Abstract

Due to the complexity of factors that influence species density on a large geographical scale, the effectiveness of the species distribution model (SDM) is still debatable. That is why the buffer zone (the area within 100 m from the outside edge of the patch), the core, i.e. (patches excluding the 100 m buffer zone from the patch’s edge) and patch shape are explored in this study to see how they affect the density of habitat specialist and generalist bird species. Two sets of generalised additive models were generated separately for each of the four bird species: One set of models contained landscape configuration metrics as an additional predictor variable, and the other did not. The results showed that models including the core, the buffer zone and the shape of patches turned out to be definitely better than models without them. Specialist species, the Corn bunting and the Wood nuthatch, are more likely to occur in the core of the preferred patches, and they choose those of a simple shape; while generalist species, the Whinchat and the Tree pipit, are more probable to be present in the buffer zone of a more complicated shape. Thus, the results clearly show that specific landscape configuration models can improve the predictive power of SDMs and can be used as an effective tool for predicting species density and functional bird diversity (specialist and generalist). Furthermore, from the applied ecology perspective, detailed landscape configuration metrics can be considered as a surrogate of elusive habitat conditions.

Highlights

  • Species distribution models (SDMs) are a group of multiple statistical tools that have been widely used to predict species occurrence, density and richness [1, 2]

  • When specific landscape metrics are not taken into account in the modelling approach as additional predictor variables, SDMs effectiveness may be decreased

  • Recent studies conducted on a small spatial scale showed that patterns of species distribution were the result of a complex interplay between environmental estimates and landscape heterogeneity and more detailed landscape configuration metrics, i.e. patch shape and the proportion between the core and the buffer zone of preferred habitats, which played an important role [9,10,11]

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Summary

Introduction

Species distribution models (SDMs) are a group of multiple statistical tools that have been widely used to predict species occurrence, density and richness [1, 2]. Recent studies conducted on a small spatial scale showed that patterns of species distribution were the result of a complex interplay between environmental estimates and landscape heterogeneity and more detailed landscape configuration metrics, i.e. patch shape and the proportion between the core and the buffer zone of preferred habitats, which played an important role [9,10,11]. This kind of data are rarely used in SDMs, especially in species density modelling [12,13,14]. The usual approach was extended so as to analyse factors shaping the distribution of four bird species, using topography, climate, vegetation and Kosicki J.Z

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