Ecological potentials of biodiversity modelled from information entropies: Plant species diversity of North-Central European forests as an example

The paper deals with the hypothesis that ecosystems have well-defined potentials of biodiversity. These potentials can be quantified as information entropy of the corresponding ecosystem type. The hypothesis is verified for the diversity of plant species.

A vegetation database of North-Central European forests containing more than 12000 relevés is analyzed computationally. The samples are classified into ecosystem types that are homogeneous with respect to vegetation patterns, ecological site factors, and, implicitly, with respect to ecosystem processes. Growing numbers of relevés are selected randomly from the representatives of different ecosystem types and investigated mathematically.

Shannon information (product of logarithmic species number and evenness) obeys a hyperbolic saturation equation approaching a finite value on infinite area. This asymptotic limit defines the ecological potential of species diversity. Within a given plant-geographical region, it is determined by ecological site factors like climate and soil controlling interrelations between plants. Competition relationships and hence potentials of phytodiversity are altered by management significantly. The curve of evenness versus area size is hump-shaped. Maximum evenness is proportional to the ecological potential of species diversity. The area size where evenness attains its maximum can be interpreted as the minimum area of the respective forest type. The ecological potentials of plant species diversity modelled from information entropies correspond to vegetation patterns consisting of a limited number of plant species. These vegetation patterns are closely related to ecosystem processes like nutrient cycling, plant nutrition, evapotranspiration, microbial processes, or net-primary production. Revealing the relationships between vegetation patterns and ecosystem processes allows scaling functional information from local measurement scales up to regional scales.

It is suggested to explore genetic, proteomic, and species data in order to derive comprehensive ecological potentials of biodiversity on various levels from population to landscape. The expected results could improve the understanding of the relationship between biodiversity and ecosystem functioning as well as the sustainability of ecosystem management.