Management of Boreal Forests: Theories and Applications for Ecosystem Services 3030880230, 9783030880231

Citation preview

Seppo Kellomäki

Management of Boreal Forests Theories and Applications for Ecosystem Services

Management of Boreal Forests

Seppo Kellomäki

Management of Boreal Forests Theories and Applications for Ecosystem Services

Seppo Kellomäki School of Forest Sciences University of Eastern Finland Joensuu, Finland

ISBN 978-3-030-88023-1    ISBN 978-3-030-88024-8 (eBook) https://doi.org/10.1007/978-3-030-88024-8 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Preface

Forestry refers to the production of forest-based goods and services, which represents the direct and indirect use of the materials and resources in the forests and forest ecosystems for manufacturing different goods and services. Forests further provide the environment for relaxation and recreation opportunities. Forestry operates locally, but its impacts extend to the global scale through the trade in wood-based products and through impacts on global ecological systems as sequestrating atmospheric carbon and affecting climate. In the context of forest ecosystem, the services are widely divided into supporting, provisioning, regulating, and cultural services. Supporting services represent the basic structure and functioning of forest ecosystems, i.e., the interaction between genotypes and environment produces provisioning, regulating, and cultural services. Provisioning services include such concrete services as timber and groundwater, while regulating services represent the reduction of wind force and retention of carbon in the forest ecosystem. Cultural services involve amenity values and recreation opportunities. Thus, forests have ecological, social, economic, and cultural functions, which are the main dimensions of sustainable forestry. This aims at providing future generations with the same goods and services from forest ecosystems and forests as the current generation has access to. This book is based on scientific research and practical experiences on how boreal forests grow and develop over time. The focus is on managed forests, but the discussion is further extended to cover forests growing in natural conditions. The biogeographic focus of the book is on northern Europe with close links to circumpolar boreal forest zone. In northern Europe, forest sciences date back more than 200 years. The main thematic focus has changed over time related to the changes in harvest and management of forests. These questions have close links to the structure and function of forest ecosystem. Climate change with impacts on growth and development of forests is currently one of the main issues in terrestrial ecology on the global and local scales. Many research problems in forestry have further the links to the local variability in environmental management and societal needs. Research findings from the early 1900s to the present are utilized in preparing this book. Many research findings from early days are still valid, such as regeneration biology of main forest tree species, with important contribution to developing proper management methods for forestry. In many cases, these findings have contributed for building forest ecosystem models, which have been used in writing this book. The models facilitate to integrate v

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e­xperimental findings for outlining the future growth and development of forests in changing environment and societies. Regarding climate change, model-based analyses provide possibilities to understand how to avoid the risks and utilize the opportunities in forestry on the global and local scales. In this respect, the research since early 1990s and thereafter is especially valuable, when addressing the proper management for mitigating the climate change and consequent impacts on the future growth and development of forests. Sustainable forestry has been a main principle in forestry since the early 1950s, but still being a challenge. Sustainable forestry refers to the use of forests and forest land to maintain the biodiversity, productivity, and regeneration capacity of forest ecosystems to meet the ecological, economic, and social functions of forests without damaging other ecosystems. In integrated forest production, a main problem is that some forest-based goods and services have a market value as timber has, whereas the remainder have no market value or a value that is difficult to define, such as that of scenic beauty. The incompatibility between different goods and services often remains unresolved, creating problems and conflicts in the management of forest resources for different purposes. The concepts of multipurpose forestry, multiple use of forests, and multifunctional forestry emphasize the need to integrate different management objects in a balanced way to satisfy varying needs in a sustainable manner. The sustainable production of goods and services in forestry is based on the management of the structure of forest ecosystems to make them function as desired. Management of the genetic properties of tree populations, changing the properties of habitats occupied by populations, or both can maintain or increase production. Ultimately, management aims to modify the interactions between genetic and environmental factors, to optimize the needs to conserve the functioning and structure of forest ecosystems, and to satisfy production needs. The performance of forest ecosystems is directed toward producing ecosystem structures that are needed in producing the specified goods and services aimed in management. In this book, the main focus is on the boreal forests mainly occupied by Scots pine (Pinus sylvestris), Norway spruce (Picea abies), and pendula (Betula pendula) birch and pubescent (Betula pubescent) birch. These few species comprise to a large extent the forest resources in northern Europe, where management produces various ecosystem services. In this region, climatic warming is expected to be pronounced. The productivity of these forests is likely to increase, but the risks of abiotic and biotic damages also increase. Regular management and harvest of timber and biomass provides opportunities to adapt and to redirect the growth and development of forests to meet in a proper way the gradual change in climate. In this respect, the structure and functioning of ecosystems are the main factors, through which climatic warming influences ecosystem dynamics and capacity to produce different ecosystem services. Experimental research findings are combined with model simulations for outlining how management ought to be acclimated to the long-term dynamics of forest ecosystem and concurrent changes induced by the climate change. This approach emphasizes such features of

Preface

Preface

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forest succession that are likely to increase the probability of having the necessary target structure and functioning for producing different ecosystem services. This book consists of 20 chapter, including the introduction, which are written in 5 parts. Introduction (Chap. 1) outlines the topics and areas described in the book and outlines forest management aimed at adapting to, and mitigating, climate change in the forestry context. In Part I, the boreal forest environment (Chap. 2) is addressed with a focus on climatic and edaphic conditions and likely impacts of climatic change on future properties of boreal upland sites. Part II further deals with the properties (Chap. 3) and structure (Chap. 4) of tree species, with the main commercial value in northern Europe. This part further addresses the regeneration (Chap. 5) and growth biology (Chap. 6) of the selected tree species. These chapters provide background for Part III, which addresses the successional dynamics of the forest ecosystem (Chap. 7), with a focus on the long-term interaction between environment and trees controlled by the regeneration, growth, and mortality of trees. This analysis provides the background for different management regimes and operations being used in management (Chap. 8). Part IV addresses different management strategies, regimes, and measures mainly used in even-aged management but some applicable in uneven-aged management. Management regimes and measures deal with regeneration (Chaps. 9, 10, and 11), management of tree stands in the seedling (Chap. 12) and commercial thinning phases (Chap. 13), and further with fertilization (Chap. 14) and pruning (Chap. 15). In Part V, management practices are further discussed in Chaps. 16 and 17. In the context of management for different ecosystem services, the discussion deals with even-aged and uneven-aged management using rule-based and optimized approaches. Part V further includes the risks of forest production (Chap. 18) related to abiotic and biotic hazards under the current and changing climate. This discussion is further expanded in Chap. 19, which addresses the production of ecosystem services and management under climate change. Chapter 20 finally outlines how to modify management to meet in a sustainable way the changes in the ecosystem dynamics likely to occur under warming. I acknowledge the support by Heli Peltola, Harri Strandman, Hannu Väisänen, and Sara Kirsikka-aho for compiling this book. I further acknowledge the School of Forest Sciences, University of Eastern Finland, for the facilities provided for this book project, which have allowed my dream to be realized. Joensuu, Finland 31.3.2021

Seppo Kellomäki

Contents

1 Background: Management of Forest for Varying Ecosystem Services����������������������������������������������������������������������������������������������   1 1.1 Forests for Human Well-Being ������������������������������������������������   1 1.1.1 Global Forest Cover������������������������������������������������������   1 1.1.2 Boreal Forests ��������������������������������������������������������������   2 1.1.3 Forest Ecosystem, Ecosystem Services, and Management����������������������������������������������������������   3 1.2 Management of Forest for Goods and Services in Ecological Context����������������������������������������������������������������   4 1.2.1 Environment/Genotype Interaction and Management����������������������������������������������������������   4 1.2.2 Forest Structure and Management��������������������������������   6 1.2.3 Control of Ecosystem Structure and Functioning in Management�������������������������������������������������������������   6 1.3 Management Strategies, Regimes, and Operations������������������   7 1.4 Scope of the Book��������������������������������������������������������������������   8 References������������������������������������������������������������������������������������������   8 Part I Forest Environment of Boreal North and Forestry 2 Environmental Conditions, Site Types, and Climate Change������  13 2.1 Forest Site, Productivity, and Climate Change ������������������������  14 2.2 Climatic Conditions������������������������������������������������������������������  15 2.2.1 Climate in Varying Scale����������������������������������������������  15 2.2.2 Radiation in Global Context ����������������������������������������  16 2.2.3 Total Radiation and Radiation Balance������������������������  19 2.2.4 Radiation Balance on Ground Surface��������������������������  19 2.2.5 Thermal Conditions������������������������������������������������������  22 2.2.6 Precipitation, Humidity, and Evaporation��������������������  22 2.2.7 Wind������������������������������������������������������������������������������  26 2.2.8 Atmospheric Carbon Dioxide ��������������������������������������  27 2.3 Interaction Between Climate and Forest Structure ������������������  30 2.3.1 Climatic Conditions and Forest Canopy ����������������������  30 2.3.2 Radiation in Forest Canopy and Tree Crown, Interception of Radiation����������������������������������������������  30 2.3.3 Evaporation of Water in Forest Canopy������������������������  34 2.3.4 Wind in Forest Canopy ������������������������������������������������  35 ix

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2.3.5 Interaction of Microclimatic Factors in Forest Canopy: Temperature of Foliage����������������������������������  36 2.4 Edaphic Conditions������������������������������������������������������������������  37 2.4.1 Bedrock and Soils ��������������������������������������������������������  37 2.4.2 Water in Soil ����������������������������������������������������������������  38 2.4.3 Soil Temperature ����������������������������������������������������������  42 2.4.4 Nutrients������������������������������������������������������������������������  42 2.4.5 Site Types in Identifying Site Fertility��������������������������  43 2.4.6 Site Index in Identifying Site Fertility��������������������������  47 2.5 Changes in Climatic and Edaphic Conditions Under Global Warming������������������������������������������������������������������������  48 2.5.1 Global Climate Change������������������������������������������������  48 2.5.2 Past Climate Change and Changes Until Now��������������  49 2.5.3 Future Climate Change: SRES Scenarios for Temperature and Precipitation��������������������������������������  51 2.5.4 Future Climate Change: RCP Scenarios for Temperature and Precipitation��������������������������������������  52 2.5.5 Climate Variability and Weather Extremes ������������������  52 2.5.6 Drought Episodes Under SRES and RCP Scenarios ����������������������������������������������������������������������  54 2.5.7 Snow Cover������������������������������������������������������������������  58 2.6 Concluding Remarks����������������������������������������������������������������  59 References������������������������������������������������������������������������������������������  60 Part II Structure and Functioning of Selected Boreal Trees 3 Selected Tree Species of Importance in Boreal North������������������  65 3.1 Outline Taxonomy and Treelike Structure��������������������������������  66 3.1.1 Development of Treelike Structure ������������������������������  66 3.1.2 Meristematic Growth and Differentiation��������������������  68 3.1.3 Life Cycle of Trees Under Varying Environmental Conditions��������������������������������������������������������������������  70 3.2 Selected Tree Species of Importance in Forestry in Northern Europe ������������������������������������������������������������������  71 3.2.1 Main Coniferous and Deciduous Tree Species ������������  71 3.2.2 Scots Pine����������������������������������������������������������������������  72 3.2.3 Norway Spruce��������������������������������������������������������������  74 3.2.4 Pendula and Pubescent Birches������������������������������������  77 3.2.5 Black and Grey Alders��������������������������������������������������  79 3.2.6 Aspen����������������������������������������������������������������������������  80 3.2.7 Tree Species Composition and Productivity Across Boreal Zone in Finland ������������������������������������  81 3.3 Concluding Remarks����������������������������������������������������������������  81 References������������������������������������������������������������������������������������������  82 4 Structure of Selected Tree Species��������������������������������������������������  85 4.1 Structure and Properties of Stem����������������������������������������������  86 4.1.1 Outline Structure of Stem ��������������������������������������������  86

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4.1.2 Wood ��������������������������������������������������������������������������   86 4.1.3 Bark����������������������������������������������������������������������������   92 4.2 Structure and Properties of Crown������������������������������������������   93 4.2.1 Branches and Shoots ��������������������������������������������������   93 4.2.2 Leaves and Needles����������������������������������������������������   95 4.3 Structure and Properties of Roots ������������������������������������������   98 4.3.1 Coarse and Fine Roots������������������������������������������������   98 4.3.2 Mycorrhizae, Root Grafts, and Nodules ��������������������  100 4.4 Structure of Whole Tree����������������������������������������������������������  101 4.4.1 Growth and Development of Tree Structure Over Time ������������������������������������������������������������������  101 4.4.2 Allometry Between Tree Organs��������������������������������  103 4.4.3 Allometry and Distribution of Growth in Different Parts of Stem in Relation to Crown������������  105 4.5 Concluding Remarks��������������������������������������������������������������  107 References����������������������������������������������������������������������������������������  108 5 Regeneration Biology of Selected Tree Species ��������������������������  111 5.1 Reproductive Cycle of Selected Boreal Trees������������������������  112 5.2 Flowering and Seed Crop��������������������������������������������������������  113 5.2.1 Outline of Reproductive in Coniferous and Deciduous Trees����������������������������������������������������������  113 5.2.2 Pollination, Fertilization, and Formation of Seeds����������������������������������������������������������������������  115 5.2.3 Development of Embryo and Structure of Seeds����������������������������������������������������������������������  115 5.2.4 Cycling of Flowering and Variability of Seed Crop����������������������������������������������������������������������������  121 5.2.5 Capacity of Trees to Produce Seeds����������������������������  123 5.3 Seeding������������������������������������������������������������������������������������  125 5.3.1 Dispersal of Seeds������������������������������������������������������  125 5.3.2 Storing of Seeds in Site����������������������������������������������  128 5.4 Germination of Seeds and Development of Seedlings������������  128 5.4.1 Establishment and Initial Growth of Seedlings����������  128 5.4.2 Growth and Development of Seedling Population ������������������������������������������������������������������  133 5.5 Vegetative Regeneration����������������������������������������������������������  135 5.6 Concluding Remarks��������������������������������������������������������������  135 References����������������������������������������������������������������������������������������  135 6 Physiology, Growth, and Acclimatizing of Boreal Tree Species to Climate��������������������������������������������������������������������������  139 6.1 Growth with Links to Physiology of Trees ����������������������������  140 6.1.1 Interaction Between Metabolism of Tree and Environment ��������������������������������������������������������  140 6.1.2 Photosynthesis, Respiration, and Growth ������������������  142 6.2 Photosynthesis������������������������������������������������������������������������  143 6.2.1 Diffusion of Carbon Dioxide into Leaves/Needles ����������������������������������������������������������  143

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6.2.2 Photosynthetic Reactions in Assimilation������������������  146 6.2.3 Modelling Photosynthesis Based on Biochemical Processes ��������������������������������������������������������������������  148 6.2.4 Carbon Uptake in Response to Seasonality of Temperature����������������������������������������������������������������  150 6.2.5 Total Canopy Photosynthesis��������������������������������������  156 6.3 Respiration and Biomass Growth ������������������������������������������  158 6.3.1 Growth and Maintenance Respiration������������������������  158 6.3.2 Use of Photosynthates in Biomass Growth����������������  162 6.3.3 Photosynthates Used for Secondary Compounds in Defence ������������������������������������������������������������������  163 6.4 Uptake of Water and Nutrients������������������������������������������������  165 6.4.1 Water Uptake��������������������������������������������������������������  165 6.4.2 Nutrient Uptake����������������������������������������������������������  169 6.4.3 Translocation of Photosynthates in Whole Tree ��������  171 6.5 Growth and Growth Dynamics ����������������������������������������������  173 6.5.1 Primary and Secondary Growth����������������������������������  173 6.5.2 Height Growth������������������������������������������������������������  174 6.5.3 Diameter Growth��������������������������������������������������������  176 6.5.4 Growth of Stem, Branches, and Foliage Related to Environmental Conditions��������������������������������������  180 6.5.5 Wood Formation as Affected by Prevailing Environmental Conditions������������������������������������������  181 6.5.6 Growth of Roots����������������������������������������������������������  183 6.5.7 Allocation of Growth Among Different Tree Organs ������������������������������������������������������������������������  185 6.5.8 Distribution of Growth in Different Stem Parts����������  187 6.6 Annual Cycle of Functioning of Boreal Trees������������������������  189 6.6.1 Active and Dormant Periods over a Year��������������������  189 6.6.2 Phenology, Frost Resistance, and Frost Damages������  192 6.7 Adaptation of Trees to Prevailing Climatic Conditions����������  195 6.8 Mortality and Lifespan of Trees����������������������������������������������  196 6.8.1 Litter of Non-woody Organs��������������������������������������  196 6.8.2 Litter of Woody Organs����������������������������������������������  199 6.8.3 Mortality of Trees ������������������������������������������������������  200 6.9 Interaction Between Genotype and Environment in Modelling Context��������������������������������������������������������������  202 6.9.1 Functioning of Trees in Ecosystem Context, with Management Implications������������������������������������������  202 6.9.2 Modelling of Ecosystem Dynamics in Ecophysiological Context ������������������������������������������  204 6.9.3 Management and Main Model Input and Output��������  205 6.9.4 Model Performance����������������������������������������������������  207 6.10 Concluding Remarks��������������������������������������������������������������  208 References����������������������������������������������������������������������������������������  210

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Part III Long-Term Dynamics of Boreal Forest Ecosystem 7 Successional Dynamics of Boreal Forest Ecosystem ������������������  219 7.1 Succession of Forest Ecosystem Over Time ��������������������������  220 7.1.1 Succession in Forest Context��������������������������������������  220 7.1.2 Autogenic and Allogenic Disturbances Driving Succession������������������������������������������������������������������  221 7.1.3 Gaps Related to Properties of Disturbances���������������  223 7.1.4 Gap Dynamics from Tree Through Patch to Landscape ��������������������������������������������������������������  223 7.2 Processes in Succession����������������������������������������������������������  225 7.2.1 Interaction Between Trees in Forest Community ������  225 7.2.2 Niche Differentiation in Succession ��������������������������  225 7.2.3 Energetics, Mass, and Nutrients in Succession����������  226 7.3 Gap Dynamics, with Effects on Environmental Conditions ������������������������������������������������������������������������������  228 7.3.1 Environmental Conditions in Relation of Area of Gaps������������������������������������������������������������������������  228 7.3.2 Radiation and Temperature in Gaps����������������������������  229 7.3.3 Hydrological Conditions in Gaps�������������������������������  233 7.3.4 Soil Disturbance and Nutrients in Gaps����������������������  234 7.3.5 Carbon Dioxide, Energy, and Water Fluxes in Gaps, with Atmospheric Interaction ����������������������  237 7.4 Structural Dynamics of Boreal Forest Over Time������������������  238 7.4.1 Regenerative Properties of Selected Tree Species������  238 7.4.2 Growth Properties of Selected Tree Species���������������� 238 7.4.3 Successional Properties of Selected Trees in Relation to Gap Dynamics������������������������������������������  240 7.4.4 Gap Dynamics and Composition of Tree Communities��������������������������������������������������������������  242 7.4.5 Composition of Ground Vegetation in Relation to Gap Dynamics��������������������������������������������������������  248 7.5 Dynamics of Organic Matter in Boreal Forest Ecosystem Over Time ������������������������������������������������������������  251 7.5.1 Mass and Ecosystem Energetics ��������������������������������  251 7.5.2 Growth and Development of Trees ����������������������������  252 7.5.3 Growth and Development of Ground Vegetation��������  257 7.5.4 Nutrients Bound in Trees and Ground Vegetation������  259 7.5.5 Litter from Trees and Ground Vegetation ������������������  261 7.5.6 Nutrient Cycle and Litter Fall ������������������������������������  264 7.5.7 Decay and Accumulation of Organic Matter in Soil��������������������������������������������������������������������������  266 7.5.8 Nutrients, Mineralization, and Biogeochemical Nutrient Flow��������������������������������������������������������������  269 7.6 Ecosystem Dynamics in Varying Temporal and Spatial Scales��������������������������������������������������������������������������������������  272 7.6.1 Functioning and Structure of Forest Ecosystem ��������  272

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7.6.2 Diversity of Habitats for Autotropic and Heterotrophic Species ��������������������������������������������  273 7.7 Concluding Remarks������������������������������������������������������������  275 References����������������������������������������������������������������������������������������  275 8 Management vs Ecosystem Dynamics������������������������������������������  279 8.1 Ecosystem Structure, Functioning, and Management Related to Gap Dynamics ����������������������������������������������������  280 8.1.1 Disturbance Dynamics on Varying Scale, with Management Implications��������������������������������������  280 8.1.2 Management in Controlling Genotype/Environment Interaction ������������������������  282 8.2 Management Strategies and Operations��������������������������������  284 8.3 Concluding Remarks������������������������������������������������������������  286 References����������������������������������������������������������������������������������������  287 Part IV Management Strategies, Regimes, and Operations 9 Preparation of Site for Natural Regeneration and Planting in Reforestation��������������������������������������������������������������  291 9.1 Preparatory Operations in Management: Concepts and Methods��������������������������������������������������������������������������  292 9.2 Preparatory Management Subjected to Vegetation ��������������  292 9.2.1 Removal of Trees with No Value or Preference for Future Management������������������������������������������  292 9.2.2 Protecting Tree Cover for Reducing Frost Damages������������������������������������������������������������������  294 9.3 Preparatory Management Subjected to Soil��������������������������  295 9.3.1 Soil Management����������������������������������������������������  295 9.3.2 Prescribed Burning��������������������������������������������������  296 9.3.3 Mechanical Soil Preparation ����������������������������������  298 9.4 Ditching Mire Ecosystem for Forestry ��������������������������������  300 9.5 Concluding Remarks������������������������������������������������������������  301 References����������������������������������������������������������������������������������������  301 10 Natural Regeneration in Management for Regrowth����������������  303 10.1 Procedures of Natural Regeneration ������������������������������������  304 10.1.1 Factors Affecting Structure and Properties of Seedling Populations������������������������������������������  304 10.1.2 Natural Regeneration in Ecological Context����������  304 10.2 Quantity and Quality of Seed Crop and Establishment of Seedlings��������������������������������������������������������������������������  307 10.2.1 Seed Crop Related to Climatic Conditions ������������  307 10.2.2 Seed Crop Related to Properties of Parent Trees����  308 10.2.3 Flowering and Number of Seedlings����������������������  308 10.2.4 Properties of Seeds and Emerging Seedlings����������  309 10.2.5 Uneaten Seeds and Effects of Seedbed ������������������  310

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10.2.6 Germination and Viability of Seeds������������������������  310 10.2.7 Survival and Growth of Seedlings��������������������������  311 10.3 Simulation Examples of the Establishment of Natural Seedling Stand����������������������������������������������������������������������  313 10.4 Natural Regeneration in Management����������������������������������  315 10.4.1 Techniques and Applications����������������������������������  315 10.4.2 Shelterwood Method ����������������������������������������������  316 10.4.3 Seed Tree Method ��������������������������������������������������  318 10.4.4 Regeneration Using Strip Cutting and Seeding from Surrounding Tree Stands��������������������������������  319 10.4.5 Growth of Natural Seedlings in Canopy Gaps Below Dominating Norway Spruces����������������������  320 10.5 Regeneration Success in Management Using Natural Seeding����������������������������������������������������������������������������������  321 10.5.1 Assessing the Success of Natural Regeneration������  321 10.5.2 Time Needed for Natural Regeneration������������������  323 10.5.3 Understory Seedlings and Ingrowth in Regeneration ������������������������������������������������������  324 10.6 Concluding Remarks������������������������������������������������������������  325 References����������������������������������������������������������������������������������������  325 11 Planting in Management for Regrowth����������������������������������������� 327 11.1 Environmental Conditions in Reforestation Area ������������������ 328 11.1.1 Interaction Between Seedlings and Environment in Forest Plantation �������������������������������������������������� 328 11.1.2 Radiation in Reforestation Area�������������������������������� 329 11.1.3 Thermal Conditions in Reforestation Area �������������� 331 11.1.4 Wind, Soil Moisture, and Nutrients in Reforestation Area������������������������������������������������ 332 11.1.5 Performance of Ground Vegetation After Clear Cutting���������������������������������������������������������������������� 334 11.2 Success of Planting in Regeneration Related to Site Properties�������������������������������������������������������������������������������� 336 11.3 Choice of Tree Species of Various Genotypes for Planting/Seeding �������������������������������������������������������������������� 337 11.3.1 Tree Species Choice for Regrowth���������������������������� 337 11.3.2 Provenance Choice for Regrowth������������������������������ 337 11.4 Tree Breeding for Improved Genotypes for Reforestation �������������������������������������������������������������������������� 343 11.4.1 Origin, Provenance, Population, and Family in Breeding���������������������������������������������������������������� 343 11.4.2 Selection in Breeding������������������������������������������������ 344 11.4.3 Growth and Properties of Timber and Biomass Related to Breeding�������������������������������������������������� 345 11.4.4 Gains in Genotype Transfer and Improving Genotypes for Reforestation ������������������������������������ 346 11.4.5 Climate Change and Tree Breeding�������������������������� 347

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11.5 Outline of Practices in Establishment of Forest Plantation�������������������������������������������������������������������������������� 348 11.5.1 Effects of Seed Sources and Site Fertility on Success of Regrowth�������������������������������������������� 348 11.5.2 Nursery Practices, Seedling Types, and Quality of Seedlings�������������������������������������������������������������� 350 11.5.3 Planning and Implementation of Reforestation�������� 351 11.5.4 Implementation of Seeding and Planting������������������ 354 11.6 Success of Reforestation �������������������������������������������������������� 358 11.6.1 Reforestation, with Natural Seedlings Fulfilling Plantation������������������������������������������������������������������ 358 11.6.2 Inventory of Reforestation Success�������������������������� 359 11.6.3 Survival of Seedlings������������������������������������������������ 360 11.6.4 Reforestation Success in 1960s, 1970s, and 1980s������������������������������������������������������������������ 362 11.6.5 Regeneration Success in 2000s �������������������������������� 363 11.7 Concluding Remarks�������������������������������������������������������������� 367 References������������������������������������������������������������������������������������������ 367 12 Management of Spacing in Pre-­commercial Phase��������������������  371 12.1 Properties of Seedling Stand������������������������������������������������  372 12.1.1 Seedling Phase in Relation to Forest Succession ��������������������������������������������������������������  372 12.1.2 Growth of Several Tree Species in Mixed Seedling Stand��������������������������������������������������������  372 12.2 Properties of Seedling Stand in Relation to Reforestation Success ����������������������������������������������������������  375 12.2.1 Density and Tree Species Composition������������������  375 12.2.2 Height Growth and Height Distribution������������������  376 12.2.3 Health and Technical Properties������������������������������  377 12.2.4 Spatial Distribution of Seedlings����������������������������  378 12.3 Competition in Seedling Stand ��������������������������������������������  379 12.3.1 Growing Space and Accumulation of Mass in Trees��������������������������������������������������������������������  379 12.3.2 Growth of Seedlings in Varying Spacing over Time����������������������������������������������������������������  381 12.4 Management of Seedling Stand��������������������������������������������  382 12.4.1 Concept and Objectives������������������������������������������  382 12.4.2 Identifying Management Needs������������������������������  383 12.4.3 Controlling the Impacts of Herbs and Grasses and Competing Trees on Seedlings ������������������������  384 12.4.4 Cleaning������������������������������������������������������������������  385 12.4.5 Pre-commercial Thinning����������������������������������������  385 12.4.6 Replanting ��������������������������������������������������������������  387 12.5 Concluding Remarks������������������������������������������������������������  387 References����������������������������������������������������������������������������������������  387

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13 Management of Spacing and Thinning in Commercial Phase������������������������������������������������������������������������������������������������  389 13.1 Growth and Development of Tree Stand Over Time������������  390 13.1.1 Growth, Yield, and Thinning ����������������������������������  390 13.1.2 Spacing in Relation to Tree Species and Mass�������  391 13.1.3 Growth, Mass, and Stocking ����������������������������������  391 13.2 Mass of Trees in Relation to Stand Density��������������������������  393 13.3 Spacing and Differentiation of Stand Structure��������������������  395 13.3.1 Growth and Development in Relation to Spacing����������������������������������������������������������������  395 13.3.2 Differentiation in Canopy Layers and Crown Classes��������������������������������������������������������������������  397 13.3.3 Spacing, Growth of Stem, Branches, and Foliage in Scots Pine����������������������������������������������  398 13.4 Thinning Impacts on Light Condition in Tree Stand������������  399 13.4.1 Effect of Canopy Structure on Light Absorption��������������������������������������������������������������  399 13.4.2 Within-Tree Shading in Tree Crown ����������������������  402 13.4.3 Between-Tree Shading in Tree Stand����������������������  402 13.4.4 Effect of Within- and Between-Tree Shading on Irradiation in Tree Crown����������������������������������  403 13.4.5 Model Simulation of How Thinning Affects Radiation Received in Scots Pine Crown����������������  405 13.5 Thinning, Thermal Conditions, Water, and Nutrients in Tree Stand ������������������������������������������������������������������������  407 13.5.1 Temperature Above and Below Soil Surface����������  407 13.5.2 Throughfall, Soil Moisture, and Nutrients��������������  407 13.5.3 Thinning-Induced Changes in Available Water and Nitrogen for Growth������������������������������  409 13.6 Thinning Linked to Growth and Development of Trees ������  410 13.6.1 Thinning in Relation to Growth Dynamics and Self-thinning����������������������������������������������������  410 13.6.2 Thinning in Different Developmental Phases ��������  413 13.6.3 Thinning Rules��������������������������������������������������������  414 13.7 Thinning Affecting Growth and Timber Yield����������������������  416 13.7.1 Responses of Diameter and Height Growth to Thinning��������������������������������������������������������������  416 13.7.2 Effects of Thinning from Below and Above on Growth and Timber Yield ����������������������������������  417 13.8 Effect of Spacing and Thinning on Properties of Timber������������������������������������������������������������������������������  420 13.8.1 Properties of Timber Related to Structural Growth of Crown����������������������������������������������������  420 13.8.2 Birth, Growth, and Mortality of Branches in Young Scots Pines ��������������������������������������������������  420

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13.8.3 Diameter and Pruning off of Branches in Young Scots Pines����������������������������������������������������������  423 13.8.4 Effects of Spacing and Age of Trees on Branches in Crown Over Rotation in Scots Pines��������������������������������������������������������������������  425 13.9 Timing and Intensity of Thinning Through Rotation ��������  427 13.10 Management of Mixture of Coniferous and Deciduous Tree Species ����������������������������������������������������  427 13.10.1 Tree Species Mixtures ����������������������������������������  427 13.10.2 Mixture of Scots Pine and Birch ������������������������  428 13.10.3 Mixture of Norway Spruce and Birch ����������������  429 13.11 Concluding Remarks����������������������������������������������������������  433 References����������������������������������������������������������������������������������������  434 14 Fertilization in Management of Site Fertility������������������������������  437 14.1 Fertilization in the Context of Forest Ecosystem ��������������  438 14.1.1 Cycle of Nitrogen in Trees and Site, with Effects on Growth������������������������������������������������  438 14.1.2 Nitrogen Uptake and Available Nitrogen Related to Fertilization����������������������������������������  439 14.1.3 Nitrogen Content of Foliage Related to Site Type and Thermal Conditions ����������������������������  440 14.1.4 Change of Foliage Nitrogen as a Function of Nitrogen Dose������������������������������������������������������  441 14.2 Effects of Nitrogen Fertilization Functioning and Structure of Trees��������������������������������������������������������  443 14.2.1 Effect on Photosynthesis and Growth������������������  443 14.2.2 Mechanisms Linking Growth Response to Nitrogen Fertilization��������������������������������������  445 14.2.3 Effects of Nitrogen Addition on Growth ������������  446 14.3 Growth Response to Fertilization��������������������������������������  447 14.3.1 Timing and Duration of Growth in Response to Fertilization ����������������������������������������������������  447 14.3.2 Position of Trees and Growth Response to Nitrogen Fertilization��������������������������������������  449 14.3.3 Growth Response to Age of Trees and Dose of Fertilization ����������������������������������������������������  450 14.4 Growth Response to Interactions Between Different Factors��������������������������������������������������������������������������������  451 14.4.1 Growth Response to the Amount of Fertilizer and Forest Structure��������������������������������������������  451 14.4.2 Growth Response Related to Combined Thinning and Nitrogen Fertilization��������������������  455 14.5 Effect of Fertilization on Properties of Stem Wood ����������  457 14.5.1 Wood Density and Chemical Properties��������������  457 14.5.2 Bark ��������������������������������������������������������������������  457 14.5.3 Branches��������������������������������������������������������������  458 14.5.4 Damages��������������������������������������������������������������  459

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14.6 Effect of Fertilization on Carbon Accumulation in Soil������������������������������������������������������������������������������������  460 14.7 Concluding Remarks������������������������������������������������������������  461 References����������������������������������������������������������������������������������������  461 15 Pruning of Branches and Management of Timber Quality ������  465 15.1 Pruning in Management of Timber Quality��������������������������  466 15.1.1 Pruning in the Context of Tree Growth������������������  466 15.1.2 Natural Pruning vs Artificial Pruning of Branches�������������������������������������������������������������  466 15.2 Pruning of Branches and Heal-over Branch Stump��������������  468 15.2.1 Growth and Mortality of Branches�������������������������  468 15.2.2 Factors Affecting Heal-over������������������������������������  469 15.2.3 Heal-over in Relation to Thickness and Length of Branch Stump ����������������������������������������  469 15.3 Effect of Pruning on Stem Growth���������������������������������������  470 15.4 Practice of Pruning����������������������������������������������������������������  472 15.4.1 Pruning in Relation to Stem Diameter��������������������  472 15.4.2 Pruning in Relation to Crown Structure and Quality of Sawn Timber������������������������������������������  472 15.4.3 Selection of Trees for Pruning��������������������������������  475 15.5 Concluding Remarks������������������������������������������������������������  475 References����������������������������������������������������������������������������������������  475 Part V Management of Forest Ecosystem for Varying Services 16 Management Strategies for Producing Different Goods and Services������������������������������������������������������������������������������������  479 16.1 Management in Directing Forest Succession in Forestry ��������������������������������������������������������������������������������  480 16.1.1 Managing Structure and Functioning of Ecosystem ��������������������������������������������������������������  480 16.1.2 Dimensions of Sustainable Management����������������  481 16.1.3 Management Strategies, Using Rule-Based vs Optimized Management ������������������������������������  483 16.1.4 Management and Sustainability in Forestry������������  483 16.2 Rule-Based Management for Timber and Biomass in Even-Aged Forestry – A Case Study��������������������������������  487 16.2.1 Management Operations and Simulations��������������  487 16.2.2 Growth and Yield����������������������������������������������������  489 16.2.3 Nitrogen Cycle and Balance�����������������������������������  490 16.2.4 Management vs Sustainability��������������������������������  492 16.3 Rule-Based Managing for Timber and Carbon in Uneven-Aged Forestry – A Case Study��������������������������������  493 16.3.1 Management Operations and Simulations��������������  493 16.3.2 Growth of Stem Wood Related to Management Mode�������������������������������������������������  494

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16.3.3 Carbon Uptake and Storage������������������������������������  494 16.3.4 Stem Wood Stocking, Harvest, and Timber������������  494 16.3.5 Uneven-Aged Management vs Even-Aged Management������������������������������������������������������������  497 16.4 Optimized Management for Producing Timber and Energy Biomass – A Case Study������������������������������������������  498 16.4.1 Optimizing Growth and Yield in Management ������  498 16.4.2 Yield of Timber and Energy Biomass ��������������������  498 16.5 Optimized Management for Combining Several Services – A Case Study ������������������������������������������������������  499 16.5.1 Outline to Combine Ecosystem Services with Synergetic and Trade-Off Relations������������������������  499 16.5.2 Potentials for Obtaining Timber, Carbon Sequestrating, and Maintaining Biodiversity����������  501 16.5.3 Optimizing Production of Timber, Carbon Sequestrating, and Maintaining Biodiversity����������  501 16.6 Even-Aged and Uneven-Aged Management for Multifunctional Forestry ������������������������������������������������  502 16.7 Concluding Remarks������������������������������������������������������������  504 References����������������������������������������������������������������������������������������  505 17 Dynamics of Forest Ecosystem vs Ecosystem Services ��������������  507 17.1 Ecosystem Services vs Ecosystem Dynamics����������������������  508 17.1.1 Structure and Functioning of Ecosystem in Producing Services��������������������������������������������������  508 17.1.2 Priority Ecosystem Services������������������������������������  509 17.1.3 Management of Ecosystem Services and Management Intensity��������������������������������������  512 17.2 Management for Supporting Services����������������������������������  514 17.2.1 Priority Supporting Services ����������������������������������  514 17.2.2 Biodiversity ������������������������������������������������������������  514 17.2.3 Primary Production ������������������������������������������������  522 17.2.4 Nutrient Cycle ��������������������������������������������������������  525 17.2.5 Water Cycle ������������������������������������������������������������  528 17.2.6 Soil Formation��������������������������������������������������������  531 17.3 Management for Provisioning Services��������������������������������  532 17.3.1 Priority Provisioning Services.��������������������������������  532 17.3.2 Timber and Biomass������������������������������������������������  533 17.3.3 Reindeer Husbandry������������������������������������������������  535 17.3.4 Wildlife��������������������������������������������������������������������  536 17.3.5 Edible Berries����������������������������������������������������������  539 17.3.6 Edible Mushrooms��������������������������������������������������  543 17.3.7 Reindeer Lichen for Decoration������������������������������  546 17.3.8 Water Supply ����������������������������������������������������������  546 17.3.9 Genetic Resources��������������������������������������������������  548 17.4 Management for Regulating Services ����������������������������������  548 17.4.1 Priority Regulating Services ����������������������������������  548

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17.4.2 Protecting Arctic and High-Altitude Forest Boundaries����������������������������������������������������  549 17.4.3 Controlling Climatic Conditions and Climatic Hazards����������������������������������������������  552 17.4.4 Controlling Excess Water Flow������������������������������  556 17.4.5 Controlling Air Impurities��������������������������������������  557 17.4.6 Noise Abatement ����������������������������������������������������  559 17.4.7 Mitigating Climatic Warming ��������������������������������  564 17.5 Management for Cultural Services ��������������������������������������  583 17.5.1 Priority Cultural Services����������������������������������������  583 17.5.2 Landscape Values����������������������������������������������������  583 17.5.3 Recreation, Health, and Social Development����������  588 17.5.4 Symbolic, Cultural, and Spiritual Significance ������  592 17.6 Concluding Remarks������������������������������������������������������������  593 References����������������������������������������������������������������������������������������  594 18 Risks for Forestry Under Current and Warming Climate��������  601 18.1 Risk Management for Sustaining Ecosystem Services��������  602 18.1.1 Disturbances, Damages, Risks, and Uncertainty����  602 18.1.2 Risk Management���������������������������������������������������  603 18.2 Risk of Wind Disturbances and Damages����������������������������  604 18.2.1 Mechanisms of Wind-Induced Damages����������������  604 18.2.2 Wind Force and Uprooting Trees����������������������������  607 18.2.3 Wind Risks Related to Thinning and Fertilization������������������������������������������������������  610 18.2.4 Wind Risks on Scale of Forest Landscape��������������  612 18.2.5 Wind-Related Risks of Forest Damages Under Warming ������������������������������������������������������  614 18.3 Risk of Snow Disturbances and Damages����������������������������  617 18.3.1 Mechanisms of Snow-Induced Damages����������������  617 18.3.2 Risk of Snow-Induced Damages Under Current and Warming Climate��������������������������������  618 18.4 Risk of Fire Disturbances and Damages������������������������������  619 18.4.1 Fire Risk Related to Weather and Site Conditions ��������������������������������������������������������������  619 18.4.2 Risk of Trees to Die in Fire ������������������������������������  622 18.4.3 Frequency of Fire Events and Burnt Area��������������  623 18.4.4 Fire Potential and Climate Change Impact on Fire Risk ������������������������������������������������������������  626 18.5 Risk of Damages Related to Frost����������������������������������������  628 18.6 Risk of Biotic Disturbances and Damages����������������������������  629 18.6.1 Disturbing Agents Behind the Most Important Biotic Damages��������������������������������������  629 18.6.2 Damages with Largest Economic Losses: Herbivore Mammals������������������������������������������������  631 18.6.3 Damages with Largest Economic Losses: Root Rot������������������������������������������������������������������  631

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18.6.4 Damages with Largest Economic Losses: Pine Weevil��������������������������������������������������������������  631 18.6.5 Potential Large-Scale Losses: Bark Beetle ������������  633 18.6.6 Potential But Locally Important Losses: Insects and Fungi����������������������������������������������������  634 18.6.7 Locally Important Losses: Agents with Pronounced Cycles��������������������������������������������������  635 18.6.8 Locally Important Losses: Insects and Fungi Damaging Cones and Seeds������������������  636 18.6.9 Locally Important Losses: Alien Insects and Fungi����������������������������������������������������������������  636 18.7 Management for Mitigating and Avoiding Forest Damages��������������������������������������������������������������������  637 18.7.1 Precautionary Management for Controlling Abiotic Damages����������������������������������������������������  637 18.7.2 Precautionary Management for Controlling Biotic Damages ������������������������������������������������������  638 18.8 Concluding Remarks������������������������������������������������������������  638 References����������������������������������������������������������������������������������������  639 19 Forest Ecosystem Services and Management Under Climate Change������������������������������������������������������������������������������  643 19.1 Climate Change, Ecosystem Dynamics, and Ecosystem Services��������������������������������������������������������  644 19.1.1 Vulnerability Related to Potential Impacts of Climate Change��������������������������������������������������  644 19.1.2 Response and Adaptation to Climate Change ��������  645 19.1.3 Management for Different Ecosystem Services Under Climate Change ����������������������������  647 19.2 Supporting Services: Impacts and Management Under Climate Change����������������������������������������������������������  647 19.2.1 Supporting Services, Climate Change, and Variability ��������������������������������������������������������  647 19.2.2 Biodiversity ������������������������������������������������������������  648 19.2.3 Primary Production ������������������������������������������������  649 19.2.4 Nutrient Cycle ��������������������������������������������������������  653 19.2.5 Water Cycle ������������������������������������������������������������  654 19.3 Provisioning Services: Impacts and Management Under Climate Change����������������������������������������������������������  655 19.3.1 Provisioning Services, Climate Change, and Variability ��������������������������������������������������������  655 19.3.2 Timber-Based Services�������������������������������������������  655 19.3.3 Reindeer Husbandry and Wildlife��������������������������  658 19.3.4 Edible Berries and Mushrooms, Reindeer Lichens for Decoration��������������������������������������������  659 19.3.5 Water Supply and Groundwater Level��������������������  662 19.3.6 Genetic Resources��������������������������������������������������  665

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19.4 Regulating Services: Impacts and Management Under Climate Change����������������������������������������������������������  666 19.4.1 Mitigation of Warming in Ecosystem and Product Technosystem��������������������������������������  666 19.4.2 Carbon in Forest Ecosystem Under Climate Warming������������������������������������������������������������������  666 19.4.3 Combining Ecosystem and Product Technosystem in Mitigating Warming��������������������  668 19.4.4 Forest Spectral Properties, Biogeochemical Emissions in Mitigating Warming��������������������������  673 19.5 Cultural Services: Impacts and Management Under Climate Change��������������������������������������������������������������������  675 19.6 Management Under Climate Change, with Selected Measures and Problems Likely to Emerge ��������������������������  675 19.6.1 Risks, Opportunities, and Uncertainties in Management��������������������������������������������������������  675 19.6.2 Reforestation Through Natural Regeneration ��������  677 19.6.3 Reforestation Through Planting������������������������������  680 19.6.4 Pre-commercial Management ��������������������������������  682 19.6.5 Commercial Thinning ��������������������������������������������  683 19.6.6 Management of Tree Species Mixtures������������������  685 19.6.7 Growth of Scots Pine, Norway Spruce, and Birch Under Warming��������������������������������������  686 19.6.8 Productivity and Rotation Length Related to Growing Conditions��������������������������������������������  689 19.6.9 Risks of Abiotic and Biotic Disturbances and Mortality����������������������������������������������������������  692 19.6.10 Outline Strategies for Adapting to Climate Change in Ecosystem Context��������������������������������  693 19.7 Concluding Remarks������������������������������������������������������������  693 References����������������������������������������������������������������������������������������  695 20 Adaptive Management – Outlines of Theories and Practices����������������������������������������������������������������������������������  701 20.1 Needs of Adaptive Management and Practices��������������������  701 20.1.1 Outline of Assessing Needs for Adaptive Management������������������������������������������������������������  701 20.1.2 Outline Strategies and Activities in Adaptive Management������������������������������������������������������������  703 20.1.3 Outline of Planning of Management in Relation to Climate Change��������������������������������  704 20.2 Concluding Remarks������������������������������������������������������������  705 References����������������������������������������������������������������������������������������  705 Units and Conversions ��������������������������������������������������������������������������  707 Index��������������������������������������������������������������������������������������������������������  709

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Background: Management of Forest for Varying Ecosystem Services

Contents 1.1 Forests for Human Well-Being  1.1.1  Global Forest Cover  1.1.2  Boreal Forests  1.1.3  Forest Ecosystem, Ecosystem Services, and Management 

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1.2 Management of Forest for Goods and Services in Ecological Context  1.2.1  Environment/Genotype Interaction and Management  1.2.2  Forest Structure and Management  1.2.3  Control of Ecosystem Structure and Functioning in Management 

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1.3 Management Strategies, Regimes, and Operations 

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1.4 Scope of the Book 

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References 

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Abstract

Forest production is based on the internal ecosystem processes (succession), but external processes (management) are needed in realizing the production to meet target goods and services. This implies a need to adjust the management to the ecosystem dynamics in order to minimize the necessary control inputs and to avoid unexpected impacts on the ecosystem dynamics (precautionary principle). Forestry is sustainable if the dynamics of a managed forest ecosystem mimics that of a natural forest ecosystem but still gives space for producing expected services. Management will be acclimated to the natural succession through emphasizing such features of succession that are likely to increase the probability

of having the necessary target structure and functioning for different ecosystem services. Keywords

Ecosystem goods and services · Forest ecosystem · Forest management

1.1

Forests for Human Well-Being

1.1.1 Global Forest Cover According to the Food and Agriculture Organization of the United Nations (FAO), the global forest cover is 5.2 billion hectares (ha). This includes 4 billion ha of forest land and 1.2

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 S. Kellomäki, Management of Boreal Forests, https://doi.org/10.1007/978-3-030-88024-8_1

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1  Background: Management of Forest for Varying Ecosystem Services

billion hectares of other wooded land. The total area of forest land and other wooded land is 31% of the global land area (FAO 2016). Forest land refers to land spanning more than 0.5  ha with trees taller than 5  m and a canopy cover of more than 10%, or where trees can reach these thresholds in situ, excluding land predominantly under agricultural or urban land use. Other wooded land is land not classified as forest. The minimum area of such land is more than 0.5 ha, with trees taller than 5 m and a canopy cover of 5–10%, or where trees can reach these thresholds in situ. Moreover, other wooded land may represent land with a combined cover of shrubs, bushes, and trees above 10%. Other wooded land does not include land that is predominantly under agricultural or urban land use (FAO 2016). More than 50% of global forest land is in tropical (44%) and subtropical (8%) countries. In temperate countries, the share of global forests is Fig. 1.1  Distribution of the boreal forest around the North Pole as indicated in green. Map available at http://www. borealforest.org, based on Hare and Ritchie (1972). (Courtesy of Borealforest.org under the copyright notice of Faculty of Natural Resources Management, Lakehead University, Canada)

26% and in boreal countries 22%. In a geographical context, Europe (including the Russian Federation) has more forest than any other region (25%), but there are also large forest areas in South America (21%) and North America (16%).

1.1.2 Boreal Forests Boreal forest land covers about 1224 million ha (30% of the global forest land) (FAO 2001, 2006, 2016; Wulder et  al. 2007; Keenan et  al. 2015), mainly in North America (Canada, Alaska), the Nordic countries (Finland, Sweden, Norway), and Russia (Fig.  1.1). Two-thirds of all boreal forests are in Eurasia, mostly in Russia (69% of the total global boreal forest area). Some boreal forests are located on peatlands, which cover 250–350 million hectares of land (e.g., Apps et al. 1993; Kauppi et al. 1997; Strack 2008), rep-

1.1  Forests for Human Well-Being

resenting 18–28% of the boreal land area (DeLuca and Boisvenue 2012). Boreal forests represent a mosaic of uplands and peatlands, including successional and subclimax plant communities, which are susceptible to various disturbances (e.g., fire, wind, snow). Boreal forests (forests and woodlands) are located at high latitudes (45–70°). They are dominated by coniferous species but mixed with deciduous species on fertile sites (Bonan and Shugart 1989). Boreal forests fall between the summer and winter limits of Arctic air mass, determining the northern and southern limits of boreal forests (Gordon et al. 1989). The northern forest limit relates to the 10  °C July isotherm, whereas the southern limit is at the 18  °C July isotherm. In these conditions, the number of days with a daily mean temperature ≥ 10  °C falls in the range of 30–120 days per year. This implies that the mean annual temperature varies from −5 °C to +5 °C. In the continental parts, the mean annual temperature may even fall below −10 °C. In the most extreme part of boreal forests compared to tundra, the soil may be frozen throughout the year. The mean annual precipitation is 200–750  mm, excluding most maritime areas (e.g., western parts of North American boreal forests), where the annual precipitation may exceed 1000  mm. In many parts of boreal forest, as in the Nordic countries, the climate is humid, and precipitation exceeds evaporation. Climatic warming likely increases the precipitation and evaporation, thus changing the water balance and soil moisture, as likely occurs in northern Europe (Ruosteenoja et al. 2016).

