Predicting Wildlife Distributions And Resilience Under Alternative Futures
Date of Award
Doctor of Philosophy (PhD)
Therese M. Donovan
James D. Murdoch
In the northeastern United States, population expansion, climate change, land use, and land-use change all pose serious concerns for wildlife. Understanding the impacts of climate and land-use change on species distributions can help inform conservation decisions. Unfortunately, empirical data on distributions are limited for many wildlife species, making conservation planning challenging. This dissertation focuses on the use of expert opinion data for modeling wildlife distributions and evaluating the impacts of future climate and land-use changes. First, I implemented expert elicitation techniques to collect wildlife occurrence data for harvested species (n = 10) in the New England region. I then used mixed-model methods to develop species distribution models (SDMs) and applied the models to the regional landscape to map species distributions relative to recent (2010) conditions. Second, I used a systematic scenario-based approach to estimate species future distributions and evaluate how two influential drivers of landscape change – socio-economic connectivity and natural resource planning – influenced distribution change and species richness. Third, I used the collection of baseline and scenario projected distribution maps to evaluate patterns of distribution change and isolate areas of greatest resilience for individual species. I also assessed resilience patterns in and out of the region’s protected network and identified protected areas with the highest representation of species resilience. Together, these three studies demonstrate the utility of expert derived SDMs and scenarios for evaluating wildlife futures, emphasize the value of species-based resilience assessments, and generate tools that can inform proactive decision-making and collaborative, multi-scale conservation planning.
Number of Pages
Pearman-Gillman, Schuyler, "Predicting Wildlife Distributions And Resilience Under Alternative Futures" (2020). Graduate College Dissertations and Theses. 1237.