2O emissions in the long term offsetting the climate benefit of increased SOC stocks (Lugato et al. 2018). Specifically, the formation of SOC may trigger a higher primary production and enhance further SOC storage, but also increase the risk of N2O emissions because of the increase in N sources and the shift to soil environmental conditions more favorable to N2O emissions (Guenet et al. 2021). Thus, climate mitigation induced by increased SOC storage is generally overestimated if associated N2O emissions are not considered but, with the exception of reduced tillage, is never fully offset. If agricultural soils do progress towards SOC saturation in the future, then N2O emissions will gain more importance, highlighting the need for effective mitigation strategies (Davies et al. 2021). Otherwise, some management practices (i.e., additions of biochar or non-pyrogenic C) may even decrease N2O emissions (Guenet et al. 2021). Among the terms to describe the stability and persistence of soil C relative to atmospheric C is the residence time which represents either the concept of transit time or system age but also the ratio of a C stock over an input or output flux (Sierra et al. 2017). When the exchange of C between the soil pool and another pool is
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balanced (i.e., at steady state), the mean residence time (MRT) equals turnover time (Carvalhais et al. 2014). For example, Chen et al. (2020c) divided the SOC stock in 0–20 cm depth by the output flux heterotrophic respiration (Rh) to estimate MRT. Across terrestrial biomes, the MRT of SOC ranged from 0.47 to 56.75 years globally. He and Xu (2021) calculated the soil microbial MRT, i.e., the duration the microbes remain alive in soils, based on the basal respiration and microbial biomass C. The global average of microbial MRT was estimated to be 38 days. Edaphic factors (soil texture, pH, topsoil porosity, soil C, and total nitrogen) dominated the MRT variations (He and Xu 2021). Turnover time is a good indicator of soil C stability. The global turnover time of C in soil to 1-m depth is estimated at 35.5 years while the global turnover time of pedogenic inorganic C was estimated at 85,000 years (Schlesinger 2006; Yan et al. 2017). Global mean subsoil (0.3–1.0 m depth) organic C turnover times have been estimated at 1015 years (Luo et al. 2019), highlighting the importance of SOC at deeper depths for sequestration (Lorenz and Lal 2005). Deep soil horizons may have a potential to bypass stoichiometry constraints (i.e., availability of N and P) on SOC storage compared to overlying horizons (Bertrand et al. 2019). Agricultural subsoils offer an untapped potential to enhance global C storage (Button et al. 2022). The median age of C at 1-m depth is >1000 years (Basile-Doelsch et al. 2020). However, the reasons for the stability of deep SOC are less well known (Button et al. 2022; Rumpel and Kögel-Knabner 2011), while about 10–20% of deep SOC may also be dynamic and not inert (Hobley et al. 2017; van der Voort et al. 2019). Kirschbaum et al. (2021) proposed that lower labile C inputs at deeper soil depths could reduce priming and potentially preserve up to half of buried C for centuries. The priming effect refers to the supply of complex decomposable substrates providing competent soil microorganisms with the energy source required to biodegrade stabilized SOC (Basile-Doelsch et al. 2020). However, there is little known about priming effects in soils under natural conditions, and its potential to enhance SOC storage at depth (Kirschbaum et al. 2021). Overall, subsoils, while highly heterogeneous, are in many cases more suited to long-term C sequestration than topsoils (Button et al. 2022). Both inaccessibility to decomposers through physico-chemical protection and recalcitrance control SOC stability and, thus, turnover time (von Lützow et al. 2006). However, long-lived SOC does not necessarily share unifying biochemical characteristics, i.e., SOC persistence does not dependent on its intrinsic biochemical properties (Waring et al. 2020). Thus, it may be more important to focus on the spatial and geochemical processes that control SOC availability to microorganisms, rather than the origin or physicochemical composition of any particular class of SOC (Waring et al. 2020). Otherwise, pyrogenic C (charcoal or black carbon) thermally altered by fire may be relatively ‘stable’ as it contains highly recalcitrant and very slowly decomposing components. Accounting for pyrogenic C presence, for example, results in overall shorter turnover time estimates for native-derived SOC as pyrogenic C is selectively preserved (Lavallee et al. 2019). Atmospheric CO2 concentrations are now higher (412.5 ppm in 2020; Blunden and Boyer 2020) than those in the last 800,000 years estimated from ice core
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records, and at levels last seen around four million years ago (Lenton et al. 2019), with a total current amount of about 880 Pg C. Increased emissions of GHGs into the atmosphere caused by human activities have also contributed to increases in global mean surface (land and ocean) and surface air temperatures by 0.87 °C and 1.53 °C from 1850–1900 to 2006–2015, respectively (Arneth et al. 2019). Historically, global mean temperature has slightly but steadily warmed, by ~0.5 °C, since the early Holocene (around 9000 years ago; Osman et al. 2021). When compared with recent temperature changes, both the rate and magnitude of modern warming are unusual relative to the changes of the past 24,000 years. The temperature variability across this period was linked to two primary climatic mechanisms: RF from ice sheets and GHGs; and a superposition of changes in the ocean overturning circulation and seasonal insolation (Osman et al. 2021). The warming has likely affected global agriculture and, in particular, food production (Ray et al. 2019). Warming, changing precipitation patterns and greater frequency of some extreme events are already affecting food security (Arneth et al. 2019). Canopy air and soil warming experiments indicate the SOC stocks may not change globally as increased soil C inputs from increases in plant productivity at higher temperatures may offset SOC losses (Liu et al. 2020b). However, SOC pool responses to warming are differently for air and soil warming manipulations (Rocci et al. 2021). Further, while the SOC and mineral-associated (MAOC) fraction did not respond to experimental warming, the particulate organic carbon (POC) fraction decreased by 10.05% (Rocci et al. 2021). Based on a global meta-analysis, Heckman et al. (2022) concluded that higher temperatures were related to decreased persistence (radiocarbon abundance) in POC and MAOC fractions. However, higher temperatures were only associated with lower SOC storage for free POC in the surface soil layers. In contrast, in other fractions and deeper layers, the influence of warmer temperatures on SOC turnover was limited. The free POC fraction is more microbially accessible than occluded POC, and the increase in biological activity in response to temperature increase may enhance microbial enzymatic attack on this fraction. In contrast, the increase in biological activity in response to increase in temperature may promote SOC storage in the occluded and MAOC fractions. Specifically, enhanced biotic activity can promote soil aggregation, and enhanced decomposition may result in more microbial necromass sorbed to mineral surfaces. Thus, temperature-driven SOC losses from occluded-POC, MAOC, and subsurface SOC pools may be less substantial under a warming climate (Heckman et al. 2022). The prospect of soil C sequestration is based on the potential to control the mounting CO2 in the atmosphere and its associated temperature increase by soil and land-use management practices (Janzen 2015). In addition, increasing SOC stocks has also numerous direct and indirect positive impacts on soil quality and soil health, and on food production (Lal 2016). Soil health for the agricultural community has been defined as the capacity of soils to provide a sink for C to mitigate climate change and a reservoir for storing essential nutrients for sustained ecosystem productivity (Toor et al. 2021). The SOC content is the most important and universally accepted master property that determines the state of many soil physical
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(soil structure, density, porosity, water-holding capacity, percolation rate and erodibility), soil chemical (nutrient availability, sorption capacity and pH), and soil biological (biodiversity, microbial biomass and basal respiration) properties (Cotrufo and Lavallee 2022; Kuzyakov and Zamanian 2019). The SOC is closely tied to soil health (Liptzin et al. 2022), and plays a central role and is a master indicator for soil functioning (Kopittke et al. 2022). Increases in SOC stocks, for example, may increase drought tolerance of the food production system (Lizumi and Wagai 2019). The SOC management contributes to climate change adaptation, mitigation and sustainable development (Arneth et al. 2019). In fact, the percentage change in SOC calculated from estimated historical SOC stocks predating anthropogenic land-use and present-day SOC stocks has been proposed as a global indicator of the soil planetary boundary (Kraamwinkel et al. 2021). Effective management of soil at a global scale is also among the most powerful practices in the fight against the combined threats of climate change and biodiversity loss (Crowther et al. 2019). However, increases in SOC stocks might not have the same positive effects on soil organisms and their associated functions as that of aboveground organisms and functions (Guerra et al. 2021). Further, trade-offs between increases in SOC stocks and other services of agroecosystems may also exist (Bartkowski et al. 2020). For example, rewetting drained organic soils may increase SOC stocks but also decrease agricultural production (Albert et al. 2017). The relationship between SOM composition and soil functioning is an active field of research (Kopittke et al. 2022; Hoffland et al. 2020). Specifically, the potential tension between the management goals enhancing SOC sequestration versus improving soil fertility, health or quality must be addressed (Waring et al. 2020). Because nutrient release and cycling depends on microbial decomposition of SOM, this co-benefit has been understood by some to be at odds with intentions of sequestering SOC (Chaplot 2021; Janzen 2015). Global cropland contains on average an estimated 6.6 Mg Nha−1, 0.7 Mg P ha−1, and 0.9 Mg Sha−1 in SOM (Duiker 2022). Dynarski et al. (2020) developed a flow-based model of SOC persistence in which consumption and transformation by soil microbes is crucial for producing mineral- associated OM, allowing movement and transformation of SOM. Thus, restoring soil biological function and SOC sequestration may be fundamentally interwoven, rather than contradictory, management goals (Dynarski et al. 2020). Both edaphic and climatic factors control the SOC stocks to 2-m depth globally (Luo et al. 2021). The SOC stock of an agroecosystem (i.e., cropland, grassland), in particular, is determined by the balance between inputs and losses, and in steady state equilibrium when environmental conditions are not changing. Thus, the most effective way to accumulate SOC is to increase C inputs by a change in management (Amelung et al. 2020). The SOC stock can also be managed to reduce net anthropogenic GHG emissions as a contribution to mitigating climate change. The technical potential for CO2 removal by SOC sequestration in cropland and grassland soils is estimated at 0.4–8.6 Gt CO2e year−1 (Jia et al. 2019). Otherwise, if sustainable soil management (SSM) practices are adopted, the global biophysical potential of SOC sequestration is between 0.14 and 0.56 Gt C per year to 30-cm depth (FAO and ITPS 2022). SSM practices include cropping systems diversification, cover cropping,
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addition of organic manures, conservation tillage, mulching, fertility management, agroforestry, and rotational grazing, water management, among others. Mitigation can be achieved by enhancing sinks through maximizing the land- surface uptake of GHGs (Schulze et al. 2009). Between 2020 and 2050, agriculture may provide a mitigation potential of 4.1 Gt CO2e year−1 from cropland and grassland SOC management, agroforestry, use of biochar, improved rice (Oryza sativa L.) cultivation, and livestock and nutrient management (Nabuurs et al. 2022). Protection, improved management, and restoration of forests, peatlands, coastal wetlands, savannas and grasslands have the potential to reduce emissions and/or sequester 7.3 Gt CO2e year−1 (Nabuurs et al. 2022). A major potential for C sequestration is in cropland soils, especially those with large yield gaps and/or large historic SOC losses, realized by soil group-specific management practices (Amelung et al. 2020). Compared to cropland management practices, grazing land management/pasture improvement has a lower potential for mitigating GHG emissions (Smith et al. 2008). Recommended management practices (RMPs) include nutrient management, increased productivity (e.g., fertilization), fire management and species introduction (including legumes). The management of organic soils (e.g., avoided drainage of wetlands) positively mitigates CO2 emissions but has a negative mitigation effect on CH4 emissions. The restoration of degraded lands (e.g., erosion control, organic amendments, nutrient amendments) has a positive effect on CO2 emissions. With respect to livestock management, improved feeding practices have the highest potential (Teague et al. 2016), followed by specific agents and dietary additives, and longer term structural and management changes and animal breeding. However, livestock management is only suitable for mitigating CH4 emissions. Improved storage and handling, and anaerobic digestion of manure and biosolids have also positive mitigation effects on CH4 emissions. More efficient use of manure and biosolids as nutrient sources has positive mitigation effects on both CO2 and N2O emissions. Bioenergy (e.g., energy crops, solid, liquid, biogas, residues) has a positive mitigation effect on CO2 emissions (Smith et al. 2008). In summary, sustainable land management options including OA can contribute to adaptation and mitigation of climate change (Arneth et al. 2019). Bolinder et al. (2020) synthesized twenty reviews on management-induced changes in agroecosystem SOC stocks at long-term experiments with a mean duration of mostly between 10 and 25 years (Table 2.1). The management-induced increases in SOC stocks (mean soil depths mainly 15–30 cm) decreased in the order recycled organic materials-manure additions>cover crops>N- fertilization>aboveground crop residue retention. In comparison, SOC stocks in boreo-temperate regions increased 64–232 kg C ha−1 year−1 under no-till (NT) or direct seeding, and globally by 500–600 kg C ha−1 year−1 under perennial forage crops. However, only two of the twenty reviews in Bolinder et al. (2020) used an equivalent soil mass (ESM) approach which is the preferable method to address effects of management practices on SOC stocks by considering also changes in soil bulk density (Meurer et al. 2018; Ellert and Bettany 1995). Also, the variation between individual sites was large, and the reasons for this is in need for additional
2 Effects of Organic Agriculture on the Soil Carbon Stock
48
Table 2.1 Mean effects of management practices on the mean relative response ratio (%) of soil organic carbon change and on the mean soil organic carbon stock change (kg C ha−1 year−1) based on twenty reviews of long-term experiments (modified from Bolinder et al. 2020) Management practice Recycled organic materials-manure Cover crops N-fertilization Aboveground crop residue retention a
Relative response ratioa,b % 30.3
Soil organic carbon stock change rateb kg C ha−1 year−1 529
10.5 7.2 9.9
358 302 212
Obtainable with either soil organic carbon concentrations or mass Mean soil depths 15–30 cm except for one review with a mean sampling depth of 13 cm
b
research. Further, the management practices in long-term experiments do not necessarily reflect today’s agronomic practices (Bolinder et al. 2020). Thus, studies on long-term changes of SOC in farmer’s field including SOC stock changes considering the ESM approach are needed to validate SOC changes observed in long-term field experiments. Between 2020 and 2050, improved and sustainable crop and livestock management, and C sequestration in agriculture, the latter including soil C management in croplands and grasslands, agroforestry and biochar, may contribute 1.8–4.1 GtCO2-eq year−1 reduction of the projected economic mitigation potential of agriculture, forestry and other land use (AFOLU) options (Skea et al. 2022). Soil C sequestration is a low-cost CO2 removal (CDR) option. Lal et al. (2018) estimated the global technical potential for SOC sequestration by managing agroecosystems (Table 2.2). The potentials varied also widely for each land use with total potentials of 0.70–4.14 and 1.06–2.93 GtCO2eq year−1 for cropland and grass/steppe ecosystems, respectively. Similarly, Bossio et al. (2020) summarized the contribution of SOC by grassland and agriculture land management to natural climate solutions (NCS; Table 2.2). Several definitions for NCS exist but focus is on climate change mitigation activities, referring specifically to nature-based solutions (NBS) for climate change mitigation (Schulte et al. 2022; Seddon 2022). Bossio et al. (2020) considered only the best-understood NCS options for incremental change to existing farming practices as, for example, NT was excluded as there is less consensus on its impact on SOC stocks (Ogle et al. 2019). Biochar had the highest mitigation potential followed by cover cropping, trees in croplands, avoided grassland conversion, and grazing either with optimal density or legumes in pastures which had similar potential. Not included were practices that reduce N2O and CH4 emissions without protecting or enhancing SOC sinks such as improved nutrient and livestock management. Overall, SOC protection and sequestration may comprise half of the total potential mitigation in grasslands and agriculture (Bossio et al. 2020). Dynarski et al. (2020 compared the effects of selected cropland management practices on SOC flow, and trade-offs/constraints. Practices with SOC sequestration potential included: (i) perennialization or inclusion of perennial crops in rotation, (ii) cover cropping, (iii) residue retention/plant high C-input crops, (iv) organic
49
2.1 Basic Principles of Soil Carbon Sequestration
Table 2.2 Technical potential of soil organic carbon sequestration in agroecosystems compared to the contribution of soil organic carbon of agroecosystems to natural climate solution (NCS) pathways (modified from Lal et al. 2018; Bossio et al. 2020)
Land use Arable cropland Tree- intercropping Grazing/ rangeland
Silvopasture Biochar
Technical potential of soil organic carbon sequestrationa GtCO2e year−1 0.22–2.24 0.33–1.65 0.51–1.03
0.51–1.83 1.58–3.44
Natural climate solution pathway Conservation agriculturec Cover cropping Trees in croplands Avoided grassland conversion Grazing-optimal intensity Grazing-legumes in pastures Silvopastoral practicesd Biochar
Contribution of soil organic carbonb GtCO2e year−1 –c 0.41 0.28 0.23 0.15 0.15 –d 1.1e
Lal et al. (2018) Bossio et al. (2020) c No-till and other conservation agriculture practices not included due to unresolved questions about long-term efficacy (Bossio et al. 2020; Page et al. 2020) d Silvopastoral practices included in the reforestation pathway e Direct mitigation potential a
b
amendments, (v) reduce tillage, (vi) biochar amendments, and (vii) deep-rooted crops. The comparison was based on the observation that SOC longevity may best be understood as resulting from continual movement and microbial transformation of organic compounds throughout the soil matrix. This definition is, however, directly at odds with how SOC longevity is represented in current policies. In climate policy, SOC is generally assumed to be a vulnerable pool at risk of being quickly lost via microbial degradation or other avenues of physical loss if SOC building practices are not maintained indefinitely. Resolving these definitions is critical given current interest in policies to promote SOC sequestration. Overall, agricultural soils that could be considered good candidates for SOC sequestration projects are those with a large potential sink size. Among them may be deep and high clay soils that are relatively depleted in SOM relative to their maximum sink size. Management practices that increase soil biological capacity should be promoted and incentivized to support both soil health and persistent SOC accumulation. Implementing agricultural management practices that support soil microbial communities may promote active C cycling in surface soils, with benefits for soil fertility and structure, as well as long-term accumulation of SOC, particularly in deeper soil horizons (Dynarski et al. 2020). Lessmann et al. (2022) combined global meta-analytical results on improved cropland management practices on SOC sequestration with spatially explicit data on current management practices and potential areas for the adoption of these practices. The studied practices included: (i) use of organic fertilizer compared to inorganic fertilizer or no fertilizer, (ii) no-tillage (NT) relative to high or intermediate
50
2 Effects of Organic Agriculture on the Soil Carbon Stock
intensity tillage, and (iii) use of cover crops and enhanced crop residue incorporation. The estimated global SOC sequestration potential varied between 0.44 and 0.68 Gt C year−1, assuming maximum complementarity among all practices, and 0.28 to 0.43 Gt C year−1, not assuming maximum complementary. The SOC sequestration potentials were at the lower end of the values summarized in Table 2.2. Among the reasons for the lower potential were limited availability of manure that has not yet been recycled, and the limited area for the adoption of improved practices. To encourage both SOC sequestration and soil fertility, Lessmann et al. (2022) recommended to focus on cropland soils with large yield gaps and/or where SOC values are below levels that may limit crop production. Aside biophysical factors influencing SOC sequestration and stocks after land- use change (LUC), socioeconomic variables such as indices of poverty, population growth, and levels of corruption may also be important to explain some of the variability in SOC stocks (Duarte-Guardia et al. 2020). Thus, societal investments may pay off in larger SOC gains, giving multiple environmental and societal benefits compared to those focusing only on biophysical variables. In the following sections, the effects of OA on changes in soil C storage and soil C sequestration will be discussed separately for SIC and SOC (SOC sequestration rates: Table 2.3). The chapter concludes with a discussion on the net effects of OA on soil C sequestration with regards to a net removal of CO2.
2.2 Soil Inorganic Carbon In many important sub-humid to arid agricultural regions, SIC stocks and their dynamic can rival those of SOC with SIC stocks in Australian agricultural soils, for example, changing by up to 1 Mg C ha−1 year−1 (Sanderman 2012). For soils in France, estimates of the SIC stocks to 30-cm depth amount to about one-third of the SOC stocks (Marchant et al. 2015). In contrast to lithogenic carbonates inherited from calcareous soil parent material, the formation of pedogenic carbonates can be an effective C sequestration mechanism as this process results in a net removal of CO2 from the atmosphere (Lal and Kimble 2000). The effectivity is indicated by the high global mean turnover time of pedogenic inorganic C ranging from 30,000 to 90,000 years (Lal and Kimble 2000; Schlesinger 2006). Importantly, Zamanian and Kuzyakov (2019) indicated that the contribution of SIC to atmospheric CO2 may be more important than previously thought. Sequestration of CO2 occurs when Ca2+ precipitated with pedogenic carbonates is released directly from silicates (Eqs. 2.1 and 2.2; Monger et al. 2015):
CaSiO3 3H 2 O 2CO2 Ca 2 2HCO3 H 4 SiO 4
Ca 2 2HCO3 CaCO3 H 2 O CO2
(2.1) (2.2)
2.2 Soil Inorganic Carbon
51
Table 2.3 Increases in cropland soil organic carbon sequestration rates (Mg C ha−1 yea−1) under organic compared to those under nonorganic management
Soil depth Region World
Soil organic carbon sequestration rate Experimental Mg C scale ha−1 year−1 Plot 0.45
cm 0–20
Dataset categories Total dataset
0–18
Measured soil bulk density Zero net input system (ZNS)b ZNS with reported external carbon and nitrogen inputs ZNS with measured soil bulk density ZNS with measured soil bulk density, and reported external carbon and nitrogen inputs Total dataset Plot and farm
0–20/30 Total dataset
Plot
Mediterranean 0–19
Total dataset
Temperate
Compost Compost with cover crops Manure with cover crops Total dataset Plot Farm Total dataset Plot and farm
0–20
References Gattinger et al. (2012)a
0.30 0.27c 0.16c
0.14
0.07
0.24
0.29e
Plot and farm 0.97
García- Palacios et al. (2018)d Tiefenbacher et al. (2021) Aguilera et al. (2013)f
1.32 0.97 0.62 1.28 0.31c 0.26
Sanders and Heß (2019)
Arable and vegetables Amount of organic fertilizers applied corresponding to the manure amount from 1.0 European livestock unit per hectare or less c Not significantly different from nonorganically managed soils d Cereal, vegetable, orchard/viticulture and grassland e Over at least 20 years f Including arable crops, orchards and horticulture a
b
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2 Effects of Organic Agriculture on the Soil Carbon Stock
An optimum amount of silicate Ca, HCO3− from respiration, water and pH is required to sequester carbonate C (Monger and Martinez-Rios 2001). Agricultural management practices can influence SIC stocks over a time span of months to years (Wang et al. 2016), and there are complex interactions between SIC and SOC (Dong et al. 2017). For example, an experiment in northern China showed that increasing SOC in the cropland can lead to an enhancement in SIC or pedogenic carbonate formation, particularly in the subsoil (Shi et al. 2017). Generally, the addition of above- and belowground biomass is critical to the formation of both SOC and that of pedogenic carbonates in agricultural soils as it increases the CO2 partial pressure indirectly by promoting CO2 production upon decomposition, and directly by increasing Ca2+ levels (Lal 2004). Further, the application of organic amendments; materials rich in cations, lime, and amendments or conditioners that conserve water in the soil column can result in an increase in SIC (Lal and Follett 2009). In contrast, soil cultivation systems (e.g., fertilizer formulation and rate) as well as management practices (e.g., tillage, NT, liming, irrigation frequency and other management practices) can result in CaCO3 dissolution and CO2 efflux (Zamanian et al. 2016). On average, soil pH decreased by 1.33% under NT compared to that under conventional tillage management (Zhao et al. 2022). Nitrogen (N) fertilization in combination with soil acidification can also potentially result in dissolution of CaCO3 and CO2 release over millennia (Zamanian et al. 2018). Soil acidification is driven by: (i) nitrification of NH4+ added as fertilizers, atmospheric N deposition, biological N2 fixation (legumes and bacteria), and mineralization of SOM; (ii) H+ release by roots for cation/anion balance by nutrient uptake; (iii) acid deposition; (iv) removal of base cations (Ca2+, Mg2+, K+, and Na+) by leaching; (v) dissolution of CO2 released from roots and microbial respiration as well as from SOM mineralization, followed by subsequent protonation; and (vi) release of organic acids during SOM mineralization, by roots into the rhizosphere and by microbial metabolic activity (Raza et al. 2020). The rhizosphere is the region of soil that is directly influenced by rhizodeposition, root growth and death, and nutrient and water uptake (Hiltner 1904). Based on meta-analysis and a random forest model, Dang et al. (2022) reported that SIC content increased by 6.55 and 9.25% for cultivation and land use change, respectively. The response of SIC content to cultivation was, however, insignificant when the cultivation period exceeded 20 years which may be explained by the leaching transport of dissolved inorganic C from soils owing to the increase in soil porosity. The grand mean changes in SIC content due to anthropogenic activities were greatly affected by climatic, edaphic, and practical factors. In addition, the relative importance of each factor was ordered as follows: pH (18.2%) > soil type (16.4%) > mean annual precipitation (16.3%) > bulk density (15.2%) > soil depth (13.4%) > mean annual temperature (13.0%) > land use type (7.52%). However, study locations were limited as those were primarily performed in the low and middle latitudes, and northern hemisphere regions. Thus, more experimental studies related to SIC in high latitude and southern hemisphere regions are needed for conducting a more comprehensive and reliable meta-analysis based on a more complete dataset (Dang et al. 2022).
