Spotted owl habitat quality maps and disturbance attribution analysis

This dataset includes annual spatial maps of spotted owl nesting habitat quality in Southern California and an accompanying ArcPython script used to attribute negative annual habitat change to wildfire (Barry et al., 2025). In the annual spatial maps, the raster values range from 0 to 1, with higher values indicating higher habitat quality. All habitat rasters are masked to National Forest boundaries and exclude lakes and private lands. Users may derive annual gains or losses in habitat quality from these layers and apply the provided ArcPython workflow (nest_fire_zonal_stats.py) to attribute change to specific disturbance drivers. In our implementation, we calculated annual declines in nest habitat quality greater than five percent (Barry et al., 2025). The code provided includes an example using annual layers of wildfire burns, but users can substitute their own annual disturbance datasets and calculate their relative impact on habitat quality change. Additional details on the disturbance layers used in our example are provided in Kramer et al. (2025).References: Barry, J., Hart, R., Jones, G.M., Kramer, H.A., McGinn, K.A., Peery, M.Z. 2025. Dynamic wildlife habitat mapping and attribution analyses reveal that wildfire, not fuels management, drives declines in an old forest species. Forest Ecology and Management.Kramer, A., Ng, E.M.-Y, Winiarski, J.M., Koltunov, A., Slaton, M.R., Jones, G.M., Peery, M.Z. 2025. Mapping disturbance in California's rapidly changing National Forests. Forest Ecology and Management. Forest Ecology and Management.