1.1.3 F  orest Ecosystem, Ecosystem Services, and Management Forest ecosystem is widely used for identifying proper management for producing various services. According to Odum (1971), the forest ecosystem refers to the interaction between living organisms and their non-living environments: “Any unit that includes all the organisms (i.e., the community) in a given area interacting with the

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physical environment so that a flow of energy leads to clearly defined trophic structure, biotic diversity, and material cycles (i.e., exchange of matter between living and non-living parts) within the system is an ecological system or ecosystem”. In ecosystem ecology, the concepts of structure and functioning are used in analysing an ecosystem’s dynamics. In this context, trees and other organisms (community) occupying a site refer to the structure of the ecosystem, including the living mass distributed among the genotypes occupying the site and the resources available at the site for the regeneration and growth of trees and other organisms. The functioning refers to the interaction of the community with the physical environment characterizing the site. The primary functioning of trees and other green plants is the interception of solar energy in photosynthesis, thus producing organic compounds under the flow of carbon dioxide, water and nutrients through primary and secondary production. In management, the long-term structure and functioning (forest succession) are controlled to produce various tangible and intangible goods and services targeted in forestry. Ecosystem services involve the direct use of materials and resources related to the ecosystem structure. Ecosystem goods further refer to the use of material provided by the ecosystem for manufacturing different goods and services. Ecosystem services include (i) inorganic matter (O2, C, N, CO2, H2O, etc.) produced in plant metabolism and functioning and (ii) organic matter (proteins, carbohydrates, lipids, etc.) produced by plants in primary production (forming organic matter from inorganic matter) used in secondary production (micro- and macroorganisms consuming primary production). Ecosystem services also include the indirect use of the ecosystem structure in modifying the properties of the environment for: (i) Reducing the impacts of energy in terms of radiation, heat, mechanical forces (wind, snow load and gravity (e.g., landslide)) and noise, etc.

4

1  Background: Management of Forest for Varying Ecosystem Services

(ii) Enhancing environmental health by absorbing chemicals and particles from the atmosphere (e.g., air impurities) (iii) Enhancing the amenity of the environment and creating a functional environment for different human activities (iv) Maintaining cultural heritage and conserving ecosystem functions and biodiversity According to the Millennium Ecosystem Assessment (2005), ecosystem services fall into four categories: supporting, provisioning, regulating, and cultural services affecting human well-being (Fig. 1.2). Supporting services refer to the cycles of nutrients, carbon, and water that define the properties of the site under the control of populations/communities of trees and other organisms. Sites with trees and other organisms are spatial units, whose functioning produces provisioning services, such as wood and non-­ wood products, and their structure provides regulating and cultural services, such as climatic regulation and aesthetic values. Provisioning ser-

Fig. 1.2  Outline relations between ecosystems and ecosystem services. Left: structural hierarchy of forest ecosystem for functioning in the context of biosphere. Right:

vices include such concrete services as timber and groundwater, whereas cultural services involve the amenity values and recreation opportunities. Thus, ecosystem services convert the structural and functional dynamics of the forest ecosystem into production functions, which outline the sustainable management of the ecosystem for satisfying human expectations.

1.2

Management of Forest for Goods and Services in Ecological Context

1.2.1 Environment/Genotype Interaction and Management Throughout the world, the availability of different ecosystem goods and services varies depending on the properties of ecosystems and their dynamics and local traditions in using forest resources (e.g., Krebs et al. 2009). The production of goods and services is further based on the

ecosystem goods and services produced by forest ecosystem identified in the Millennium Ecosystem Assessment (2005)

1.2  Management of Forest for Goods and Services in Ecological Context

management of the structure of forest ecosystems. Any kind of forest-based production P(i, j, k) is a result of the interaction between the environment E(j) and genotype G(i) controlled in management M(k):

P  i, j, k   G(i )  E ( j )  M (k )



(1.1)

Management of the genetic properties of tree populations, the properties of sites (habitats) occupied by populations, or both, can maintain or increase production. Ultimately, management aims to modify the interaction of both factors to optimize the need to conserve the functioning and structure of forest ecosystems and to satisfy production needs. This occurs by controlling in the management process of the long-term functional and structural development of forest ecosystems (succession) for producing the goods

Fig. 1.3  Schematic presentation of the structure and functioning of a forested ecosystem as an interaction between climatic and edaphic factors and the populations of organisms, with the implications for management based on Kellomäki et  al. (2001) and Kellomäki et  al. (2009). If the future structure deviates from that expected, there is a need to direct the ecosystem dynamics (succes-

5

and services determined in the management goals. The physiological and ecological performance of tree populations (and populations of other species) or succession of tree populations/ communities is directed at producing such ecosystem structures that are needed in producing the specified goods and services targeted by management (Fig. 1.3). Sustainability is widely used to indicate the success of management in providing various ecosystem goods and services. Sustainability (sustainable forest management (SFM)) involves the management applying the concept of sustainable development in forestry. This implies “the use of forests and forest lands in a way, and at a rate, that maintains their biodiversity, productivity, regeneration capacity, vitality and their potential to fulfil, now and in the future, relevant ecological, economic and social functions, at local,

sion) through management (M(k)), which produces a more optimal ecosystem structure and functioning regarding the management objectives (P(i, j)), ecosystem services) in the interaction of genotype (G(i)), tree species and species provenance) and environment (E(j)) as shown in Eq. (1.1)

6

1  Background: Management of Forest for Varying Ecosystem Services

national and global levels, and that does not cause damage to other ecosystems” as agreed in the European context (State of Europe’s Forests 2003). In this respect, the ecological limits for sustainable management are described as (i) absorbing energy; (ii) converting energy to chemical energy and matter; and (iii) the distribution of matter between different organisms (biodiversity). The management may alter the habitat distribution and biogeochemical cycles but still within the limits set by the long-term dynamics (succession) of the forest ecosystem.

1.2.2 Forest Structure and Management Management needs are dependent on the management objectives and the properties of sites and tree stands (site fertility, structure of tree stand (e.g., species, density, maturity) and the forest landscape (e.g., distribution of site fertility, tree species composition, age-class distribution). Management strategies, and regimes, combining different management measures (operations), are tools for directing the succession towards the necessary structures and functioning at the levels of forest patches and regions. Management strategy refers to the main outlines of management like even-aged and uneven-aged management, while management regime includes a single or few management operations like natural regeneration under even-aged management. In management, succession is directed mainly through modifying the structure and the subsequent functioning of populations and communities. Populations are composed of single species, while the community includes several species occupying the same site. The population and community may be decomposed into structural elements, which include the trees (genotype) and the space within the environment, including forces and resources (radiation, temperature, nutrients, water) driving the regeneration, growth, and development of trees in the area defined by the crown area of a tree. Consequently, the forest succession refers to the interaction between structural elements, where trees regenerate, grow,

and die. For example, the community structure is changed during thinning by removing trees from the site but leaving the forces and resources for the remaining trees, expanding their space for growth and development. Thinning is thus a disturbance, driving succession to produce the community structure needed for producing different ecosystem services. In management, the target structure refers, for example, to the species composition, spacing, or size distribution of trees that are feasible for producing selected goods and services. In this respect, the tree species choice is closely linked with the site fertility and growing conditions that are optimal for different tree species. The structural and functional properties of species also affect whether single species or a mixture of two or more species is preferred by management. The variability in the interaction between tree species and site conditions further influences whether uneven-aged or even-aged management is used. In uneven-aged management, the focus is on the scale of single trees of varying ages and sizes, while in even-aged management, the focus includes several trees forming a stand of trees on the same patch of land of similar ages and sizes but differing from those in the nearby stands.

1.2.3 Control of Ecosystem Structure and Functioning in Management The structure and functioning of a forest ecosystem are hierarchical, which may limit the potential to direct the succession (Table  1.1). This implies a need to adjust the management to the ecosystem dynamics in order to minimize the necessary control inputs and to avoid unexpected impacts on the ecosystem dynamics (precautionary principle). Consequently, forestry is sustainable if the dynamics of a managed forest ecosystem mimics that of a natural forest ecosystem but still gives space for producing expected goods and services (Kalela 1946). Thus, the management ought to be acclimatized to the natural succession through emphasizing such features of succession that are likely to increase the

1.3  Management Strategies, Regimes, and Operations

7

Table 1.1  Potentials to control structure and functioning of forest ecosystem in management

ceed from regeneration through seedling and thinning phases to full maturity for regeneration, etc. Management is widely divided into phases, which link the management to the structural and functional dynamics of the ecosystem. Management regimes (e.g., forest regeneration) may include several operations, while an operation refers to a single measure needed in implementing the given management regime. For example, regeneration includes any direct and indirect operations that enhance the establishment of seedlings through the seedling phase to the thinning phase providing biomass and timber during harvest (Table 1.2). Further maturation of the tree population and community increases the harvest opportunities while still maintaining stocking and subsequent growth high enough to meet the potential productivity of selected tree species at the site. In even-aged management, tree populations and communities resistant to abiotic and biotic damages are preferred through the management cycle (rotation) to avoid unnecessary risks and damages to forest ecosystems and forestry. This also holds for uneven-aged management, where the production cycle is defined by consecutive selection and removal of trees in cuttings. In even-aged management, the production cycle integrates several management regimes and operations in a sequence, which follows the growth and development of tree populations or communities from the seedling phase to full maturity. In this case, management of rotation may include the following regimes and operations: soil management (e.g., soil preparation), regeneration (natural or planting and seeding), tending of seedling populations and communities (spacing, cleaning, removal of competition due to ground vegetation, replanting), thinning (repeated thinning in maturing stands with harvest of pulp wood/energy biomass, saw logs), and terminal cutting with clear-felling for planting or cutting for natural regeneration with the shelterwood or seed tree method. In uneven-aged management, the production cycle is also related to the maturing of trees, but in this case the length of cycle is defined by the consecutive thinning interventions, providing space for natural regeneration in

Structural features Climate  Macroclimate  Mesoclimate  Microclimate Soil  Moisture  Temperature  Nutrients  Gases in soil profile Plant community  Trees  Ground cover and other species Consumers  Herbivores  Pathogens  Decomposers

Potential to control in management Not possible Not possible Not possible or only small Possible Small or possible Possible or large Small or possible Large Possible or large

Not possible or small Not possible or small Not possible or small

p­ robability of having the necessary target structure needed for producing different ecosystem goods and services.

1.3

Management Strategies, Regimes, and Operations

Management is used to control the regeneration, growth, and mortality of trees growing in populations and/or communities. Management has a target, which defines necessary management strategies, regimes, and operations to sustain the future potentials to produce varying goods and services. Management operations, including timing and intensity, are defined based on future structure in relation to the structure optimizing the production potentials for the targeted goods and services. The necessary management is further related to the past forest structure and management (management history), which likely have effects on the future growth and development of forests. Based on the expected target structure, one may identify the necessary management for controlling the pattern of succession needed in producing targeted goods and services. Over a succession of tree populations and communities, the growth and development pro-

1  Background: Management of Forest for Varying Ecosystem Services

8

Table 1.2  Division of even-aged management into necessary basic sciences and the management applications and operations typical of managed boreal forests Management operations Transfer of tree species and their provenances, breeding new cultivars, seed orchards Soil management Natural Tree species for natural and regeneration, and their artificial artificial regenerative regeneration, regeneration properties nurseries for (seeding, producing seedlings planting) in for planting, forest planting operations plantations using varying technics Management of Tending of forest in Tree species trees in seedling seedling phase and their (spacing, cleaning), and thinning growth spacing forest in phases properties thinning phase, pruning Reducing abiotic Forest Other (wind, snow, fire) organisms and protection for and biotic their properties abiotic and biotic damages (herbivores, in competing pathogens) with trees damages using various techniques and maintaining and enhancing forest health Choice of site in Soil management Site and site using various relation to properties in relation to the requirements of mechanical requirements of tree species, soil methods, fertilization, management tree species prescribed burning

Basics Tree species and their general biological properties

Management regimes Tree species choice, tree breeding

removing mature trees. Thus, uneven-aged management integrates the regeneration and thinning but excludes terminal cutting for regeneration as occurs in even-aged management.

1.4

Scope of the Book

This book addresses the dynamics and management of boreal forests, with a focus on the selected ecosystem goods and services. In this context, supporting services represent the basic

structure and functioning of forest ecosystems, e.g., biomass and energy uptake, thus producing provisioning, regulating and cultural services. Provisioning services include, for example, timber biomass, groundwater, and wildlife, whereas regulating services address, for example, the role of forests in controlling wind force and removing air impurities and reducing urban noise. Cultural services involve, for instance, amenity values, and recreation opportunities. In the ecosystem context, management controls the succession of a forest ecosystem, when aiming at the production of selected goods and services under the current and changing climate. In both cases, climate-­ induced disturbances and risks are demonstrated with a focus on the impacts on different ecosystem goods and services. The adaptation of management to climate warming is outlined with a view to mitigating the harmful effects of such warming on the dynamics of managed boreal forests.

References Apps MJ, Kurz WA, Luxmore RJ, Nilsson LO, Sedro RA, Schmidt R, Simpson LG, Vinson TS (1993) Boreal forests and tundra. Water Air Soil Pollut 70:39–53 Bonan GB, Shugart HH (1989) Environmental factors and ecological processes in boreal forests. Annu Rev Ecol Syst 20:1–28 DeLuca TH, Boisvenue C (2012) Boreal forest soil carbon: distribution, function, and modelling. Forestry 85(2):161–184 FAO (2001) Forest resources assessment (2000). Rome. http://www.fao.org/forestry/11747/en/ FAO (2006) Global forest resources assessment 2005. progress towards sustainable forest management. FAO For Papers 147:1–320 FAO (2016) Global forest resources assessment 2015. How are the world’s forests changing?, 2nd edn. Rome. 44 p Gordon B, Bonan GG, Shugart HH (1989) Environmental factors and ecological processes in boreal forests. Annu Rev Ecol Syst 20:1–28 Hare F, Ritchie JC (1972) The boreal microclimates. Geogr Rev 62:333–365 Kalela EK (1946) Metsät ja metsien hoito. Werner Söderström Oy, Porvoo. 367 p Kauppi P, Posch M, Hänninen P, Henttonen H, Ihalainen A, Lappalainen E, Starr M, Tamminen P (1997) Carbon reservoirs in peatlands and forests in the boreal region of Finland. Silva Fennica 31(1):13–25 Keenan RJ, Reams GA, Achard F, de Freitas JV, Grainger A, Lindquist E (2015) Dynamics of global forest

References area: results from the FAO Global Forest Resources Assessment 2015. For Ecol Manag 352:9–20 Kellomäki S, Kouki J, Niemelä P, Peltola H (2001) Timber industry. Encyclopaedia Biodivers 7:212–221 Kellomäki S, Koski V, Niemelä P, Peltola H, Pulkkinen P (2009) Management of forest ecosystem. In: Kellomäki S (ed) Forest resources and sustainable management. Gummerus Oy, Jyväskylä, pp 252–373 Krebs CJ, Boonstra R, Cowcill K, Kenney AJ (2009) Climatic determinants of berry crops in the boreal forests of the southwestern Yukon. Botany 87:401–408 Millennium Ecosystem Assessment (2005) Ecosystems and human well-being: synthesis. Island Press, Washington, DC. 102 p Odum EP (1971) Fundamentals of ecology, 3rd edn. W.B. Saunders Company, Philadelphia. 574 p

9 Ruosteenoja K, Jylhä K, Kämäräinen M (2016) Climate projections for Finland under the RCP forcing scenarios. Geophysica 51:17–50 State of Europe’s Forests (2003) The MCPFE report on sustainable forest management in Europe. Jointly prepared by the MCPFE Liaison Unit Vienna and UNECE/FAO.  Edited and published by Ministerial Conference on the Protection of Forests in Europe. Liaison Unit Vienna, Vienna, Austria Strack M (ed) (2008) Peatlands and climate change. International Peat Society, Saarijärven Offset Oy, Saarijärvi Wulder MA, Campbell S, White JC, Flannigan M, Campbell ID (2007) National circumstances in the international circumboreal community. For Chron 83(4):539–556

Part I Forest Environment of Boreal North and Forestry

2

Environmental Conditions, Site Types, and Climate Change

Contents 2.1 Forest Site, Productivity, and Climate Change 

 14

2.2 C  limatic Conditions  2.2.1  Climate in Varying Scale  2.2.2  Radiation in Global Context  2.2.3  Total Radiation and Radiation Balance  2.2.4  Radiation Balance on Ground Surface  2.2.5  Thermal Conditions  2.2.6  Precipitation, Humidity, and Evaporation  2.2.7  Wind  2.2.8  Atmospheric Carbon Dioxide 

 15  15  16  19  19  22  22  26  27

2.3 I nteraction Between Climate and Forest Structure  2.3.1  Climatic Conditions and Forest Canopy  2.3.2  Radiation in Forest Canopy and Tree Crown, Interception of Radiation  2.3.3  Evaporation of Water in Forest Canopy  2.3.4  Wind in Forest Canopy  2.3.5  Interaction of Microclimatic Factors in Forest Canopy: Temperature of Foliage 

 30  30  30  34  35

2.4 E  daphic Conditions  2.4.1  Bedrock and Soils  2.4.2  Water in Soil  2.4.3  Soil Temperature  2.4.4  Nutrients  2.4.5  Site Types in Identifying Site Fertility  2.4.6  Site Index in Identifying Site Fertility 

 37  37  38  42  42  43  47

2.5 C  hanges in Climatic and Edaphic Conditions Under Global Warming  2.5.1  Global Climate Change  2.5.2  Past Climate Change and Changes Until Now  2.5.3  Future Climate Change: SRES Scenarios for Temperature and Precipitation  2.5.4  Future Climate Change: RCP Scenarios for Temperature and Precipitation  2.5.5  Climate Variability and Weather Extremes  2.5.6  Drought Episodes Under SRES and RCP Scenarios  2.5.7  Snow Cover 

 48  48  49

2.6 Concluding Remarks 

 59

References 

 60

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 S. Kellomäki, Management of Boreal Forests, https://doi.org/10.1007/978-3-030-88024-8_2

 36

 51  52  52  54  58

13

2  Environmental Conditions, Site Types, and Climate Change

14

Abstract

Trees grow in sites, the properties of which are characterized by climatic and edaphic factors. In growth and yield studies, the productivity (m3  ha−1  year−1) involves the potential stem wood growth in trees. Productivity combines the edaphic and climatic properties of sites on growth, including soil texture, supply of water and nutrients, precipitation, radiation, temperature and atmospheric carbon dioxide. In this context, climate change is likely to have multiple impacts on the properties of sites, thereby affecting the dynamics of the forest ecosystem. Climate change effects on the growing conditions like temperature sum, which integrates the changes in the length of growing season and thermal conditions. Climate change is likely to affect productivity substantially, thereby making it necessary to revise management to meet properly the benefits and problems induced by warming climate. Keywords

Boreal environment · Climatic conditions · Edaphic conditions · Site fertility · Site classification · Climate change

2.1

 orest Site, Productivity, F and Climate Change

The regeneration, growth and development of trees are linked to the properties of a site, representing patches of forest land combining the climatic and edaphic conditions in a given way. A site is the place where trees regenerate and grow in interaction with climatic and edaphic factors. In the forestry context, for example, primary production and biodiversity are important supporting services maintaining provisioning services like biomass and timber, which the trees occupying these sites provide at a given rate. In growth and yield studies, the provisioning rate equals productivity (e.g., m3 ha−1 year−1 of stem wood),

which involves the potential growth of a tree stand per unit area and unit time. This holds both for natural stands and for those managed in a specific way. Productivity (P) varies in relation to the given genotype (tree species), site fertility, stand structure (e.g., density), and the specified management (Skovsgaard and Vanclay 2008; Leuzinger and Baber 2012): P  f  genotype, climatic factors, edaphic factors, management  (2.1) where climatic and edaphic factors imply the prevailing environment affecting the regeneration, growth, and development of the given tree species (genotype) under the given management. In the site context, the main climatic factors affecting regeneration and growth include radiation, temperature, precipitation, and atmospheric carbon dioxide (CO2). These factors directly/ indirectly drive the CO2 assimilation for compounds used in the growth and maintenance of living functions of trees. On the other hand, edaphic factors refer to the physical and chemical properties of soil, with impacts on the amount and supply of water and nutrients for physiological and ecological processes of trees. The properties of soil are correlated to the properties of bedrock and the properties of soil fractions loosened from bedrock under continental ice or transferred from outside to patches in ice and water flows originating from melting ice. In the Finnish territory, for example, soils are mainly podzols, from which infiltrating water carries phosphorus and potassium from surface soil deeper in the soil profile, thus enriching silicates and other nutrient-­ poor compounds in the surface soil. Nutrient supply, especially that of nitrogen, is closely related to the atmospheric deposition. Nitrogen cycle is further related to the release of nitrogen bound in soil organic matter (SOM; including litter and humus in varying decay phase). In the decay of SOM, nitrogen is released for physiological and ecological processes, which drive the regeneration, growth, and development of trees. The climatic and edaphic conditions in sites are dependent on the developmental phase of

2.2  Climatic Conditions

trees and management. Moreover, climate change is likely to have multiple impacts on the properties of sites, thereby affecting the dynamics of the forest ecosystem. Warming has direct effects on the physiological and ecological processes driving the regeneration, growth, and development of trees. Climate change further directly/indirectly affects the properties of soil, including soil moisture, temperature, and nutrient supply, thus affecting the decay of SOM. On the other hand, abiotic damages are related to changes in wind force and snow load, inducing the turning down and destruction of trees. These disturbances may trigger biotic damages, such as an excessive attack of bark beetles, increasing the mortality of trees. In forestry, such changes can be controlled through proper management, including tree species choice, thinning intensity, and rotation length. Management related to climatic change facilitates the mitigation of harmful effects on the forest ecosystem that climate warming likely triggers.

2.2

Climatic Conditions

2.2.1 Climate in Varying Scale Climatic factors form the climate, which is divided into macro-, meso-, and microclimate depending on the spatial scale. Macroclimate

Fig. 2.1  Schematic presentation of the CO2 and H2O exchange in a forest ecosystem if airflow through the canopy is laminar (left) and turbulent (middle). The exchange

15

refers to the climate over a large geographic area, e.g., continents or their parts. Macroclimate is widely characterized by the annual amount and distribution of radiation, temperature, wind, clouds, precipitation, and air humidity. Macroclimate has a decisive effect on the global distribution of forests and their structure and functioning, including the composition and productivity of tree species. In Finland (60°–70° N), for example, temperature and the length of the growing season have a strong effect on the dynamics of forests (regeneration and growth and development of trees), while the effects of precipitation are most pronounced on soil with a low water holding capacity (e.g., sandy soils). The dynamics of forests is further related to the CO2 content in the atmosphere. A mesoclimate falls between a macro- and a microclimate (Fig.  2.1). Microclimate refers to local atmospheric conditions, surrounding trees and having immediate effects on the physiological and ecological processes driving the growth and development of trees. The properties of a microclimate are closely correlated to the properties of a macroclimate. Moreover, the properties of trees affect how radiation, temperature, precipitation, wind, air humidity, and atmospheric CO2 are distributed within populations and communities of trees. The interaction between trees and their immediate environment is a complex

of O2, CO2, and H2O takes place through the boundary layer and stomata in leaves (right)

16

2  Environmental Conditions, Site Types, and Climate Change

process, where the structure of trees modifies the properties of the environment with feedback to the growth and structural development of trees (e.g., Leuzinger and Bader 2012). The properties of a microclimate are further related to the properties of the boundary layer between the atmosphere and the crowns/canopies of trees and the soil surface below trees (or soil surface in treeless sites).

2.2.2 Radiation in Global Context Solar radiation is divided into short-wave (wavelength    4,000  nm) radiation (Fig.  2.2). Visible radiation (light) falls in the wavelength range of 400–700  nm. Radiation drives photosynthesis and includes heat. Radiation further affects plant morphology, as does radiation with a shorter wavelength than that of visible radiation (ultraviolet radiation UV-A 320–400  nm and UV-B 280–320  nm). However, the heating effect of short-wave radiation is small, and it does not drive photosynthesis. Radiation with a wavelength longer (> 700 nm) than that of the visible one has a large heating effect, but it does not drive photosynthesis. Long-wave radiation is divided into far-red (700–800  nm) and infrared (800–4,000 nm) radiation (Box 2.1).

2.2  Climatic Conditions

Box 2.1: Sun and Earth Geometry Affecting Irradiation at Any Point on the Earth

The earth travels around the sun in an elliptical orbit on a plane (the ecliptic plane) and spins around its polar axis (Fig. 2.3). A solar irradiation incident at a point on the earth depends on the time of year, time of day, and latitude. The location of the sun in the hemisphere is defined by the altitude above the horizon and azimuth, which indicates the direction of the sun clockwise from the north. The rotational axis of the earth is inclined at an angle of 66.5° in relation to the ecliptic plane, pointing constantly to the Pole Star. As the earth moves in its orbit around the sun, the earth axis moves in parallel. The angle between the ecliptic plane and the equatorial plane is 23.5°. The angle that the line of the sun’s ray to the earth makes with the equatorial plane is the declination of the sun (δ [−23.5°, +23.5°]). Thus, the declination indicates the angular distance of the sun north (positive) or south (negative) of the equatorial plane. March 21 and September 23 are the spring and autumn equinoxes, when the sun is passing directly over the equator. The tropics of cancer and capricorn indicate the maximum declination of the sun in northern and southern hemisphere. As the earth orbits around the sun, the declination varies, but it is dependent only on the day of the year. In the northern hemisphere, the value of declination is −23.5° at the winter solstice (December 22). This implies that the northern hemisphere is more declined away from the sun. Consequently, the mean amount of incoming irradiation is smaller in the northern than in the southern hemisphere. At the summer solstice (June 22), declination is +23.5°. Now the northern hemisphere is more declined towards the sun than the southern hemisphere, and the incoming irradiation is larger in the northern than in the southern hemisphere. At the spring (March 21) and autumn (September 23) equinox, both hemispheres receive an equal amount of irradiation. The location of the sun in relation to the given point is defined by the altitude and azimuth of the sun. The sun’s altitude is defined

17

by the solar altitude angle, which is the angle between the sun’s ray and a horizontal plane. The solar altitude angle is related to the solar zenith angle, which indicates the angle between the sun’s ray and the vertical line pointing towards the zenith. Consequently, Φ + α = π/2 = 90°. The solar angle is (Gates 1980, pp. 99–103): sin    cos    sin  L   sin   (2.2)  cos  L   cos    cos  h  where α is the solar altitude angle, Φ is the solar zenith angle, L is the latitude, δ is the declination and h the hour angle of the sun (angular distance from the meridian or hour angle). Similarly, the solar azimuth angle is sin    



 sin  h   cos   sin  

(2.3)

where β is the solar azimuth angle. The solar azimuth angle can also be calculated with Eqs. (2.4) and (2.5): cos    

sin    cos  L   cos  h   cos    sin  L  sin  

,

if h  0

(2.4)





cos 360 o   

sin    cos 

  sin   , sin    cos  L 

if h  0

 (2.5)

The angular distance or hour angle (h [−180°, +180°]) refers to the angular distance from the prime meridian: negative values towards the west and positive values towards the east. The daily highest altitude of the sun at the given latitude can be obtained based on Eq. (2.3). In southern Finland (60° N), for example, the sun’s altitude at the summer solstice is 53.5°, while at the Arctic Circle (66° N) and in northernmost Finland (70° N), the altitude is

2  Environmental Conditions, Site Types, and Climate Change

18

Box 2.1:  (continued)

47.5° and 43.5° above the horizon, respectively. Explanations for the main concepts are the following: • Orbit is the regular, repeated path of the earth in space around the sun. • Ecliptic is the apparent path that the sun traces out in the sky during the year. • Elevation is the altitude of the sun, the angle between the horizon and the centre of the sun’s disc. Since these two angles are complementary, the cosine of either one of them equals the sine of the other. • Altitude is the sun’s elevation angle between the horizon and the centre of the sun’s disc.

Fig. 2.3  Left/Above: Orbit of the earth around the sun. Right/Above: Daily rotation of the earth around the axis perpendicular to the equator, with the rotation being tilted by 23.5° in relation to the plane of its orbit. The plane parallel to the celestial equator of the earth and through the centre of the sun is the plane of the sun. The earth passes

• Azimuth angle is the compass direction from which the sunlight is coming. • At solar noon, the sun is directly in south. • Declination of the sun is the angle between the rays of the sun and the plane of the earth’s equator. The earth’s axial tilt (called the obliquity of the ecliptic) is the angle between the earth’s axis and a line perpendicular to the earth’s orbit. • Spring equinox: March 21. • Autumn equinox: September 23. • Summer solstice: June 22. • Winter solstice: December 22.

above and below this plane, when completing the yearly elliptic cycle. Left/Below: Altitude of sun defined by the angle (α) between the sun’s ray and the horizontal plane. Azimuth of the sun (Φ) is in the direction clockwise from the north. Right/Below: Declination of the sun as a function of different seasons. Figure based on several sources

2.2  Climatic Conditions

19

2.2.3 T  otal Radiation and Radiation Balance Total radiation refers to the energy over all the wavelengths in the solar radiation. Total radiation above the atmosphere is 1,360 W m−2 (So, solar constant). The atmosphere absorbs about 30% of the radiation passing through the atmosphere depending on the atmospheric transmittance (τ, 0…1). Transmittance is reduced, for example, by water vapour and dust in the air. Transmittance is further dependent on the angle at which radiation passes through the atmosphere. Thus, radiation from the sun close to the horizon (low solar elevation) takes a longer route (th) in passing through the atmosphere than the radiation coming from the sun far up from the horizon (high solar elevation) (Gates 1980, pp. 111–117): RADCLD  h   So   th  sin   



 So 0.271  0.294   th

 sin   



(2.6)

Fig. 2.4  Left: Daily total solar irradiation per unit horizontal area as a function of latitude and atmospheric transmittance (τ) at the time of equinox. Right: Irradiation of direct, diffuse, and global short-wave radiation on the horizontal surface (England, 52.8°N,1.3°W) as a function

where h means an hour and RADCLD the hourly value of radiation above clouds. Figure 2.4 shows that the daily total of solar irradiation per unit horizontal area on the earth reduces towards the poles as a function of latitude and atmospheric transmittance at the time of equinox. In boreal conditions (60°–70° N), the irradiation is about a half of that at the equator. In clear-sky conditions, the contribution of diffuse radiation is 20–30% of the global radiation at high solar elevation, and more for low solar elevation.

2.2.4 R  adiation Balance on Ground Surface Solar radiation on ground surface represents short-wave (wavelength  21 m s−1, but the probability of such wind episodes is very small. Most storm episodes are local, represented by local thunderstorms, with small-scale damage to forests. Large-scale storm catastrophes may be expected to occur twice every 10  years, as in 1961, 1978, 1982, 1985, 2001, and 2002. Under the current climate conditions, wind episodes with very high wind speeds are rare and have a very low probability (Fig. 2.11).

2.2.8 Atmospheric Carbon Dioxide In the scale of the earth, the atmosphere is among the main components of the global carbon cycle, holding approximately 720 Gtons of carbon (one Gton is equal to 109  Mg) (IPCC 2007). In the global carbon cycle, the atmospheric carbon

28

2  Environmental Conditions, Site Types, and Climate Change

Fig. 2.11  Upper: Distributions of wind velocity in southern (Helsinki, 60° N) and northern (Rovaniemi, 66° N) Finland based on long-term weather statistics. Below/ Left: Spatial distribution of wind speed over the Finland (Laapas et  al. 2019). Courtesy of MDPI and Wiley and

Sons under Open Access. Below/Right: Distribution of 10-year return level of the maximum wind velocity for the years 1979–2014, and the annual probability of wind speeds exceeding 25  m  s−1. (Venäläinen et  al. 2020. Permission of Wiley & Sons)

dioxide (CO2) integrates the difference between carbon emissions and uptake from/in geological and ecological processes in the earth. The exchange of atmospheric carbon between the water and the land systems implies that the atmosphere is both a sink and a source of carbon. In this context, the biosphere takes CO2 from the atmosphere in primary production and emits to

the atmosphere in autotrophic respiration, driving and maintaining the regeneration and growth functioning of the biosphere. On the other hand, carbon in fossil fuels and biomass is released in burning and decay of organic materials (IPCC 2014). Carbon emissions are further related to land use converting forest land into agricultural land and pastures (deforestation). The devasta-

2.2  Climatic Conditions

Fig. 2.12 Concentration of greenhouse gases in the atmosphere over the period 1850–2010, with green for carbon dioxide (CO2), orange for methane (NH4), and red

29

for nitrous oxide (N2O). The values are based on ice cores (dots) and direct atmospheric measurement (lines). (IPCC 2014, Figure SPM 1, p. 3. Permission of IPCC)

Fig. 2.13  Decay of pulse emission of CO2, N2O, and CH4 in the atmosphere in natural processes. (Sathre et al. 2013. Courtesy of Springer Nature)

tion of forests further reduces the CO2 uptake and enhances the decay and oxidation carbon compounds in soil organic matter (SOM). The CO2 emissions indicate further the secondary production through decaying detritus into CO2 in aerobic conditions and into methane (NH4) and nitrous oxide (N2O) in anaerobic conditions (Fig. 2.12). The increase in atmospheric CO2 originates largely (80%) from the combustion of fossil fuels

(coal, oil) and the production of cement, while the rest (20%) originates from land use. The lifetime of CO2 in the atmosphere is 30–95  years (e.g., Sathre et  al. 2013). The lifetime of other greenhouse gasses, like that of N2O, is substantially longer (120  years) than that of CO2. The lifetime indicates the time over which equilibrium in the given CO2 (or other GHGs) concentration is achieved after a sudden increase/ decrease in concentration (Fig. 2.13). Molecules

2  Environmental Conditions, Site Types, and Climate Change

30

of GHGs are removed from the atmosphere in deposition and adsorption as on surfaces on land and water. Molecules of CO2 are absorbed in photosynthesis and bound in biomass.

2.3

I nteraction Between Climate and Forest Structure

2.3.1 Climatic Conditions and Forest Canopy Most radiation is intercepted in upper canopy layers. They further absorb the majority of wind momentum, thus reducing wind velocity and the exchange of heat, water vapour, and CO2 between foliage surfaces and air. Temperature and air humidity in the canopy are related to the distribution of foliage area, affecting the distribution of energy and wind momentum in the upper canopy. In the lower canopy, the temperature is lower and humidity higher than in the upper canopy in relation to the transpiration and evapo-

Fig. 2.14  Left: Vertical profiles of temperature (T(z)), water vapour (e(z)), and wind velocity (u(z)) in relation to the foliage area density in the canopy of a tree stand. Right: Profiles of temperature (solid lines) and water vapour (dotted lines) in relation to the foliage area density

ration of water from the surface of soil. Both transpiration and evaporation are dependent on the precipitation, which is partly intercepted by canopy surfaces. The rest of the precipitation falls through the canopy onto the soil surface, where water is also evaporated. Excess water may run in surface flow from the site and infiltrate the soil profile. Excluding precipitation, other factors affecting water balance are related to the properties of tree stands and canopies, thereby having effects on the growth and development and structure of tree stands (Fig.  2.14) (Box 2.3).

2.3.2 R  adiation in Forest Canopy and Tree Crown, Interception of Radiation Foliage intercepts and reflects radiation, and only on the uppermost crown layer, the incoming radiation equals to that on the soil in a treeless area (Io, W m−2). On lower crown layers, the incoming

in the canopy of a tree stand before (time = 0–5 s), during (time = 5–30 s), and after (time > 30 s) the passage of a wind gust through a stand. The dashed arrows show the penetration of gusts in the canopy. (Landsberg and Gower 1997, pp. 73–74. Permission of Elsevier)

2.3  Interaction Between Climate and Forest Structure

Box 2.3: Foliage Distribution in a Scots Pine Crown

The structure of a tree crown is a hierarchical one formed by branches, shoots, and leaves/ needles. Branches refer to an assemblage of shoots attached to each other providing the platform for leaves and needles and the subsequent foliage mass and area. The crown structure further depends on the shoot structure and on the density and distribution of shoots in the crown space (Kellomäki and Oker-Blom 1981; Kellomäki and Oker-Blom 1983; Ross et al. 1986). In this context, the overall shape of the crown is species-specific (genetic) and dependent on the branch growth in different crown layers affected by prevailing growing conditions. In young boreal Scots pine, for example, the crown shape is regular, representing the cone-like upper part and cylinderlike lower part sharing the same bottom, regardless of the position of the tree in the stand (Fig.  2.15). The volume of the upper cone and lower cylinder is dependent on the length of branch main axes. In the upper crown, the branch length and number of shoots on branches increase down to the middle crown (branch whorl 7–8 from the stem apex), while in the lower crown, the branch length and shoot number reduce towards the crown bottom. This implies that the vertical distribution of shoots and needle mass through the crown is related to the birth, growth, and mortality of shoots in different parts of the crown over tree growth. In young boreal Scots pines, the distribution of foliage mass and area is normal or slightly skewed, with the maximum needle mass slightly below the middle crown. Such a distribution can be described with the β-function (Fig. 2.15) (Kellomäki et al. 1980):

  x   c   x  a   b  x  







(2.15)

where ρ is the needle density and x is the relative height in the crown from the stem apex. The factor a is the position at the lower crown,

31

b is the position at the upper crown, c is the scaling factor, and α and γ are parameters. Needle mass and area are located between the stem apex and crown bottom, when a = 0 and b = 1. Consequently:

  x   c  x  1  x 







(2.16)

The parameter values in Fig.  2.15 show that the new needles are located in the upper part of the crown, while older needles are in the lower crown. This vertical distribution of needle mass is independent of the structure of the tree stand (density, height of trees), while the horizontal distribution is dependent on the position of the crown in the canopy and spacing of trees. In dominating Scots pines, for example, the needle mass is distributed evenly through the crown space, even in the inner and lower parts of the crown. In dominated trees, needle mass is mainly located in the upper and surface parts of the crown, with no needles in the innermost lowest parts of the crown. In suppressed Scots pines, needle distribution resembles an umbrella, with the majority of the needles in the upper crown. The crown structure is further dependent on how branches and shoots are distributed in relation to the compass point (orientation). In general, this is even towards all compass points (Kellomäki and Oker-Blom 1983), whereas the branch angle in relation to the stem increases as a function of the location of branch whorls in the crown. In young boreal Scots pines, for example, the branch angle in the upper crown is 30–40° and in the lower crown 80–90°. In both cases, the branches were born at an angle of 30–40°, but the increasing mass of branches bends them over time in the middle and lower parts of the crown. At the same time, the new shoots are located horizontally around the branch main axis, while in the lower crown, new shoots are located in the horizontal position around the branch main axis (Kellomäki and Oker-Blom 1983).

2  Environmental Conditions, Site Types, and Climate Change

32

Fig. 2.15  Relative distribution of needles in Scots pine crown: A, 1-year-old; B, 2-year-old; C, 3-year-old needles. Right: The needle distribution in different age classes Needle age class, years One-year-old Two-year-old Three-year-old Total needle biomass

Parameter α 3.638 3.126 3.075 2.977

calculated using Eq. (2.15) with the parameters given below. (Kellomäki et al. 1980. Courtesy of Finnish Society of Forest Science)

Parameter γ 4.458 5.832 6.832 7.543

radiation (I, W m−2) is reducing as a function of the cumulative foliage area index (L(z)= ∑LAI (z), m2 m−2) downwards from the stem apex (Oker-Blom and Kellomäki 1981; Stenberg 1986): GL  I  z   I o  Top   exp   (2.17)  sin 

where z indicates the distance of a crown layer [m] from the stem apex (Top), θ is the sun’s ­altitude [degrees] and G is the extinction coefficient [dimensionless]. The extinction coefficient determines the ratio between the both-sided foliage area and one-sided foliage area projected on the surface perpendicular to the sun’s rays. The extinction coefficient is dependent on the sun’s

Relative location in crown 0.553 0.482 0.346 0.432

altitude and the position of needles or leaves in foliage (Fig. 2.16).

I  z   I o  Top   exp  k  L 



(2.18)

The parameter k =  G/sin θ  is also called the extinction coefficient, but it indicates the ratio between the both-sided foliage area and one-­ sided area projected on the horizontal surface. Thus, the coefficient G indicates the extinction of radiation as a function of foliage area (L/sin θ), while the coefficient k indicates the extinction of radiation as a function of canopy/crown depth or the cumulative foliage area index (L). Radiation is intercepted in a canopy compiled by tree crowns. In a dense tree stand, only a small

2.3  Interaction Between Climate and Forest Structure

33

Fig. 2.16  Values of extinction coefficients G (left) and k (right) as a function of the sun’s altitude and the needle/ leaf angle (θl) in relation to the horizontal surface. The

needle/leaf angle 0° indicates the position on the full horizontal and 90° on the full upright position. (Stenberg 1996. Courtesy of University Helsinki/Pauline Stenberg)

Fig. 2.17 Left (A): Fraction of radiation extinction. Middle/Left (B): Fraction of light interception of radiation. Middle/Right (C): Fraction of radiation on foliage, each factor being a function of leaf area index (L) when the extinction coefficient k  =  0.5 and 1.0 (Oker-Blom et  al. 1983; Stenberg 1996. Courtesy of University Helsinki/Pauline Stenberg). Right: Example of the mean

radiation on a clear-cut area and below the canopy of the nearby young Scots pine stand in the main growing season (April 15–September 15) in the middle boreal conditions (62° N). The calculation is done using the FinnFor model (Kellomäki and Väisänen 1997) for a stand with a density of 3000 trees per hectare, volume 60 m3 ha−1, basal area 24 m2 ha−1, height 10 m, and diameter 10 cm

fraction of radiation above the canopy penetrates the canopy and falls on the ground. The radiation intercepted in the crown Q(L) is:

The share of the intercepted radiation is dependent on the depth of the canopy or cumulative foliage area (L) and the value of the extinction coefficient. Large extinction implies large interception and vice versa as demonstrated in Fig. 2.17. The curves represent the given moment, and they change following the sun’s altitude. Furthermore, the position of needles/leaves

Q  L   I o  Top   I  L   I o  Top 

  G  L     1  exp    sin   

(2.19)

34

2  Environmental Conditions, Site Types, and Climate Change

affects the interception, which is large on the horizontal needles/leaves under a high sun ­altitude. Similarly, the interception is large on vertical needles/leaves under a low sun altitude. Momentary differences in relation to needle/foliage position and sun altitude are large, but over a longer period, their contribution to the total interception is small (Stenberg 1996). Figure 2.17 further demonstrates how a tree stand affects the radiation falling on the ground. In this case, the radiation over a growing season (April 15– September 15) below a Scots pine crown is about one-third of that falling on the nearby clear-cut area. In the latter case, there is, therefore, much more energy for evaporation and heating, both further affecting soil moisture and temperature. Trees and canopy reduce the variability in the inflow/outflow of energy and temperature, e.g., reducing the risk of night frost in the main growing season compared to the situation in the clear-­ cut area.

2.3.3 E  vaporation of Water in Forest Canopy

Fig. 2.18  Left: Outline of the main processes controlling the water balance on a site occupied by trees under the control of climatic factors and properties of soil and the tree stand. Right: Evaporation from young Scots pine stand and a nearby clear-cut area in the main growing season (April 15–September 15) in the middle boreal condi-

tions (62° N). The calculation is done using the FinnFor model (Kellomäki and Väisänen 1997) for a stand with a density of 3,000 trees per hectare, volume 60  m3 ha−1, basal area 24 m2 ha−1, mean height 10 m, and mean diameter 10 cm

Water in precipitation (water/snow) falls on soil through the canopy, where some precipitation is intercepted and evaporated (Fig.  2.18). Evaporation of water from the wet canopy is affected by the properties of foliage and ­atmosphere, as is the case for evaporation from the ground surface. Water on the surface may flow in surface flow, infiltrate the soil profile and percolate more deeply to groundwater outside the rooting zone, or evaporate from the surface pool. Water in the rooting zone is further taken up by trees and lost to the atmosphere in transpiration, which is controlled by the properties of foliage and atmosphere. Evaporation from the water pool on the wet surface of the canopy/soil is dependent on the balance between incoming precipitation (P, mm) and intercepted water evaporated from canopy

2.3  Interaction Between Climate and Forest Structure

surfaces, and water infiltrated through the canopy onto the soil. Water intercepted on the canopy surfaces (AWV, mm) is equal to the interception (INTERCEPT, mm) minus evaporation (EVA, mm): AWV = INTERCEPT – EVA. The daily climatic potential of evaporative water loss (PEV, mm d−1) can be calculated using the Penman-­ Monteith equation (Jarvis and McNaughton 1986; Monteith and Unsworth 1990): PEV 

s  Rnc   a  C p  ( es  Ta   ea  / rac s   1  rsc / rac   Hv

(2.20)

where s is the slope of the curve relating saturation water vapour pressure [Pa oC−1] to temperature in the range of air temperature (Ta, oC) to saturation temperature (Ts, oC), Rnc [W m−2] is the radiation intercepted on the surface, ρ is the air density [1.220  kg  m−3], Cp is the specific heat capacity of air at a constant pressure [1004.0 J kg−1 °C−1], es(Ta) is the saturated water vapour pressure [kPa], ea is the water vapour pressure [kPa], rac [s  m−1] is the aerodynamic resistance of the surface, γ is the psychrometric constant [66.0  Pa oC−1], rsc is the surface resistance [s  m−1] when water exists, and Hv is the vaporization heat of the water [2260 kJ kg−1]. The water bound on the canopy surface (AWV, mm) is a function of the water capacity of the canopy surface per unit area (c, mm m−2), the amount of precipitation (Precip, mm), and the surface area of the canopy (L, m2):

Intercept  d   min  c  L,Precip  d   AWV 

(2.21)

Thus, the canopy binds an amount of water that is equal to its capacity (c × L) or the amount equal to the amount of water already bound on the canopy, plus the water falling on the canopy in precipitation. Furthermore, the interception and evaporation allow the fall of precipitation through the canopy onto the soil to be calculated (INFIL(d), mm):

INFIL  d   max  0,Precip  d   AWV  c  L 

(2.22)

35

where the water bound on the canopy surface (AWV, mm) is the difference between the interception and realized evaporation (E(d), mm): AWV = Intercep(d) – E (d). Precipitation falling on the ground is the share of precipitation falling through the canopy as demonstrated in Fig. 2.18 for a Scots pine stand with a closed canopy. A large proportion (60%) of intercepted water from precipitation is evaporated from canopy surfaces in the main growing period (April 15–September 15). At the same time, the evaporation from the soil surface in a clear-cut area is 40% of the evaporation. Consequently, the water flow on the soil surface and into the soil profile remains substantially smaller below the canopy than outside the stand, where the soil moisture through the soil profile is larger than below the canopy. In the latter case, the water uptake into transpiration reduces further the soil moisture in forest stands.

2.3.4 Wind in Forest Canopy In the canopy, wind force declines from the upper layers downwards (Fig.  2.19). The wind force anywhere in the canopy is stronger when the wind force is stronger above the canopy. Wind force is profiled in relation to canopy layers (Landsberg and James 1971): 2



  z  u  z   uh   1     1     h  

(2.23)

where u(z) is the wind velocity [m  s−1] at the height z in the canopy [m], uh is the wind velocity on the surface of the upper canopy layer at the height h [m], and α is a factor (Eq. 2.24 below).



  h

Cd  uh  L  6 K

0.5



(2.24)

where Cd is the drag coefficient [dimensionless], L is the mean foliage area density [m2 m−3] in the canopy and K is the momentum exchange coefficient (eddy viscosity), m2 s−1). With respect to conifers, the drag coefficient is Cd  =  0.32σ-0.42, where σ is the frontal area of shoot implying the

36

2  Environmental Conditions, Site Types, and Climate Change

Fig. 2.19 Wind velocity in the tree stand as a function of the height from the ground surface, the variability of mean foliage area density in the canopy representing the range of 1–5 m2 m−3 and the wind velocity above the crown being 5 m s−1, calculation based on Landsberg and James (1971)

total area of needles per the total area of shoot. In spruces, for example, the value of σ is 1.2 ± 0.5. The wind velocity is layered in a forest stand in relation to variable mean foliage area density and the wind velocity above the canopy as shown in Fig.  2.19. A high foliage area density reduces substantially the wind velocity even in the upper crown. This is especially pronounced if the wind velocity above the canopy is low. At a high wind velocity above the crown, the wind velocity is only slightly reduced even in the lower crown at a high foliage area density. Under a high wind velocity, the effects of the canopy on wind are small compared to the situation when the above canopy wind velocity is low.

