MODERN BIOGEOCHEMISTRY Second Edition Environmental Risk Assessment MODERN BIOGEOCHEMISTRY: SECOND EDITION Environmental Risk Assessment VLADIMIR N BASHKIN Moscow State University Institute of Basic Biological Problems RAS, Russia A C.I.P Catalogue record for this book is available from the Library of Congress ISBN-10 1-4020-4182-9 ISBN-13 978-1-4020-4182-2 ISBN-10 1-4020-4586-7 ISBN-13 978-1-4020-4586-8 Published by Springer, P.O Box 17, 3300 AA Dordrecht, The Netherlands www.springer.com Printed on acid-free paper All Rights Reserved C 2006 Springer No part of this work may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, microfilming, recording or otherwise, without written permission from the Publisher, with the exception of any material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work Printed in the Netherlands ABOUT THE AUTHOR Vladimir N Bashkin was born in 1949 in the town of Dobrinka, Lipetsk region, Russia He graduated from the Biology-Soil department of Moscow State University in 1971, where in 1975 he was awarded a PhD, and in 1987, a Doctor of Science degree His scientific career began at the Pushchino Biological Center of the Russian Academy of Sciences in 1971 For many years Vladimir Bashkin delivered lectures in various universities such as Cornell University, USA, Seoul National University, Korea, and King Mangkut’s University of Technology, Thailand At present he is a professor of biogeochemistry and risk assessment at Moscow State University, and the principal researcher at the Gazprom company and Institute of Basic Biological Problems RAS His main research is related to environmental risk assessment, biogeochemistry, urban ecology, and trans-boundary pollution Professor Bashkin is the author of 22 books, including Modern Biogeochemistry and Environmental Chemistry: Asian Lessons (published by Kluwer), and more than 100 papers Under his supervision more than 20 PhD and DrSc dissertations have been presented in various countries and universities He is a member of the board of five international journals in the field of environmental pollution During a five year period he was selected as vice-chairman of the Working Group of Effects (scientific committee) of the UN/EC Long-Range Trans-boundary Air Pollution Convention v CONTENTS Preface xv PART I BIOGEOCHEMICAL CYCLING AND POLLUTANTS EXPOSURE CHAPTER ASSESSMENT OF ECOSYSTEMS RISKS Concepts of environmental impact assessment and risk assessment and approaches to their integration Biogeochemical approaches to environmental risk assessment Integration of risk assessment and environmental impact assessment for improved treatment of ecological implications Assessment of ecosystem effects in EIA: methodological promises and challenges Critical Load and Level (CLL) approach for assessment of ecosystem risks Uncertainty in IRA and ERA calculations Benefits of applying CCL in EIA 13 20 21 CHAPTER BIOGEOCHEMICAL STRUCTURE OF ECOSYSTEMS Characterization of soil-biogeochemical conditions in the world’s terrestrial ecosystems Biogeochemical classification and simulation of biosphere organization 2.1 Biogeochemical classification of the biosphere 2.2 Methodology of biogeochemical cycling simulation for biosphere mapping Biogeochemical mapping for environmental risk assessment in continental, regional and local scales 3.1 Methods of biogeochemical mapping 3.2 Regional biogeochemical mapping of North Eurasia 23 CHAPTER BIOGEOCHEMICAL STANDARDS Critical load as biogeochemical standards for acid-forming chemical species 47 vii 23 30 30 32 38 39 46 47 viii CONTENTS 1.1 General approaches for calculating critical loads 1.2 Biogeochemical model profile for calculation of critical loads of acidity 1.3 Deriving biogeochemical parameters for critical loads of acidity Critical load as biogeochemical standards for heavy metals 2.1 General approaches for calculating critical loads of heavy metals 2.2 Deriving biogeochemical parameters for critical loads of heavy metals 2.3 Calculation methods for critical loads of heavy metals CHAPTER BIOGEOCHEMICAL APPROACHES TO ECOSYSTEM ENDPOINTS Environmental risk assessment under critical load calculations 1.1 Suggested ERA frameworks and endpoints for development of acidification oriented projects 1.2 Comparative analysis of CL and ERA calculations of acidification loading at ecosystems Biogeochemical endpoint in critical loads