2.2 Soil Inorganic Carbon
53
2.2.1 Effects of Organic Agriculture Practices on Soil Inorganic Carbon Managing soils by OA practices can affect SIC. For example, the formation of pedogenic carbonates can be enhanced through increase in biogenic processes by soil application of animal byproducts, composts, crop residues and manures, particularly, if those are rich in cations (Ca2+, Mg2+) and in materials that conserve water in the soil column, as well as by soil application of lime (Lal and Follett 2009). The SIC content was found to increase after the application of organic fertilizers (Dang et al. 2022). The addition of organic amendments is critical to the formation of pedogenic carbonates in OA soils as this increases the CO2 partial pressure indirectly by promoting CO2 production upon decomposition, and directly by increasing Ca2+ levels. Pedogenic carbonate formation may particularly benefit from manure application to alkaline soils as this has been recommended to sequestrate much more C than in neutral and acidic soils (Li et al. 2021d). Further, OA practices that enhance soil fertility may also lead to the formation of pedogenic carbonates following increased root and shoot biomass production (Lal 2004). Calcium (Ca) supplied as dolomite, gypsum (Ca-sulfate) or lime, and Mg from rock minerals are among permitted OA amendments (Sapinas and Abbott 2020). The dissolution of agricultural lime (CaCO3) and hydrated lime can be either a net source or sink of CO2 (Kunhikrishnan et al. 2016). For example, lime-derived CO2 reacts with microbial respiration derived H2CO3 to produce carbonate material, which is a sink for CO2 in soil. Agricultural lime is a net sink for CO2 in calcareous soils with high pH, but it is a net source of CO2 in acidic soils. Further, adding lime to soils can contribute to C sequestration by increasing CH4 oxidation and reducing GHG emissions (Kunhikrishnan et al. 2016). Liming acidic soils to neutrality may also decrease soil N2O emissions (Hénault et al. 2019). Thus, depending on whether the reaction of lime in soil is with strong acids or with carbonic acid, agricultural lime can either be a source or a sink for CO2 (Hamilton et al. 2007), and may or may not contribute to soil C sequestration and mitigation of GHG emissions. Potential C removal could be attained by spreading crushed carbonate minerals (lime) on non- carbonate soils which may result in 0.843 Gt more C removal per year (Zeng et al. 2022). Liming on non-carbonate landscapes to increase potential C removal needs to focus on the areas with higher C removal efficiency, in order to lower the economic and energy costs (Zeng et al. 2022). Otherwise, liming may also affect SOC stocks but increases, decreases and no changes have been reported (Paradelo et al. 2015). Any OA practice including the application of organic and mineral amendments that results in a higher soil inputs of Ca2+, Mg2+ or Na+ may enhance the formation of pedogenic carbonates (Lal 2004). This process contributes to soil C sequestration when these cations are supplied from outside the OA ecosystem via fertilizers or other soil amendments (Nordt et al. 2000). The soil application of rock dust is sometimes an allowed OA practice for increasing nutrient availability to plants. If these soil amendments contain crushed silicate rock, sequestering of CO2 as bicarbonate
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and carbonate minerals may occur (Kantola et al. 2017). About 0.5–1.0 Mg CO2 may be sequestered per Mg of silicate rock applied by this process of enhanced weathering (Moosdorf et al. 2014). Another OA practice that may affect SIC is irrigation as it may drastically increase biomass addition to the soil (Lal and Kimble 2000). Irrigation may enhance carbonate formation by stimulating plant growth and soil biotic activity, particularly, in cultivated dryland ecosystems (Denef et al. 2008). Further, Ca2+ and Mg2+ applied with the irrigation water may promote the formation of new soil carbonates. However, the effects of irrigation on changes in SIC stocks of principal soils of different ecoregions is not known (Lal and Kimble 2000). Irrigation can also dissolve carbonates and leach them into the groundwater or precipitate CaCO3 depending on the amount and quality of irrigation water and the application method (Denef et al. 2008). For example, irrigation resulted in SIC losses to 7.3-m depth from croplands on decadal timescales (Kim et al. 2020a). Dang et al. (2022) reported a clear shift from an increase to a decrease in SIC content with increasing irrigation amounts potentially ascribed to surface erosion or the vertical leaching effect of irrigation on SIC. Overall, the effect of irrigation on SIC is closely determined by both the amount or frequency of irrigation and the quality of the irrigation water (Dang et al. 2022). Soil acidification resulting from OA practices may release CO2 and acidifying compounds, and promote carbonate dissolution. For example, decomposition of organic amendments in OA soils may release organic acids which may solubilize CaCO3. Specifically, the transformation of C, N, and sulfur (S) in soils under OA releases H+ into the soil solution and, thus, cause soil acidification (Kunhikrishnan et al. 2016). Further, the cultivation of N-fixing crops (i.e., legumes) which is a common OA practice, and crop harvest may acidify soil and dissolve CaCO3 (Fisher et al. 2003). The soil pH may also increase under OA practices due to alkalinity of applied compost and the addition of rock phosphate (von Arb et al. 2020). This increase in soil pH may decrease carbonate dissolution and increase carbonate formation (Dang et al. 2022). From the previous section it is obvious that OA practices can result in higher SIC stocks and in soil C sequestration when they promote pedogenic carbonate formation but in lower SIC stocks when they promote carbonate dissolution. Some studies on the effects of OA on SIC stocks will be presented in the following section. However, baseline data on SIC stocks were not always available before the OA practice was implemented, and SIC stocks are often not reported on ESM basis (Ellert and Bettany 1995). Comparing SIC stocks of different treatments with different bulk densities to a fixed depth implies an unequal soil mass comparison. Thus, studying absolute changes in SIC stocks as well as that in SOC stocks requires the analysis of ESM (von Haden et al. 2020).
2.2 Soil Inorganic Carbon
55
2.2.2 Soil Inorganic Carbon Stocks under Organic Agriculture A previous literature review indicated that there is no consensus on the impact of OA practices on SIC dynamics and stocks based on a limited number of published studies (Lorenz and Lal 2016). Further, most of the studies were performed on farmer’s fields, and it is challenging to quantitatively document material inputs and to ascertain the similarity of baseline soil characteristics among study sites (Jacinthe et al. 2011). Some results from the previous review and from a recently published study are briefly summarized in the following section (Table 2.4). At an irrigated cotton (Gossypium arboreum L.) agroecosystem in semi-arid New Mexico, U.S.A., SIC stocks in 0–30 and 0–100 cm depths after 3 years of OA management were 19 and 25% lower, respectively, than those under conventional practices. After 9 years, SIC stocks were 16 and 18% lower in 0–30 and 0–100 cm depth at the OA fields, respectively. However, it was unclear whether irrigation and manuring, and differences in calcareous soil parent material contributed to the observed differences (Jacinthe et al. 2011). Similarly, at one farm in North Dakota, U.S.A., SIC stocks to 30.5-cm depth were three times lower under OA compared to
Table 2.4 Soil inorganic carbon stocks (Mg C ha−1) under organic compared to nonorganic management
Location New Mexico, U.S.A
Soil depth cm 0–100
Soil inorganic carbon stock Mg C ha−1 83.4
Rotation Three years organic alfalfa (Medicago sativa L.)–irrigated cotton (Gossypium arboreum L.) Six years organic alfalfa-occasional plantings 79.8 of corn (Zea mays L.), chile (Capsicum annuum L.) and lettuce (Lactuca sativa L.) Nine years organic alfalfa–irrigated cotton 91.6 Ten years nonorganic alfalfa–irrigated cotton 111.9 North Nineteen years organic oats (Avena sativa 0–30.5 29.5 Dakota, L.)-sweet clover (Melilotus officinalis L.)-rye (Medina) U.S.A. (Secale cereale L.)-sunflower (Helianthus 2.2 (Windsor) annuus)-buckwheat (Fagopyrum esculentum)alfalfa-spring wheat (Triticum aestivum L.)-flax (Linum usitatissimum L.)-pearl millet (Pennisetum glaucum L.). Nonorganic spring wheat-sunflowera 9.8 (Medina) 3.1 (Windsor) Minnesota, Five years organic soybean (Glycine max 0–15 21.2 U.S.A L.)-wheat-fallow Five years nonorganic soybean-sugar beet 24.2b (Beta vulgaris)-wheata a
Past management history not available Not significantly different from organically managed soils
b
Reference Jacinthe et al. (2011)
Liebig and Doran (1999)
Phillips (2007)
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2 Effects of Organic Agriculture on the Soil Carbon Stock
those under conventional practices after 19 years but no differences were found between conventional and OA rotations at other farms in North Dakota and Nebraska. It was assumed that less frequent tillage and the inclusion of cover crops under OA practices contributed to lower SIC stocks (Liebig and Doran 1999). The absence of differences at the other farms may partially be explained by a high buffering capacity of soil resisting rotation-induced changes in pH resulting from OM decomposition, and, thus, carbonate dissolution by soil acidification (Sheoran et al. 2019). Similarly, OA practices at a cropland cultivated to soybean (Glycine max L.) in Minnesota, U.S.A., for 5 years did not result in differences in SIC stocks in 0–15 cm depth (Phillips 2007). In contrast, carbonate contents in 0–10, 10–20 and 20–30 cm depths under some OA rotations in a semi-arid region in Spain were lower after 18 years while no differences compared to conventional rotations were found under other OA practices. Again, interpretation of the differences was difficult under non-controlled on-farm conditions (Romanyà and Rovira 2007). Only a few studies on CaCO3, carbonate or SIC for paired conventional-OA comparisons have been published since the previous review (Lorenz and Lal 2016). For example, Sheoran et al. (2019) studied soils from 25 vegetables and horticultural organic and adjacent conventional farms in 11 districts of Hryana, India. The mean CaCO3 content in 0–15 cm depth averaged over all comparisons was lower under OA than that under conventional practices. This was explained by solubilization of CaCO3 in OA soils by more organic acids released due to higher amounts of organic amendments applied compared to the conventional practices. However, at ten of the sites, CaCO3 percentages to 15-cm depth were higher for OA than those at the conventional farms. Among the limitations of this study were that baseline data on CaCO3 contents before the establishment of the rotations were not available, and the age of the farms was also unknown (Sheoran et al. 2019). In conclusion, OA can potentially affect SIC stock and dynamics through various mechanisms but published data from well-designed and replicated long-term experiments including baseline data are scanty. However, effects of soil and land-use management practices on the SIC stock relative to atmospheric CO2, and on soil C sequestration must receive more attention as SIC appears to be more dynamic than previously thought.
2.3 Soil Organic Carbon The SOC stock consists of small molecules from plant, microbial and faunal residues at various stages of decomposition, collectively called SOM (Kleber and Johnson 2010; Basile-Doelsch et al. 2020), and often know as humus - Earth’s most important natural resource (Paul 2016). Otherwise, SOM is also understood as consisting of a complex mixture partly of recognizable, largely unaltered plant components plus a group of highly modified materials that bear no morphological resemblance to the original components (Hayes and Swift 2020). The modified components are though to result from transformation and decomposition processes collectively known as ‘humification’. Humic substances, a family of closely related
57
2.3 Soil Organic Carbon
compounds, are considered to be a major product of this process (Hayes and Swift 2020). However, the ‘humic substances paradigm’ has been questioned in recent years (Kleber and Lindsley 2022). Specifically, humic substances are the result of an operational extraction procedure and cannot be observed in situ with alternative methods (Lehmann et al. 2008). The purported properties of these extracts, such as macromolecularity, polymeric nature, high aromaticity, and their origin from a secondary synthesis pathway, have been refuted over the past 30 years (Kleber and Johnson 2010). Further, there is no thermodynamic rationale for the making of resistant’ compounds including humic substances by microorganisms (Burdon 2001). The dynamic of the SOC stock is regulated by: (i) climatic variables such as precipitation and temperature, (ii) soil conditions including various physico- chemical properties, and (iii) biotic properties consisting mainly of the quantity and quality of C inputs into soil (Luo et al. 2017). The turnover of SOM is determined by heterotrophic soil organisms including bacteria, fungi, archaea, protists, and animals as those govern ecological processes that are responsible for the uptake and release of C and nutrients (Crowther et al. 2019). Heterotrophic soil microorganisms are primarily limited by organic C and secondarily by nutrients (Soong et al. 2020). However, the fundamental biology regulating SOM decomposition has not been discovered and the associated biochemical pathways are not well understood (Jansson and Hofmockel 2020). Soil Carbon Input Land-based plants’ photosynthesis is the major source of SOC in agroecosystems (Fig. 2.1; Lorenz and Lal 2018). Some soil C input from heterotrophic CO2 CH4, CO, BVOC fluxes
CO2 flux vertical
GPP
NEE
Organic amendments
CO2 advection, drainage
Harvest
Herbivory
Ra
CH4
DIC, DOC leaching
Rh
CO2, CH4, Soot
DIC, DOC, PC lateral transfer
Fig. 2.1 Carbon fluxes in agroecosystems associated with the net ecosystem carbon balance or the net of all C imports to and exports from the agroecosystem. (GPP gross primary production, NEE net CO2 exchange, Ra autotrophic respiration, Rh heterotrophic respiration, CH4 methane, CO carbon monoxide, BVOC biogenic volatile organic compounds, CO2 carbon dioxide, DIC dissolved inorganic carbon, DOC dissolved organic carbon, PC particulate carbon) Modified from Lorenz and Lal (2010) and Chapin et al. (2006)
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fixation may also occur in agroecosystems (Braun et al. 2021). Autotrophic CO2 fixation by photosynthesis at the leaf level is limited by CO2 concentration, availability of N and P, light, temperature, air humidity and water potential; and by phenology, leaf area density and canopy structure at the stand level (Farquhar 1989). The spatial variation of the amount of CO2 removed from the atmosphere every year to fuel photosynthesis or gross primary production (GPP) is associated with precipitation in 69% of the area of temperate grasslands and shrublands, in 55% of the area of tropical savannahs and grasslands, and in 51% of the area of croplands, respectively (Beer et al. 2010). Thus, in many agroecosystems, water availability determined by precipitation and irrigation has a large effect on GPP. The contemporary land GPP flux has been estimated at 115–190 Pg C year−1 (Cai and Prentice 2020). The total amount of OM produced annually in an agroecosystem (NPP) is lower than GPP as respiratory C losses (photorespiration, dark respiration) occur during the synthesis of organic compounds in plants and the maintenance of living plant cells (Lorenz and Lal 2018). The contemporary land NPP flux has been estimated at 44–57 Pg C year−1 (Ciais et al. 2020). About 61% of C assimilated by crops is allocated to shoots, 20% to roots, 7% to soils while 12% is respired back into the atmosphere by autotrophic respiration of crop plants (Mathew et al. 2020). The remaining bulk of agroecosystem NPP after accounting for respiratory losses is allocated to the production of biomass in foliage, shoots and roots (Ciais et al. 2010). NPP sets the upper limit of SOC sequestration by plant activity. Estimates for global cropland, tropical savanna and grassland, and temperate grassland NPP are 10.8, 7.5 and 6.1 Mg C ha−1 year−1 with totals of 5.3, 14.0 and 5.3 Pg C year−1, respectively (Chapin and Eviner 2014; Wolf et al. 2015). About 10 and 120 Pg C are stored globally in cropland, and grassland and grazing land biomass, respectively (Erb et al. 2018). The aim of agricultural production is to increase the amount of harvestable product which may be achieved by maximizing total NPP. The C flux associated with the consumption of harvested crops has been estimated at 1.5 Pg C year−1 (Ciais et al. 2020). For a given crop production, C returns to soils increase with NPP (Basile- Doelsch et al. 2020). Thus, increasing NPP per unit area is probably the most effective option to enhance SOC sequestration (Kätterer et al. 2012). Maximizing agroecosystem NPP can be realized by large-scale irrigation, increase in the availability of soluble nutrient sources (fertilizers), agricultural mechanization, improved varieties and application of agrochemicals for pest control (Whalen and Sampedro 2009). Globally, SOC is temporally and spatially decoupled from NPP by lateral C fluxes from biomass harvest, grazing and C export to rivers, as well as by emissions of reduced biogenic C compounds (Ciais et al. 2020). Specifically, not all of NPP remains in the agroecosystem as some plant biomass is removed by harvest, herbivory and fire. For example, on average only about 7% of the C assimilated by crops is found in the soil after harvest, with wheat (Triticum aestivum L.) having the highest proportion (23%), followed by rice (20%), and maize (Zea mays L.) and ryegrass (Lolium perenne L.) each with 19% (Mathew et al. 2020). More losses of agroecosystem NPP occur during weed and seed production, by the emission of
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biogenic volatile organic compounds (BVOCs), by exudation from roots (i.e., the loss of soluble organic compounds that diffuse or are secreted by roots into the soil), and by C transfer to root symbionts (Ciais et al. 2010). Importantly, only a small fraction of GPP initially fixed during plant photosynthesis enters the soil as shoot litter and via restitution of unharvested aboveground plants but predominantly as dead roots and rhizodeposition (Basile-Doelsch et al. 2020). The proportion of recently assimilated C allocated belowground in 0–30 cm depth as rhizodeposition accounts for 3% for crops and 5% for grasses, whereas 10% of C in crops and 16% in grasses reside in the roots (Pausch and Kuzyakov 2018). Compared to cropland, belowground C inputs account for the major proportion of soil C inputs in grassland and pastures as a greater proportion of aboveground plant biomass is exported or grazed (Basile-Doelsch et al. 2020). Further, crop breeding aimed historically at increasing allocation to harvestable products, and to growth under fertilization and irrigation conditions. Thus, the fraction of total NPP allocated belowground is 32% in croplands and 64% in grasslands with the amount of cropland belowground NPP per unit area being about a quarter lower compared to that for grasslands (Gherardi and Sala 2020). How much NPP is globally transferred to soil is, however, under discussion (Ciais et al. 2020). No fraction of soil C inputs with OM in plants and animals can withstand decomposition to CO2 and water under aerobic conditions in the long term (Jenkinson 1981). Specifically, a large portion (80–90%) of fresh C inputs to soil is subject to rapid mineralization (Angers et al. 2022). However, any soil C input is a potential source for SOC formation (Lorenz and Lal 2018). The SOC formation efficiency or the amount of input-derived C retrieved in the soil vs. the amount of C lost during the decomposition of such input typically ranges between 3% and 33% (Cotrufo and Lavalle 2022). The C retention efficiency is 16% when manure is applied to the soil and 10% when plant residues are applied (Alvarez 2021). However, the pathways and mechanisms connecting plant C inputs with SOC accumulation and stabilization (i.e., mineral-associated soil C formation) are not completely understood (Pierson et al. 2021). For example, increased soil C inputs do not necessarily lead to increased SOC formation as changes in soil microbial populations and the presence of live roots can diminish the effects of increased C inputs (Pierson et al. 2021; Lajtha et al. 2018). Plant-derived molecules are estimated to have a turnover time of years to decades in soils based on incubation and isotope tracing experiments, i.e., much shorter than anticipated for the ‘stable’ SOC pools (Feng 2022). However, the short duration of experiments is unable to depict dynamic changes in the slowly cycling SOC pool. Further, analytical methods used to isolate plant-derived molecules (biomarkers) from soils are also subject to bias due to low (or unknown) extract efficiency for OM bound to minerals. Thus, the turnover time of plant- derived compounds may be underestimated but it is important to examine the soil environment in studies of plant C turnover (Feng 2022). Hence, the long-term stability of increasing amounts of C transferred to soils is an active field of research (Cotrufo and Lavallee 2022; Mathew et al. 2020). For geographic Europe, the total rate of organic C accumulation in an agroecosystem integrated over time and space or the net biome production (NBP) is only
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3% of GPP (Schulze et al. 2010). The NBP is a measure of the “apparent” change in SOC (Baker and Griffis 2005). Importantly, the SOC stock represents the major accumulation of C and the most important long-term C storage pool in agroecosystems as the harvested proportion of NPP from shoots is removed periodically and some biomass may also be lost to herbivory and fire (Lorenz and Lal 2018; Basile- Doelsch et al. 2020). In most agricultural soils, SOC stocks have declined through time because C inputs are relatively low (e.g., due to biomass harvest, small root systems of annual plants, and fallow periods) and C outputs are relatively high (e.g., due to soil disturbance reducing microbial access constraints; Cotrufo and Lavallee 2022). Soil Organic Carbon Persistence, Preservation, Protection and Stabilization Research on SOM stabilization aims at to improve model projections of SOC dynamics such that the C cycle is represented as accurately as possible in global land models (Kleber and Lindsley 2022). It can also inform management decisions aimed at increasing SOC stock. Any soil C input in agroecosystems can potentially contribute to an increase in the SOC stock when it is protected, stabilized and not completely mineralized to CO2 (Kleber and Johnson 2010). However, many unknowns remain as the science of SOM stabilization is continuously evolving (Kleber and Lindsley 2022). Also, there is neither a precise definition nor an unequivocal means of quantification for the terms ‘stable carbon’; ‘soil carbon stabilization potential’; ‘stable carbon forms’; or ‘stabilized carbon’. A slow-cycling carbon compound does not do so because it has the enigmatic property of being ‘stable’, it simply persists because it is not being decomposed. Future research should address questions such as: (i) what happens with that supposedly stable OM once it has been ‘formed’ and, (ii) what are the constraints that prevent the decomposer community from processing soil carbon at their full metabolic potential (Kleber and Lindsley 2022). Plant rhizodeposition, in particular, may be a key factor for SOM formation in ‘stable’ fractions (Villarino et al. 2021). The transfer of atmospheric C to the soil for maize, ryegrass, rice and wheat has been estimated at 1.00 Mg C ha−1 year−1, 0.95 Mg C ha−1 year−1, 0.70 Mg C ha−1 year−1, and 0.80 Mg C ha−1 year−1, respectively (Mathew et al. 2020). The SOC production ‘yield’ from initial substrates depends on the yield of C used by microorganisms, and the association of SOC with minerals which stabilize microbial compounds (Basile-Doelsch et al. 2020). At the mineral–organic interface, a broad set of interactions occur, with minerals adsorbing organic compounds to their surfaces and/or acting as catalysts for organic reactions (Kleber et al. 2021). Soil minerals can serve as redox partners for OM through direct electron transfer or by generating reactive oxygen species, which then oxidize OM. The compartmentalization of soil by minerals creates unique microsites that host diverse microbial communities. However, no C cycle model has succeeded in predicting C turnover dynamics based on a generalized, broadly applicable set of mineral phase parameters (Kleber et al. 2021). Unclear is also the importance of the composition of soil C inputs for the formation of mineral-associated SOC (Castellano et al. 2015).
