Quantifying uncertainty in inferences of landscape genetic resistance due to choice of individual‐based genetic distance metric

Estimates of gene flow resulting from landscape resistance inferences frequently inform conservation management decision-making processes. Therefore, results must be robust across approaches and reflect real-world gene flow instead of methodological artefacts. Here, we tested the impact of 32 individual-based genetic distance metrics on the robustness and accuracy of landscape resistance modelling results. We analysed three empirical microsatellite datasets and 36 simulated datasets that varied in landscape resistance and genetic spatial autocorrelation. We used ResistanceGA to generate optimised multi-feature resistance surfaces for each of these datasets using 32 different genetic distance metrics. Results of the empirical dataset demonstrated that the choice of genetic distance metric can have strong impacts on inferred optimised resistance surfaces. Simulations showed accurate parametrisation of resistance surfaces across most genetic distance metrics only when a small number of environmental features was impacting gene flow. Landscape scenarios with many features impacting gene flow led to a generally poor recovery of true resistance surfaces. Simulation results also emphasise that choosing a genetic distance metric should not be based on marginal R2-based model fit. Until more robust methods are available, resistance surfaces can be optimised with different genetic distance metrics and the convergence of results needs to be assessed via pairwise matrix correlations. Based on the results presented here, high correlation coefficients across different genetic distance categories likely indicate accurate inference of true landscape resistance. Most importantly, empirical results should be interpreted with great caution, especially when they appear counter-intuitive in light of the ecology of a species

Conservation by trans-border cooperation: population genetic structure and diversity of geoffroy’s bat (Myotis emarginatus) at its north-western european range edge

In the European Union, all bat species are strictly protected and member states must ensure their conservation. However, if populations are genetically structured, conservation units that correspond to whole countries may be too large, putting small populations with specific conservation requirements at risk. Geoffroy’s bat (Myotis emarginatus) has undergone well-documented declines at its north-western European range edge between the 1960 and 1990s and is considered to be negatively affected by habitat fragmentation. Here we analysed the species’ genetic population structure and diversity to identify subpopulations with reduced genetic diversity and to scientifically inform conservation management. We generated 811 microsatellite-based genetic profiles obtained from 42 European nursery colonies and analysed a total of 932 sequences of the hypervariable region II of the mitochondrial control region sampled from across Europe. While two geographically widespread genetic populations were inferred to be present in north-western Europe, both nuclear and mitochondrial genetic diversity were lowest in the areas that had experienced a decline during the last century. A microsatellite-based analysis of demographic history did not permit, however, to unequivocally link that reduced genetic diversity to the population contraction event. Given the large geographic extent of the genetic populations, preserving the connectivity of mating sites requires concerted conservation efforts across multiple political jurisdictions. Genetic monitoring ought to be done on a regular basis to ensure that large-scale connectivity is maintained and further loss of genetic diversity is prevented