The conversion of natural lands to developed uses may pose the single greatest human threat to global terrestrial biodiversity. Continued human growth and development over the next century will further exacerbate these effects of habitat loss and fragmentation. Natural resource managers are tasked with managing wildlife as a public trust, yet often have little say in land use decisions. Generally speaking, decision makers could benefit from an understanding of what different regulations mean in terms of wildlife distribution. In a previous paper (Bettigole et al., 2013), we surveyed town residents throughout Vermont to measure how respondents feel about a range of development levels within their town boundaries. We estimated the “social carrying capacity for development” – orSK_d – for 251 towns in Vermont. SK_d provides an estimate of the level of developed land cover classes that town residents deem “acceptable” within their town boundaries. In this paper, we design a framework for linking the town-specific SK_d estimates with the wildlife distribution patterns for three wide-ranging mammalian species: American black bear (Ursus americanus), fisher (Martes pennanti), and bobcat (Lynx rufus). We simulated landscape conditions at SK_d for each town in Vermont, and then used existing occupancy models for the three target species to spatially map and compare occupancy rates in the baseline year 2000 with occupancy rates at SK_d. With nearly 90% of Vermont towns willing to increase developed landcover classes within town boundaries compared to baseline levels, significant state-wide changes in occupancy rates were predicted for all three focal species. Average occupancy rates declined by −15.9% and −3.1% for black bear and bobcats, respectively. Average occupancy rates for fisher increased by 9.0%. This study provides a method for linking development standards within a town with wildlife occurrence. Across towns, the methodology spatially identifies areas that may be at risk of future development, as well as identifying areas where wildlife distribution patterns may face future change as a result of increased human population growth and development.