Environmental factors shaping ungulate abundances in Poland

Abstract

Population densities of large herbivores are determined by the diverse effects of density-dependent and independent environmental factors. In this study, we used the official 1998-2003 inventory data on ungulate numbers from 462 forest districts and 23 national parks across Poland to determine the roles of various environmental factors in shaping country-wide spatial patterns of ungulate abundances. Spatially explicit generalized additive mixed models showed that different sets of environmental variables explained 39 to 50 % of the variation in red deer Cervus elaphus, wild boar Sus scrofa, and roe deer Capreolus capreolus abundances. For all of the studied species, low forest cover and the mean January temperature were the most important factors limiting their numbers. Woodland cover above 40-50 % held the highest densities for these species. Wild boar and roe deer were more numerous in deciduous or mixed woodlands within a matrix of arable land. Furthermore, we found significant positive effects of marshes and water bodies on wild boar abundances. A juxtaposition of obtained results with ongoing environmental changes (global warming, increase in forest cover) may indicate future growth in ungulate distributions and numbers.

Keywords: Arable land; Forest cover; January temperature; Red deer; Roe deer; Wild boar.

Fig. 1

Distribution of sample areas (forest districts, national parks) and forests in Poland during 1999–2003

Fig. 2

Abundance indices of red deer, roe deer, and wild boar in forest districts (n = 439) and national parks (23) in Poland during 1999–2003

Fig. 3

Effects of environmental factors on red deer abundance indices in Poland: results of generalized additive mixed models (GAMMs). The distribution of explanatory variable values is marked with black vertical lines on the x-axis. The y-axis presents the partial residuals of the model after removing the effects of the other covariates. The slope of zero indicates a constant influence of the covariates on red deer abundance indices. Dashed lines correspond to 1 SE. Environmental factors: forest cover, January temperature, arable land, deciduous and mixed forest, marsh, and water

Fig. 4

Effects of environmental factors on roe deer abundance indices in Poland: results of generalized additive mixed models (GAMMs). The distribution of explanatory variable values is marked with black vertical lines on the x-axis. The y-axis presents the partial residuals of the model after removing the effects of the other covariates. The slope of zero indicates a constant influence of the covariates on roe deer abundance indices. Dashed lines correspond to 1 SE. Environmental factors: forest cover, January temperature, arable land, deciduous and mixed forest, marsh, and water

Fig. 5

Effects of environmental factors on wild boar abundance indices in Poland: results of generalized additive mixed models (GAMMs). The distribution of explanatory variable values is marked with black vertical lines on the x-axis. The y-axis presents the partial residuals of the model after removing the effects of the other covariates. The slope of zero indicates a constant influence of the covariates on wild boar abundance indices. Dashed lines correspond to 1 SE. Environmental factors: forest cover, January temperature, arable land, deciduous and mixed forest, marsh, and water