Abstract
ContextFunctional connectivity models are essential in identifying major dispersal pathways and developing effective management strategies for expanding populations of invasive alien species. However, the extrapolation of models parameterized within current invasive ranges may not be applicable even to neighbouring areas, if the models are not based on the expected responses of individuals to landscape structure.ObjectivesWe have developed a high-resolution connectivity model for both terrestrial and aquatic habitats using solely potential sources. The model is used here for the invasive, principally-aquatic, African clawed frog Xenopus laevis, which is a species of global concern.MethodsAll ponds were considered as suitable habitats for the African clawed frog. Resistance costs of lotic aquatic and terrestrial landscape features were determined through a combination of remote sensing and laboratory trials. Maximum cumulative resistance values were obtained via capture-mark-recapture surveys, and validation was performed using independently collected presence data. We applied this approach to an invasive population of the American bullfrog, Lithobates catesbeianus, in France to assess its transferability to other pond-dwelling species.ResultsThe model revealed areas of high and low functional connectivity. It primarily identified river networks as major dispersal pathways and pinpointed areas where local connectivity could be disrupted for management purposes.ConclusionOur model predicts how the dispersal of individuals connect suitable lentic habitats, through river networks and different land use types. The approach can be applied to species of conservation concern or interest in pond ecosystems and other wetlands, including aquatic insects, birds and mammals, for which distribution data are limited or challenging to collect. It serves as a valuable tool for forecasting colonization pathways in expanding populations of both native and invasive alien species and for identifying regions suitable for preventive or adaptive control measures.
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