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 calibrat..., , , # Habitat availability is insufficient to explain regional variations in white stork breeding habitat preference

Dataset DOI: [10.5061/dryad.fxpnvx148](10.5061/dryad.fxpnvx148)

## Description of the data and file structure

The aim of the study was to model the nesting distribution of white storks in France. Nest location data were collected nationwide and combined with land use data, using species distribution models to infer nesting habitat preferences across different regions of France.

### Files and variables

#### File: data.zip

**Description:** This folder contains a table and two shapefiles:

* final_dataset_nest_locs.csv: locations of white stork nests;
* locs_buffer_with_vars.gpkg: nest locations with associated extracted environmental variables;
* grid_buffer_with_vars.gpkg: extracted environmental variables across a 1km x 1km grid covering France;

**Column names:**

* *annee*: year of census;
* *departement*: department of census;
* *support_clean*: support categories (f...,