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An approach to evaluating ecological status of populations in forest-nesting birds (Passeriformes and Piciformes)
Authors:S. E. Cherenkov
Affiliation:1.Severtsov Institute of Ecology and Evolution,Russian Academy of Sciences,Moscow,Russia
Abstract:A 13-year study of forest-nesting birds (orders Passeriformes and Piciformes) has been conducted at five constant census areas in European Russia, Caucasus, and the mountains of Southern Siberia. The nesting individuals are mapped at each census area for two or more nesting periods. The nesting densities for each species are estimated. Raster maps of spatial allocation (MSA) at the scale of the raster grid of 50 × 50 m are obtained for each species. The degree of spatial conservatism (DSC) for each local population is inferred from the pairwise comparisons of the specific MSAs obtained at the same area in different years with the use of the Gamma rank correlation method. This index characterizes the connection of population with the habitat. Based on 5-year observations at that particular census area, the areas of habitats are estimated (Y) and mean DSC values (X) are obtained for all 18 model species. Using the regression model (Y = 117–103.5X; R = 0.84; p < 0.01), it is demonstrated that, under conditions of almost complete saturation, when a population uses almost the entire area of available habitats and maximum carrying capacity of habitat is almost achieved, the total area occupied by the individual nesting home ranges of the particular species is in an inverse linear relationship with the DSC estimates. Based on this model, it is possible to calculate the maximum carrying capacity of habitat for each species from its DSC value. Maximum nesting density for each species at a particular census area is calculated based on its DSC values and mean size of its nesting home range. The ratio between observed and maximum nesting densities allows estimating the degree of saturation of carrying capacity of habitat and the population status of a particular species under different environmental conditions.
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