Problems and Methods of Experimental Geographical Ecology

The author’s paradigm of experimental geographical ecology and its core-landscape ecology—has been set forth. The empirical statistical models and the ecological geographical concepts developed on their basis are described. They disclose the mechanisms of formation of regional- and local-level landscape-ecological systems, their natural and anthropogenic dynamics and evolutionary trends. New provisions on the mono- and polysystemic organization of the geographical environment have been put forward and substantiated: 1) environmental principles and mechanisms for the formation of zonal geospace and its borders; 2) the concept of polymorphism of landscape-zonal systems as a basic model for the further development of integrated physical geography; 3) a paleo-forecasting concept that describes the predicted scenarios and their paleogeographic analogues as a single system of global changes in the environment; 4) topo-ecological forecasting concept as a scientific and methodological basis of local geosystem monitoring; 5) new provisions of the theory of sustainability of natural ecosystems and methods for calculating their functional stability based on the parameters of the biological cycle. A methodology for numerical landscape-ecological forecasting developed by the author and brought to the prescription level is presented, and regional and local landscape-ecological forecasts are given based on forthcoming global climate changes. The predictive ecological analysis was performed by models of base states of the geo(eco-)systems and there climatogenic changes, with application of methods of empirical simulation techniques for the estimated prognostic situations. A strategy is proposed, and algorithms are developed for applying landscape ecology methods for quantitative forecast estimates of the biotic regulation of the carbon cycle under global climate changes. In the constructed models, geographical ecology acquires an effective formalized tool for analysis and prediction using the methods of discrete mathematics for the processing and generalization of bulk empirical data obtained from field and laboratory landscape studies.

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