Determining the invasibility of habitats by alien species is crucial for understanding their spread potential, the habitats the most at risk and to implement adequate management actions. This is urgent for introduced taxa that show high invasion potential across broad geographical scales. We here assess these processes in invasive Pelophylax water frogs which are widespread colonizers across Western Europe and for which the invasibility of habitats remains to be quantified. Specifically, we used hierarchical occupancy models in a Bayesian framework to identify local-and landscape-scale features that can enhance occupancy of the most common invasive water frog, the marsh frog (P. ridibundus), in southern France. Water frogs were highly detectable and showed high occupancy across the invaded landscape. The invaders expressed a very broad habitat tolerance for both local-and landscape-scale variables while their invasion was facilitated by the occurrence of deep, permanent ponds with abundant aquatic vegetation and high sun exposure. Cross-validation showed a good transferability of models across space. The high invasibility of a wide range of habitats by Pelophylax water frogs is alarming and unveils their invasiveness, contributing therefore to explain their success of invasion over broad geographic scales.

Identifying and tracking individuals across time are a prerequisite to uncover key traits of their ecology and behaviour. However, obtaining fine-grain individual data at multiple locations, especially in aquatic environments, is challenging due to trade-offs between time constraints and detection probabilities. Aquatic telemetry of passive integrated transponder (PIT)-tagged organisms has been proposed to cope with detectability issues, but its efficiency has not been tested in stagnant waters. This technology was evaluated in ponds by monitoring marsh frogs (Pelophylax ridibundus). Multivariate survival models were fitted to quantify the success of detection rates over detection times and across ponds characterized by different habitat features. An average detection rate of 81% was obtained in less than 18 minutes on average, whereas a maximum detection rate was achieved in almost a quarter of the surveys. The detection rates were lower in the deeper and larger ponds but increasing detection times improved detection probabilities. Altogether, these results show that PIT-tag telemetry is a powerful tool to survey aquatic organisms, such as pond-breeding amphibians. The generalization of the use of this monitoring technique in ponds can therefore encompass finegrain analyses over numerous sites and fill the gap between studies at local and landscape scales.