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Some of the CO2 removal from the atmosphere with soil C inputs must be essentially permanent for centuries to millennia as up to 40% of CO2 emitted until 2100 will remain in the atmosphere for longer than 1000 years (Ciais et al. 2013). Processes which slow down mineralization are major centennial-scale stabilization mechanisms (Sanderman et al. 2010). Two important groups of processes contributing to long-term stabilization of OM are: (i) processes which lead to physical protection, rendering OM spatially inaccessible to decomposers or their water-soluble degradative enzymes, and (ii) organo-mineral complexes and organo-metal interactions, i.e., interactions of OM with minerals, metal ions, and other organic substances, and particularly poorly crystallized minerals (von Lützow et al. 2006; Basile-Doelsch et al. 2020). Thus, SOC stocks can be linearly correlated with soil’s specific surface area (Kirschbaum et al. 2020). Both mycorrhizal presence and root suberin may also promote SOC stabilization (Poirier et al. 2018). Physical protection may slow down decomposition for decades to centuries whereas organo-mineral complexes or organo-metal interactions may be responsible for most of the highly ‘stable’ (i.e., protected and stabilized for centuries to millennia) non-charred SOM (Kögel-Knabner et al. 2008). Mineral-organic associations may occur throughout grassland soil profiles, and be equally important in top- and subsoil horizons (Sanaullah et al. 2011). Based on various protection and stabilization mechanisms, mean SOC turnover times of 36.2, 34.4 and 17.7 years for shrubland, grassland and cropland have been estimated by Yan et al. (2017), respectively. Different biotic and abiotic properties control SOC storage at different spatial scales ranging from micro-scales (particles to pedons) to the global scale (Wiesmeier et al. 2019). Important factors include clay mineralogy, specific surface area, metal (aluminum [Al], iron [Fe], manganese [Mn]) oxides, Ca and Mg cations, microorganisms, soil fauna, aggregation, texture, soil type, natural vegetation, land use and management, topography, parent material and climate (Wiesmeier et al. 2019). The contribution of the microbial necromass and microbial by-products to SOC may be much higher than previously thought (Anthony et al. 2020). Microbial soil C inputs are relatively enriched with polysaccharides other than celluloses, lipids, proteins, amino-saccharides, nucleic acids and a diverse range of metabolites compared to plant-derived C inputs (Basile-Doelsch et al. 2020). Globally, the relationship between soil biodiversity and SOC levels is not well characterized (Guerra et al. 2020). Guerra et al. (2021) proposed the SOC stock as indicator in the context with other indicators, and linked to the essential biodiversity variables litter decomposition, soil respiration, soil biomass, enzymatic activity, and nutrient cycling. The net benefits of agricultural management for improving SOC sequestration depends on the soil microbial community (Bhattacharyya et al. 2022). For example, microbial detritus C may contribute 59 and 64% of SOC in arable agricultural and grassland systems (Coonan et al. 2020). Liang et al. (2019) estimated that microbial necromass can make up more than 50% of SOC. Fungal necromass C (>70% of total microbial necromass), in particular, may consistently contribute more to SOC than bacterial necromass C (26–28%) in temperate agricultural and grassland ecosystems. Similarly, the ratio of fungal to bacterial biomass is positively associated with SOC storage (Malik et al. 2016). Wang et al. (2021) performed a global
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meta-analysis of contents of fungal and bacterial necromass estimated based on glucosamine and muramic acid contents. Glucosamine is the main component of chitin in fungal cell walls and is also found in bacterial peptidoglycan bonded to muramic acid, whereas muramic acid uniquely originates from bacterial peptidoglycan. Microbial necromass C contributed 51%, and 47% to the SOC in cropland and grassland, respectively, in 0–20 cm soil depth. The contribution of microbial necromass to SOC increased with soil depth in grasslands (from 47% to 54%), while it decreased in croplands (from 51% to 24%). Fungal necromass C (>65% of total necromass) contributed more to SOC than bacterial necromass C (32–36%; Wang et al. 2021). Thus, microbial detritus C and necromass may play an important role as building block for ‘stable’ SOC, and microbial compounds may be the predominant components of SOC in the long term (Liang et al. 2019; Anthony et al. 2020; Basile-Doelsch et al. 2020; Coonan et al. 2020; Soong et al. 2020). Based on the global average soil microbial MRT of 38 days combined with the global Rh, He and Xu (2021) estimated that the microbial contribution to SOC stabilization can be largely >60%. Recently, Deng and Liang (2022) derived a more applicable estimate of the microbial necromass contribution to SOC by considering the stoichiometric differences of microbes and the full range of the microbial necromass proportion in soil N. They estimated that the proportion of microbial necromass C in SOC may range between 24% and 60%. About 6–16% of total SOC may stem from bacterial necromass, and 18–44% of total SOC may stem from fungal necromass. Accordingly, the implementation of SOC sequestration through increasing microbial necromass strategy would require science-based guidelines that may develop through a framework based on a good understanding of soil C/N and microbial biomass C/N ratios. Thus, land management for increasing microbial necromass contribution to SOC should be designed based on the soil N availability and should focus on microbial species associated with high biomass C/N ratio to boost SOC accrual (Deng and Liang 2022). However, knowledge about soil microbial necromass must be improved concerning process understanding, driving and regulatory mechanisms, and the associated microbiomes to clarify the role of microbial necromass for SOC formation and stabilization (Liang et al. 2020). For example, Angst et al. (2021) reported a relatively balanced contribution of plant and microbial biomolecules to stabilized SOM in aggregates and mineral-associated organic matter (MAOM) which is inconsistent with suggestions that microbial compounds contribute strongly to the ‘stable’ SOM. In some soils, however, substantial or even dominant contributions of plant-derived OM to MAOM have been found (Yu et al. 2022). Thus, both plantand microbial-derived C should be considered as source for MAOM. Further, the C storage in the MAOM fraction is not different between arbuscular mycorrhiza (AM) and ectomycorrhizal (ECM) fungi ecosystems (Wu et al. 2022a, b). Although ECM ecosystems have a higher SOC storage and lower N demand per unit SOC compared to AM ecosystems, most C is distributed in relative labile particulate organic matter (POM). However, the data coverage in deep soil layers, especially for ecosystems with deep root systems, is limited (Wu et al. 2022a, b).
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Lehmann et al. (2020) suggested that SOC persists in soil when many different molecules with individually low concentrations are distributed throughout a heterogeneous landscape of pores interacting with different minerals under variable environmental conditions. Soil management should, therefore, focus on ongoing care to manipulate the intricate balance between C inputs and losses, rather than rely on locking away C in soil for the long term (Lehmann et al. 2020). Hall et al. (2020) characterized C functional groups and molecules of North American surface mineral soils of forests and grasslands or open canopy shrublands based on nuclear magnetic resonance spectroscopy and a molecular mixing model. With regard to SOC persistence among ecosystems, microbial necromass may be more important than lignin where reactive Al phases are scarce, and vice versa. Further, where physico-chemical protection mechanisms mediated by Fe are scarce and high-quality root C inputs are small, char assumes a more important role for SOC persistence. The differences in temperature and pH among ecosystems may be ultimately linked to lipid abundance. Overall, controversies regarding the genesis of SOC and its potential responses to global change may be partially reconciled by considering diverse ecosystem properties that drive complementary persistence mechanisms (Hall et al. 2020). Both mineral protection and resource limitations may combine to explain profile- scale SOC persistence (Lacroix et al. 2022). For example, even in soils with high short-range order (SRO) mineral content, oxygen and nutrient limitations contribute to SOM preservation. Thus, management practices that alter soil structure, such as tillage, will increase oxygen supply and remove metabolic restrictions imposed by anaerobic conditions. Further, anthropogenic N additions to soils, through fertilizers or deposition, can alleviate nutrient limitations. Overall, in soils with lower SRO mineral content, resource limitations may play an even more important role in SOM preservation (Lacroix et al. 2022). Similarly, Heckman et al. (2021) showed for forest and grassland soils of the conterminous U.S. that reactive Fe- and Al-oxyhydroxide phases may not be present in high enough concentrations in most soils to offer any significant protective capacity. Further, in grasslands, SOC persistence was not associated with exchangeable Ca concentrations, but instead was explained by depth and inorganic C concentrations. This implies stabilization of SOC also through association with carbonate precipitation (Heckman et al. 2021). Oxalate and citrate–dithionite extractable Al and Fe are used as proxies for mineral phases that may protect SOC from microbial decomposition (Hall and Thompson 2022). The question is, however, whether those proxies are driving or responding to SOC content (or both). To sum up, knowledge about SOC persistence, preservation, protection and stabilization is continuously evolving (Cotrufo and Lavallee 2022). Soil Organic Carbon in Agroecosystems Globally, SOC stocks to 200-cm depth in grasslands are as double as high as those in croplands (Fig. 2.2). Grasslands in temperate regions have also higher SOC stocks than croplands (Lorenz and Lal 2018). In natural grassland ecosystems under semi-arid conditions and in temperate environments, plant diversity and functional
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2 Effects of Organic Agriculture on the Soil Carbon Stock Soil organic carbon stock Pg C
Croplands
Grasslands
Savannas
Croplands/natural vegetation mosaics
Shrublands
Soil depth 0-30 cm:
73
132
143
59
148
0-100 cm:
162
308
163
128
183
0-200cm:
246
496
519
196
610
Fig. 2.2 Soil organic carbon stocks (Pg C) in 0–30 cm, 0–100 cm and 0–200 cm depths for International Geosphere-Biosphere Programme (IGBP) land cover categories affected by agricultural activities in the year 2010. (Modified from Sanderman et al. 2017)
composition may affect SOC storage at different spatial scales (Soussana et al. 2004). Further, at the (sub)regional scale, SOC storage among different grassland types can differ significantly (Liu et al. 2016). Generally, plant diversity in grassland ecosystems is positively correlated with SOC accumulation at the local scale, mainly due to higher root biomass production induced by specific plant functional traits (e.g., positive interactions between N-fixing legumes and grasses; enhanced N mineralization in species-rich grasslands without legumes) (Cong et al. 2014). Converting grassland to cropland is associated with a loss of SOC which has been attributed to erosion, lower C inputs in croplands, a reduced stabilization of SOM due to reduced aggregation, and a subsequent mineralization promoted by increased soil temperature and aeration (Six et al. 1998). In contrast, land use extensification, particularly the conversion of cropland to grasslands, may lead to SOC increases (Wiesmeier et al. 2019). The soil parent material may control soil mineralogy, texture and fertility, which affect NPP and the stabilization of SOM in agroecosystems. Higher cropland SOC stocks are recorded for clayey soils (Mathew et al. 2020). The SOC stocks in a semi- arid region in Turkey were the greatest under grazing on alluvial and lacustrine soils, whereas cropland in this region had greater SOC stocks on limestone terraces (Mayes et al. 2014). Topographical features are indicative of the soil moisture- induced accumulation of SOC, and the topographic wetness index (TWI) is a promising indicator for SOC storage (Wiesmeier et al. 2019). For example, TWI was an important factor for the spatial variability of SOC in agricultural soils in a regional SOC inventory in Germany due to its indicative power for SOC accumulation in groundwater-affected soils (Wiesmeier et al. 2013). Agricultural land management influences SOC storage with crop rotations generally associated with higher amounts of SOC than monoculture systems (Jarecki and Lal 2003). Increased SOC storage under crop rotations may be driven by enhanced root C input, soil microbial diversity, and soil aggregate stability (Tiemann et al. 2015). Crops with greater root biomass or a greater surface area of roots that
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actively release C into soil may contribute to SOC accumulation (Jansson et al. 2021). For example, crops with higher transfer of atmospheric C into soils and those with distinctive and deep root systems such as those of perennial crops may promote SOC storage as retention of root derived C in soil can be 2.3 times higher than that for aboveground residues (Kätterer et al. 2011; Mathew et al. 2020; Peixoto et al. 2020b). Inclusion of perennial legumes in a rotation may be critical for enhancing SOC stabilization, in particular in N-limited deep subsoils (Peixoto et al. 2022). Incorporating perennial grassland in crop rotations provides access to improve the soil C input from crops, and may enhance SOC stocks (Hu and Chabbi 2021). Thus, agroecosystems with perennial crops/forages and cover crops may have distinctly high SOC stocks (Paustian et al. 1997; Jarecki and Lal 2003; Poeplau and Don 2015; Ledo et al. 2020). Including cover crops into crop rotations increases SOC stocks on average by 15.5% or 0.56 Mg C ha−1 year−1 (Jian et al. 2020). Cover crop mixtures result in greater increases in SOC stocks compared to mono-species cover crops while grass species cover crops may not affect SOC stocks (Jian et al. 2020). Legume-based cover crops, in particular, may enhance SOC sequestration (De Notaris et al. 2020). However, cover-crop induced SOC increases are generally observed only in 0–30 cm depth but not at deeper soil depths (Jian et al. 2020). Crop rotational diversity, the use of organic amendments or perennial cropping systems may be indicative of SOC accumulation (Wiesmeier et al. 2019). The SOC stocks can be higher under NT management in some soil types and climatic conditions even with redistribution of SOC, and contribute to reducing net GHG emissions (Ogle et al. 2019). As a management practice, residual cereal straw, corn (Zea mays L.) stover, or similar unused plant residues could also be collected and preferentially deposited on clayey soils as those have a higher specific surface area than sandy soils (Kirschbaum et al. 2020). Less is known in terms of grassland management effects on SOC storage due to limited data availability and large spatial variability of grassland SOC stocks (Soussana et al., 2004). Conant et al. (2017) reported the effects of improved grazing management on SOC with an average sequestration rate of 0.28 Mg C ha−1 year−1. However, this rate did not apply uniformly to all grazing lands, and improved grazing management may not always lead to an increase in SOC stocks. Among the mechanisms discussed contributing to higher SOC stocks in grazing lands is trampling by grazing animals which may be important for SOC formation and stabilization (Wei et al. 2021). However, trampling may have also indirect effects, i.e., injure to plants, decrease in plant production, or compaction of soil which may decrease SOC stocks (Wei et al. 2021). In general, rotational grazing can lead to increased productivity and potentially to increased SOC stocks. However, there are few studies available (Conant et al. 2017). Evidence on managing livestock grazing to increase SOC stocks is based on studies suffering substantial, overlooked methodological problems (Reinhart et al. 2021). Studies often include unrealistic and overly simplistic livestock grazing treatments (e.g., grazed vs. not grazed), suboptimal experimental designs (e.g., lack pretreatment data, low number of treatment replications) and problematic SOC stock metrics. Thus, to better quantify benefits
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of C ranching, Reinhart et al. (2021) advise using current best practices and expanding C ranching research with more realistic treatments over either broader spatio- temporal scales and/or climate change treatments (e.g., drought, warming, elevated CO2). Kirschbaum et al. (2020) indicated that providing supplemental feed to cattle (Bos taurus Linneaus, 1758) preferentially on clayey rather than sandy soils in New Zealand has the potential to increase SOC stocks because of the higher specific surface area of clayey soils. Cattle could also be moved to clayey soils for rest periods and restrict their time on sandy soils to the time needed for feeding so that more dung would be deposited on clayey soils (Kirschbaum et al. 2020). Combining different grassland management practices may be suitable to enhance SOC storage. For example, avoiding fires and overgrazing, using a grazing rotation plan and a mixture of C3 and C4 species may ensure a continuous SOC storage in tropical pastures established after deforestation (Stahl et al. 2017). Other common grassland management practices affecting SOC include the repeated addition of lime and nutrient fertilizers to soils. For example, addition of lime, N fertilizer or cattle slurry resulted in increased SOC storage (Fornara et al. 2011, 2013, 2016). Grassland management effects on SOC are not restricted to the topsoil but can also be detected in the subsoil (Ward et al. 2016). Lehmann et al. (2020) proposed regenerative SOC practices consistent with the promotion of functional diversity to increase SOC persistence. Practices include mixtures of inputs, and a diversity of plant species to stimulate a diverse microbial community and rhizodeposits. Further, reduced soil mixing (by tillage), should also be explored to increase SOC persistence and sequestration. It is important to better understand how to sequester SOC by increasing persistence based on functional complexity in comparison to merely increasing organic C inputs (Lehmann et al. 2020). Prescott et al. (2021) suggested that regenerative agriculture (RA) should encourage high rates of photosynthesis but limit the aboveground sink for carbohydrates so that a proportion of the photosynthate is transported belowground. This plant surplus C may potentially generate SOM. However, some improved RA management practices, such as increased fertilizer use, manuring, and applications of biochar, are constrained by biogeochemical stoichiometry and the availability of organic inputs (Schlesinger 2022). Other RA management practices, such as fertilizer applications, irrigation, and applications of ground silicate minerals, entail ancillary and off-site emissions of CO2 that reduce the net sequestration of C in soils (Schlesinger 2022). Thus, the potential for climate change mitigation through RA is an active field of research. The Importance of Soil Organisms Soil organisms affect SOC storage in agroecosystems as all soil organisms mineralize C into inorganic forms (primarily CO2; Crowther et al. 2019). Heterotrophic respiration by soil bacteria and fungi, for example, amounts to 36–70% of total soil respiration (Bond-Lamberty et al. 2004; Tian et al. 2015). Globally, mean values for heterotrophic respiration in croplands and grasslands are 297 and 399 g C m−2 year−1, respectively (Tang et al. 2020). Respiration by soil microorganisms is
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positively correlated with GPP highlighting the importance of the vegetation control. Further, climate is the most important environmental control of heterotrophic respiration by microorganisms (Tang et al. 2020). Soil microorganisms can also affect agroecosystem SOC by promoting plant productivity (soil C input) and N mineralization (Kaminsky et al. 2019). The soil microbial biomass carbon (SMB-C) pool is positively related to the SOM content in arable and grassland ecosystems except for those with >2.5% SOC or peat/organic soils (Anderson and Domsch 1980; Wardle 1992). Further, soil and land-use management in arable and grassland soils also affect the SMB-C to SOC ratios (Anderson and Domsch 1980; Wardle 1992). If management results in shifts from high efficiency towards low efficiency soil microbes, this can decrease SOC stocks due to differences in carbon use efficiency (CUE) between soil microbes (Saifuddin et al. 2019). Microbial CUE can be defined as the microbial biomass produced per substrate consumed (Dijkstra et al. 2022). Exudation and microbial turnover rather than high maintenance energy demand in soil microbial communities may explain the variation in CUE. Thus, SOC cycling models should incorporate a greater spectrum of microbial traits, including growth and survival strategies, and cell death through predation and grazing (Dijkstra et al. 2022). Overall, CUE is a key determinant of the balance between soil C inputs and outputs, and internal SOC cycling (Kallenbach et al. 2019). The microbial CUE may play a strong role in modulating changes in SOC sequestration (Wu et al. 2022a, b). Fertilization that contains inorganic fertilizer (either pure inorganic fertilizer or combined with organic fertilizer) may increase both microbial CUE and SOC contents (Wu et al. 2022a, b). The soil microbial detrital or necromass contributes strongly to SOC storage (Coonan et al. 2020). For example, the contribution of microbial necromass may account for more than 50% of total SOC stock for temperate agricultural (55.6%) and grassland soils (61.8%) in the surface layer (250 μm), in particular, are sensitive to land management and mechanical disruptive forces of cultivation because they are formed from plant inputs and much less stable than microaggregates (soil particles sunn hemp (Crotalaria juncea L.) (5.77 Mg ha−1) > millet (Pennisetum glaucum L.) (4.95 Mg ha−1) > rye (Secale cereale L.) (4.93 Mg ha−1) > two-species mix (4.18 Mg ha−1). However, cover crop biomass can be highly dependent on climate, species, cropping system, and management (Ruis et al. 2019). For example, in a Mediterranean-type climate, bean (Vicia faba L.) aboveground cover crop biomass was 6.16–10.35 Mg ha−1 while aboveground vetch (Vicia spp.) + oats (Avena sativa L.) cover crop biomass was 2.85–8.32 Mg ha−1 differing between years (Herencia et al. 2021). In addition to soil biological and chemical properties, cover crops may also improve most soil physical properties, but again the magnitude of improvement is highly site- and management specific (Blanco-Canqui and Ruis 2020). Properly managed cover crops are important to both soil protection and improvement, and for control of weeds, diseases and pests (von Fragstein und Niemsdorff 2019). Cover crops with thick and deep roots can be used for bio-tillage as they may effectively improve soil structure, and water and air conductivity by forming bio-pores which may promote root growth (Zhang and Peng 2021). Cover cropping may also increase soil microbial abundance, activity, and diversity compared to those of bare fallow (Kim et al. 2020b). Specifically, cover crops enhance soil microbial community biomass and affect community structure, and the responses vary with soil and climatic conditions (Muhammad et al. 2021). Overall, cover crops contribute to soil quality by improving soil biological, chemical and physical properties (Adetunji et al. 2020). Beneficial effects are less pronounced for continental climate, chemical cover crop termination, and conservation tillage. Cover crop species selection, termination stage and termination methods have been identified as the most critical factors to enhance multiple benefits of cover crops (Adetunji et al. 2020). Otherwise, cover crops may also have detrimental effects on the cash crop either by competing for water and nutrients, and by building up diseases or retarding seed germination. Among the reasons for the generally low adoption of cover crops may be: (i) the direct and indirect costs of seeds, cultivation and management, (ii) potential for consumption by livestock in winter, particularly in smallholder settings, and (iii) possible economic losses (Adetunji et al. 2020). Cover crops are included in OA rotations to ‘catch’ the available N or as ‘green manure crops’ to improve nutrition of the subsequent main crop (Niggli 2007). For example, legume cover crops such as clover, pea (Pisum L.) and vetch (Vicia L.) convert atmospheric N2 to organic N (Tully and McAskill 2020). Another aim for
