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Context Habitat suitability models (HSM) have been used to understand the impacts of landscape-scale habitat connectivity and gene flow mostly by assuming a regular decrease in the cost of movement as habitat improves. Yet, habitat selection and gene flow are governed by different behavioural processes which may limit the reliability of this approach as individuals are likely to disperse through unsuitable habitat for breeding. Objectives The aim of this study was to identify the optimal relationship between gene flow and HSMs for two bat species ( Myotis bechsteinii  and  Eptesicus serotinus ) in Britain by testing a range of nonlinear negative exponential functions for the transformation of HSMs into resistance surfaces. Methods We modelled habitat suitability using a hierarchical, multi-level approach that integrates models across three nested levels. Then, we measured the relationship between published genetics data of both species and six negative exponential transformations of the predicted outputs. Results The two most extreme transformations provided the best fit to genetic data for both  M. bechsteinii  (c = 32; R 2  = 0.87) and  E. serotinus  (c = 16; R 2  = 0.42). The negative linear transformations had the poorest fit. Conclusions These results suggest that bats are able to disperse through areas of poor habitat for breeding, but will avoid the most unsuitable areas. We recommend comparing multiple transformations of HSMs at different resolutions to gain a more accurate representation of gene flow across heterogeneous landscapes and to inform cost-effective, targeted management.

Characterising the relationship between suitable habitat and gene flow for Myotis bechsteinii and Eptesicus serotinus in Britain