Habitat assessment for forest dwelling species using LiDAR remote sensing: capercaillie in the Alps.

Abstract Large-scale information on habitatsuitability is indispensable for planning management actions to further endangered specieswith large-spatial requirements. So far, remote sensing based habitatvariables mostly included environmental and land cover data derived from passive sensors, but lacked information on vegetation structure. This is a serious constraint for the management of endangered specieswith specific structural requirements. Light detection and ranging ( LiDAR), in contrast to passive remote sensing techniques, may bridge this gap in structural information at the landscape scale. We investigated the potential of LiDARdata to quantify habitatsuitability for capercaillie ( Tetrao urogallus), an endangered forest grousein Central Europe, in a forest reserve of 17.7 km 2 . We used continuous variables of horizontal and vertical stand structure from first and last pulse LiDARdata and presence–absence information from field work to model habitatsuitability with generalized linear models (GLM). The two final habitatsuitability models explained the observed presence–absence pattern moderately well (AUC of 0.71 and 0.77) with horizontal structure explaining better than vertical structure. Relative tree canopycover was the most important variable with intermediate values indicating highest habitatsuitability. As such, LiDARallowed us to translate the results from habitatmodeling at the landscape scale to effective management recommendations at the local scale at a level of detail that hitherto was unavailable for large areas. LiDARthus enabled us to integrate individual habitatpreferences at the scale of entire populations and thus offers great potential for effective habitatmonitoring and management of endangered species.