2.3.5 Interaction of Microclimatic Factors in Forest Canopy: Temperature of Foliage In the canopy, climatic factors interact with impacts on foliage temperature. Temperature is related to the incoming radiation on the foliage in different parts of the canopy (Fig.  2.20). Furthermore, air humidity, wind, and the properties of foliage affect the heat balance in different parts of the foliage and the temperature difference between the air temperature and the tem-

perature of the foliage  shown in the Eq.  2.25 below. Tl  Ta 

 0.93M

Q Hf  E

a

 C p  / rb  4   Ta  273 

3

(2.25)

where Tl is the temperature of leaf [°C], Ta is the air temperature [°C], Q is the radiation [W m−2], Hf is a parameter with a value of 0.177, λ is parameter with a value obtained from the equation λ = 45,064–4Ta, E is transpiration [mm s−1], Ma is a parameter with a value of 28.97, Cp is the specific heat capacity of water [1.012 kJ kg−1 K−1], rb is the boundary layer resistance [0.29  s  m−1] and σ is the Stefan-Boltzmann constant [5.67·10−8 W m−2 K−4]. On a calm summer’s day with clear sky, the temperature of needles of boreal Scots pine is up to 1 °C higher than that of air temperature, especially in the upper canopy where the incoming radiation is high. Lower in the canopy, the temperature difference is smaller because the radiation reduces along with the canopy depth. However, the increasing wind velocity reduces the temperature difference, especially in the upper canopy where the wind velocity tends to be higher than in the lower canopy. Evidently, even a small increase in the temperature of foliage

2.4  Edaphic Conditions

37

Fig. 2.20  Outline of impacts of selected microclimatic factors on the heat balance in foliage. The insert shows the temperature difference between needles of Scots pine and

below air temperature calculated (Eq. 2.25) for the middle boreal conditions (62° N) using the FinnFor model (Kellomäki and Väisänen 1997)

enhances the photosynthesis in limited temperature conditions as found in boreal forests.

During the last glaciation, the bedrock surface was broken and the movement of ice ground stones into pieces of varying sizes, from large boulders to small stones (size >20 mm) and clay particles (size 95%) than in the period 1971–2000 (Jylhä et al. 2009). Temperature zones will shift northwards in such a way that in the last simulation period (2070–2100), the annual mean temperature in the south will be 9–10° C. At the same time, the mean annual temperature of 0 °C currently in the central country likely shifts northwards beyond the current northern timber line. These changes suggest that even in the first simulation period (1991–2020), the temperature sum will increase by 10–15% throughout the country (Fig.  2.36). During the second period (2021–2050), the increase will be 30–50%, with a further 50–90% during the third period (2070–2099). By the end of this century, the temperature sum could be 800–900 d.d. (currently 600 d.d.) in the northernmost and 2,000– 2,300 d.d. (currently 1,400 d.d.) in the southernmost parts of the country.

2.5.5 Climate Variability and Weather Extremes Climate change might further lead to extreme weather episodes: exceptionally high wind veloc-

2.5  Changes in Climatic and Edaphic Conditions Under Global Warming

53

Fig. 2.34  Simulations on the expected changing of climate based on the SRES A2 emission scenario over Finland for the selected periods (Kellomäki et al. 2005). Left: Annual mean temperature. Right: Percentage change in precipitation in the selected time periods (1991–2020,

2021–2050, 2070–2999) compared to the current climate (1961–2000). The lines and number on the maps refer to the administrative areas. (Courtesy of Finnish Environmental Institute)

ity, heavy rainfall, and high or low temperatures devastating infrastructure and properties and injuring humans. Even under the current climate, the occurrence of extreme weather episodes is poorly known, but local episodes of high wind and heavy rain/snow might increase. Based on weather statistics, Gregow et al. (2008) found that in the period 1961–2000, the mean wind velocity exceeded 14 m s−1 at least 155 times, and five times 17 m s−1 at inland sites. However, the frequency of strong winds is likely to increase marginally as shown by Ruosteenoja et al. (2018) based on simulations of geostrophic winds based on global climate models. They found that strong wind episodes may

increase by 0–2% in summer and autumn, while the increase in spring and winter is likely even smaller. The share of westerly winds is likely to increase more than that of easterly ones. In the same period, the average snow load on trees exceeds 20 kg m−2 a total of 65 times. The past weather records further show that in the north, very cold winter weather (daily minimum temperature below −20  °C, lasting 2–3 weeks) occurred once in every 20 years. In the south, the length of this cold weather was seldom longer than a week. On the other hand, summer temperatures exceed 31–32  °C once every 20 years on average, but hot weather with a daily

54

2  Environmental Conditions, Site Types, and Climate Change

maximum temperature above 25 °C lasting longer than 1 week occurs once every 20 years (Jylhä et al. 2009). Climate warming also affects the frequency distributions of mean, maximum, and minimum temperatures, all likely to shift towards higher values. The largest changes occur in the lowest daily minimum values in winter temperatures, thus reducing the variability in winter temperatures. Winter temperatures may increase to such an extent that the thermal winter (daily mean temperature is permanently 5 °C) would elongate by one to one and a half months. The lengthening is likely to be the largest in the southern parts of the country. By the end of this century, the length of the thermal growing season in the north might be the same as it is now in the south (Jylhä et al. 2009).

2.5.6 D  rought Episodes Under SRES and RCP Scenarios

Fig. 2.35 Recent IPCC climate change scenarios. Upper: Likely CO2 content in the atmosphere. Middle: Changes in temperature (annual means). Lower: Changes in precipitation (annual means) in relation to the current climate. Climate change represents scenarios RCP2.6, RCP4.5, RCP6.0, and RCP8.5 for the period 2010–2099, based on the Coupled Model Intercomparison Project Phase 5 (CMIP5) of IPCC AR5. (Venäläinen et al. 2020. Permission of Wiley & Sons)

Precipitation and warming affect the water balance on the surface of soil, with subsequent effects on water availability in rooting zones, affecting, for example, canopy conductance and further regeneration and growth of trees (e.g., Sturm et al. 1996; Granier et al. 1999, 2000). The available water is defined by the field capacity and wilting point specific to different soil types holding water. The frequency and duration of such episodes or drought episodes may be indicated by the number of dry days as used by Kellomäki et al. (2005) in assessing the availability of soil moisture and the vulnerability of boreal forests to drought. The number of dry days indicates the frequency of days when moisture in rooting zones is below the wilting point. Drought is an event of prolonged shortage of water for physiological and ecological functions of trees in the water cycle through the ecosystem. Drought affects trees directly by slowing or stopping growth, even injuring or drying trees. Drought also affects trees indirectly, by increasing their susceptibility to the risks of wildfire, insect pests, and diseases (e.g., Timofeeva et al. 2017).

2.5  Changes in Climatic and Edaphic Conditions Under Global Warming

Fig. 2.36  Changes in temperature sum for different climate change scenarios (RCP2.6, RCP4.5, RCP8.5) as per subperiods (2010–2039, 2040–2069, and 2070–2099) outlined by Kellomäki et al. (2018), based on Ruosteenoja et al. (2018). The temperature sum lines across the coun-

55

try separate the southern (TS > 1,200 d.d.), middle (1,000 d.d.   90% of that above the canopy if the radius >17.8 m or the area >1,000 m2. Expanding trees around the gap reduce the radiation only in a small part of the gap. In this case, the succession is cohort based rather than gap based, mainly driven by the loss of trees from patches, including several trees in

an area smaller than the area of the patch. Such patches represent openings allowing more radiation beneath the residual canopy, thus making it easier for several tree cohorts to establish and grow through canopy layers above (Box 7.1). The size, shape, and orientation of canopy openings affect how radiation, soil temperature, and precipitation are distributed in different parts of an opening. The properties of the opening affect most the share of opening exposed to direct radiation. In temperate and boreal forest, the sur-

7.3  Gap Dynamics, with Effects on Environmental Conditions

Box 7.1: Gap Size and Site Conditions

Radler et al. (2010) found that in small clear cuts solar radiation was very heterogeneously distributed but the radiation was 5–11 times higher than below the remaining canopy (measured at a latitude of 51° N). The maximum amount of radiation through the growing season was in northern parts and the minimum in south-­western parts of the clear cut. Radler et al. (2010) further found that the daily maximal soil temperature (at a 10 cm depth) was higher by up to 6  °C in northern parts of a clear-cut area than under the tree canopy. Soil temperature patterns were mainly related to seasonally changed incoming solar radiation, ground vegetation, and soil moisture. According to Radler et  al. (2010), the mean daily maximal air temperature measured at the clear cut was up to 2.5 °C higher and the mean daily minimal temperature up to 0.5 °C lower than in the surrounding forest. Pang et  al. (2016) also studied how gap size affects local microclimate, but they fur-

rounding trees cast shade in some parts of openings at any time of day. This is because the sun angle (the angle of incidence at which sunlight falls on the earth at a given time and place) is 50 m

232

7  Successional Dynamics of Boreal Forest Ecosystem

Fig. 7.8  Left/Above: Shaded and exposed parts of small forest opening under direct radiation. Left/Below: Apparent movement of the sun around a small forest opening. Right: Distribution of shaded and exposed areas in forest openings (patches) of various shapes, with an area of 0.2 ha each at a latitude of 44° N. (Marquis 1965. Courtesy of US Forest Service). Explanation of main concepts is below The shadow length (S) cast by the surrounding trees: S = h/tangent a, where h is the height of surrounding trees and a is the angle of sun elevation (altitude).

The sun altitude: sine a = (cosine L) × (cosine d) × (cosine H) + (sine L) × (sine d), where L is the latitude, d is the sun declination, and H is the sun hour angle (i.e., 15 times the number of hours from solar noon). The horizontal angle between the sun and true south (sun bearing, Z): tangent Z  =  sine H/(cosine L)  ×  (cotangent p)  –  (sine L)  ×  (cosine H), where p is the polar angle (90° – sun declination).

allowed any gap receiving >75% of the radiation in the nearby open area. When the gap diameter was less than 25  m, the radiation was 50% or less, and 25% or less under the gap diameter of 10 m. Evidently, the radiation tended to stabilize when the gap diameter was 110–120 m. Coates and Burton (1997) further emphasized that under gaps of 110  m in diameter, the total gap area (65% of the total area) received radiation of more

than 75% of that in an open area. A further increase of the gap size increased the percentage of the area with full radiation. According to Coates (2000, 2002), there is a strong and consistent trend in the growth response among conifer seedlings to increasing gap size from a small gap up to a large gap of 1,000  m2. Thereafter, the growth response to the gap size levels off. In medium-large and large gaps (301–1,000 m2), the

7.3  Gap Dynamics, with Effects on Environmental Conditions

233

Fig. 7.9  Percentage of gap area receiving the same photosynthetic photon flux density as that in the upper canopy of a cedar-hemlock forest in north-western British

Columbia, Canada (55° N), in the period April 15– September 15 as a function of the gap diameter/area. (Coates and Burton 1997. Permission of Elsevier)

largest growth of seedlings was in the middle gap regardless of species, but the differences between the sunny north and shady south positions were small, apart from lodgepole pine (Pinus contorta) growing poorly in a southern position. The growth response of light-demanding lodge pine exceeded the response of the other species in large gaps (1,001–5,000 m2).

soil moisture along with the distribution of radiation in different parts of an opening in a semi-­ natural beech-dominated (Fagus sylvatica L.) forest in Denmark (55° N). Spatial and temporal distribution of photosynthetically active irradiance (IP), soil and air temperature (TS and TA), and soil water content (SWC) were monitored until the third growing season since natural formation of the gap (Fig. 7.10). As expected, radiation was largest in the northern part of the gap. This further held for the nearby forest in the middle of summer, whenever the contribution of direct radiation was dominant. Monitoring further showed that the total radiation in the southern part of the gap and at the gap edges decreased to 20% from the first to the second year after gap formation, i.e., the decline related to the growth of the canopy and subcanopy of trees near the edges of an opening (Ritter 2005; Ritter et  al. 2005; Ritter and Bjørnlund 2005). In contrast to radiation, the maximum and mean soil temperature (at a depth of 5 cm in mineral soil) were generally highest in the southern central part of the gap. Soil temperature was

7.3.3 Hydrological Conditions in Gaps In addition to the radiation, the openings of forest canopy also modify environmental conditions in other respects compared to those under the canopy. Gray et al. (2002) found that summer solar radiation and soil moisture were related to the gap size and position in the gap. Soil moisture was largest in gaps of intermediate size of several trees and tended to decline for single tree gaps, especially on the north side of gaps. Similarly, Ritter et  al. (2005) measured how the canopy opening changes the soil and air temperature and

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7  Successional Dynamics of Boreal Forest Ecosystem

Fig. 7.10 Mean irradiation (Ip), soil temperature, air temperature, and soil water content (SWC) in the north-south (above) and west-east gradients in the period May 12– September 13, 2001, in the Danish monitoring site. (Ritter et al. 2005. Permission of Elsevier)

equally high at the center of the gap in late spring and summer, with consequent effects on the available nitrogen (Fig.  7.11). The spatial variability of soil temperature was small compared to that in soil moisture. In summer, for example, the soil water content down to 50  cm was close to field capacity in the gap, but moisture was higher than that under the closed canopy. Ritter et  al. (2005) further found that the soil water content declined from the first to the second monitoring year. The growth of trees at gap edges likely increased the light interception, and consequent shading and further the extraction of water at gap edges.

7.3.4 Soil Disturbance and Nutrients in Gaps In boreal forests, thinning and clear cut tend to enhance the nitrogen mineralization of soil organic matter over 3–5 years following soil disturbance and the addition of litter in harvest residues (Prescott 2002; Prescott et  al. 2003). This also holds for gaps in natural forests depending on the gap size and the impacts of disturbance on the cycle of nutrients related to the scale and intensity of the disturbance. For example, the uprooting of single trees or several trees in patches increases the transfer of nutrients from tree cover to soil, thus increasing the nutrient

7.3  Gap Dynamics, with Effects on Environmental Conditions

235

Fig. 7.11  Soil water content (%) at a depth down to 50 cm in the canopy opening and in the nearby forest outside the opening. (A) the mean value for July; (B) the

mean value for August; (C) the lowest value in September; and (D) the location of large trees in and outside the opening. (Ritter et al. 2005. Permission of Elsevier)

cycle at the community level. Coulombe et  al. (2017) further defined how clear cut and the forest structure representing commercial thinning resembling the pre-commercial structure (harvest gap size 0.05  ha) affected the nitrogen cycle in stands dominated by balsam fir [(Abies balsamea L.) Mill.]. The increase in nitrogen mineralization along with the increase in the proportion of nitrate (NO3) and ammonium (NH4) nitrogen was related to the increase in soil temperature and water content. According to Coulombe et  al. (2017), the threshold of nitrogen cycling in relation to the size of a thinning-induced gap was equal to the removal of one to three trees representing a gap size of 500 m2. The changes in nutrient cycle are further related to the changes in litter fall and decay rate, which are increased by pit-and-mound formation in the soil profile. This is especially the case for stand-replacing disturbances. In this case, the lit-

ter fall is substantially larger than on the scale of trees and patches. On the other hand, stand-­ replacing disturbances tend to mix the organic layer and underlying mineral layers when trees are uprooted due to excessive wind force. Consequently, root-soil plates become upright, thus disturbing the soil profile, representing the main location of roots in soil. Over time, roots decay and soil and root-soil plates form mounds representing partly open mineral soil providing a favorable microsite for the seedbed and establishment of seedlings. Lyford and MacLean (1966) demonstrated that uprooting with subsequent soil disturbance is likely a continual process and enhances the regeneration of both coniferous and deciduous trees in temperate and boreal conditions. This is indicated by the main location of trees on mounds on which trees have grown larger than on other microsites such as in pits or intermediate surfaces between mounds and pits.

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7  Successional Dynamics of Boreal Forest Ecosystem

The same was also found by Ulanova (2000) for the central Russian Plain occupied by boreal forest. Soil surface was covered by mound-pit topography of up to 25%, especially after widespread windthrows representing the wind velocity ≥20 m s−1 (Fig. 7.12). The recovery of soil after uprooting is dependent on the structure and properties of soil and the scale of pit-and-mound topography. According to Ulanova (2000), the rate of soil recovery after uprooting varied depending on the rooting depth, e.g., under shallow uprooting, the recovery was likely to be completed in 100 ± 200 years, but 200 ± 300 years after uprooting had occurred in communities with deep rooting (Fig.  7.12). In the recovery, the spatial distribution of trees tended to follow the pit-and-­ mound topography regardless of the forest type. Ulanova (2000) further found that the regeneration of Norway spruce was more successful on mounds than on undisturbed soil. In the southern

boreal zone, multi-aged regeneration tended to be commonly related to soil disturbance, with the pit-and-mound topography covering 7 ± 12% of the soil surface. The share of pit-and-mound topography was further increased along with the increasing intensity of disturbances. The share of pit-and-mound topography was up to 15 ± 25% following stand-displacing disturbances. The scales of windthrow gaps in space and time seemed to affect substantially the structure and concurrent functioning of ecosystems and multi-­ aged establishment of trees (Ulanova 2000). Blown-down trees or forest patches with mix soil horizons, thus, expose fresh parent soil to weathering in pit-and-mound microrelief. Such disturbances further affect the dynamics of water, nutrients, and ground vegetation when mixing soil organic matter and mineral soil in the soil profile down to the main rooting depth. However, the impacts on soil properties in the profile remain smaller than disturbances induced by fire

Fig. 7.12  Left: Outline of the dynamic processes in soil profile after uprooting of Norway spruce after A: 0–1, B: 30–50, and C: more than 100  years since uprooting. Right: Soil profile in pit-and-mound complexes A: 20–30,

B: 50–60, and C: 80–100 years since windthrow in podzolic soil in southern taiga zone in eastern Europe. (Ulanova 2000. Permission of Elsevier)

7.3  Gap Dynamics, with Effects on Environmental Conditions

in the scale of patches and landscapes, with impacts on biologic, chemical, and physical properties of site. The effects of fire are dependent on the intensity and duration of burning. Changes in soil surface represent the accumulation of ash, charcoal, and partially burned soil organic matter (partially burned stem wood, litter, and humus). This increases the radiation absorption and temperature in the soil surface, with effects on ground vegetation, organic matter on the forest floor, biogeochemistry, and hydrology in sites. Nitrogen, for example, tends to ­volatilize in fires, while increasing amounts of ash with mineral nutrients (phosphorus, potassium, calcium) may enhance the growth of seedlings under higher soil moisture. Even on the landscape scale, the post-fire succession may rep-

Fig. 7.13  Climatic conditions and carbon dynamics in a forest opening after clear cut in the growing season before reforestation in the late summer following timber harvest in a mixed spruce/birch/aspen forest in southern boreal zone in European Russia (56° N, 33° E). (Mamkin et al. 2016. Courtesy of IOP Science/Open Access). Explanation of main concepts below

237

resent rapid recovery of vegetation, because of improved seedbed for germination and initial growth of seedlings under reduced competition in relation to ground cover species (Certini 2005).

7.3.5 C  arbon Dioxide, Energy, and Water Fluxes in Gaps, with Atmospheric Interaction Disturbances with openings in forest canopy affect the biophysical and biochemical interaction between forest and atmosphere as Mamkin et al. (2016) show to occur when monitoring a small clear cut in a southern boreal forest patch (Fig. 7.13). They found that airflow in the clear cut was most affected close to the ground at the wind-

Left/Upper: Modelled pattern of horizontal wind velocity Left/Lower: Turbulent exchange along transect over the clear cut from south to north Right/Upper: Diurnal variability of latent heat (LE), sensible heat (H), soil heat flux (G) Right/Lower: Diurnal variability net ecosystem exchange (NEE), total ecosystem respiration (TER), and gross primary production (GPP)

7  Successional Dynamics of Boreal Forest Ecosystem

238

ward edge of the gap, while the effect was small at the leeward edge. They further found that the site turned immediately into a CO2 source after cut, but this later decreased following the growth of ground vegetation. In the main growing season, the daily net ecosystem exchange (NEE) varied from small source to small sink depending on solar radiation, temperature, and soil moisture, with a zero balance between the CO2 uptake and emission. Over the period from April to August, the total CO2 emission from the clear-cut area (155  g C m−2) indicated that the gap area was a CO2 source before reforestation. In the main growing season, the daily fluxes of sensible (H) and latent (LE) heat were closely controlled by net radiation and the amount of ground vegetation in the gap area, where soil moisture was high enough throughout the growing season (Mamkin et al. 2016). The situation seems to be different for poor sites.

7.4

Structural Dynamics of Boreal Forest Over Time

7.4.1 Regenerative Properties of Selected Tree Species Macroclimatic conditions, for example, limit the main distribution area of Norway spruce and birch in the southern and middle boreal forests, while the distribution area of Scots pine extends through the boreal zone up to the Arctic timber

line (Table 7.2). These species regenerate through seeds (sexual regeneration) or also buds like birch (asexual regeneration) whenever their requirements meet the site conditions provided by disturbances. On the other hand, the structure and properties of parent trees affect the regeneration: parent trees are mature (tall) enough and grow in spacing, allowing necessary seeding even in large gaps. Seed crop in birch, for example, is frequently large even in younger and smaller trees than in the case of Scots pine and Norway spruce. Furthermore, the dispersal of birch seeds is wide, and the germination capacity of seeds lasts longer than that of conifers. Typically, birch rapidly invades sites of medium and high fertility whenever growing space is made available in gap-forming disturbances. However, the high demand for resources (light, water, nutrients) makes birch susceptible to being outcompeted by shade-tolerant Norway spruce.

7.4.2 G  rowth Properties of Selected Tree Species Macroclimate limits substantially the growth of Norway spruce and birch through the northern boreal zone (Table 7.3). On the other hand, Scots pine needs less water and nutrients than Norway spruce and birch, but Scots pine is shade-­intolerant like birch. Scots pine needs more irradiation like birch to obtain a high photosynthetic rate. This is

Table 7.2  Outline description of regenerative properties of Scots pine, Norway spruce and birch regeneration or possible regeneration Factor affecting success of regeneration Scots pine Norway spruce Macroclimate, lower limit 10 11 Mean annual temperature in Finland, °C Mean annual temperature sum in Finland, d.d. 400–500 500–600 Properties of parent trees 60 80 Age at start of abundant seed crops, year Cessation of abundant seed crops, year 260 180 Total time for abundant seed crops, year 200 100 Initial dominant height for abundant seeding, m 15 20 Optimal spacing of parent trees, trees ha−1 50–120 15–250 Capacity to form canopy gaps Large Small Seed crop No No Seed bank Time for formation of seed, year 3 2 Maximum seed crop, seeds m−2 450 3500

enhancing/slowing Birch 10 400–550 40 100 60 10 30–80 Large Yes 1 200,000 (continued)

7.4  Structural Dynamics of Boreal Forest Over Time

239

Table 7.2 (continued) Factor affecting success of regeneration Cycle of abundant seed crop, times per 10 year Annual mean seed crop, seeds m−2 Share of empty seed, % Total seed crop over life cycle, seeds m−2 Share of seed from dominant trees, % Share of seed from suppressed tree, % Spreading of seeds Weight of seeds per 1000 seed, g Spreading distance at wind speed 2 m s−1, m Germination and necessary seedbed Cold treatment needed Temperature for germination, °C Light for germination, % of full light Soil moisture needed for germination, % Effect of soil mounds on establishment Effect of open mineral soil on establishment Effect of humus and mosses on establishment Germinates (initial seedlings) Need of light, % of full daylight Risk of mortality due to fungal attack Risk of mortality in temperature 1000 40–80 900,000 Main part – 1–2

100 Yes

150 Yes

200 Yes

5–7 0.005 40–70 Enhance Enhance Decline 60

5–7  infiltration rate) may result in surface flow, but the risk tends to increase in managed forests. Clear-cutting or thinning further reduces

the evapotranspiration, thus increasing the risk excess surface flow (e.g., Chen et  al. 2014). Management and harvest operations tend to compact soil, thereby reducing infiltration and creating water channels like trails of harvest machines or like ditches in soil management. In these cases, the risk of surface flow is local rather than regional, in contrast to the excessive flow risks related to the drainage of peatlands on the watershed scale. In peatland-rich forest regions, drainage may result in flooding. Drained peatlands loose a part of their capacity to retain rainwater and water originating from melting snow. In the watershed context, the water flow from the watershed is affected by the size, form, and share of lakes in the total watershed area, thus affecting the capacity to store water and to level off the flow rate in the main flow channels (Fig.  17.38). In the forestry context, the area and location of cuttings

Fig. 17.38  Left: Schematic presentation of the structure of pristine and drained fens and bogs in relation to the recharging of groundwater from precipitation and surface water from surrounding sites, and the effects of drainage

on groundwater in mires. (Gong et al. 2012. Permission of Elsevier). Right: Schematic presentation showing how the ditching in the sections A and B in the watershed affects the maximum flow in the main channel in the watershed

17.4.4 Controlling Excess Water Flow

17.4 Management for Regulating Services

and soil management, including ditching and soil disturbance in upland sites, affect the performance of the watershed. They affect how fast water from different parts of the watershed flows to the main channels leading water outside the watershed. Hazards are further affected by peatland types, which mainly characterize the regions. In this respect, drained peatbogs retain water more than drained mires, where drainage effectively reduces the water storing capacity. The location and the area of drained peat sites in the watershed affect the water flow in the main outflow channel as demonstrated in Fig.  17.38. Draining of the upper part of the watershed (case B) tends to increase the excess flow in the lower parts of the outflow channel and surrounding land because of the increasing maximum outflow but not to increase the capacity of the main channel to lead extra water outside the watershed. The situation is the opposite when the lower part of the watershed (case A) is drained before the upper part of the watershed, thus mitigating the maximum outflow rate. The concurrent drainage of lower and upper parts of the watershed increases outflow but the maximum flow rate falls between cases A and B. Evidently, the location of a drainage project acclimatized to the properties of the watershed is likely to reduce the

Fig. 17.39  Schematic presentation of the capture of particles in shelterbelt/forest at seashore. Rough forest cover creates turbulent eddies and increases their size, bringing more particles into contact with forest vegetation, thus

557

risk of excess water flow when using peatlands in forest production.

17.4.5 Controlling Air Impurities Forest reduces impurities in the air (or air pollution), i.e., harmful substances including dust, particles, and molecules of gaseous substances emitted into the atmosphere. Pollution may cause diseases, allergies, and death in humans. Pollution also damages other organisms, including animals, food crops and trees, as well as the natural environment and infrastructure as buildings. Forests filter air, which flows through the canopy and canopy space between trees (Fig. 17.39). The removal of air impurities is based on the sedimentation, adsorption, and absorption of particles and gaseous impurities in vegetation and soil. Filtering is active when air flows through tree stands, slowing the flow rate. The consequent reduction of the flow rate enhances the sedimentation of particles carrying harmful chemicals. Filtering is passive when tree stands form a barrier slowing down airflow. On the other hand, airflow rises and forms turbulences and stoppages in airflow behind the barrier. This changes the direction, flow rate, and pressure in air, which enhances

reducing their density in the air. (Tukle et  al. 2006. Courtesy of Food and Agriculture Organization of the United Nations)

558

the mixture of impurities in the airflow and the sedimentation. Sedimentation is especially important for removing large particles, while hovering small particles and liquid drops may be attached to surfaces of foliage of trees, shrubs, and ground cover. Particles might be washed down into soil in the fall of water and snow on the surfaces of crowns and canopies. Impurities may further be bound in biomass when gaseous impurities enter the synthesis of biomass through stomata and through the uptake of water and nutrients from soil. The sedimentation capacity of trees in stands and larger areas increases along with the increasing height of trees, thus reducing the flow rate in the wide space behind the canopy (Warren 1972). At the same time, the increasing spacing improves the access of airflow with particles within forest. However, the sedimentation rate tends to level off if spacing is too wide with little or no effect on the flow rate of air. In boreal conditions, coniferous stands before regeneration cutting might have a high sedimentation capacity of up to 10,000–20,000 kg ha−1 year−1, the density of particles in air likely being one-third of that outside the tree stands (Herbst 1965; Dimitri 1976). The sedimentation capacity may also be high in temperate deciduous forests, where the density of particles might be 2,000 (diameter > 0.1 μm) per liter, while outside the forest the density might be 9000 particles per liter (Robinnette 1972). In such conditions, a shelterbelt of 200 meters wide might reduce the density of particles per liter of air by 75%. Depending on the properties of the forest cover, even the density of submicroscopic particles (diameter 15 m s−1, with Extreme wind episodes may devastate a huge velocity of gusts up to 30 m s−1, seems to be the amount of timber as occurred in France in the threshold for wind damages, including uprooting winter of 1999, when 170 million m3 of wood of whole trees or breaking the stem in the crown was destroyed in two episodes. Losses were also area or lower. In boreal forests, major wind damlarge in southern Sweden in the winter of 2005, ages have involved extremely high mean  wind when 80 million m3 of timber was destroyed in a velocity (>19 m s−1, with about double the velocsingle storm episode (Fitzgerald and Lindner ity in gusts) combined with snowfall. However, 2013). In Finland, damages in single-storm epi- wind-induced damage frequently occurs on a sodes tend to be smaller than in more maritime smaller scale, resulting in continuous losses of conditions in western central Europe, but storm-­ timber, representing single trees or a few trees like winds also create unpredictable variability in creating small gaps. Even small-scale damages the timber supply. For example, strong winds are tightly linked to wind velocity, but vulnerabilblew down more than 11 million m3 of timber ity to wind damage is related to the properties of between 1975 and 1985 (Laiho 1987) (Fig. 18.3). trees and stands, e.g., to species, height and diamIn recent years, large damages occurred in the eter, crown area, rooting depth, and spacing summer of 2010, when 8.1 million m3 of trees (Coutts 1986) (Fig. 18.4). However, major wind

18.2  Risk of Wind Disturbances and Damages

605

Fig. 18.3  Damages to forests  in monetary terms leading to compensation by insurance companies annually in the period 1980–2016. (Venäläinen et al. 2017. Courtesy of Ari Venäläinen, Finnish Meteorological Institute)

Fig. 18.4 Interaction between main properties of forest landscapes, tree stands, and trees, with wind-induced impacts on the risk of damages for forestry. (Heli Peltola, unpublished). (Courtesy of University of Eastern Finland/Heli Peltola)

606

18  Risks for Forestry Under Current and Warming Climate

damages cannot be avoided or reduced through management, but proper management may increase/reduce the intensity and extent of damages. For example, thinning into wide spacing allows wind to penetrate deep into the canopy, with a subsequent increase in the wind load on trees, while  unthinned stands or narrow spacing tend to dissipate airflow, thereby reducing damages. The probability of damage decreases with the time elapsed since thinning, i.e., the growth of remaining trees increases the strength and thus the ability of the stem and roots to resist dynamic wind load (e.g., Peltola 1996) (Fig. 18.4). Figure 18.5 shows how wind velocity capable (critical wind speed) of uprooting or breaking a tree depends on the properties of the tree when snow of varying mass is attached to crown (Peltola et  al. 1999a, b). In general, a tree is blown down more easily than the stem breaks regardless of the properties of the tree. The

uprooting and breaking wind velocity varies in relation to tree height, stem form, and snow load. However, the breaking velocity is larger than the uprooting one. For uprooting, the critical wind velocity without snow load declines is from 15 to 25 m s−1 when the tree height increases from 12 to 20 m. When snow load is assumed, the critical wind velocity reduces to half of that under no snow load. The critical wind speed further reduces if the crown length in relation to the total tree height increases. On the contrary, critical wind speed increases if the stem diameter increases in relation to the tree height, with the stem form turning from a cylinder towards a cone. According to Fig.  18.5, the critical wind velocity for turning and breaking is higher in the trees of the same height, with the stem form (tree height/diameter at breast height, H/dbh) being a cone (stem form 1:80) rather than a cylinder (1:120) (Box 18.1).

Fig. 18.5  Critical wind speed in Upper Panel (A) for turning and in Lower Panel for breaking Scots pines (B) at stand edge as a function of tree height, stem form, and

snow load. (Peltola et  al. 1997. Courtesy of Canadian Science Publishing)

18.2  Risk of Wind Disturbances and Damages

607

Box 18.1: Outline of Mechanisms for How Wind and Gravity Affect the Failure of Trees

The threshold wind speed (critical wind speed) for uprooting or breaking trees is determined by the bending moment affecting the crown and stem (Jones 1983; Peltola 1996). The total torques exposed to stem and roots (MT) include that induced by wind force (M1) and the displacement (M2) of the upper stem and crown from the upright position (Fig.  18.6). The torque exposed to the stem butt is given in the Eq. 18.1

M T = M1 + M 2 = f1 × d1 + f2 × d2

(18.1) where f1 and f2 are the forces due to wind and gravity, and d1 and d2 are the distances used in calculating the respective turning moment. Wind force is dependent on the wind velocity and the crown area:

f1 =

1 2 × ρ × Cd ( z ) × u ( z ) × a ( z ) 2 (18.2)

where ρ is the air density [kg m−3], Cd(z) is the drag coefficient indicating the horizontal component of wind force at the height z in the crown, u(z) is the wind velocity [m s−1], and a(z) is the crown area [m2] against the wind direction. The total wind force exposed on crown is: H

f1 =

1 2 × ρ × ∫Cd ( z ) × u ( z ) × a ( z ) dz 2 0

(18.3)

18.2.2 Wind Force and Uprooting Trees Wind load may uproot or even break a tree whenever the total moment exceeds the strength of the root system or stem. Fraser and Gardiner (1967) pulled down Sitka spruce (Picea sitchensis) trees when the pulling power was 10–70 Nm depend-

where H is the tree height [m], and the values of Cd = 0.5 × ρ × u2 × a. Wind sways the tree around the stem butt. The subsequent displacement of the mass of stem and crown from the upright position induces the turning moment: M2 = f2 × d2 = m × g × d, where m is the mass of the tree [kg], including snow load on crown surface, g is the gravity constant [m s−2], and d is the displacement from the upright position. W ∆H 2 The value of d2 = , where W is the 3∆E ∆I stem mass [kg], E is the modulus of elasticity of the stem, and I is the moment of inertia. The bending moment is resisted by the bending strength (S, Pa), which for a beamlike cylinder is:



S=

T × dbh 2× I

(18.4)

where dbh is the stem diameter [m] and I inertia [m4]. The root system resists uprooting through the supporting moment (RS, Nm):

RS =

g × M × RSm Arsw

(18.5)

where g is the gravity constant, M is the mass of roots and soil in the area defined by the root system (root/soil plate, kg), RSm [m] is the mean depth of the root system, and Arsw is a parameter. If the turning moment exceeds the strength of the stem or roots, the stem breaks or the tree turns down.

ing on the height and mass of the trees (Fig. 18.7). They further found that the soil properties had a large effect on the critical wind velocity. On coarse-grained soils, such as sands, the critical wind velocity was double that on fine soils such as on clay. Regardless of the site, the critical wind velocity was a double one to uproot a tree with a height of 5 m compared to a tree with a height of

608

18  Risks for Forestry Under Current and Warming Climate

Fig. 18.6  Left: Mechanisms of wind-induced damage as a balance of turning and resisting forces to stem and root systems. Right: Schematic presentation of how to calculate forces imposed on trees induced by wind and gravity

20 m. The uprooting is gradual rather than sudden, the latter holding only for a wind gust of extreme velocity. However, even slow wind velocity sways trees, swaying the stem butt and moving roots and weakening the anchorage. This implies that the capacity of trees to resist wind load is smaller than that found in pulling experiments (Fraser 1964; Fraser and Gardiner 1967; Mayhead 1973; White et al. 1976). Uprooting under swaying is further dependent on whether the swaying is regular or random. Regular swaying with a proper frequency seems to be detrimental even under low wind velocity, if wind gusts and swaying are in resonance with each other. For example, White et al. (1976) found that the swaying frequency in Sitka spruces (Picea sitchensis) was 0.36 Hz at the upper stem and 1.1 Hz at the butt. Swaying decreased rapidly depending on whether the

branches in a tree overlapped with branches of nearby trees, thus limiting the swaying amplitude. In thinning, overlapping of branches is removed/reduced, thus increasing the potential swaying amplitude and the velocity and turbulence of wind. Wind damages are further related to the structure of forest landscapes, the structure of stands, and the management used to modify the structure. Wind damages related to harvest are further dependent on whether the harvest creates places where free airflow is curbed (Fig. 18.8). Such a situation may be created when a clear-cut area on flat terrain is extended onto the slope of a nearby hill or meets the edge of uncut forest. Now, air flows freely over the open flat area, but on the slope or at the forest edge the wind velocity increases. This is because the same amount of air flows onward as over the open flat area.

18.2  Risk of Wind Disturbances and Damages

609

Fig. 18.7 Upper: Critical wind velocity uprooting Sitka spruces (Picea sitchensis) as a function of tree height and soil type. Lower: Torque at the stem butt of an uprooted Sitka spruce as a function of the stem mass and soil type. (Fraser and Gardiner 1967. Courtesy of Crown copyright 1967)

Consequently, trees on the windward slope might be uprooted by increased wind force. Trees might also be damaged even on leeward slopes, where the tree crown extends up to the enhanced wind force. The variability of direction in the edges of clear-cut areas also increases damages. This is because the variability of edges increases the variability in the velocity and turbulence of airflow. Damages might be reduced if the harvest is topographically located in such a way that the

airflow is directed towards tree stands and forest edges, which are resistant to wind force. The force exposing trees is the greatest in the narrow area of a stand behind the edge towards the open area (Fraser 1964). Deeper in the stand, the wind force declines rapidly, and the wind velocity in the stand stabilizes in a distance related to the height of the trees from the stand edge (Fig. 18.8). However, the properties of the stand edge and the size of clear-cut area (gap size) affect substantially the wind force: thinning or wide spacing

610

18  Risks for Forestry Under Current and Warming Climate

Fig. 18.8  Upper/Left: Schematic presentation of how topography affects airflow from clear-cutting area towards hill slope. Upper/Right: Schematic presentation of how the velocity of wind from clear-cutting area increases and uproots trees when meeting the forest edge. Below: Normalized turning moments (Tnorm, 0–1) and critical wind velocity for uprooting (u(h)upr, m s−1) and stem

breakage (u(h)break, m s−1) in relation to the situation at the forest edge as a function of the stand density and the distance in terms of tree height (h) from the edge for a boreal Scots pine stand of 20  m high and breast diameter of 20  cm, with varying spacing exposed by wind.  (Peltola et al. 1999a, b. Courtesy of NRC Canada)

and increasing gap area increases the wind force exposed to trees. Similarly, roads through forest create wind channels, where the wind velocity may be exceptionally high, thus uprooting trees in the immediate vicinity of the roads (Peltola et al. 1999a, b).

18.2.3 Wind Risks Related to Thinning and Fertilization Management combining thinning and fertilization tends to increase the vulnerability of trees to wind damages. In thinning, the core issues affect-

18.2  Risk of Wind Disturbances and Damages

611

ing the probability of damages are: (i) what the developmental phase at thinning is; (ii) how intensive thinning is used; and (iii) how long the time is since thinning. Persson (1974, 1975) found that a thinning intensity greater than 30% of the basal area removel increased the uprooting

of Scots pines and Norway spruces (Fig.  18.9). This is especially the case when mature thinning stands are located at the edges of a clear-cutting area. Consequently, wind damages increased as a function of the dominant height (or maturity) of trees in such a way that the majority of damages

Fig. 18.9  Upper: Percentage of uprooted trees related to the total basal area before damage of Norway spruces in thinned forest as a function of the thinning intensity in percentage of the removed basal area (Persson 1974, 1975). In the insert, the relative total windthrows of Scots pine and Norway spruce as a function of the width of

strip-road and depth of harvest tracks. (Kyttälä 1980. Courtesy of Natural Resources Institute Finland). Lower: Percentage of uprooted trees of volume  related to total volume before thinning as function of dominant height and time in years from thinning (Persson 1974, 1975)

612

18  Risks for Forestry Under Current and Warming Climate

occurred immediately after thinning. However, trees were still uprooted 5  years after thinning even though the exposure of trees to wind force declined. Under regular thinning, fertilization may increase the risk of wind damage. This is because fertilization increases the foliage mass and area with a subsequent increase of wind drag over several years (Valinger et al. 1994; Valinger and Petersson 1996) Wind damages might further be increased depending on harvest techniques, because harvest passes and the rails of harvest machines channel wind forces (Fig. 18.9). Rails of machines further cut roots and reduce the anchorage of trees. This is common for summertime harvest in Norway spruce stands, where the mean depth of rails is greater than 5–6  cm in fertile sites with fine-grained moraine soils (Kyttälä 1980). The uprooting is further enhanced by the increasing roughness of the canopy, with a consequent increase of the turbulence of the wind and swaying of trees. The uprooting risk is especially large immediately after thinning due to low anchorage and wide swaying.

18.2.4 Wind Risks on Scale of Forest Landscape

Fig. 18.10  Distribution of damaging wind speeds across Finland, currently (left) and when the rotation length is increased (middle, +10%) or decreased (right, −10%). (Kellomäki et  al. 2009, pp.  253–373. Courtesy of Paper Engineers’ Association/Paperi ja Puu Oy). Calculations

are based on the forest inventory data sets for the whole country, and they represent the average critical wind speeds needed to uproot trees based on the mechanistic wind damage model (Peltola and Kellomäki 1993). The numbers in the figures refer to the administrative regions

Regardless of tree species, the probability of wind damage may be reduced by decreasing the rotation length with a reduction of the bending moment that wind force induces. The left panel in Fig. 18.10 shows the current distribution of damaging wind velocity when the current rotation is assumed throughout the boreal zone in the Finnish territory. Similarly, the middle and right panels show the changes in the damaging wind velocity when the current rotation length is increased (+10%) or reduced (−10%). Currently, the forests are most vulnerable in southern Finland, where mature Norway spruces dominate. Longer rotation makes these forests even more vulnerable, since further maturing will increase the bending moment, thus reducing the damaging wind velocity. Shorter rotation has the opposite effect, reducing vulnerability along with reducing the bending moment, with higher values of wind velocity being  needed to damage trees (Fig. 18.10).

18.2  Risk of Wind Disturbances and Damages

613

Table 18.1 further shows the results of some model simulations for balancing the timber ­production and risk of wind damages on a forest landscape scale. Risk is related to the length of vulnerable edges when using clear cutting and planting in reforestation (Zeng et  al. 2007). Heuristic optimization was employed over three 10-year planning periods. The risk of wind damage was either minimized or maximized with or without an even flow timber targeted in harvest. The planning problems focused solely on either minimizing the length of edges at risk (problem 2) or maintaining an even timber flow (problem 5) or combined both objectives (problem 4). Optimizing problems 1 and 3 represent the maximum impacts of harvesting on the risk of damages at forest edges. This demonstrates how improper management using clear cut would increase the risk of wind damage. Applying a proper intensity, interval, and location of cuttings, it was possible to reduce the risk of wind damage. This implied that the total length of vulnerable edges could be reduced by: (i) aggregating clear-cutting areas (i.e., decreasing the total length of edges); (ii) locating clear cuttings at the edges of young stands (i.e., tree height < 10 m) or at the edges of stands with high critical wind speeds; and (iii) making the landscape smooth in terms of the mean height of trees in stands. Furthermore, clustering the clear-­ cutting areas of the same period will decrease the costs of logging operations. However, the require-

ment for an even flow of timber in harvests may limit the possibility of decreasing the risk of wind damage as indicated by the total length of vulnerable edges (problem 4 compared to problem 2). When minimizing the risk of wind damage without setting any specific harvest objective, the amount of timber does not necessarily increase when the critical wind speed criterion is decreased and vice versa. At the landscape level, the optimized clear-­ cutting management and harvest regimes also depend on the age and spatial distribution of tree stands and the area and spatial distribution of permanent gaps (e.g., fields, lakes). Damage is most likely to occur in sites where there are sudden and large increases in wind loading on trees not acclimatized to the situation after thinning. Such a situation is evident when thinned stands are adjacent to newly clear-cut areas or the stands have recently been heavily thinned (Peltola et al. 1999a, b). When planning the spatial pattern of clear cuttings and the management of forest edges, the fundamental issue is how clear cuttings affect the local wind velocity and the direction of airflow at the downwind edges of clearings. The risk of wind damage can further be reduced on a regional scale, for example, by avoiding new edges in old stands and prioritizing the most vulnerable stands in cuttings such as old ones. After the closure of regenerated gaps over time, the risk of wind damage at the edges will decrease again (Zeng et al. 2007).

Table 18.1  Management of risk of wind damage in forest planning when assuming the risky edges of clear-cut areas (gaps) at a critical wind speed of ≥ 20 m s−1 (Zeng et al. 2007). The calculations are applied to a boreal forest

area of 395 ha in central Finland (62° N). The area was mostly dominated by Scots pine and Norway spruce, but some birch stands were also present. The preferable optimizing problems are in bold

Planning problems and planning periods Harvest, m3 Period 1 Period 2 Period 3 Total Final volume, m3 Gaps, ha 1. Period 1 2. Period 2 3. Period 3

Problem 1: Max risk edges

Problem 2: Min risk edges

Problem 3: Max risk edges, cut 12,000 m3

Problem 4: Min risk edges, cut 12,000 m3

Problem 5: Cut 12000 m3

6,964 9,307 15,561 31,832 67,536

2,989 8,752 3,698 15,439 81,929

12,015 12,006 12,007 36,028 64,087

11,958 11,932 11,999 35,889 64,606

11,998 11,999 12,003 36,000 64,874

17 (2.4) 27 (1.9) 45 (1.4)

10 (2.0) 12 (3.6) 9 (2.8)

26 (2.3) 33 (1.7) 24 (2.3)

20 (2.9) 19 (3.1) 25 (2.1)

20 (3.2) 27 (2.0) 23 (2.3)

614

18  Risks for Forestry Under Current and Warming Climate

18.2.5 Wind-Related Risks of Forest Damages Under Warming Until now, there has been no evidence that climate has changed the mean wind velocity (the mean in 10-min periods) at high latitudes such as in Finland. This also holds for the frequency of strong winds (velocity >14  m s−1), which has decreased rather than increased, except in the last 50 years with a slight increasing tendency (Jylhä et  al. 2009). However, climatic warming may lead to extreme weather episodes, including exceptionally high wind velocity in thunderstorms. Based on weather statistics, Gregow et al. (2008) found that in the period 1961–2000, the mean wind velocity exceeded 14  m s–1 at least 155 times, and 17 m s–1 five times in continental sites. However, a turbulent wind velocity exceeding 17  m s−1 breaks crowns and branches and turns down single trees and trees in patches. Large-scale wind damages occur when the mean wind velocity exceeds 20–23  m s−1, inducing stand-replacing catastrophes locally.

Warming reduces soil frost, thus increasing the risk of wind damages for reducing anchorage of trees (Laapas et al. 2019). Soil frost is further affected by snow cover, which reduces the heat flow in and out of the soil profile, thus affecting the seasonality, duration, and depth of soil frost (temperature < 0 °C). Under the current climate, soil freezes in late October in southern and middle boreal areas, and in late September in the northern boreal area (Fig. 18.11). Soil frost disappears in April in the south but still exists in May in the north. The current pattern is likely to hold under warming, but the duration of soil frost may decrease from 4 to 5 months to 2 to 3 months in the south and from 5 to 6  months to 4 to 5 months in the north when assuming a temperature elevation of 4  °C (Venäläinen et  al. 2001). Under the current temperature pattern, the depth of soil frost exceeds 100 cm across wide areas in middle and northern boreal areas (Kellomäki et al. 2010). In the south, the depth of soil frost is less than elsewhere in the country, with a depth of just a few centimetres in most southern areas.