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including cover crops in OA rotations is to manage weeds. For example, grass cover crops such as rye (Secale L.) produce large quantities of biomass and are effective at suppressing weeds. Thus, multi-species cover crops (i.e., including legume and grass cover crops) can be used in OA rotations to manage weeds and meet N needs (Tully and McAskill 2020). Further, the intentional management of cover crop mixtures may enable OA farmers to manage for increased mycorrhizal colonization of cash crops or decreased belowground pest pressures (Cloutier et al. 2020). This increased mycorrhizal colonization may contribute to AM fungi diversity and SOC sequestration (Agnihotri et al. 2022). Cover crops may increase SOC stocks by adding above- and belowground biomass, and by reducing erosion (Blanco-Canqui et al. 2015; Poeplau and Don 2015). The magnitude of SOC build-up by cover crops is site-specific, and varies with cover crop biomass amount, duration of life materials before termination, initial SOC stock, soil type, cover crop type, tillage management, and climate (Blanco- Canqui et al. 2015). For example, Blanco-Canqui (2022) recommended to modify current CC management practices to boost SOC sequestration in the U.S. In addition, the potential of cover crops to increase SOC stocks may also be limited due to their less lignified shoot biomass and low C/N ratio (von Fragstein und Niemsdorff 2019). Under conventional management, Poeplau and Don (2015) observed that cover crop treatments had higher SOC stocks than the reference croplands without cover crops. The maximum increase was 16.7 Mg SOC ha−1, and the average annual SOC sequestration rate was 0.32 Mg C ha−1 year−1 to a soil depth of 0–22 cm globally. Porwollik et al. (2022) simulated median SOC sequestration rates to 30-cm depth of 0.52 and 0.72 Mg C ha−1 year−1 with and without tillage, respectively, during the first decade of cover crop adoption in global croplands. In contrast, the SOC accumulation rate was only 0.12 Mg C ha−1 year−1 to 30-cm depth for studies from the U.S. (Blanco-Canqui 2022). Beneficial effects of cover crops on SOC stocks can be observed for decades as the predicted new steady state equilibrium in SOC stocks was reached only after 155 years of cover crop cultivation (Poeplau and Don 2015). Also, for a credible assessment of the climate forcing of cover crop cultivation, data on N2O emissions and surface albedo changes in addition to those in SOC stocks are needed (Poeplau and Don 2015). For example, Abdalla et al. (2019) reported increased SOC sequestration under cover crop cultivation but no effects on direct N2O emissions. On average, cover crops could mitigate the net GHG balance by 2.06 Mg CO2e ha−1 year−1, however, with a large standard deviation of 2.10 Mg CO2e ha−1 year−1 (Abdalla et al. 2019). Short-term effects of cover crops on crop yield were highest in an OA system with reduced tillage (+24%), intermediate in an OA system with tillage (+13%) and in a conventional system with no tillage (+8%), and lowest in a conventional system with tillage (+2%) in Switzerland (Wittwer et al. 2017). However, assessing the effects of cover crops under OA practices on SOC stocks is hampered by the limited quantity of published data, and the short duration of studies of less than two years (Tully and McAskill 2020). Based on a relatively small number of observations, Crystal-Ornelas et al. (2021) found that SOC concentrations were 10% higher at
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0–15 cm depth but not different at 0–50 cm depth at cover-cropped compared to not cover-cropped OA systems. For example, Welch et al. (2016) did not find differences in SOC stocks up to 40-cm depth over three years between fields without and with cover crops at OA grain farms. This trend was attributed to the resilient nature of the studied soils and extreme weather pattern observations. Clark et al. (2017) reported no changes in SOC stocks under Cover Crop-Based Reduced Tillage (CCBRT) management which was explained by the short time frame of the experiment. However, CCBRT may generally provide a management practice to minimize soil erosion risks and build SOM stocks (Silva and Delate 2017). Similarly, cover crop based organic rotational no-till (CCORNT) may have the potential to overcome the tillage trade-off between weed control and soil health (Osterholz et al. 2020). Cavigelli et al. (2013) reviewed the literature and indicated that cover crops, and particularly legume cover crops in OA systems, can result in greater SOC stocks. This assessment was, however, based on a limited number of studies. Similarly, results from long-term OA comparison trials in the U.S. indicated that including cover crops/forage legumes has the potential to promote SOC sequestration (Delate et al. 2015). When cover crops were combined with compost application, SOC increased by 26% and SOC sequestration rate increased by 0.97 Mg C ha−1 year−1 under OA compared to that under conventional management practices in Mediterranean croplands (Aguilera et al. 2013). When cover crops were combined with manure, the increase was 35.8% and the sequestration rate was 0.62 Mg C ha−1 year−1. However, Gattinger et al. (2012) did not include cover crop effects on SOC stock under OA management in a global meta-analysis. In summary, more research is needed with regards to the long-term effects of cover crops in OA systems on soil health, and, in particular, on SOC stocks (Tully and McAskill 2020). Crop Rotation Crop rotation provides many benefits in controlling environmental stresses and crop performances including buffering effects of climate stresses such as increased temperature and rainfall variability (Barbieri et al. 2017). For example, diversification of maize rotations increases agricultural resilience to adverse growing conditions in North America (Bowles et al. 2020). The first OA crop rotations were implemented in the 1920s, and OA systems now heavily rely on them (Nair and Delate 2016; Freyer 2019). Well-designed OA crop rotations contain crops with different rooting depths and volumes to make best use of the available soil profile (Watson and Stockdale 2019). Energy crops may also be included in OA crop rotations (Rempelos et al. 2021). Freyer (2019) provides an overview on the roles of crop rotations in OA on management of soil fertility, water, nutrients, pests, diseases, weeds, biodiversity, and on socio-economic and other non-agricultural functions. Intercropping, i.e., the mixed cultivation of crop species on the same field, leads to higher and more stable grain yield than the mean sole crops at OA cereal-grain legume intercrop systems in Europe (Bedoussac et al. 2015). OA crop rotations maintain N supply, influence SOC, and moderate weed, pest and disease populations. Crop rotations are longer under OA than those under
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conventional practices, and result in higher diversity and evener crop species distribution (Barbieri et al. 2017). These changes are driven by a higher abundance of temporary fodders, catch and cover-crops. The increased complexity of OA crop rotations is likely to enhance ES provisioning to agroecosystems (Barbieri et al. 2017). For example, OA crop rotations may include grass-clover or forage legume leys that allocate more C below ground, and avoid or reduce the use of bare fallow (Ghabbour et al. 2017). Further, integrating perennial crops in OA rotations can build soil health similar to conventional rotations (Wachter et al. 2019; Nunes et al. 2020). Specifically, alfalfa-based systems often increase biological soil health over grain-based systems (Tully and McAskill 2020). In addition to N fertilization, temporary fodders provide SOC sequestration as an additional service (Barbieri et al. 2017). Chen et al. (2020a) reported that increasing plant diversity had no effects on SOC stocks in croplands and grasslands compared to monocultures based on a global meta-analysis of controlled-diversity experiments. However, this study had some limitations as, for example, more biodiversity-manipulation experiments in croplands incorporating a wide range of species richness levels are needed. Further, shorter experimental durations likely resulted in the lack of significant mixture effects in grassland studies. Study duration needs to be sufficiently long (≥5 years) to properly estimate plant diversity effects on SOC content and stock (Chen et al. 2020a). Also, the effects of OA rotations were not analyzed separately. Liu et al. (2022) concluded that crop rotation is a critical practice to increase SOC content in global croplands, whereas the variations in response are governed by specific climatic, edaphic, and agronomic factors. Rather than the rotational diversity pers se, the inclusion of a cover crop may drive increases in SOC stocks (McDaniel et al. 2014). Forage legumes in OA crop rotations, in particular, may have a positive effect on top soil SOC stocks (Gattinger et al. 2012). It is challenging to identify RMPs for forage legumes in stockless OA farms (Freyer 2019). Compared to conventional farming, the higher humus balance under OA is mainly the result of the higher humus replenishment due to crop rotations with increased cultivation of legumes and catch crops (Kasper et al. 2015). In contrast, Garnier et al. (2022) found no evidence that OA would increase SOC concentration in 0–30 cm depth owing to a higher occurrence of legumes in crop rotations. The soil health outcomes of OA including increases in SOC stocks may eventually reach a saturation point with two or three crops in the OA rotation, and further increasing rotational diversity may not necessarily be associated with soil health benefits (Tully and McAskill 2020). Integration of Livestock The principle role of livestock in any farming system is the ability to convert biomass from leys or pastures to economically viable products, and to increase flow rates of nutrients (Entz and Martens 2009). Conventional and OA livestock production systems differ in some sustainability indicators (van Wagenberg et al. 2017). For example, OA systems have lower impact on biodiversity, lower eutrophication and acidification potential per unit land, equal or lower likelihood of antibiotic
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resistance in bacteria, and higher beneficial fatty acid levels in cow milk. Otherwise, conventional livestock production systems have higher production per animal per time unit, higher reproduction numbers, lower feed conversion ratio, lower land use, generally lower acidification and eutrophication potential per unit product, equal or better udder health for cows, and equal or lower microbiological contamination. However, productivity is consistently lower in OA than that in conventional livestock production systems (van Wagenberg et al. 2017). Jackson et al. (2019) reported some evidence that OA management can stimulate soil biota but no evidence for soil stock or soil transformation rate differences between OA and nonOA pastures. The separation of crops and livestock is widespread in conventional agriculture, and also increasingly observed in OA systems (Entz and Martens 2009). However, as mineral fertilizers are prohibited, integrated crop-livestock systems are indispensable to OA. Integration ranges from simple to complex. For example, beef–forage–grain and dairy–forage–grain are common OA crop-livestock systems in North America. Nevertheless, adoption of integrated OA systems has been slow globally, and much of its potential is yet to be realized (Entz and Martens 2009). Specifically, integrating animal grazing into OA field crop systems has potential benefits but is generally not practiced (Carr et al. 2020). Differences in top soil SOC concentrations and stocks between conventional and OA systems are mainly influenced by elements of mixed farming, i.e., livestock plus crop production (Gattinger et al. 2012). Thus, recycling of OM and forage legumes in OA integrated crop-livestock systems may contribute to SOC sequestration. Integration of Multiple Conservation Practices Combining multiple practices simultaneously within OA cropping systems is increasingly common to achieve economic and environmental viability such as: (i) suppressing weeds, pests, and disease pressure; (ii) meeting crop nutrient demands; and (iii) optimizing overall crop productivity (Tully and McAskill 2020). This stacking or layering of practices may improve soil health including maintaining or increasing SOC stocks. For example, combining reduced tillage practices with different combinations of organic amendments may cause increases in SOC stocks. Similar outcomes were achieved when reduced tillage or NT were supplemented with green manure, animal manures or compost. Overall, the effect of stacking practices may have an additive or synergistic effect on soil health and SOC stocks (Tully and McAskill 2020). Further, increasing the heterogeneity of organic resources in OA systems by, for example, incorporation of cover crops, residues, dynamic organic fertilizer applications, and rotational planting has potentially large implications to build SOC (Anthony et al. 2020). Sprunger et al. (2021) reported that reducing tillage intensity and incorporating perennials are main management drivers for improved soil biochemical health in OA corn production systems in the eastern Corn Belt of the US. Soil Carbon Inputs Increasing soil C input may be the best measure to increase SOC stocks (Xu et al. 2020). However, the soil C input at OA-conventional comparisons is often not
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reported although increases in SOC in short, medium and long-term experiments are positively related to the C input (Aguilera et al. 2013; Keel et al. 2019). For example, only six studies included in the meta-analysis of Gattinger et al. (2012) provided data on total soil C inputs derived from organic fertilizers and plant residues. The mean total annual C input was 4.23 Mg C ha−1 year−1 for non-OA and 4.86 Mg C ha−1 year−1 for OA farming systems. A long-term experiment in Sweden by Kirchmann et al. (2007) indicated that the inclusion of cover crops, incorporation of crop residues and weeds, and use of solid manure led to higher C input under OA compared to those under conventional practices at (3.9 vs. 2.7 Mg C ha−1 year−1). Liang et al. (2022) reported that total belowground C inputs to 1-m depth (0.57–1.00 Mg C ha−1) were similar across long-term management (OA and conventional, with or without a history of cover crops) at an experimental site in Denmark. Root exploitation, and thus plant C inputs into the subsoil, was probably enhanced in relatively N poor cropping systems. Some studies published after Gattinger et al. (2012) have reported input of soil C in OA systems. For example, under Mediterranean climate, mean additional C inputs for OA rotations compared with conventional systems were 4.8 and 3.2 Mg C ha−1 year−1 in irrigated and rainfed systems, respectively (Aguilera et al. 2013). Further, C inputs were 6.1, 2.5 and 3.1 Mg C ha−1 year−1 higher in horticulture, cereals and woody crops, respectively, under OA compared to those under conventional practices. In contrast, Bell et al. (2012) estimated higher soil C inputs of 40.5–40.6 Mg C ha−1 at conventional systems compared to 27.0–27.2 Mg C ha−1 at OA systems over 18 years at a long-term experiment in Canada. Similarly, C inputs were 25% lower under an OA rotation compared to those under conventional NT practices in Wisconsin, USA due to lower OA crop residue yields (Cavigelli et al. 2013). In contrast, inputs of biomass-C to the soil were higher in another OA rotation in Wisconsin than those under the NT system, largely due to manure and/or compost additions. At two OA systems without N fertilization in Sweden, lower yields resulted in less C input through crop residues compared to conventional systems (Kirchmann et al. 2013). Cumulative C inputs over 8 years of intensive OA vegetable production at a site in California were estimated at 25.2–30.4 Mg C ha−1 for vegetable shoot residues, roots and root exudates (White et al. 2020). In comparison, C inputs with cover crop shoots, roots and root exudates were estimated at 8.3–34.7 Mg C ha−1. For an OA vegetable production system in Central Italy, estimated total C inputs (residue C + root C + shoot C + root exudate C + weed C) ranged between 1.03 Mg C ha−1 for lettuce (Lactuca sativa L.) and 7.17 Mg C ha−1 for hairy vetch (Vicia villosa R.; Farina et al. 2018). Measured C inputs from aboveground barley (Hordeum vulgare L.) used as cover crop, melon (Cucumis melo L.) and weeds in this study were 3.38 to 7.53 Mg C ha−1. At one long-term experiment in Switzerland, soil C inputs were similar between conventional and OA treatments (Keel et al. 2019). In contrast, at another Swiss long-term experiment, soil C inputs under OA were lower than those under conventional practices (Keel et al. 2017). Differences in plant-derived C (yields, harvest residues) and in organic C amendments (fertilizers, cover crops) contributed to the
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differences in soil C inputs (Keel et al. 2019). However, allometric equations adapted to country-specific agricultural practices, and to local crop types and varieties are needed to increase the credibility of soil C input estimations based on plant residues (Keel et al. 2017). The soil C inputs of the main crops should be assessed under on-farm in-field conditions (Taghizadeh-Toosi and Christensen 2021). To sum up, a very important limitation in studies on SOC dynamics is the lack of reliable C input data in the form of organic amendments and residues (Alvarez 2021). This may be the most significant variable to understand the functioning of conventional and OA systems, and would allow to address the C retention efficiency of both production systems (Alvarez 2021). Soil Organic Carbon Destabilizing Management Practices OA management practices may not only affect soil C inputs and SOC stabilization but also SOC destabilization processes. For example, tillage is a common OA practice that destabilizes SOC by aggregate disruption and altering the soil microbial community (Bailey et al. 2019). Increased earthworm numbers under OA despite tillage disturbance (Crittenden et al. 2014; Blakemore 2018), may also contribute to increased release of SOC by reducing the physical occlusion of OM (Bailey et al. 2019). Total microbial abundance and activity, and of bacterial taxa involved in C cycling in soils under OA practices may also be increased (Bill et al. 2021; Lori et al. 2017). On one hand, this may result in higher SOC stocks due to increase in microbial necromass (Liang et al. 2019). On the other hand, SOC destabilization may also be enhanced, as is indicated by more priming of SOM decomposition by soil microorganisms in more resource deprived OA soils compared to those under conventional management (Arcand et al. 2017). Results from a long-term (14 years) experiment indicated that OA with legume green manures improved mainly the bacterial pathway of the soil food web, and endogeic and anecic earthworms (Henneron et al. 2015). However, CA showed a higher overall improvement than OA. Specifically, CA increased the number of many organisms such as bacteria, fungi, anecic earthworms, and phytophagous and rhizophagous arthropods. Overall, long-term, NT, and cover crops were better for soil biota than periodic legume green manures, pesticides, and mineral fertilizers (Henneron et al. 2015). In conclusion, OA practices may result in lower primary soil C inputs from plants, particularly, as yields are often lower. This may contribute to lower steady state equilibrium SOC stocks compared to those for the same eco-region under conventional practices. However, practices such as returning plant residues and manures from livestock back to the soil, and/or integrating perennial plants, mainly grass– clover mixtures in the OA rotation can also result in higher soil C inputs compared to that of conventional systems. This trend may result in higher SOC stocks and a net decrease of atmospheric CO2 in OA systems but whether adding extraneous OM to a soil counts as SOC sequestration is a debatable issue (Olson et al. 2014). Further, tillage is a widespread OA practice and may result in SOC destabilization and loss. However, whether other OA practices also enhance SOC destabilization processes requires additional research (Bailey et al. 2019).
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2.3.2 Soil Organic Carbon Stocks Under Organic Agriculture Observations of changes in SOC stocks under OA compared to those under conventional management are limited as those are often based on data from a small number of well-replicated field experiments with a geographical bias towards studies in temperate regions (Sanders and Heß 2019; Gattinger et al. 2012). On-farm evaluations in all major growing regions are needed as those would provide direct evidence of the effect of OA management on SOC sequestration based on the complexity of crop, livestock, and forage systems deployed by farmers and ranchers. Based on a global meta-analysis and considering only the highest quality data (i.e., zero net input systems, measured soil bulk densities, reported external C and N inputs), Gattinger et al. (2012) reported that the topsoil (median depth 0–15 cm) SOC stock and sequestration rate was on average 1.98 Mg C ha−1 and 0.07 Mg C ha−1 year−1 higher under OA than that under nonorganic management (Table 2.3). When all data were included, the increase was 3.50 Mg C ha−1 with a sequestration rate of 0.45 Mg C ha−1 year−1 compared with nonorganic management. However, the drivers for this increase, and global significance and transferability of the results are uncertain (Table 2.5). For example, SOC stocks at the beginning of some experiments or baseline data were not available, and the coverage of climatic regions and Table 2.5 Relative effects of organic versus conventional practices on soil organic carbon stocks Practice Growing plants
Increasing plant species diversity Integration of livestock in cropping systems Adding organic amendments
Soil tillage
Relative effect of organic compared to conventional practices Lower plant-derived soil C input due to lower yields Similar plant-derived soil C input due to similar yields in tropical agroforests Lower plant-derived soil C input due to growing non- organic agriculture plant species and varieties Higher annual plant-derived soil C input due to higher proportion of perennials in the rotation Higher annual plant-derived soil C input due to higher proportion of cover crops in the rotation Higher weed-derived C input due to higher weed incidence Higher plant, in particular, forage legume-derived soil C input Higher soil C inputs
Higher exogenous and plant-derived soil C inputs Lower plant-derived soil C input due to lower nutrient contents of amendments derived from organic agriculture Higher soil organic carbon losses by tillage compared to no-till Similar soil organic carbon losses under reduced tillage
Soil organic carbon stock Lower Similar? Lower? Higher at deeper depths? Lower difference? Lower difference? Higher at shallow depths? Higher at shallow depths Higher at shallow depths Lower difference? Lower at tillage depth Similar
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continents was unbalanced (Gattinger et al. 2012). Sanders and Heß (2019) performed another meta-analysis using only data for temperate regions from Gattinger et al. (2012) and those published for the period 2012–2017. The median SOC stocks and sequestration rates to the average 0–20 cm depth were 3.42 Mg C ha−1 (10.8%) and 0.26 Mg C ha−1 year−1 higher under OA soils of temperate regions than those under conventional practices. This analysis included pairwise comparisons of field experiments with at least three replications, and those in which OA management was implemented for at least 3 years before soil sampling (Sanders and Heß 2019). Tiefenbacher et al. (2021) synthesized the most recent scientific literature regarding the impact of agricultural management practices on cropland SOC stocks. On average, OA practices sequestered 0.29 Mg C ha−1 year−1 more C in 0–20/30 cm depth than conventional farming practices. The increased SOC stocks of OA soils may have a positive effect on crop yield and on soil health (Lal 2020). Leifeld et al. (2013) indicated that the comparison between the systems in Gattinger et al. (2012) was biased, i.e., conventional systems with low livestock stocking densities and C return were compared to OA systems with high stocking densities and C inputs. Specifically, the average external C input to OA was about four times that of conventional systems. Leifeld et al. (2013) concluded that OA may have none or minimal climate-mitigation benefits through SOC sequestration. However, the total mitigation potential of OA has not been quantified (Reise et al. 2022). Importantly, OA may only increase SOC stocks when off-site C from other agroecosystems is added (Alvarez 2021). Without C transfer between agroecosystems, SOC stocks did not differ between OA and conventional systems based on this meta-analysis of 66 experiments. The off-site effects of OA on the SOC stocks of organic soils and the soils that provide manure-compost should be addressed in the future together for a full assessment of the C sequestration potential of OA. The determination of the soil bulk density is also essential. Initial SOC stocks at the onset of the experiments must be determined (Alvarez 2021). Another important limitation of many studies is also the shallow sampling depth (Gattinger et al. 2012; Sanders and Heß 2019). Similarly, Ghabbour et al. (2017) presented percent SOM data based on 0–30 cm depth for both conventional and OA farms across the United States. However, measuring SOC to 2-m depth revealed that an OA system in California had substantially greater capacity to sequester C than what would have been thought based on sampling of only the surface soil (top 30-cm depth; Tautges et al. 2019). At this experiment, a 19 Mg ha−1 increase in SOC stocks down to 100-cm under OA compared to a conventional system was reported over 25 years (Rath et al. 2022). Most of this SOC gain was concentrated in the 0–15 cm (5 Mg ha−1) and 15–60 cm depths (10 Mg ha−1). The combination of growing cover crops and compost amendment created conditions conducive to C transport and accumulation in the OA subsoils. This was, in part, likely due to increased hydraulic conductivity facilitated by cover crop roots leading to higher rates of transport of soluble C and nutrients from the surface to subsoil. These results demonstrate the potential for subsoil SOC storage in tilled OA systems, and highlight a potential pathway for increasing C transport, storage, and sequestration in subsoil layers (Rath et al. 2022). Thus, ignoring the subsoil SOC dynamics may fail to