calculations for heavy metals 2.1 Calculation and mapping of critical loads for HM in Germany 2.2 Calculation and mapping of critical loads for Cd and Pb in the European part of Russia CHAPTER BIOGEOCHEMICAL APPROACHES TO HUMAN EXPOSURE ASSESSMENT Biogeochemical and physiological peculiarities of human population health 1.1 Biogeochemical structure of ecosystems and cancer endpoints 1.2 Cancer risk endpoints in different biogeochemical provinces Human health endpoints in technogenic and agrogenic biogeochemical provinces 2.1 Physiological endpoints for human biogeochemical studies 2.2 Case study of interactions between human health endpoints and pollution in the Crimea Dry Steppe region of the biosphere 48 50 52 58 59 59 68 75 75 75 79 80 80 82 93 93 95 97 111 111 116 PART II NATURAL BIOGEOCHEMICAL PECULIARITIES OF EXPOSURE ASSESSMENT CHAPTER ARCTIC AND TUNDRA CLIMATIC ZONE Geographical peculiarities of biogeochemical cycling and pollutant exposure 1.1 Landscape and vegetation impacts 1.2 Pollutant exposure and chemical composition of plants 1.3 Influence of soil on pollutant exposure 127 127 127 129 130 CONTENTS 2.1 2.2 3.1 3.2 3.3 Biogeochemical cycles and exposure assessment in polar zones Biogeochemical cycles Exposure to airborne and ground pollutants Biogeochemical cycles and exposure assessment in tundra zones Plant uptake of pollutants Tundra soils and exposure to pollutants Exposure to pollutants and productivity of tundra ecosystems ix 131 131 132 133 134 134 134 CHAPTER BOREAL AND SUB-BOREAL CLIMATIC ZONE Biogeochemical cycling of elements and pollutants exposure in Forest ecosystems 1.1 Nitrogen cycle and exposure pathways 1.2 Sulfur cycle and exposure pathways 1.3 Phosphorus cycle and exposure pathways 1.4 Carbon cycle and exposure pathways Geographical peculiarities of biogeochemical cycling and pollutant exposure 2.1 North American forest ecosystems 2.2 Spruce Forest ecosystem of Northwestern Eurasia 2.3 Swampy ecosystems of North Eurasia 2.4 Broad-leafed deciduous forest ecosystems of Central Europe Biogeochemical fluxes and exposure pathways in soil–water system of Boreal and Sub-boreal zones 3.1 Soil compartment features 3.2 Biogeochemical exposure processes in the soil–water system 137 CHAPTER SEMI-ARID AND ARID CLIMATIC ZONES Biogeochemical cycling of elements and pollutants exposure in semi-arid and arid climatic zone 1.1 Biogeochemical cycle and exposure pathways in arid ecosystems 1.2 Role of aqueous and aerial migration in pollutants exposure 1.3 Role of soil biogeochemistry in the exposure pathways in arid ecosystems 1.4 Role of humidity in soil exposure pathway formation in steppe and desert ecosystems Geographical peculiarities of biogeochemical cycling and pollutant exposure 2.1 Dry steppe ecosystems of South Ural, Eurasia 2.2 Meadow steppe ecosystems of the East European Plain 2.3 Dry desert ecosystems of Central Eurasia 167 CHAPTER SUBTROPIC AND TROPIC CLIMATIC ZONE Biogeochemical cycling of elements and pollutants exposure in subtropic and tropic climatic zone 137 139 141 142 142 145 145 147 153 154 156 156 160 167 167 168 172 173 174 174 175 177 181 181 x CONTENTS 1.1 Biogeochemical cycles and exposure pathways of chemical species in tropical ecosystems 1.2 Biogeochemical and exposure peculiarities of tropical soils 1.3 Biogeochemical exposure pathways in soil–water systems Geographical peculiarities of biogeochemical cycling and pollutant exposure 2.1 Biogeochemical cycling and pollutant exposure in tropical rain forest ecosystems 2.2 Biogeochemical cycling and pollutant exposure in Seasonal Deciduous tropical forest and woody savanna ecosystems 2.3 Biogeochemical cycling and pollutant exposure in dry desert tropical ecosystems 2.4 Biogeochemical cycling and pollutant exposure in mangrove ecosystems 181 182 185 186 186 189 190 193 PART III EXPOSURE ASSESSMENT IN TECHNOGENIC BIOGEOCHEMICAL PROVINCES CHAPTER 10 OIL AND GAS BIOGEOCHEMICAL PROVINCES Biogeochemical steps of hydrocarbon formation Geological and biological factors of oil composition formation Peculiarities of ecological risk assessment in oil technobiogeochemical provinces 3.1 Vertical oil migration 3.2 Lateral oil migration 3.3 Spatial and temporal evolution of oil pollution areas 3.4 Biogeochemical feature of environmental risk assessment 201 201 203 CHAPTER 11 METALLOGENIC BIOGEOCHEMICAL PROVINCES Environmental ranking of