Fig. 18.11  Duration of soil frost in upper soil layer (10 cm) for selected regions in Finland under a warming climate in the selected latitudes based on the SRES A2 emission scenario (Ruosteenoja et al. 2005). The duration

of soil frost was the sum of days with a soil temperature < 0 °C in the uppermost soil layer. The period 2001–2020 represents the current climate. (Courtesy of Finnish Society of Forest Science)

18.2  Risk of Wind Disturbances and Damages

Box 18.2: Carrying Capacity of Forest Soil for Timber Harvest Under Climate Warming

In winter, soil frost is of primary importance for mechanized management and harvest. A soil surface layer frozen down to 20 cm or a snow layer of 40 cm on the soil surface (i.e., adequate carrying capacity) is needed to avoid major problems in the trafficability of forest soils, including ruts on the soil and damages to roots. In this context, Lehtonen et al. (2019) modeled how soil type, soil temperature, and snow accumulation under the current climate and climate warming affect the number of days per year in wintertime when the carrying capacity of boreal soils is adequate. When using the current climate (1981– 2010), the adequate carrying capacity was largest on sandy and smallest on peat soils throughout the country (Fig. 18.12). In northern Finland, the carrying capacity was adequate through 5–7  months, depending on forest and soil type. In central Finland, the adequate carrying capacity was clearly less: 3–4 months on peat soils, and about 5 months

Under warming, this spatial pattern holds but the thickness of soil frost decreases throughout the country, and nearly disappears in the south towards the end of this century (Box 18.2). From the strategic perspective, climatic warming has large effects on the risks of wind-induced damages depending on changes in growth and tree species composition, and the return of high wind speed in relation to frozen and unfrozen soil conditions (Laapas et al. 2019). Currently, critical wind velocity is lowest (i.e., the risk of damage is highest) in the south, where mature Norway spruce dominates (Fig. 18.13). In the north, the damaging wind velocity is much higher (i.e., the risk is lower) due to the dominance of Scots pines, which are mainly in the intermediate phases of development. Warming is likely to increase the damaging wind velocity (i.e., reduce the risk) in the south, where the stocking of wind-­ resistant Scots pine and birch likely increases and

615

on upland soils. In southern Finland, the length of adequate carrying capacity varied in the range of 2–4 months per winter depending on the soil type and subregions. On truck roads, the carrying capacity is adequate 3–4 months per winter in the south and half a year in the north (Lehtonen et al. 2019). Under climatic warming (climate scenarios RCP4.5 and RCP8.5), the adequate carrying capacity will tend to reduce by 1 month in the period 2021–2050, the change being slightly smaller for the RCP4.5 than for the RCP8.5 scenario (Fig.  18.12). Later in this century (2070–2099), the length of carrying may shorten by more than 3  months under warming scenario RCP8.5. On sandy and clay or silt soils, the adequate carrying capacity shortens most in southern and western Finland. Later in this century, the warming climate implies that the adequate carrying capacity on truck roads may last, on average, only about 1 month per winter in the south-­ western parts of the country if the RCP8.5 warming scenario realizes.

the stocking of wind-prone Norway spruce declines. The damaging wind velocity is also to reduce in the north due to the maturing of trees, which are more vulnerable to wind forces than trees in seedling and thinning phases. However, there are large differences locally in the risks of wind-inducing damages, because of differences in the structure and properties of trees. The interaction between the properties of trees and wind force indicates that the probability and the extent of wind-induced damages are, in general, larger in southern than in middle and northern boreal forests (Fig. 18.14). Under warming, this spatial distribution is related to the species composition and maturity of trees, which are dominated by mature Norway spruces in the south, while medium-mature Scots pine are common in the north. A longer crown and shallow rooting make Norway spruce more prone to wind force than Scots pine with their shorter crown

616

18  Risks for Forestry Under Current and Warming Climate

Fig. 18.12  Annual mean number of days with adequate wintertime carrying capacity in drained Scots pine-­ dominated peatland sites, with multi-model standard deviations as averaged over the whole of Finland for the global climate model (GCM) and the regional climate model

(RCM) ensembles. The simulations are for the periods 1981–2010, 2021–2050, and 2070–2099 under the RCP4.5 and RCP8.5 climate change scenarios. (Lehtonen et  al. 2019. Courtesy of Natural Hazard Earth System Science. Open Access)

Fig. 18.13  Left: Distribution of mean values of damaging wind speeds over Finland in the period 1991–2018. Middle: Distribution of average values of damaging wind speeds in the period 2070–2099 under climate warming. Right: Percentage change in the damaging wind speed in

the period 2070–2099  in relation to that in the period 1991–2099. (Peltola et al. unpublished data, University of Eastern Finland). The numbers in the figures refer to the administrative regions

18.3  Risk of Snow Disturbances and Damages

617

Fig. 18.14  Simulated probabilities and extent (m3 ha−1) of stem wood likely to be damaged by wind force in the period 2070–2099 under the RCP4.5 climate change scenario. In baseline management, the tree species choice in reforestation represents the species that dominated the sites during the previous rotation recommended currently (Äijälä et al. 2014). Given the preference for Scots pine and birch, the reforestation of these species is expanded to fertile sites (Myrtillus site type, MT). The reforestation of

Norway spruce is limited to extremely fertile sites (Oxallis-Myrtillus site type, OMT) (Ikonen et  al. 2017; Venäläinen et al. 2020). Simulations were done for summertime, with birch having full foliage. The simulations using a gap-type model were combined with the HWIND model (Peltola et  al. 1999a) calculating the wind force capable (critical wind speed) of throwing down trees depending on the species and development phase. (Courtesy of Wiley & Sons. Free to Read & Use)

and deep rooting. This is especially the case for unfrozen soils, which are common for southern boreal soils even under the current climate. Damages to birches are mainly located in the south, where these species are common. In the north, damages to birch are small because of low stocking (Ikonen et al. 2017).

tree under snow loading (Fig. 18.15). The risk of snow-induced damage is highest if wet snow falls during low wind (velocity < 9 m s−1) and the temperature is around zero. Under such weather conditions, wet snow attaches tightly onto crown surfaces. In general, trees bend and branches and crown break when the snow load >40 kg m−2. A snow load >60 kg m−2 implies a large-scale failure and breaking of crowns. Snow load may also turn trees down if soil frost is missing with no extra anchorage for trees (Peltola et  al. 1997, 1999a, b). Damage takes place if the bending moment exceeds the maximum resistive moment of the crown, stem, or roots. Wind loading (velocity >9  m s−1) further enhances the bending moment.

18.3 R  isk of Snow Disturbances and Damages 18.3.1 Mechanisms of Snow-Induced Damages Snow damage refers to breakage of the crown or stem, bending of the stem or uprooting of a whole

618

18  Risks for Forestry Under Current and Warming Climate

In Scots pine and Norway spruce, snow load in the crown is distributed following the distribution of foliage in the crown (Fig. 18.15). In Scots pine, snow load is especially located in the upper crown, and in Norway spruce smoothly over the whole crown. In both species, the wind load follows the same distribution pattern, with the consequence that the combined moment induced by wind and snow load is largest in Scots pine in the upper stem, while in Norway spruce it is lower than that in Scots pine. Consequently, a Scots pine crown usually breaks just below the crown bottom, while in Norway spruce the stem fails with no specific location along the stem, thus breaking the stem in various places. Young Scots pines are especially prone to snow load alone or combined with wind load. This holds further young low-tapering birches, which frequently become curved under heavy snow load. In

Fig. 18.15  Left: Attachment of snow to tree crown as a function of the intensity of snow fall, wind velocity, and air temperature based on Päätalo et  al. (1999), Päätalo (2000), and Kilpeläinen et al. (2010a, b). Right: Relative distribution of bending moment induced by wind (8 m s−1) and snow load (20–60  kg m−2) along the stem of Scots

Finland, the mean return period of severe snow damage is 5–15 years (Box 18.3).

18.3.2 Risk of Snow-Induced Damages Under Current and Warming Climate The highest risk of snow-induced damage is currently in north-western and north-eastern Finland (Fig. 18.15), where the risk (i.e., snow accumulation in water >20 mm in 5 days) occurs on more than 20  days per year. The lowest risk is in the western coastal areas and in southern Finland. During the periods of unfrozen soil (in late autumn and early spring), the risk of snow-­ induced uprooting and stem bending can increase under climate change. The probability of frozen ground would decrease especially in central and

pine, Norway spruce and birch. The horizontal lines above the columns indicate the stem breaking under snow load in calculations, with the height of trees being 12 m and the ratio between the stem diameter and tree height being 1:120. (Nykänen et al. 1997. Courtesy of Finnish Society of Forest Science)

18.4  Risk of Fire Disturbances and Damages

Box 18.3: Accumulation of Snow Load on Tree Crown

Snow accumulation (Snowaccn, kg m−2) in crowns is the function of snowfall and snow loss (Snowloss, %) related to air temperature (T, °C) and wind speed (U, m s−1) (Gregow et al. 2008). Snow loss related to temperature and wind speed is: Snowloss ( T ) = 11.502 × T 2.6361 , if T > 0° C

(18.6)

Snowloss ( T ) = 0

, if T < 0° C

(18.7)

Snowloss (U ) = 0.0038 × U 3 − 0.2176 × U 2 + 0.8605 × U (18.8) Based on the 3-h time step, the snow accumulation is (Gregow et al. 2008): Snowacc n = Prec n + Snowacc n −1

 1 − Snowloss n ( T )   / 100  +Snowlossn (U )  (18.9)

×

where Precn is the precipitation of snow and Snowaccn the snow accumulation. On any day, there is a risk of snow damage if the snow accumulates at a rate ≥ 20 kg m−2 per 3-h period.

northern Finland, where the maximum annual soil frost length and depth is expected to decrease (Venäläinen et al. 2001). Until now (the first period 1991–2020), climate warming has reduced the risk of snow damage by a few days consistently over the whole country (Kilpeläinen et  al. 2010a) (Fig.  18.16). This disagrees with the findings of Lehtonen et al. (2016a) because of the differences in calculating snow load. When the snow load is decomposed into rime, dry snow, wet snow, and frozen snow, the snow load based only on dry snow gave

619

a similar result to that of Kilpeläinen et  al. (2010a). Under warming, the load of dry snow likely increases in northern Europe in areas where the mean winter temperature tends still to fall below −8 °C, mainly in the eastern and northern parts of Finland. On the other hand, some of the snow accumulated previously may persist unloaded on tree crowns in cold climates, thus affecting the total snow load on exposed trees (Hedstrom and Pomeroy 1998). In the second 30-year period (2021–2050), the decrease continues, especially in north-western Finland. Until the end of this century (2070– 2100), the risk may decrease to 0–6 days per year in the south and to 6–12 days in the north. Over the whole country, the mean number of risk days per year will decrease by 11, 23, and 56 % in the first, second, and third 30-year periods with warming, respectively, compared to the period 1961–1990 before warming. This implies that the occurrence of risk of snow damage per year will be less than 8 days in most of central and southern Finland until the end of this century. This will also be the case currently in the most hazardous areas, north-western and north-eastern Finland, where the number of risk days per year will decrease from the current over 30 days to about 8  days per year until the end of this century (Kilpeläinen et al. 2010a).

18.4 R  isk of Fire Disturbances and Damages 18.4.1 Fire Risk Related to Weather and Site Conditions Fire risk refers to the occurrence of fire damage or return of damaging fire. Fire damage is any fire-induced damage to trees, including the death of whole trees under fire. In pure natural conditions, lightning is a reason for forest fire (Fig. 18.17). Currently, most forest fires are triggered by careless use of fire by people, but weather also affects the risks of ignition. Longand short-term variability in precipitation, temperature and air humidity affects the moisture of fuel like litter, with the probability of forest fire to

620

18  Risks for Forestry Under Current and Warming Climate

Fig. 18.16  Number of snow damage risk days (i.e., snow accumulation in water >20 mm in 5 days) per year for the baseline period (1961–1990) (A) and for the past near-­ term (1991–2020), future mid-term (2021–2050) and future long-term (2070–2099) 30-year periods (B–D) (Kilpeläinen et al. 2010a. Permission of Springer Nature). In simulations, the current (1961–1990) and changing (2000–2099, SRES A2 scenario) temperature and precipi-

tation values were interpolated to a 50  ×  50  km grid (Ruosteenoja et al. 2005). During warming, CO2 will rise from 350 to 840  ppm by 2099, with the increase in the mean temperature 4  °C in summer and 6  °C in winter. Precipitation increased by 20% in winter but remained unchanged in summer. Wind values were the same under the current and changing climate. The numbers in the figures refer to the administrative regions

18.4  Risk of Fire Disturbances and Damages

621

Fig. 18.17 Outline of factors affecting fire and its spreading in boreal forests, with impacts on soil, ground vegetation, and trees. (Päätalo 1998. Courtesy of Finnish

Dominating species in ground cover Cladonia/Calluna Vaccinium vitis-idaea Vaccinium myrtillus Cladonia/Vaccinium sp. Empetrum/V. myrtillus Empetrium/Calluna V. vitis-idaea/V. myrtillus Hyloconium/V. myrtillus Grand mean

Society of Forest Science). The return period of wildfire in northern Europe is a function of forest vegetation type

Fire return in years

Source

26–78 18–98 54–138 76–244 60–100 40–235 44–183 18–372 40–140

Hörnsten et al. 1995 Zackrisson 1977 Zackrisson 1977 Zackrisson 1977 Zackrisson and Östlund 1991 Haapanen and Siitonen 1978 Haapanen and Siitonen 1978 Haapanen and Siitonen 1978

occur. Climate and weather further affect the moisture of fuel, impacting the intensity of fire and the subsequent fire risk, spreading of fire, and area being burnt. The spreading rate of fire is further related to the topography, but also wind velocity and the availability of fuel affect the spreading rate. Fire return period indicates the length in years in which a given site may be burnt again. In

northern Europe, the mean length of a fire return period ranges from 30 to 300  years, shorter in sites of poor fertility (dry) than in sites of high fertility (mesic) (Fig.  18.17) (e.g., Shorohova et al. 2011). In the north, fire occurrence is further related to high summer temperatures and lower precipitation. Furthermore, the length of return periods varies substantially depending on the site conditions, ground vegetation and tree

622

18  Risks for Forestry Under Current and Warming Climate

species. Drobyshev et  al. (2014) estimated that the mean return period of large-scale natural fires has been 40 years in southern Scandinavia during the past 600 years. Regarding Finland with less maritime climate, Hyvärinen and Sepponen (1988) estimated that the fire interval in Norway spruce-dominated mesic sites was 450  years. This was nearly double compared to that (238  ±  48  years) found by Tolonen (1978) for similar conditions. In Scots pine-dominant sites, the fire interval is substantially shorter, i.e., 46 ± 22 years in northern (Zackrisson 1977) and 120  years in middle (Haapanen and Siitonen 1978) boreal forests. Even in pure natural conditions, most forest fires have been small in relation to the small-sized mosaic of dry upland sites. Long-term and short-term variability in precipitation, temperature, and air humidity affect the moisture of fuel and thus the risk of fire and intensity of burning (Fig.  18.17). One to two weeks without rain is needed to significantly increase the fire risk under the current climate (e.g., van Wagner 1983). However, even a few millimetres of rainfall are enough to saturate the litter surface and temporarily lower the fire risk. Climate also determines the length of the fire season in terms of the interaction between fuel accumulation and soil conditions. Wind also has a very strong effect on fire damage in making vegetation more flammable and increasing the spread of fire once ignited. In general, the rate of spread is doubled for each 4 m s−1 increase in wind speed (van Wagner 1983). Topography and the availability of fuel further affect the spreading rate and the intensity of burning and the height of flames.

18.4.2 Risk of Trees to Die in Fire Fire might kill trees directly, but high temperatures might partly damage foliage, branches, stems, and roots, thus reducing growth and increasing the risk of biotic damages. This is especially the case for trees where the crown extends low, and the stem bark is thin as in

Norway spruce. Even tall Norway spruces die in fires of low intensity and flame height, while tall Scots pines with long branchless stem and thick bark at the stem below the crown may survive even in intensive fire with high flames. Birch is also vulnerable to fire due to its sensitive foliage, even though the stem bark is fire resistant. The differences between tree species in terms of fire tolerance affect the fire-induced succession, with major effects on the reproduction of trees and the accumulation of litter and humus in soil. According to Kercher and Axelrod (1984), damaging fire is dependent on the height of flames (HS, m), which is a function of the intensity of burning (FI, Wm−2) and the wind velocity (WIND, km h−1) pushing fire through forest: C1 × ( FI )

1.1.667

HS =

(C 2 × FI + (C3 × WIND ) ) 3

0.5

× ( TKILL − T ) (18.10)

where TKILL [60  °C] is the lethal temperature and T is the air temperature [°C], and C1, C2 and C3 parameters. Consequently, the burning intensity is: FI =



384 × XIR × R SIGMA

(18.11)

where XIR is the reaction rate of the burning material, R is the spreading rate of fire [m s−1], and SIGMA is a parameter representing the area of burning material per mass unit [m2 kg−1] for plain terrain, excluding the effects of topography on the spreading rate of fire. Kercher and Axelrod (1984) linked the probability of trees (PD, 0…1] to die or to be damaged by fire to the height of flames in relation to the diameter (dbh) of trees divided them into those with dbh ≥ 12.7 cm and those < 12.7 cm: 1  dbh  = 1−   ≥ 12.7 cm  (1 + exp ( A0 × A1 × dbh + A2 × HS ) )

PD 

(18.12)





18.4  Risk of Fire Disturbances and Damages

PD



(

dbh < 12.7 cm

)

= 1−

623

1

 1 + exp  B 0 − B1 × dbh       − B 2 dbh + A2 × HS   2

(18.13) where A0, A1, A2, B0, B1, and B2 are parameters. The performance of the equations is demonstrated in Fig. 18.18 as a function of tree dimeter and height of flame. The probability of a small tree with small diameter and crown bottom close to the ground dies in a year with a high probability. On the contrary, tall trees with large diameter and high crown bottom likely survive under high flames. The survival of trees is further related to the properties of species. In this respect, Kolström and Kellomäki (1993) analyzed the survival of Scots pine, Norway spruce, and birch exposed to surface fire. The measurements included 335 trees grown in mixtures in two sites of intermediate (Myrtilllus site type, MT) and low (Vaccinium site type, VT) fertility representing middle boreal conditions. Nearly all Norway spruce and birch trees died (survival < 2%), whereas the mortality of Scots pine trees was substantially smaller (survival 18%). Kolström and Kellomäki (1993) found that the survival of Scots pine increased along with increasing diameter. This further indicated that increasing height of crown bottom and bark thickness, with the reducing probability to die for fire (Fig. 18.19) as found by Kercher and Fig. 18.18 Probability of tree dying as a function of tree diameter and flame height based on Kercher and Axelrod (1984). (Permission of Elsevier)

Axelrod (1984). In boreal conditions, about 20% of vegetative biomass and less than 50% of humus layer are burnt in fire events (Lynch et al. 2004). This implies that about 10% of woody biomass is converted to charcoal, with the residence time of carbon being thousands of years (DeLuca and Boisvenue 2012).

18.4.3 Frequency of Fire Events and Burnt Area In Finland, the mean annual precipitation varies in the range of 300–700 mm in such a way that summertime precipitation is evenly distributed through the main growing season. Even low precipitation keeps litter and humus moist because of low evaporation. Therefore, the general fire risk is low under the current climate, but climatic warming with longer summers and the consequent increase in drought events is likely to increase fire risk. For example, Zackrisson (1977) found that wildfires are most likely in summers when the temperature in June and July is above the long-term mean. Furthermore, changes in the amount and seasonal distribution of precipitation may alter the risk of damaging fires. Early snow melt combined with only a small increase of precipitation in the spring and early summer is likely to increase fire risk even in humid boreal conditions (Box 18.4).

624

18  Risks for Forestry Under Current and Warming Climate

Fig. 18.19  Upper: Share of dead and living Scots pines exposed to fire as a function of tree diameter. Middle: Share of dead and living Scots pines exposed to fire as a function of height of living crown. Lower: Probability of surviving Scots pines is  a function of tree diameter:

prob ( x ) =

eZ , where Z = β o + β1 × X1 + β 2 × X 2 + … + β n × X n . 1 + eZ

(

)

In the equation, βo…βn are coefficients for the factors X1…Xn affecting survival. (Kolström and Kellomäki 1993. Courtesy of Finnish Society of Forest Science)

18.4  Risk of Fire Disturbances and Damages

625

Box 18.4: Fire Risks and Moisture of Surface Fuel in Boreal Forests

represented a relatively small water storage of around 4–6  mm. Regardless of tree species, moisture in moss layer under a canopy was larger than in open areas. The mean moisture of surface fuel was correlated with effective leaf area index and canopy openness. In clearcut areas of previous Scots pine stands, the frequency distribution of daily moisture was mostly skewed towards the left of the distribution. In this case, the moisture content of fuels reached the ignition threshold moisture content of 30% (a fire risk value of 3.6) earlier than in other cases. These differences showed that stand structure has a clear impact on the moisture of surface fuel and ignition of fire.

Fire risk refers to the number of days per year when fire is possible in the main growing season in relation to drought episodes making forests vulnerable to fire. Fire risk indicates the climatic potential for wildfire, not the realized incidence of fire. In boreal forests, fire risk and spreading of fire are related to the moisture of surface fuel, which is mainly a mixture of dwarf shrubs, mosses, litter, and upper layers of humus. The moisture of moss may be used to indicate fire risk as shown by Tanskanen et al. (2006) (Fig. 18.20). According to Tanskanen et  al. (2006), the mixture of litter and moss on the forest floor

1

Moisture content (%)

500

Scots pine site after clear cut

2

3

4

5

6

Scots pine site 45 years since regeneration

Norway spruce 40-years since regeneration

400 300 200 100 0 1

2

3

4 5 6 Fire risk index (FFI)

1

2

5 6 3 4 Fire risk index (FFI)

Fig. 18.20  Daily observations of moisture content in surface fuel in coniferous stands in southern boreal conditions as a function of the Finnish fire risk index (FFI) (Venäläinen and Heikinheimo 2003) when used for three stands dominated by Scots pine: Pinus_0 = immediately after clear cut, Pinus_45 = 45  years since regeneration,

Picea_40 = mixture of 40 and 60 years since regeneration. The dashed lines indicate a moisture content of 30%, which is the likely limit for fire propagation in fuels used in the study. (Tanskanen et  al. 2006. Permission of Elsevier)

In Finland, the frequency of forest fires was stable from the 1950s to the 1990s (Peltola 2006) but thereafter increased (Fig. 18.21). In general, burnt areas are mainly limited to a few tens or hundreds of hectares per year, and only occasionally do large-scale catastrophes occur. However, the total burnt area has been less than 1,000  ha

per year, with an average area of 0.6  ha in the 1990s and between 0.2 and 0.5 ha in the 2000s. The burnt area is greatly affected by the properties of the forest landscape, i.e., what the mosaic structure is like and how peatlands and lakes modify the landscape. This is the case for Finland, where the percentage of forest land burnt annu-

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18  Risks for Forestry Under Current and Warming Climate

Fig. 18.21  Number (blue line, the scale on the right with the mean events of 1,385 per year) and area (orange line, the scale on left with the mean area 0.22 ha per year) of

forest fires in Finland in the period 1910–2015. (Venäläinen et  al. 2017. Courtesy of Ari Venäläinen, Finnish Meteorological Institute. 28.9.2020)

ally is < 0.005% of the total area of forest land, with the mean burnt single areas being < 1 hectare. In more continental climates, single fires may affect larger areas than in humid climates (e.g., Forest Fire Statistics 1991–1992, 1993). Climatic warming is likely to increase the fire risk and fires even in northern Europe. The increase in fire risk will be especially large at the end of this century assuming that the mean annual temperature will have increased by up to 4 °C. At the same time, the annual precipitation will have increased in southern Finland by up to 20% and in northern Finland by up to 40%, mainly during winter. However, the evapotranspiration in summer will be increased to such an extent that the number of days with fire risk will likely double even in northern Finland, where low evaporation is currently limiting the risk of forest fire. A temperature increases of 3–4 °C from June to August may increase the potential fire area 15 to 50 times in western central Europe if there is no increase in precipitation (Suffling 1992). This implies that conflagrations may occur even under the current climatic conditions as happened in Sweden in 2014, with a burnt area of 15,000 ha. The risk of such fire catastrophes is likely to increase along with climatic warming. Lehtonen et al. (2016b), for example, estimate that the number of large-­ scale forest fires may double and even triple in Finland during this century. However, such esti-

mates are still uncertain due to the uncertainties in climate scenarios and human activities related to using fire in forest areas.

18.4.4 Fire Potential and Climate Change Impact on Fire Risk Kilpeläinen et  al. (2010b) simulated the fire risk based on fire potential and fire frequency over the whole territory of Finland (60–70° N) (Fig. 18.22). Forest fire potential refers to the number of days per year under fire alert, while fire frequency refers to the likely number of fire episodes per year. The fire potential relates to the volumetric water content [m3 m−3] in the surface soil down to 60 mm, based on the daily potential evaporation and precipitation (Venäläinen and Heikinheimo 2003). Water loss from the surface layer is based on the drying curve, i.e., the drier the soil the smaller the amount of water that is lost from the surface layer under evaporation. In the calculation period, any rainfall event [mm] wets the soil based on the wetting curve. Thereafter, the volumetric moisture content of the soil surface layer is calculated by adding the water in any rain event to the previous value of water content and subtracting water lost in evaporation. Finally, the moisture content is scaled to forest fire index values (Fw, 1–6) based on the Eq. 18.14 below the figure.

18.4  Risk of Fire Disturbances and Damages

Fig. 18.22  Distribution of days under fire alert under the current and changing climate over Finland based on the current and warming climate (SRES A2 climate scenario)

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(Kilpeläinen et al. 2010b). The numbers in figures refer to the administrative regions. (Permission of Springer Nature)

18  Risks for Forestry Under Current and Warming Climate

628



FW = 30.71 × W 2 + 30.88 × W − 8.76 (18.14)

where W is the volumetric water content [m3 m−3] in surface soil. If the fire index value exceeds 4, a fire alert is in force (Venäläinen and Heikinheimo 2003). The fire index is further used to estimate the likely frequency of forest fires per year, using the surface moisture data from several monitoring sites throughout the country. The data are converted to annual forest fire potential, i.e., the annual number of days when the forest fire index value ≥ 4. In the period 1961–1990, the fire potential was highest in the coastal areas and in southern Finland, varying from 60 to 100  days per year representing the current climate (Fig.  18.22). Under warming, the fire potential is likely to increase towards the end of this century related to the increasing evaporation (Kilpeläinen et  al. 2010b). This is especially the case for the south, where summer evaporation likely increases more than the rise of precipitation. The expected increase in the annual frequency of forest fires over the whole country is likely about 20% by the end of this century compared to the present day. In this respect, the greatest increase in the frequency of fires per 1,000 km2 will be in the southernmost part of the country: six to nine fires expected annually per 1,000 km2 at the end of this century. The increase is 24–29% larger than the present-day frequencies. Furthermore, the area burnt per fire episode is likely to increase as shown by Venäläinen et  al. (2020). They found that burnt areas >10 ha may double from the current ones (four to six incidents) by the end of this century.

18.5 R  isk of Damages Related to Frost Frost damage refers to the damage in plant tissues related to below-zero temperatures, which is lower than that tolerated by tissues. The risk of frost damage is greatest in early summer and early autumn, when night frost may coincide with low frost resistance/hardiness. Damages are

most likely during the transition from winter dormancy to active growth in early spring and summer. Similarly, frost damages are possible during the transition from active growth to winter dormancy in early autumn. Frost may damage trees whenever the frost resistance of tree tissues is less than the temperature occurring any time of the year. The basic question is how the climate affects the phenological cycle of trees and consequent frost hardiness in relation to the annual temperature cycle and variability (Kramer et al. 2000). In general, the local provenances of boreal trees are resistant to low winter temperatures as shown by Leinonen et al. (1995) and Leinonen (1997). They explored the vulnerability of boreal Scots pine to frost damage with model calculations. The simulations utilized the daily frost hardiness and the daily minimum temperature under the current climate. Based on model simulations, Leinonen (1997) found that under the current climate less than 5% of the needle area in Scots pine was damaged in a 100-year period related to the daily variability of temperature over years. Only once was the damage rate in springtime high, with up to 25% of the needle area being affected. Needle loss affected only vslightly the total light interception and photosynthesis. The elevation of temperature by 6 °C through the simulation increased the needle loss by up to 10%. Until now, there has been no empirical evidence that earlier bud burst under climatic warming would lead to catastrophic frost damages. This claim is supported by old provenance transfer experiments, where northern provenances of Norway spruce and Scots pine were grown in southern Finland. They underwent considerable warming (increase of temperature sum by up to 600 d.d.), with the consequence that the bud burst and growth cessation and forming the winter buds were earlier (Beuker 1994; Kellomäki 1996). This is in line with the chamber-based findings, which indicated that the frost hardiness of local provenance of Scots pine at bud burst is still lower than −20 °C even under a warming climate (e.g., Repo et  al. 1996; Kellomäki 2017, pp. 248–250) (Box 18.5).

18.6  Risk of Biotic Disturbances and Damages

Box 18.5: Frost Resistance of Boreal Scots Pine

Based on open-top chambers, Repo et  al. (1996) found that the temperature alone or combined with elevated CO2 made the bud burst of Scots pine up to 2 months earlier and advanced the springtime loss of frost hardiness by a month. This experiment used an extreme elevation of winter temperature (i.e., 5–20  °C higher than outside the chambers). However, even a smaller elevation of temperature outside the growing season may cause earlier spring loss of frost hardiness, as demonstrated in Fig. 18.23. The elevation of win-

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ter temperature was up to 6  °C compared to ambient conditions (Kellomäki 2017, pp. 248– 250). These measurements showed that the loss of spring frost hardiness may be advanced by 14 days compared to ambient temperature. Frost hardiness under elevated temperature alone or combined with elevated CO2 was from −70 to −80 °C in deep winter, and under the other treatments frost hardiness was from −80 to −110  °C.  During the bud burst, the frost hardiness was more than −20 °C under the elevated temperature.

Fig. 18.23  Effects of current and changing climate on the annual course of frost hardiness of Scots pine in a chamber experiment (Seppo Kellomäki, unpublished, University of Eastern Finland). LT50 values indicate the

temperature at which half of the needles subjected to low temperatures are damaged if grown in ambient conditions or under elevated CO2 or temperature or both combined in a chamber experiment

18.6 R  isk of Biotic Disturbances and Damages

warming climate or be in imported timber and seedlings. From the forestry point of view, only a few damaging agents of the most biotic damages are strategically important in forest management. In this respect, the protection is divided into those causing: (i) the largest economic losses; (ii) potential large-scale losses; (iii) potential but locally important losses; and (iv) locally important losses due to agents with pronounced cycles (Maa- ja metsätalousministeriö 2014):

18.6.1 Disturbing Agents Behind the Most Important Biotic Damages Damaging biotic agents include herbivore mammals, insects, and pathogens damaging trees. They may be divided into those currently existing and alien ones, which may invade under a

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18  Risks for Forestry Under Current and Warming Climate

• The first category represents mammal herbivores, especially moose (Alces alces), root rot (Heterobasidion sp.), and pine weevil (Hylobius abietis). • The second category includes bark beetle (Ips typographus). • The third category includes common pine shoot beetle (Tomicus piniperda and T. minor), web-spinning pine sawfly (Acantholyda posticalis), fungal diseases (e.g., Gremmenniella abietina, Lophodermella sulcigena), and resin-top disease (Cronartium flaccidum and Cronartium pini). • The fourth category covers damaging agents such as voles, sawfly (Neodiprion sertifer), agents damaging cones and seeds, and alien agents likely invading. The majority of biotic damages are consequential to abiotic damages, excluding herbivore mammals belonging to those causing the largest economic losses. In other cases, abiotic damages provide a breeding platform for several insects and fungi and a successful environment for populations to expand. The success/losses of many insects and fungi are further dependent on their population dynamics in relation to the environmental conditions, the properties of their host and their breeding pattern (e.g., Evans et  al. 2002; Battisti 2004), including: (i) the survival and reproduction of species (life cycle); (ii) natural enemies (parasites, predators) of species; (iii) the availability and properties (e.g., nutrients, fiber content, secondary compounds) of biomass in host trees; (iv) the vigor and defense capabilities

of host trees; and (v) the phenological synchrony of damaging species and host trees. Under warming, the effects of defoliators, woodborers, and bark beetles are related to the lengthening of the growing season, which allows populations to expand (e.g., Virtanen et al. 1996; Niemelä et al. 2001; Bale et al. 2002). The short life cycle (months, years) of damaging insects facilitates a rapid adaptation to warming in a few years, while the adaptation of tree populations extends over decades/centuries. This may increase the vulnerability of current tree species and make it difficult to predict damages under climate warming. Insects with periodic outbreaks have great genetic potential for adaptation when migrating to new environments. The outbreaks of insect population or excessive increase of the population density of damaging species (pests) reduce growth and even increase the death of trees. Outbreaks vary substantially between pests in frequency, intensity, duration, and area. Major patterns of population dynamics of forest insects represent gradients, cycles, and eruptions (Fig. 18.24). The population dynamics of many bark beetles breeding in stumps in clear-cut areas is of gradient type  (A), such as Hylobius abietis, Tomicus piniperda, and Tomitus minor. The cyclic outbreaks occur at regular intervals, such as every 8–11 years for some invertebrates or at intervals of 4–5  years for some rodents (Fig. 18.24). Cycling outbreaks (B) are linked to the given site and stand properties. Cycling represents host defense responses or the cycling of natural enemies, as with the autumnal

Fig. 18.24  Major patterns of population dynamics of forest insects. Left: Gradients, Middle: Cycles, and Right: Eruptions. (Kellomäki et al. 2009, pp. 253–373. Courtesy of Paper Engineers’ Association/Paperi ja Puu Oy)

18.6  Risk of Biotic Disturbances and Damages

moth(Epirrita autumnata) and rodents (Microtus spp., Clethrionomus spp.) in birch forests in/ above timber line forests in northern Europe. In contrast to the outbreak of gradient and cycling types, eruptive pests (C) tend to have low population densities for long periods, with a sudden and rapid increase/reduction in population density within a few years. Eruptive outbreaks might expand from a local center over large areas and continue for several years, as with diprionid sawflies (Neodiprion sertifer) and some bark beetle (Ips typographus, Dendroctonus) species (Kellomäki et al. 2009, p. 334).

18.6.2 Damages with Largest Economic Losses: Herbivore Mammals Currently, the most important biotic risks for forests are related to mammal herbivores, such as hare (Lepus timidus), moose (Alces alces), and white-tailed deer (Odocoileus virginianus) (e.g., Kuokkanen et al. 2004). Moose are currently the most important in terms of damaging trees, especially in seedling and pre-commercial phases, which provides plenty of winter forage but no clear links to abiotic damages. The diet of moose includes shoots of birch, aspen, Scots pine and even Norway spruce, shrubs, and ground vegetation. The provision of winter forage in relation to the natural succession represents a similar choice in medium-fertile and fertile sites, but the provision through the succession cycle is a function of site fertility. In forestry, management tends to change substantially the winter food provision for herbivore mammals. This is especially the case for conifer plantations in fertile sites, where deciduous trees and shrubs not cleaned may outcompete coniferous plants. The full removal of deciduous trees and shrubs in the seedling phase may decrease the food provision in the phases of pre-­ commercial and commercial thinning. On the other hand, moose are stressed by temperatures above −5 °C in winter and above +14 °C in summer. Therefore, weather is likely to impact on the seasonal patterns of food quality and quantity,

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and further migration for using particular habitats and foraging patterns. This makes moose assemble in subpopulations in winter pastures, where trees might be severely damaged under high grazing pressure.

18.6.3 Damages with Largest Economic Losses: Root Rot Root rot includes two species (Heterobasidion sp.), separately hosted by Norway spruce and Scots pine, commonly in southern and middle boreal forests. Root rot is also hosted by larch (Larix sp.), representing a similar root rot to that in Norway spruce. Root rot in Scots pine is also hosted by several other species, including juniper, and deciduous trees growing in a mixture with Scots pine. In both cases of root rot, the contamination occurs through fresh stumps and harvest damages in roots (Fig. 18.25). Climatic warming combined with increasing precipitation is likely to expand root rot further to the north, where climatic warming reduces soil frost and increases the soil temperature closer to the optimum (22–28 °C) for root rot. Müller et al. (2012) estimated that climatic warming (SRES A2 scenario, with a 5 °C increase by 2100) might enhance the activity of root rot by 50% in southern and 90% in northern boreal forests. Mitigating the risks of root rot might be enhanced by preferring wintertime cuttings, when snow cover and soil frost reduce damages in roots. Later in spring/summer, surfaces of fresh stumps are no longer available for contamination through spores. When the site fertility allows it, the mixture of several tree species is likely to reduce the spreading of root rot in managed forests.

18.6.4 Damages with Largest Economic Losses: Pine Weevil In general, pine weevil (Hylobius abietis) occurs regularly in reforestation areas, where coniferous trees have grown before. Pine weevil damages bark and phloem at the stem butt of many wood plants, including Scots pine and Norway spruce

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18  Risks for Forestry Under Current and Warming Climate

Fig. 18.25  Upper: Sites where root rot currently exists (separate green triangles) and where root rot likely to exist due to climate warming (green shading) in the future. (Viiri 2018). Lower: Factors affecting the spreading of root rot under current and warming climate. (Müller et al. 2012. Courtesy of Natural Resources Institute Finland)

seedlings that are 1–3 years old. The life cycle of pine weevil is 2–3 years, longer in the northern boreal than in southern and middle boreal zones. Climatic warming is likely to increase pine weevil-­ induced risks, because the growth and development of this species is enhanced under higher temperature and increasing drought episodes (Viiri 2018). It is also evident that the increasing growth of ground vegetation might be beneficial for pine weevil. However, the risks

induced by pine weevil are difficult to predict. The success of this species is dependent on the timing of harvest and storing of timber in forest, tree species composition prior to the cut, soil management and timing, and the size of seedlings used in reforestation. Pine weevil damages might be avoided when planting seedlings on mounds, excluding soil organic matter, on bare mineral soil in a radius of 10–15 cm around seed-

18.6  Risk of Biotic Disturbances and Damages

lings. Coniferous seedlings are usually treated with protective chemicals in nurseries.

18.6.5 Potential Large-Scale Losses: Bark Beetle High temperatures and subsequent droughts increase the risk of insect damages. In such conditions, outbreaks of many damaging insects and fungi are closely related to the occurrence of dying and dead trees. This may lead to detrimental attacks on the remaining living trees by insects such as the European spruce bark beetle (Ips typographus) (Wermelinger and Seifert 1998; Fischlin et  al. 2009; Netherer et  al. 2015). The flight period of bark beetle is initiated when the daily mean temperature exceeds 18 °C in spring. Two generations of bark beetles (daughter generations plus second generation) may be born in warm summers (temperature sum >1500  d.d.), thus increasing the risks of major damage to Norway spruce (Fig. 18.26). Currently, the risk is highest in southern boreal forests (< 62° N), but in the future, the risk may be high even in middle boreal forests and the southern parts of northern

Fig. 18.26  Temperature sum in degee days (d.d) shown by lines with numbers) over Finland for the periods 1971– 2000, 2010–2039, and 2040–2069 when using the RCP4.5

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boreal forests (< 64° N). This is likely to occur because the main growing seasons are lengthening, and temperatures are rising. This is indicated by the increase in the temperature sum in the southern and middle boreal zones. On the other hand, bark beetle seems to be becoming more common throughout Europe because of wind-­ induced damages with an increasing number of breeding sites in damaged trees (e.g., Marini et al. 2016; Mezei et al. 2017). Currently, the occurrence of daughter generations plus the second generation of bark beetle (Ips typographus) is still limited in south-eastern parts of Finland, where the main growing seasons are warm (Fig. 18.27). In these conditions, more frequent drought episodes are likely reducing the growth of Norway spruce making it susceptible to attacks (Ruosteenoja et al. 2018). Under warming, the combined effects of increasing population and frequent droughts imply an increasing number of attacks further north. Viiri (2018) concluded that the temperature sum is likely to exceed the value of 1500 d.d. at a latitude of 64° N later in this century (the period 2070–2099), when the warming scenario RCP4.5 is used in calculations. Under more severe warming repre-

climate change scenario. (Venäläinen et al. 2020. Courtesy of Wiley & Sons. Free to read & use)

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18  Risks for Forestry Under Current and Warming Climate

Fig. 18.27  Estimated population levels (catches in pheromone traps) of bark beetle (Ips typographus) in southern Finland in 2012–2015. The location of monitoring sites is

indicated by black dots. (Viiri 2018. Courtesy of Natural Resources Institute Finland)

senting the scenario RCP8.5, the attacks by bark beetles are likely to become common at 66° N and even further north.

cidum anis cronartium pini) has been in the balance with hosting Scots pine, but recent findings show that this disease might form local epidemics (Table 18.2). Common pine shoot beetles refer to widespread bark beetles, with galleries below bark being vertical (Tomicus piniperda) and horizontal (Tomicus minor) depending on the species. In southern Finland, the breeding and attacks of common pine shoot beetles are initiated in March–April, when the daily temperature exceeds +11 °C. In northern Finland, the activities are initiated later in April–May. Common pine shoot beetles attack fresh Scots pine timber, stumps, logging residues, and trees uprooted and damaged in wind and under snow load. These beetles also attack sound trees and reduce growth, but seldom do they kill trees. Their larvae eat young shoots hollow, and shoots die and fall away but they do not kill the tree. Common pine shoot beetles further spread blue-stain fungi, including Ceratocystis, Graphium, Ophiostoma, Alternaria, Diplodia, and Sclerophoma fungi.

18.6.6 Potential But Locally Important Losses: Insects and Fungi The third strategic category includes several insects and fungi. They are locally important agents damaging trees, including common pine shoot beetle (Tomicus piniperda and Tomicus minor), web-spinning pine sawfly (Acantholyda posticalis), and several fungal diseases (e.g., Gremmenniella abietina, Lophodermella sulcigena) and further resin-top disease (Cronartium flaccidum and Cronartium pini). Web-spinning pine sawfly (Acantholyda posticalis) has always been a harmless insect. Currently, this species is potentially important species grazing Scots pine needles of any age class, thus destroying pines. Similarly, resin-top disease (Cronartium flac-

18.6  Risk of Biotic Disturbances and Damages

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Table 18.2  Selected domestic and alien insects and fungi that may potentially damage trees and forests under climate change in Finland (e.g., Perry 2000; Fischlin et al. 2009) Scientific name Common name Domestic insects likely to increase damage Pine flat bug Aradus cinnamomeus Pine shoot beetle Tomicus spp. Spruce bark beetle Ips typographus European pine sawfly Neodiprion sertifer Common pine sawfly Diprion pini Pine looper Bupalus piniarius Pine Beauty Panolis flammea Winter moth Operophtera brumata Domestic fungi likely to increase damage Annosum root rot Heterobasidion annosum Honey fungus Armillaria spp. Lachnellula pini Lachnellula pini Common needle disease Lophodermella sulcigena Potato late blight Phacidium infestans Lophodermium seditiosum Snow/needle blight Lophodermium needle cast Coleosporium tussilaginis Brunchorstia disease Ascocalyx abietina

The damages due to pine shoot beetles are reduced, when harvest of uprooted and damaged trees occurs by the end of June in southern Finland, and by the middle of July in northern Finland. High winter temperatures and high humidity seem to increase the epidemics of damaging fungi such as Scleroderris canker (Gremmenniella abietina) and pine needle cast (Lophodermella sulcigena). However, high summer temperatures, along with drought, may dampen epidemics of some fungi, but they may flourish in cool rainy summers even under the changing climate (e.g., Straw 1995; Perry 2000). Until now, large-scale epidemics of fungal diseases have been rare as regards the main tree species. This is likely to hold even under climatic warming, excluding root rot likely to spread further north under warming.

18.6.7 Locally Important Losses: Agents with Pronounced Cycles Behind locally important losses, there are several local agents occurring in pronounced cycles. These agents include voles, sawfly (Neodiprion

Scientific name Common name Alien insects likely to cause damage Large elm bark beetle Scolytus scolotys Small elm bark beetle Scolotys multistriatus European oak leafroller Totrix viridana Gypsy moth Lymantria dispar Nun moth Lymantria monacha Bursaphalencus xylophilus Pine wilt nematode

Alien fungi likely to cause damage Ceratocystis ulmi Dutch elm disease

sertifer), and several other agents damaging cones and seeds, and alien agents likely to invade under climatic warming (Table 18.2). The short-term cycle of voles is 3–4 years, but the density of vole populations seems to fluctuate even in longer cycles as shown by the peaks in vole density in the 1970s, 1980s, and 1990s. Such dynamics in vole populations are likely related to the long-term fluctuation in available forage, thus damages are dependent on the variability in environmental conditions and changes in management. In the latter case, reforestation affects substantially the occurrence of vole-induced damages in forests. For example, seedlings of southern origin and seedlings raised in nurseries under a given practice might attract grazing to such an extent that reforestation fails. This has been the case for birch and aspen, and their use has nearly ended in reforestation of fertile sites. European pine sawfly (Neodiprion sertifer) is a defoliator whose population density fluctuates on a small scale over 5–6  years and on a large scale over 10–20  years. The density of sawfly populations is largest when summers are warm and precipitation low. Normally, large-scale damages extend over a few years, and the population density declines for natural reasons, e.g., due to parasites, predators, and viruses. Adult sawflies

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18  Risks for Forestry Under Current and Warming Climate

lay eggs on the youngest needles in August– September, and the larvae born in the next May– June graze on the needles born in the previous summer. Thus, sawfly does not eat the currently growing needles. Therefore, Scots pine may resist even long-term grazing and large growth reduction (e.g., Tiihonen 1970; Austarå et  al. 1987). However, Scots pine exposed to long-term defoliation might die from consequential damages induced by other biotic agents, such as larger banded pine weevil (Pissodes pini) disturbing the phloem functions below bark. Cold winters control outbreaks of European sawfly, because its eggs cannot survive in temperatures below −36 °C (Niemelä and Veteli 2006). Under climate warming, the frequency of such low winter temperatures is likely to reduce, thus increasing the risk of sawfly outbreaks even in northern boreal forests (e.g., Virtanen et al. 1996; Niemelä et al. 2001). Similarly, the populations of other defoliators, such as common pine sawfly (Diprion pini) and pine beauty (Panolis flammea), may grow if the summer temperature is 2–3  °C higher than the long-term mean along with increasing drought episodes (Virtanen et  al. 1996). Common pine sawfly is not as common as European pine sawfly, but it causes serious damage to Scots pine. It lays eggs on the previousyear needles in May–June and further on the new needles in July. Grazing might continue until September, thus exposing all the needles regardless of needle age. Larvae overwinter in soil, and they reach maturity early in the next spring and summer. Grazing of common pine sawfly over 2 years tends to be detrimental for Scots pine.

18.6.8 Locally Important Losses: Insects and Fungi Damaging Cones and Seeds In forestry, damages of cones and seeds are especially harmful for Norway spruce, because 20% of seeds of Norway spruce needed in nurseries come from seed orchards. In this respect, poor flowering and large-scale damages of cones and

seeds limit substantially the use of highly productive genotypes in forestry. Several damaging insects and fungi live in cones, such as spruce cone pyralid (Dioryctria abietella), the spruce cone moth (Cydia strobilella), and cherry-spruce rust (Thekopsora areolata), destroying seeds and reducing the seed crop. Breeding of damaging insects coincides with the larger seed crop, with the consequence that several large seed crops in line enhance damages in cones and seeds. Climatic warming might further enhance such development, thus increasing the risk of a shortage of high-quality seeds for nurseries.

18.6.9 Locally Important Losses: Alien Insects and Fungi Biotic damage may further be related to alien insects and pathogens, which may invade under a warming climate. Outbreaks of such invaders are likely to increase in frequency and intensity in the distribution margins of host tree species, thus changing the current pest/host interactions (e.g., Harrington et al. 2001; Battisti 2004). The distribution of insects and pathogens is ultimately determined by climatic factors such as day length, temperature, precipitation, and length of growing season. Changes in winter temperatures are especially important in boreal conditions, since higher minimum temperatures shift pest distribution further north (Niemelä et al. 2001). Table 18.2 further lists some existing and alien insects and fungi that are likely to damage trees under a changing climate in Europe. The list is based on expert assessments rather than systematic experiments or monitoring of how damaging insects and fungi respond to the elevation of temperature and CO2 and changes in precipitation (Perry 2000). For example, the pine wood nematode (Bursaphalencus xylophilus) came in fresh timber from North America. Until now, low summer temperatures and short growing seasons have curbed this nematode outside northern Europe, but climatic warming might remove the temperature limitations. This also holds for the ambrosia beetle (Gnathotrichus materiarius) introduced from

18.7  Management for Mitigating and Avoiding Forest Damages

637

Fig. 18.28 Distribution of nun moth (Lymantria monacha). Upper: Under the current climate. Lower: Under temperature increased by 5.8 °C (Vanhanen et al. 2007). The shaded area indicates the current distribution and the dots the distribution simulated with the CLIMEX model as indicated by the ecoclimatic index (EI). (Courtesy of Finnish Society of Forest Science)

North America to Europe in the 1930s. In the late 1990s, the ambrosia beetle occurred in southern parts of northern Europe. Low summer temperatures and short growing seasons have curbed this species outside Finland, but climatic warming might change the situation (Fischlin et al. 2009). Higher temperatures may also expand the habitat of nun moth (Lymantria monacha) far above 60° N in northern Europe. Currently, this insect damages Norway spruce in central and southern Europe (Beje 1988), where the mean temperature in July exceeds 16 °C and the mean temperature in September 10.5  °C.  High summer temperatures and frequent drought episodes allow the nun moth to expand further north, as noted by Vanhanen et al. (2007). In model-based analysis, they found that the nun moth might currently be

successful in southern boreal forests. An annual mean temperature of 5.8 °C higher than the current one might allow a northward shift of this insect beyond the Arctic Circle (N 66°) (Fig. 18.28).

