How many wolves (Canis lupus) fit into Germany? The role of assumptions in predictive rule-based habitat models for habitat generalists.

Dominik Fechter,Ilse Storch,Cédric Sueur

doi:10.1371/journal.pone.0101798

Abstract

Due to legislative protection, many species, including large carnivores, are currently recolonizing Europe. To address the impending human-wildlife conflicts in advance, predictive habitat models can be used to determine potentially suitable habitat and areas likely to be recolonized. As field data are often limited, quantitative rule based models or the extrapolation of results from other studies are often the techniques of choice. Using the wolf (Canis lupus) in Germany as a model for habitat generalists, we developed a habitat model based on the location and extent of twelve existing wolf home ranges in Eastern Germany, current knowledge on wolf biology, different habitat modeling techniques and various input data to analyze ten different input parameter sets and address the following questions: (1) How do a priori assumptions and different input data or habitat modeling techniques affect the abundance and distribution of potentially suitable wolf habitat and the number of wolf packs in Germany? (2) In a synthesis across input parameter sets, what areas are predicted to be most suitable? (3) Are existing wolf pack home ranges in Eastern Germany consistent with current knowledge on wolf biology and habitat relationships? Our results indicate that depending on which assumptions on habitat relationships are applied in the model and which modeling techniques are chosen, the amount of potentially suitable habitat estimated varies greatly. Depending on a priori assumptions, Germany could accommodate between 154 and 1769 wolf packs. The locations of the existing wolf pack home ranges in Eastern Germany indicate that wolves are able to adapt to areas densely populated by humans, but are limited to areas with low road densities. Our analysis suggests that predictive habitat maps in general, should be interpreted with caution and illustrates the risk for habitat modelers to concentrate on only one selection of habitat factors or modeling technique.

Highlights

Large carnivores are currently recolonizing much of Europe [1], [2], [3]
Despite the fact that extrapolating results from different study areas or making general assumptions on wildlife-habitat relationships can lead to erroneous estimations on potentially suitable habitat [6], [14], [15], [16], these methods have been applied for a variety of species worldwide, including large carnivores (Wolf (Canis lupus): [17]
All model input parameter sets were in accordance, that the most potentially suitable habitat is located in the east and north-east of Germany, areas with similar characteristics as the Lausitz

Summary

Introduction

Large carnivores are currently recolonizing much of Europe [1], [2], [3] Due to their large spatial requirements and that they compete for game and poach livestock, this recolonization comes with a high potential for human-wildlife conflicts [4]. To address these potential conflicts in advance, managers often use predictive habitat models to determine the amount and distribution of potentially suitable habitat and areas likely to be recolonized (for a review on different modeling techniques see [5], [6]). In Spain wolves frequently use agricultural fields [29], while in Italy and Romania wolves use shrub land and garbage dumps [23], [30], [31]

Methods

Results

Discussion

Conclusion