Development of a method to describe potential big mammal habitats

Abstract

The presented thesis introduces a methodological approach to identifying potential habitats of big mammals using available preference data, landscape metrics and statistical classification. The innovative element of the approach is the combination of a range of well-known analytical methods for this purpose. Objectives The general aim of using landscape metrics is to assess landscape permeability and landscape structure based on landscape patches; expressed as composition or configuration. The calculated quantitative measures serve to better understand the ecological processes related to different spatial levels (patch, class, landscape). Here landscape metrics originating from different spatial levels are applied to statistically model habitat suitability. Large mammals, particularly large herbivores, are characteristic species in landscapes and play a guiding role in ecosystems through their behaviour and interactions with other components of the ecosystem. In many studies on the occurrence of mammals, a modelling approach follows, where landscape metrics serve as predicting variables (RITTER 2008, BOYCE et al. 2003). Methods In the present thesis, the general approach to identifying preferred habitats with the help of landscape metrics is demonstrated with red deer preference data and biotope data of a landscape in Mecklenburg West-Pomerania. The preference data are derived from hunting statistics over a 5-year period and are interpreted as habitat suitability values. Forest distribution data are used to calculate landscape metrics. Local data are generalized to the landscape level using the moving window approach. Various statistical methods are used first to identify relevant landscape metrics (correlation analysis) and then to derive a binary classifier for preferred and less preferred habitats (logistic regression) in the target landscape. To find both effective and reasonable landscape metrics, it was necessary to assign the biological-ecological and structural requirements of the red deer to appropriate landscape metrics. The biological-ecological and structural requirements of red deer concerning their habitats were taken from a thorough review of the relevant literature. Results The whole approach is described in detail. Raw data, analytical and classification results are presented in tables and maps. In particular, the classification results are carefully discussed from the viewpoint of both the uncertainties in the reference data and the quality of the biotope (forest) data. Summary viii Conclusion The derived classifier is able to identify preferred red deer habitats in a significant qualitative manner. The quantitative accuracy could certainly be improved if biotope data were provided with greater explicitness. The presented approach can be analogously applied to other mammals if the relevant structural requirements and empirical habitat suitability data (e.g. home range, biotopes, food resources) are known.