Boreal Forests Under Global Warming: Empirical Simulation Predictive Modeling

by Erland G. Kolomyts

Overview

This groundbreaking book presents an innovative predictive concept in geographical ecology that reveals local  and regional mechanisms of global environmental changes.  This work provides environmental scientists with formalized tools for analysis and prediction that can be applied to real-world ecological challenges. Ecological modeling through the application of discrete mathematics for processing extensive empirical data from field and laboratory landscape studies.

Empirical simulation of forecasts is implemented as a reproduction of predicted scenarios of biogeocoenotic systems according to the laws of their basic spatial organization, with  the fundamental properties of ergodicity of the natural environment. The methodology presented transforms geographical ecology into a more precise and quantifiable discipline capable of addressing complex environmental dynamics.

This monograph is primarily intended for specialists in  ecological modeling and forecasting, and ecological planning in forestry. Additionally, as it draws from the Russian school of landscape science—an approach not widely familiar to many Western European and American researchers—the book offers valuable theoretical and methodological insights for both landscape scientists and ecologists across various specializations. Researchers seeking innovative approaches to understanding environmental change will find this work particularly valuable for its unique perspective and practical applications.

Product Details

ISBN-13:	9781041225959
Publisher:	CRC Press
Publication date:	03/24/2026
Pages:	288
Product dimensions:	6.12(w) x 9.19(h) x (d)

About the Author

Erland G. Kolomyts has been a scientist in Institute of Geography of Siberia and Far East, Russian Academy of Science, Irkutsk, 1960-1972, a scientist in Pacific Institute of Geography, Russian Academy of Science, Vladivostok, 1972-1977, the Head of Laboratory of geo-ecology of High mountain geophysical institute, Nalychik, 1977-1986, the Head of (sub-)faculty of Physical geography in Nizhniy Novgorod pedagogical University, 1986-1990, and the Head of Laboratory of landscape ecology in Institute of ecology of the Volga River Basin of Russian Academy of Science, Togliatti, 1990. Since December 2022, he has moved to work at the Institute for Fundamental Problems of Biology of the Pushchino Scientific Center of the Russian Academy of Sciences as a leading researcher. His Honours and/or awards include: Doctor of geographical sciences,1976; Professor, 1986; Meritorious Science Worker of Russian Federation, 2003; The Grigoryev Prize laureate by Russian Academy of Science, 2015.