metal toxicity 1.1 Heavy metal migration in biogeochemical food webs 1.2 Sources of heavy metals and their distribution in the environment Usage of metals 2.1 Anthropogenic mercury loading 2.2 Anthropogenic lead loading 2.3 Anthropogenic cadmium loading Technobiogeochemical structure of metal exploration areas 3.1 Iron ore regions 3.2 Non-iron ore areas 3.3 Uranium ores 3.4 Agricultural fertilizer ores 215 216 216 218 220 220 221 223 224 224 225 226 228 CHAPTER 12 URBAN BIOGEOCHEMICAL PROVINCES Criteria of urban areas classification 229 229 208 208 209 210 214 CONTENTS 5.1 5.2 5.3 Ecological problems of urbanization Urban biogeochemistry Modern approaches to exposure assessment in urban areas Case studies of urban air pollution in Asia Outdoor pollution Indoor air quality Urban air pollution and health effects CHAPTER 13 AGROGENIC BIOGEOCHEMICAL PROVINCES Impact of agrochemicals on the natural biogeochemical cycling 1.1 Mineral fertilizers 1.2 Disturbance of nitrogen biogeochemical cycle in agrolandscapes 1.3 Disturbance of phosphorus biogeochemical cycle in agrolandscapes Impact of pesticides in agrolandscapes 2.1 Pesticides in the Asian countries 2.2 Major environmental exposure pathways 2.3 DDT example of environmental exposure pathway xi 229 231 231 232 232 238 239 245 245 245 246 247 251 251 252 256 PART IV ENVIRONMENTAL RISK ASSESSMENT IN A REGIONAL SCALE CHAPTER 14 CALIFORNIA CASE STUDIES Selenium effects research 1.1 San Joaquin River Valley, California 1.2 Selenium in fodder crops of the USA Pollutants exposure pathways 2.1 Chemical exposure 2.2 Characterization of the composition of personal, indoor, and outdoor particulate exposure 2.3 Beryllium exposure Occupational exposure 3.1 Occupational exposure to multiple pesticides 3.2 Occupational exposure to arsenic 3.3 Air pollutants Cancer researches 4.1 Childhood cancer research program 4.2 Adult cancer research program Respiratory effects research 261 261 261 263 263 263 CHAPTER 15 EURASIAN CASE STUDIES Environmental risk assessment of Se induced diseases 1.1 Northern Eurasia 1.2 Selenium in China’s ecosystems Environmental risk assessment of Co–Zn–Ni induced diseases 275 275 275 278 280 266 267 267 267 268 268 270 270 271 272 ASSESSMENT OF ECOSYSTEMS RISKS 17 Figure The model for assessment of ecosystem risks in the EIA for projects with significant ecological implications 18 CHAPTER It is the responsibility of the appointed environmental consultants to undertake preliminary investigations and decide if a proposed development may result in significant ecological effects Data on “risk agents” including ecosystem stressors associated with the project and their potential impacts on the environment underpin screening decisions Scoping should include defining project alternatives, compiling the list of project impacts, which should be subject to comprehensive impact assessment and planning the further steps of the assessment process In the formal EcoRA framework this step is related to problem formulation A separate task of this stage is to select methods and procedures for dealing with particular impacts For ecosystem effects available information on stressors, effects, and receptors is analyzed to define risk assessment endpoints (assessment and measurement endpoints) and possible conceptual models In addition, policy and regulatory requirements, available budget and an acceptable level of uncertainty are considered in developing a plan for EcoRA Here the assessment team may consider applicability of the CLL concept to project ecological effects and develop a plan of specific studies for calculating and mapping critical loads The outcome of the scoping is to be an EIA Terms of Reference (ToR) referring to all abovementioned issues The next step is impact prediction that requires detailed quantitative information about the sources of risk agents, exposure models, the receptors and possible changes in the state of these receptors caused by the defined agents If the CLL concept was selected for assessment ecosystem effects it should firstly be utilized for impact baseline studies or assessing the “do-nothing” scenario In this context CLL calculation includes the following steps (Bashkin, 2002): r characterizing receptors that are potentially affected by the proposed development, r defining environmental quality criteria, r collecting input data for CLL calculations, r