Small-scale habitat use of black grouse (Tetrao tetrix L.) and rock ptarmigan (Lagopus muta helvetica Thienemann) in the Austrian Alps

We investigated the small-scale habitat use of two grouse species, black grouse (Tetrao tetrix L.) and rock ptarmigan (Lagopus muta helvetica Thienemann) in a study area in the Austrian Central Alps in summer. To build habitat suitability models, we applied multiple logistic regression using presence–absence data from fieldwork as the response variable and a set of habitat characteristics as explanatory variables, respectively. To gain a better understanding of the mechanisms that drive habitat selection, we tested for two-way interaction terms before excluding any variables from the initial variable set. Four explanatory variables significantly contributed to the black grouse model: dwarf shrub cover, dwarf shrub height, patchiness and ant hills. The final model for rock ptarmigan contained three explanatory variables: dwarf shrub cover, rock cover and dwarf shrub height. Most notably, the interaction terms dwarf shrub cover×patchiness in the black grouse model and dwarf shrub cover×dwarf shrub height, rock cover×dwarf shrub height in the rock ptarmigan model point out trade-off mechanisms between food, cover and overview providing features. Thus, our models do not only identify the parameters that mainly drive habitat selection, but also deepen our understanding about the causal relationships between these factors. Therefore, the information gained in this study allows for a deduction of appropriate habitat management strategies and supports conservation efforts of local stakeholders

Searching the right tie—Expert-based vs. statistical niche modeling for habitat management at the alpine treeline ecotone

Understanding of wildlife-habitat relationships is a fundamental issue in conservation ecology allowing for the formulation of specific management demands. As habitats of various species are shifting and contracting in the course of global change, ecological niche models (ENMs) have to provide more than distributional maps. Rather, applicability of models for practitioners, conservationists and land managers should be prioritized, providing guidelines for management decisions. We developed correlative ENMs (cENMs, logistic regression) for alpine Black grouse (Tetrao tetrix L.) for five different study areas in Austria. We further propose one expert-based ENM (xENM) and a new hybrid approach (xcENM). We validated the models with independent test data sets and compared them in terms of discriminatory power, calibration, and parsimony. The xcENM reached an intermediate position between cENMs and xENM in terms of accuracy and calibration power. The cENM for the entire data pool had the best performance of all approaches in terms of accuracy, but showed a weaker transferability and a lower parsimony than the xENM. All models highlighted the importance of well-structured habitats for Black grouse, providing resources for feeding, resting, and rearing chicks. We further show the importance of habitat patches without anthropogenic disturbances for habitat suitability and provide recommendations for habitat management and habitat creation