Species richness of bats (Chiroptera) along lakeshore habitats in western South Carolina
The conservation of bats has been a topic of increasing interest over the last decade due to drastic population declines. The introduction of white-nose syndrome in the northeastern United States, landscape modification, and interactions with wind turbines have all contributed to these declines. Devising management plans that are efficient at protecting bat populations is difficult because little is known about the critical habitat on which individual species rely. In this study we examine the habitat and climate factors that influence species richness in bats across a variety of lakeshore habitats. Two acoustical sampling techniques were used to identify bat composition at 32 sites on Lake Keowee and Lake Jocassee, in northwestern South Carolina. These presence/absence data were used in a null-model analysis program, Ecosim, to determine the co-occurrence of observed species. We determined the variables that influence species richness in the region using multiple regression analyses, and calculated the change in species composition between sites using the Jaccard dissimilarity index. Finally, multivariable logistic models were used to identify the habitat and climate variables that predicted the presence or absence of individual species.
Overall, nine species of bats were documented in the region, with four of the nine species classified as rare. Species richness values ranged from three to eight across both lakes and mean species richness was not significantly different between the two lakes. Ecosim analyses on all species indicate that they are randomly distributed among sites. However, a separate Ecosim analysis on the rare species suggests that they are habitat specialists and require specific environmental and climatic variables to be present. Species richness among all bats was positively correlated to the amount of water, evergreen forest, and slope within the region, but negatively correlated to the amount of urban development. The Jaccard dissimilarity index showed two changes in species composition, with the changes corresponding to habitat shifts from upland piedmont habitats to mountainous, steep-sloping mesic habitats. These data suggest that species richness is highest in the rural mountainous regions of the state, which corresponds to the habitat in which the rare species were observed. No multivariable model exhibited strong support for predicting the presence of any species in the region, but these models combined with the species richness analyses provide insight into which variables maybe critical for sustaining rare species.