calculating critical loads (CLs), r comparing CLs with actual loads to calculate the exceedances When the environmental baseline is established one can proceed with predicting the magnitude of potential impacts onto receptors at risk for exposure assessment in EcoRA terms This includes: r quantifying emissions of pollutants of concern, r modeling their transport in the environmental media, r estimating the predicted exposure levels, r estimating predicted loads Under the CLL approach, ecosystem effect assessment means comparing critical loads with predicted loads of pollutants Of importance, this may be limited to an ASSESSMENT OF ECOSYSTEMS RISKS 19 ecosystem as a whole without further evaluating adverse effects on specific ecosystem components CL mapping with help of GIS is especially useful for this purpose Impact prediction should cover all project alternatives selected at scoping (either spatial or technological) and project phases (construction, operation, closure and postclosure are the main subdivisions) Moreover, exposure assessment should cover both normal operation and accidental conditions Significance of the predicted impacts should be assessed in the process of impact evaluation or interpretation At this stage the health risk estimates (quantitative and qualitative) are analyzed in terms of their acceptability against relevant regulatory and/or technical criteria: environmental quality standards or exposure limits Critical load exceedances may serve as the basis for interpreting ecological impacts as ecological risks (or rather changes in the level of current risk to “ecosystem health”) This would refer to the process of ecological risk characterization There are a number of approaches to measuring risks depending on assessment and measurement endpoints selected At ecosystem level, one can propose a percentage of the affected area with CLs exceeded as an acceptable quantitative parameter for ecosystem risk magnitude In pristine areas, actual state of the environment may be taken as a reference point for risk characterization As to risk significance, the degree of alteration in the current environment should be amended with qualitative and semi-qualitative criteria Ecological impact significance should be considered in terms of: r ecosystem resilience to particular impacts, r principal reversibility of potential ecosystem damage, r threats to valuable ecosystem components, etc The estimation of accuracy of quantitative predictions and the degree of uncertainty of the assessment findings should be attempted as well The results of impact prediction and evaluation are used for designing impact mitigation measures that aim to prevent or reduce the adverse effects associated with the projects and restore or compensate the predicted damage to the environment Impact mitigation should firstly involve risk reduction measures: (1) control of the source of risk agents; (2) control of the exposure; (3) administrative/managerial improvements; (4) risk communication allowing for more comprehensive risk perception The selection of appropriate mitigation measured would benefit from using risk–benefit analysis (with formal quantification of residual risks for every option if applicable) Following the logic of the CLL approach, impact mitigation in EIA is to derive critical limits of exposure (concentrations of pollutants in exposure media) and based on these values calculating maximum permissible emissions that ecosystems in the site vicinity would sustain during the life-time of the proposed facility Therefore, any technology that allows for not exceeding CLs for potentially affected ecosystems should be acceptable from the environmental viewpoint, not exclusively the Best Available Technology (BAT) as often recommended 20 CHAPTER UNCERTAINTY IN IRA AND ERA CALCULATIONS One can identify two major categories of uncertainty in EIA: data (scientific) uncertainty inherited in input data (e.g., incomplete or irrelevant baseline information, project characteristics, the misidentification of sources of impacts, as well as secondary, and cumulative impacts) and in impact prediction based on these data (lack of scientific evidence on the nature of affected objects and impacts, the misidentification of source–pathway–receptor relationships, model errors, misuse of proxy data from the analogous contexts); and decision (societal) uncertainty