Estimating density of a forest-dwelling bat: a predictive model for Rafinesque's big-eared bat
Data on species distribution and abundance are the foundation of population ecology. However, due to difficulties in surveying bats, abundance estimates for tree-roosting microchiropterans are non-existent. Therefore, our objective was to develop methods for estimating colony abundance and density, taking as our model Rafinesque's big-eared bat Corynorhinus rafinesquii, a species of conservation concern found in cypress-gum swamps of the southeastern United States. We searched 123 transects at eight study sites in the Coastal Plain of Georgia, USA to locate and characterize diurnal summer roosts of C. rafinesquii. We modeled the relationship between the number of bat colonies and landscape-scale habitat variables with zero-inflated negative binomial regression and used Akaike's information criterion to select the most parsimonious models. We generated a predictive density map to identify areas of high colony density and to estimate overall abundance. Colony density was predicted by the duration of wetland flooding, wetland width, and study site. Application of the regression model to a GIS indicated there were 3,734 colonies containing 6,910 adult bats on the eight study sites. Predicted density ranged from 0.07 colonies/ha and 0.07 adult bats/ha in saturated wetlands to 0.47 colonies/ha and 1.18 adult bats/ha in semi-permanently flooded wetlands. This study is the first to estimate density and abundance of forest-dwelling microchiropterans over a large area. Such data can serve as a baseline for future work on population trends in C. rafinesquii. In addition, our approach could be replicated for other bat species with moderately cryptic roosts.