Modelling landscape connectivity for greater horseshoe bat using an empirical quantification of resistance

1. Habitat fragmentation and isolation as a result of human activities have been recognized as great threats to population viability. Evaluating landscape connectivity in order to identify and protect linkages has therefore become a key challenge in applied ecology and conservation. 2. One useful approach to evaluate connectivity is Least-Cost Path (LCP) analysis. However, several studies have highlighted importance of parameterization with empirical, biologically-relevant proxies of factors affecting movements, as well as the need to validate the LCP model with an independent dataset. 3. We used LCP analysis incorporating quantitative, empirical data about behaviour of the greater horseshoe bat Rhinolophus ferrumequinum to build up a model of functional connectivity in relation to landscape connecting features. We then validated the accumulated costs surface from the LCP model with two independent datasets; one at an individual level with radio tracking data and one at a population level with acoustic data. 4. When defining resistance, we found that the probability of bat presence in a hedgerow is higher when the distance between hedgerows is below 38 m, and decrease rapidly when gaps are larger than 50 m. The LCP model was validated by both datasets: the independent acoustic data showed that the probability of bat presence was significantly higher in areas with lower accumulated costs, and the radio tracking data showed that foraging was more likely in areas where accumulated costs were significantly lower. Synthesis and applications. Through our modelling approach, we recommend a maximum of 38m (and no more than 50m) between connecting features around colonies of greater horseshoe bats. Our quantitative study highlights the value of this framework for conservation: results are directly applicable in the field and the framework can be applied to other species sensitive to habitat loss, including other bats. Provided that it is parameterized with empirical, biologically-relevant data, this modelling approach can be used for restoring and evaluating green networks in agri-environmental schemes and management plans.20-Jun-2018