resulting from, e.g., inadequate scoping of impacts, imperfection of impact evaluation (e.g., insufficient provisions for public participation), “human factor” in formal decision-making (e.g., subjectivity, bias, any kind of pressure on a decision-maker), lack of strategic plans and policies and possible implications of nearby developments (Demidova, 2002) Some consequences of increased pollution of air, water and soil occur abruptly or over a short period of time Such is the case, for instance, with the outbreak of pollution-induced diseases, or the collapse of an ecosystem as one of its links ceases to perform Avoiding or preparing for such catastrophes is particularly difficult when occurrence conditions involve uncertainty In spite of almost global attraction of the critical load concept, the quantitative assessment of critical load values is connected till now with some uncertainties The phrase “significant harmful effects” in the definition of critical load is of course susceptible to interpretation, depending on the kind of effects considered and the amount of harm accepted (De Vries and Bakker, 1998a, 1998b) Regarding the effects considered in terrestrial ecosystems, a distinction can be made in effects on: r soil microorganisms and soil fauna responsible for biogeochemical cycling in soil (e.g., decreased biodiversity); r vascular plants including crops in agricultural soils and trees in forest soils (e.g., bioproductivity losses); r terrestrial fauna such as animals and birds (e.g., reproduction decrease); r human beings as a final consumer in biogeochemical food webs (e.g., increasing migration of heavy metals due to soil acidification with exceeding acceptable human daily intake, etc.) In aquatic ecosystems, it is necessary to consider the whole biogeochemical structure of these communities and a distinction can be made accounting for the diversity of food webs: r aquatic and benthic organisms (decreased productivity and biodiversity); r aquatic plants (e.g., decreased biodiversity, eutrophication); ASSESSMENT OF ECOSYSTEMS RISKS 21 r human beings who consume fish or drinking water (surface water) contaminated with mobile forms of heavy metals due to acidification processes (e.g., poisoning and death) BENEFITS OF APPLYING CCL IN EIA Therefore, the CLL concept is a valuable methodology for ecological impact and risk assessment and is easily adjusted to the formal EIA procedure The proposed framework could be applied to EIAs of development projects with high ecological implications that can potentially affect the environment both on local and regional scales The model may be applicable to developments that involve releases of acidifying and eutrofying compounds, heavy metals and POPs into the environment in areas with high ecosystem vulnerability and/or pristine areas Ecological effects are often treated inadequately in the assessment of environmental impacts of proposed developments, while lack of quantitative ecological impact predictions is mentioned among key drawbacks of the current EIA practice The idea of integrating RA into EIA for improving the quality of EI studies has been supported by many EIA practitioners At the same time, formal ecological risk assessment has significant limitations for assessing ecosystems risks related to proposed developments To improve addressing ecological implications of human activities, the author has attempted to incorporate the Critical Load and Level (CLL) approach, an established methodology for assessing effects of industrial pollution on ecosystems and their sensitive components, into the EIA process Benefits of and obstacles to applying that approach to assessing ecosystem effects within EIA were analyzed Finally, a structured framework for CLL application for ecosystem risk assessment in EIA aimed at integrating three assessment tools was presented and key CLL inputs into impact assessment stages were discussed The proposed model of integrated assessment process is suggested for testing in EIAs for development projects with high ecological implications: those associated with releases of pollutants covered by current CLL calculating and mapping methodology and located in areas particularly sensitive to the selected indicator chemicals CHAPTER BIOGEOCHEMICAL STRUCTURE OF ECOSYSTEMS The biogeochemical structure of natural ecosystems resulted from the