ISSN 10674136, Russian Journal of Ecology, 2012, Vol. 43, No. 1, pp. 1–12. © Pleiades Publishing, Ltd., 2012.
Original Russian Text © E.G. Kolomyts, L.S. Sharaya, 2012, published in Ekologiya, 2012, No. 1, pp. 3–15.
Conservation of the biodiversity and natural
resources of alpine ecosystems is an important task.
Natural associations of alpine regions are among the
most dynamic units of the biosphere; they are highly
sensitive to both climatic changes and anthropogenic
impact. Climatic variations cause shifts in the heat ad
moisture supply to the alpine stratum, which results in
periodic destabilization of mountain slopes and con
sequent catastrophic phenomena, such as landslides,
mudflows, and avalanches. They also play a role in the
rearrangement of the alpine phytobiota, including a
shift of the upper timberline, an important biogeo
graphic and landscape boundary in high mountains.
The prediction of the ecological consequences of the
forthcoming (actually ongoing) global climate warm
ing, which is determined by technogenic growth of the
atmospheric contents of carbon dioxide, methane, flu
orocarbons, and other greenhouse gases, is one of
urgent global ecological problems. Global biospheric
processes originate in individual regions (Sochava,
1974); however, the transition from global to regional
and, especially, local ecological prediction encounters
substantial methodological problems.
response to global climate change takes the form of a man
ifold response of vegetation and soil to background hydro
The global and regional geographic
trends themselves are usually described by two parame
ters: air temperature and precipitation, whose relation
ships with biogeocenoses are weak and often statistically
nonsignificant. At the same time, there are no local
level prognostic climatic models (Theurillat et al.,
1998), although the biogeocenosis as an elementary
unit of the biogeochemical activity of the biosphere
(TimofeeffRessovsky, 1970) is “the primary apparatus
of energy and material exchange” (Sochava, 1974, p. 5).
Spreading widely, local processes become global.
Here, we describe our experience in predicting the
possible ecological consequences of global climate
warming for alpine ecosystems (as exemplified by the
vicinity of Mount Elbrus) with the use of new methods
of landscape ecology (Kolomyts, 2008; Sharaya,
The landscape ecological approach
revealing the spatial diversity of climaterelated
changes in biogeocenoses determined by their catenic
organization under different regional and zonal condi
tions. Landscape ecological prognostic analysis is
based on the construction of
tical models of natural associations
Kolomyts, 2008). They are used to obtain probabilistic
prognostic estimates of the behavior of phytocenoses
under various geomorphological and edaphic condi
tions of specific ecoregions. The landscape ecological
prediction itself consists of two stages, analytical and
cartographic, which are considered below.
ANALYTICAL METHODS OF LANDSCAPE
The prediction strategy is based on the actualism
method. It consists of original identification of plant
units with specific parameters of basic climatic condi
tions and subsequent quantitative estimation of the
most probable transformations of these objects corre
sponding to the expected climatic changes within a
specified time. This approach assumes multifold,
probabilistic transformations of ecosystems at the
same value of the hydrothermal trend, when a new
state may have characteristics of several states existing
at the initial moment, rather than a single state.
Prognostic Simulation of Alpine Ecosystems in View of Global
E. G. Kolomyts and L. S. Sharaya
Institute of Ecology of the Volga Basin, Russian Academy of Sciences, ul. Komzina 10, Tolyatti, 445003 Russia
Received November 9, 2010
—Experience in predicting the state of alpine ecosystems on the basis of empirical–statistical simu
lation is described using the example of the Central Caucasus. Two types of analytical and cartographic prog
nostic models, chorometric and chronometric, are presented. They are used to obtain probabilistic estimates
of alpine meadows and forests in the vicinity of Mount Elbrus in view of the forthcoming global climate
warming for the period until the year 2100 (by means of GISS Model E for climate prediction).
: alpine ecosystems, global climate warming, empirical–statistical simulation, prediction, mapping.