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


Brown, M. L., T. M. Donovan, W. S. Schwenk, and D. M. Theobald. 2013. Predicting impacts of future human population growth and development on occupancy rates of forest-dependent birds . Biological Conservation. Available online 31 October 2013, ISSN 0006-3207, http://dx.doi.org/10.1016/j.biocon.2013.07.039

Abstract

Forest loss and fragmentation are among the largest threats to forest-dwelling wildlife species today, and projected increases in human population growth are expected to increase these threats in the next century. We combined spatially-explicit growth models with wildlife distribution models to predict the effects of human development on 5 forest-dependent bird species in Vermont, New Hampshire, and Massachusetts, USA. We used single-species occupancy models to derive the probability of occupancy for each species across the study area in the years 2000 and 2050. Over half a million new housing units were predicted to be added to the landscape. The maximum change in housing density was nearly 30 houses per hectare; however, 30% of the towns in the study area were projected to add less than 1 housing unit per hectare. In the face of predicted human growth, the overall occupancy of each species decreased by as much as 38% (ranging from 19% to 38% declines in the worst-case scenario) in the year 2050. These declines were greater outside of protected areas than within protected lands. Ninety-seven percent of towns experienced some decline in species occupancy within their borders, highlighting the value of spatially-explicit models. The mean decrease in occupancy probability within towns ranged from 3% for hairy woodpecker to 8% for ovenbird and hermit thrush. Reductions in occupancy probability occurred on the perimeters of cities and towns where exurban development is predicted to increase in the study area. This spatial approach to wildlife planning provides data to evaluate trade-offs between development scenarios and forest-dependent wildlife species.