Experimental Geographical Ecology: Problems and Methods

· Cambridge Scholars Publishing
eBook
705
Pages
Eligible

About this eBook

This book sets out a paradigm of experimental geographical ecology and its core—landscape ecology—providing a number of empirical statistical models and ecological geographical concepts developed on the basis of these. It highlights the mechanisms of formation of regional- and local-level landscape-ecological systems, their natural and anthropogenic dynamics, and their evolutionary trends. It presents numerical methods of making landscape-ecological forecasts and assessing forest sustainability, and provides quantitative estimates of local and regional biotic regulation of the carbon cycle according to the scenarios of modern temperature growth and mitigation of warming, set out by the Paris (2015) Agreement on Climate Change. As such, the book will be a useful source of reference for field research, statistical and cartographic processing of the obtained data, mathematical modeling, geoecological interpretation of results, and the creation of theoretical schemes of geosystem analysis. It will appeal to specialists in the fields of geographical ecology, landscape-ecological modeling, and environmental forecasting.

About the author

Erland G. Kolomyts graduated from the Geographical Faculty of Moscow State University in 1960, and received his DSc in Geographical Sciences from the same institution in 1972. He is a Professor of Physical Geography and Ecology and the author of a large number of articles and books. He has received several awards for his work, including the Grigoryev Prize Laureate of the Russian Academy of Science in 2015, an Honorary Doctorate of Letters in 2016, and an Honorary Doctorate of Philosophy awarded by the International Biographical Centre, Cambridge, in 2018. His scientific interests include complex physical geography, geophysics, landscape ecology, structural and evolutionary snow studies, ecological-geographical prognosis, and evolutionary biosphere processes.

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