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recognize potential opportunities for SOC sequestration, and may lead to false conclusions about the impact of conventional vs. OA management practices on SOC sequestration (Tautges et al. 2019). Gattinger et al. (2012) reported that the estimates of C sequestration in the meta- analyzed experiments followed SOC sink saturation dynamics. The SOC stocks showed increasing differences between farming systems for longer trial durations. However, median experimental duration was only 10 years. It is unclear whether this time period is sufficient to credibly assess differences in equilibrium steady- state SOC stocks between soils under different management practices. In some cases, for example, it may take more than 100 years until steady-state conditions are reached as was indicated by temporal changes in SOC stocks under cover cropping (Poeplau and Don 2015). Similarly, OA sites in Germany studied by Drexler et al. (2022) may have not reached a new equilibrium of SOC levels at the time of sampling after the conversion from conventional practices. This is in contrast to the expected higher SOC contents associated with OA (Gattinger et al. 2012). Other reasons for the lower SOC contents could be that OA in Germany is often practiced on sites with less favorable site conditions or is associated with lower yields which could, however, be compensated for by a higher root C allocation with OA (Drexler et al. 2022). Under Mediterranean conditions, SOC sequestration in topsoil (average soil depth 19.4 cm) of croplands was 0.97 Mg C ha−1 year−1 higher under OA than that under conventional management practices (Aguilera et al. 2013). However, credibility of the results of this meta-analysis were affected by often missing soil bulk density data, SOC stocks calculated not on ESM basis, short/medium-term experiment length (average age 8.7 years), shallow sampling depth, and scanty data on total soil C inputs. The type of experimental approach was also critical. For example, the increase in SOC concentration and sequestration rate in OA plots was much more pronounced in plots of controlled experiments (51.6% and 1.28 Mg C ha−1 year−1, respectively) than in real farms (11.4% and 0.31 Mg C ha−1 year−1, respectively; Aguilera et al. 2013). Lorenz and Lal (2016) collated and reviewed SOC stock data on conventionalOA comparisons published after Gattinger et al. (2012). Based on an 18-year study and soil sampling to 120 cm depth in Manitoba, Canada, Bell et al. (2012) reported that without manure and compost additions, OA managed cropping systems had lower SOC stocks (165 and 178 Mg C ha−1 for alfalfa/crop and annual crop, respectively) than conventionally managed systems (190 and 209 Mg C ha−1, respectively). The lower SOC stocks were associated with reduced estimated C input from crop residue and roots. However, it is unclear to what extent management contributed to the differences as the studied Vertisol may be characterized by self-plowing (soil inversion by crack formation), which may affect the detection of management effects on SOC stocks. In addition, baseline data from the start of the experiment were not available (Bell et al. 2012). Studies under Mediterranean climate also indicated the necessity to study entire soil profiles to assess the long-term effects of conversions from conventional to OA practices on SOC stocks (Lorenz and Lal 2016). Reduced tillage intensity under OA management often resulted in
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accumulation of plant residues and higher SOC stocks under Mediterranean climate compared to conventional management. Tillage intensity had a greater impact on some soil health indicators than OA vs. conventional management at long-term trials in North Carolina, USA (van Es and Karlen 2019). Similarly, results from long-term experiments indicated that composition and management of crop rotations including tillage, and the availability and utilization of manure were more important for SOC stocks than whether conventional or OA practices were used (Lorenz and Lal 2016). This was shown for several Long-Term Agricultural Research sites (LTARs) and grain-crop-based OA comparison experiments in the U.S. (Cavigelli et al. 2013; Delate et al. 2015). However, there has been comparatively little research conducted on OA compared with conventional systems. Further, some of the comparative studies at the long-term experiments did not measure baseline SOC stocks before plot establishment, and sampling depths were sometimes not sufficient to capture long-term effects of plant root- derived C inputs on SOC stocks (Cavigelli et al. 2013). Franzluebbers et al. (2020) studied SOC stocks after 19 years of farming systems management in sandy Coastal Plain soils in North Carolina, U.S. Among similar 6-year rotations of 3 year hay production with 3 year of grain production [crimson clover (Trifolium incarnatum L.) + hairy vetch cover crop preceding corn–rye cover crop preceding soybean–rye cover crop preceding sunflower (Helianthus annuus L.)], SOC stocks in 0–12 and 0–20 cm depths did not differ significantly between OA (16.4 and 23.8 Mg C ha−1) and conventional systems (20.1 and 26.9 Mg C ha−1). Also, SOC stocks in 0–12 and 0–20 cm depths were not different between conventional tilled 3-year OA rotation of legume cover crop (crimson clover + hairy vetch) preceding corn–rye cover crop preceding soybean–rye cover crop preceding sunflower with conventional tillage, and the same OA rotational system but with reduced tillage (Franzluebbers et al. 2020). Rui et al. (2022) studied soil C accrual on Mollisols at the Wisconsin Integrated Cropping Systems Trial, a 29 years old field experiment in the North Central United States. The SOC stocks in 0–30 cm depth were not different between conventional (continuous monoculture maize with annual tillage, NT maize-soybean rotation, maize-alfalfa-alfalfa-alfalfa rotation) and OA (maize-soybean-wheat rotation with legume cover crop after wheat, maize-oats/alfalfa/alfalfa rotation) systems. Further, SOC decomposition was faster under OA while MAOM-C did also not differ between OA and conventional practices. Overall, persistent SOC was not enhanced by OA (Rui et al. 2022). Hu et al. (2018a) compared a range of arable organic and conventional crop systems at three sites in Denmark through long-term experiments initiated in 1997. The experimental OA treatments included use of whole-year green manure crops, catch crops and animal manure. There were no consistent differences between conventional and OA systems in SOC stocks to 25-cm depth despite higher soil C inputs under OA (Hu et al. 2018a). Specifically, estimated root biomass for cereals, catch crops and weeds was higher for OA than that under conventional practices (Hu et al. 2018b). Based on a study at one of the long-term experiments in Denmark, De Notaris et al. (2021) suggested that SOC was at steady state independent of
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conventional or OA management. All treatments at this site were based on crop rotations and had limited soil disturbance. Büchi et al. (2022) conducted an on-farm study of 60 winter wheat fields in Switzerland under OA or conventional practices. The SOC stocks under tillage management did not differ in 0–5 cm, 5–20 cm and 20–50 cm depths for OA compared to those at the conventional systems. This was explained by the absence of differences in external OM inputs between the cropping systems, along with reduced biomass production and yield in the OA fields. The OA fields showed a higher mean aggregate size and proportion of macroaggregates in 0–5 cm compared to conventional fields, with a greater amount of C in the large macroaggregates. However, large within-system variability was observed, which tended to override differences between systems (Büchi et al. 2022). Lee et al. (2020) simulated changes in SOC stocks in 0–20 cm depth for the period 1991–2013 with the scenario that all cropland in Switzerland is converted to OA practices. The practices included manure and compost addition with reduced tillage and winter cover cropping in combination. The data showed that addition of OM with high decomposability (e.g., litter or animal manure and slurry) and of partially decomposed OM (e.g., compost) increases SOC stocks by 104 and 259 kg C ha−1 year−1, respectively, relative to conventional practices. The greatest increase of 433 kg SOC ha−1 year−1 was estimated when addition of partially decomposed OM was combined with reduced tillage and cover cropping. However, the OA practices to increase SOC stocks are considered as a non-permanent mitigation option as soils have the limited biophysical capacity to store new C until a new SOC equilibrium is reached even when soil inputs and nutrients are sustainably maintained (Lee et al. 2020). Further, it was unclear whether the amount of OM produced in Switzerland is sufficient to meet the demand for organic amendments when all cropland is managed by OA practices. Maintaining and/or increasing SOC stocks in frequently tilled, intensive OA vegetable production systems is a major challenge. In contrast, reduced tillage or NT practices may help preserve SOC stocks (Kaufman et al. 2020). Compost, cover crops and manure are often used in OA vegetable production to add OM to improve soils. For example, the amount of manure may have been the key component for storing SOC in OA vegetable farms in Japan (Matsuura et al. 2018). Compared to conventional systems, SOC sequestration predicted over the next 20 years was the highest in a NT OA system with grass mulching. Based on a study of vegetable production in California, White et al. (2020) showed that compost additions increased SOC stocks by 9.4 Mg C ha−1 in 0–30 cm depth over study years 2–8 at an intensive OA system from a baseline of 19 Mg C ha−1 for the first year (White et al. 2020). Further, increased frequency of cover cropping led to an additional increase of 3.4 Mg SOC ha−1. Other benefits of increased use of annually planted nonlegume cover crops at this site were improved efficient N use and cropping system yield (White et al. 2022). Farina et al. (2018) reported also benefits of both compost and green manure additions for SOC stocks in an OA vegetable cropping system in Central Italy. For example, after two years of 10 Mg C ha−1 compost application, the SOC stock in 0–30 cm depth was higher by 4.9 Mg C ha−1
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compared to the initial stock of 36.8 Mg C ha−1. In comparison, cover crops incorporated into soil as green manure increased SOC stocks by 3.3 Mg C ha−1 (Farina et al. 2018). However, much longer study periods may be needed to assess the effects of cover cropping on SOC stocks (Poeplau and Don 2015). Lazicki and Geisseler (2021) compared soil health indicators and yields in two crops – corn and processing tomato (Solanum lycopersicum L.) – for a conventional rotation using synthetic fertilizer, pesticides, and winter fallow with a certified OA rotation with yearly applications of composted poultry manure and a winter cover crop in a Mediterranean climate. After 25 years of consistent management, SOC stocks in the 10-to-25-cm depth were 18.9 Mg C ha−1 in the conventional plots and significantly higher at 23.2 Mg C ha−1 in the OA plots (Lazicki and Geisseler 2021). The higher SOC stock was likely the result of 67% higher aboveground C inputs at the OA compared to that at the conventional plots (Tautges et al. 2019). Intensive OA vegetable production in greenhouses is also affecting SOC stocks. For example, adding high amounts of organic fertilizers (132.6 Mg ha−1 year−1) to an OA vegetable system in a greenhouse in China increased SOC stocks by 4.0 and 0.2 Mg C ha−1 year−1 in 0–20 and 20–40 cm depths, respectively, after eleven years (Zhao et al. 2020). In comparison, SOC stocks increased by 0.5 and 0.1 Mg C ha−1 year−1 in 0–20 and 20–40 cm depth, respectively, under conventional management. The organic fertilizer was composted cow dung and chicken dung (Zhao et al. 2020). Similarly, soil fertility management in OA greenhouses in Europe may increase SOM contents (Möller 2018). Borges et al. (2019) studied SOC stocks at commercial sugarcane (Saccharum officinarum) farms in Goianesia, Goiás, Brazil. Ten years after introducing OA practices, SOC stocks in 0–60 cm depth were higher for the OA system (100.2 Mg C ha−1) compared to those under conventional practices without (51.6 Mg C ha−1) and with straw burning before harvest (68.4 Mg C ha−1). The OA SOC stocks were higher in all studied depths (0–10, 10–20, 20–30, 30–40, 40–50, and 50–60 cm) compared to those of both conventional systems. This trend may be attributed to higher OM inputs for the OA system (31 Mg OM ha−1 5 year−1) while the conventional systems received no external C inputs. Further, sugarcane-derived C inputs may have also been higher under OA management as the yield of OA sugarcane was 90.6 Mg ha−1 compared with 74.7 and 73.5 Mg ha−1 under conventional practices without and with straw burning, respectively (Borges et al. 2019). Agroforestry Agroforestry practices are sometimes combined with OA practices for their beneficial effects on the environment (Wilson and Lovell 2016). The inclusion of trees or other woody perennials within farming systems captures the interactive benefits of perennials and seasonals, and/or animals for sustainable agricultural production (Lorenz and Lal 2018). Among the benefits is the greater ability of agroforestry systems to capture and utilize growth resources (i.e., light, nutrients, water) compared to single-species systems. Numerous and diverse agroforestry systems are practiced in the tropics because of favorable climatic conditions and various socio- economic factors (Nair et al. 2008).
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Similar to nonorganic agroforestry systems (Lorenz and Lal 2018), data on SOC stocks and sequestration of agroforests managed by OA practices are scanty. For example, Noponen et al. (2013) studied two long-term coffee (Coffea arabica L.) agroforestry experiments in Costa Rica and Nicaragua. While SOC stocks in 0–40 cm depth did not differ between conventional and OA systems, SOC stocks in 0–10 cm depth at the site in Turrialba, Costa Rica, were higher under OA than those under conventional management. This increase was explained by the organic fertilizer inputs under OA practices (Noponen et al. 2013). At the Turrialba site, Chatterjee et al. (2020) assessed SOC stocks up to 100-cm depth after 17 years. High OM inputs including pruned litter, chicken manure and coffee pulp resulted in higher SOC sequestration potential (1.3 Mg C ha−1 year−1) in 0–40 cm depth, and higher SOC stocks in 0–10 cm depth at one OA system compared to the other OA and the conventional systems. However, no differences in SOC stocks were observed between conventional and OA systems for deeper soil depths. High amounts of aboveground biomass alone were not good indicators for increased SOC stocks due to confounding effects of the nature of shade tree, soil type, quality of litter and prunings added to the soil, and previous land-use, amongst others (Chatterjee et al. 2020). Otherwise, incorporation of pruned materials or green manure and high biomass may have contributed to higher SOC stocks in 0–30 cm depth at OA cocoa agroforestry systems in Ghana compared to those under conventional management (59.7 vs. 49.7 Mg C ha−1; Asigbaase et al. 2021). In conclusion, global meta-analyses indicate that topsoil SOC stocks can be higher under OA compared to those under conventional practices. However, studies on farming systems effects on soil profile SOC stocks are scanty. Further, it is unclear whether OA practices build and/or maintain SOC more effectively compared to conventional practices.
2.4 Net Effect of Organic Agriculture on Soil Carbon Sequestration Soil C sequestration assumes a net removal of atmospheric CO2 by increases in soil C stocks, i.e., a positive net change in the sum of SIC and SOC stocks in a landscape. In contrast, later transfer of inorganic C and/or organic C with amendments originating from outside of the landscape and their addition to a specific agricultural soil area may locally increase soil C stocks but not increase the associated CO2 removal form the atmosphere by the landscape (Chenu et al. 2019). Thus, internal and external C inputs to an agricultural area must be distinguished. A credible assessment is, however, difficult as review articles and meta-analyses evaluating soil C sequestration as defined here at OA vs. conventional landscapes have not been published. Internal inorganic C inputs to soil of a landscape managed by OA practices can result from dust deposition. Specifically, transfer and deposition of dust particles
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containing limestone, calcitic pedogenic or silicatic pedogenic carbonates within an agricultural landscape can result in increases in the SIC stock (Monger et al. 2015). However, Monger and Gallegos (2000) reported that only 3 g CaCO3 ha−1 year−1 was deposited within a landscape in southern New Mexico, USA. In contrast, external lime addition rates for adjusting soil pH can be as much as 6 Mg CaCO3 ha−1 year−1 in conventional systems (Paradelo et al. 2015). Thus, external inputs of inorganic C may far exceed the inputs of internal inorganic C in a landscape managed by OA practices. Inputs of internal inorganic C may, therefore, not contribute to SIC sequestration although small increases in SIC stocks may occur by deposition of carbonates with dust redistributed internally. As described previously, inputs of internal organic C to soil of an OA landscape occur directly as a result of plant photosynthesis including that of main crops, catch crops, cover crops and weeds. On the basis of data from a grass-clover ley in a Swiss long-term cropping experiment, Keel et al. (2017) estimated the maximum input of soil C for some main crops at about 5 Mg C ha−1 year−1. This is compared with about 10 Mg C ha−1 year−1 of indirect inputs of internal organic C. The sources of indirect inputs included those when livestock were fed with fodder produced in the OA landscape or the plant biomass for producing compost was harvested in the OA landscape, and manure, slurry or compost were subsequently applied as organic fertilizer to different soil areas within the OA landscape. Gattinger et al. (2012) reported that on average, OA managed soils receive 1.2 Mg C ha−1 year−1 with organic fertilizers. Therefore, a correction must be made when the organic fertilizer C is produced and imported from outside into the OA landscape by subtracting it from the inputs of internal organic C for an accurate assessment of SOC sequestration. However, a major issue is how to subtract the indirect effect of organic fertilizer addition on internal C inputs. Specifically, organic amendments potentially improve soil health and, thus, result in an increase in main crop, catch crop, cover crop and weed yields and associated soil C inputs. Considering only zero net input OA systems, based on measured soil bulk densities, and measured external C and N inputs, Gattinger et al. (2012) reported higher topsoil SOC stocks but no differences in sequestration rates under OA compared to those under conventional practices. For comparisons in temperate regions, Sanders and Heß (2019) reported 0.26 Mg C ha−1 year−1 higher C sequestration rates in topsoil under OA compared to that under conventional management. The higher C sequestration rates in OA zero net input systems is somewhat surprising as lower OA crop yields are expected to be associated with lower soil C inputs and, thus, lower SOC stocks in the absence of addition of external organic amendments. Among the possible reasons is that equations used for estimating inputs of soil C were not specifically developed for local OA crop types and varieties, and have not been validated under on-farm or field conditions (Keel et al. 2017). Higher SOC stocks in OA have also been attributed to the use of non-comparable treatments in some experiments, e.g., rotations with a higher proportion of forages or higher rates of organic fertilizers under OA in relation to conventional ones. When the rotations and the rates of organic fertilizers are similar (similar inputs of C), the differences between the managements in the concentration of SOC disappear (Alvarez 2021).
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A global meta-analysis indicated that OA had positive effects on SOC stocks and sequestration rates even for OA farms with low manure application rates (García- Palacios et al. 2018). Besides fertilization intensity, leaf and root N concentrations also played a significant role. Thus, the choice of crop species, and more importantly their functional traits (e.g., leaf and root N), should be considered in addition to management practices and climate, when evaluating the potential of OA for climate change mitigation (García-Palacios et al. 2018). In conclusion, there is some indication that the net effect of OA on soil C sequestration may be higher than that under conventional practices due to differences in inputs of external C and N, and crop functional traits. However, data on inputs of inorganic C and appropriate allometric equations to obtain estimates of inputs of organic C into soil are needed to reduce uncertainty.
2.5 Conclusions Agricultural soil and land-use management affects the soil C stock comprised of the SIC and SOC stocks. Compared to SIC, the SOC stock has received much more attention as it sustains crop yield and soil health, especially under OA management (Table 2.6). However, some OA practices (e.g., liming and manuring) may also alter the SIC stock and, thus, the amount of CO2 sequestered in the long-term as carbonate-C. The latter has a much longer average turnover time than that of SOC. Some studies indicate that SOC stocks in topsoil under OA are higher than those under
Table 2.6 Major knowledge gaps on the effects of organic agriculture on soil carbon stocks Stock Soil carbon
Knowledge gap No data from paired long-term experiments and paired old farm fields for all major organic agriculture practices in all major global growing regions Missing soil bulk density measurement data No data for entire rooted soil profiles Missing data on lateral soil carbon fluxes No data on effects of climate and global changes No harmonized soil sampling and analytical methods Soil inorganic carbon Virtually no data Soil organic carbon Almost no measurements for plant photosynthesis Little data on plant-derived soil carbon inputs, in particular, from roots No data on microbial necromass inputs Little data on organic amendment carbon inputs Almost no data on grazing livestock carbon inputs Little data on persistence, protection, stabilization and destabilization No data on nutrient limitation of plants and soil microorganisms for soil organic carbon formation Little data on erosion, gaseous and leaching losses
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conventional management. However, lower inputs of primary soil C because of lower average crop yields together with tillage for weed control in OA fields, may result in lower profile SOC stocks in the long-term as long as those losses are not compensated by addition of external C inputs such as animal or green manures or by crop rotations and cover crops. Whether the addition of extraneous C from other agroecosystems contributes to C sequestration in OA soils by causing a net decrease in atmospheric CO2 is a researchable priority. There are numerous knowledge gaps regarding SOC formation, stabilization and destabilization in agricultural systems. Inputs of C into soil (aboveground but more importantly belowground plant residues, root exudates and rhizodeposits) appear to be the most important pathway for increasing SOC stocks. Microbial necromass must also be considered as an input to SOC formation. There is some evidence that root C allocation is higher under OA than that under conventional practices. Yet, soil C inputs are often not quantified in OA rotations. Long-term experiments on OA are scanty but needed in all global growing regions to credibly assess the effects of OA versus those of conventional management on soil profile C stocks.
2.6 Review Questions 1. What is the difference between soil C sequestration and increases in soil C stocks? 2. Describe the dynamics of SIC in soils of agroecosystems and how OA practices affect them 3. Describe the dynamics of SOC in soils of agroecosystems and how OA practices affect them 4. What is the role of SOM in OA? 5. How are SIC and SOC dynamics connected? 6. What would happen to global soil C stocks by a 100% conversion to OA? 7. How can effects of OA practices on soil C contribute to climate change mitigation? 8. What are the major knowledge gaps in the effects of OA practices on SIC and SOC stocks, and how can those be studied?
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Chapter 3
Organic Agriculture and Greenhouse Gas Emissions
Contents 3.1 Introduction 3.2 Carbon Dioxide 3.2.1 Fossil Fuel Combustion 3.2.2 Soil Carbon Dioxide Emissions 3.3 Methane 3.3.1 Soil Methane Fluxes 3.3.2 Methane Emissions from Livestock Production 3.3.3 Methane Emissions from Biomass Burning 3.4 Nitrous Oxide 3.4.1 Soil Nitrous Oxide Emissions 3.4.2 Nitrous Oxide Emissions by Livestock Production Systems 3.5 The Hidden Carbon Cost of Organic Agriculture Practices 3.6 Conclusions 3.7 Review Questions References
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Abstract Agricultural practices including those of organic agriculture (OA) affect the fluxes of the greenhouse gases (GHGs) carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) between the land surface and the atmosphere. Increasing atmospheric concentrations of GHGs result in increases of Earth’s temperate through radiative forcing (RF). The CO2 emissions in OA occur primarily from fossil fuel combustion (i.e., farm machinery use), and by soil and land-use management practices. While fossil fuel-derived CO2 emissions may be smaller for OA, soil CO2 emissions may be higher compared to those under nonorganic management based on a limited number of studies. Similarly, differences in soil CH4 emissions between both systems may be small. Specifically, while upland soils under OA can be stronger sinks for CH4 (0.09 kg CH4-C ha−1 year−1 higher soil uptake in temperate regions compared to nonorganic management), paddy soils under OA may be stronger CH4 sources compared to nonorganically managed soils but data are scanty.
