COS 117-9
Using a combined hydrologic network-climate model of the invasive nutria (Myocastor coypus) to understand current distributions and range expansion potential under climate change scenarios

Friday, August 9, 2013: 10:50 AM
101H, Minneapolis Convention Center
Catherine Jarnevich, Fort Collins Science Center, U.S. Geological Survey, Fort Collins, CO
Trevor R. Sheffels, Environmental Science and Management Department, Portland State University, Portland, OR
Jacoby Carter, National Wetlands Research Center, US Geological Survey, Lafayette, LA
Nick Young, Natural Resource Ecology Laboratory, Colorado State University, Ft. Collins, CO
Mark D. Sytsma, Environmental Science and Management Department, Portland State University, Portland, OR

The nutria (Myocastor coypus) is an invasive rodent that has become established in many parts of the world, including the southeast and the pacific northwest USA.  Large-scale management of the species requires knowledge of its current and potential distribution.  What is the relationship between extreme winter weather and the influence of cold temperatures on the geographical distribution of nutria populations?  Taking previous work on modeling the impact of cold weather on nutria mortality we examined the current distribution of nutria in the Pacific Northwest and compared it to recent extreme weather events. Because the resolution of available climate data was a limiting factor there was a trade-off between spatial and temporal resolution.  We developed a mechanistic model of nutria distribution using proximity to water and winter temperature data for the United States (fine temporal scale) and the globe (large spatial scale).  We also evaluated current and potential distribution using a physiologically informed statistical model along with the mechanistic model.  We developed statistical models using the Software for Automated Habitat Modeling with global point location data and biologically relevant climate data at the global level.  All models were evaluated at a global and a regional (United States and USA Pacific Northwest) level using coarser scale independent data.


Comparison of the mechanistic models with nutria density data for Oregon and Washington and with nutria population assessments for the United States had high overlap, with current known distribution generally matching the predictions.  The fine temporal scales models had less predicted suitable habitat in Pacific Northwest areas with no reported nutria populations compared to global models (12% and 19%, respectively).  The statistical models were generally limited to the area of known nutria populations in the northwest (west of the Cascade Mountains).  For the United States similar patterns seemed to hold, with the fine temporal scale mechanistic models matching state level nutria distribution knowledge.  The statistical models also had coldest month temperature as the most important factor, matching the mechanistic understanding of nutria distribution.  Although nutria distribution in the United States has been relatively stable over the last several years, model results suggest that nutria populations could extend their range substantially both in the Pacific Northwest and the contiguous United States in the future with changing climatic conditions.