Helmholtz Centre for Environmental Research—UFZ, Permoserstr. 15, 04318 Leipzig, Germany
Forest and Landscape Structure as Predictors of Capercaillie Occurrence
Article first published online: 13 DEC 2010
2007 The Wildlife Society
The Journal of Wildlife Management
Volume 71, Issue 2, pages 356–365, April 2007
How to Cite
GRAF, R. F., BOLLMANN, K., BUGMANN, H. and SUTER, W. (2007), Forest and Landscape Structure as Predictors of Capercaillie Occurrence. The Journal of Wildlife Management, 71: 356–365. doi: 10.2193/2005-629
- Issue published online: 13 DEC 2010
- Article first published online: 13 DEC 2010
- forest grouse;
- habitat model;
- logistic regression;
- spatial scale;
- Tetrao urogallus.
ABSTRACT Capercaillie (Tetrao urogallus) is a large, endangered forest grouse species with narrow habitat preferences and large spatial requirements that make it susceptible to habitat changes at different spatial scales. Our aim was to evaluate the relative power of variables relating to forest versus landscape structure in predicting capercaillie occurrence at different spatial scales. We investigated capercaillie-habitat relationships at the scales of forest stand and forest-stand mosaic in 2 Swiss regions. We assessed forest structure from aerial photographs in 52 study plots each 5 km2. We classified plots into one of 3 categories denoting the observed local population trend (stable, declining, extinct), and we compared forest structure between categories. At the stand scale, we used presence-absence data for grid cells within the plots to build predictive habitat models based on logistic regression. At this scale, habitat models that included only variables relating to forest structure explained the occurrence of capercaillie only in part, whereas variables selected by the models differed between regions. Including variables relating to landscape features improved the models significantly. At the scale of stand mosaic, variables describing forest structure (e.g., mean canopy cover, proportion of open forest, and proportion of multistoried forest) differed between plot categories. We conclude that small-scale forest structure has limited power to predict capercaillie occurrence at the stand scale, but that it explains well at the scale of the stand mosaic. Including variables for landscape structure improves predictions at the forest-stand scale. Habitat models built with data from one region cannot be expected to predict the species occurrence in other regions well. Thus, multiscale approaches are necessary to better understand species-habitat relationships. Our results can help regional authorities and forest-management planners to identify areas where suitable habitat for capercaillie is not available in the required proportion and, thus, where management actions are needed to improve habitat suitability.