© Springer Nature Switzerland AG 2023 K. Lorenz, R. Lal, Organic Agriculture and Climate Change, https://doi.org/10.1007/978-3-031-17215-1_3
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Differences in livestock CH4 emissions between conventional and OA systems appear to be small. However, soil N2O emissions under OA management may be smaller than those under conventional management due to lower inputs of reactive nitrogen (Nr) into OA soils. Otherwise, the more widespread use of leguminous cover crops, manure and slurry, poultry litter, and higher soil organic carbon (SOC) stocks in topsoil can also contribute to increased N2O emissions at OA farms. Overall, soils under OA may emit 1.05 kg N2O-N ha−1 year−1 less than those under nonorganic management with the difference being 0.3 kg N2O-N ha−1 year−1 for studies in temperate regions. In conclusion, while there is some evidence that OA contributes less to the increases in atmospheric levels of GHGs, the database on farm emissions of CO2, CH4 and N2O must be improved for more credible comparisons between conventional and OA systems. Therefore, the objectives of this chapter are to describe in detail what processes, and what livestock, soil and land-use management practices contribute to GHG emissions from OA systems, and how those emissions may be reduced. Keywords Agriculture greenhouse gas emissions · Food system greenhouse gas emissions · Radiative forcing · Global warming potential · Carbon footprint · Climate-smart agriculture · Climate-resilient agriculture · Soil and land-use management · Fossil fuel combustion · Soil tillage · Livestock production system emissions · Social cost of greenhouse gases · Life cycle analysis
3.1 Introduction Agricultural activities alter the land-atmosphere exchange of the greenhouse gases (GHGs) carbon dioxide (CO2) and methane (CH4; Fig. 2.1), and nitrous oxide (N2O). Between 2010 and 2019, agricultural CH4 and N2O emissions were estimated to average 4.2 and 1.8 Gt CO2e year−1, respectively (Nabuurs et al. 2022). Both continue to increase with enteric fermentation from ruminant animals being the main source for CH4, and manure and poultry litter application, N deposition, and N fertilizer use contributing mainly to N2O emissions. Estimated anthropogenic net CO2 emissions from agriculture, forestry and other land uses (AFOLU) sector based on bookkeeping models result in a net source of 5.9 Gt CO2 year−1 between 2010 and 2019. Based on FAOSTAT or national GHG inventories, the net CO2 emissions from AFOLU were 0.0 to 0.8 Gt CO2 year−1. Overall, land constituted a net sink of 6.6 Gt CO2 year−1 in terms of CO2 emissions (Nabuurs et al. 2022). This chapter begins with an overview on GHG-related climate effects of agriculture and the food sector. This is followed by a section on fossil fuel and soil CO2 emissions, and how OA practices may affect them. The soil-atmosphere exchange of CH4, and CH4 emission associated with livestock production and biomass burning, and effects of OA on them are discussed in a subsequent section. This is followed by an overview on N2O emissions from soil and livestock production systems, and how emissions under OA may differ from those under conventional or nonorganic
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management. The chapter concludes with a discussion on the hidden C cost of OA practices. Food system GHG emissions include more than agriculture emissions as the former consider also crop and livestock production; on-farm energy use; land use and land use change; supply chain emission associated with processing, transport, storage, and packaging of products; and food waste disposal (Tubiello et al. 2021). For example, food transport constitutes about 19% of food emissions, equivalent to 6% of emissions from all sources (Li et al. 2022). In 2018, total GHG emissions (except hydrofluorocarbons [HFCs] and black carbon [BC]) from the food system amounted to about 16 Gt CO2e year−1, i.e., one-third of the global anthropogenic total, i.e., three-times more than those from agriculture (Lamb et al. 2021). About 13 Gt CO2e year−1 were generated either within the farm gate or in pre- and post- production activities, such as manufacturing, transport, processing, and waste disposal. The remainder was generated through land use change at the conversion boundaries of natural ecosystems to agricultural land (Tubiello et al. 2021). Crippa et al. (2021) developed a global food emissions database estimating GHG (CO2, CH4, N2O, fluorinated gases) emissions, complemented with land use/land-use change emissions. Accordingly, food-system emissions amounted to 18 Gt CO2e year−1 globally, representing 34% of total GHG emissions in 2015. The largest contribution came from agriculture and land use/land-use change activities (71% or 12.8 Gt CO2e year−1; Crippa et al. 2021). Thus, food systems are one of the most important contributors to GHG emissions, but they also need to be adapted and transformed to cope with climate change impacts (Zurek et al. 2022). Animal agriculture alone contributed about 14.5% (7.1 Gt CO2e year−1) to global GHG emissions in 2010 (Gerber et al. 2013). Xu et al. (2021) provided spatially explicit estimates of production- and consumption-based GHG emissions worldwide from plant- and animal-based human food in 2010 using a model–data integration approach that ensured full consistency between subsectors. Global GHG emissions from the production of food were found to be 17.3 Gt CO2e year−1, of which 57% corresponded to the production of animal-based food (including livestock feed), 29% to plant-based foods and 14% to other utilizations. Farmland management and land-use change amounted to 38 and 29% of total GHG emissions, respectively. Rice (Oryza sativa L.) and beef (Bos taurus Linnaeus, 1758) were the largest contributing plant- and animal-based commodities (12 and 25% of total GHG emissions, respectively; Xu et al. 2021). The CO2e is calculated from the global warming potential (GWP) or time- integrated radiative forcing (RF) of GHGs (Gohar and Shine 2007). Specifically, GWP is the “time-integrated RF due to a pulse emission of a given component, relative to a pulse emission of an equal mass of CO2” (Myhre et al. 2013). The RF integrated over a given time period of the perturbation is the absolute global warming potential (AGWP; Joos et al. 2013). Carbon dioxide has a GWP of 1 regardless of the time period used. Methane has an estimated GWP over 100 years (GWP100) of 27.9 while GWP100 of N2O is estimated at 273 (IPCC 2021). The RF is defined as the change in net radiative flux (downward minus upward in W m−2) at the tropopause due to a perturbation from an external driver, after allowing the stratosphere
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to come to radiative-dynamical equilibrium (Myhre et al. 2013). It is a measure of how a perturbation to an ecosystem alters Earth’s energy budget. For any amount of any GHG, CO2e is the amount of CO2 which would warm Earth’s atmosphere as much as that amount of that gas. However, only agricultural non-CO2 sources are considered as anthropogenic GHG emissions by the Intergovernmental Panel on Climate Change (IPCC) as CO2 emitted is considered neutral, being associated to annual cycles of C fixation and oxidation through photosynthesis and respiration. Further, the IPCC ‘agriculture’ sector used in the National GHG inventory (NGHGI) covers only the non-CO2 emissions generated within the farm gate (Tubiello et al. 2021). Important CO2 emissions on the farm, e.g., from drained organic soils on agricultural land or from on-farm energy use are not accounted for. Additionally, large amounts of CO2 emissions, which stem from processes at the conversion boundaries between farmland and natural ecosystems, including emissions from tropical deforestation and tropical peatland fires are also excluded from agriculture in NGHGI accounting. These food-related CO2 emissions are instead reported by countries within the LULUCF sector of countries’ NGHGI (Tubiello et al. 2021). The term ‘carbon footprint’ is increasingly being used by organizations in the public and private sectors to indicate their effects on anthropogenic climate change (Wright et al. 2011). However, there is no universally accepted definition which is a pre-requisite before a consistent, accurate, comparable and transferable methodology can be developed. For example, studies of agricultural carbon footprint use inconsistent boundaries, and most use emission factors (EFs) based on national averages or regional models (Adewale et al. 2018). The local and farm-to-farm variability of EFs are obscured, and the comparability of carbon footprints from different studies is uncertain. Thus, Adewale et al. (2018) proposed three principles for agricultural carbon footprint calculation: (i) use of consistent broad agricultural system carbon footprint boundaries, (ii) incorporation of soil emissions and sequestration, and (iii) development and use of fine-scale EFs for agricultural inputs. Otherwise, Wright et al. (2011) emphasized that the carbon footprint should act as a proxy indicator of the contributions to anthropogenic climate change by a process, product, activity or population, accounting for the most prominent anthropogenic GHGs, CO2 and CH4. Wright et al. (2011) proposed the following definition for carbon footprint: “A measure of the total amount of CO2 and CH4 emissions of a defined population, system or activity, considering all relevant sources, sinks and storage within the spatial and temporal boundary of the population, system or activity of interest. Calculated as CO2e using the relevant 100-year global warming potential (GWP100).” The carbon footprint is a subset of the indicators covered by the Life Cycle Assessment (LCA) methodology discussed in the final section below. The GWP has its limitations. For example, Neubauer and Megonigal (2015) argued that the use of GWPs is inappropriate when calculating radiative balances for ecosystems because ecosystems exchange GHGs with the atmosphere year after year, not just as a one-time pulse. They proposed the sustained-flux global warming potential (SGWP), which is the “time integrated RF due to sustained emissions of a given component, relative to sustained sequestration of an equal mass of CO2”. For CH4, which has a much shorter lifetime than CO2, the SGWP is very different from
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the GWP (45 vs. 30 over 100 years). In contrast, because CO2 and N2O have similar average atmospheric lifetimes of roughly 100 years, the 100-year SGWP and GWP values of N2O are similar (270 vs. 263, respectively; Neubauer and Megonigal 2015). Importantly, GWP and SGWP are metrics that describe the relative radiative impact of different GHGs, and have been widely used to normalize GHG fluxes as CO2 equivalents to facilitate comparisons (Neubauer 2021). However, GWP and SGWP should not be used as synonyms for GHG fluxes. The use of clear, consistent, and unambiguous terminology is needed (Neubauer 2021). Liu et al. (2021) also question the applicability of GWP to short-lived climate pollutants (SLCPs) such as CH4, BC, HFCs, and tropospheric ozone (O3). First, the physical interpretation of a SLCP’s GWP becomes increasingly ambiguous as the selected time horizon extends, i.e., magnitudes of GWPs are strongly dependent on the selection of the target time horizon for assessment. Second, GWP does not accurately reflect the actual climate impacts of CH4, specifically, it cannot reflect the potential “cooling” caused by a decline of the CH4 emissions. In contrast, GWP* is designed to characterize the short-lived nature of SLCPs. However, the practical application of GWP* is encountering many challenges. For example, Meinshausen and Nicholls (2022) argue that GWP* is not a new metric but a new class of ‘micro climate models’. Nevertheless, GWP* may be used in combination with GWP to provide feasible strategies for mitigating SLCPs-induced climate change (Liu et al. 2021). To sum up, there is no single “perfect” metric for addressing and mitigating the various environmental, social, and economic impacts of climate change (Neubauer and Megonigal 2015). A comprehensive mitigation approach that pairs rapid decarbonization with strong, rapid and sustained reductions in CH4 emissions and additional targeted SLCP mitigation is needed to slow warming in the near term (Dreyfus et al. 2022). The enteric fermentation and agricultural soils represented together about 70% of annual total non-CO2 emissions, followed by paddy rice cultivation (9–11%), biomass burning (6–12%), and manure and slurry management (7–8%; Smith et al. 2014). Soils contribute a major share (37%; mainly as N2O and CH4) of agricultural non-CO2 emissions (Tubiello et al. 2015), and the emissions are increasing. The contribution of soils to GHG emissions was estimated at 21% of the total increase in RF due to anthropogenic increases in GHGs (Kopittke et al. 2021). About 16% was due to the loss of SOC from historical and ongoing land-use change, 3.7% due to N2O emissions from soils during agricultural production, and 1.4% due to CH4 emissions from soil systems. Soil fauna and microorganisms also directly contribute to soil GHG fluxes via their respiratory and metabolic activities and indirectly by changing the physical, chemical and biological properties of soils through bioturbation, fragmentation and redistribution of plant residues, defecation, soil aggregate formation, herbivory, and grazing on microorganisms and fungi (Zaman et al. 2021b). Climate-smart agricultural (CSA) management practices, including conservation tillage, use of cover crops and biochar application to agricultural fields, and strategic application of synthetic and organic fertilizers are considered a way to reduce GHG emissions (Zaman et al. 2021c). Some organic agriculture (OA) organizations link OA with reduced GHG emissions (Table 3.1; Ascui et al. 2019). For example,
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Table 3.1 Researchable priorities to improve knowledge about effects of organic agriculture on greenhouse gas emissions Greenhouse gas Monitoring of greenhouse gas fluxes at long-term field experiments and farmer’s fields in comparison to those under conventional management for all major organic agriculture practices in all major global growing regions Monitoring of soil properties and their effects on soil greenhouse gas fluxes Developing aims for reducing greenhouse gas emissions in organic agriculture standards Life-cycle analyses Design of low greenhouse gas emitting organic agriculture Carbon Assessment of emissions associated with whole-farm energy use dioxide Assessment of emissions associated with agronomic inputs (e.g., organic (CO2) amendments, agricultural lime) Eddy covariance measurements for estimating the net exchange between field and atmosphere Measurements of plant respiration Measurements of livestock emissions Methane Monitoring emissions from paddy soils (CH4) Assessment of antagonistic soil microbial activities under anaerobic and aerobic conditions including determination of soil moisture content Monitoring of soil mineral nitrogen contents (i.e., ammonium, nitrate) Assessment of emissions from livestock (i.e., cattle) production systems Nitrous Assessment of effects of soil aeration, soil water content, soil temperature and oxide (N2O) soil mineral nitrogen content on emissions Studies on the management of crop rotations, leguminous crops, leguminous cover crops, cover crops and organic amendments for reducing emissions Development of site-specific emission factors that consider organic amendment chemistry, soil characteristics and climate conditions Studies on management of livestock manure and urine patches for reducing emissions
IFOAM asserts that OA has the potential for reducing C emissions. However, no aim or principle to reduce GHG emissions is provided but support for reductions through advocating the use of renewable energy and energy efficiency. Further, the IFOAM standard requires monitoring, recording and optimizing energy used for artificial light, heating, cooling, ventilation, humidity and other climate control but does not link this to verification of GHG emissions (Ascui et al. 2019). Climate-resilient agriculture (CRA) is a new model of agricultural management that follows the concept of sustainable development, aiming to address hunger and poverty under climate change (Zong et al. 2022). Resilience to climate change in this regard describes how quickly agriculture recovers from a disturbance related to climate change, evaluates the ability to adapt and transform to a changing environment, and how to achieve specific developmental goals. CRA is a management model considering the entire process of agricultural production from a holistic perspective, ensuring that the measures taken by departments are coordinated with each other, and the overall development degree is within the carrying capacity of natural resources. CRA also supports cross-border cooperation (such as planting,
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breeding, aquaculture, agroforestry systems, and others) to solve cross-border climate/weather monitoring, resource management, space optimization, and scientific policy formulation. Thus, the development of CRA inherited the general characteristics of the agroecosystem, which also considered the multidimensionality and dynamics in the process of climate resilience construction. The characteristics of CRA can be summarized as sociality, multidimensionality, and dynamics. Among CRA practices are use of organic fertilizer and renewable energy instead of chemical fertilizer, pesticide, and fossil fuel resulting in a positive and significant effect on food production and soil health and decrease C emissions in the long term. Other CRA practices are related to conservation agriculture technologies (reduced tillage, crop rotations, and cover crops), soil conservation practices (contour farming), and nutrient recharge strategies that can restore SOC by providing a protective soil cover. Among CRA technologies to improve the climate resilience of agriculture and solve potential climate change risks are changes in the planting time, supplementary irrigation, intercropping, establishing short and long-term crop and seed storage infrastructure, and changing crop types or planting more climate-resilient crop varieties. To sum up, goals of CRA are improving agricultural productivity and income, enhancing adaptability to respond to climate change, and reducing GHG emissions (Zong et al. 2022). Thus, CRA, CSA and OA share some common practices and principles. Data for GHG emissions from soils under agricultural land use are mainly available for studies in Europe, China and the United States (Oertel et al. 2016). In comparison, the southern hemisphere is comparatively underrepresented. Further, rather limited information has been published for soil GHG emissions in fruit tree orchards and from those under vegetable production (Oertel et al. 2016). Relatively little is also known about how management practices affect all GHGs, particularly CH4 and CO2, and their impact on GWP and the GHG budget (Khalil et al. 2020). Methods to estimate net GWP and greenhouse gas intensity (GHGI, i.e., net GWP divided by crop yield) that account for all sources and sinks of GHG emissions in agroecosystems are evolving (Sainju 2020). For example, a meta-analysis indicated that there is little-to-no effect of no-tillage (NT) on soil CH4 emissions when used in arable soils, but a reduction by 23% in rice production compared to conventional tillage (Maucieri et al. 2021). Otherwise, estimates of N2O emissions under NT vs. conventional tillage systems are uncertain (Page et al. 2020). Thus, long-term monitoring of all GHG sources and sinks including soil GHG fluxes is needed to identify soil and land-use management practices associated with lower GWP, GHGI and soil GHG emissions (Maier et al. 2020; Sainju 2020). For a more comprehensive accounting of the contribution of C sequestration to climate change mitigation, it is necessary to quantify the avoided warming effects of sequestered C in agroecosystems over the timescale the C is stored (Sierra et al. 2021). The GWP metric is inappropriate to quantify avoided warming potential as a result of C sequestration. GWPs are useful to quantify the climate impacts of increasing or reducing emissions of GHGs to the atmosphere. However, it is also necessary to quantify the climate benefits of C flows in the opposite direction, i.e., from the atmosphere to land. Further, it is also important to quantify not only how
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much and how fast C enters ecosystems, but also for how long C stays in an ecosystem. Thus, Sierra et al. (2021) introduced the climate benefit of sequestration (CBS), a metric that quantifies the radiative effect of fixing CO2 from the atmosphere and retaining it for a period of time in an ecosystem before releasing it back as the result of respiratory processes and disturbances. Similarly, Neubauer and Megonigal (2015) proposed the sustained-flux global cooling potential (SGCP), for situations where ecosystems remove GHGs from the atmosphere. In the following sections, the effects of OA practices on the emissions of GHGs will be discussed separately for CO2, CH4 and N2O (Table 3.2). The chapter concludes with a discussion on the hidden carbon cost of OA practices.
Table 3.2 Sources for greenhouse gas emissions in organic agriculture Greenhouse gas In agroecosystems Carbon Plant and livestock respiration dioxide (CO2) Herbivory Soil respiration by decomposition of crop residues, organic amendments, and soil organic carbon Agricultural lime applied to soils Combustion of agricultural residues Fossil fuel combustion associated with farm machinery use and irrigation Methane Methanogenic archaea in rice (Oryza (CH4) sativa L.) paddies and in waterlogged anaerobic soils Anaerobic microbial decomposition of organic matter and organic amendments Enteric fermentation by grazing animals [i.e., cattle (Bos taurus Linnaeus, 1758)] Manure deposited on fields and pastures Biomass combustion (i.e., flame weeding) Nitrous oxide Nitrification of ammonia (NH3) (N2O) Oxidation of NH3 to nitrate (NO3−) by bacteria and archaea Organisms that oxidize NH3 to nitrite (NO2−) Denitrification of nitrite or nitrate Nitrite accumulation in urine patches Residues of leguminous crops, cover crops, and pasture species Soil organic matter-induced stimulation of microbial processes Grazing livestock
Other sources Fossil fuel combustion associated with heated greenhouses Fossil fuel combustion during production and transport of organic amendments and pesticides
Enteric fermentation by housed animals (i.e., cattle) Anaerobic decomposition of organic materials in livestock manure Manure handled in a dry form Liquid manure management systems such as lagoons and storage tanks
Combination of nitrification and denitrification associated with storage and treatment of livestock manure Housed livestock Nitrite accumulation in urine patches of housed animals, and in compost piles
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3.2 Carbon Dioxide The atmospheric CO2 concentration increased from ~277 ppm in 1750 to ~418 ppm in 2021 (Friedlingstein et al. 2021). It is unprecedented in the last 2 million years and, the current rate of atmospheric CO2 increase is at least 10 times faster than at any other time during the last 800,000 years. The atmospheric concentration of CO2 is now higher than that in the last 800,000 years estimated from ice core records, and probably at levels last seen around 23 million years ago based on δ13C values of terrestrial C3 plant remains (Cui et al. 2020; Lenton et al. 2019). This increase in atmospheric CO2 concentration causes an increase in atmospheric temperatures. As of 2019, CO2 accounts for two-third (2.076 W m−2 out of 3.140 W m−2) of the total anthropogenic RF from long-lived gases (not including O3, aerosols, and clouds; http://www.esrl.noaa.gov/gmd/aggi/). Since 1990, CO2 is responsible for about 65% of the total RF of the GHGs CO2, CH4 and N2O plus several halogenated gases (Dlugokencky et al. 2019). The associated long-term effects of twenty-first century warming will be felt for centuries to come beyond the year 2100, even if emissions are limited in the future (Lyon et al. 2022). Besides contributing directly to warming, elevated CO2 contributes also indirectly to atmospheric temperature increases by enhancing N2O emissions from soils of agroecosystems by 44% according to meta-analysis (Du et al. 2022). Major natural CO2 sources in agriculture are respiration of animals, soils (microbial respiration) and plants, while major anthropogenic sources include burning of fossil fuels, deforestation, and the cultivation of land that increases decomposition (Zaman et al. 2021a). For example, farmland soil CO2 emissions (sum of soil disturbance and tillage emissions) and livestock respiration emissions were estimated at 2.4 and 4.9 Gt CO2e year−1, respectively, in 2010 (Xu et al. 2021). Emissions from savannah burning, peat drainage and peat fires were not accounted for. OA practices may also contribute to the increase in atmospheric CO2 concentrations. The CO2 emissions by OA practices occur primarily from fossil fuel combustion, and by soil and land-use management (Table 3.2). Direct CO2 emissions from fossil fuel combustion are associated with farm machinery use, irrigation, and heated greenhouses (Muller and Aubert 2014). Using zero-emission sources (e.g., battery electric power) to operate tractors and irrigation pumps may greatly reduce CO2 emissions (Ahmed et al. 2020). Indirect CO2 emissions from fossil fuel combustion mainly accrue from production and transport of OA fertilizers and pesticides (Lal 2004). Further, CO2 emissions from fields managed by OA practices may occur: (i) from plant and livestock respiration, and herbivory, (ii) from soil respiration by decomposition of crop residues, organic amendments and SOC, (iii) from lime applied to soils, and (iv) from burning of agricultural residues (Gomiero et al. 2011). In addition to autotrophic and heterotrophic respiration, geologic sources and CO2 production in bedrock beneath soils may also contribute to the CO2 efflux from the agroecosystem surface (Tune et al. 2020). Otherwise, not all CO2 produced in soil and bedrock may reach the soil surface as some soil microorganisms can fix
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CO2 present in soil pore spaces through non-phototrophic or dark CO2 fixation (Miltner et al. 2004).
3.2.1 Fossil Fuel Combustion Estimates of emissions from energy use in conventional agriculture in kg carbon equivalents (CEs) per hectare are 2–20 for different tillage operations, 2–4 for drilling or seeding, and 6–12 for combine harvesting (Lal 2004). Estimates of C emissions in kg CE per kg lime are 0.03–0.23. The CO2 emissions from organic fertilizers may be treated as zero since they are sourced from renewable biomass (Muller and Aubert 2014). Irrigation emits 129 kg CE for applying 25 cm of water and 258 kg CE for applying 50 cm of water. Emission for different tillage methods are 35.3 kg CE ha−1 for conventional till, 7.9 kg CE ha−1 for chisel till or minimum till, and 5.8 kg CE ha−1 for no-till (NT) method of seedbed preparation (Lal 2004). The CO2 emissions from machinery use and irrigation can be similar for both OA and conventional agriculture (Muller and Aubert 2014). However, irrigation requirements and associated CO2 emissions may be lower for soils managed by OA practices because of higher soil water holding capacity due to higher SOM contents under OA at least in the topsoil (Gattinger et al. 2012). Also, CO2 emissions from heated greenhouses can be lower for OA systems because the use of heated greenhouses is restricted by some OA standards (Muller and Aubert 2014). In contrast, less effective pest and weed control in OA can increase machinery use for mechanical control of pests and weeds, and associated fossil fuel combustion. Otherwise, CO2 emissions from the production and application of synthetic fertilizers and pesticides do not arise as those are prohibited in OA (Muller and Aubert 2014). Overall, whole-farm energy use and associated CO2 emissions can potentially be lower for OA systems except probably for poultry and fruit sectors (Lynch et al. 2011; Tuomisto et al. 2012).
3.2.2 Soil Carbon Dioxide Emissions The net CO2 exchange of agroecosystem surface with the atmosphere can be estimated based on gas collected from chambers at the soil surface or eddy covariance (EC) measurements. The EC technique allows the calculation of annual budgets of CO2 fluxes between agroecosystems and the atmosphere (Baldocchi et al. 2018). EC measurements can resolve annual C stocks on the order of 0.5 Mg C ha−1 (50 g C m−2) integrated over a management-relevant spatial scale of 100–1000 ha (Hemes et al. 2021). Croplands are generally CO2 sinks as indicated by negative values for the net ecosystem exchange (NEE). NEE consists of gross photosynthesis (assimilation or
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gross primary production GPP), autotrophic (plant) respiration (Ra) and heterotrophic (animal, bacteria and fungi) respiration (Rh; Fig. 2.1; Eq. 3.1).