18.7 Management for Mitigating and Avoiding Forest Damages 18.7.1 Precautionary Management for Controlling Abiotic Damages There is no legislative framework for mitigating and avoiding abiotic damages, but management

638

18  Risks for Forestry Under Current and Warming Climate

recommendations emphasize the capacity of forest to resist main abiotic hazards to damage forests. In this respect, wind-induced damages are the most common, and they have links to management. Hence, abiotic damages are mainly controlled in precautionary management, with using proper regeneration and raising practices. In longer perspective, the choice of Scots pine and birch in regeneration likely reduces wind-­ induced damages, which are common in Norway spruce-dominated forests. In this respect, the success of Scots pine extends over the whole fertility range of sites, while the success of Norway spruce and birch is limited to the sites with the fertility higher than in the  sites of  Vaccinium (VT) type. In shorter perspective, wind damages might be reduced when the resistance of trees can be enhanced through regular pre-commercial and commercial thinning. Both measures increase the anchorage and the strength of trees to resist wind force and snow load. Wind-induced damages might further be reduced when avoiding intensive thinning in forests likely exposed to strong winds, e.g., in hill slopes and sites limited to open areas lake shores. Furthermore, the preference for a mixture of coniferous and deciduous tree species is likely to reduce the major risk of abiotic and biotic damages, which single-species stands may experience in sites proper for mixing trees species (e.g., Mitchell 2013).

18.7.2 Precautionary Management for Controlling Biotic Damages In contrast to controlling abiotic damages, there is a legislative framework for mitigating and avoiding biotic damages that pests may cause. In this respect, the law on the protection of forests against pests (Law 1087/2013) is aimed at mitigating and avoiding damages that current pests may produce. The focus is to limit the summertime storing of fresh timber in forests to reduce breeding platforms for pests. This allows the excessive growth of pest populations to be reduced, as well as attacks on the remaining trees

in cutting areas or stands around these cutting areas. According to the given guidelines (Section 3), an owner of timber is obliged to transport the timber outside the cutting area or temporary store whenever the butt diameter of Scots pine and Norway spruce timber exceeds 10 cm. Landowners are further obliged to remove coniferous trees that wind, snow, wildfire, or some other factors have destroyed (Law 1087/2013, Section 6). This holds when the volume of damaged Norway spruces exceeds 10 m3 ha−1 and that of Scots pines 20 m3 ha−1 representing trees with a butt diameter exceeding 10 cm. For Scots pines damaged in wintertime, the timber must be removed during the next summer, at the latest by July 1 in the south and by July 15 in the north. Similarly, Norway spruces damaged by wintertime catastrophes must be removed during the next summer at the latest by July 15 in southern, July 24 in central and August 15 in northern parts of the country. Previously, the Ministry of Agriculture and Forestry had decided that damaged trees must be removed whenever the number of damaged trees per hectare is larger than 10% of the total number of trees per hectare prior to the damage. This holds further when at least 20 damaged trees in one or more groups are present in forests (Decision 1397/1991, Section 3). The law on the protection of forests against pests (Law 1087/2013, Section 9) further rules that the Ministry of Agriculture and Forestry may order landowners to execute necessary management and harvest to control the rise and expansion of pest-induced damages whenever damaging pests occur in exceptionally large areas. In such cases, the Ministry may further oblige the Finnish Forest Centre to take the necessary steps to avoid further damages, applying biological and mechanical means to reduce the risks of further damages.

18.8 Concluding Remarks In boreal conditions, the mean annual wind velocity is unlikely to increase under warming. However, wind damage may increase due to the shorter duration of soil frost in autumn and

References

spring, which coincides with episodes of the highest wind speeds. This is especially the case for mature Norway spruce, whose superficial rooting does not give the same support as the deep rooting of Scots pine and birch. However, the risks of wind damage and damaged trees are likely to be increased by the increasing stock of mature trees throughout this century. In contrast to wind damage, the number of days with a risk of snow damage is likely to decrease by up to 50% towards the end of this century due to reducing snow fall period. At the same time, the risk of forest fires may increase by 20% by 2100, especially in southern boreal forests, where evaporation may exceed precipitation including early, main, and late growing seasons. Biotic damage may be due to currently existing insects and fungi and/or alien insects and fungi expanding to cover new areas. In both cases, damaging insects are likely to benefit from the warming climate: population sizes are likely to increase due to successful breeding and an increasing number of generations per year. Increasing attacks on trees may also be due to an increase of abiotic damage in forests providing breeding platforms, for example, for bark beetles (e.g., Schlyter et  al. 2006). The possible reduction of growth in Norway spruce in southern boreal forests further increases the risk of attacks by bark beetles. The risk of insect attacks is further increased by alien species, to which the current tree populations have not yet adapted. This also holds for alien fungal pests, and there is even a risk of increasing damage by domestic fungal pests. In this respect, root rot common in Norway spruce and Scots pine in southern and middle boreal forests is likely to expand further north because of the elongation of the growing season and higher soil temperature and moisture.

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Kuokkanen K, Niemelä P, Matala J, Julkunen-Tiitto R, Heinonen J, Rousi R, Henttonen H, Tahvanainen J, Kellomäki S (2004) The effects of elevated CO2 and temperature on the resistance of winter-dormant birch seedlings (Betula pendula) to hares and voles. Glob Chang Biol 10:1504–1512 Kyttälä T (1980) Puuston vaurioituminen harvennushakkuissa  – kirjallisuustarkastelu. Summary: Stand damage during thinnings  – literature review. Folia Forestalia 431 Laapas M, Lehtonen I, Venäläinen A, Peltola H (2019) The 10-year return levels of maximum wind speeds under frozen and unfrozen soil forest conditions in Finland. Climate 7:1–17 Laiho O (1987) Metsiköiden alttius tuulituhoille Etelä-­ Suomessa. Summary: susceptibility of forest stands to wind throw in Southern Finland. Folia Forestalia 706:1–24 Lehtonen I, Kämäräinen M, Gregow H, Venäläinen A, Peltola H (2016a) Heavy snow loads in Finnish forests respond regionally asymmetrically to projected climate change. Nat Hazards Earth Syst Sci 16:2259–2271 Lehtonen I, Venäläinen A, Kämäräinen M, Peltola H, Gregow H (2016b) Risk of largescale fires in boreal forests of Finland under changing climate. Nat Hazards Earth Syst Sci 16:239–253 Lehtonen I, Venäläinen A, Kämäräinen M, Asikainen A, Laitila J, Anttila P, Peltola H (2019) Projected decrease in wintertime bearing capacity on different forests and soil types in Finland under a warming climate. Nat Hazards Earth Syst Sci 23:1611–1631 Leinonen I (1997) Frost hardiness and annual development of forest trees under changing climate. PhD thesis, University of Eastern Finland, Joensuu Leinonen I, Repo T, Hänninen H, Burr KE (1995) A second-­order dynamic model for the frost hardiness of trees. Ann Bot 76:89–95 Lynch JA, Clark JS, Stocks BJ (2004) Charcoal production, dispersal, and deposition from the Fort Providence experimental fire: interpreting fire regimes from charcoal records in boreal forests. Can J For Res 34:1642–1656 Maa- ja metsätalousministeriön varautumissuunnitelma metsätuhoihin (2014) Helsinki Marini L, Økland B, Jönsson AM, Bentz B, Carroll A, Forster B, Grégoire J-C, Hurling R, Nageleisen LM, Netherer S, Ravn HP, Weed A, Schroeder M (2016) Climatic drivers of bark beetle outbreak dynamics in Norway spruce forests. Ecography 40:001–010 Mayhead GJ (1973) Sway periods of forest trees. Scott For 27:19–23 Mezei P, Jakuš R, Pennerstorfer J, Havašov M, Skvarenina J, Ferenčík J, Slivinsý J, Bičárová S, Bilčík D, Blaženec M, Netherer S (2017) Storms, temperature maxima and Eurasian spruce bark beetle Ips typograhus – an infernal trio in Norway spruce forests of the Central European High Tatra Mountains. Agric For Meteorol 242:85–95

References Mitchell SJ (2013) Wind as a natural disturbance agent in forests: a synthesis. Forestry 86:147–157 Müller M, Piri T, Hantula J (2012) Ilmaston lämpeneminen haastaa nykyistä tehokkaampaan juurikäävän torjuntaan. Metsätieteellinen aikakauskirja 4(2012):312–315 Netherer S, Matthews B, Katzensteiner K, Blackwell E, Henschke P, Hietz P, Pennerstorfer J, Rosner S, Kikuta S, Schume H, Schopf A (2015) Do water-limiting conditions predispose Norway spruce to bark beetle attack? New Physiol 205:1128–1141 Niemelä P, Veteli T (2006) Ilmastonmuutoksen vaikutukset metsätuhoihin ja -tauteihin boreaalisessa vyöhykkeessä. In: Riikonen J, Vapaavuori E (eds.) Ilmasto muuttuu  – mukautuvatko metsät. Metsäntutkimuslaitoksen tiedonantoja 944, pp 92–98 Niemelä P, Chapin FS III, Danell K, Bryant JP (2001) Herbivory-mediated responses of selected boreal forests to climatic change. Clim Chang 48:427–440 Nykänen M-L, Peltola H, Quine CP, Kellomäki S, Broadgate M (1997) Factors affecting snow damage of trees with particular reference to European conditions. Silva Fennica 31:193–213 Päätalo M-L (1998) Factors influencing occurrence and impacts of fires in northern European forests. Silva Fennica 32(2):185–202 Päätalo M-L (2000) Risk of snow damage in unmanaged and managed stands of Scots pine, Norway spruce and birch. Scand J For Res 15:530–541 Päätalo M-L, Peltola H, Kellomäki S (1999) Modelling the risk of snow damage to forests under short-term snow loading. For Ecol Manag 116:51–70 Peltola H (1996) Model computations on wind flow and turning moment by wind for Scots pines along the margins of clear-cut areas. For Ecol Manag 83:203–215 Peltola A (ed) (2006) Metsätilastollinen vuosikirja 2006  - Skogsstatistisk årsbok  – Finnish Statistical Yearbook of Forestry. SVT Maa-, metsä- ja kalatalous 2006. Metsäntutkimuslaitos Finnish Forest Research Institute. 438 p Peltola H, Kellomäki S (1993) A mechanistic model for calculating windthrow and stem breakage of Scots pine at stand edge. Silva Fennica 27(2):99–111 Peltola H, Nykänen M-L, Kellomäki S (1997) Model computations on the critical combination of snow loading and windspeed for snow damage of Scots pine, Norway spruce and birch sp. at stand edge. For Ecol Manag 95:229–241 Peltola H, Kellomäki S, Väisänen H (1999a) Model computations on the impacts of climatic change on soil frost with implications for wind throw risk of trees. Clim Chang 41:17–36 Peltola H, Kellomäki S, Väisänen H, Ikonen V-P (1999b) A mechanistic model for assessing the risk of wind and snow damage to single trees and stands of Scots pine, Norway spruce and birch sp. Can J For Res 29:647–661 Perry ML (ed) (2000) Assessment of potential effects and adaptation for climate change in Europe: The European ACACIA Project. Report of concerted action of the environment programme of Research

641 Directorate General of the Commission of the European Communities 1465–458X 1465–458X, Jackson Environment Institute, University of East Anglia, Norwich Persson P (1974) Beståndsbehandlingens inverkan på risken för vind- och snö-skador. In: Framtidsskogen – skogsproduktionens mål och medel. Skogshögskolan, Institutionen för skogsproduktion, Rapporter och uppsatser nr 33, pp 162–177 Persson P (1975) Stormskador på skog – uppkomstbetingelser och inverkan av skogliga åtgärder.Institutionen för skogsproduktion, Rapporter och uppsatser, Nr 36. Skogshögskolan, Stockholm. 294 p Repo T, Hänninen H, Kellomäki S (1996) The effect of long-term elevation of air temperature and CO2 on frost hardiness of Scots pine. Plant Cell Environ 19:209–216 Reyer C, Bathgate S, Blennow K, Borges JG, Bugmann H, Delzon S, Faias S P, Garcia-Gonzalo J, Gardiner B, Gonzales-Olabarria JR, Hernándes JG, Kellomäki S, Kramer K, Lexer MJ, Linder M, van der Maaten E, Maroschek M, Muys B, Nicoll B, Palahi M, Palma JHN, Paulo JA, Peltola H, Pukkala T, Rammer W, Ray D, Sabaté S, Schelhaas M-J, Seidl R, Temperli C, Tomé M, Yousefpour R, Zimmermann NE, Hanewinkel M (2017) Are forest disturbances amplifying or canceling out climate change-induced productivity changes in European forests? Environ Res Lett 12(3):1–12. https://doi.org/10.1088/1748-­9326/aa5ef1 Ruosteenoja K, Jylhä K, Tuomenvirta H (2005) Climate scenarios for FINADAPT studies of climate change adaptation. Finn Environ Inst Finadapt Working Paper 15:1–15 Ruosteenoja K, Markkanen T, Venäläinen A, Räisänen P, Peltola H (2018) Seasonal soil moisture and drought occurrence in Europe in CMIP5 projections for the 21st century. Clim Dyn 50:1177–1192 Schlyter P, Stjernquist I, Bärring L, Jönsson AM, Nilsson C (2006) Assessment of the impacts of climate change and weather extremes on boreal forests in northern Europe, focusing on Norway spruce. Clim Res 31:75–84 Shorohova E, Kneeshaw D, Kuuluvainen T, Gaunthier (2011) Variability and dynamics of old-growth forests in circumboreal zone: implications for conservation, restoration and management. Silva Fennica 45:785–806 Straw NA (1995) Climate change and the impact of green spruce aphid, Elatobium abictinum (Walker), in the UK. Scott For 49:134–145 Suffling R (1992) Climate change and boreal forest fires in Fennoscandia and Central Canada. Greenhouse impact on cold-climate ecosystems and landscapes. Catena Suppl 22:111–132 Tanskanen H, Granström A, Venäläinen A, Puttonen P (2006) Moisture dynamics of moss-dominated surface fuel in relation to the structure of Picea abies and Pinus sylvestris stands. For Ecol Manag 226:189–198 Thom B, Seidl R (2016) Natural disturbance impacts on ecosystem services and biodiversity in temper-

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Forest Ecosystem Services and Management Under Climate Change

19

Contents 19.1 Climate Change, Ecosystem Dynamics, and Ecosystem Services  19.1.1  Vulnerability Related to Potential Impacts of Climate Change  19.1.2  Response and Adaptation to Climate Change  19.1.3  Management for Different Ecosystem Services Under Climate Change 

 644  644  645  647

19.2 Supporting Services: Impacts and Management Under Climate Change  19.2.1  Supporting Services, Climate Change, and Variability  19.2.2  Biodiversity  19.2.3  Primary Production  19.2.4  Nutrient Cycle  19.2.5  Water Cycle 

 647  647  648  649  653  654

19.3 Provisioning Services: Impacts and Management Under Climate Change  19.3.1  Provisioning Services, Climate Change, and Variability  19.3.2  Timber-Based Services  19.3.3  Reindeer Husbandry and Wildlife  19.3.4  Edible Berries and Mushrooms, Reindeer Lichens for Decoration  19.3.5  Water Supply and Groundwater Level  19.3.6  Genetic Resources 

 655  655  655  658  659  662  665

19.4 Regulating Services: Impacts and Management Under Climate Change  19.4.1  Mitigation of Warming in Ecosystem and Product Technosystem  19.4.2  Carbon in Forest Ecosystem Under Climate Warming  19.4.3  Combining Ecosystem and Product Technosystem in Mitigating Warming  19.4.4  Forest Spectral Properties, Biogeochemical Emissions in Mitigating Warming 

 666  666  666  668  673

19.5 Cultural Services: Impacts and Management Under Climate Change 

 675

19.6 Management Under Climate Change, with Selected Measures and Problems Likely to Emerge  19.6.1  Risks, Opportunities, and Uncertainties in Management  19.6.2  Reforestation Through Natural Regeneration  19.6.3  Reforestation Through Planting 

 675  675  677  680

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 S. Kellomäki, Management of Boreal Forests, https://doi.org/10.1007/978-3-030-88024-8_19

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644

19.6.4  Pre-commercial Management  19.6.5  Commercial Thinning  19.6.6  Management of Tree Species Mixtures  19.6.7  Growth of Scots Pine, Norway Spruce, and Birch Under Warming  19.6.8  Productivity and Rotation Length Related to Growing Conditions  19.6.9  Risks of Abiotic and Biotic Disturbances and Mortality  19.6.10  Outline Strategies for Adapting to Climate Change in Ecosystem Context 

 682  683  685  686  689  692  693

19.7 Concluding Remarks 

 693

References 

 695

19.1 C  limate Change, Ecosystem Dynamics, and Ecosystem In general, the productivity of managed boreal Services Abstract

forests in northern Europe is likely to increase in response to warming but the risks of abiotic and biotic damages will also increase. In forest production, the proper choice of tree species and their provenance are of primary importance. Towards the end of this century, the growth of Norway spruce is likely to decline on sand-rich moraines in southern boreal sites, making this species susceptible to an increasing number of insect attacks. Opportunities related to warming might only be realized if the increasing cutting potential is utilized. Regular management and harvest of timber and biomass provides opportunities to redirect the growth and development of forests to meet in a proper way the gradual change in climate. The increase in productivity is likely to exceed the losses in damages before 2050, beyond which risks are likely to increase more rapidly than opportunities. Keywords

Climate change · Ecosystem dynamics and ecosystem services · Risk management under climate change · Mitigating climate change

19.1.1 Vulnerability Related to Potential Impacts of Climate Change The current structure and functioning of managed boreal forest ecosystems are related to climatic and edaphic conditions that have prevailed for a long time. In the short term, climatic warming changes the conditions, making the ecosystem vulnerable to changes in different climatic factors, including systematic change, variability, and extremes. The vulnerability of the ecosystem to climate change is dependent on the sensitivity of the structure and functioning to climatic change and the adaptive capacity of the ecosystem (IPCC 2007) (Fig. 19.1). Vulnerability is the key to adaptation, with the necessary actions to meet the warming climate in the proper way. In forestry, vulnerability and the factors affecting vulnerability may be decomposed into the following outline concepts (Fig. 19.1): • Vulnerability refers to the extent to which a natural or social system is susceptible to sustaining damages due to climate change, and it is a function of the sensitivity, adaptive capacity, and exposure of the system to climate change.

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Fig. 19.1  Vulnerability related to potential impacts of climate change, adaptive capacity of ecosystem, exposure of ecosystem to climate change and sensitivity of ecosystem to climate change (Locatelli et al. 2010. Courtesy of IUFRO)

• Sensitivity refers to the degree to which systems will respond to a given change in climate, including beneficial and harmful effects. • Adaptive capacity refers to the degree to which adjustments in practices, processes, or structures can moderate or offset the potential for damages or take advantage of opportunities created by the given change in climate. • Exposure refers to the degree to which the system is exposed to climate hazards. • Resilience refers to the flip side of vulnerability, i.e., a resilient system or population is not sensitive to climate variability and change, and they have the capacity to adapt. In the context of the forest ecosystem, the adaptation refers to the adjustment of responses to climatic warming for mitigating detrimental effects and providing benefits in forestry. Adaptation might be: (i) anticipatory (proactive), occurring before no clear impacts; (ii) reactive, occurring after clear impacts; (iii) autonomous, occurring spontaneously triggered by changes in ecosystem structure and functioning or societal needs; and (iv) planned, occurring for maintaining/achieving the target structure and functioning

to meet climate change in a proper way in the selected time perspective (IPCC 2007).

19.1.2 Response and Adaptation to Climate Change Under changing climate, ecosystem responses indicate the reactions of processes (e.g., growth, nutrient cycle) and further structure to environmental factors (e.g., CO2, temperature), which disappear when the stimulus is removed. Acclimatization with adjustment of the reactions represents a gradual or permanent change in the environment. (e.g., elevated CO2, temperature, precipitation). Acclimatization may involve varying timescales (e.g., days to weeks, years), but removing the change in the environment reverses (redirects) the adjustment. Adaptation further refers to changes in genotypes (i.e., provenance selection, natural selection) induced by long-­ term/permanent alteration of environmental conditions. Adaptation (adaptive responses) may include changes in phenology, growth and development, morphology, and biochemistry. Adaptation refers to the differentiation of species

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into different ecotypes of the same species, with varying responses to the same environmental factors, such as tolerance to low temperatures. In forestry, the forest production of goods and services is based on management making ecosystems produce different goods and services aimed at forestry (Fig.  19.2). This includes modified ways to use the current management strategies, regimes, and operations for coping with changing genotypes and site conditions for producing selected ecosystem services. Under management or with no management, the genetic properties of populations and the properties of sites and their interaction are controlled to produce selected services (e.g., Krebs et  al. 2009). In this context, provisioning, regulating, and cultural services are dependent on supporting services, which sustain the structure and functioning of the ecosystem under proper management. Genotype/management interaction links ecosystem functioning and the consequent structure with climate change, with changes in management for producing different ecosystem services.

From the management point of view, ecosystem functioning, and structure form a production hierarchy (Fig. 19.2), where supporting services are related to the basic structure and functioning of ecosystem. The interaction between genotypes and environment maintains the primary biodiversity (autotrophic organisms) driven by the flow of energy through the ecosystem producing first-­ order services in the primary production. At the same time, secondary biodiversity (heterotrophic organisms) maintains second-order services through herbivory and decaying detritus making nutrients available. In the context of supporting services, the ecosystem structure and functioning further provide third-order services: provisioning, regulating, and cultural services. Primary and secondary production links the impacts of climate change directly/indirectly to the dynamics of the forest ecosystem (structure and functioning) for producing different ecosystem services targeted in management.

Fig. 19.2  Outline of the interaction between genotype and environment for producing ecosystem services under the control of management and changes in climate. Any kind of forest-based goods and services (P(i,j)) is a result

of the interaction between environment (E(j)), genotype (G(i)), and management (M(i,j) specific to site and genotype: P(i,j) = G(i) x E(j) x M(i,j)

19.2 Supporting Services: Impacts and Management Under Climate Change

19.1.3 Management for Different Ecosystem Services Under Climate Change Impacts of climate change may be introduced in the ecosystem dynamics through productivity, which is controlled by biodiversity, primary production, and water and nutrient cycles. The impacts may be divided into the separate effects of elevating CO2 and temperature, changes in precipitation and extreme weather episodes on ecosystem dynamics and their interaction (Fig. 19.2): • Under warming, supporting services are likely to increase the productivity of ecosystems with the increase of species in flora and fauna. Furthermore, extreme weather and abiotic disturbances increase habitats for inverte­ brates because of the increase of decaying and burnt wood both in the short and long term, for example. • Provisioning services are further related to the productivity and production of biomass, which contributes to timber and non-timber services. Major abiotic and biotic damages and severe drought episodes reduce primary and secondary production, with direct and indirect effects on provisioning services both in the short and long term. • Regulating services are also related to the productivity and the increase of sheltering vegetation. The nutrient cycle is further tightly combined with ecosystem dynamics. In this respect, leaching of nutrients might be increased in surface flow during extreme weather episodes and abiotic and biotic disturbances. • Cultural services also relate to the increase of biomass production, which might reduce/ increase the amenity and accessibility of forest landscape for recreation and pleasure. Warming probably make boreal outdoor environments more pleasant in summertime opposite for winter activities due to reducing snow cover.

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In the management context, climate change (elevation of atmospheric CO2 and temperature, change in precipitation, extreme weather episodes) is likely to have direct/indirect impacts on the production of different goods and services through: (i) genotype choice (tree species, provenance), and (ii) reforestation (regeneration mode). These factors are widely used in even-­ aged forestry and have further effects on: (iii) tending and pre-commercial thinning of seedling stands, commercial thinning (thinning mode) and the length of the production cycle affected by extreme weather events. Furthermore: (iv) site management (soil treatment, fertilizing, management of groundwater level) affects the production of ecosystem services under climate change. The current management regimes and operations are still applicable, but their use is likely to be modified for mitigating the adverse effects of climate change on the production of different ecosystem services. However, an appropriate management strategy (even-aged, uneven-aged forestry) is needed to enhance the benefits that climate change may bring.

19.2 Supporting Services: Impacts and Management Under Climate Change 19.2.1 Supporting Services, Climate Change, and Variability Supporting services link the biological diversity and the production of matter under the control of nutrient and water cycles. Biological diversity represents the adaptation of primary and secondary production to local environment, with resistance to local abiotic and biotic disturbances. Extreme weather episodes of abiotic disturbances further provide habitats for many native and alien vertebrates and invertebrates. This likely holds especially for those that are dependent on decaying dead wood either burnt or not burnt in varying decaying phases. Under climate change, the primary production and biodiversity have no strong trade-off interactions between each other.

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19.2.2 Biodiversity According to IPCC (2007), global warming of 1.5–2.5 °C implies that 20–30% of known plant and animal species in the planet are likely to be at an increasing risk of extinction. The tree species composition is dependent on the invasion history of different species and their adaptability to the prevailing conditions and future dynamics. In northern forest ecosystems, the current species, with their wide geographic distribution, are likely to retain their role under climate change (Aitken et al. 2008). However, the future distribution of different species might change (expand/reduce), with consequent changes in tree species composition throughout Europe. According to Aitken et al. (2008), “widespread species with large populations and high fecundity are likely to persist and adapt but will likely suffer adaptational lag for a few generations”. Tree species with small populations, fragmented ranges, and low fecundity further decline due to insects and diseases (e.g., Aitken et al. 2008; O’Neil et al. 2008). Changes in structure of forests are most probable in the ecotones (transition regions) between biomes, such as in the southern boundary areas of boreal forests, where ecosystems are vulnerable to climatic warming. In southern ecotone, there are several deciduous tree species with marginal importance in boreal forests. These species are likely increasing under warming as oak (Quercus robur), lime (Tilia cordata), ash (Fraxinus excelsior), elm (Ulmus laevis, Ulmus glabra), and maple (Acer platanoides). They are common in central Europe, but they are domestic even in the northern parts of the middle boreal zone. Under warming, the natural invasion of new sites by new tree species outside the boreal region is likely slow as 40–1500 m per year since the last glaciation (Huntley and Birks 1983). In the northern ecotone, climatic warming is likely to have most effect on forests at high latitudes and higher altitudes, and even in lower latitudes. In these conditions, the current special features of forests and terrestrial ecosystems are likely to decline when the timber line moves further north and to higher altitudes. The forests in the tundra and in upper mountainous areas are

likely to become suboptimal for reindeer husbandry and the recreation industry. However, climatic warming may further provide many opportunities even for forestry related to increasing forest growth. Concurrently, biodiversity likely increases with changes because of increasing primary production. The future timberline forests likely resemble those currently in middle boreal zone, while the southern boreal forests gradually turn into temperate forest currently dominating central-European low-land forests. Simulations in the early 1990s already suggested that the total area of boreal forest might be reduced by 40% (e.g., Monserud et  al. 1993) under climatic warming, but there was a great deal of variability between simulations. However, climatic warming is likely to imply a 500– 1,000  km shift of southern edge boreal forests northwards (Kauppi and Posch 1985; Kirilenko and Sedjo 2007). Consequently, the dominance of deciduous species is likely to increase in southern parts of northern boreal forests, whereas in the northern parts the dominance of coniferous species will remain or increase (Falk and Hempelmann 2013). However, climatic warming is likely to change the spatial dominance of different tree species such as Norway spruce. Dahl (1990), for example, found that Norway spruce might fail in central and central-eastern Europe, while the conditions in northern parts of Europe and northern-western Russia remain favorable for this species. Scots pine, Norway spruce, and birches are likely to experience shift lags and consequent increase/reduction of interspecific competition but persistence under future conditions. Pollen analyses show that the dominance of different tree species since the melting of the last continental ice has been dependent on the temperature conditions. During warm periods, the dominance of Scots pine and deciduous trees has increased, while the dominance of Norway spruce has declined. During cool periods, deciduous species have retreated southwards, and the dominance of Norway spruce has increased in northern and southern areas. However, the warming-induced changes in species composition probably indicate changes in the vegetation functional types rather

19.2 Supporting Services: Impacts and Management Under Climate Change

649

than a shift of the boreal vegetation zone northwards (Bonan 2008; Fitzgerald and Lindner 2013). Such changes are likely to affect substantially the future management of European boreal forests, which are important for commercial use and environmental conservation (Fig. 19.3). In managed boreal forests, nonclimatic stresses such as cuttings are combined with climatic warming, affecting the biodiversity and the resilience and adaptive capacities of ecosystems. The adaptation of trees and other species occurs through phenotypic plasticity, evolution, or migration to suitable sites. The latter has probably been the most common response to climatic changes in the past. Regarding biodiversity, there are several options for sustaining the structure and functioning in managed ecosystems. Regarding even-aged and uneven-aged management, Noss (2001) lists the following options, mainly dealing with land use and the role of natural forests in conserving biodiversity in managed forest landscapes:

• Avoiding fragmentation and maintaining connectivity parallel to climatic gradients. • Providing buffer zones for the adjustment of reserve boundaries. • Using low-intensity forestry and avoiding the conversion of natural forests to plantations. • Maintaining natural fire regimes. • Maintaining diverse gene pools. • Identifying and protecting functional groups and keystone species.

• Setting aside reserves of representative forest types across environmental gradients. • Protecting climatic refuges on multiple scales. • Protecting primary forests.

19.2.3 Primary Production

Fig. 19.3  Expected changes in plant functional types due to climate change as indicated by the difference between the future and current dominance of deciduous (left) and coniferous (right) species throughout Europe. (Fitzgerald and Lindner 2013). Combined results are based on several

models, using the SRES A1B emission scenario. (Courtesy of the Motive Project of the European Community’s Seventh Framework Programme (FP7/2007–2013) under grant agreement no 226544)

The framework is applicable in land use and management for mitigating long-term effects of climate warming on functional and structural diversity. In this respect, the productivity of tree community is likely related to the tree species diversity (primary diversity) (Liang et  al. 2015, 2016), with the impacts on a secondary diversity (diversity of consumers) related to the productivity of the forest landscape.

Throughout Finland, climatic warming is likely to increase the primary growth of Scots pine in

19  Forest Ecosystem Services and Management Under Climate Change

650

the northern (above 63° N) more than in the middle (62–63° N) and southern (below 62° N) boreal forests. Over this south-north gradient, the increase of net photosynthesis is related to the increase of current temperature (Fig.  19.4), i.e., by 5% in the south and 25% in the north in response to the temperature elevation. Regarding the elevating CO2 alone, the total annual net photosynthesis may increase by 30%, more in the north than in the south. Under the combined increase of both factors, photosynthesis increases by 25% in the south and 60% in the north. The simulations further show that the increase in total photosynthesis is related to the elongation of the growing season. Snow cover, for example, decreases from 100–160 days to 50–100 days in the south, and from 180–220  days to 150– 180  days in the north. At the same time, the length of the growing season (the number of days with a mean T ≥ 5  °C) increases by 5% in the

south and 20% in the north. Under the current climate, the moisture in the soil surface layer is below wilting point (0.21  m3 m−3) two to three days per year over a 100-year period in the south. Under warming, the moisture below wilting point likely increases to 5–20 days per year. Warming further increases the decay of litter and humus, thus recycling 2–17% more nitrogen for reuse (Kellomäki et al. 2005). Throughout the whole of Finland, precipitation seldom limits forest growth, except in poor sites with a coarse soil texture (e.g., Cladonia and Calluna site types, ClT and CT). This implies that more than 80% of sites are currently not drought-prone, mainly those on moraine soils with medium-coarse and fine textures. However, drought episodes in these sites are possible if long rainless periods coincide with high summer temperatures. This was evident in the simulations by Briceño-Elizondo et al. (2006a, b), who stud-

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Fig. 19.4  Upper: Total net photosynthesis of Scots pine across boreal zone in Finland per 100-year period (Seppo Kellomäki, unpublished, University of Eastern Finland). Lower: Percentage change of total net photosynthesis due to climate change related to that under current climate. In the simulations, the temperature rose 0.4 °C per decade,

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and carbon dioxide 35 μmol mol−1 per decade from 350 to 700 μmol mol−1. Precipitation was basically the same in each location, but it increased/reduced depending on cloudiness related to temperature conditions (Strandman et  al. 1993). The simulations are done with the FinnFor model (Kellomäki and Väisänen 1997)

19.2 Supporting Services: Impacts and Management Under Climate Change

ied the sensitivity of biomass growth to changes in temperature, precipitation, and atmospheric CO2 in southern (62° N) and northern boreal (66° N) sites. The simulations showed that warming substantially enhanced the growth of Scots pine in

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Fig. 19.5  Relative effects of the elevation of temperature (T, °C from the mean annual current one) and precipitation (P, % of the mean annual current one) on the growth of Scots pine, Norway spruce, and birch compared to the growth under the current climatic conditions. Regardless of the site and tree species, the density of initial stand was

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the north regardless of precipitation. In the south, warming increased growth only slightly under increasing precipitation or even decreased it under reducing precipitation (Fig. 19.5). The performance of birch resembled closely that of Scots pine, thereby responding similarly to the variabilScots pine, north

Scots pine, south 25 20 15 10 % 5 0 -5 -10 -15

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2,500 seedlings per hectare. In both locations, the sites were of medium fertility (Myrtillus site type, MT), with the fertility suitable for Scots pine, Norway spruce, and birch. In each case, the soil was a till, with an initial mass of organic matter in the soil of 45  Mg ha−1. (Briceño-­ Elizondo et al. 2006a, b. Permission of Elsevier)

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19  Forest Ecosystem Services and Management Under Climate Change

ity of temperature and precipitation alone and combined. In the south, warming increased the growth of Norway spruce only under substantially increased precipitation, and even reduced it under no or slightly increased precipitation. In contrast, warming in the north clearly increased the growth of Norway spruce even under declining precipitation. The growth of birch responded to the changes in temperature and precipitation in a similar way as Scots pine: a large temperature increase combined with a reduction in precipitation reduced growth in the south, while in the north the growth increase was clear (Briceño-­ Elizondo et al. 2006a, b). In simulations using other models with a short time resolution, the growth increase/decrease was in the range of 15–30%, regardless of tree species (e.g., Bergh et  al. 2003; Matala et  al. 2003). On the other hand, more aggregated mod-

Box 19.1: Climate Change Impacts on Growth of Main Trees in the Nordic Countries

Bergh et al. (2003) used a process-based ecosystem model (BIOMASS) to investigate how rising temperatures and atmospheric CO2 affect the net primary production (NPP) of the main tree species in the Nordic countries. The simulations concerned coniferous Scots pine (Pinus sylvestris), Norway spruce (Picea abies), and deciduous broadleaves as beech (Fagus sylvatica) and  black cottonwood (Populus trichocarpa), which are successful in different Nordic countries (Denmark, Finland, Iceland, Norway, and Sweden). The simulations represented sites in a climatic gradient from a continental climate in Finland and Sweden to a maritime one in Denmark, Norway, and Iceland. Simulations showed that warming likely increased NPP by 5–27% for the conifers, the increase being less in a maritime climate compared with a continental one (central Sweden,

els with longer time resolution tend to give a large range as in the simulations by Kellomäki and Kolström (1993, 1994). The growth increase was 5% in the south and 170% in the north when using a gap-type model under the same temperature increase. Similarly, Kauppi and Posch (1985) showed that climatic warming could increase growth by 40% in the south and by 140% in the north when relating growth increase to the likely increase in temperature sum. This pattern holds further as indicated by Kauppi et al. (2014). The Finnish national forest inventories (NFI) show that the growth through the whole of Finland has increased since late 1960s. The growth increase may be related to changing climate, with the further contribution of changes in management, nitrogen deposition, enhanced nitrogen cycle, increasing stocking and more optimal age distribution of forests than previously (Box 19.1).

eastern Finland). The increase in NPP could largely be ascribed to the earlier initiation of the growing season, with rapid recovery of photosynthesis from winter dormancy, while warming increased respiration, and thus reduced carbon gain. The effect of elevated temperature on NPP was similar for black cottonwood in Iceland, representing an early bud break and a rapid leaf development in spring. However, warming reduced NPP for beech in Denmark. Evidently, elevated temperatures had no effect on bud break but increased the water deficit and water demand during the summer and reduced photosynthesis. The increased atmospheric CO2 had an additional effect on NPP by 25–40% for conifers and beech. The increase was related to the increased photosynthesis, representing enhanced carboxylation efficiency in summer and improved water use efficiency (beech). The effect of elevated CO2 on NPP was somewhat less (13%) for black cottonwood.

19.2 Supporting Services: Impacts and Management Under Climate Change

19.2.4 Nutrient Cycle In general, the growth of boreal forests is greatly limited by the short supply of available nitrogen, even though several Mgs of nitrogen per hectare is bound in soil organic matter (SOM, litter, and humus) (Fig.  19.6). The amount of SOM increases from the north to the south, correlating

Fig. 19.6  Mean amount of soil organic matter and available nitrogen in boreal forest sites as a function of temperature sum and site type based on the simulations using Finnish National Forest inventory data. The values are for the period 1990–2099 divided in three subperi-

Region and period South Current 1990–2020 2021–2050 2071–2099 North Current 1990–2020 2021–2050 2071–2099 Total Current 1990–2020 2021–2050 2071–2099

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positively to the current temperature sum. On the other hand, the SOM increases from poor to fertile sites in relation to the differences in productivity due to site fertility. The differences are especially pronounced between very poor sites (Calluna site type, CT) and poor sites (Vaccinium site type, VT) in relation to medium-fertile (Myrtillus site type, MT) and fertile (Oxalis-

ods under climate warming (SRES A2 scenario). Southern Finland refers to the area  below 63° N and northern Finland to that above 63° N. (Kellomäki et  al. 2005. Courtesy of Finnish Environmental Institute)

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26.2 27.1 (+3) 43.4 (+65) 46.7 (+78)

73.4 73.3 (0) 91.9 (+25) 115 (+57)

36.3 37.4 (+3) 50.4 (+39) 56.8 (+56)

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19  Forest Ecosystem Services and Management Under Climate Change

Myrtillus site type, OMT) ones. The differences between the latter two are small (Kellomäki et al. 2008). Climate change has clear impacts on soil organic matter (SOM) and nitrogen bound in SOM  (Fig. 19.6). Even small warming likely increases SOM over the boreal zones, because of increasing growth and litter fall. In the latter part of this century (2071–2100), the amount of SOM will further increase, exceeding 30% occasionally in the north. In the south, the amount of SOM might also increase locally, but SOM in many places might decline (20–30%). By the end of this century, climatic warming might increase the mean amount of SOM by 40% in the north and 60% in the south (Kellomäki et  al. 2005). This implies that the links to growth and decay of SOM make the nitrogen cycle temperature-­

Fig. 19.7  Left: Distribution of annual current precipitation in the period 1961–2000, and the percentage change related under the climate change (the period 1991–2020, 2021–2050, 2070–2099). Right: Distribution of evaporation under the current climate and the percentage change under climate change in the same periods as for precipita-

dependent (Fig. 19.6). According to the simulations based on SRES A2 scenario, the increase will be up to 30–60% in the period 2021–2050, and up to 50–80% in the period 2070–2100. The relative increase might be especially pronounced in the north, where the percentage changes will exceed those in the south. At the end of this century, the amount of available nitrogen might still be greater in the south than in the north.

19.2.5 Water Cycle In Finland, the current mean annual precipitation is 600–800  mm in the southern (60° N), 500– 600 mm in the central (63° N) and 300–400 mm in the northern (70° N) boreal forests (Fig. 19.7). Under climate change, precipitation is likely to

tion (Kellomäki et al. 2005). Evaporation is the potential evaporation related only to temperature based on the SRES A2 emission scenario (Ruosteenoja et  al. 2005). The numbers in the figures refer to administrative regions. (Courtesy of Finnish Environment Institute)

19.3 Provisioning Services: Impacts and Management Under Climate Change

increase most in the northern areas: by up to 15% in the period 2021–2050 and 40% in the period 2071–2100. In the south, the precipitation is likely to increase by 10%. At the same time, precipitation is likely to increase most in winter (10–40%), and in summer the increase is likely to be 0–20% by the end of this century. The average snow depth in water equivalent may decrease in the southern and central parts by 70–80% or even more in the north (Jylhä et al. 2009). The average annual maximum snow water content and the duration of snow cover (number of days with snow cover) reduce most in early and late winter. Warming climate increases potential evaporation, with the effects of water cycle on the functioning and structural dynamics of forest ecosystem (Fig. 19.7). Based on the model simulations, Kellomäki et al. (2005) found that in the period 2021–2050, potential evaporation may increase by up to 8–13%, more in the south than in the north, when comparing to the simulated evaporation in the late 1990s and early 2000s. During the period 2070–2099, potential evaporation may increase by up to 25% in the south and 10–15% in the north. In the south, potential evaporation locally increased more than precipitation, whereas in the north the situation tended to be reversed. In the south, the frequency and length of drought episodes are likely to increase in the future under both SRES and RCP scenarios (Kellomäki et al. 2005; Ruosteenoja et al. 2017). Drought episodes occur even in the north (temperature sum 66° N) in Finnish Lapland in the monitoring period 1997–2006 (Pudas et al. 2008). Left/Upper: Julian day (day from the beginning of the year) for flowering and ripening of berries in blueberry. Right/Upper: Julian day for flowering and ripening

of berries in lingonberry. Left/Below: Julian day of flowering as a function of mean May temperature for blueberry and lingonberry. Right/Below: Length of vegetative growing period of blueberry and lingonberry in days as a function of temperature sum per year. (Courtesy of Boreal Environmental Research/Open Access)

19.3 Provisioning Services: Impacts and Management Under Climate Change

July 4 to June 25. On the other hand, a higher mean May temperature implied two to three weeks earlier flowering. The flowering and ripening of berries in lingonberry were later than those in blueberry. This also held in relation to the mean May temperature: the same temperature indicated later flowering for lingonberry than for blueberry. Pudas et al. (2008) concluded that the mean May temperature and the timing of snow melt explained the timing of bud burst and initiation of flowering. Vegetative parts of blueberry and lingonberry are resistant to low winter temperatures and frost in spring and summer. In blueberry, summer frost is more detrimental to flowers than spring frost (Tolvanen 1997). In boreal and temperate zones, the yield of fruiting of mushrooms is related to the temperature and precipitation, which affect the growth of saprophytic and mycorrhizal fungi both collected for diet. Changes in the productivity and phenology of fruiting bodies indicate how climate variability and climate change are likely to affect the fungal activity and yield under warming climate. Until now, the extent to which temperature and precipitation affect the productivity and phenology of fungi has been poorly known, because their life cycle is mostly below ground. However, some European-scale studies show that climate change may have clear effects on the fruiting of mushrooms as demonstrated by Kauserud et  al. (2012). They carried out a field study in a Swiss nature park in which a total of 65,631 individual mycorrhizal mushrooms, including 273 species, were recorded weekly in the monitoring period 1975–2006. In this period, the mean number of fungi prior to 1991 increased from 131 species to 2,730 species by the end of the period. Kauserud et  al. (2012) further found that the fruiting occurred earlier with the elongated fruiting in the latter part of the period compared to that in the early period. Evidently, the increasing number of fungi and the spring and autumn elongation of the fruiting period were related to the variability of temperature and precipitation, thus enhancing the photo-

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synthesis and growth of host trees of mycorrhizal fungi. This relation refers to the possible increase of fungal yield under climate change if warming is combined with increasing precipitation (Büntgen et al. 2012; Kauserud et al. 2012) (e.g., climate scenarios GFDL-CM3-RCP4.5 and GFDL-CM3-RCP8.5). On the other hand, the elongation of the growing period of fungi is likely to enhance the decay of soil organic matter, thus reducing the carbon sequestration in soil. Partly based on the same material, Boddy et al. (2013) compiled Fig. 19.11, which shows the spring and autumn elongation of the fruiting season of common fungi in selected countries in northern and central Europe. The impacts of climate change on reindeer lichens used for decoration are poorly known. Dry reindeer lichens are fragile, and they are easily damaged in forest management and harvest, and even trampled in recreational use of forest land (Kellomäki and Saastamoinen 1975). This also limits the lichen harvest to periods when lichen mat is moist enough to avoid damages. Moist lichen mat is further capable of recovering rapidly to its original shape after trampling or related pressure as a function of moisture. For example, Heggenes et  al. (2017) found that dry lichen mat under reindeer trampling lost twice as much thickness as moist lichen mat. They further found that dry lichen virtually did not regain its original volume, whereas lichens with 50% of humid regained a large part of its original volume. Further higher humidity enhanced the regaining of volume rapidly, i.e., 100% humid lichen regained its original volume in 10–20 min. The application of these findings in lichen harvest implies that high humidity of lichen mat limits damages and increases the yield. This also holds for a warming climate, but the enhanced evaporation is likely to limit the no-risk time of harvest. This is especially the case if climatic warming implies concurrently the current or even reduced precipitation in the main growing season as in climate change scenarios HadGEM2-­ RCP4.5 and HadGEM2-RCP8.5.

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Fig. 19.11  Share of mushrooms at the start  mean  and end of fruiting season, with the mushrooms between these phenological phases in Austria, Norway, Switzerland, and the United Kingdom in the period 1970–2007  (Boddy et al. 2013). The start of the season is indicated by the 2.5

percentile and the end by the 97.5 percentile, rather than the actual first and last observations. Bars are the share of all species with earlier (left bars) or later (right bars) fruiting, while dark bars indicate the significant share of species. (Permission of Elsevier)

19.3.5 Water Supply and Groundwater Level

how warming is likely to affect evapotranspiration and infiltration across the boreal zone in sites dominated by Norway spruce (Fig.  19.12). Finland was divided into five climatic zones following the temperature sum (TS, +5  °C threshold): TS > 1,050 d.d. for zone I (ZI) and zone II (ZII) in southern, 900 < TS < 1,050 d.d. for zone III (ZIII) in central, and TS < 900 d.d. for zone IV (ZIV) and zone V (ZV) in northern Finland. The plots were of medium fertility (Myrtillus site type, MT), with the soil water moisture in field capacity being 52% and in wilting 30% of the volume. The initial mass of soil organic matter was in the range of 60–70 Mg ha−1 for each site. Ge et  al. (2013a) found that the mean annual evapotranspiration was 19–24% larger than that under the current climate, if no thinning was assumed (Fig. 19.12). The ratio of evapotranspiration to precipitation increased from 5% to 14% under warming. At the same time, the infiltration of water decreased by 24% and 13% in the south (sites ZI and ZII). In the north (sites ZIv and Zv),

Warming modifies several hydrological responses, including interception and transpiration, infiltration, and water flow over land, and finally water flow in soil and subsoil. Consequently, warming changes water yield, floods, and low flow in soil profile (drought episodes), sedimentation, and the chemical properties and temperature of water (e.g., Kløve et al. 2014). Water flows and storages are dependent on management and harvest, with the feedback modifying the functioning and structure of forests. Ground water resources are closely related to the precipitation and infiltration of water in soil profile. Under warming, the infiltration is a function of how future temperature conditions change in relation to the current temperature conditions, rainfall, and evaporation affecting the water balance on soil surface. Ge et  al. (2013a) used a process-based model (FinnFor) for assessing

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Fig. 19.12  Left: Location of five Norway spruce sites in the temperature sum zones used in the simulations showing how Norway spruce is affected by climate change over boreal forests. Right: Annual variation in mean annual temperature and precipitation for the current (solid line) and changing (dashed line) climate at the sites. Below: Mean annual evapotranspiration, its share of precipitation, and mean annual water infiltration into soil over the 100-­

year simulation period under the current and changing climate, assuming no thinning. The numbers in parentheses indicate the share (%) of infiltration under climate change of that under the current climate (Ge et al. 2013a, b). Changing climate represented SRES A2 emission scenario, with the temperature increased by 4 °C in summer and 6 °C in winter, and the atmospheric CO2 from 350 to 840 ppm by 2099. (Permission of Springer Nature)

increasing precipitation compensated for increasing evapotranspiration. Water distributed by municipal waterworks or used in single households is mainly of groundwater (more than 60%), and it mainly represents water from upland sites managed for forestry. Rusanen et  al. (2004) and Mannerkoski et  al.