co-evolution of the geosphere and the biosphere (Degens, 1989; Schlesinger, 1997; Bashkin, 2002) During this co-evolution each elementary geochemical unit (the smallest unit of the Earth’s surface organization) has corresponded to a specific ecosystem with regular biogeochemical food webs In turn, these food webs have been adapted to the specific parameters of migration and accumulation of different chemical species in the biosphere CHARACTERIZATION OF SOIL-BIOGEOCHEMICAL CONDITIONS IN THE WORLD’S TERRESTRIAL ECOSYSTEMS The biogeochemical cycling in different ecosystems is to a large extent determined by biota, especially by the primary production of plants and by microbial decomposition At present we recognize the development of the intensive biogeochemical investigations of a large number of ecosystems in North America, Europe, Asia and South America The biogeochemical cycling picture is designed to summarize the circulation features in various components of ecosystems such as soil, surface and ground water, bottom sediments, biota and atmosphere (Figure 1) Ecosystem and soil regionalization can be a basis for biogeochemical mapping (Fortescue, 1980; Glazovskaya, 1984; Ermakov, 1993) The combination of this mapping with the quantitative assessments of biological, geochemical and hydrochemical turnover gives an opportunity to calculate the rates of biogeochemical cycling and coefficients of biogeochemical uptake, Cb , for different ecosystems (Bashkin, 2002) In addition to the coefficient of biogeochemical uptake, we can also apply the active temperature, Ct , and relative biogeochemical, Cbr , coefficients The application of these coefficients for the characterization of soil-biogeochemical conditions in various ecosystems is based on the following hypothesis: (a) For northern areas the real duration of any processes (biochemical, microbiological, geochemical, biogeochemical) must be taken into account because they are depressed annually for 6–10 months and the influence of acid forming compounds, 23 24 CHAPTER Figure The general scheme of biogeochemical food webs in the terrestrial ecosystems as well as any other pollutant, occurs during summer A process duration term has been derived as the active temperature coefficient, Ct , which is the duration of active temperatures >5◦ C relative to the total sum (b) The relative biogeochemical, Cbr , coefficient is the multiplication of the first two coefficients This may characterize the influence of temperature on the rates of biogeochemical cycling in various ecosystems The relative biogeochemical, Cbr , coefficient is applied as a correction to Cb values Table shows the combinations of soil-biogeochemical and temperature conditions in various geographical regions of the World The given combination of factors is represented by ecosystem types, FAO main soil types, biogeochemical, Cb , active temperature, Ct , and relative biogeochemical, Cbr , coefficients The subdivision of ecosystem types is based on various parameters, including vegetation and soil types, and main climate characteristics like temperature and ratio of precipitation-toevapotranspiration The corresponding values of active temperature coefficients ranged in accordance with the main climatic belts are shown in Table The values of Cbr for each geographical area were ranged to determine the type of biogeochemical cycling and these ranks are shown in Table Five types of biogeochemical cycling are divided: very intensive, intensive, moderate, depressive and very depressive Using the above-mentioned approaches, we may describe the peculiarities of biogeochemical structure for the main global ecosystems in various continents Detailed Table The values of biogeochemical cycling (Cb ), active temperature (Ct ) and relative biogeochemival (Cbr ) coefficients in various soil-ecosystem geographical regions of the World (Bashkin and Kozlov, 1999) Ct Cbr North American 10.0 0.06 0.6 Eurasian 10.0 0.06 0.6 North American 18.0 0.15 2.7 Eurasian 18.0 0.15 2.7 Alaskan-Cordillera 10.0 0.28 4.2 Laurentian 8.5 0.35 3.0 North Atlantic 5.5 0.55 3.0 North European 8.0 0.45 3.6 European–West-Siberian 8.5 0.35 3.0 North Siberian 9.5 0.25 2.4 Central Siberian 9.3 0.30 2.8 East Siberian 7.5 0.20 1.5 Kamchatka–Aleutian 5.0 0.25 1.7 Central Yakutian 10.0 0.35 3.5 Central Canadian 10.0 0.32 3.2 Main FAO soil types Geographical region Arctic Deserts and Primitive Tundra Litosols, Regosols Tundra Cryic Gleysols, Histosols, Humic Podzols Boreal Taiga Forest Taiga Meadow-Steppe Podzols, Podsoluvisols, Spodi-Distric, Cambisols, Albi-Gleyic Luvisols, Gelic and Distric Histosols, Rendzinas and Gelic Rendzinas, Andosols, Gleysols Planosols BIOGEOCHEMICAL STRUCTURE OF ECOSYSTEMS Cb Ecosystems (Conti.) 