NEE = GPP – R a – R h
(3.1)
However, NEE does respond to lateral C fluxes. Thus, Schulze et al. (2021) proposed to include “dead” material of grain and straw of croplands that is removed after harvest, which should lower Rh as compared to a situation where grain and straw remain on site. The C in grain and straw is respired geographically elsewhere, maybe on a different continent. Thus, the net flux balance of cropland should be expressed following Eq. 3.2:
NEE GPP R a R h onsite R h harvest
(3.2)
Similarly, the NEE of grasslands should be expressed based on Eq. 3.3:
NEE = GPP – R a – R h onsite – R h grazers
(3.3)
In the case of grasslands, the removal of green biomass has profound positive feedback on GPP that could balance the export. Further, for rangelands, respiration of grazing animals would be included, but in case of hay-meadows Rh of domestic animals would not be included (Schulze et al. 2021). Some grasslands may be on the verge of switching to CO2 sources as year-to- year changes in respiration are outpacing those in photosynthesis in contrast to croplands (Baldocchi et al. 2018). Both, biotic and abiotic processes contribute to CO2 production in soil. In carbonate-bearing agricultural soils, local soil respiration rates and CO2 exchange are likely to be influenced by dissolution and precipitation of calcium carbonates (Gallagher and Breecker 2020. Data of EC measurements for OA fields with standardized methodology have not been published (Ball et al. 2014). Published data on direct measurements of soil CO2 emissions from paired conventional and OA experiments and farmer’s fields are also scanty (Lorenz and Lal 2016). Lower primary soil C inputs under OA because of lower yields are expected to result in lower soil CO2 emissions as less substrate for microbial decomposition may be available. However, higher CO2 emissions under OA than those under conventional practices are often observed based on a global meta-analysis (García-Palacios et al. 2018). Likely reasons are enhanced decomposition of organic amendments (i.e., animal and green manures) and SOM facilitated by the improved soil structure under OA management. Shifts in microbial community composition may also contribute (García-Palacios et al. 2018). In the rhizosphere, the microbial respiration may also be increased following the addition of organic amendments (Kontopoulou et al. 2015). Some studies of field CO2 emissions under OA published since the review by Lorenz and Lal (2016) are summarized in the following sections. Necpalova et al. (2018) examined the long-term impact of OA vs. conventional soil management practices on soil CO2 emissions at four long-term experimental
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sites in Switzerland estimated from the changes in SOC stocks. At one site, soil CO2 emissions for an OA system fertilized with farmyard manure and slurry were lower than those for an unfertilized conventional system. Slurry is a mixture of feces and urine from housed livestock, mixed with bedding material and cleaning water (Pain and Menzi 2011). At another site, OA in combination with reduced tillage resulted in estimated net soil CO2 uptake while OA combined with mouldboard ploughing had similar soil CO2 emissions than those under conventional NT (Necpalova et al. 2018). Overall, reduced long-term SOC losses under OA may have contributed to reduced soil CO2 emissions. Specifically, OA combined with reduced tillage led to a strong reduction in estimated CO2 emissions (Necpalova et al. 2018). Lenka et al. (2017) studied CO2 emissions from soils in the eighth and ninth year of a soybean-wheat (Glycine max L.-Triticum spp.) cropping system in central India. Seasonal emissions of CO2 were higher from soils under soybean and wheat under OA management (1.3 and 4.2 Mg C ha−1, respectively) than for those under conventional management (0.9 and 3.0 Mg C ha−1, respectively). The higher CO2 emissions under OA were explained by higher availability of organic C in the soil resulting in increased soil respiration rates (Lenka et al. 2017). Feiziene et al. (2016) reported that OA crop rotations involving red clover (Trifolium pratense L.) at a field site in Lithuania had higher SOC sequestration and soil net CO2 emissions during 5 experimental years than those involving other legumes or rotations without legumes. Apparently, red clover created soil environmental conditions more favorable for soil respiration. Specifically, red clover was associated with the highest soil mesoporosity, the lowest microporosity, best supply of plant-available water, high soil resistance to dry conditions, and increases in soil N and K reserves compared to other legumes (Feiziene et al. 2016). Sainju et al. (2021) examined GHG emissions under wheat-based sequences in OA and conventional crop productions in the northern Great Plains, USA. OA crop production included sheep grazing (Ovis aries L.) to control weeds without N application, and conventional crop production included herbicides, pesticides, and N applications. Cropping sequences in a 5-year rotation were safflower (Carthamus tinctorius L.)/sweet clover cover crop [Melilotus officinalis (L.) Lam.]–sweet clover cover crop–winter wheat–lentil (Lens culinaris L.)–winter wheat were lentil after winter wheat, winter wheat after sweet clover cover crop, and winter wheat after lentil. Overall, OA wheat production reduced CO2 emissions compared with conventional crop production. Higher CO2 emissions under conventional practices was explained by N fertilization, which may have promoted root growth and respiration as a result of increased N availability. Nitrogen fertilization may have also reduced the soil C/N ratio that resulted in increased C mineralization and CO2 flux (Sainju et al. 2021). Autret et al. (2016) assessed the net CO2 emissions from soil based on the SOC change rate in a 16-year cropping experiment without manure fertilization. Soils under OA sequestered relatively more atmospheric CO2 in 0–30 cm depth than those under conventional management (0.28 Mg C ha−1 year−1 vs. 0.08 Mg C ha−1 year−1). The main reason for the positive effect of OA on SOC storage was extra C input from fescue (Festuca spp.) and alfalfa (Medicago sativa L.; Autret et al. 2016).
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A subsequent study of this experiment after 19 years also indicated that the OA system acted as a CO2 sink (Autret et al. 2019). However, direct measurements of soil CO2 fluxes in the field were not available but would be needed to clarify this. Bosco et al. (2019) studied GHG emissions in a Mediterranean environment at crop rotations including Savoy cabbage (Brassica oleracea var. sabauda L. cv. Famosa), spring lettuce (Lactuca sativa L. cv. Justine), fennel (Foeniculum vulgare Mill. cv. Montebianco) and summer lettuce (L. sativa cv. Ballerina). Cumulative CO2 emissions over 16 months at two fields were higher under OA (18.3 and 22.6 Mg C ha−1, respectively) compared to those under conventional management (13.0 and 16.7 Mg C ha−1, respectively). At the OA fields, green manure incorporation and organic fertilizer application may have increased soil heterotrophic respiration while living mulch may also have increased autotrophic respiration together contributing to the increased CO2 emissions. However, the cropping systems were implemented only recently at this site, and a longer monitoring period is needed for more credible conclusions regarding vegetable cropping system effects on GHG emissions (Bosco et al. 2019). Three-year cumulative CO2 emission in a low input OA system of a vegetable crop rotation in Kentucky, USA, was 50% higher than that of the conventional system (Shrestha et al. 2019). Incorporation of plant residues from the previous 5-year mixed grass/legume pasture has likely contributed to higher CO2 emissions at the OA rotation compared to the conventional system without a similar fallow period. In Washington State, USA, soils were predicted to lose 57 kg SOC ha−1 year−1 in 0–30 cm depth without residue C additions to OA vegetable rotations (Adewale et al. 2016), which would indicate a net flux of CO2 to the atmosphere. However, when residue C was added to the SOC stock, a gain of 20 kg C ha−1 year−1 was predicted for the top 30-cm depth, i.e., a net CO2 sink for this OA vegetable system relative to the atmosphere (Adewale et al. 2016). At vegetable farms in Japan, simulated CO2 emission per ha for OA were eight times lower than that for conventional management (Matsuura et al. 2018). However, the highest CO2 emission per kg of crop was estimated for an OA system with no grass mulching due to very low yield. After 6 years of management, lower soil respiration in an OA orange (Citrus sinensis) orchard in Brazil suggested a small positive C balance (Escanhoela et al. 2019). This indicated a significant C sequestration after a longer period of management compared to that of conventionally managed orchards. Aside from the soil, CO2 emissions from OA fields occur also by autotrophic plant respiration Ra. No data on plant respiration under OA compared to those under conventional practices have been published. It is likely that crop respiratory CO2 emissions are lower for OA because of lower crop biomass and yield (Seufert 2019). Otherwise, higher abundance of weeds and cover crops in the OA rotation may also result in higher plant CO2 emissions at OA fields compared to those for conventionally managed fields. Plant respiration at OA systems should be measured to facilitate the development of a more complete field CO2 balance. Crop-livestock systems are indispensable to OA (Entz and Martens 2009). Often neglected in the C cycle of agroecosystems are CO2 emissions from animals. The CO2 in livestock respiration should be counted as emission and not considered a
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balanced return of recent photosynthetically fixed C to the atmosphere (Goodland 2014). For example, livestock respiration C emissions range between 1.25 kg C year−1 for chickens (Gallus gallus domesticus), ducks, geese, and turkeys (Meleagris spp.), and 217.00 kg C year−1 for cattle (Bos taurus) and buffaloes (Bison spp.), and to 305.04 kg C year−1 for horses (Equus ferus caballus; Cai et al. 2018). Thus, CO2 emissions from grazing livestock contribute to field CO2 emissions but no data under OA practices have been published. Similarly, whether addition of agricultural lime (CaCO3) and hydrated lime to OA soils contributes to field CO2 emissions is a matter of debate (Kunhikrishnan et al. 2016). Further, field CO2 emissions may also originate from flaming as it is sometimes used to control weeds in heat-tolerant herbaceous and horticultural crops under OA management (Melander et al. 2005). Burning of weeds, for example, is a common practice in bio-dynamic agriculture (Chalker-Scott 2013). However, burning in the field is thought to be CO2 neutral due to ‘C sequestration’ of the emitted CO2 during the next cropping season (Lin et al. 2012). To sum up, soil CO2 emissions for OA systems can be higher compared to those from conventionally managed soils most likely because of higher availability of labile substrates added with organic amendments and more favorable soil structure for decomposer activity. This implies that OA may contribute less to SOC sequestration even when the organic amendments origin from the same land unit under consideration. However, more long-term studies on the net CO2 exchange comparing fields under OA with those under conventional practices are needed to support this observation (Table 3.1).
3.3 Methane The globally averaged atmospheric CH4 concentration in 2021 was 1895.7 ppb, increasing 17 ppb compared to 2020, i.e., the largest annual increase recorded since systematic measurements began in 1983 (NOAA 2022). Increasing atmospheric CH4 concentrations contributes to warming the climate. In 2019, CH4 contributed 0.52 W m−2 to global total anthropogenic RF, about a quarter of that due to CO2 (http://www.esrl.noaa.gov/gmd/aggi/). However, the reasons for the recently rapidly increasing atmospheric CH4 concentration are not well understood (Saunois et al. 2016). Jackson et al. (2020) estimated that the recent growth in atmospheric CH4 concentrations may be due in roughly equal parts to emissions from fossil fuel sources, and the combined emissions from agricultural and waste sources. Fifty-six percent of the total anthropogenic CH4 emissions for the period 2008–2017 came from agriculture and waste (206–219 Tg CH4 year−1; Saunois et al. 2020). Similarly, Zhang et al. (2022) estimated that agriculture, landfill and waste sectors were responsible for 53% of the renewed growth in atmospheric CH4 over the period 2007–2017 compared to 2000–2006. Industrial fossil fuel sources explained an additional 34%, and wetland sources contributed the least at 13%. In addition to directly contributing to RF, CH4 is an important contributor to the formation of
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tropospheric O3 (Mar et al. 2022). Ozone is a GHG, damages plants, may reduce crop yields and reduce the ability of terrestrial ecosystems to absorb CO2. Thus, the rapid increase in atmospheric CH4 concentration jeopardizes efforts to achieve the goals of the 2015 United Nations Convention on Climate Change Paris Agreement (Nisbet et al. 2020). Natural sources of CH4 emissions include wetlands and termite activities (Zaman et al. 2021a). Paddy fields used for rice production, livestock production systems (enteric emission from ruminants), landfills, and the production and use of fossil fuels are the main anthropogenic sources of CH4 (Zaman et al. 2021a).
3.3.1 Soil Methane Fluxes The CH4 emissions from soils result from antagonistic microbial activities under anaerobic and aerobic conditions (Le Mer and Roger 2001). On one hand, CH4 is produced under strictly anoxic conditions in the anaerobic zones of submerged soils by methanogens. Rice paddies and waterlogged anaerobic soils, for example, are emitters of large amounts of CH4 produced by methanogenic Archaea. The anaerobic microbial decomposition of OM and organic fertilizers contributes also to CH4 emissions (Muller and Aubert 2014). The biogenic methanogenesis may, however, not be a strictly anaerobic process exclusive to Archaea. For example, Bižić et al. (2020) reported that cyanobacteria produce CH4 in terrestrial environments, a process which is enhanced during oxygenic photosynthesis. Thus, cyanobacteria in addition to Archaea have been identified as a source for CH4 in oxic soils. There is also growing evidence that algae, plants, animals and fungi produce CH4 under oxic conditions (Bižić et al. 2020). Soil methanotrophy is the only biological process that removes CH4 from the atmosphere as well aerated or drained soils are generally sinks for CH4 (Skinner et al. 2014). By this process, CH4 is oxidized to CO2 by aerobic CH4 oxidizing bacteria or methanotrophs in upland soils and aerobic zones of wetland soils. The oxidation of CH4 by soils represents about 5% of its loss (Mar et al. 2022). Specifically, soil methanotrophy globally removes 11–49 Tg CH4 year−1 from the atmosphere, an amount in the range of annual global emissions of CH4 from rice agriculture (Murguia-Flores et al. 2021). Rates of soil methanotrophy are controlled by atmospheric CH4 concentration, temperature, moisture, soil texture, N content, and land use practices (Castro et al. 1995). Upland mineral soils under natural vegetation are the strongest atmospheric CH4 sink with the uptake rate decreasing in the order natural forest > reforested land > grassland > cultivated land (Reay et al. 2018). Recently, a widespread soil bacterium was isolated that grows on air at atmospheric concentrations of CH4 (Tveit et al. 2019). High mineral N contents in soil (ammonium [NH4+] and nitrate [NO3−]) such as those found under conventional agricultural practices suppress CH4 uptake which would mean OA soils can be relatively stronger CH4 sinks (Skinner et al. 2014). This is supported by the observation that organic N additions common in OA have a lower reduction effect on soil CH4 uptake
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compared to the addition of inorganic N forms by conventional agriculture (Wu et al. 2022). However, effects depend also on the geographic region as N inputs dominate changes in soil methanotrophy in Europe and Asia, while soil moisture is the most important influence in tropical South America (Murguia-Flores et al. 2021). Knowledge on the impact of OA practices on soil CH4 emissions compared to those of non-OA farming practices is scanty (Tables 3.1 and 3.2; Skinner et al. 2019). Compared to conventional systems, a global meta-analysis reported higher area-scaled CH4 uptake in upland soils managed by OA (Skinner et al. 2014). Similarly, soils managed by OA practices in temperate regions took up 18.3% more CH4-C (0.09 kg CH4-C ha−1 year−1) than those under conventional practices (Sanders and Heß 2019). In contrast, higher area-scaled CH4 emissions under OA practices were reported for rice paddies (Skinner et al. 2014). Under upland conditions, lower soil N levels in OA soils may have reduced CH4 oxidation activity to a lesser degree compared to that under conventional practices, and contributed to the relative increase in CH4 uptake. In contrast, organic fertilizers may have favored CH4 production from the anaerobic decay of OM in OA rice paddies (Skinner et al. 2014). However, only one comparative study on rice paddies was included in the meta- analysis by Skinner et al. (2014), and all other 22 retrieved studies were conducted in the Northern hemisphere under temperate climate conditions (Sanders and Heß 2019). Thus, additional CH4 flux measurements in farming systems comparisons are required to confirm these preliminary observations. In a grass-clover – silage maize (Zea mays L.) – green manure cropping sequence in the long-term DOK field trial in Switzerland, area-scaled CH4 emissions did not differ between OA and non-OA farming practices (Skinner et al. 2019). On one hand, the regular application of stacked cattle manure may have increased the biomass of methanogenic archaea in OA soils. In combination with high soil water contents, this may have contributed to increased CH4 emissions under OA practices. In contrast, application of composted organic materials may have transiently fostered CH4 oxidation activity which could have contributed to CH4 uptake under OA practices during silage maize cropping. However, anoxic conditions due to high soil water content in the OA soil may have reduced CH4 oxidation and uptake but allowed CH4 from deeper layers to pass through upper soil horizons to the atmosphere. Overall, OA and non-OA system effects on CH4 fluxes were comparable (Skinner et al. 2019). Krauss et al. (2017) monitored CH4 fluxes for 2 years in a grass-clover ley – winter wheat – cover crop sequence in an OA managed long-term tillage trial on a clay rich soil in Switzerland. There was no clear influence of tillage, conservation tillage or fertilization system under OA practices on cumulative CH4 uptake (Krauss et al. 2019). This was explained by overlapping effects of CH4 emissions after slurry applications and CH4 uptake for most of the year by the soil under OA management (Krauss et al. 2017). Biernat et al. (2020) measured CH4 fluxes for 2 years at farms in Northwest Germany after more than 10 years of continuous management. The CH4 fluxes per unit area were close to zero, and not different between soils under OA compared to those under conventional management. Sainju et al. (2021) did also find no
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differences in CH4 fluxes for wheat-based OA compared to conventional crop production systems in the northern Great Plains, USA. Mohanty et al. (2015) demonstrated that organic fertilizer stimulated CH4 consumption in tropical upland soil under soybean–wheat cropping system at an OA farm. This was likely due to the alteration in soil physical properties and microbial populations. However, whether OA generally enhances CH4 consumption in tropical soils needs additional research (Mohanty et al. 2015). For example, seasonal cumulative CH4 uptake was highest for OA during the soybean growing season but lowest during the wheat growing season compared to that under conventional practices in central India (Lenka et al. 2017). Differences in precipitation and soil moisture contents may have contributed to the differences in CH4 uptake between OA and non-OA farming systems, and to differences between both seasons (Lenka et al. 2017). No difference in soil CH4 uptake between conventional and OA practices was reported for a 2-year irrigated vegetable crop rotation in a Mediterranean environment (Bosco et al. 2019). Both, the higher mineral fertilizer rate at the conventional system and the higher tillage disturbance at the conventional and OA vs. the NT OA system have apparently not inhibited the soil CH4 oxidation capacity. However, long-term monitoring is needed to verify these initial observations (Bosco et al. 2019). In summary, there is some evidence that OA can result in lower net CH4 emissions from upland soils but higher net CH4 emissions from paddy soils compared to soils managed conventionally. However, conclusions are preliminary as those are based on a limited number of data from long-term paired field studies, and additional long-term experiments are needed (Table 3.1).
3.3.2 Methane Emissions from Livestock Production Methane from livestock contributes 30% of the global anthropogenic CH4 emissions (Jackson et al. 2020). The CH4 emissions from livestock production can derive from: (i) enteric fermentation, (ii) anaerobic decomposition of organic materials in livestock manure, (iii) manure deposited on fields and pastures, or handled in a dry form, and (iv) liquid manure or slurry management systems, such as lagoons and storage tanks (Kupper et al. 2020). During 2000–2017, livestock (especially enteric fermentation) were among the dominant drivers of observed CH4 emission increases (Stavert et al. 2022). Ruminants, such as cattle, sheep, and goats (Capra aegagrus hircus), predominantly ferment plant material in their rumen to acetate, propionate, butyrate, CO2, and CH4 (Wolin 1981). Important CH4 emitters are cattle (Saunois et al. 2020). Emission intensity, i.e., the amount of CH4 emitted per unit of animal proteins decreased for most livestock categories globally during 2000–2018 (Chang et al. 2021). Forage nutritive value and, in particular, digestibility affects enteric CH4 production (Sollenberger et al. 2019). Thus, lower amounts of CH4 produced per unit of
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feed consumed and per unit of animal product may be associated with increased intake of higher digestibility feeds. There is also some evidence that enteric CH4 emissions are lower from ruminants fed forage legumes than fed grasses (Sollenberger et al. 2019). In the future, the microbiome development of cows may be modulated to lower CH4 emissions (Furman et al. 2020). However, efforts on the demand-side to promote balanced, healthy, and environmentally sustainable diets in most countries will not be sufficient to mitigate livestock CH4 emissions without parallel efforts to improve production efficiency (Chang et al. 2021). The CH4 escapes the rumen into the atmosphere via eructation and breathing of the animals. Enteric fermentation alone is responsible for about 40% of total agricultural GHG emissions (Tubiello et al. 2013). The CH4 emission from enteric fermentation accounts for 47% of the livestock sector’s GHG emissions, and 90% of the total CH4 emissions (Opio et al. 2013). Otherwise, manure management is associated with a smaller contribution to livestock production CH4 emissions (Chang et al. 2019). The CH4 emissions from livestock manure can be reduced by composting (Bernal et al. 2017). As measurements of CH4 production from individual animals, groups of animals, or at a regional level from herds of livestock is expensive and requires specialized equipment, CH4 emission data are uncertain and quantitative approaches such as mathematical modeling are used to estimate them (Wolf 2020; Niu et al. 2018). The differences between CH4 emissions from manure management under OA compared to those under conventional practices are unclear as the number of published studies is very limited (Table 3.1; He 2019). Comparisons between CH4 emissions from ruminants raised by OA practices with those raised by conventional practices are scanty. For example, a review by Gross et al. (2022) of 22 studies at dairy farms in industrialized countries highlighted the great importance of CH4 emissions from enteric fermentation in both conventional and OA production systems. Specifically, absolute and relative enteric CH4 emissions under OA milk production were slightly higher compared to those under conventional practices. Van Wagenberg et al. (2017) also reported that an OA livestock production system had a higher enteric CH4 emission per unit milk because of a lower milk yield per cow and an increased use of roughage. However, this observation was based on only 12 studies with most of them from Europe. Differences in CH4 emissions between studies were uncertain as those were mainly related to methodological differences and differences in assumptions on production data (van Wagenberg et al. 2017). Feed additives and diet (i.e., forage legumes) may provide a great opportunity for reducing CH4 production by dairy cattle and ruminants (Rotz 2018). Grazing at the optimal maturity to achieve high forage nutritive value and at a stocking rate that optimizes animal performance are other potential strategies for mitigating CH4 emissions (Sollenberger et al. 2019).
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3.3.3 Methane Emissions from Biomass Burning Methane emissions from biomass burning (i.e., tropical C4 savanna grasslands, crop residues) are globally important. Burning occurs very widely in savanna grasslands of Africa. Globally, biomass and biofuel burning emitted 30 Tg CH4 year−1 in the period 2008–2017 (Saunois et al. 2020). In OA, flame weeding is sometimes used, and may result in CH4 emissions. However, whether CH4 emissions associated with biomass burning differ between conventional and OA systems is not known.
3.4 Nitrous Oxide The atmospheric N2O concentration has increased by more than 20% from 270 parts per billion (ppb) in 1750 to 331 ppb in 2018 (Tian et al. 2020). This increase contributes to warming the climate. In 2019, N2O contributed 0.2 W m−2 to global anthropogenic RF, about a tenth of that due to CO2 (http://www.esrl.noaa.gov/gmd/ aggi/). On one hand, N2O is emitted by natural processes from terrestrial ecosystems (Zaman et al. 2021a). Otherwise, anthropogenic N2O emissions occur mostly through agricultural and other land-use activities, and are associated with the intensification of agricultural and other human activities such as increased use of synthetic N fertilizers, inefficient use of irrigation water, deposition of animal excreta (urine and dung) from grazing animals, excessive and inefficient application of farm effluents and animal manure to croplands and pastures, and management practices that enhance soil organic N mineralization and C decomposition (Zaman et al. 2021a). In recent decades, atmospheric N deposition has increased as an important agricultural soil N input (Yang et al. 2021). Agricultural practices and, in particular, the use of ammonia (NH3)-based and other N-fertilizers, and NH3 deposition from fertilizer, livestock excreta, animal manure and poultry litter have greatly enhanced N2O emissions (Lin et al. 2022; Zaman et al. 2021a; Thompson et al. 2019). Globally, total NHx deposition has increased by 70% from 1980 and 2018, and N fertilizer is over-used in many countries, i.e., China, India and the United States (Liu et al. 2022). However, 38% of N fertilizer can be reduced without impacting current yields of wheat, maize, and rice. Global agricultural NH3 emissions increased by 78% from 1980 and 2018, with cropland NH3 emissions increased by 128%, and livestock NH3 emissions increased by 45%. Three crops (wheat, maize, and rice) and four animals (cattle, chicken, goats, and pigs) accounted for over 70% total NH3 emissions (Liu et al. 2022). The NH3 EFs average 12.6% and 14.1% of applied N fertilizer for synthetic N fertilizer and manure, respectively (Ma et al. 2021). For temperate wet climates, NH3 EFs for broadcast cattle solid manure and slurry were estimated at 0.03 and 0.24 kg NH3–N kg−1 total N (TN), respectively, whereas the NH3 EF of broadcast swine (Sus domesticus Erxleben, 1777) slurry was 0.29 kg NH3–N kg−1 TN (van der Weerden et al. 2021). Soil application of cattle and swine manure in wet climates had EFs of
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0.005 and 0.011 kg N2O–N kg−1 TN, respectively, whereas in dry climates the EF for cattle manure was 0.0031 kg N2O–N kg−1 TN. The N2O EFs for cattle urine and dung in wet climates were 0.0095 and 0.002 kg N2O–N kg−1 TN. The N2O EFs for sheep urine and dung in wet climates were 0.0043 and 0.0005 kg N2O–N kg−1 TN, respectively. However, more data from underrepresented regions (e.g., Asia, Africa, South America) are needed to increase the credibility of EF estimates (van der Weerden et al. 2021). Some OA practices may be beneficial for NH3 emission reductions. For example, Xu et al. (2022) reported that NH3 emissions from organically managed fields in China (overall the substitution of N fertilizer with livestock manure) decreased by an average of 57.2% compared to those from conventionally managed fields while enhancing crop yields for wheat, maize, and rice. Further, partial substitution of N fertilizer with manure on organically managed fields increased nitrogen use efficiency (NUE) by 27.9%, while full substitution decreased NUE by 13.3% (Xu et al. 2022). However, it was unclear what organic practices included in addition to substituting N fertilizer with livestock manure, and whether those practices were certified as OA. After NH3 is emitted to the atmosphere and reacts with acids, it forms salts which then return to Earth’s surface and act as a N source for N2O emissions, similar to a fertilizer-N application (Zaman et al. 2021a). Synthetic N fertilizer applications to croplands may have accounted for 70% of total N2O emissions from croplands during 2000–2014 (Xu et al. 2020). Overall, direct and indirect N2O emissions from N additions in agriculture contributed 3.95 Tg N year−1 between 2007 and 2016 while global total N2O emissions amounted to 16.9–17.0 Tg N year−1 (Tian et al. 2020). Further, N deposition may account for 25% of global cropland soil N2O emissions (Yang et al. 2021). N deposition may explain 15% of the increase of 2% year−1 in global soil N2O emissions over croplands during 1996–2013 (Yang et al. 2021). Uncertainty in estimates of annual N2O emissions by agriculture is high as emissions are highly variable and short-lived peak emission periods may contribute more than 50% to annual emissions (Dorich et al. 2020).