(2005) showed no clear effects of cuttings (thinning, clear cut) on the level of the groundwater table in southern and middle boreal zones. Therefore, the simulated groundwater fluctuation in Fig. 19.13 is mainly site-specific and related to climate change-induced variability in groundwater in the selected sites across the boreal zone

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Fig. 19.13  Right: Mean groundwater level in the selected groundwater monitoring sites for the reference period (1971–2000) and for climate scenarios A1B in the selected

periods. (Veijalainen et  al. 2012. Courtesy of Suomen ympäristökeskus)

(Veijalainen et  al. 2012). Under warming, the earlier snow melt raises the groundwater level in late winter and spring regardless of the site. This is especially pronounced in the southern and middle boreal zones, where the groundwater level is likely to rise throughout the whole simulation period until 2099. This also holds for the northern boreal zone, but there the wintertime

elevation is moderate. In summertime, warming tends to lower the groundwater level in the south but raise it in the north, where the summertime groundwater level may become higher. Under warming, the groundwater level is likely to be higher in wintertime but lower in relation to the annual variability under the current climate (Veijalainen et al. 2012) (Box 19.3).

Box 19.3: Impacts of Warming on Groundwater in Peatlands

In peatlands, the groundwater level also varies substantially from site to site in response to the seasonality and warming climate. In natural conditions, groundwater tends to be higher in fens than in bogs in response to warming (Gong et  al. 2012). Warming impacts are especially pronounced in drained peatlands, particularly in the western parts of Finland. In this respect, the effect is dependent on the precipitation: even a 20% increase in precipitation would offset the drawdown under warming of 6  °C by the end of this century.

In terms of the dynamics of greenhouse gases, the variable groundwater level is likely to have large effects on the sink-­ source relation in peatlands. For example, Nykänen et al. (1998) estimated that lowering the groundwater level by 10 cm from the current level would remove 70% of the methane (CH4) emissions from fens and 45% from bogs. The CO2 effluxes from soil are likely to increase, but the increasing growth of ground vegetation and trees under warming and rising CO2 will likely compensate partly for the emissions into the atmosphere (Gong et al. 2012).

19.3 Provisioning Services: Impacts and Management Under Climate Change

19.3.6 Genetic Resources Genetic resources are among the core primary provisioning services representing species and genetic diversity that facilitate other ecosystem services mainly related to ecosystem structure and functioning and their adaptation to climate change. According to Loo et al. (2011), the survival of different tree species through rapid and intensive changes in environmental conditions requires the capacity to: “(i) quickly adapt genetically to new conditions at existing sites; (ii) survive changing conditions through a high degree of phenotypic plasticity without genetic change; and/or (iii) migrate rapidly to newly evolving environments that match basic physiological requirements”. Loo et al. (2011) emphasize that likely effects on genetic diversity and evolution process are of importance for avoiding extinction

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under climatic warming. Therefore, the natural selection occurring in natural regeneration makes it possible to utilize genetic diversity in meeting climate change. In establishing forest plantations, proper genetic diversity is equally important, and a high planting density is likely to increase opportunities to adapt to meet climate change (Table 19.2). Adaptive properties like drought tolerance and cold hardiness vary across ecological and geographic gradients in the distribution areas of species. The success of regenerating and growing under new environmental conditions needs phenotypic plasticity to grow in a reasonable way under different conditions without genetic change. Phenotypic plasticity is likely related to epigenetic effects. For example, Johnsen et  al. (2005a, b) have shown that the adaptive traits of Norway spruce progenies are related to maternal

Table 19.2  Risk of, and opportunities for adapting genetic resources to climate change in forest regeneration, slightly modified from that compiled by Loo et al. (2011) Advantages, disadvantages in regeneration and practices Advantages

Disadvantages

Natural regeneration Good capacity for adaptation. Good sampling of local genetic diversity for natural selection. Good integration with ecosystem dynamics for increasing general resistance (coadaptation).

Risk of limited number of effectively producing trees. Risk of small number of seedlings. Risk of limited local genetic diversity unavailable for adaptation.

Recommended Maximize the effective number management practices of reproductive trees. Monitor effective seedling density frequently enough through rotation, consider additional planting if necessary.

Planting/seeding material from local region of provenance Good capacity for adaptation. Materially selected sources based on quality. Good integration with ecosystem dynamics and sufficient general resistance. Risk of poor sampling for natural selection in seed harvest. Limited space for natural selection. Risk of too limited regional diversity and poor adaptation to climatic change.

Mix selected stands within the region of provenance when technically possible. Increase initial planting/seeding density.

Planting and seeding of introduced seedlings and seeds in areas where the species already exist Remedying lack of local genetic diversity. Contribution to new ways of adapting.

Risk of poor adaptation. Risk of declining genetic diversity due to material with narrow genetic basis. Risk of declining local genetic resources under threat of massive introduction from outside. Risk of further disturbances of already weakened dynamics of ecosystems. Introduce material originating from region representing conditions likely to be realized in the current region in the future. Introduce material with broad genetic diversity.

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temperatures during seed production. Epigenetic effect refers to the variation in the physiological changes without changes in the DNA sequence, i.e., external, or environmental factors turn genes on and off. Epigenetic changes may adapt offspring to the parental environment, thus ­facilitating cross-generation adaptation to slow transient warming (Saxe et al. 2001). Genetically diverse populations with a high degree of plasticity may have a selective advantage during climate change (Saxe et al. 2001). Adaptation may further be related to genotypic changes or genotypic adaptation, referring to evolutionary changes in genotypes (i.e., natural selection) induced by permanent changes in environmental conditions. Adaptation (adaptive responses) may include changes in structure (e.g., morphology, biochemistry) and functioning (e.g., phenology, growth, and development), representing different ecotypes of the same species with varying responses to the same environmental factors, such as tolerance of low temperatures. Adaptation is driven by the gene flow in the dispersal of pollens and seeds. Pollen dispersal occurs on the scale of thousands of kilometres in airflows from central to northern Europe. On the other hand, seed dispersal represents the scale of kilometres as found by Juntunen and Neuvonen (2006). They have shown that the timber line in western Lapland (the area above 68° N) proceeded northwards 140 m per year in the period 1788–1973  in such a way that the northward movement was 30  km in the 1900s. The movement rate was variable, depending on the variability of seed crop and establishment of seedlings related to climatic variability.

19.4 R  egulating Services: Impacts and Management Under Climate Change 19.4.1 Mitigation of Warming in Ecosystem and Product Technosystem Regulating services are mainly related to the structure of the forest ecosystem, with links to

the structure and functioning of a forest ecosystem. The ecosystem structure provides barriers to reduce the impacts/damages related to, e.g., extreme weather episodes, landslides, snow avalanches, excessive water flow, wind force, heat load, urban noise, and air impurities. The dynamics of forest ecosystem and forests further control the CO2 exchange between forest ecosystem and atmosphere and carbon stored in ecosystem, thus providing feedback between the forest ecosystem, forestry, and atmosphere, with close links to the land use. Regarding separate regulating services, the sustainable regeneration and growth are important for a large set of regulation services. Proper biomass stocking (quality and quantity) is a ­common nominator for regulating climatic hazards, impacts of excess water flow, air impurities, noise abatement, and mitigating climate warming. These services hold under changing climate for solving local problems, excluding mitigating climate warming with important global dimension. However, the mitigation also needs local activities like in land use, including forestry. The forest-­based mitigation includes CO2 uptake in the forest ecosystem and emissions from the ecosystem and technosystem, where timber and biomass are manufactured materials and fuels. Bio-geophysical (water and energy) fluxes further enhance the potential of forestry to mitigate warming like aerosols emitted from forest ecosystems. Mitigation combines carbon uptake and emissions in the ecosystem and technosystem, thus affecting radiative forcing. This further indicates climatic substitution benefits, which are related to the use of wood-based products and fuels (Fig. 19.14).

19.4.2 Carbon in Forest Ecosystem Under Climate Warming Based on a meta-analysis, Sathre and O’Connor (2010) concluded that each Mg of carbon in wood products substitutes for 2.1 Mg of carbon in non-wood products. Intensive management, including nitrogen fertilization, may reduce 28% of the total greenhouse gas emissions over the

19.4 Regulating Services: Impacts and Management Under Climate Change

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Fig. 19.14  Major flows of carbon in/from managed forest ecosystem and forest product technosystem, with radiative forcing related to the net emissions of CO2 into the

atmosphere compared to the radiative forcing under no managed forests

whole of Sweden when the increased forest growth is used to substitute for fossil-based materials and energy. Any management regimes that allow a higher tree stocking and carbon accumulation in soil than a business-as-usual (conventional) one is likely to increase the timber production and simultaneously maintain/increase the total carbon stock in the forest ecosystem and outside (e.g., Jandl et  al. 2007; Paradis et  al. 2019). However, the age-class distribution over a forest landscape has even larger effects on the capacity of the forest ecosystem to retain carbon within it (Garcia-Gonzalo et al. 2007; Kilpeläinen et al. 2017). On the global scale, the residence time of carbon in the atmosphere is variable: 5–15  years depending on the estimates of the atmospheric carbon reservoir and the photosynthetic uptake and flow to oceans (e.g., Cawley 2011). In the terrestrial biosphere, like forests, the residence time varies from the carbon uptake through growth into the ecosystem until carbon is emitted into the atmosphere in respiration and the burning of forest-based materials in the technosystem. On the scale of global boreal forests, residence time is about 90 years, but it varies substantially from tens of years in sites of high fertility to more than 100 years in sites of low fertility (e.g., Raich and Schlesinger 1992). In a managed boreal for-

est ecosystem, the residence time is shorter, in the range of 30–80 years: shorter in fertile sites dominated by deciduous trees and longer in poor sites dominated by coniferous trees. In boreal conditions, the increasing growth in response to climate change implies that carbon storage in forests (trees plus soil) might increase by 5–20% by the year  2050, and 30% by the year 2100 in Finland (e.g., Kellomäki et al. 2005, 2008). However, the accumulation of carbon is dependent on tree species composition, growth, and management. In simulation over a 100-year-­ long rotation. Stendahl et  al. (2010) found that the accumulated detrital and soil carbon down to 1 m in managed Norway spruce forests (9.2 kg C m−2) was 38% larger than in managed Scots pine forests (5.7  kg C m−2). The difference between these tree species indicated the differences in the productivity and difference in litter fall as shown in Table 19.3 for the main tree species in Finland as a function of site type (Akujärvi et al. 2016). However, climate warming is likely to reduce the carbon accumulation in the ecosystem under extreme warming. Based on eddy covariance measurements, Geddes et  al. (2014) found that extreme high temperature reduced the gross ecosystem productivity by 25% in 2011 compared to that under normal temperature in 2010  in the southern boreal zone in Canada. The reduction

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Table 19.3  Mean annual carbon input to soil in southern boreal managed forests as a function of tree species and site fertility (site type) from extremely high fertility to extreme low fertility (Akujärvi et  al. 2016): OMaT = Oxalis-Maianthemum, OMT = Oxalis-Myrtillus, MT = Myrtillus, VT = Vaccinium and ClT = Cladionia site type Main tree species Scots pine Norway spruce Silver birch

Site type and carbon input, kg C m−2 year−1 OMaT OMT MT VT CT ClT 0.19 0.21 0.22 0.20 0.15 0.15 0.32 0.32 0.24 0.19 0.16 0.14 0.27

0.29

0.23 0.15 0.24 0.23 a

Legend: The alphabet (a) indicates that the value is estimated based on litter production in Scots pine in sites of Vaccinium site type, VT

was partly related to the mortality of flushing foliage with the subsequent low leaf area index. Warming is likely to enhance the decay of soil organic matter in interaction with soil moisture defined by the balance between precipitation and evaporation. Kirschbaum (1995) showed that an increase of 1 °C in the annual mean temperature is likely to increase the loss of soil carbon by more than 10%. This is true for regions where the annual mean temperature of organic soil is 5 °C, while it is 3% in regions where the annual mean soil temperature is 30 °C. Using the decay model of Meentemeyer (1978), Kellomäki et al. (2005) found that carbon in soil organic matter will reduce by 5% in southern and middle boreal conditions by 2050 and a further 10% by 2100. The reduction will be local and related to a reduction in the growth and litter fall of Norway spruce for increasing drought episodes. Regionally, the soil carbon will continue to increase even in the southern boreal zone to the end of this century, but the rate of decay is likely be slower than in the northern boreal conditions (Kellomäki et al. 2005). Experimental ecosystem warming has been used to investigate how climate warming is likely to affects the decay of soil organic matter and soil respiration. Regarding experimental warming, Rustad et al. (2001) summarized the findings in 32 experiments extended over 2–9  years. Warming was in the range 0.3–6.0 °C, representing a 20% increase in soil respiration and net nitrogen mineralization of 46%, inducing a 10% increase in plant growth. The response of soil res-

piration was, in general, larger in forested ecosystems than in low tundra and grassland ecosystems. Rustad et al. (2001) further emphasize the importance of the spatial and temporal variability of the response to warming when scaling the findings over larger areas (Box 19.4).

19.4.3 Combining Ecosystem and Product Technosystem in Mitigating Warming In the following,  forest-based carbon balance (CB) includes the net accumulation rate of carbon in biomass (CBBiomass) in trees, carbon in soil (CBSoil), and carbon in wood-based products and fuels (CBProducts). Following Kilpeläinen et  al. (2014), Zubizarreta-Gerendiain et al. (2016), and Pukkala (2017):

CB  CBBiomass  CBSoil  CBProducts (19.1)

CBBiomass  Growth  Ingrowth – Litter – Harvest (19.2) CBSoil  Mortality  Litter  Residues – Decomposition



CBProducts  New Products – Decomposition – Release  Substitution Effects

(19.3)

(19.4)

where New Products are the products based on Harvest, Decomposition is the decay of old and new products, Release is the carbon emission due to harvest, transporting and manufacture of new product, and Substitution is the reduction of carbon emission related not to the use of fossil energy and materials (Fig. 19.15). Zubizarreta-Gerendiain et  al. (2016) investigated how management, harvest and use of wood for different purposes would affect carbon in forestry related to carbon balance and carbon stocks. The calculations were done for Scots pine, Norway spruce, and birch growing in the middle boreal zone (62° N) under current and warming climate. Warming climate represented the SRES

19.4 Regulating Services: Impacts and Management Under Climate Change

Box 19.4: Root as Sink and Source of CO2

According to Clemmensen et al. (2013), roots and associated fungi have a large role in longterm carbon sequestration in boreal forests, i.e., 50–70% of stored carbon in forest is related to roots and root-associated microorganisms. Fine roots form a major sink for the total carbon taken up by trees, as demonstrated by Högberg et al. (2001) for Scots pine. They girdled trees to the depth of xylem, curbing the supply of photosynthates to roots. Consequently, the soil respiration declined about 50% compared to ungirdled trees. Thus, respiration in fine roots recycled in a few days a large part of carbon bound in photosynthesis back to the atmosphere (Pregitzer et al. 2000; Högberg et  al. 2001). Högberg et  al. (2002) suggested that 75% of the carbon allocated to the roots of Scots pines is respired and 25% used for growth. The root respiration rate, nitrogen uptake rate, and specific root length (i.e., root length per root mass) are closely correlated with each other, thus showing the links between root respiration and primary production in canopy (Reich et al. 1998). In general, elevated CO2 increases the growth and mass of fine roots (e.g., Saxe

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et  al. 2001; Janssens et al. 2005). This suggests an increase in soil respiration as found by Drake et  al. (2008) in the Duke FACE experiment for loblolly pine (Pinus taeda L.). Fine root respiration represented 43% of the annual soil respiration under ambient CO2, while the same share was 50% under elevated CO2. However, the specific respiration rate in fine roots decreased (Hamilton et  al. 2002); i.e., elevated CO2 reduced the mean respiration rate by 23% relative to the values in the ambient CO2. The reduction was relative to the declined nitrogen in roots. On the other hand, Qi et al. (2004) found that the fine root respiration in Douglas fir (Pseudotsuga menziesii) decreased by 4–5  nmol CO2 per gram of root dry weight for every doubling of CO2 in the soil. Boone et al. (1998) further found that the Q10 value for roots in a mixed temperate forest was 4.6, which was substantially higher than that (2–3) commonly used for other organs. The high sensitivity of fine roots to warming is likely to limit carbon sequestration in soil, even though elevated CO2 and temperature are likely to increase carbon uptake (e.g., Melillo et al. 1982).

Fig. 19.15  Outline for cycling of carbon in the context of based energy and materials. (Olsson 2011, pp.  22–23. forest ecosystem and forest-based production, including Courtesy of Air Pollution & Climate Secretariat) forest-based energy and materials in substituting fossil-­

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A1B emission scenario, doubling the atmospheric CO2 concentration, increasing the annual temperature by 4 °C and increasing precipitation by 10% by the year 2100 (Jylhä et al. 2009). The simulations were done for three 20-year-long periods (in total up to 60 years) when using even-­ aged management with thinning from below and above. The current management recommendations were used to define the earliest thinning from below and above, and the timing of final felling. In addition, thinning and final cutting were delayed beyond the earliest possible. In optimization, the equal and sustainable net income (NPV) for each 20-year period was maintained using a 2% interest rate (Fig. 19.16). As expected, the thinning from below reduced the carbon balance, regardless of climate (Fig. 19.17). The dominance of both Scots pine and Norway spruce implied that management scenarios TB1 (thinning from below, no biofuel) and TB2 (thinning from below, Norway spruce pulpwood used for biofuel) gave the lowest carbon balance. This was because of the low amount of carbon in trees and soil. In both cases, the amount of carbon increased substantially when thinning was delayed beyond the recommended limit. Carbon was also increased when thinning was done from above. The use of Scots pine and birch pulpwood for fuel increased the carbon balance more than when using Norway spruce pulpwood for paper and related products. Furthermore, the use of harvest residues (treetops, branches,

Fig. 19.16  Outline of the links between harvest and use of timber and biomass for manufacturing simulated by Zubizarreta-­ Gerendiain et al. (2016). (Permission of Elsevier)

stumps, and coarse roots) for fuel (TA6) increased the total carbon balance by 3–9%. In general, the carbon in forest biomass increased under the changing climate compared to under the current climate (Fig. 19.17). This was because of the increase of final biomass related to the equal income targeted under both climate scenarios. This contrasted with the amount of carbon in soil, where the carbon balance decreased slightly because of the accelerated decay under warming. Climatic warming increased by 2–7% of the net present value, regardless of management scenario. Any scenario increasing carbon in a forest-based system raised the net present value. However, the net present value tended to be lower when thinning from below was used than under thinning from above (Zubizarreta-Gerendiain et  al. 2016). In the context of forestry and forest-based industry, radiative forcing integrates the climate impacts related to the carbon uptake in growth and the carbon emissions in harvest and manufacturing processes and heterotrophic respiration. Radiative forcing further includes the radiative forcing related to the carbon emissions in the management, harvest and production of wood-­ based material and energy. Carbon emissions from abundant materials burnt or left in landfills further affects radiative forcing. Such a forest-­ based forcing integrates ecological and technological systems covering the atmospheric/

Saw log

Sawn wood

Fuel wood

Waste

Pulpwood

Paper and packing material

Fuel wood

Waste

Fuel wood

19.4 Regulating Services: Impacts and Management Under Climate Change

Fig. 19.17  Upper: Regarding carbon balance and carbon stocks under varying management over 60 years for Scots pine and Norway spruce forests in middle boreal forests  (62° N). Lower: Carbon stocks including carbon in timber, soil and wood products (Zubizarreta-Gerendiain et  al. 2016. (Permission of Elsevier). Warming climate TB1 TB2 TB3 TA4 TA5 TA6

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represented the SRES A1B emission scenario, doubling the atmospheric CO2 concentration, increasing the annual temperature by 4 °C and increasing precipitation by 10% by the year 2100 (Jylhä et  al. 2009).  The description of management scenarios is below

Thinning from below when stand basal area exceeds the thinning limit. Only saw logs and pulpwood are harvested. Same as in TB1, excluding spruce pulpwood. Stem part in the diameter range 5-16 cm is harvested for fuel. Same as in TB2, except delaying thinning in young stands allowed without any limit. Same as TB3, except that thinning from above was replaced by thinning from above. Same as TA4, excluding pine and birch pulpwood. Small stems and the upper parts of log-sized pines and birches were harvested for fuel (diameter < 5 cm). Same as TA4, except that 70% of treetops, branches and stumps were harvested for biofuel in clear felling site.

terrestrial carbon cycle controlling the carbon dioxide content in the atmosphere. The cumulative radiative forcing (CRF, nW m−2) indicates the cumulative increase of energy heating (posi-

tive forcing, energy lost in space < energy entering) or the cumulative reduction of energy cooling (negative forcing, energy lost in space > energy entering).

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The integrated cycle of forest-based carbon can be used for the overall assessment of how the use of forest-based biomass affects climate warming as Torssonen et  al. (2016) did. In the simulations, a forest region was dominated by Norway spruce, with a stable age-class distribution, located in the middle boreal conditions (62° N). The simulations extended over an 80-year period, using the current climate and gradually warming climate under emission scenarios SRES B1 and A2 (IPCC 2007). A forest ecosystem model was further integrated with a life cycle

assessment tool for simulating the climate effects of varying management options on the production of biomass used for energy. The impacts of varying management options were compared to the business-as-usual management in order to identify how different management options affect radiative forcing when substituting coal with biomass in energy production (Fig. 19.18). Net carbon uptake was smallest when using business-as-usual thinning and allowing harvest residues decay in sites (management option BT). As expected, net carbon uptake increased when

Fig. 19.18  Effects of climate change and even-aged management on net climate impacts (CRF, cumulative radiation forcing) of production and utilization of energy biomass in Norway spruce with stable age-class distribution. (Torssonen et al. 2016. Permission of Wiley & Sons). Explanations for Figure: Left: Mean annual net ecosystem exchange (g CO2 m−2 year−1) for different forest management scenarios under different climate scenarios. Legend: BT is thinning on a business-as-usual basis, with no harvest of logging residues; BN is thinning on a business-as-­usual basis, but logging residues (branches, needles, and stem tops at final felling) are harvested; BNR is thinning on a business-as-

usual basis along with harvest of logging residues at final felling; BN/BNR±20 is a 20% increase/decrease of the basal area before and after thinning; F is nitrogen fertilization (150 kg N ha−1), twice during the rotation. Right: Cumulative radiative forcing (nW m−2) when using forest biomass for energy related to management and climate scenario. Upper/Right: For current climate, Middle/ Right: For climate scenario SRES B1; and Below/Right: For climate scenario SRES A2. Output under business-asusual (BT) management was used for the reference scenario assuming that the same amount of energy was produced under management BN/BNR20(F) as using coal.

19.4 Regulating Services: Impacts and Management Under Climate Change

logging residues were harvested and further when management options represented more intense thinning for the use of logging residues for energy biomass. At the highest, the increase was 90–100% when higher thinning thresholds, nitrogen fertilization and intensified harvest of energy biomass were used (management option BNR20F). The net ecosystem CO2 exchange slightly increased under the SRES B1 scenario compared to that under the current climate, whereas the situation was opposite under the SRES A2 climate scenario, regardless of management option (Torssonen et al. 2016). Cumulative radiative forcing (CRF, nW m−2) shows that the forcing was negative when coal was replaced with energy biomass, regardless of management option. The cooling effect was largest when management options BNR20 and BNR20F were used in the simulations. Intensive harvest of energy biomass led to greater cooling, regardless of climate scenario. Cumulative radiative forcing under management options BN(F)/ BN20(F) varied from −0.7 to −1.1 nW m−2, but there were no differences between climate scenarios. For management scenarios BNR(F)/ BNR20(F), the corresponding range was from −2.1 to −3.6  nW m−2. Under climate scenarios SRES B1 and A2, the values of cumulative radiative forcing were smaller than under the current climate, partly because of the higher background CO2 concentration in the atmosphere and the declining growth of Norway spruce under warming (Torssonen et al. 2016).

19.4.4 Forest Spectral Properties, Biogeochemical Emissions in Mitigating Warming Management and harvest, in general, change the forest spectral properties (albedo) and enhance the capacity of the forest sector to mitigate climate change (Fig. 19.14). In this respect, albedo controls the heat fluxes and consequent warming related to the forest cover (e.g., Bright et al. 2011, 2015). Albedo is high in deciduous but low in coniferous canopies. Therefore, deciduous species in pure plantations, or mixed in coniferous

673

plantations, are likely to reduce warming. On the other hand, albedo decreases towards the maturity of trees with full canopy cover (e.g., Kuusinen et al. 2012, 2015; Kuusinen 2014). Management combining high carbon stocks and albedo is likely to mitigate warming more than management only for timber and biomass (e.g., Schwaiger and Bird 2010; Kirschbaum et al. 2011). Biogeochemical (GHG emissions) and bio-­ geophysical (water and energy) fluxes further enhance the potential of forestry to mitigate warming (e.g., Jackson et al. 2008; Naudts et al. 2016; Bright et al. 2015). Particles emitted from forest reflect short-wave radiation into space, thus reducing warming. Aerosols and volatile organic compounds (BVOCs) emitted from forest ecosystems increase cloudiness and the reflectance of short-wave radiation (e.g., Spracklen et al. 2008). Thus, forest policies based only on management and harvest of timber and biomass are unlikely to lead to optimal use of the forest sector for slowing warming (Sjølie et  al. 2013; Lutz and Howarth 2014; Bright et al. 2014; Lutz et al. 2016) (Box 19.5). Climate change likely affects BVOCs in several ways, including the changes in the growing

Box 19.5: Emissions of BVOCs in Boreal Forest Related to Dynamics of Primary Production

Forests emit volatile organic compounds (BVOCs), with isoprene (C5H8) and terpenes (C10H16) being dominant. Tree species are roughly divided into isoprene emitters and, like many deciduous trees including oak (Quercus sp.), terpene emitters, like Scots pine and birch. Norway spruce emits both isoprene and terpenes. Monoterpene emissions (EPS) are light-­ independent and mainly from monoterpenes stored (Epool) in resin ducts and from the emissions taking place as light-­ dependent biosynthesis (Esynthesis):

EPS  Epool  Esynthesis



(19.5)

19  Forest Ecosystem Services and Management Under Climate Change

674

Box 19.5: (continued)



Epool  EFmt  exp     T  Ts   (19.6)

Esynthesis  EFmt  CL  CT (19.7) where EFmt is the emission at a temperature of 25  °C, and flux density of 1000  μmol m−2 s−1, and CL and CT are the correction factors dependent on flux density and temperature. Ts is the parameter [25 °C] and β is the temperature dependency of the emitted compound. Natural BVOC emissions are sensitive to disturbances such as herbivory or forest management and timber harvest. Räisänen et al. (2008), for example, found that from June to September the monoterpene concentration in the air was two to three times the normal level during the first days or month after a clear cut of a boreal Scots pine stand compared to the uncut area (Table 19.4). The increase was larger than in the thinned stands. The differences in monoterpene concentrations between clear-cut and thinned areas were related to the differences in the amount of logging residues and pulpwood left in the areas. At the end of the monitoring period (four months after the cut), there were only small differences in monoterpene concentrations between the clear-cut and uncut areas.

Table 19.4  Effects of clear cut and thinning with 30- and 60-percent removal of basal area on monoterpene concentration (μg m−3) over a summer months  in the air in Period June 22–23 June 29–July 3 July 22–24 July 27–29 August 16–20 September 22–24 Mean over periods

season, tree species composition, the mass of foliage in different tree species and the emission rates specific to different BVOCs. Kellomäki et  al. (2001a, b) showed that the proportions of Scots pine and Norway spruce in southern Finland (60° N < latitude 1000 ppm) (Leverenz and Lev 1987). The regeneration success might, however, be improved in response to the elevating atmospheric CO2 because of the increase of seed crops, and the accelerated growth of seedlings (Kimball 1983). The CO2 elevation may further increase the water use efficiency of seedlings, enabling them to tolerate the water shortage and shading among competing ground cover species. However, the regeneration success might be reduced by the herbivory of many invertebrates and fungi destroying seeds and seedlings (Box 19.6).

19  Forest Ecosystem Services and Management Under Climate Change

678

Fig. 19.20  Likely tendences in how climate change affects the processes of natural regeneration of forest trees in boreal conditions. (Nygren 1990; Karjalainen et al. 1991)

Process in regeneration Production of seeds Amount of flowers Amount of pollen Dispersal of pollen Pollination Seed maturation Dispersal of seeds Establishment of seedlings Germination Initial growth Growth of seedlings Survival of seedlings

Elevating CO2

Elevating temperature

Changes in precipitation

+ + ? + ?

+ + + + +

+ + +/– +/– +/–

?

+

+/–

? + + +

+ + + +

+/– +/– +/– +/–

4000 A

2000 1000

25000

1

3

B

Southern Finland Northern Finland

15000 10000 5000 0

1

3

5 7 9 11 13 15 17 19 Age of cohort (yr)

Fig. 19.21  Left: Density of a 20-year-old Scots pine seedling stand in southern and northern boreal conditions  as a function of the age of seedling cohorts under current (upper) and elevated temperature (lower). Right: Diameter distribution (diameter 1.3 m above ground level)

Box 19.6: Success of Natural Regeneration of Scots Pine Under Climatic Warming

Kellomäki and Väisänen (1995) simulated the regeneration of Scots pine under the current and warming climate. The sites were of medium fertility (Myrtillus site type, MT) in the southern (61° N) and northern (66° N) boreal zone. The moisture content in the surface soil was 21  m3 m−3 at the wilting point and 54 m3 m−3 at field capacity (Fig. 19.21). The current mean annual temperature represented the period 1960–1980, while under warming the mean annual temperature was 5 °C higher than the current one. Regardless of the site and climate, the mean annual precipitation was 600 mm throughout the simulations, which were extended over 20  years representing the timescale typical in natural regeneration. Atmospheric CO2 concentration was 350  ppm over the whole simulation period. The number of seedlings varied from year to year following temperature fluctuation.

16000

679

Current temperature Southern Finland Northern Finland

12000 8000 4000 0

5 7 9 11 13 15 17 19 Age of cohort (yr) Elevated temperature

20000

Density (seedlings ha-1)

Southern Finland Northern Finland

3000

0

Density of cohort (seedlings ha -1)

Current temperature

2 Stem diameter (cm) Elevated temperature

100000

Density (seedlings ha -1)

Density of cohort (seedlings ha -1)

19.6 Management Under Climate Change, with Selected Measures and Problems Likely to Emerge

Southern Finland Northern Finland

60000 40000 0

2 Stem diameter (cm)

of Scots pine seedlings in a 20-year-old stand under the current (upper) and elevated (lower) temperature. (Kellomäki et al. 1997b. Permission of Canadian Science Publishing)

Under the current climate, the number of seedlings was particularly abundant every 4–6 years, with a shorter interval in the south than in the north (Koski and Tallqvist 1978; Pukkala 1987). This pattern held under warming, but even in the north there were no years without establishment. Under warming, the probability of seedlings dying was highest just after establishment, whereas only some of the original seedlings survived under the current climate over 20 years. Warming improved the growth and survival of seedlings, thus increasing the final density of seedling stands (Kellomäki and Väisänen 1995). Under warming, ground ice, snow compaction, and an absence of snow likely damage tree seedlings (e.g., Martz et al. 2016). Shortly after regenerative cutting (parent tree method), most seedlings had a diameter 1050 d.d., southern boreal  Evapotranspiration −1 −2 −3 −6 −10  Water infiltration +10 +8 +6 +4 +2  Total GPP −1 −8 −18 −30 +3  Total stem wood −5 −11 −16 0 +1 growth −2 +16 +16 +12 +6  Total timber yield  Mean diameter +15 +25 +35 +47 +7 Site ZIII (900 d.d. < TS < 1050 d.d.), middle boreal  Evapotranspiration −1 −2 −3 −5 −9  Water infiltration +7 +6 +5 +3 +2  Total GPP −3 −10 −21 −32 +1  Total stem wood −3 −9 −16 0 +1 growth −4 +4 +13 +13 +9  Total timber yield  Mean diameter +15 +24 +34 +46 +7 Site ZIV (TS < 900 d.d.), northern boreal  Evapotranspiration −2 −4 −7 −12 −17  Water infiltration +10 +9 +6 +4 +2  Total GPP −1 −9 −18 −30 −42  Total stem wood −2 −6 −12 −19 0 growth +21 −6 −13 +4 +6  Total timber yield  Mean diameter +13 +21 +29 +39 +6 Site ZV (TS < 900 d.d.), northern boreal  Evapotranspiration −1 −3 −7 −10 −15  Water infiltration +10 +8 +7 +5 +3  Total GPP −7 −17 −29 −41 −51  Total stem wood −1 −5 −10 −16 −22 growth −2 −5 −10 −15 −21  Total timber yield  Mean diameter +16 +20 +29 +9 +4

19.6 Management Under Climate Change, with Selected Measures and Problems Likely to Emerge

(T30, T40, T50). Further north (ZIII–ZV, temperature sum < 1050 d.d.), thinning of any intensity reduces the total gross photosynthesis by up to 50% under thinning T50. Based on model calculations and experimental findings, Bergh et al. (2005) showed that a water deficiency of the same magnitude as in our case is likely to reduce the potential growth of Norway spruce by 10–20% of that under no water deficiency. As expected, the relationship between the total gross photosynthesis and thinning intensity implies a similar relationship between the thinning intensity and the total stem wood growth (Table 19.6). The total stem wood growth in the south is up to 3% larger than that under no thinning when thinning intensity is moderate (thinning intensity < T30). Under more intensive thinning, the total stem wood growth reduces by up to 16%. Further north, even small thinning reduces the total stem wood growth in relation to the thinning intensity. In the northern boreal zone (Zv, temperature sum < 900 d.d.), the reduction is 50% under very intensive thinning (T50). This implies that the timber yield decreases as a function of the reducing total stem wood growth across the boreal zone. The highest timber yield is obtained under low- or moderate-intensity thinning (thinning intensity < T30). This implies that intensive thinning reduces stocking and growth to such an extent that this loss is not fully compensated for by the likely increase in growth of single trees induced by climatic warming. This is most evident in the north, where the impact of reducing stocking is larger than in the middle and southern boreal zones.

19.6.6 Management of Tree Species Mixtures Compared to Scots pine and birch, Norway spruce is shade-tolerant, but its growth might be reduced due to the increasing drought episodes both in pure and mixed stands. Ge et al. (2011b) carried out a simulation experiment with two

685

unmanaged stands dominated by Norway spruce, with a mixture of Scots pine and birch growing in southern (62° N) and northern (66° N) boreal zones over a 100-year period (Table  19.7). The initial tree species composition included 50, 25 and 25% initial density for Norway spruce, Scots pine, and birch. In the simulations, the pure stands of Norway spruce, Scots pine and birch were further used for identifying whether species-­ specific response is different in mixed and pure stands. In the simulations, rainwater was depleted in evapotranspiration (ET, mm), including transpiration (Et, mm) and evaporation from canopy (Ec, mm) and ground surfaces (Eg, mm): ET = Ec + Et + Eg). Water on the surface infiltrated (Win, mm) into the soil profile, while water in the surface pool (Wsurf) representing water in throughfall was not intercepted and did not evaporate in the canopy. Concurrently, water is evaporated from the surface pool (Eg) and runs outside the pool (Wrunoff) in the surface flow (Eqs. 19.8, 19.9).  The relative availability of water in the rooting zone indicated a potential soil water deficit (Wd, mm) (Granier et al. 1999):



Win  Wsurf  Eg  Wrunoff



Wd  0.4   WF  WW    WS  WW  

(19.8)

(19.9)

where WF and Ww are the volumetric water content [m3 m−3] at the field capacity and at the wilting point, and WS is the soil volumetric water content in the rooting zone. Regardless of tree species, both annual net canopy photosynthesis (Pnc) and total stem wood growth (Vs) decreased, on average, in the south under a warming climate. The situation was opposite in the north (Table 19.7). In pure stands, the growth of Norway spruce in the south could be even lower because of a 15% reduction in the total net photosynthesis compared to that under the current climate. This also held for Scots pine and birch, with a 13% reduction. In the north, the situation was different, with the total net photo-

19  Forest Ecosystem Services and Management Under Climate Change

686

Table 19.7 Cumulative net photosynthesis and total stem wood growth in mixed stands for Scots pine, Norway spruce, and birch under the current and changSites and species in Species in mixed stands Southern site  Norway spruce  Scots pine  Birch  Total Northern site  Norway spruce  Scots pine  Birch  Total Species in pure stands Southern site  Norway spruce  Scots pine  Birch Northern site  Norway spruce  Scots pine  Birch

ing climate in southern boreal (62° N) and northern boreal (66° N) sites over a 100-year simulation period (Ge et al. 2011a)

Total net photosynthesis (Pnc, Mg C ha−1) Current Changing

Total stem wood growth (Vs, m3 ha−1) Current Changing

780 78 84 924

676 (−15) 69 (−12) 74 (−13) 819 (−15)

667 156 133 956

610 (−9) 144 (−8) 127 (−5) 881 (−8)

634 63 79 776

715 (+11) 80 (+21) 88 (+10) 883 (+12)

394 100 76 569

441 (+10) 125 (+20) 83 (+8) 649 (+12)

940 807 1026

795 (−18) 926 (+13) 1,198 (+14)

834 902 1274

738 (−13) 984 (+8) 1,311 (+7)

753 685 869

824 (+12) 896 (+24) 1,090 (+20)

507 745 865

562 (+11) 957 (+22) 1,044 (+17)

Figures in parentheses show the percentage change in total net photosynthesis and total stem wood growth under the changing climate (SRES A2 emission scenario) compared to those under the current climate. The simulations are done with a process-based forest ecosystem model (FinnFor) (Kellomäki et al. 1997a). The site fertility (Myrtillus site type, MT) and moisture conditions were the same at the beginning of the simulations for both sites. The atmospheric CO2 content was 350 ppm for the current climate, increasing up to 840 ppm by 2,100

synthesis tending to increase under warming for each tree species. The increase was 11, 21, and 10% for Norway spruce, Scots pine, and birch in relation to that under the current climate. As expected, the total stem wood growth (Vs) reduced in the south by 9% for Norway spruce, 8% for Scots pine and 5% for birch in relation to the current climate. Furthermore, drought likely reduced litter and humus, thus affecting the nitrogen availability in the long run (Ge et al. 2010). In the north, the situation was the opposite: stem wood growth (Vs ) increased by 10, 20, and 8% for Norway spruce, Scots pine and birch when warming was assumed. This indicated that in the future the management should be properly adapted to climate change in order to sustain the productivity of mixed stands dominated by Norway spruce.

19.6.7 Growth of Scots Pine, Norway Spruce, and Birch Under Warming Future dominance of birch and a decline in conifers have previously been found in several model simulations (e.g., Kellomäki and Kolström 1994; Kellomäki et  al. 2008; Ge et  al. 2013c), field monitoring (e.g., Mäkinen et al. 2000, 2001) and field experiments (e.g., Jyske et  al. 2010). This holds especially for the growth of Norway spruce in the south, where soil water reduces with increasing drought events as found by Lagergren and Lindroth (2002). This was also evident in the simulation by Kellomäki et al. (2018), who used a gap-type growth and yield model for investigating the climate change impacts on the annual diameter growth of Scots pine, Norway spruce

19.6 Management Under Climate Change, with Selected Measures and Problems Likely to Emerge

687

and birch. Under different RCP scenarios (Fig.  19.25), warming tends to increase the growth of different tree species in the north over a 100-year period substantially more in birch and Scots pine than in Norway spruce. In the south, the growth of Norway spruce may decrease largely under moderate (RCP4.5) and severe (RCP8.5) climate change towards the end of the

simulation period, in contrast to that of birch. The growth of Scots pine may also decrease slightly under severe warming. The degree of differences between tree species and different parts of boreal forest tends to increase along with the severity of climate change (Box 19.8). Under different RCP scenarios and 30-year calculation periods, the diameter growth in Scots

Fig. 19.25  Left: Percentage change of diameter growth of Scots pine, Norway spruce, and birch over time, representing upland medium-fertile (Myrtillus site type, MT) sites under minor (RCP2.6), moderate (RCP4.5) and severe (RCP8.5) climate change in relation to that under the current climate. Dotted lines indicate the changes in the north (Rovaniemi, 66° N) and solid lines the changes

in the south (Tampere, 61° N). Right: Mean percentage change of diameter growth for Scots pine, Norway spruce, and birch per subperiod in the north and south representing different RCP scenarios in relation to that under the current climate. (Kellomäki et  al. 2018. Courtesy of Forests/Open Access)

688

19  Forest Ecosystem Services and Management Under Climate Change

Box 19.8: Outlines for Developing Growth Response Functions

The gap-type forest ecosystem model Sima (Kellomäki et al. 2008) was used to generate the data for compiling the functions to analyze the response of the diameter growth (Δdbh, cm) of boreal Scots pine, Norway spruce, and birch to different climate change projections. The climate change data were based on the means of 28 recent generations (CMIP5) representing mild, moderate, and severe RCP forcing for the period 2010–2099. The current climate data represented the measured temperature and precipitation during the period 1981–2010. The relative diameter growth (Δdbhrel) under the current (cur) and certain climate change (cc) scenarios at year t under otherwise similar site and tree properties is (Kellomäki et al. 2018):

medium (fresh heath, Myrtillus site type, MT) to rich (grove-like heath, OxalisMyrtillus site type, OMaT) sites under each climate change scenario. The values of shape parameter q in Eqs. (19.10) and (19.11) were not affected by climate change, thus allowing the multiplier for diameter growth (dbhm(t, cc)) to be: dbhm(t cc) = K(t, cc)/K(t, cur)(19.12)

In the numerator, the values of K(t, cc) are a nonlinear function of the time since the launch of a certain climate change scenario as estimated separately for each tree species, site type, location, and climate scenario: K(t, cc)  =  (a  ×  t2  +  b  ×  t  +  c)  −  K(t  =  1, ×cc). The location-specific values of parameters a, b, and c were linearly related to the temperature sum (TS, dd.). dbh  t ,cur  Climate change projections represented dbhrel  t ,cur   dbh GCM runs: GFDL-CM3-RCP4.5, GFDL K  t ,cur   exp  q  cur   dbh  CM3-RCP8.5, HadGEM2-RCP4.5, and HadGEM2-RCP8.5 for the period 2010−2099. (19.10) In the south and north, the annual mean temdbh  t ,cc  perature increased by up to 3.8−5.9  °C dbhrel  t ,cc   depending on the climate change projection. dbh In the south, the annual mean precipitation  K  t ,cc   exp  q  cc   dbh  increased by 6% and 13% by GFDL-CM3(19.11) RCP4.5 and GFDL-CM3-RCP8.5, while it where dbh is the diameter [cm]. The values reduced by 6% and 9% by HadGEM2-RCP4.5 of parameters K and q were estimated for the and HadGEM2-RCP8.5. In the north, the preten-year subperiods representing the interval cipitation increased by 11−27% depending on 2010–2099 for each tree species for southern the GCMs. In the simulations, the current boreal (61° N), middle boreal (63° N) and atmospheric CO2 will increase from 350 to northern boreal (66° N) sites. The estimates 538 ppm (RCP4.5) and 927 ppm (RCP8.5) by were further extended from poor (dry heath, the year 2100. The simulations used the invenCalluna site type, CT), through quite poor tory plots of the Finnish National Forest (dry heath, Vaccinium site type, VT) and Inventory (NFI).

pine increased by up to 10–16% on medium-­ fertile (Myrtillus site type, MT) sites in the south, and by up to 34–94% in the north (Fig.  19.25). However, the growth declines in the south after the first 30–60  years, depending on the climate

scenario. During the last 30-year period, the growth increase in the south is still on average 7–13% higher under RCP2.6 and RCP4.5 than under the current climate, but 29% lower under RCP8.5. Growth also declines slightly in the

19.6 Management Under Climate Change, with Selected Measures and Problems Likely to Emerge

north under RCP2.6 during the last 30-year period. The growth of Norway spruce increases substantially less than that of Scots pine. Growth increases only in the north, up to 14–27% under different RCP scenarios compared to the current climate. During the last 30-year period, growth declined slightly in the north under RCP2.6 and RCP4.5. Under RCP8.5, the decline is up to 7% compared to the growth under the current climate. In the south, growth decreases under the changing climate during the first 30–60  years, i.e., up to 3–12% lower depending on the RCP scenario. During the last 30-year period, growth in the south is 10–95% lower than under the current climate. Concurrently, the growth of birch increases significantly more than that of Scots pine and Norway spruce, by up to 21–76% over different 30-year periods in the south, and by 41–167% in the north under different RCP scenarios. However, the growth of birch declines slightly in the south under RCP2.6 during the last 30-year period. Simulations were further carried out throughout the country, using the sample plot grid used in the National Forest Inventory (NFI 11). In general, the growth response of boreal forests is dependent on the severity of the climate change scenario, tree species, and local climatic and site conditions. Figure  19.26 shows that the mean growth may increase significantly more in the northern than in the southern boreal region, regardless of the RCP scenario. Under RCP2.6, mean forest growth may increase throughout the country. On the other hand, the growth may decrease substantially towards 2100 under RCP4.5 and RCP8.5, especially in the south. However, in the middle boreal region, forest growth may also reduce slightly under the RCP8.5 scenario in the last 30-year period. The simulations suggest that the preference for Scots pine and birch or mixtures of conifers and broadleaves is likely to reduce the future risk of declining forest growth in the southern boreal region, while in the northern boreal forest drought effects are marginal (Table 19.8).

