Climate change and habitat loss are recognized as important drivers of shifts in wildlife species' geographic distributions. While often considered independently, there is considerable overlap between these drivers, and understanding how they contribute to range shifts can predict future species assemblages and inform effective management. Our objective was to evaluate the impacts of habitat, climatic, and anthropogenic effects on the distributions of climate‐sensitive vertebrates along a southern range boundary in Northern Michigan, USA. We combined multiple sources of occurrence data, including harvest and citizen‐science data, then used hierarchical Bayesian spatial models to determine habitat and climatic associations for four climate‐sensitive vertebrate species (American marten [Martes americana], snowshoe hare [Lepus americanus], ruffed grouse [Bonasa umbellus], and moose [Alces alces]). We used total basal area of at‐risk forest types to represent habitat, and temperature and winter habitat indices to represent climate. Marten associated with upland spruce‐fir and lowland riparian forest types, hares with lowland conifer and aspen‐birch, grouse with lowland riparian hardwoods, and moose with upland spruce‐fir. Species differed in climatic drivers with hares positively associated with cooler annual temperatures, moose with cooler summer temperatures, and grouse with colder winter temperatures. Contrary to expectations, temperature variables outperformed winter habitat indices. Model performance varied greatly among species, as did predicted distributions along the southern edge of the Northwoods region. As multiple species were associated with lowland riparian and upland spruce‐fir habitats, these results provide potential for efficient prioritization of habitat management. Both direct and indirect effects from climate change are likely to impact the distribution of climate‐sensitive species in the future and the use of multiple data types and sources in the modelling of species distributions can result in more accurate predictions resulting in improved management at policy‐relevant scales.

This data comprises 3 .csv files, containing spatial locations for moose, American marten, and snowshoe hare (*Note that location data for ruffed grouse was entirely composed of eBird data, which is publically available elsewhere (eBird Basic Dataset). Hence no .csv file is included here). 
. Data has been compiled from various sources (as indicated in files) and identifying information has been removed. 

• Column 1: Name = "ID" An integer type unique identifier for each row of the data. 
• Column 2: Name = "Spp" A character type label indicating the species name.
• Column 3: Name = "OBS" An integer type value of 1 (one) or 0 (zero) indicating presence (1) or absence (0).  
• Column 4: Name = "Year" An integer type value indicating the year of data collection (i.e., "1997", "2017", etc.).
• Column 5: Name = "Long" The longitude as an unprojected geographic coordinate of the location (decimal).   
• Column 6: Name = "Lat" The latitude as an unprojected geographic coordinate of the location (decimal).
• Column 7: Name = "Source" A character type label indicating the person/organization providing the data.  

R code is available on Zenodo at https://doi.org/10.5281/zenodo.7908523