3.4.1 Soil Nitrous Oxide Emissions Average soil background N2O emissions, i.e., from soils that receive no N fertilizer or soil management were estimated at 1.10 and 0.84 kg N ha−1 year−1, with variations from 0.18 to 3.47 (5th–95th percentile, hereafter) and −1.16 to 3.70 kg N ha−1 year−1 for cropland and grassland, respectively (Yin et al. 2022). Nitrifier nitrification, nitrifier denitrification, and heterotrophic denitrification are considered as the dominant biological processes contributing to the production of N2O in soil (Chang et al. 2022). Soil pH, soil N mineralization, atmospheric N deposition, soil volumetric water content, and soil temperature are principal drivers of soil background N2O emissions (Yin et al. 2022). The large uncertainty in N2O emissions from agricultural soils is partly attributed to the temporal resolution of the
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available data sets (Lammirato et al. 2021). It was recommended to: (i) measure four times per day for maximum accuracy, (ii) measuring more than four times per day is not necessary, because the benefits are negligible, (iii) measure twice per day for a good compromise between accuracy and the number of plots that can be monitored, (iv) avoid measuring less than twice per day because the resulting annual cumulative N2O fluxes can be biased in an unpredictable and significant way, and (v) especially avoid measuring less than once per day because, in addition to being biased, the annual cumulative N2O flux estimates can be considerably uncertain (Lammirato et al. 2021). Some of the variance can also be explained by crop type and SOC (Maaz et al. 2021). However, the relationship between N2O flux and soil temperature may be variable, contrary to many previous observations (Wu et al. 2021). In addition to soil temperature, the diurnal variability of the soil N2O flux is affected by soil drainage property, soil water-filled pore space (WFPS) level and land use. In addition, other diurnal parameters such as photosynthetically active radiation (PAR) and root exudation should also be studied to improve the accuracy of soil N2O emission predictions (Wu et al. 2021). Globally, emissions from agricultural soils increased from 1.5 Tg N year−1 in the 1980s to 2.3 Tg N year−1 in 2007–2016 (Tian et al. 2020). In addition to nitrifier nitrification, nitrifier denitrification, and heterotrophic denitrification, N2O production in soil may also result from heterotrophic nitrification, dissimilatory nitrate reduction to ammonium, and chemical and other processes (Table 3.2; Chang et al. 2022; Baggs and Phillipot 2010). In contrast, increasing rates of dissimilatory NO3− reduction to NH4+ in soil are associated with lower N2O emission rates but this N cycle process is less well studied (Cheng et al. 2022). Nitrification is the sequential aerobic oxidation of NH3 to NO3− via nitrite (NO2−), with N2O as a by-product. Net nitrification is the balance between NO3− production and consumption processes. Soil gross nitrification, i.e., absolute amount of NO3− produced, occurs through microbial oxidation of NH3 or organic N (Elrys et al. 2021). Soil gross nitrification can occur as autotrophic or heterotrophic nitrification. Soil gross autotropic nitrification uses NH4+ as a substrate mainly by ammonia-oxidizing bacteria (AOB) and ammonia-oxidizing archaea (AOA). In contrast, soil gross heterotrophic nitrification is carried out by fungi and bacteria, and utilizes both organic N and NH4+ (Elrys et al. 2021). Denitrification reduces NO3− or NO2− to NO, N2O, and N2. Oxidation of NH3 to NO3− by AOB and AOA is responsible for global emissions of N2O directly (Prosser et al. 2020). AOB, in particular, produce more N2O in soils than AOA (Lu et al. 2020). Indirectly, N2O emissions occur by nitrification through provision of NO2− and, after further oxidation, NO3− to denitrifiers (Prosser et al. 2020). Denitrifiers are also considered major producers of N2O, but N2O is also emitted by organisms that oxidize NH3 to NO2−. AOA may be accountable for up to 70% of N2O production in soil (Wu et al. 2020). This direct contribution to N2O emissions is particularly important given the increases in N fertilizer applications. AOA are favored by low soil pH and, similar to AOB, by low rates of NH4+ supply equivalent to application of slow-release fertilizer, or potentially by high rates of NH4+ supply equivalent
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to addition of high concentrations of inorganic NH4+ or urea (Prosser et al. 2020; Wu et al. 2020). How soil properties affect the relative contribution of AOA to N2O production compared to that of AOB, and the importance of AOA overall is under discussion (Stein et al. 2021; Wu et al. 2020). Changes in soil C:N, soil total N, microbial population size, and/or soil pH may influence soil gross nitrification (Elrys et al. 2021). Nitrification is an aerobic process that depends on the availability of oxygen and NH3 (Firestone and Davidson 1989). In contrast, denitrification is an anaerobic process controlled by the availability of C, NO3− and the oxygen supply (Tiedje 1988). The terrestrial removal of N2O occurs in the last step of the denitrification process, i.e., the reduction of N2O to N2. The key enzyme responsible is nitrous oxide reductase (Nos)Z but understanding of the role of NosZ in controlling soil N2O emissions is incomplete (Shan et al. 2021). The reduction of N2O to N2 is mainly driven by soil pH and progressively inhibited when the pH is 10 million inhabitants), in particular, make the food chain and supply system, from field to tables, increasingly complex to manage. In 2018, there were 33 megacities and by 2030, the world is projected to have 43 megacities, most of them in developing regions (UN 2019). Aside food supply, megacities are important for addressing other global environmental challenges. For example, Kennedy et al. (2015) quantified the energy and material flows through the world’s 27 megacities in the year 2010. The flows amounted to 9% of global electricity, 10% of gasoline and 13% of solid waste. Many of the megacities are growing rapidly in population but are growing even faster in terms of energy use (Kennedy et al. 2015). There are interrelationships between urbanization and each aspect of food security, i.e., food availability, food access, food utilization and food stability (Szabo 2016). Aside the loss of cropland due to urban expansion, urbanization has other impacts on food security risks, and negative effects on both water and food security. Macro-level urban growth, in particular, has a significant effect in raising a country’s food insecurity risk. However, the future in relation to associations between urbanization and food security is uncertain. The global convergence patterns in fertility and urbanization, and also in economic and human development, provide arguments for an optimistic outlook in terms of sustainable urban development, and the fight against hunger and under-nutrition. The increased policy focus on the need for green growth and sustainable cities may also be associated with an improvement in urban food security. It will be critical to prioritize sustainable urbanization strategies, in particular in countries with the lowest levels of human development, to reduce the negative impacts of rapid urban growth on food security (Szabo 2016). Among the approaches to increase urban food security is producing food within urban areas by urban agriculture (UA). Practices may include allotments for self- consumption, large-scale commercial farms, community gardens, edible landscapes, animal husbandry, aquaculture, and arboriculture, and may occur at any scale from roof-top gardens to larger cultivated open spaces (Lorenz 2015). For example, aside for ornamental reasons, residential yards can also be used for food production, typically for direct consumption by the household or for sharing with neighbors and friends (Lovell 2010). Edible landscaping includes backyard vegetable gardens and the visible portion of the yard (i.e., the front yard). Edible fruiting trees, shrubs, and herbaceous plants can also be incorporated into the design of the
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edible residential landscape. Green roofs can also be used for growing edible plants and, thus, be part of the edible urban landscape (Lovell 2010). Reliable data on UA’s potential to provide food are scanty. Focusing on the urban poor specifically and on urban land availability, Badami and Ramankutty (2015) showed that in the high-income countries, UA is feasible – in terms of urban land availability to grow the basic daily vegetable intake for the urban poor. In contrast, in cities in low-income countries, UA has a low potential in terms of land availability in urban areas to achieve growing the daily vegetable intake for the urban poor. For example, as much as 10–20% of the urban area would be required in some low- income countries to grow the daily vegetable intake, but in some cases nearly all or even more than the total urban area. Thus, UA can only make a limited contribution to urban food security in low-income countries where it is, however, needed the most as the vast majority of the world’s urban poor live in those countries. On the positive side, UA contributes to improving food availability and access in low- income countries, and to food security and nutritional status of the urban households that engage in it (Badami and Ramankutty 2015). Martellozzo et al. (2014) performed a global analysis of the space constraint to meet urban vegetable demand by UA practices. Accordingly, one third of the global urban area would be required to satisfy the global vegetable consumption by urban dwellers. However, how much urban area may actually be suitable and available for UA was not considered in this analysis. Importantly, UA has only a limited potential to contribute to global cereal production as the global annual harvested area for cereals is about ten-times larger than the global urban area (Martellozzo et al. 2014). Whereas UA can make a valuable contribution to food security especially by producing vegetable and fruit crops, cities may always depend on a significant external non-urban area for food production (Ward et al. 2014). The benefits of UA are interconnected with those of OA. This includes building up natural resources through biological mechanism and recycling of wastes, keeping the nutrients cycle within the system, strengthening communities, and improving human capacity (Lorenz 2015). However, studies on organic UA often neglect natural and soil science, although management of urban soils is a prerequisite for maintaining or improving soil fertility and health. Thus, effects of specific organic UA practices on soil properties and their impacts on climate change adaptation and mitigation are poorly known (Lorenz 2015). Similar to non-urban agriculture, more sustainable and climate-resilient agricultural practices should be developed for site- specific implementation in areas managed by UA rather than adhesion to fixed sets of principles (Chap. 5). New forms of agriculture have been introduced in urban areas. This includes rooftop farming free from urban surface soil exploitation, and vertical indoor farming using hydroponics. Commercial urban rooftop farming, in particular, is increasing in popularity (Buehler and Junge 2016). It is a practice that is well-suited to enhancing food security in cities, and for reducing the environmental impact that results from long transportation distances. Two main types of commercial urban rooftop farming can be differentiated: (i) hydroponic systems in greenhouses where mostly leafy greens, tomatoes (Solanum lycopersicum L.), and herbs are grown, and
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(ii) soil-based open-air farms that grow a large variety of vegetables. Hydroponics is frequently seen as the key technology for commercial urban food production but in most countries it is not eligible for OA certification as some nutrients are mined and, therefore, not renewable. Nevertheless, hydroponic farms often make efforts to implement environmentally friendly technologies and methods. In contrast, some soil-based rooftop farms follow OA principles (Appolloni et al. 2020). To enhance urban food security, there may be an untapped potential to systemically integrate farms into buildings (Buehler and Junge 2016). Greenhouse technologies are well-established and guarantee a safer, more reliable food supply that can be produced year-round, and they can be located in buildings in urban areas (Despommier 2011). By “stacking” these greenhouses on top of each other in an integrated well-engineered fashion, the environmental footprint can be greatly reduced, and the vertical farm concept can be applied to every urban center, regardless of its location. Thus, the vertical farm industry did grow rapidly since 2010, and vertical farming is projected by some to become a common feature of the built urban environment on a global scale within the next 10–20 years (Despommier 2020). Hydroponics, aeroponics where roots are exposed to air, and aquaponics, which incorporates fish production integrated into the hydroponic growing scheme, are among the vertical UA farm technologies. Among the challenges of vertical farming is indoor lighting for growing crops in the controlled environment, and its associated energy budget. Finding qualified people to run the farms, crop selection and the politics of UA are among the additional challenges for vertical farms. However, profitability will determine the long-term fate of vertical farms in urban areas (Despommier 2020). To sum up, large and increasing amounts of food are consumed in expanding and more populous urban areas. Some of the vegetables and fruits but not cereals may be produced with urban areas by UA practices, and meet the demand of the urban population. This may reduce the climate impact of the food system by reducing processing, storage and transport related GHG emissions, and reducing the need for creating agricultural land outside of urban areas by deforestation. Soilless practices of production and vertical farming can also be part of UA practices. Whether a combination of OA practices with those of UA practices can reduce the climate impact of the food system needs to be assessed in relation to non-OA site-specific management practices.
6.3 Future Research and Developments Reducing GHG emissions from agriculture, forestry, and land use (i.e., from enteric fermentation in livestock and manure, agricultural soils, crop burning, deforestation, cropland degradation, and rice cultivation) is essential to address the goals of the Paris Agreement (De Fries et al. 2022), aside reducing emissions associated with fossil fuel combustion. At the same time, more food must be produced for an increasing and more urbanized population. Aside OA, many types of more
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sustainable agricultural practices than the so-called conventional agriculture are discussed as solutions for the land. This includes agroecology, CA, sustainable intensification, ecological intensification (nature-based management), eco-functional intensification, and RA, with some of them discussed in Chap. 5. Among the major challenges of any agricultural production is Earth’s diminishing potential for resource production, due to a range of reasons, leading to resource scarcity, especially in the case of depletable resources such as phosphorus (P; Breure et al. 2018). This may be addressed by a circular economy system which focuses on maximizing the reuse of resources and products, and minimizing their depreciation. The circular economy greatly influences, and depends on, soil and land management. Management issues that need to be addressed for provisioning of food in a circular economy include the reduction of use of fertilizers/pesticides/energy, and closing mineral cycles (Breure et al. 2018). Site-specific agricultural practices need to be designed for concise management of the resources land and soil to make a circular economy successful. Enhancing the adoption of more sustainable and climate-resilient agricultural practices comes at a cost for farmers, ranchers and landowners. To reward them, multiple approaches can economically incentivize reduced GHG emissions and carbon (C) sequestration from land management, including fines for violating regulations, subsidies and tax credits, capped emission in cap-and-trade programs, and payments (DeFries et al. 2022). All of the approaches can play a role in a transition to low-GHG land management for provisioning of food, feed, fuel and fiber. The current net-zero commitments and strong growth in the voluntary carbon market may offer an unprecedented opportunity to bring finance to the land sector for mitigating climate change. However, there is low confidence in carbon market credits, including difficulties with assurances of additionality (i.e., whether interventions to reduce emissions or store C would occur in the absence of revenue from the carbon market), permanence (i.e., the integrity of how reversed benefits of avoided or stored emissions are addressed), leakage (i.e., whether reductions in one place are displaced by emissions to another place), and quantification (i.e., whether reductions are accurately quantified relative to an appropriate baseline and reported). Specifically, the reversibility of SOC sinks has been a point for discussion in the context of carbon markets with their attempt to offset fossil fuel emissions. Leifeld and Keel (2022) simulated, however, that not only permanent but also reversible soil C sinks provide a climate benefit. This benefit is thought to be proportional to the average SOC balance (Leifeld and Keel 2022). Rather than adhering to perceived more sustainable and climate-positive agricultural practices, an increased focus on enteric fermentation in livestock, irrigation management, and other agricultural practices is needed for reducing emissions of multiple GHGs. For example, enteric fermentation emits almost as much carbon dioxide equivalents (CO2eq; 100-year time frame) globally as does forest conversion. Further, non-CO2 GHG emissions must also be reduced as, for example, land use–related CH4 and N2O emissions cause more than half of the climate impacts from the land sector (DeFries et al. 2022).
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Instead of adhering to a strict principle such as agroecology, RA or OA, carbon farming or using land for C removal may be the guiding principle for climate change adaptation and mitigation by soil-based agricultural production while at the same time enhancing food security. Carbon farming refers to the management of C pools, flows and GHG fluxes at the farm level, with the purpose of mitigating climate change (COWI, Ecologic Institute and IEEP 2021). It involves the management of both land and livestock, all pools of C in soils, material and vegetation plus fluxes of CO2, CH4 and N2O. Carbon farming includes C removal from the atmosphere, avoided GHG emissions and emission reductions from ongoing agricultural practices (COWI, Ecologic Institute and IEEP 2021). Increases in SOC stocks following the implementation of carbon farming practices results in more healthy and productive soils, and, thus, higher crop yields (Oldfield et al. 2019; Lal 2016). Soil organic matter (SOM) which consists of 50% organic C (Pribyl 2010), is among the most important factors in explaining cereal yield variations, and high-quality soils high in SOM may better moderate the impact of rainfall variability on soil moisture and crop growth (Qiao et al. 2022). Carbon farming may also include designing crops with the attributes: (i) increased belowground C allocation for larger and deeper root biomass; (ii) interactions with a tailored, synthetic soil microbiome for increased rhizosphere sink strength and enhanced plant growth-promoting properties that facilitate nutrient acquisition and water-use efficiency; and (iii) increased source strength for enhanced photosynthesis and biomass accumulation (Jansson et al. 2021). Thus, carbon farming may contribute to more healthy, productive and climate-resilient soils while also contributing to a more circular agricultural production system. Transforming an existing food system into a more sustainable and climate- resilient system combined with enhancement in food production incurs costs. Some of the financial burden may be covered by price premiums on more sustainable and climate-resilient commodities. Importantly, land managers must be rewarded for the numerous environmental and societal benefits associated with the implementation of those practices. For example, payments for ecosystem services can incentivize the transition to more sustainable and climate-resilient agriculture and food systems (Northrup et al. 2021). Another financial incentive may be rewarding land managers for the value of SOC maintenance or accrual based on the avoided social cost of carbon internalizing the long-term environmental and health damage resulting from GHG emissions (Mikhailova et al. 2019). Recent global estimates for the social cost of carbon ranged between USD 80 and USD 300 per Mg CO2 (Pindyck 2019). As of 2019, however, existing carbon pricing schemes only covered about 20% of global emissions, and more than two-thirds of these have prices below USD 20 per Mg of CO2eq (Rosenbloom et al. 2020). This pricing is far too low to be effective, and increasing coverage and prices present also serious challenges. The costs of carbon credits remain low, and this represents the primary reason for the limited engagement of farmers and ranchers in carbon markets. Aside carbon pricing, effective policy responses in the soil-land-climate interface of agriculture and food systems should include emissions trading schemes (including net CO2 emissions), carbon taxes, regulations limiting GHG emissions,
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incentives for ecosystem services and secure tenure, protecting the environment, microfinance, crop and livelihood insurance, agriculture extension services, agricultural production subsidies, low export tax and import tariff rates on agricultural goods, dietary awareness campaigns, taxes on and regulations to reduce food waste, improved shelf life, sugar/fat taxes, and instruments supporting sustainable land management (including payment for ecosystem services, land-use zoning, standards and certification for sustainable biomass production practices, legal reforms on land ownership and access, legal aid, and legal education), as well as reframing these policies as entitlements for women and small agricultural producers (Rogelj et al. 2018). This may also include border carbon adjustments to prevent emissions leakage (Peters et al. 2011). Pressured by consumers and stakeholders, the private sector involved in agriculture and food production is increasingly looking into practices to reduce the GHG footprint along the supply chain. Whether this will result in sustained incentivization of more sustainable and climate-resilient modes of production is not known as the major goal of the private sector is staying profitable rather than enhancing human well-being by climate change adaptation and mitigation (Bigger and Millington 2020). Similarly, sustainable and climate-resilient policies may come and go with the election cycles, and incentivization and support of climate-resilient food systems may be rescinded after an election. In the end, farmers, growers, ranchers and other landowners are stewards of the land and decide which site- specific agriculture and food production system is implemented. Thus, it is essential that science-based knowledge on more sustainable and climate-resilient agricultural practices is communicated to the agricultural community as they will implement them. This points towards the importance of agricultural extension service as the facilitator of knowledge transfer into action. Land managers are often suspicious of external advice, particularly, when it is perceived as additional regulation. Co-creation of knowledge on site-specific more sustainable and climate-resilient practices with researchers, extension personnel, commodity groups, private sector, the public, land managers and others may be a way forward to guarantee their long- term success. The science community must be able to give credible scientific advice to land managers on soil and land-use management practices contributing to more sustainable and climate-resilient agriculture and food systems. Adhering to a fixed set of principles is not the way forward in the selection of practices when, for example, some non-OA practices are superior for climate change adaptation and mitigation than practices following OA certification standards. A major issue is that side-by- side comparisons of experimental fields managed by concepts and principles such as OA, agroecology, CA, sustainable intensification, ecological intensification, eco- functional intensification, and RA practices study not all but only a subset of them. Thus, there is the need to establish new experiments in all major agricultural regions to compare the sustainability, climate impact and climate resilience of a range of practices under well-managed conditions. This must be accompanied by research on a similar range of practices on working lands as farmers, rangers and land managers adjust soil and land-use management practices based on the complexity of
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crop, livestock, and forage systems. Importantly, long-term studies are needed as effects on the climate and the environment may only be detectable several years after implementation of specific management practices. Required is also an assessment of the climate footprint of the entire supply chain. Fluxes of all GHGs at the field scale and those associated with soil and land-use management inputs and the entire supply chain, and biogeophysical and biogeochemical effects need to be considered to identify more sustainable, climate-friendly and climate-resilient agriculture and food systems. The urgency of the climate crisis demands effective interventions to reduce, avoid, and remove GHG emissions in all sectors (DeFries et al. 2022). Low-GHG agricultural land management and food systems are not a panacea as long as fossil fuel emissions continue to increase.
6.4 Conclusions The climate crisis demands reduction, avoidance and removal of GHG emissions in all sectors including agriculture and food systems. At the same time, the demands of a growing and more urban population for food, feed, fiber and fuel have to be met. Some food may be produced by UA practices including indoor hydroponic and rooftop farming systems also sometimes combined with OA practices but urban areas continue to depend on non-urban areas for food supply. Agriculture and food systems can be managed more climate-friendly with a lower GHG footprint when site-specific practices are developed and implemented by co-creation of knowledge involving a diverse community of stakeholders. The more sustainable, climate- friendly and -resilient practices incur additional costs for land managers, and society must reward them for the ecosystem services. The evolving voluntary carbon market may be a way forward to reduce the financial burden for implementation of practices with lower GHG footprint such as those associated with carbon farming.
6.5 Review Questions 1. What are the challenges to satisfy the food demands of the increasing and more urbanized global population? 2. How can megacities be managed more sustainably? 3. What role does urban sprawl, local production, OA and UA may play for agriculture and food systems with lower GHG footprint? 4. How can demand side changes such as those in diet and reduction in food loss and waste contribute to more sustainable and climate-positive agriculture and food systems and how can those changes be implemented? 5. Contrast and compare incentives to financially reward land managers for implementing more sustainable, and climate-friendly and -resilient soil and land-use management practices.
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6. Describe an approach for effective knowledge transfer from science into action to support the implementation of site-specific practices to make agriculture and food systems part of the solution of the climate crisis.
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