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Tuesday, January 26 • 1:20pm - 1:40pm
Using Demographically-Informed Species Distribution Models To Identify Management Options For Threatened Species In The Face of Climate Change

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AUTHORS: Ilona Naujokaitis-Lewis, University of Wisconsin-Madison; Benjamin Zuckerberg,* University of Wisconsin-Madison

ABSTRACT: Identifying management actions aimed at ensuring long-term persistence and recovery of threatened species requires a consideration of the vulnerability of species to climate change. As part of an ongoing project, we present findings from a case study using spatially-explicit demographic modeling to assess the vulnerability of eastern massasauga rattlesnake Sistrurus catenatus to climate change in the upper Midwest and Great Lakes region of the United States. Based on empirical data, we identified key demographic sensitivities to several climatic factors across biologically-relevant seasons representing the complete life-cycle. These relationships were used to parameterize a range-wide population dynamics model with spatio-temporal variation in climate over a recent historical period and under future climate change scenarios. Despite variation in range-wide persistence to uncertainties associated with choice of general circulation models, our models consistently project distinct regions of high vulnerability to future climate change. While our results point to a gradient of increasing risk of extinction with peaks in south-west populations, time to predicted extinction risk was not consistently correlated with spatial regions of vulnerability. Overall our results suggest that management actions aimed at abating climate-related threats need to be spatially and must consider the temporal scale of risk. The use of demographically-informed species distribution models enabled critical insight into the selection of management actions that are both spatially and temporally optimized for a given species.

Tuesday January 26, 2016 1:20pm - 1:40pm EST