High‐resolution habitat modeling with airborne LiDAR for red tree voles

Habitat suitability maps are important tools for conservation planning and species investigations, but maps at resolutions that are biologically meaningful and useful for local‐level decision‐making are lacking for many species that use resources at fine scales. Airborne light detection and ranging (LiDAR) describes 3‐dimensional structure of forests and other habitats at high resolution, which can improve habitat models for many species and facilitate investigations otherwise impossible with field data or other remote‐sensing techniques. We used an information‐theoretic approach and logistic regression to model habitat of red tree voles ( Arborimus longicaudus ) at multiple spatial scales with predictors derived from airborne LiDAR in southwestern Oregon. We developed a priori models to evaluate habitat associations and identify good models useful for high‐resolution mapping of habitat suitability across a large spatial extent. Our best models that compared habitats around nest trees of red tree voles to available sites performed well (i.e., accuracy = 0.83) on an independent test data set. We found fair performance in comparisons of habitat around nest trees to unused locations within areas previously identified as red tree vole habitat (i.e., accuracy = 0.71). Red tree vole nests were often in the largest trees in the stand and away from forest edges. Both analyses suggested that fine‐ and broad‐scale predictors are important for modeling habitat of red tree voles. Habitat suitability for red tree voles should be predicted effectively by LiDAR acquisitions even with low point densities because maps were robust to reductions in point densities as low as 1 point/m 2 . We found that LiDAR was effective for modeling habitat of red tree voles and expect it to improve performance of models for other species with similar habitat requirements. © 2016 The Wildlife Society.