689

19.6.8 Productivity and Rotation Length Related to Growing Conditions In general, the productivity of boreal forests is likely to increase in response to elevated CO2 and temperature due to longer growing seasons and increasing mineralization of nitrogen. To avoid increasing self-thinning and to utilize the increasing growth and yield, an earlier and/or more intensive thinning and shortened rotation may be necessary, as found by Kellomäki et al. (1997a). They used a process-based ecosystem model (FinnFor) to study how increasing CO2, temperature and precipitation would affect the timber yield from stands of boreal Scots pine in southern boreal conditions (61 N). In the simulations, the initial stand density was 2,500 seedlings per hectare established in a site of medium fertility (Myrtillus type, MT), with a water content of 0.21 m3 m−3 at the wilting point and 0.53 m3 m−3 at field capacity. Under the current climate, the mean annual temperature was +3.6 °C, with the precipitation being 610 mm and the CO2 concentration 350 ppm. Climate change included: (i) a temperature increase of 0.4 °C per decade; (ii) a precipitation increase of 9 mm per decade; (iii) a CO2 increase of 33  ppm per decade; and (iv) a combined increase of temperature, precipitation, and CO2 based on the IS92a emission scenario (Carter et al. 1995). In general, growth is larger in unthinned than thinned stands. This is because the stocking is lower in thinned stand through the rotation than that in unthinned stand. In both cases, trees mature faster under the changing climate than under the current one (Fig.  19.27), especially when temperature, precipitation, and CO2 increases are combined. More rapid growth and development under the changing climate reduce the rotation length and make thinning earlier than under the current climate. The average total stem wood production over the rotation was 6.2  m3 ha−1year−1 under the current CO2 and temperature and increasing precipitation alone. When temperature alone is increased or along with precipi-

690

19  Forest Ecosystem Services and Management Under Climate Change

Fig. 19.26  Left: Spatial distribution of the mean combined relative change of diameter growth over Scots pine, Norway spruce, and birch in upland forest sites for the 30-year calculation periods (2010–2039, 2040–2069, and 2070–2099) under minor (RCP2.6), moderate (RCP4.5), and severe (RCP8.5) climate change. The numbers in the figures indicate the old administrative regions used in

practical forestry and in forestry statistics. Right: Percentage distribution of changes in combined growth responses in relation to the total number of cases for the 30-year periods and RCP scenarios across the whole country. (Kellomäki et al. 2018. Courtesy of MDPI Forests/ Open Access)

tation, the mean annual growth is 6.8  m3 ha−1 year−1 (+ 9%). Similarly, the annual growth is 7.4 m3 ha−1year−1 (+19%) for elevating CO2 alone and 8.0 m3 ha−1 year−1 (+ 28%) for the combined elevation of temperature, precipitation, and CO2. In the simulations, climate changes gradually, thus the differences in growth between climatic scenarios are small in the early rotation

(Fig.  19.28). The first thinning is made at the same time in all cases, and only the timing of the last two thinnings and the final cut differs substantially, when the same diameter is used to define the maturity for the final cut and the length of rotation. Under the current climate, the rotation length is 99  years (Figs.  19.27 and 19.28). Increased precipitation has no effect on the rota-

Table 19.8  Mean change in the diameter growth (% of that under the current climate) summarizing the changes in Scots pine, Norway spruce, and birch in upland forest TS region Period Southern boreal, TS > 1200 d.d. Central boreal, TS 1000–1200 d.d. Northern boreal, TS < 1000 d.d. Across the whole boreal region

RCP2.6, mean growth response change (%) 2040– 2010–2039 2069 0.2 −0.1 (2.8) (8.3) 3.2 8.9 (2.4) (7.2) 8.5 (3.3) 3.5 (4.0)

24.9 (9.7) 10.1 (12.1)

sites under minor (RCP2.6), moderate (RCP4.5), and severe (RCP8.5) climate change scenarios

2070– 2099 −1.6 (8.7) 7.7 (7.5)

RCP4.5, mean growth response change (%) 2040– 2010–2039 2069 0.7 −0.2 (3.7) (13.2) 4.7 13.7 (3.2) (11.4)

24.2 (10.1) 8.9 (12.5)

12.0 (4.5) 5.3 (5.5)

38.6 (15.3) 15.5 (18.9)

2070– 2099 −7.0 (19.9) 12.8 (16.8)

RCP8.5, mean growth response change (%) 2040– 2010–2039 2069 0.5 −13.4 (7.9) (27.4) 7.4 11.1 (6.0) (21.7)

2070– 2099 −52.9 (38.9) −19.1 (34.5)

47.4 (21.3) 15.2 (27.0)

18.2 (6.1) 8.0 (9.1)

50.2 (45.4) −13.1 (53.5)

52.9 (25.0) 13.9 (33.8)

The results are for the calculation periods and the regions representing southern, middle, and boreal regions defined by the current temperature sum (TS). The numbers in parentheses indicate the standard deviation of the percentage change in radial growth (Kellomäki et al. 2018)

Fig. 19.27  Left: Average diameter and height and Right: Average stem wood growth in unmanaged and managed Scots pine in southern boreal conditions (61° N) as a function of current and changing temperature, precipitation,

and atmospheric CO2. For further explanation of simulations, see the text. (Kellomäki et al. 1997a. Permission of Elsevier)

Fig. 19.28  Left: Removal of timber and biomass (total removal, saw logs, pulpwood, and logging residues), and Left: Relative removal of timber and biomass in thinned

Scots pine stands under varying climate compared to current climate in southern boreal conditions (61° N). (Kellomäki et al. 1997a. Permission of Elsevier)

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19  Forest Ecosystem Services and Management Under Climate Change

tion length, but a temperature increase alone shortens the rotation by nine years. The combined increase of temperature and precipitation also reduces the rotation. The elevating CO2 has the most pronounced effect: the CO2 increase alone shortens the rotation by 17 years, and the combined effect of increased CO2, temperature and precipitation further shortens the rotation by 26  years. The mean timber yield per year increases by 10% due to the temperature increase or combined with the increase in precipitation. Similarly, elevating CO2 alone increases the timber yield by 20%. Under a combined increase of all the factors, the timber yield increases by 30% (Kellomäki et al. 1997a).

19.6.9 Risks of Abiotic and Biotic Disturbances and Mortality In general, climate change is likely to increase the mortality of trees in the context of ecosystem dynamics. The likely increase of mortality is related to two main mechanisms: (i) the acceleration of the life cycle of trees, with a reduction of the life span for earlier self-thinning (e.g., Yoda et al. 1963); (ii) and more frequent occurrence of abiotic and biotic disturbances (e.g., Dale et  al. 2001). Both mechanisms are related to climatic change, which affects the occurrence, timing, frequency, duration, extent, and intensity of abiotic disturbances (e.g., fire, drought, strong wind, and high snow load) damaging trees, with consequent biotic damages. Allen et  al. (2010) and Zhao and Running (2010) claimed that some forest ecosystems are currently vulnerable to mortality in response to longer and more severe drought episodes. Parmesan and Yohe (2003) estimated that the distribution ranges of different tree species have moved northwards by 6.1  km per decade. According to Choat et al. (2012), the productivity and survival of 70% of 226 forest species across the globe are likely to decline in the long run. Drought reduces the ability of trees to supply water for photosynthetic gas exchange, the con-

sequent desiccation and mortality. Based on permanent sample plots, Peng et al. (2011) showed that the tree mortality in the Canadian boreal forests increased by 4.7% in the period 1963–2008. The increasing mortality is likely related to rising temperatures and longer drought episodes, as also occurred in northern and eastern Europe (e.g., Mäkinen et  al. 2000, 2001; Vygodskaya et al. 2002; Ge et al. 2014). Global warming is likely to increase the diversity of pests (insects and fungi), which further increases the risk of large-scale disturbance. The mechanisms of sudden large-scale biotic damages are poorly known but the response of host trees species and pests to warming might be nonlinear. In such cases, catastrophes are triggered by high warming with drought exceeding the threshold. This might have occurred in British Columbia, where more than 14 million ha of lodgepole pines (Pinus contorta) have been damaged since the early 1990s. Outbreaks of mountain pine beetle (Dendroctonus ponderosae) and Dothistroma needle blight (Dothistroma septosporum) are further related to warming (Woods et  al. 2010). Thus, the multiple changes in herbivory–host interactions are likely to alter the successional path of trees and ecosystem from that based only on physiological responses to changing climate Even in boreal conditions, drought episodes are currently possible (e.g., Welp et  al. 2007). Under warming, drought episodes will likely become more frequent and longer, which reduces growth, making biotic disturbance and death earlier than those related to the current climate (e.g., Ruosteenoja et al. 2017). Biotic disturbances also become more frequent because of the increasing number of annual generations of insects under a warming climate. The number of extreme weather events, like storms and heavy snowfall, is also expected to increase, with a likely increase in windthrows and snow damages in the boreal forests. Probably, such disturbances will be frequent but local, while the return of major wind, snow and fire catastrophes will be 20–30 years or even shorter under climate change.

19.7 Concluding Remarks

19.6.10

Outline Strategies for Adapting to Climate Change in Ecosystem Context

Managed boreal forests may adapt to the changing climate, but the rate of autonomous adaptation is probably too slow to meet future expectations regarding using forests for different purposes. Globally, the changes in CO2, temperature, and precipitation may make boreal sites suboptimal for some tree species, whereas the conditions for some other species may become more optimal (e.g., Boisvenua and Running 2006; Wertin et al. 2012). From the perspective of 30–40 years (i.e., by 2060 and thereafter), the mean annual temperature elevation will probably exceed the year-to-year variability in the temperature under boreal conditions, with further changes in annual precipitation and its seasonality, with most increase in wintertime. Under climate change, the current management provides many opportunities even beyond 2050, but the risks are increasing in interaction. The future socioeconomic context is unknown, which makes it difficult to identify a proper adaptive forest policy responsive to future conditions. The changes induced by climate change on growth and development imply a need to modify the current management practices in order to adapt the growth and development of forests to climatically different conditions. Based on model simulations, Kellomäki et  al. (2008) used rule-­ based management in formulating management strategies for adapting to climate change. The main task was to maintain the productivity of forest ecosystems, especially the growth of Norway spruce, if the current patterns of timber p­ roduction are preferred. Five optional management strategies were used in the simulations. • Strategy 1: Management with no modifications of the current management rules was used for detecting the impacts of different management strategies on adapting to climate change. • Strategy 2: Management with reduced rotation regardless of tree species. • Strategy 3: Norway spruce was replaced by Scots pine in sites of medium and high fertil-

693

ity if Norway spruce occupied the site prior to the terminal cutting. • Strategy 4: Norway spruce was replaced by birch on sites of medium and high fertility if Norway spruce occupied the site prior to the terminal cutting. • Strategy 5: More southern provenance of Norway spruce, with tolerance of higher temperatures, was used in reforestation in sites of medium and high fertility as outlined in the second case. The simulations showed that the reduction of rotation length (Strategy 2) clearly increases the total growth (up to 28%) due to avoiding the excess reduction of growth in Norway spruce in this century (Table 19.9). At the same time, the growth of Scots pine and birch increases. The increase is largest in the south, where the total growth increases by up to 12% of the total growth for the preference of Scots pine (Strategy 3). The total growth increases most (38%) if birch is preferred in replanting sites previously occupied by Norway spruce (Strategy 4). The use of tolerant provenances of Norway spruce also increases the total growth (31%) in relation to the management outlined by the current rules (Strategy 5). Thus, a proper choice of tree species and provenance seems to maintain the productivity of forest land under climate change. However, even the reduction of rotation length, with more rapid turnover of forest resources, may help to maintain the productivity and make it possible to modify management to meet successfully the climate-induced changes in site conditions (Kellomäki et al. 2008; Innes et al. 2009).

19.7 Concluding Remarks In general, the productivity of managed boreal forests is likely to increase in response to warming, but the risks of abiotic and biotic damage will also increase. The increase in productivity is likely to exceed the losses in damages before 2050, beyond which the risks will likely increase more rapidly than the opportunities (Table 19.10). Opportunities might well be realized only if the increased cutting potential is utilized. Regular

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19  Forest Ecosystem Services and Management Under Climate Change

Table 19.9  Mean annual growth of different tree species over southern and northern Finland for the period 2070– 2099 under climate change (SRES A2 scenario) and

selected management regimes, with the percentage of that under management if no modification in management has been made (Kellomäki et al. 2008)

Growth, m3ha−1year−1 (% of that with no modifications in management) Management regime Scots pine Norway spruce Birch Total Strategy 1: Management with no modifications of current management rules 6.69 3.62 0.26 2.81  South 4.61 0.84 0.58 3.19  North 5.84 2.49 0.39 2.96  Total Strategy 2: Management with reduced rotation 9.02 (+35) 5.36 (+48) 3.42 (+22)  South 0.24 (−8) 5.26 (+14) 1.07 (+27) 3.70 (+16)  North 0.49 (−16) 7.50 (+28) 3.62 (+45) 3.54 (+20)  Total 0.34 (−13) Strategy 3: Preferring Scots pine on Myrtillus site if previously occupied by Norway spruce. Reduced rotation 7.53 (+13) 4.06 (+44)  South 3.29 (−9) 0.17 (−35) 5.08 (+10) 3.99 (+25)  North 0.70 (−17) 0.39 (−33) 6.53 (+12) 4.03 (+36)  Total 2.24 (−10) 0.26 (−33) Strategy 4: Preferring birch on Myrtillus site if previously occupied by Norway spruce. Reduced rotation 10.08 (+51) 6.79 (+88) 3.12 (+11)  South 0.17 (−35) 5.16 (+12) 1.14 (+36) 3.53 (+11)  North 0.49 (−16) 8.08 (+38) 4.49 (+80) 3.29 (+11)  Total 0.30 (−23) Strategy 5: Preferring Norway spruce of more tolerant ecotype. Reduced rotation 9.27 (+39) 5.56 (+54) 0.67(+158) 3.04 (+8)  South 5.27 (+14) 1.23 (+46) 0.44(−24) 3.60 (+13)  North 7.64 (+31) 3.80 (+53) 0.57(+46) 3.27 (+10)  Total Southern Finland refers to the forest land in the latitude range 60–63° N and northern Finland to the range 63–70° N. The calculations are based on the sample plots used in the National Forest Inventory (NFI)

Table 19.10  Likely impacts of climate change on managed boreal forests and forestry in Finland from short- (2010– 2039), medium- (2040–2069), and long-term (2070–2099) perspectives (Peltola et al. 2012) Impact of climate change on forests and possible ways to adapt to climate change Opportunities  Potential forest growth  Potential cutting drain  Potential climate change mitigation Risks  Reduced wood quality  Wind damage  Snow damage  Fire damage  Insect attacks  Fungi attacks  Invasion of alien organisms  Reduced biodiversity  Reduced carrying capacity of soil

2010–2039

2040–2069

2070–2099

↑ ↑ ↑

↑↑ ↑↑ ↑↑↑

↑↑↑ ↑↑ ↑↑

↑ ↑↓ ↑ ↑ ↑ ↑ ↑ ↑ ↑ ↑

↑ ↓↓ ↑↑ ↑↑ ↑↑ ↑↑ ↑↑ ↑↑ ↑↑ ↑↑

↑ ↓↓↓ ↑ ↑↑↑ ↑↑↑ ↑↑↑ ↑↑↑ ↑↑↑ ↑↑↑ ↑↑

The assessment is based mainly on model simulations using the FinAdapt SRES A2 climate scenarios, assuming the atmospheric CO2 rise from 350 to 840 ppm by 2100, with a mean annual temperature rise of 5 °C. Legend for opportunities and risks: small increase/reduce ↑ or ↓, large increase/reduce ↑↑ or ↓↓, very large increase/reduce↑↑↑ or ↓↓↓

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Kellomäki S, Rouvinen I, Peltola H, Strandman H, Steinbrecher R (2001b) Impact of global warming on the tree species composition of boreal forests in Finland and effects on emissions of isoprenoids. Glob Chang Biol 7:531–544 Kellomäki S, Strandman H, Nuutinen T, Peltola H, Korhonen KT, Väisänen H (2005) Adaptation of forest ecosystems, forests, and forestry to climate change. Finnish Environment Institute, FinAdapt Working Paper vol 4, pp 1–50 Kellomäki S, Strandman H, Nuutinen T, Peltola H, Korhonen KT, Väisänen H (2008) Sensitivity of managed boreal forests in Finland to climate change, with implications for adaptive management. Philos Trans R Soc B363:2341–2351 Kellomäki S, Strandman H, Heinonen T, Asikainen A, Venäläinen A, Peltola H (2018) Temporal and spatial change in diameter growth of boreal Scots pine, Norway spruce and birch under recent-generation (CMIP5) global climate model projections for the 21st century. Forests 9(3):118. https://doi.org/10.3390/ f9030118 Kellomäki S, Strandman H, Peltola H (2019) Effects of even-aged and uneven-aged management on carbon dynamics and timber yield in boreal Norway spruce stands: a forest ecosystem model approach. Forestry 2019:1–13. https://doi.org/10.1093/forestry/cpz040 Kilpeläinen A, Strandman H, Kellomäki S, Seppälä J (2014) assessing the net atmospheric impacts of wood production and utilization. Mitig Adapt Strateg Glob Chang 19:955–968 Kilpeläinen A, Strandman H, Grönholm T, Ikonen V-P, Torssonen P, Kellomäki S, Peltola H (2017) Effect of initial age structure of managed Norway spruce Forest area on net climate impact of using forest biomass for energy. Bioenergy Res 10:4999–4508 Kimball BA (1983) Carbon dioxide and agricultural yield: an assemblage and analysis of 430 prior observations. Agron J 75:779–788 Kirilenko AP, Sedjo RA (2007) Climate change impacts on forestry. PNSA 104(50):19697–19702 Kirschbaum MUF (1995) The temperature dependence of soil organic matter decomposition and the effect of global warming on soil organic C storage. Soil Biol Biochem 27(6):753–760 Kirschbaum MUF, Whitehead D, Dean SM, Beets PM, Shephard JD, Ausseil A-G (2011) Implications of albedo changes following afforestation on the benefits of forests as carbon sinks. Biogeosciences 8:3687–3696 Kløve B, Ala-aho P, Bertrand G, Gurdak JJ, Kupfersberger H, Kværner J, Muotka T, Mykrä H, Preda E, Rossi P, Uvo CB, Velasco E, Pulido-Velazques M (2014) Climate change impacts on groundwater and dependent systems. J Hydrol 518:250–266 Kohler M, Sohn J, Nägele G, Bauhus J (2010) Can drought tolerance of Norway spruce (Picea abies (L.) Karst.) be increased through thinning? Eur J For Res 129:1109–1118

Koski V, Tallqvist R (1978) Tuloksia monivuotisista kukinnan ja siemensadon määrän mittauksista metsäpuilla. Summary: Results of long-time measurements of the quality of flowering and seed crop of forest trees. Folia Forestalia 364:1–60 Krebs CJ, Boonstra R, Cowcill K, Kenney AJ (2009) Climatic determinants of berry crops in the boreal forests of the southwestern Yukon. Botany 87:401–408 Kurjak D, Strelcová K, Ditmarová L, Priwitzer T, Kmet J, Homolák M, Pichler V (2012) Physiological response of irrigated and non-irrigated Norway spruce trees as a consequence of drought in field conditions. Eur J For Res 131:1737–1746 Kuusinen N (2014) Boreal forest albedo and its spatial and temporal variation. PhD thesis, University of Helsinki, Helsinki, Finland Kuusinen N, Kolari P, Levula J, Porcar-Castell A, Stenberg P, Berninger F (2012) Seasonal variation in pine forests albedo and effects of canopy snow on forest reflectance. Agric For Meteorol 164:53–60 Kuusinen N, Stenberg P, Tomppo E, Bernier P, Berninger F (2015) Variation in understory and canopy reflectance during stand development in Finnish coniferous forests. Can J For Res 45:1077–1085 Lagergren F, Lindroth A (2002) Transpiration response to soil moisture in pine and spruce trees in Sweden. Agric For Meteorol 112:67–85 Leverenz JW, Lev DJ (1987) Effects of carbon dioxide-­ induced climate changes on the natural ranges of six major commercial tree species in the western United States. In: Shands WE, Hoffman JS (eds)The green-­ house effect, climate change, and U.S. forests. The Conservation Foundation, Washington, DC. 123 p Liang J, Zhou M, Tobin PC, McGuire AD, Reich PB (2015) Biodiversity influences plant productivity through niche-efficiency. PNAS 112(18):5738–5743 Liang J, Crowther TW, Picard N, Wiser S, Zhou M, Alberti G, Schulze ED, McGuire D et  al. (2016) Positive biodiversity-productivity relationship predominant in global primary production. Science 354(6309):aaf8957. https://doi.org/10.1126/science. aaf8957 Locatelli B, Brockhaus M, Buck A, Thompson I, Bahamondez C, Murdock T, Roberts G, Webbe J (2010) Forests and adaptation to climate change: challenges and opportunities. In: Mery G, Katila P, Galloway G, Alfaro RI, Kanninen M, Lobovikov M, Varjo J (eds) Forests and society – responding to global drivers of change. IUFRO world series, vol 25, pp 21–42 Loo J, Fady B, Dawson I, Vinceti B, Baldinelli G (2011) Climate change and forest genetic resources  – state of knowledge, risks, and opportunities. FAO. Commission on genetic resources for food and agriculture. Background Paper No. 56:1–22 + Annex 1 Lutz DA, Howarth RB (2014) Valuing albedo as an ecosystem service: implication for forest management. Clim Chang 124:53–63

References Lutz DA, Burakowski EA, Murphy MB, Borsuk ME, Niemiec RM, Howarth RB (2016) Trade-offs between three forest ecosystem services across the state of New Hampshire, USA: timber, carbon, and albedo. Ecol Appl 26(1):146–161 Mäkinen H, Nöjd P, Mielikäinen K (2000) Climatic signal in annual growth variation in Norway spruce [Picea abies (L.) Karst.] along a transect from central Finland to the Artic timberline. Can J For Res 30:769–777 Mäkinen H, Nöjd P, Mielikäinen K (2001) Climatic signal in annual growth variation in damaged and healthy stands of Norway spruce [Picea abies (L.) Karst.] in southern Finland. Trees 15:177–185 Mannerkoski H, Finér L, Piirainen S, Starr M (2005) Effect of clear-cutting and site preparation on the level and quality of groundwater in some headwater catchments in eastern Finland. For Ecol Manag 220(1–3):107–117 Martz F, Vuosku J, Ovaskainen A, Stark S, Rautio P (2016) The snow must go on: ground ice encasement, snow compaction and absence of snow differently cause soil hypoxia, CO2 accumulation and tree seedling damage in boreal forests. PLoS One 11(6):e0156629. https:// doi.org/10.1371/journal.pone.0156620 Matala J, Hynynen J, Miina J, Ojansuu R, Peltola H, Sievänen R, Väisänen H, Kellomäki S (2003) Comparison of a physiological model and a statistical model for prediction of growth and yield in boreal forests. Ecol Model 161:95–116 Mattson WJ, Kuokkanen K, Niemelä P, Julkunen-Tiitto R, Kellomäki S, Tahvanainen J (2004) Elevated CO2 alters birch resistance to Lagomorpha herbivores. Glob Chang Biol 10:1402–1413 Meentemeyer V (1978) Macroclimate and lignin control of litter decomposition rates. Ecology 59:465–472 Melillo JM, Aber JD, Muratore JF (1982) Nitrogen and lignin control of hardwood leaf litter decomposition dynamics. Ecology 63:621–626 Monserud RA, Tchebakova NM, Leemans R (1993) Global vegetation change predicted by modified Budyko model. Clim Chang 25:59–83 Natural Resources Institute Finland (2018). https://www. luke.fi/en/natural-­r esources/agriculture/reindeer-­ husbandry/reindeer-­and-­climate-­change/. Visited 28 Nov 2018 Naudts K, Cheng Y, McGrath MJ, Ryder R, Valade A, Otto J, Luyssaert S (2016) Europe’s forest management did not mitigate climatic warming. Science 351(6273):597–599 Niemelä P, Veteli T (2006) Ilmastonmuutoksen vaikutukset metsätuhoihin ja -tauteihin boreaalisessa vyöhykkeessä. In: Riikonen J, Vapaavuori E (eds) Ilmasto muuttuu  – mukautuvatko metsät. Metsäntutkimuslaitoksen tiedonantoja, vol 944, pp 92–98 Noss RF (2001) Beyond Kyota: forest management in a time of rapid climate change. Conserv Biol 15(3):578–590

699 Nygrén M (1990) Seed production response to climate. Blecsco Workshop. Helsinki. December 12–14, 1990. Handout. 3 p Nykänen H, Alm J, Silvola J, Tolonen K, Martikainen P (1998) Methane fluxes on boreal peatlands of different fertility and the effect of long-term experimental lowering of the ground water table on flux rates. Glob Biogeochem Cycles 12(1):53–69 O’Neil GA, Hamann A, Wang T (2008) Accounting for population variation improves estimates of the impact of climate change on species’ growth and distribution. J Appl Ecol 45:1040–1049 Olsson R (2011) To manage or project?  – boreal forests from a climate perspective. Air Pollut Clim Ser 26:1–67 Paradis L, Thiffault E, Achim A (2019) Comparison of carbon balance and climate change mitigation ­potential of forest management strategies in boreal forest of Quebec (Canada). Forestry 92(3):264–277 Park A, Puettmann K, Wilson E, Messier C, Kames S, Dhar A (2014) Can boreal and temperate forest management be adapted to the uncertainties of 21st century climate change? Crit Rev Plant Sci 33(4):251–285 Parmesan C, Yohe G (2003) A globally coherent fingerprint of climate change impacts across natural systems. Nature 421(2):37–42 Peltola H, Vapaavuori E, Niemelä P, Kellomäki S, Gregow H, Huitu O, Kallio M, Kilpeläinen A, Müller M, Neuvonen S, Salemaa M, Siitonen J, Venäläinen A (2012) Ilmastonmuutokseen sopeutuminen metsätaloudessa. Report to ISTO, pp.  38–46. Maaja metsätalousministeriön julkaisuja  – Publikationer av Jord- och skogsbruksministeriet  – Publications of Ministry of Agriculture and Forestry Peng C, Ma Z, Lei X, Zhu Q, Chen H, Wang W, Liu S, Li W, Fang X, Zhou X (2011) A drought-induced pervasive increase in tree mortality across Canada’s boreal forests. Nat Clim Chang 1:467–471 Pregitzer KS, King JS, Burton AJ, Brown SE (2000) Responses of tree fine roots to temperature. New Phytol 147:105–115 Pudas E, Tolvanen A, Poikolainen J, Sukuvaara T, Kubin E (2008) Timing of plant phenophases in Finnish Lapland in 1997–2006. Boreal Environ Res 13:31–43 Pukkala T (1987) Kuusen ja männyn siemensadon ennustemalli. Summary: a model for predicting the seed crop of Picea abies and Pinus sylvestris. Silva Fennica 21:135–144 Pukkala T (2017) Does management improve the carbon balance of forestry? Forestry 90(1):125–135 Qi J, Marshall JD, Mattson KG (2004) High soil carbon dioxide concentrations inhibit root respiration of Douglas fir. New Phytol 128:435–442 Raich JW, Schlesinger WH (1992) The global carbon dioxide flux in soil respiration and its relationship to vegetation and climate. Tellus 44B:81–99 Räisänen T, Ryyppö A, Kellomäki S (2008) Impacts of timber felling on the ambient monoterpene concen-

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tration of A Scots pine (Pinus sylvestris L.) forests. Atmos Environ 42:6759–6766 Reich PB, Oleksyn J (2008) Climate warming will reduce growth and survival of Scots pine except in the far north. Ecol Lett 11:588–597 Reich PB, Walters MB, Tjoelker MG, van Der Klein D, Buschena C (1998) Photosynthesis and respiration rates depend on leaf and root morphology and nitrogen concentration in nine boreal species differing in relative growth rate. Funct Ecol 12:395–405 Ruosteenoja K, Jylhä K, Tuomenvirta H (2005) Climate scenarios for FINADAPT studies of climate change adaptation. Finnish Environment Institute, FinAdapt Working Paper 15, pp 1–15 Ruosteenoja K, Markkanen T, Venäläinen A, Räisänen P, Peltola H (2017) Seasonal soil moisture and drought occurrence in Europe in CMIP5 projections for the 21st century. Clim Dyn 2017:1–16. 10.1007/ s00382-017-3671-4 Rusanen K, Finér L, Antikainen M, Korkka-Niemi K, Backman B, Britschgi R (2004) The effect of forest cutting on the quality of groundwater in large aquifers in Finland. Boreal Environ Res 9:253–261 Rustad LE, Campbell JL, Marion GM, Norby RJ, Mitchell MJ, Hartley AE, Cornelissen JHC, Gurevitch J (2001) A meta-analysis of the response of soil respiration, net nitrogen mineralization, and aboveground plant growth to experimental ecosystem warming. Oecologia 126:543–562 Sathre R, O’Connor J (2010) Meta-analysis of greenhouse gas displacement factors of wood product substitution. Environ Sci Pol 13:104–114 Saxe H, Cannell MRG, Johnsen O, Ryan MG, Vourlitis G (2001) Tree and forest functioning in response to global warming. New Phytol 149:369–400 Schwaiger HP, Bird DN (2010) Integration of albedo effects caused by land use change into the climate balance: should we still account in greenhouse units? For Ecol Manag 260:278–286 Sjølie HK, Latta GS, Solberg B (2013) Potential impact of albedo incorporation in boreal forest sector climate change policy effectiveness. Clim Pol 13(6):665–679 Sohn JA, Hartig F, Kohler M, Huss J, Bauhus J (2016) Heavy and frequent thinning promotes drought adaptation in Pinus sylvestris forests. Ecol Appl 26(7):2190–2205 Spracklen DV, Carslaw KS, Kulmala M, Kerminen V-M, Sihto L-S, Riipinen I, Merikanto J, Mann GW, Chipperfield MP, Wiedensohler A, Birmili W (2008) Contribution of particle formation to global cloud condensation nuclei concentrations. Geophys Res Lett 35:1–5 Stendahl J, Johansson M-B, Eriksson E, Nilsson Å, Landvall O (2010) Soil organic carbon in Swedish spruce and pine forests–differences in stock levels and regional patterns. Silva Fennica 44(1):5–21 Strandman H, Väisänen H, Kellomäki S (1993) A procedure for generating synthetic weather records in conjunction of climatic scenario for modelling ecological

impacts of changing climate in boreal conditions. Ecol Model 70:195–220 Talkkari A, Hypén H (1996) Development and assessment of a gap-type model to predict the effects of climate change on forests based on spatial forest data. For Ecol Manag 83:217–228 Tolvanen A (1997) Recovery of the bilberry (Vaccinium myrtillus L.) from artificial spring and summer frost. Plant Ecol 130:35–39 Torssonen P, Strandman H, Kellomäki S, Kilpeläinen A, Jylhä K, Asikainen A, Peltola H (2015) Do we need to adapt the choice of main boreal tree species in forest regeneration under the projected climate change? Forestry 88:564–572 Torssonen P, Kilpeläinen A, Strandman H, Kellomäki S, Jylhä K, Asikainen A, Peltola H (2016) Effects of climate change and management on net climate impacts of production and utilization of energy biomass in Norway spruce with stable age-class distribution. Glob Change Biol Bioenergy 82:419–427 Urvas L, Erviö R (1974) Metsätyypin määrittäminen maalajin ja maaperän kemiallisten ominaisuuksien perusteella. Influence of the soil type and the chemical properties of soil on the determining of the site type. Maataloustieteellinen Aikakauskirja 46:307–319 Veijalainen N, Jakkila J, Nurmi T, Vehviläinen B, Marttunen M, Aaltonen J (2012) Suomen vesivarat ja ilmastonmuutos – vaikutukset ja muutoksiin sopeutuminen. Suomen Ympäristö 16:1–138 Vygodskaya NN, Schulze E-D, Tchebakova NM, Karpachevskii LO, Kozlov D, Sidorov KN, Panfyorov MI, Abrazko MA, Shaposhnimkov ES (2002) Climatic control of stand thinning in unmanaged spruce forests in the southern taiga in European Russia. Tellus 54B:443–461 Welp LR, Randerson JT, Liu HP (2007) The sensitivity of carbon fluxes to spring warming and summer drought depends on plant functional type in boreal forest ecosystems. Agric For Meteorol 147:172–185 Wertin TM, McGuire MA, van Israeli M, Rutter JM, Teskey OR (2012) Effects of elevated temperature and [CO2] on photosynthesis, leaf respiration, and biomass accumulation of Pinus taeda seedlings at a cool and a warm site within the species’ current range. Can J For Res 42:943–957 Woods AJ, Heppner D, Kope HH, Burleigh J, Maclauchlan L (2010) Forest health and climate change: a British Columbia perspective. For Chron 864:412–422 Yoda K, Kira K, Ogawa H, Hozumi K (1963) Intraspecific competition among higher plants. XI. Self-thinning on overcrowded pure stands under cultivated and natural condition. Osaka City University. J Biol D14:107–129 Zhao M, Running RW (2010) Drought induced reduction in global terrestrial net primary production from 2000 through 2009. Science 329:940–943 Zubizarreta-Gerendiain A, Pukkala T, Peltola H (2016) Effects of wood harvesting and utilization policies on the carbon balance of forestry under changing climate: a Finnish case study. Forest Policy Econ 62:168–176

Adaptive Management – Outlines of Theories and Practices

20

Contents 20.1 Needs of Adaptive Management and Practices  20.1.1  Outline of Assessing Needs for Adaptive Management  20.1.2  Outline Strategies and Activities in Adaptive Management  20.1.3  Outline of Planning of Management in Relation to Climate Change 

 701  701  703  704

20.2 Concluding Remarks 

 705

References 

 705

Abstract

Forest ecosystems may adapt autonomously to climate change, but the importance of forests for societies makes it important to influence the direction and timing of the adaptation processes and measures. However, the necessary actions are highly speculative and susceptible to uncertainties in the future climate and necessary management for avoiding adverse effects of climatic change. The future socioeconomic context is also unknown, with the need for a future forest policy to be responsive to a wide variety of economic, social, political, and environmental circumstances. Flexible approaches are needed that promote reversible and incremental steps, and that favor ongoing learning and the capacity to modify direction of management as situations change under warming.

Keywords

Vulnerability · Sensitivity · Adaptive capacity · Exposure · Resilience · Adaptive management

20.1 Needs of Adaptive Management and Practices 20.1.1 Outline of Assessing Needs for Adaptive Management In general, adaptive management is a strategy enabling the structure and functioning of a forest ecosystem to resist harmful impacts of climate change, and to utilize the opportunities created by climate change (Table  20.1). Forest ecosystems may adapt autonomously to climate change, but the importance of forests for societies makes it

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 S. Kellomäki, Management of Boreal Forests, https://doi.org/10.1007/978-3-030-88024-8_20

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Table 20.1  Assessing the need for adaptive management, with a focus on boreal forests (Kellomäki and Leinonen 2005) Factors affecting the need for adaptive management Climate change and climate variability  Higher temperatures and precipitation, with shorter duration of snow cover and soil frost, increasing risk of local thunderstorms with high wind, increasing risk of heavy snowfall with wet snow, wet soil with low carrying capacity Impacts and climate sensitivities  Enhanced regeneration and growth, increasing dominance of deciduous species thereby reducing fire risk, increasing risk of wind and snow damage, increased risk of insects and pathogens, enhanced input of carbon into soil, enhanced decomposition of soil organic matter Capacity to adapt autonomously  Mainly native tree species are used with much genetic variability to acclimatize forests to rising temperatures and high variability in temperature. Enhancing seed production and the success of natural seeding even in commercial forests, where two-thirds of regeneration is natural (seed tree and shelterwood methods)  Productivity of forests will increase, with higher turnover of carbon in forest ecosystems. However, the low supply of nitrogen may limit the enhancement of growth, which is highest in the northern parts of boreal forests  Currently, local tree species are well adapted to local insects and pathogens, with low frequency of major outbreaks. The risk of invasion of alien species and the invasion of local species further north may increase the risk of major outbreaks of damaging insects and pathogens. This may increase the risk of wind and snow damage, with a possible increase in susceptibility to biotic damage Vulnerability  Increasing competition capacity of deciduous species may alter species composition, especially in southern boreal forests  Timber line may move northwards and to higher altitudes, with a disappearance of current timber line forests  Rising growth rates may reduce timber quality (branchiness, wood density, fiber length)  Likely increase of abiotic and biotic damage may result in major losses in the quantity and quality of timber, with more unscheduled cuttings and management  Reducing soil frost along with higher precipitation may reduce the carrying capacity of soils, with problems in the harvest and transportation Need for planned adaptation  Control of tree species composition to meet future needs and expectations  Choice of even-aged or uneven-aged management whenever appropriate  Modifications of thinning practices (timing, intensity) and rotation length to meet the increasing growth and turnover of carbon, to maintain high quality of timber and resistance to abiotic and biotic damage  Maintenance of infrastructure for forestry and non-timber forest production

important to influence the direction and timing of the adaptation processes and measures. In planned adaptation, actions are needed to meet the future conditions in a proper way (Spittlehouse  and Stewardt 2003). Until now, the necessary actions are highly speculative and susceptible to uncertainties in the future climate. The future socioeconomic context is also unknown, with the need for a future forest policy to be responsive to a wide variety of economic, social, political, and environmental circumstances. Adaptive management is a process where management needs and management practises meet in proper ways the warming-induced changes in the ecosystem dynamics in a given

time perspective (Table  20.1). Bussotti et  al. (2015) emphasize the following properties of a forest ecosystem and forestry in increasing/ reducing the capacity of forests to adapt to climate change: (i) persistence of current forests related to the phenotypic plasticity and acclimatization to the local conditions; (ii) changes in genotypic properties, with large within-­ population diversity of given species and gene flow between populations; (iii) migration and substitution of species; and (iv) extinction of species with low plasticity as at the edges of their distribution or growing in isolation. In this context, (v) species with a larger geographical distribution are likely to represent large genotypic and

20.1  Needs of Adaptive Management and Practices

phenotypic variability, making these species capable of adapting to changing environments like warming-induced droughts. This is possible even in boreal conditions at high latitudes.

20.1.2 Outline Strategies and Activities in Adaptive Management Under climate change, the future forest environment deviates from the current one but the changes are uncertain. Therefore, Millar et  al. (2007) emphasize “flexible approaches that promote reversible and incremental steps, and that favour ongoing learning and the capacity to modify direction as situations change” under warming. Consequently, proper adaptive management

703

includes options: (i) to reduce the impact and enhance protect of forests (resistance); (ii) to improve the capacity of ecosystems to recover from disturbances (resilience); and (iii) to facilitate the transition of ecosystems from the current to new conditions (response). In the strategic perspective, adaptive management represents a set of management operations, which may be used alone (management measure) or combined (management regime) for directing the dynamics of forest succession under climate change to produce different services targeted in management (Table  20.2). Management may concern basic functioning and structures of the ecosystem, with a consequent imbalance between different goods and services aimed in forestry. Therefore, the damages should be considered in relation to the management targets, i.e., (i) what

Table 20.2  Outline ways to adapt forestry in boreal forests (Kellomäki and Leinonen 2005) Management priorities Management planning

Gene management

Forest protection

Silvicultural management

Technology and infrastructure

Perspective before 2050 Include climate variables in growth models for specific predictions on development of forests Include monitoring and risk management in management rules in forest plans

Make choices on preferred tree species composition for future Identify suitable genotypes Breeding programs to increase resistance of trees to biotic damage Revise rules for importing fresh timber, to reduce the risk of introducing alien species Breeding for reducing biotic hazards Conservation of biodiversity for controlling forest health Revise management rules to consider effects of climate variability on regeneration, growth, and mortality Prefer natural regeneration wherever appropriate Revise management rules for reducing climatic hazards and warming Develop technology to use altered wood quality and tree species composition Develop infrastructure for biomass and timber harvest and transportation, and for non-timber use of forests Procedures to fight climatic hazards

Perspective after 2050 Plan forest landscape to resist high winds and fire spreading Plan forest landscape to minimize spread of insects and diseases Plan forest landscape for mitigating risks of excess water flow and flooding Plant alternative genotypes or new species Modify seed transfer zones and management of genetic resources Breeding for meeting climate change Revise management rules to increase resistance of forest to abiotic and biotic damage Breeding for reducing biotic hazards Conservation of biodiversity for controlling forest health Develop soil management to reduce influence of ground cover on success of regeneration Modify management rules to meet enhanced growth and turnover of carbon Change rotation length and thinning rules to meet increased turnover of carbon and enhanced growth Develop technology to use altered wood quality and tree species composition Develop infrastructure for biomass and timber harvest, transportation, and non-timber use of forests Technology and procedures to fight climate hazards and disturbances

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the tangible and intangible services aimed at in the management are, and (ii) how sensitive the different services are to climate change or climate variability (Spittlehouse and Stewardt 2003). In this context, the adaptive strategy and the necessary measures and operations may be divided into several implementing task areas with necessary research and development, including: (i) management planning, (ii) genotype management, (iii) silvicultural management, (iv) forest protection, and (v) technology and infrastructure.

20.1.3 Outline of Planning of Management in Relation to Climate Change In forestry, adaptive management operates on the scale of forest landscape rather than on the scale of single patches/stands, which are used in implementing operative measures (Fig.  20.1). Forest landscape and patches provide the framework for assessing the abiotic and biotic impacts of climate change on ecosystem structure and functioning, and further on the vulnerability of forest Fig. 20.1  Outlines of factors affecting the formulation of adaptive management in the context of forest ecosystem (Kellomäki and Leinonen 2005)

and the forest ecosystem to climate change. The degree of vulnerability is related to the agreed aims in forest production not disturbed by climate change. The discrepancy between the expected and likely realizing production should lead to the policy actions, with the modification of management objectives and management policy for avoiding detrimental effects of climate change. Optimization of management including the choice of adaptive actions are needed for proper management to resist climate change-­ induced changes in ecosystem dynamics. In boreal conditions, several existing tree species, either native or exotic, probably grow faster with a more rapid life cycle and enhancement of turnover of tree populations (Table  20.2). This requires shorter rotations and regular thinning in order to avoid biotic damages associated with diminishing tree growth in rapidly maturing trees. From the adaptive point of view, the preference for natural regeneration provides a huge genetic potential to adapt forest to climate change. Even in forest plantations natural seedlings affect substantially the total success of reforestation. Natural deciduous regrowth in coniferous plantations may require more pre-­

References

commercial cuttings in favor of coniferous species. The preference for different species may require intensification of regeneration practices in terms of careful choice of tree provenance and tree species with more optimal response to climatic warming and likely increase of drought episodes (Table  20.2). Tree improvement with breeding programs may be launched in order to increase the genetic potentials of trees to adapt to climate change with variable changes in site properties. However, effective results and the availability of suitable regeneration of seeds and seedlings require a minimum of about 25 years, with longer periods for adequate testing. In the period later after 2050s, more frequent and intensive thinning may be needed for reducing the risks of biotic damages. Regular thinning will also increase the mechanical strength of trees due to the enhanced growth.

20.2 Concluding Remarks International environmental and forest policy emphasizes the increasing role of forests in responding to the need to reduce the net carbon dioxide emissions into the atmosphere and conserve biodiversity as outlined in the Rio Convention and the Kyoto Protocol. From the European perspective, the close links between the environmental and forest policies are clearly outlined in the Resolutions of the European Forestry Ministries’ Conferences agreed in 1993, with a clear focus on making forests capable of adapting to climate change and producing in a sustainable way biomass, timber, and other goods and services to sequestrate carbon and conserve biodiversity. Sustainable forest production and carbon sequestration need to be balanced with conservation of biodiversity and other goals of forestry needed to meet future demands.

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The Kyoto Protocol drew attention to forest management strategies from two perspectives, with implications for adaptive management. First, there is an increasing interest in developing improved forest management strategies that enhance carbon sequestration in forests (link to Article 3.4 of the Kyoto Protocol). Second, there is a concern that some management techniques may result in a net release of carbon from the forest ecosystem, for example, if soil carbon storage is reduced due to cultivation techniques. In short, the problem faced in the management of carbon resources in forest ecosystems is how to maintain and enhance the capacity to sequester and store atmospheric carbon. Any major changes in the area of forest cover, tree species composition, and age structure will have implications for conservation policy, challenging the strategies on how to conserve rare and endangered species under adverse environmental conditions. Sustainable functioning of forest ecosystems is also important for protecting human settlements and infrastructure from avalanches, rockfalls, and torrents. Consequently, adaptive management is needed to ensure the multitude of forest functions and to minimize risks and subsequently costs.

References Bussotti F, Plastron M, Holland V, Brüggemann W (2015) Functional traits and adaptive capacity of European forests to climate change. Environ Exp Bot 111:91–113 Kellomäki S, Leinonen S (2005) Management of European forests under changing climatic conditions, Research notes 163. University of Joensuu. Faculty of Forestry, pp 1–427 Millar CI, Stephenson NL, Stephens SL (2007) Climate change and forests of the future: managing in the face of uncertainty. Ecol Appl 17:2145–2151 Spittlehouse DL, Stewart RB (2003) Adaptation to climate change in forest management. BC J Ecosyst Manag 4(1):1–11

Units and Conversions

In studies of forest ecology and forest management, the units used vary even in the same publication. This is especially the case in papers dating back to the time before standards are provided by the SI-system. The tables below therefore list a selection of frequently used dimensions in plant physiology and ecology with application in producing biomass and energy based on forest biomass. They are used in this book and can also be used to convert earlier units of measurement into the SI-system, which was not used in older publications.