25 26 Table (Continued ) Main FAO soil types Geographical region Cb Ct Cbr Subboreal Forest Podzols, Dystric and Eutric Cambisols, Umbric Leptosols, Podsoluvisols Eastern North American 2.0 0.65 1.3 West European 1.5 0.83 1.2 East European 2.0 0.60 1.2 Hercian Alpine 2.5 0.72 1.8 East Asian 2.6 0.67 1.7 East Chinese 1.5 0.81 1.2 Coastal Pacific 1.6 0.67 1.1 New Zealand 1.2 0.78 0.9 South Chilean 1.2 0.75 0.9 Luvic Carpathian–North Caucasian 1.2 0.75 0.9 Fhaeozems, Cambisols, Chernozems Central Russian 1.4 0.65 0.7 West Siberian 1.5 0.47 0.8 South Siberian 2.0 0.42 1.0 Amur–Manchurian 1.5 0.65 0.8 Central Cordillera 1.1 0.70 0.8 South Canadian 1.3 0.60 0.8 Central Plain 1.1 0.71 0.8 Forest Meadow Steppe Steppe CHAPTER Ecosystems Chernozems, Vertisols Eastern Pampa 0.8 0.95 0.8 Steppe Chernozems, Kastanozems Solonetzes European Kazakhstan 0.7 0.57 0.4 Mongolo–Chinese 0.8 0.61 0.5 Central Plains 0.7 0.70 0.5 Mediterranean 0.9 0.87 0.8 North African 0.8 0.95 0.8 Texas 0.8 0.95 0.8 South East African 0.9 0.95 0.9 Central Asian 0.4 0.70 0.3 Pamiro–Tibetan 0.6 0.62 0.4 Middle Asian 0.5 0.77 0.4 Preasiatic 0.3 0.89 0.3 Hindukush–Alai 0.4 0.86 0.3 Tien Shan 0.6 0.60 0.4 West American 0.4 0.70 0.3 Mexican–Californian 0.3 0.95 0.3 Saharan 0.2 1.00 0.2 Arabian 0.2 1.00 0.2 Mountain Vertisols, Eutric Cambisols Depression Forest, Bush and Steppe Desert-Steppe and Desert Xerosols, Regosols, Arenosols, Yermosols, Solonetzes, Solonchaks 27 (Conti.) BIOGEOCHEMICAL STRUCTURE OF ECOSYSTEMS South American Meadow Steppe 28 Table (Continued ) 0.3 0.80 0.3 0.4 1.00 0.4 0.5 0.71 0.4 0.2 1.00 0.2 South Asian 0.3 1.00 0.3 Caribbean 0.3 1.00 0.3 Brazilian 0.2 1.00 0.2 East Brazilian 0.3 1.00 0.3 Cis–Andean 0.3 0.98 0.3 Somalian–Yemenian 0.3 1.00 0.3 Sudan–Guinean 0.4 1.00 0.4 East African 0.3 1.00 0.3 Angolo-Zimbabwean 0.3 1.00 0.3 North Australian 0.2 1.00 0.2 East Australian 0.3 1.00 0.3 South Australian 0.4 1.00 0.4 West Australian 0.3 1.00 0.3 CHAPTER Cbr Central Australian Livi-Plinticic Ferrasols, Luvisols, Vertisols, Subtropical Rendzinas, Ferralitic Cambisols, Nitosols, Ferralitic Arenosols, Subtropical Solonchaks Ct Patogonian Savanna, Tropical Forest Cb Andean Main FAO soil types Geographical region South African Ecosystems Ferrasols, Eutric Subtropical Histosols, Gleyic Subtropical Podzols, Plinthic Gleysols, Nitosols South East Asian 0.2 1.00 0.2 Himalayan 0.4 0.80 0.3 Andean–Equatorial 0.3 1.00 0.3 Central American 0.1 1.00 0.1 Malaysian–New Guinean 0.1 1.00 0.1 Brazilian–Atlantic 0.15 0.98 0.1 Amazonian 0.1 1.00 0.1 Congo–Guinean 0.1 1.00 0.1 South East Latin American 0.1 1.00 0.1 East Australian 0.1 1.00 0.1 BIOGEOCHEMICAL STRUCTURE OF ECOSYSTEMS Subtropical and Tropical Wet Forest 29 30 CHAPTER Figure Dependence of biochemical and physiological processes in organisms on the content of essential chemical elements in the biogeochemical food webs as a physiological adaptation curve 1—lower (deficient) content; 2—optimum content; 3—excessive (upper) content descriptions are given in the additional references (see Glazovskaya, 1984; Bailey, 1998; Bashkin, 2002) BIOGEOCHEMICAL CLASSIFICATION AND SIMULATION OF BIOSPHERE ORGANIZATION 2.1 Biogeochemical Classification of the Biosphere Biogeochemical mapping is the scientific method for understanding biosphere structure This method is based on the co-evolution of geological and biological parameters of the biosphere and deals with the quantification of the interrelations between biota and the environment in consequent biogeochemical food webs The fundamentals of biogeochemical mapping have been intensively developed during the twentieth century in Russia and other countries Biogeochemical mapping combines the definitions of soil zones (Dokuchaev, 1948) and provinces (Prasolov, 1939), geochemical provinces (Fersman, 1931), biogeochemical provinces (Vinogradov, 1938), Table The ranges attached to temperature regime data to assess the duration of active biogeochemical reactions Active temperature coefficient, Ct Ranks Temperature regime Arctic