TABLE 1.
Landscape data used to create resistance surfaces
| Landscape variable | Source | Hypothesized relationship with gene flow |
|---|---|---|
| Continuous Low Traffic Areas | Federal Agency for Nature Conservation 2010 | + |
| Agricultural land | OpenStreetMap 2018 (land use = farmland) | + |
| Forest | Forest type, European Union, Copernicus Land Monitoring Service 2015 | + |
| Forest fragmentation index, proportion of forest edge | Forest type, European Union, Copernicus Land Monitoring Service 2015 | + |
| Forest fragmentation index, proportion of forest interior | Forest type, European Union, Copernicus Land Monitoring Service 2015 | + |
| Grassland | OpenStreetMap 2018 (land use = grass, greenfield, meadow) | + |
| Habitat suitability model | Klar et al. (2008) | + |
| Global Urban Footprint | German Aerospace Center 2016 | − |
| Railways | OpenStreetMap 2018 (land use = railway) | − |
| River | OpenStreetMap 2018 (waterway = river, canal) | − |
| Road | ESRI Germany, Federal Agency for Cartography and Geodesy; Open Data Portal 2015 | − |
| Settlement | OpenStreetMap 2018 (landuse = residential, industrial, retail) | − |
| Topographic slope | Digital elevation model, European Union, Copernicus Land Monitoring Service 2012 | − |
In the third column, a positive sign indicates a hypothesized positive effect of this variable on gene flow in wildcats (i.e., higher values of the variable lead to lower resistance), while a negative sign indicates that the variable was hypothesized to impede gene flow (i.e., higher values of the variable lead to higher resistance).