Prefixes and Units Prefix in SI-system T G M k h d c m μ n p

Explanation teragigamegakilohectodecicentimillimicronanopico-

Value 1012 109 106 103 102 10−1 10−2 10−3 10−6 10−9 10−12

Unit Transformations cal 1 cal = 4.1868 J kcal 1 kcal = 1.163 W · h

Pressure Unit Transformations MPa 1 MPa = 106 Pa = 10 bar bar 1 bar = 105 N · m−2 = 105 Pa = 100 J · kg−1 = 106 erg · cm−3 bar 1 bar = 750 Torr = 0.9869 atm atm 1 atm = 1.0132 bar = 760 Torr

Amount and Concentration Unit Molarity ppm ppb ppm

Transformations mol · kg−1 of liquid 1 ppm = 10−6 mol · mol−1; 1 μg · g−1; 1 μl · l−1 1 ppb = 10−9 mol · mol−1; 1 ng · g−1; 1 nl · l−1 1 ppm CO2 = 1.82 mg · m−3 = 41.6 μmol · m−3 = 0.101 Pa (at the temperature of 20 °C and pressure 101.3 kPa)

Radiation and Energy Energy Unit Transformations J 1 J = 1 N·m = 1 kg ·m2 ·s−2 = 1 W·s = 0.239 cal = 107 erg W·h 1 W·h = 3.6 kW · s = 3.6 kJ = 0.86 kcal MJ 1 MJ = 0.278 kWh

Transformations 1 W · m−2 = 1 J · m−2 s−1 = 31.53 MJ · m−2 · a−1 1 mol photon = 1.8 · 105 J (when λ 650 nm) … 2.7 · 105 J (when λ 450 nm) 1 cal · cm−2 · min−1 = 6.98 · 102 W · m−2 = 6.98 · 105 erg · cm−2 · s−1 1 erg · cm−2 · s−1 = 1.43 · 10−6 cal · cm−2 · min−1 = 10−3 W · m−2

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 S. Kellomäki, Management of Boreal Forests, https://doi.org/10.1007/978-3-030-88024-8

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Units and Conversions

708

Gas Exchange Transformations 1 g CO2 (exchange) ≈ 0.73 g O2 (exchange) 1 g O2 (exchange) ≈ 1.38 g CO2 (exchange) Diffusion DCO2 = 0.64 DH2O Diffusion DH2O = 1.56 DCO2 0.03 %vol CO2 = 300 μ · l−1 = 282 μbar = 28 Pa CO2 (partial pressure) 1 μl · l−1 = 1.963 μg CO2 · l−1 (at a pressure of 1013 mbar and temperature 0 °C) 1 mg CO2 · dm−2 · h−1 = 0.028 mg CO2 · m−2 · s−1 = 0.63 μmol CO2 · m−2 s−1 1 mg CO2 · m−2 · s−1 = 36 mg CO2 · dm−2 · h−1 = 22.7 μmol CO2 · m−2 · s−1 1 μmol CO2 · m−2 · s−1 = 0.044 mg CO2 · m−2 · s−1 = 1.58 mg CO2 · dm−2 · h−1 1 mg H2O · dm−2 · h−1 = 1.54 μmol H2O · m−2 · s−1 Conductance (at temperature of 20 °C and pressure 101.3 kPa) 1 cm · s−1 ≈ 0.416 mol · m−2 · s−1 1 mol · m−2 · s−1 ≈ 0.024 mm · s−1

Biomass Transformations 1 g DM · m−2 = 10−2 Mg · ha−1 1 g DM ≈ 0.42 − 0.51 g C ≈ 1.5 – 1.7 g CO2 1 g C ≈ 2 – 2.22 g DM ≈ 3.1 – 3.4 g CO2 1 g CO2 ≈ 0.59 – 0.66 g DM ≈ 0.27 – 0.30 g C 1 g CO2 = 3.67 g [=44/12] C Biomass = Volume [m3] × Density of mass [kg m−3] Carbon content in stem wood [kg C m−3]: Scots pine 0.3091, Norway spruce 0.3715, birch 0.4152

DM = Dry Mass

Index

A Aaltonen, V.T., 392 Acceleration phase, 115, 692 Accumulation of organic matter, 263, 268 Active period, 70, 150, 180, 189–192 Adaptation to climate change, 347, 645, 646, 665, 681 Adaptive capacities, 336, 348, 644, 645, 649 Adaptive management, 695, 701–705 Alien insects and fungi, 635–637, 639 Allocation of growth, 185–187, 399 Allogenetic disturbance, 284 Allogenic successions, 222, 223, 243, 329 Allometry, 103–107, 398 Andersson, B., 385, 386 Angiosperms, 68, 89, 91, 93, 100, 117, 178 Annual cycle, 70, 112, 153, 180, 189 Annual growth, 86, 87, 89, 102, 169, 181, 182, 248, 256, 257, 260, 272, 338, 399, 413, 414, 426, 453, 454, 533, 534, 690 Arctic and high-altitude forest boundaries, 549–552 Aspens, 68, 72, 80, 81, 112, 113, 128, 135, 191, 202, 237, 293, 351, 427, 533, 537, 558, 631, 635 Assessing needs for adaptive management, 701–703 A taproot, 66–67 Atmospheric carbon dioxide, 14, 27, 29, 30, 52, 145, 514 Autochthonous subpopulation, 195 Autogenetic disturbances, 284 Autogenic succession, 221–223 Autotrophic respiration, 142, 143, 205, 206, 252, 253, 523, 565 Autumn dormancy, 191, 192 Autumn transition, 189 Avoiding forest damages, 637–638 Axillary bud, 67 B Bark, 15, 69, 70, 73, 75, 76, 80, 86, 87, 92–93, 105, 163, 173, 174, 196, 199, 258–262, 265, 267, 270, 271, 387, 457–458, 475, 489, 622, 623, 630, 631, 633–636, 639

Bark beetles, 163, 387, 630, 631, 633, 634, 639 Bedrock, 14, 37–41, 298, 485, 486, 533, 547 Betula pendula, 71, 72, 77, 89, 176, 193, 341, 342, 430, 433, 533, 659 Betula pubescent, 433 Between-tree shading, 158, 398, 402–403, 405, 406, 421 Biodiversity, 4–6, 14, 486, 500–503, 509, 514–522, 533, 593, 602, 646–649, 694, 703, 705 Biogeochemical nutrient flow, 269–272 Biosphere, 4, 28, 508, 667 Black alder, 71–72, 79, 100, 114 Boreal forests, 2, 3, 8, 22, 37, 38, 43, 46, 47, 49, 52, 54, 57, 71–74, 81, 82, 116, 134, 143, 183, 195, 197, 204, 206, 221, 224, 225, 230, 234, 236–238, 243, 245, 247, 248, 253, 257, 269, 270, 286, 308, 313, 320, 323, 325, 329, 334, 335, 340, 347, 362, 364, 432, 433, 438, 439, 459, 486, 491, 500, 504, 511, 512, 516, 517, 519, 525–527, 531–533, 535, 544, 549, 550, 566, 573, 574, 584, 604, 613, 615, 621, 622, 625, 631, 633, 636, 637, 639, 644, 648–650, 653–657, 659, 660, 663, 667, 669, 673, 674, 680, 682, 687, 689, 692–695, 702, 703 Branches, 31, 66–68, 70, 73, 75, 77, 79, 80, 86, 87, 92–96, 98, 101–103, 105–107, 113, 135, 141, 142, 158, 159, 163, 166, 173, 174, 176, 180–181, 183–185, 187, 196, 199, 203, 205, 206, 229, 241, 242, 244, 247, 260–262, 265, 267, 270, 271, 343, 345, 357, 358, 378, 381, 382, 385, 386, 394, 399, 400, 402–405, 420–427, 444, 457–459, 465–475, 487, 489, 498, 523, 525, 552, 563, 569, 587, 608, 614, 617, 622, 670, 672, 674 Bud burst, 80, 160, 161, 174–176, 192–194, 196, 200, 628, 629, 660, 661 Bunches of cellulose molecules, 179 C Cambium, 66–67, 69, 70, 76, 86, 87, 90, 92, 93, 100, 173, 174, 176–179, 181, 377, 457, 475, 550

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 S. Kellomäki, Management of Boreal Forests, https://doi.org/10.1007/978-3-030-88024-8

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710 Canopies, 2, 15, 27, 30–36, 41, 42, 44, 54, 95, 132, 146, 155–158, 169, 200, 202, 203, 205, 221–225, 228–231, 233–235, 237, 238, 240–243, 250, 251, 257, 259–261, 268, 272, 273, 275, 280, 283–285, 292–295, 313, 316, 318–321, 332–334, 357, 372, 373, 376, 381, 382, 384, 397–403, 405, 407, 411, 415, 416, 426, 438, 445, 447, 448, 474, 493, 514, 516, 517, 530, 531, 536, 539, 546, 548, 553, 557–559, 561, 572–574, 576, 587, 606, 612, 625, 669, 673–675, 677, 685 Canopy layers, 30, 35, 230, 320, 382, 397, 398, 410, 411, 413, 420, 561, 587 Canopy photosynthesis, 155, 156, 202, 203, 685 Carbon accumulation in soil, 667 Carbon dioxide (CO2), 14, 15, 20, 28–30, 48, 49, 51, 52, 141–205 Carbon uptake, 145, 149, 150, 152, 203–205, 225, 457, 494, 495, 523, 565, 567, 570, 666, 667, 669, 670, 672 Casparian, 172 Cellulose molecules, 90, 179 Cell wall, 43, 68, 86, 88–92, 118, 165, 172, 176, 179, 181–183, 259, 345 Chemical properties, 14, 38, 183, 297, 298, 457, 519, 659, 662 Chilling, 191, 193 Chilling unit, 191, 193 Chronosequences, 199, 243, 246, 248 Clark, S.G., 226 Cleaning, 7, 8, 286, 293, 372, 373, 382, 383, 385–387, 487, 500, 524, 543, 558, 593, 683 Climate changes, 14–60, 135, 146, 152, 155, 160, 165, 169, 183, 187, 203, 206, 306, 342, 347, 348, 483, 498, 499, 526, 565, 583, 616–618, 626–628, 633, 635, 643–695, 701–705 Climax, 74, 76, 128, 135, 224, 226, 247, 250–253, 273, 316, 337, 351, 535, 546 Climax tree species, 76 Coarse roots, 68, 73, 86, 92, 93, 98, 103, 142, 158, 166, 173, 174, 183, 187, 196, 199, 203, 205, 261, 263, 265, 267, 271, 498, 523, 528, 670 Combining several services, 499–502 Competition, 7, 140, 201, 208, 225, 237, 240, 247, 259, 283, 304, 312, 336, 357, 361, 372–374, 377, 379–383, 392, 394–397, 429, 432, 480, 481, 540, 648, 683, 702 Composition of ground vegetation, 334 Controlling air impurities, 549, 557–559 Controlling climatic conditions, 552–556 Controlling excess water flow, 556–557 Coniferous trees, 86, 115, 118, 128, 135, 169, 174, 176, 202, 407, 550, 556, 631, 638, 667 Cortex, 66–67, 69, 70, 93, 97, 99–101, 172 Cotyledons, 70, 74, 76, 115, 118, 120, 129, 130 Crossbreeding, 115, 120 Crown classes, 397, 398 Crowns, 6, 16, 27, 30, 31, 33, 36, 59, 66, 73, 75–77, 79, 80, 86, 88, 93, 95, 98, 99, 101–103, 105–108, 113, 120, 123, 125, 156–158, 168, 176, 183, 199, 223, 225, 228, 230, 240–243, 261, 262, 308, 336,

Index 357, 372, 377, 379, 380, 382, 386, 394, 397–407, 410, 411, 416, 420, 422, 423, 425–427, 431, 438, 439, 444, 445, 447, 448, 458, 459, 466–475, 514, 530, 535, 546, 553, 558, 561, 563, 573, 587, 604, 606, 607, 609, 614, 615, 617–619, 622–624 Crown structure, 31, 77, 79, 93, 102, 241, 401, 405, 472–475 Cultural services, 4, 8, 220, 508, 509, 511, 512, 515, 531, 533, 583–585, 592, 593, 646, 647, 675 Cycle interval, 191 Cycle of nitrogen, 203, 438–439 Cycle rate, 191 D Damages, 6–8, 15, 27, 59, 76, 129, 192, 194, 200, 208, 222, 223, 292, 294, 295, 301, 317, 319, 333, 336, 338, 347, 355, 360, 361, 377, 378, 385, 386, 410, 411, 431, 459–461, 475, 485, 486, 516, 539, 550, 557, 558, 602–639, 644, 645, 647, 655, 661, 666, 675, 679, 692–695, 702–705 Death, 70, 102, 115, 184, 196, 199, 202, 206, 221, 223, 225, 229, 243, 244, 246, 251, 253, 261–264, 273, 312, 381, 382, 398, 405, 422, 424, 467–469, 473, 517–519, 557, 619, 630, 692 Decays, 14, 15, 28, 29, 37, 38, 43, 86, 102, 131, 150, 203, 205, 228, 235, 244, 252, 262–264, 266–270, 273, 292, 295, 298, 333, 372, 407, 409, 424, 439, 460, 461, 485, 490, 508, 514, 517–521, 525, 526, 529, 531, 544, 565, 566, 569, 570, 650, 654, 661, 668, 670, 672 Deciduous trees, 68, 71, 72, 86, 89, 94, 115, 116, 118, 120, 123, 135, 168, 169, 173, 174, 176, 196, 198–200, 202, 235, 259, 292–295, 320, 378, 386, 387, 427–433, 438, 516, 521, 531, 535, 537–539, 544, 561, 585, 588, 604, 631, 638, 648, 667, 673, 677, 695 Densities, 6, 14, 30, 31, 33–36, 41, 47, 74, 79, 81, 100, 113, 118, 123–127, 133–135, 143–146, 149, 154, 155, 157, 166, 181–184, 199–202, 205, 208, 209, 228, 233, 241, 242, 246, 247, 253, 254, 257, 258, 260–266, 268–271, 274, 280, 282, 295, 297, 307–309, 314–319, 321, 322, 324, 325, 332, 339, 345, 351, 357–363, 365–367, 373, 375, 377–384, 387, 391–396, 399–405, 407, 409–412, 414–417, 420–424, 426, 428, 432, 438, 452, 453, 457, 468, 471, 473, 474, 489, 491, 492, 519, 520, 524, 541, 543, 550–553, 557, 558, 561–564, 566, 567, 574, 586, 587, 607, 610, 630, 631, 635, 651, 657, 659, 665, 674, 675, 679, 685, 689, 708 Diameter growth, 90, 102, 105–107, 174, 176, 181, 184, 187, 188, 202, 244, 319, 416, 419, 423, 448, 449, 456–458, 468, 469, 471, 472, 520, 686–688, 690, 691 Differentiation, 66, 89, 121, 135, 141, 179, 195, 223, 225, 242, 246, 274, 338, 339, 377, 382, 395–399, 416, 420, 504, 514, 517, 593, 645 Diffusion of carbon dioxide, 143–146 Dispersal of seeds, 126, 304, 319

Index Distribution of growth, 106, 187, 270, 470 Disturbance dynamics, 517, 518 Ditching, 286, 292, 300–301, 485, 498, 530, 540, 541, 556, 557 Diversity of habitats, 484 Dormancy I, 190–192 Dormancy II, 190–192 Dormancy unit, 191 Dormant period, 189–192 Droughts, 40, 41, 54, 56, 57, 90, 120–122, 145, 152, 184, 244, 542, 544, 546, 602, 623, 625, 632, 633, 635–637, 647, 650, 655, 657, 658, 662, 665, 668, 677, 680, 683, 685, 686, 689, 692, 703, 705 E Ecosystem, 15, 49, 54 Ecosystem dynamics, 5, 6, 203–205, 221, 273, 283, 292, 297, 481, 488, 509–511, 515, 533, 644–647, 665, 675, 692, 702, 704 Ecosystem energetics, 252, 273, 515, 521 Ecosystem goods and services, 203 Ecosystem services, 3–6, 286, 427, 499–502, 504, 507–593, 602–604, 643–695 Ecosystem services under climate change, 647 Edaphic factors, 5, 14, 47, 144, 156, 202, 205, 329, 372, 550 Edible berries, 539–543, 655, 659–661 Edible mushrooms, 533, 543, 545 Effect of pruning on stem growth, 470–472 Effects on photosynthesis, 443 Elintoimintojen ja ympäristön vuorovaikutus, 140 Embryos, 112, 115, 117, 118, 120, 129, 132, 309 Emerging of seedlings, 305, 306, 309–310 Endodermis, 66–67, 97, 100, 101, 167, 172 Endosperm, 115, 117, 120 Epicotyl, 120, 130 Epidermis, 66–69, 93, 96, 97, 99–101, 166, 167, 169, 172 Epigeal germination, 130 Equilibrium, 29 Even-aged management, 6–8, 47, 205, 207, 257, 280–286, 315, 320, 345, 367, 372, 375, 391, 410–412, 414, 427, 432–434, 483, 486–488, 491, 494–497, 499, 503, 504, 521, 522, 524, 534, 535, 539, 567, 575–581, 583, 584, 670, 672, 677 Exposure, 88, 95, 220, 229, 612, 644, 645 F Factors affecting heal-over, 469 Family in breeding, 343–348 Fagerström, 446 Female gametophytes, 117, 118 Fertilizations, 8, 70, 90, 91, 112, 115, 117, 118, 120, 128, 205, 206, 283, 292, 308, 309, 350, 398, 399, 437–461, 480, 485, 487–493, 498, 524, 540, 543, 610–612, 666, 672, 673 Fine roots, 40, 68, 86, 98, 101, 103, 105, 141, 142, 158, 166, 171, 173, 181, 183, 184, 187, 188, 196, 198,

711 199, 203, 205, 206, 259, 261–263, 265, 267, 354, 440, 523, 525, 530, 531, 669 Flowering, 66–67, 70, 76, 78, 112–125, 135, 192, 304, 307–309, 539, 541–543, 551, 636, 660, 661 Forcing unit, 193 Forest ecosystems, 3–8, 15, 49, 143, 203, 204, 206, 226, 242, 243, 248, 254, 261, 263, 271–273, 275, 283, 286, 296, 304, 438–443, 460, 481, 482, 484–486, 491–494, 497, 503, 504, 507–593, 602–639, 643–695, 701–705 Forest sites, 14, 41, 44, 298, 316, 525, 544, 585, 653, 690, 691 Formation of seeds, 112, 114, 121, 133, 135, 238, 304, 305 Fotosynteesin valoreaktiot, 146 Frost damages, 192–195, 292, 295, 320, 333, 347, 357, 461, 628 Frost hardiness, 193, 628, 629 Frost resistance, 194, 195, 602, 628, 629 Fujimori, T., 470, 473, 474 Functioning, 3–8, 15, 28, 49, 86, 105, 107, 178, 189–196, 202–203, 206, 220, 222, 223, 225, 226, 236, 245, 250, 254, 272–275, 283, 286, 304, 443–447, 480–482, 484, 485, 488, 491, 504, 508–511, 513–515, 522, 524, 528, 531, 533, 544, 554, 558, 559, 566, 573, 589, 593, 602, 603, 644–646, 649, 655, 662, 665, 666, 677, 701, 703–705 Functions, 4, 5, 14, 18, 19, 31–33, 35, 36, 40, 43, 44, 47, 54, 68, 74, 76, 78, 80, 81, 89, 91, 104, 106, 107, 116, 117, 124–126, 133, 134, 142, 144–147, 150, 158, 160, 161, 163, 164, 168, 174–177, 179–182, 186, 190, 191, 194, 196, 197, 199, 201, 220, 224, 228–231, 233, 241, 242, 244, 250, 253, 255, 257, 258, 260, 264, 267, 268, 293, 306, 307, 309–314, 318–322, 324, 329, 331, 333, 335–337, 340, 341, 343, 354, 355, 359–363, 366, 367, 376–380, 382–385, 391–394, 396, 398, 400–405, 408, 412, 414, 416, 421–427, 429, 431–433, 441–446, 448–451, 458–460, 466, 468–470, 472, 474, 484, 485, 488, 494, 495, 498, 503, 504, 509, 512, 519–521, 526, 532, 533, 537, 539, 541, 542, 548–553, 555, 558, 559, 562–564, 567, 570, 575, 584, 586, 588, 590, 592, 606, 609–611, 618, 619, 621–625, 631, 636, 644, 653, 657, 659–662, 667, 668, 679–681, 685, 688, 691 G Gap, 144, 148, 149, 171, 221, 223–225, 228–238, 240, 242–248, 250, 251, 272, 275, 280, 285, 320, 321, 329–333, 517, 609, 610 Gap dynamics, 223, 228–237, 240, 242, 248, 250, 251 Genetic resources, 533, 548, 665, 666, 703 Genotype transfer, 346–347 Geographical distribution, 46, 71, 72, 74, 75, 79, 80, 195, 244, 658, 702

Index

712 Germination, 70, 115, 117, 118, 125, 128–135, 237–240, 304–306, 309–311, 313, 316, 318, 320, 350, 353, 354, 390, 551, 677, 695 Global forests, 1, 2 Goods, 3–8, 49, 203, 220, 226, 282, 285, 286, 322, 323, 337, 358, 363–365, 382, 383, 433, 479–504, 508, 509, 533, 535, 585, 593, 602, 646, 647, 665, 703, 705 Greis, I., 318, 319 Grey alders, 71, 79, 80, 100, 114, 128, 135, 202, 295, 427, 537, 538 Gross primary production (GPP), 206, 237, 252, 253, 273, 481, 523, 565, 572, 684 Growing space, 238, 242, 379–382, 391, 392, 394, 411, 422, 455, 658 Growth, 14–16, 22, 28, 30, 31, 37, 39, 40, 43, 47, 51, 54, 59, 60 Growth and mortality of branches, 420–422, 468–469 Growth cessation, 192, 193, 198, 341, 448, 461, 474, 628 Growth of root, 183–185 Growth respirations, 142, 143, 158–161, 163, 206, 253 Growth response to fertilization, 447–451 Gymnosperms, 66, 68, 86, 89–91, 93, 97, 100, 102, 117, 163, 178 H Habitat diversity, 274, 275, 518 Hänninen, 322–324 Happa, 80–81 Hardened period, 192 Hardening, 192 Health, 4, 8, 325, 360, 377–378, 450, 484, 485, 509, 510, 533, 549, 553, 583, 585, 588, 593, 658, 675, 695, 703 Heal-over branch stump, 468–470 Heartwood, 74, 77, 86, 87, 169, 199, 260, 262, 263, 265, 457, 474 Height distributions, 134, 208, 321, 377 Height growth, 66, 77, 79, 94, 102, 107, 134, 174–176, 184, 187, 196, 208, 241, 242, 293, 312, 313, 317–320, 336, 338, 341, 354, 355, 365, 376–377, 385, 387, 416–417, 428, 466–467, 471, 472, 497, 680, 681 Helms, J.A., 399 Herbivore mammals, 629–631 Heterotrophic respiration, 206, 207, 252, 273, 461, 524, 525, 565–567, 670 Heterotrophic species, 508 Humus, 14, 37–39, 43, 46, 47, 98, 99, 130, 132, 203, 205, 206, 237, 239, 244, 248, 252, 266–270, 273, 292, 296–301, 306, 310, 314, 332–334, 361, 372, 407, 409, 460, 491, 492, 494, 495, 514, 517, 525, 526, 529, 531, 544, 545, 565, 575, 622, 623, 625, 650, 653, 686 Hydrological cycles, 273, 514, 525, 547, 573, 593 Hypocotyl, 115, 120, 129, 130 Hypogeal germination, 120, 130

I Ikäheimo, E., 386 Ilmasto lämpö, 22 tuuli, 26–27 Ingrowth, 256, 320, 428, 493, 524, 576, 578 Initial growth, 70, 115, 237, 316, 350, 357, 377, 381, 398 Inner bark, 174 Intensity of thinning, 405, 412, 414, 427, 434, 489 Interception, 3, 30, 33, 35, 203, 205, 234, 300, 400, 405, 406, 515, 522, 548, 573, 628, 662 Interception of precipitation, 35 Interception of radiation, 30, 32, 33, 522 Inventory of reforestation, 359–360 K Karlsson, L., 295 Kasvu kasvun jakautuminen, 105–107 Kasvumekanismit ja sukkessio, 238 Kasvun käsite, 140 Kasvupaikka maan lämpötila, 42 maassa oleva vesi, 38–42 mikroilmasto, 30, 31 ravinteet, 42 tuuli, 35–36 Kauppila, A., 300 Kellomäki, S., 133, 318, 319, 394, 402, 403 Kinnunen, K., 322 Koski, V., 308 Kovakuoriaiset, 522 L Lähde, E., 300 Lamella, 88, 92, 179 Lämpö, 22 Landscapes, 6, 220, 222, 223, 228, 237, 273–275, 280, 483, 499–503, 510, 511, 514–518, 539, 573, 583–589, 593, 605, 608, 612–613, 625, 647, 649, 667, 677, 703, 704 Landscape values, 220, 583–588, 675 Lappi-Seppälä, M., 428 Latent heat, 26, 42, 166, 237, 573 Lateral bud, 67 Lateral roots, 66–67, 98–100 Leaf primordium, 66–67 Lehto, 322, 323 Leikola, M., 294, 295, 300, 317 Life cycle, 70, 117, 189, 195, 221, 223, 227, 239, 265, 275, 350, 387, 391, 415, 448, 461, 519, 524, 571, 630, 632, 661, 672, 677, 692, 704 Lifespan, 70, 79, 81, 90, 95, 98, 102, 103, 107, 112, 113, 123, 158, 196–202, 208, 239–241, 243, 246, 247, 377, 405, 429, 450, 451, 461, 474 Light absorption, 399–402 Lignification, 192

Index Lignin, 66, 68, 90, 162, 163, 179, 183, 184, 266, 267, 519, 520, 525, 526 Linnimäki, J., 322 Litter, 14, 37–39, 43, 46, 130, 132, 150, 169, 196–200, 203, 205, 206, 223, 231, 234, 235, 237, 244, 252, 253, 261–273, 292, 296–301, 306, 310, 314, 332–334, 372, 407, 409, 439, 440, 444, 460, 461, 489–492, 494, 495, 514, 517, 525, 526, 529, 531, 544, 545, 562, 565–570, 572, 575, 619, 622, 623, 625, 650, 653, 654, 667, 668, 686 Lohm, U., 446 M Maintenance respiration, 142, 158–162, 206, 460 Mäki-Kojola, S., 322 Mälkönen, E., 319 Management, 14, 15, 47, 49, 59 Management in directing forest succession, 480–482 Management needs, 6, 282, 292, 383, 702 Management operations, 6–8, 286, 383, 384, 483, 485–489, 493–494, 516, 535, 575, 587, 677, 703 Management regimes, 6–8, 206, 280, 285, 314, 485, 488, 494, 500–503, 574, 576, 578–583, 647, 667, 694, 703 Management strategies, 6, 7, 283, 285, 479–504, 512, 575–578, 580, 583, 646, 647, 693 Mänty, 72–74 Massan dynamiikka ja kertyminen puustoon, 252, 257 Mean annual growth, 256, 257, 341, 489, 494, 534, 580, 690, 694 Mechanical soil preparation, 298–300 Megaspores, 115, 117, 118 Meristemaattinen kasvu ja erilaistuminen, 68–70 Meristematic growth, 68–70 Metabolic activity, 70, 189 Metabolic cycle, 189, 192 Microfibrils, 90, 92, 179 Microspore mother cells, 117 Mielikäinen, K., 428, 429, 431–433 Mineralization, 43, 234, 235, 268–270, 333, 447, 461, 526, 668, 689 Mitigating climate warming, 571, 666 Mixture of Norway spruce and birch, 429–433 Mixture of Scots pine and birch, 685 Modelling, 40, 49, 142, 148–150, 200, 202–208, 243, 246, 251, 307, 309, 405 Model performance, 207 Mortality, 7, 15, 31, 95, 106, 133, 134, 150, 181, 183, 184, 196–202, 205, 206, 208, 220, 221, 225, 226, 239, 243, 244, 246, 250, 252–255, 257, 260, 263, 272, 275, 295, 304–306, 313, 336, 338, 340, 348, 349, 351, 355, 357, 361, 367, 378, 384, 386, 391, 398, 399, 412, 420–423, 425, 444, 458, 459, 461, 468, 488, 494, 498, 518, 524, 534, 550, 551, 563, 568, 576, 578, 602, 623, 657, 658, 668, 680, 692, 703 Multifunctional forestry, vi, 502–504 Mycorrhizae, 99–101, 169, 171, 183, 184, 523, 544

713 N Natural pruning vs artificial pruning, 466–468 Natural regeneration, 6–8, 133, 135, 205, 206, 208, 284, 286, 292, 304–307, 309, 315, 316, 320, 322, 323, 325, 329, 365–367, 375–378, 383, 390, 428, 483, 485–487, 489, 493, 500, 518, 578, 588, 665, 677–680, 695, 703, 704 Natural seedlings in canopy gaps, 320–321 Natural thinning, 200 Needle cohort, 184, 197–198 Needs of adaptive management, 701–705 Nerg, J., 322 Net biome production (NBP), 252, 524, 566, 567 Net ecosystem exchange (NEE), 207, 237, 238, 524, 565, 566, 570, 577, 578, 672 Net ecosystem production (NEP), 523, 524, 565–567 Net growth, 254–256, 271, 272, 399 Net primary production (NPP), 183, 207, 252, 253, 441, 445, 481, 523, 524, 565, 566, 572, 652 Niches, 225–227, 519 Nitrogen content of foliage, 438, 441–443 Nitrogen uptake, 169, 439–441, 490, 492, 669 Nodes, 66–67, 173, 174 Nodules, 79, 100 Noise abatement, 549, 559–561, 563, 564, 666 Non-woody litter, 196 Norokorpi, Y., 386 Norway spruces, 40, 47, 59, 69–81, 86, 88, 90, 91, 94, 98, 99, 107, 108, 112–114, 118, 120–124, 126–129, 131, 135, 149, 150, 155, 174, 184, 191, 192, 196–199, 202, 206–208, 223, 225, 236, 238–250, 252, 253, 255, 258, 264, 266, 273, 275, 280, 292, 294, 295, 304, 307–310, 312–314, 316–320, 322–325, 338, 340, 345–348, 351, 353, 356, 358, 360–367, 372, 373, 375–378, 383–387, 391, 392, 396, 409, 415–420, 427–433, 440–442, 446–452, 454–457, 460, 461, 475, 493, 494, 497, 499, 500, 519, 524, 525, 530, 533, 535, 538, 545, 546, 550, 558, 559, 562–564, 569, 575, 580, 583, 585, 586, 611–613, 615, 617, 618, 622, 623, 628, 631, 633, 636–639, 648, 651, 652, 655–658, 662, 663, 665, 667, 668, 670, 672–677, 680–691, 693–695, 708 Nursery practices, 328, 350, 353, 354, 364 Nutrient cycles, 204, 225, 227, 235, 251, 252, 259, 263, 265, 270–273, 351, 438–440, 461, 485, 514, 517, 519, 525–529, 544, 645, 647, 653, 654 Nutrients, 14, 43, 46 Nutrient uptake, 101, 169–172, 269, 272, 438, 544 O Odum, E.P., 226 Oker-Blom, P., 31–33, 402, 403 Ontogenetic cycle, 191, 192, 194 Ontogenetic development, 193 Ontogenetic events, 193 Openings, 66–67, 97, 118, 143, 145, 221, 223, 224, 228–233, 235, 237, 275, 280, 283, 285, 296, 299, 315, 493

714 Optimizing management, 498 Organs, 66, 68, 86, 97, 103–107, 117, 141, 142, 157–159, 161–163, 166, 167, 171, 173, 178, 180, 181, 184–186, 188, 189, 194, 196, 205, 206, 244, 253, 259–263, 270, 271, 398, 399, 415, 438, 461, 500, 525, 602, 669 Origins, 38, 68, 163, 192, 195, 196, 338–347, 349, 350, 457, 635 Outer bark, 76, 80, 93 P Palisade parenchyma, 66–67 Patches, 6, 14, 135, 220, 223, 230, 232, 234–237, 243, 246, 273–275, 280, 282, 283, 285, 296, 300, 306, 323, 332, 334, 354, 357, 378, 385, 483, 485, 486, 489, 493, 502, 515–517, 521, 522, 546, 553, 602, 614, 677, 704 Pectin, 43, 179 Pendula birch, 71, 77–78, 80, 113, 114, 124, 128, 192–194, 202, 351, 375, 391, 431–433, 475 Pericycle, 66–67, 101, 172 Phenology, 142, 192–195, 206, 339, 461, 574, 645, 659–661, 666 Phloem, 66–67, 69, 70, 86, 87, 90, 92, 93, 100, 101, 143, 171–174, 176–179, 259, 377, 457, 475, 535, 550, 631, 636 Photoperiod, 90, 176, 194, 338, 340, 341, 347, 349 Photosynthates, 66, 70, 87, 92, 142, 143, 148, 162–165, 171–173, 176–178, 181–185, 200, 205, 399, 467, 508, 669 Photosynthesis, 3, 16, 30, 37, 43, 66, 71, 89, 140–160, 163, 165, 174, 175, 180, 185, 192, 202, 203, 205, 206, 239, 253, 347, 398, 399, 402, 404, 405, 409, 439–445, 448, 514, 524, 525, 550, 551, 558, 559, 570, 628, 650, 652, 661, 669, 684–686 Photosynthetic reactions, 146–148 Picea abies, 71, 72, 75, 89, 94, 128, 176, 202, 241, 248, 337, 533, 558, 652 Pine weevil, 378, 630–633, 636 Pinus sylvestris, 71, 89, 176, 202, 337, 444, 533, 558, 652 Pioneer tree species, 78, 135, 224, 225, 247, 250–252, 315, 318, 334, 337, 351 Pith, 66–67, 69, 87, 90, 101–103, 105, 174, 179, 416, 426, 467, 474 Planning and implementation of reforestation, 351–354 Planning of management in relation to climate change, 704–705 Plasmodesmata, 172 Pohtilan ja Pohjolan (1985), 353 Pohtila, E., 300 Pollen grains, 115, 117, 118, 125, 309 Pollen mother cell, 117 Pollen sacs, 117 Pollen tube, 117, 118 Pollination, 76, 112, 114, 115, 118, 120, 125, 309, 344, 345, 541, 551 Polyembryonism, 115 Pölytys, hedelmöitys ja siementen muodostuminen, 115

Index Populations, 4–7, 51, 72, 106, 113, 120, 121, 123, 140, 191, 200–205, 208, 220–226, 228, 240, 241, 243, 246, 255, 257, 263, 265, 272, 273, 275, 283, 285, 286, 300, 304, 315, 338, 339, 343–345, 347, 348, 361, 372–374, 378, 379, 382, 383, 391, 394, 395, 398–400, 405, 406, 410, 412, 413, 422, 425, 428, 475, 481, 508, 514, 515, 537, 546, 549, 589, 590, 602, 603, 630, 631, 633–636, 638, 639, 645, 646, 648, 659, 666, 677, 684, 702, 704 Position of trees, 243, 422, 449–450, 466 Potential impacts, 503, 644, 645 Practice of pruning, 472–475 Precautionary principles, 6, 203 Precipitation, 3, 14, 15, 22, 24, 26, 30, 34, 35, 38, 40, 49, 51–54, 56, 58, 59, 113, 115, 116, 128, 130, 155, 203, 206, 230, 239, 244, 269, 304, 316, 317, 332, 347, 372, 409, 451, 525, 529–531, 544, 546, 548–552, 556, 575, 602, 619–623, 626, 628, 631, 635, 636, 639, 645, 647, 650–652, 654, 655, 658, 659, 661–664, 668, 670, 671, 674, 675, 677, 679, 680, 682, 683, 688–693, 702 Pre-commercial thinning, 257, 259, 285–286, 373, 382, 385, 387, 395, 458, 647 Preparatory management, 292, 351 Prescribing burning, 296 Primary forests, 649 Primary growth, 68, 70, 87, 93, 163, 173, 174, 176, 187, 399, 494, 499, 565, 649 Primary productions, 3, 14, 28, 163, 164, 220, 273, 286, 304, 508, 509, 514, 515, 522, 524, 525, 529, 646–652, 669, 673, 674 Primary wall, 179 Primary xylem, 87, 93 Priority provisioning services, 532–533 Priority regulating services, 548–549 Priority supporting services, 514 Procambium, 87, 93 Properties of roots, 98–101 Properties of seedling stands, 304, 360, 375, 379 Properties of seeds, 129, 306, 309, 328 Properties of timber, 345, 420–427 Provenance choice for regrowth, 337–343 Provenances, 5, 8, 75, 81, 141, 195, 196, 328, 337–349, 524, 533, 548, 628, 645, 647, 677, 681, 682, 693, 695, 705 Pruning in management, 466–468 Pubescent birches, 71, 77–79, 81, 113, 122–124, 128, 135, 175, 191, 194–196, 202, 310, 316, 367, 375, 385, 431–433 Puiden sukkessiobiologiset ominaisuudet kasvumekanismit, 238 uudistumismekanismit, 238 Pukkala, T., 308 Puulajit haapa, 80–81 kataja, 71 kuusi, 74–77 mänty, 72–74 marjakuusi, 71 rauduskoivu, 77–79 tervaleppä, 79–80

Index Q Quality of seedlings, 349, 350 Quiescent, 192 R Radiation, 14–16, 19, 20, 22, 30, 32, 33, 36, 57 Radiation balance, 19, 20, 206, 332 Radicles, 66–67, 70, 115, 118, 120, 129 Räsänen, P.K., 364, 376–378 Rate of forcing, 193 Raulo, J., 319, 384 Rikala, R., 384 Ravinteet liikkumattomat ravinteet, 259 RCP scenarios, 52, 57, 655, 687, 689, 690 Recreation, 4, 8, 485, 508, 510, 512, 533, 536, 553, 585–593, 647, 648, 695 Reed, K.L., 226 Regeneration, 14, 15, 28, 54 Regeneration using strip cutting, 319–320 Regenerative cycle, 113 Region of provenance, 349, 665 Reindeer husbandry, 535, 536, 648, 655, 658, 659 Reindeer lichen for decoration, 655 Relative growth, 104, 164, 256, 257, 320, 338, 339, 415, 416, 418, 419, 431, 432, 447, 448, 450 Replanting, 7, 286, 292, 349, 363, 383, 387, 487, 575, 693 Respirations, 28, 71, 142–143, 147–149, 151, 153, 156, 158–165, 180, 185, 205, 206, 227, 239, 273, 347, 399, 444, 461, 523, 524, 550, 570, 652, 667–669 Response to climate change, 667, 675 Rest, 22, 23, 29, 30, 38, 125, 172, 190, 192, 193, 196, 231, 357, 529, 546, 567 Rest break, 193 Rest completion, 192, 193 Rikala, R., 294, 295 Risk of biotic disturbances, 629–637 Risk of damages related to frost, 628–629 Risk of fire disturbances, 619–628 Risk of snow disturbances, 59, 617–620 Risk of wind-induced damages, 633, 638 Root apex, 66–67, 141, 169, 171, 184 Root cap, 66–67, 99 Root graft, 100–101 Root hair, 66–67, 99, 169, 171 Root rot, 301, 317, 461, 630–632, 635, 639 Roots, 27, 39, 40 Rule-based management, 487–493, 693 S Sapwood, 74, 77, 86, 87, 90, 103, 162, 163, 169, 259, 260, 263, 399, 550 Sarvaksen (1950), 322, 323 Sarvas, R., 319, 322 Scots pines, 31–37, 40, 41, 43, 44, 47, 59, 69–77, 79–81, 86, 88, 93–96, 98–100, 102, 103, 105, 107, 108,

715 112–116, 118–124, 126–129, 131, 134, 144–146, 149–155, 157–160, 162, 163, 165, 168, 174–176, 180–188, 192, 193, 195–199, 202, 206–209, 223, 238–240, 243–247, 249, 253–255, 258–265, 267–273, 275, 293, 300, 304, 307–310, 312–320, 322–325, 334, 338–341, 345–347, 349, 351, 353, 355–366, 372, 373, 375–379, 381–386, 391–394, 397, 398, 400–410, 415–430, 432, 438, 440–444, 446–448, 450–452, 454–461, 466, 468, 470–475, 488–492, 498, 500, 518–520, 525, 528, 530, 531, 533, 537, 538, 541, 542, 546, 549–552, 558, 559, 562–564, 569, 572, 575, 585, 606, 610, 611, 613, 615, 617, 618, 622–625, 628, 629, 631, 634, 636, 638, 639, 648–652, 655–658, 667–670, 673–675, 677, 679–683, 685–691, 693–695, 708 Seasonality, 82, 150, 153, 154, 614, 664, 693 Secondary compounds, 163–165, 461, 630 Secondary growth, 66–69, 87, 93, 100, 173, 176, 177, 179, 183, 187 Secondary walls, 68, 179 Seed, 7, 67, 112, 173, 223, 284, 292, 304, 328, 376, 414, 457, 486, 533, 630, 665, 702 Seedbeds, 70, 132, 223, 235, 237, 240, 275, 283, 295, 296, 304, 306, 310, 313, 316, 319, 320, 350, 353, 357, 361, 378, 390, 427, 677 Seed coat, 118, 120, 129, 131, 132 Seed crops, 70, 74, 76, 112, 113, 115, 118, 121–125, 133, 134, 238, 239, 241, 253, 304–311, 313, 316, 320, 325, 367, 494, 496, 551, 552, 636, 666, 677 Seed dormancy, 129, 131, 132, 677 Seedling, 7, 70, 115, 154, 221, 280, 292, 304, 328, 372, 393, 474, 486, 513, 615, 647, 704 Seedling types, 350, 351, 384 Seed sources, 125, 126, 328, 338, 339, 342–344, 349, 358 Seed structure, 67, 115–121 Seed tree methods, 284, 315, 317–320, 588 Selection in breeding, 344–345 Self-thinning, 200–202, 206, 208, 271, 395, 396, 398, 399, 411, 412, 414, 689, 692 Sensible heat, 26, 166, 237 Sensitivities, 145, 153, 181, 319, 450, 480, 488, 644, 645, 651, 669, 680, 682, 702 Services, 3–8, 14, 49, 203, 220, 221, 226, 232, 282, 285, 286, 337, 358, 382, 383, 433, 479–504, 507–593, 602–639, 646, 647, 655–658, 660, 665–667, 675, 683, 695, 701–705 Sexual regeneration, 80, 135, 238 Shade tolerance, 223, 320 Shelterwood methods, 284, 292, 315–318, 320, 414, 702 Shoots, 31, 66–69, 73–76, 78, 87, 90, 93–95, 97, 100–102, 113, 115, 129, 141, 173–176, 180, 181, 189, 190, 199, 241, 242, 263, 268, 293–295, 324, 337–339, 400–403, 405–407, 438, 439, 444, 445, 535, 537, 541–543, 630, 631, 634, 635, 659 Siemensadon suuruus, 124 Siementyminen, 125 Silvertown, 374 Site, 14–60

716 Site fertility, 6, 14, 43, 46, 47, 59, 74, 79, 98, 106, 113, 120, 124, 133, 149, 156, 180, 186, 187, 197, 200, 208, 243, 245, 253, 255, 258, 260, 261, 263, 268, 282, 292, 298, 300, 314, 320, 323, 325, 337, 351–353, 357–361, 363–366, 375–378, 381, 385, 387, 391, 393, 398, 399, 414, 420–422, 424, 427, 432, 433, 438, 439, 443, 447, 451, 453, 455, 457–460, 466, 487, 524, 525, 534, 536, 566, 631, 653, 668, 680, 686 Site indexes, 47, 48, 398, 452, 453 Site types, 41–47, 60, 74, 76–78, 80, 116, 124, 155, 186, 187, 199, 208, 209, 239, 244, 245, 248–250, 252–255, 257, 258, 260–266, 268–271, 310, 311, 314, 322, 323, 334, 337, 358, 360, 361, 363, 365–367, 375–377, 382, 383, 392–394, 409, 415, 418, 420–425, 427, 428, 432, 433, 438, 440–442, 444, 449, 455, 457, 459, 460, 473, 474, 486, 488, 494, 518, 524, 525, 531, 535, 541, 542, 544–546, 551, 562, 566, 575, 617, 623, 650, 651, 653, 654, 657, 662, 667, 668, 679, 680, 682–684, 686–688 Skogsstyrelsen 1975, 387 Snow covers, 23, 24, 42, 49, 58, 59, 79, 206, 311, 332, 353, 529, 536, 537, 588, 614, 631, 647, 650, 655, 659, 660, 702 Social development, 533, 585, 588–593 Soil, 14, 15, 26, 30, 34, 35, 37–43, 46, 47, 54, 57–59 Soil formation, 38, 39, 514, 525, 531 Soil frost, 42, 49, 57–59, 132, 154, 332, 357, 361, 409, 614, 615, 617, 619, 631, 638, 702 Soil heat flux, 237 Soil management, 7, 8, 283, 285, 286, 292, 295, 296, 298–301, 310, 314, 316, 317, 319, 322, 323, 329, 334, 335, 337, 351–354, 357, 360–367, 379, 380, 383, 384, 387, 427, 480, 481, 485, 487, 531, 539, 541, 543, 545, 556, 557, 566, 632, 703 Soil organic matter (SOM), 14, 15, 29, 38, 43, 46, 184, 203, 206, 228, 234, 236, 237, 244, 245, 264, 268, 270, 273, 292, 297, 439, 460, 494, 525, 526, 528, 531, 565, 566, 569, 570, 575, 632, 653, 661, 662, 668, 684, 702 Soil temperature, 42, 90, 150, 154–156, 205, 206, 228–231, 233–235, 268, 292, 296, 297, 299, 300, 316, 332, 408, 551, 614, 615, 631, 639, 668 Spacing, 6–8, 31, 59, 73, 75, 88, 95, 107, 108, 113, 121, 127, 199, 201, 205, 238, 242, 259, 262, 263, 282–284, 286, 292, 296, 315–317, 325, 350, 354, 357, 358, 378, 379, 381–383, 385, 387, 389–434, 439, 443, 447, 453, 466–468, 471, 474, 480, 481, 487, 524, 535, 536, 541–544, 558, 563, 575, 580, 585, 588, 604, 606, 609, 610, 658, 683 Spacing and differentiation, 395–400 Spatial distributions, 21, 49, 113, 121, 125, 156, 236, 307, 321, 323, 325, 375, 378, 379, 400, 402, 403, 613, 615, 674, 675, 690 Sperm nucleus, 117 Spiritual significance, 585 Spongy mesophyll, 66–67 Spring transition, 189 SRES scenarios, 49

Index Staminate cones, 117, 118 Stele, 66–67, 172 Stem, 14, 27, 31, 32, 41, 43, 44, 59, 66–70, 72–82, 86–88, 90–95, 97–99, 101–108, 120, 129, 135, 141, 142, 158–160, 163, 166–169, 173–183, 185, 187–190, 196, 197, 199, 200, 203, 205, 206, 208, 209, 237, 239, 241, 242, 244, 246–248, 253, 255–257, 260, 261, 263, 265, 267, 268, 270, 271, 280, 281, 304, 324, 340–343, 345–347, 356, 357, 377–382, 385–387, 391, 392, 394, 396, 397, 399, 400, 402–405, 416–420, 423–426, 428, 429, 431, 432, 446, 457–460, 466–475, 487–489, 492–498, 518–521, 523–525, 528, 533, 534, 552, 562, 563, 571, 577, 580, 581, 587, 602–604, 606–610, 617, 618, 622, 631, 655, 657, 672, 674, 684–686, 689, 691, 708 Stocking, 7, 41, 72, 81, 82, 121, 199, 200, 205, 208, 227, 243, 246–248, 253–257, 263, 270, 271, 309, 311–316, 318, 374, 384, 386, 391, 393, 395, 398, 399, 409, 411–416, 419, 427, 429–432, 434, 455, 486, 487, 491, 492, 494, 496, 497, 499, 518, 521, 522, 524, 525, 533, 535, 538, 541, 544, 551, 563, 573, 574, 585, 586, 591, 592, 615, 617, 652, 656–658, 666, 667, 684, 685, 689 Stomata, 15, 43, 66–67, 96, 97, 143, 144, 146, 166, 167, 205, 558 Storing of seeds, 125 Strategies and activities in adaptive management, 703–704 Structures, 3–8, 14–16, 30, 31, 38, 39, 41, 43, 44, 49, 66–69, 77, 79, 82, 85–108, 113, 117, 118, 120, 123, 125, 133, 134, 140, 141, 156, 157, 168, 171, 173, 176, 177, 181–183, 198, 200, 202–206, 220–223, 225–227, 235, 236, 238, 241, 243, 245, 250, 254, 257–259, 263, 267, 268, 272–275, 280, 282, 283, 285, 286, 295, 297, 304, 308, 315, 379, 380, 395, 399–402, 405, 406, 410, 414, 433, 438, 439, 443–447, 466, 468, 470, 472–475, 480–485, 487, 488, 491, 493, 503, 504, 508–517, 519, 521, 522, 524, 528, 531–534, 537, 538, 543, 544, 548, 549, 554, 556, 558, 559, 561, 566, 573–576, 583–589, 592, 593, 602, 603, 608, 615, 625, 644–646, 648, 649, 655, 662, 665, 666, 677, 701, 703–705 Successions, 3, 5–8, 128, 135, 203, 205, 220–227, 230, 237, 240, 242, 243, 246, 247, 249–251, 253, 255, 258, 260, 261, 263, 264, 268, 272, 273, 275, 283, 286, 292, 295, 296, 304, 328, 334, 395, 397, 398, 426, 428, 434, 480–487, 493, 503, 508, 511, 514, 517, 538, 539, 541, 563, 567, 592, 602, 603, 622, 631, 675, 703 Success of natural regeneration, 304, 305, 307, 320, 322, 323, 677, 679 Success of reforestation, 135, 359–361, 363, 375, 383, 677, 704 Suomen metsät (2007), 484 Survival of seedlings, 133, 134, 196, 354, 363, 382, 384, 551, 679 Sustainable management, 4, 6, 204, 481–484, 488, 533

Index Suvuton uudistuminen, 135 Symbolic values, 593 T Tallqvist, R., 308 Target structure, 6, 7, 203, 282, 645 Technical properties, 357, 360, 377, 410, 411, 591 Thermal conditions, 22, 26, 42, 46, 47, 191, 228, 245, 292, 299, 331, 332, 399, 407, 544 Thinning, 15, 47 Thinning affecting growth, 416–420 Thinning from below and above, 411, 413, 670 Thinning in different developmental phases, 413–414 Thinning rules, 280, 286, 414, 415, 429, 432, 657, 703 Timber and biomass, 283, 322, 323, 345, 434, 484, 487–494, 513, 528, 532–535, 539, 540, 545, 547, 565, 566, 570, 593, 655, 658, 666, 670, 673, 677, 683, 691, 695 Timber quality, 458, 466–468, 472, 474, 475, 702 Timing of thinning, 488 Tirén, L., 398 Total ecosystem respiration, 237 Total growth, 47, 76, 78, 80, 81, 176, 185, 187, 189, 190, 203, 208, 209, 256, 257, 270–271, 357, 394, 405, 409, 412, 419, 420, 428–433, 489, 490, 534, 657, 658, 680, 693 Total radiation, 19, 20, 22, 233, 329 Total removal, 256, 498, 534, 691 Transition phase, 70 Translocation, 90, 91, 148, 171, 185, 440, 531 Tree, 14, 15, 27, 30–32, 34, 36, 41, 43, 44, 47, 59, 60 Tree breeding, 8, 343–345 Tree-like structure, 68 Tree species, 14, 15, 60 Tree species choice for regrowth, 337–338 Tree species composition, 6, 81, 82, 113, 242, 247, 249, 259, 307, 321, 359, 360, 365, 375, 384, 431, 432, 485, 487, 522, 537, 550, 574, 583, 585, 615, 632, 648, 659, 667, 674, 685, 702, 703, 705 Tree species mixtures, 205, 247, 367, 387, 428, 515, 685, 686 Tuuli, 26–28 U Understory seedlings, 325 Uneven-aged management, 6–8, 205, 206, 208, 257, 280–286, 292, 315, 320, 367, 397, 410, 411, 413, 483, 486, 493–497, 504, 518, 522, 524, 535, 539, 567, 575–578, 580, 583, 585, 677, 702

717 V Vaartaja, 324 Vascular cambium, 87, 93, 173 Vascular tissue, 66–67, 101 Vegetative regeneration, 78, 79, 135, 293, 304 VG analysis, 208 Viability of seeds, 305, 311 Viro, P.J., 298, 299 Vulnerabilities, 54, 243, 602, 604, 610, 612, 628, 630, 644, 645, 702, 704 Vuokila 1982, 385 Vuokila, Y., 420, 427 W Walfridsson, 386 Water cycles, 54, 292, 514, 525, 528, 529, 531, 548, 647, 654, 655 Water supply, 130, 144, 181, 183, 347, 443, 510, 533, 546, 548, 550, 662–664, 680, 683–684 Water uptake, 35, 39, 40, 66–67, 165–169, 171, 225, 361, 531, 677 Weather extremes, 52, 53 Wildlife, 8, 72, 533, 536–539, 655, 658, 659 Winds, 3, 8, 15, 26–28, 30, 35, 36, 49, 51–53, 59, 75, 79, 80, 88, 98, 102, 107, 108, 113, 118, 125–127, 133, 141, 156, 191, 200, 202, 206, 208, 220–225, 228, 229, 235–237, 239, 240, 261–263, 272, 275, 294, 316, 319, 329, 332, 333, 424, 425, 460, 461, 486, 509, 519, 539–541, 548–550, 552–554, 556, 558, 560, 562, 602–622, 634, 638, 639, 666, 692, 694, 702, 703 Winter dormancies, 70, 71, 113, 154, 155, 181, 191, 192, 194, 196, 628, 652, 660 Within- and between-tree shading, 158, 403 Within-tree shading, 158, 400, 402 Wood, 14, 41, 43, 44, 46, 59 Wood density, 77, 102, 181–183, 345, 346, 391, 420, 424, 426, 457, 519, 702 Wood formation, 90, 181–183 Woody litter, 199, 265, 267 X Xylem, 66–67, 69, 70, 86, 87, 89, 90, 93, 97, 98, 100, 101, 166–169, 171, 172, 176–179, 182, 669 Xylem cells, 176, 179, 182 Z Zygote, 117