Imperiled Mammals (Southeast Blueprint Indicator)

Reason for Selection Mammals play key roles in maintaining ecosystem integrity, forest health, productivity, pollination, and other ecosystem services within the Southeast (Trani et al. 2007). As a taxonomic group, mammals are highly diverse, spanning a broad range of sizes, physiologies, life histories, and behaviors. They inhabit a wide array of ecosystems and habitats throughout the region, and some mammal species—such as white-tailed deer (Odocoileus virginianus)—are deeply rooted in the region’s cultural heritage. The species used in this indicator come from the Southeast animal Regional Species of Greatest Conservation Need (RSGCN) list. For their Wildlife Action Plans, each state and territorial fish and wildlife agency identifies a list of species most in need of conservation action, known as Species of Greatest Conservation Need (SGCN). Using the SGCN lists developed for the 2015 Wildlife Action Plans, the Southeast Association of Fish and Wildlife Agencies’ (SEAFWA) Wildlife Diversity Committee (WDC) created the RSGCN list to identify regional priority species. The Southeast animal RSGCN list includes 960 species representing amphibians, birds, bumblebees, fish, invertebrates (crayfish and mussels), mammals, and reptiles. In addition, the SEAFWA WDC ranked each species by degree of conservation concern (very high, high, or moderate concern). This indicator identifies potential habitat for 58 out of 60 mammal species and subspecies on the RSGCN list. While all RSGCN warrant consideration, this indicator emphasizes places that support potential habitat for range-restricted species and narrow endemics that only occur in very small and often singular places, making them more vulnerable to extinction. For example, the Buxton Woods white-footed deermouse (Peromyscus leucopus buxtoni) only occurs on the southern end of Hatteras Island in North Carolina (Shipp-Pennock et al. 2005). In contrast, the Northern long-eared bat (Myotis septentrionalis) has a much broader range and is found in 13 states within the Southeast region. To highlight the most important places for range-restricted species, we used a measure called “rarity-weighted richness” that measures the importance of each place to the species that occur there (IUCN 2025). With this approach, a place important for just one particularly rare species may score more highly than another place where multiple common species occur. Rarity-weighted richness is complementary to species richness, which measures the total number of species that occur in a given location. Input Data * [2021 National Land Cover Database] (NLCD): Land cover * Elevation-based mask used to separate the marine environment from terrestrial areas: available in the [Southeast Blueprint 2025 Ancillary Data Download]; see Appendix II of [the Southeast Blueprint 2025 Development Process] for details on how this layer was developed * [USGS Global Islands data] based on 2024 Landsat imagery, released 03-01-2023 * [Southeast Blueprint 2025 extent] * U.S. Geological Survey (USGS) [Southeast Gap Analysis Project] (GAP) species distribution models for mammal RSGCN, provided by Dr. Steve Williams on March 18, 2025 (available on request by emailing [sgwillia@ncsu.edu] or Nathan Tarr at [nathan_tarr@ncsu.edu]) The Southeast Gap Analysis Project (SE-GAP) is part of the National GAP, which is sponsored by the USGS. “Gap analysis” is the science of examining how well we are protecting common plants and animals (USGS 2025). Using known species ranges and habitat relationships, SE-GAP models the distributions of terrestrial vertebrate species that breed in the Southeast or use habitat there for an important part of their life history. The original SE-GAP models used 2001 landcover, and they have recently been updated to 2016 landcover. This indicator uses the latest SE-GAP models (65 species-habitat models) for 58 mammal species and subspecies on the RSGCN list out of 60 mammal RSGCN identified (does not include marine mammals). A full list of all species included appears in the Full Species List section of this indicator’s chapter in the [Blueprint Development Process]. Mapping Steps * Using island name (“Name_USGSO”), extract boundaries for Cape Hatteras (“Hatteras”), Sanibel (“Sanibel”), and Captiva (“North Captiva”) Islands from the USGS island boundary data for big islands (“USGSEsriWCMC_GlobalIslandsv2_BigIslands”). * Limit the potential habitat for hispid cotton rat in the GAP data to only the subspecies range for insular hispid cotton rat using boundaries for Sanibel and Captiva Islands, since only this subspecies is an RSGCN. Subtract the potential habitat value of 1 from the mammal richness layer for all hispid cotton rat potential habitat outside the subspecies’ smaller range. * Limit the potential habitat for white-footed deer mouse to only the subspecies range for the Buxton white-footed deer mouse using boundaries for Cape Hatteras Island, since only this subspecies is an RSGCN. Subtract the potential habitat value of 1 from the mammal richness layer for all white-footed deer mouse potential habitat outside the subspecies’ smaller range. * Estimate rarity-weighted richness. This means the smaller the area of potential habitat for the species, the higher the weight. Conceptually, to determine the weight for a particular species, we look at the proportion of all the potential habitat for a species that’s represented by a single 30 m pixel. However, there are species with very large ranges and some with very small ranges, which gives ArcGIS a hard time. So, we tweak the general idea of just calculating 1 pixel/(number of pixels of potential habitat). To deal with large areas of potential habitat, we use 10,000/(number of pixels of potential habitat). If we just use 1, some of the resulting decimals are so small that ArcGIS just rounds them down to zero. To deal with species with very small ranges, we set the maximum weighted value of a species to 1. As a final step, we sum the weights for all species to get the total rarity-weighted richness for a given pixel. * Use the elevation-based mask raster to remove marine areas from the rarity-weighted richness layer by assigning them a value of NoData. * Reclassify the NLCD to create a developed areas mask. Assign all developed