Table of Contents

FOREWORD INTRODUCTION Chapter 1. EMPIRICAL-SIMULATION PREDICTEV MODELING IN THE GEOGRAPHICAL ECOLOGY (Framework Concept) 1.1. Introductory Provisions 1.2. Strategy of scientific and methodological search 1.3. Originality of the concept 1.4. The novelty of given scientific search 1.5. Numerical methods of landscape-ecological forecasts Chapter 2. LANDSCAPE-ECOLOGICAL STRATEGY FOR GROUND GEOECOLOGICAL MONITORING OF THE FORESTS 2.1. Regional ecology and problem of global changes 2.2. Current state of the concept of geo-ecological monitoring in a changing climate 2.3. Bioclimatic zonality as an object of ecological-geographical research 2.4. Zonal structure of East-European sub-continent 2.5. Some inferences Chapter 3. BOREAL GEOGRAPHICAL ECOTONE IN THE NORTHERN EURASIA 3.1. The main provisions for the theory of geographical ecotones 3.2. Boreal ecotone of the East-European Plain as a landscape- ecological system 3.3. The boreal ecotone as a natural “fast-flowing” model of global change 3.4. Functioning of geo(eco-)systems as an object of the ecological monitoring 3.5. Environmentally sustainability 3.6. Strategy of science search 3.5. Some inferences Chapter 4. METHODS OF LOCAL AND REGIONAL LANDSCAPE-ECOLOGICAL MODELING 4.1. Introductory remarks 4.2. General features of landscape ecological modeling 4.3. Mono-system information-statistical models 4.4. Typical schemes of binary ordination 4.5. Poly-system fuzzy-set-theoretical models 4.6. Integral parameters of mono- and poly-system organization of natural complexes 4.7. Distinguishing of forest biogeocoenosis eco-types 4.8. Representation of calculating predictive climatic models Chapter 5. REGIONAL AND LOCAL GEOSYSTEMS AS THE OBJECTS OF PREDICTIVE RESEARCH 5.1. Introductory notes 5.3. Ground empirical material for modeling 5.3.1. Landscape structure of the nature zones 5.3.2. Regional bioclimatic system 5.3.3. Experimental test sites 5.3.4. System of local and regional landscape coupling 5.3.5. Large-scale landscape-ecological surveys 5.4. Parameters of the biological cycle as indicators of ecosystem sustainability 5.5. The importance of studying local geo(eco)systems for landscape-ecological forecasts Chapter 6. HYDRO-CLIMATIC SYSTEM OF THE VOLGA RIVER BASIN AND ITS ENCIRCLEMENT 6.1. Chain reactions in the regional landscape-geophysical relations 6.2. Methods for calculating landscape-geophysical characteristics 6.3. Space relations of temperature and precipitation 6.4. Regional scenarios of primary bio-productivity change in the system of background climatic fluctuations Chapter 7. LANDSCAPE-GEOPHYSICAL FOUNDATIONS OF ECOLOGICAL PROGNOSES 7.1. Functional ordination of forest ecosystems according to arid climatic trend 7.1.1. Introductory remarks 7.1.2. Ergodic system of nature complexes 7.1.3. Hydro-thermal ordination of biological cycle parameters 7.1.4. Empirical simulation of climate-genic changes in the biological cycle 7.2. Regional and local humidity factors and their significance for ecological prognoses 7.2.1. Issues of the problem and basic materials 7.2.2. The space diversity of annual atmospheric humidity factor 7.2.3. Edaphic humidity factor and the methods of its calculation 7.2.4. Local coefficient of common humidification 7.3. Humidity factors and levels functioning of geo(eco-)system 7.4. Hydro-edaphic conditions of the critical states of forest eco- systems 7.5. The predictive estimates od edaphic humidity changes and their ecological effect 7.5. Some inferences Chapter 8. PECULIARITY OF LANDSCAPE-ECOLOGICAL FORECASTIGS 8 1. The ways of development of regional prediction concept 8.2. Landscape-ecological system as an object of predictive modeling 8.3. Ideological foundations and strategy of predictive research Chapter 9. EMPIRICAL-SIMULATION PREDICTIVE MODELING OF FOREST ECOSYSTEMS 9.1. The value of empirical simulation in landscape-ecological forecasts 9.2. Statistical analysis of functional biogeocoenotic relationships 9.3. Ordination as a basis for empirical-statistical modeling 9.4. Local empirical simulation of the regional climatic trend 9.5. Polyzonality of local ecosystems as a way of reresponse to climate change 9.6. The principle of optimality in the functioning of ecosystems 9.7. The driving forces of climate-genic successions Chapter 10. REGIONAL LANDSCAPE-ECOLOGICAL PROGNOSES 10.1. Analytic methods of landscape-ecological prognoses 10.1.1. Evaluate of probabilities of changes in the functional states of ecosystems 10.1.2. Algorithm of predictive calculations 10.1.3. Calculations of the rates of ecosystem transformations 10.2. Prognoses of functional changes of plant formations 10.2.1. Main features of climatic prognosis in the region 10.2.2. Forecasting changes in the functional states of plant formations 10.2.3. Dynamics of biological cycle parameters in zonal-regional ecosystems 10.3. Modern regional analogues of predicted landscape-ecological situations under global warming 10.4. Main inference Chapter 11. CARTOGRAPHIC MODELS OF REGIONAL LANDSCAPE-ECOLOGICAL FORECASTING 11.1. Ideological foundations of predictive research 11.2. Predictive mapping of focal landscape transformations 11.3. Analytical and cartographic assessment of inductive landscape transformation 11.4. Brief analysis of forecast scenarios 11.4. Main inference Сhapter 12. LOCAL LANSCAPE-ECOLOGICAL PROGNOSES 12.1. The ideology of local environmental forecasting 12.2. Prerequisites of research 12.3. Empirical materials 12.4. Polyzonality of local ecosystem as a way of their reaction on the global climatic signals 12.5. The main characteristics of climate prediction 12.6. Prediction procedure 12.7. Prognostic scenarios of transformation of forest ecosystems 12.7.1. Changes of the soil moisture content 12.7.2. Climate-genic dynamic of the forest biogeocoenoses 12.8. Main inferences Chapter 13. PHYTOCOENOTIC AND SOIL SIGNS OF CURRENT GLOBAL WARMING 13.1. Main features of the climatic trend 13.2. General changes in soil-plant cover 13.3. Phytocoenotic changes at the Main landscape Border of the Russian Plain 13.4. Phytoecological effect of enhanced non-stationarity of the сlimate 13.5. Main inferences Chapter 14. MECHANISMS OF STABILITY OF FOREST ECOSYSTEMS 14.1. Problem status 14.2. Analytical modeling of the stability of forest biogeocoenoses 14.2.1. Labile phytocoenotic resistance 14.2.2. Inertial soil-biotic stability 14.3. Stability of forest biogeocoenoses in cartographic terms 14.4. Models of stability for forest formations 14.5. Main inferences Chapter 15. THE ROLE OF BOREAL FORESTS IN REGULATION THE CARBON CYCLE AND MITIGATING MODERN GLOBAL WARMING 15.1. Adaptation and mitigation is the final stage of geoecological monitoring 15.2. The concept of ecological resources of forests in the regulation of the carbon cycle . 15.3. Carbon balance of forest ecosystems for different climate trends 15.3. 1. The general trends and objectives of research 15.3.2 Methods of prognostic analysis 15.3.3. The carbon balance of forest ecosystems predicted for different climatic trends 15.3.4. Mapping predictive scenarios of the carbon balance 15.4. Ecological resources of restored primary forests of the Volga River basin 15.5. Verification of predictive calculations of the carbon balance 15.6. Toward the solution of the dual problem of adsorption and adaptation (in accordance with the Paris Agreement) 15.8. Main inferences CONCLUSION SUPPLEMENTS. LIST OF THE SIGNS FOR MODELING REFERENCES ABOUT AUTHOR SUDJECT INDEX