Basic approaches to the analysis and modeling of forest ecosystems

The increasing human impact on the biosphere leads to the growing climate changes, variations in the structure of natural ecosystems, and impoverishment of biological diversity. The mechanisms for resolving this problem are much-needed. Scenarios of the transition to the stable use of natural resources can be developed on the basis of universal models of ecosystems. However, by now the concept of uniqueness of natural ecosystems has been formed. On the one hand, natural ecosystems are highly diverse; on the other hand, current research is aimed mainly at revelation of distinguishing features in their organization and not the common properties.  The lack of understanding of the organizational basis of ecosystems prevents constructing universal models of the latter that could be effectively integrated in biosphere models. The problem is complicated by the lack of powerful yet flexible mathematical methods that would reflect the fundamental properties of natural ecosystems that give rise to the observed diversity.

The aim of this work was to develop a systematic theoretical basis for universal description, analysis, and modeling of ecosystems as structural units of the biosphere as the highest-level ecosystem. Modeling is grounded on the developed concept of adaptive self-organization (CAS) of complex natural systems. The models are verified by an original field of domestic forest science named genetic forest typology.

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We considered the main problems of modern science and the ways of solving them. The existing problems led to the huge gap between mathematical and experimental (field) ecology. The current situation in science complicates the study of the biosphere and its ecosystems, because qualitative representations cannot span the extreme complexity of living systems without quantitative models.

Considering the possibilities of existing mathematical methods, we can hardly expect building of the universe theory for describing and modeling of ecosystems in the nearest future. A more realistic way is to develop new approaches to the description of specific ecological situations. Methods of mathematical physics transferred in biology and ecology cannot fully reflect complexity, flexibility, and polyvariance of living systems. Despite certain success attained in the description of biological subsystems and processes, accomplishments of biophysics (and biology) in studying general properties of living things, as was mentioned in (Bartsev, Bartseva, 2007),  have been rather spare. The authors of (Chaikovskii, 2008) said that if biology can be mathematisized, it requires its own mathematics.

The aim of this work was to demonstrate the main difficulties of traditional mathematical modeling of ecosystems, consider the ways of overcoming these difficulties using the concept of self-organization (CAS) of complex natural systems, and modify adaptive self-organization algorithms that ensure consistence of ecosystem processes in models of the biosphere and its ecosystems.
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