Modelling the functional connectivity of landscapes for greater horseshoe bats Rhinolophus ferrumequinum at a local scale

Context The importance of habitat connectivity for wildlife is widely recognised. However, assessing the movement of species tends to rely on radio-tracking or GPS evidence, which is difficult and costly to gather. Objectives To examine functional connectivity of greater horseshoe bats (GHS, Rhinolophus ferrumequinum ) at a local scale using Circuitscape software; comparing our results against expert opinion ‘fly ways’. Methods Expert opinions were used to rank and score five environmental layers influencing GHS movement, generating resistance scores. The slope and resistance scores of these layers were varied, and validated against independent ground truthed GHS activity data, until a unimodal peak in correlation was identified for each layer. The layers were combined into a multivariate model and re-evaluated. Radio-tracking studies were used to further validate the model, and the transferability was tested at other roost locations. Results Functional connectivity models could be created using bat activity data. Models had the ability to be transferred between roost locations, although site-specific validation is strongly recommended. For all other bat species recorded, markedly more (125%) bat passes occurred in the top quartile of functional connectivity compared to any of the lower three quartiles. Conclusion The model predictions identify areas of key conservation importance to habitat connectivity for GHS that are not recognised by expert opinion. By highlighting landscape features that act as barriers to movement, this approach can be used by decision-makers as a tool to inform local management strategies.