classes a value of 0, and all other classes a value of 1. Developed classes include “Developed, Open Space”, “Developed, Low Intensity”, “Developed, Medium Intensity”, and “Developed, High Intensity”. * To remove developed areas, multiply the mammal rarity-weighted richness layer (with marine areas removed) by the developed mask. While there may be a limited amount of potential habitat for some species in the lower intensity urban classes, GAP tends to greatly overpredict potential habitat for species in urban areas. * Reclassify the resulting raster into the indicator classes seen below. * As a final step, clip to the spatial extent of Southeast Blueprint 2025. Note: For more details on the mapping steps, code used to create this layer is available [in the Southeast Blueprint 2025 Data Download] under > 6_Code. Final indicator values Indicator values are assigned as follows: 5 = Highest importance for range-restricted species (top 5% of larger analysis area) 4 = Very high importance for range-restricted species (upper 5-10% of larger analysis area) 3 = High importance for range-restricted species (upper 10-20% of larger analysis area) 2 = Medium importance for range-restricted species (above average in larger analysis area) 1 = Low importance for range-restricted species (below average in larger analysis area) 0 = Developed landcover or no potential habitat Known Issues * Misclassification and the older age of the GAP data (which is based on 2016 LANDFIRE landcover) results in some potential habitat being underestimated in restoration areas that were previously row crop (e.g., large areas of Catahoula National Wildlife Refuge in LA). * The GAP data does not include models for two mammals on the RSGCN list: Louisiana black bear (Ursus americanus luteolus) and Sherman’s short-tailed shrew (Blarina shermani). * GAP provides [the following disclaimer] for their predicted habitat maps: “While the actual distributions of many species are likely to be habitat limited, suitable habitat will not always be occupied because of population dynamics and species interactions. Furthermore, these maps correspond to midscale characterizations of landscapes, but individual animals may deem areas to be unsuitable because of presence or absence of fine-scale features and characteristics that are not represented in our models (e.g. snags, vernal pools, shrubby undergrowth).” * GAP data generally overpredicts potential habitat, especially for RSGCN subspecies with limited ranges. To address this issue, we constrained certain species’ ranges to better represent potential habitat for the subspecies, like the subspecies of the hispid cotton rat, which only occurs on Sanibel and Captiva Islands off the coast of Florida. There may be some species-habitat models for which we did not reduce ranges appropriately, and we will work to improve this in future updates. * GAP species-habitat distribution maps predict suitable landcover and environmental conditions for individual species based on their ranges and life history requirements. This data tends to overpredict habitat and cannot always separate development from potential habitat. Also, the 2016 landcover used to inform these data does not reflect the most current conditions. We attempted to address these issues by removing more current developed landcover from the predicted habitat, but there is room for further improvement in this approach. GAP is also currently working on updating these species-habitat models based on more recent landcover data, and we will incorporate this newer data in future revisions. * The depiction of potential habitat for Florida bonneted bat over southern Lake Okeechobee is very coarse and both over- and underestimates important habitat in that area. This is the reason for the coarse polygon of high indicator value over Southern Lake Okeechobee. This polygon misses some important habitat but also tends to overvalue habitat with it. * Because this indicator is intended to represent terrestrial and freshwater ecosystems, we attempted to remove any predicted mammal habitat in the marine environment. However, in aquatic systems, it is difficult to determine where freshwater ends and saltwater begins, as that transition is highly dynamic and influenced by many factors including topography, instream flow, tides, storms, and more. To define the extent of this indicator, we used an elevation-based approach that includes all areas greater than -1 m in elevation (i.e., all areas above 1 m below sea level), then backfilled to capture low-lying coastal areas that are disconnected from the ocean. We intentionally erred on the side of including more terrestrial and freshwater areas so as not to exclude small islands that provide important habitat for species like beach mice, as well as coastal freshwater lakes (like Lake Mattamuskeet in NC). This is an imperfect methodology but produced better results than some of the other alternatives we explored. Disclaimer: Comparing with Older Indicator Versions There are numerous problems with using Southeast Blueprint indicators for change analysis. Please consult Blueprint staff if you would like to do this (email [hilary_morris@fws.gov]). Literature Cited Dewitz, J., 2023, National Land Cover Database (NLCD) 2021 Products: U.S. Geological Survey data release. [[https://doi.org/10.5066/P9JZ7AO3]]. International Union for Conservation of Nature (IUCN). Other Spatial Downloads. The IUCN Red List of Threatened Species. Accessed April 10, 2025. [[https://www.iucnredlist.org/resources/other-spatial-downloads]]. Sayre, R., 2023, Global Islands: U.S. Geological Survey data release. [[https://doi.org/10.5066/P91ZCSGM]]. Shipp-Pennock MA., Webster WD., and Freshwater DW. 2005. Systematics of the white-footed mouse (Peromyscus leucopus) in the mid-Atlantic region. Journal of Mammalogy 86(4):803-813. [[https://academic.oup.com/jmammal/article-abstract/86/4/803/880584]]. Trani MK., Ford MW, and Chapman BR., editors. 2007. The Land Manager’s Guide to the Mammal’s of the South. The Nature Conservancy, Southeastern Region, Durham, North Carolina, USA. 546 pages. [[https://www.nrs.fs.usda.gov/pubs/jrnl/2007/nrs_2007_trani-lndmgr-full_009.pdf]]. U.S. Geological Survey. Gap Analysis Project. Accessed February 25, 2025. [[https://www.usgs.gov/programs/gap-analysis-project]].