Habitat availability is insufficient to explain regional variations in white stork breeding habitat preference

Understanding species–habitat associations is key for making predictions of species distributions of relevance to ecology and conservation. Regional differences in species habitat preferences can hinder the transferability of habitat models in space and time, but our ability to account for these differences will depend on the mechanisms underlying them (differences in habitat availability, genetics, culture). Here, we modelled the large‐scale breeding distribution of an expanding species, the white stork Ciconia ciconia in France, applying machine‐learning algorithms to an extensive dataset of the distribution of nests spanning the whole country. Specifically, we assessed the transferability of the models across different geographic zones and contrasted the modelled nesting habitat preferences of the species across these zones. Finally, we assessed whether local differences in model transferability were related to habitat availability in each zone. Our models generally had good calibration performances, but were not equally transferable to all zones. Additionally, environmental variables did not have the same effects in the different zones, with particularly striking differences between Alsace and the rest of France. This included a certain preference for urban areas in Alsace – absent from other zones ‐ that was consistent with their tendency to nesting on buildings in that zone. Differences in habitat availability between Alsace and the rest of France, as well as connectivity within the French white stork metapopulation appeared to be insufficient to explain the lack of transferability of models to this zone, suggesting some possible local historical and cultural effects on habitat selection.