Cooperative Fish and Wildlife Research Units Program: Vermont
Education, Research and Technical Assistance for Managing Our Natural Resources

The conversion of natural lands to developed uses poses a great threat to global terrestrial biodiversity. Natural resource managers, tasked with managing wildlife as a public trust, require techniques for predicting how much and where wildlife habitat is likely to be converted in the future. Here, we develop a methodology to estimate the “social carrying capacity for development” –SKd – for 251 towns across the state of Vermont, USA. SKd represents town residents’ minimum acceptable human population size and level of development within town boundaries. To estimate SKd across towns within the state of Vermont (USA), as well as the average state-wide SKd, we administered a visual preference survey (n = 1505 responses) to Vermont residents, and asked respondents to rate alternative landuse scenarios in a fictional Vermont town on a scale of +4 (highly acceptable) to −4 (highly unacceptable). We additionally collected demographic data such as age and income, as well as ancillary information such as participation in town-planning meetings and location of residence. We used model selection and AIC to fit a cubic function to the response data, allowing us to estimate SKd at a town scale based on town demographic characteristics. On average, Vermonters had a SKd of 9.1% development on the landscape; this estimate is 68% higher than year 2000 levels for development (5.4%). Respondents indicated that management action to curb development was appropriate at 9.4% development (roughly the statewide SKd average). Management by local, regional, and state levels were considered acceptable for curbing development while federal level management of development was considered unacceptable. Given a scenario where development levels were at SKd, we predicted a 16,753 km2 reduction in forested land (−11.16%) and a 1038 km2 reduction in farmland (−60.45%). Such changes would dramatically alter biodiversity patterns state-wide. In a companion paper, we estimate how these changes would affect the distribution of wildlife species.