Understanding the summer roosting habitat selection of the greater mouse-tailed bat (Rhinopoma microphyllum) and the small mouse-tailed bat (Rhinopoma muscatellum) in Iran

Abstract

Roost for bats, which are responsible for a wide range of vital ecological and economic services, is crucial. Their availability affects both the geographic occurrence and the diversity of bat communities. Hence, understanding how bats use roosts and variables that influence these patterns could contribute to the development of management plans to ensure their survival. In this study, species distribution modeling of two bat species, the greater mouse-tailed bat (Rhinopoma microphyllum) and the small mouse-tailed bat (Rhinopoma muscatellum), were carried out using the sdm package in R. To do so, 16 environmental variables were used as the predictors to explore their relationships with the occurrence of the two species using 12 modeling algorithms. The prediction models for each species were then combined into an ensemble model. The random forest modeling algorithm showed better performance than the other individual models in this modeling. Moreover, the prediction performance of the ensemble model was more substantial than all the individual models for both species. For the greater mouse-tailed bat, elevation, annual mean temperature, temperature seasonality, and distance to roads-railways were identified as the essential variables for summer roosting habitat selection. Meanwhile, distance to roads-railways, annual mean temperature, elevation, and distance to the ridge were significant for the small mouse-tailed bat. Since this study facilitates the management of future and suitable habitats by identifying important environmental conditions, it can be used in conservation plans.