Composition versus physiognomy of vegetation as predictors of bird assemblages: The role of lidar

Abstract

Whether diversity and composition of avian communities is determined primarily by responses of species to the floristic composition or to the structural characteristics of habitats has been an ongoing debate, at least since the publication of MacArthur and MacArthur (1961). This debate, however, has been hampered by two problems: 1) it is notoriously time consuming to measure the physiognomy of habitat, particularly in forests, and 2) rigorous statistical methods to predict the composition of bird assemblages from assemblages of plants have not been available. Here we use airborne laser scanning (lidar) to measure the habitat (vegetation) structure of a montane forest across large spatial extents with a very fine grain. Furthermore, we use predictive co-correspondence and canonical correspondence analyses to predict the composition of bird communities from the composition and structure of another community (i.e. plants). By using these new techniques, we show that the physiognomy of the vegetation is a significantly more powerful predictor of the composition of bird assemblages than plant species composition in the field and as well in the shrub/tree layer, both on a level of p < 0.001. Our results demonstrate that ecologists should consider remote sensing as a tool to improve the understanding of the variation of bird assemblages in space and time. Particularly in complex habitats, such as forests, lidar is a valuable and comparatively inexpensive tool to characterize the structure of the canopy even across large and rough terrain.