Land use and climate alter species distributions worldwide, and detecting and understanding how species ranges shift can facilitate conservation planning and action. Following extirpation from most of the contiguous USA, gray wolves (Canis lupus) have partially recolonized former range in the western Great Lakes region, but it is unknown how land use and climate change may alter amounts of wolf habitat. Using wolf observation data collected during winters 2017–2020 in Minnesota, Wisconsin, and Michigan, we created ensemble models to predict how land use and climate change may affect the amount of wolf habitat within these states. A projection model for the western Great Lakes region suggested three of four scenarios of land use and climate change will lead to 9–35% increases in wolf habitat, while a solely climate-based projection model supported our expectation that changes in climate, in isolation, will have limited effect on current wolf range. Our results support stable or increasing amounts of wolf habitat in the western Great Lakes region during the 21st century, suggesting limited or no adverse effects on the current distribution or further recolonization of wolves. Our findings can inform policy development regarding wolf conservation, and identify areas where recolonization is plausible, thus where promoting human-wolf co-existence is most pertinent.

The files '01_process_landuse_data.R' and '02_fit_landuse_model.R', along with supporting code in 'plot_functions.R', can be used to run the land use model in the paper. Data for this analysis includes wolf presence coordinates (at 0.25-degree resolution) for Michigan and Minnesota in the file 'wolf_presence_coordinates.csv'. Raw species presence data are not publicly available as the subject species (Gray wolf) is federally protected under the Endangered Species Act, and subject to poaching within the study area. Data for Wisconsin cannot be made publicly available due to legal restrictions, but data can be obtained by qualified researchers through the Wisconsin Department of Natural Resources (david.macfarland@wisconsin.gov). See the R files for information on how to download the LUH2 data. The file '03_fit_climate_model.R' fits the climate model and uses the historic wolf range shapefile found in the 'wolf_historic_range' folder. See the R file for information on how to download the corresponding climate data.

All software required to run the code is open source and freely available. Running the models requires the R statistical software, along with libraries 'biomod2', 'dismo', 'dplyr', 'ggplot2', 'maps', 'ncdf4', 'raster', 'RStoolbox', 'sf', and 'tidyr'.