Influence of contemporary warming on landscape-zonal systems of the East-European sub-continent: Predictive empirical-statistical modeling

Abstract

Presented in the given article regional geo-ecological prognoses are based on the construction of discrete empirical-statistical models of zonal and regional ecosystems. The analysis was carried out on the examples of the flat territories of the Volga River basin, as well as the northern macro-slope of the Main Caucasian ridge. Regional landscape-ecological calculations and mapping were carried out according to the global climatic models GISS-1988 and E GISS-2007 belong­ing to the family of models of general atmospheric circulation. The strategy of geo-ecological prognosis was as follows: first to identify the selected ecosystem objects (either zonal type of plant formations and regional kinds of landscape) to certain values of contemporary climatic conditions and then to estimate the most probable transformation of the revealed ecological niches of the given objects according to the expected climatic changes for the given prognostic date. The geo-ecological analysis has been performed using mainly two types of empirical models: (a) informational, describing the geo-component interrelations, serving as a basis for the regional bank of their ecological niches that characterizes their parametric space; (b) “fuzzy” set-theoretical models, describing the polysystem units of landscape-zonal organization by operations with the ecological niches as descriptive vectors. Predictions of ecosystem transformations include two stages of analysis: (1) evaluation of the probabilities of changes in the functional states of ecosystems and (2) calculations of the rates of ecosystem transformations. Quantitative predictive analysis is carried out by means of operations with the hydro-thermal niches of zonal-regional ecosystems. The ecological estimates of forthcoming global warming refer first of all to the functional but not structural-morphological prediction. The most probable directions and degree of conversion of the ecosystem are estimated by the maximum values of transformation. The algorithms of predictive calculations are described in detail for both stages of analysis. The results of the zonal-regional prognostic analysis are presented in both graphic-analytical models and small-scale maps.