COS 61-6
Using high-resolution future climate scenarios for predicting climate change effects on biological invasions in Rocky Mountain National Park

Wednesday, August 7, 2013: 9:50 AM
L100I, Minneapolis Convention Center
Amanda M. West, Natural Resource Ecology Laboratory and Bioagricultural Sciences and Pest Management Department, Colorado State University, Fort Collins, CO
Sunil Kumar, Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO
Tewodros Wakie, Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO
Cynthia S. Brown, Graduate Degree Program in Ecology, Bioagricultural Sciences and Pest Management, Colorado State University, Fort Collins, CO
Thomas J. Stohlgren, Natural Resource Ecology Laboratory, Fort Collins
Melinda Laituri, Ecosystem Science and Sustainability, Colorado State University, Fort Collins, CO
Jim Bromberg, Rocky Mountain National Park, U.S. National Park Service, CO
Background/Question/Methods

National parks are the hallmarks of ecosystem preservation in the United States. The introduction of non-native invasive species into these areas threatens natural ecosystems, altering their structure and functioning. Species distribution models (SDMs) are commonly used for evaluating the potential spread of invasive species under changing climate, however the coarse resolution of the maps most often created from these models may not capture specific microclimates in regional landscapes such as those represented by national parks. We used the program ClimateWNA for generation of high-resolution (90 m) current and future climate change scenarios for Rocky Mountain National Park (RMNP), Colorado. Our first objective was to develop a high-resolution potential distribution map for an invasive grass, Bromus tectorum, in the Park. This was based on occurrence data (what we assume to be the environmental niche of B. tectorum in RMNP; n=211) and variables including current climate, vegetation community type, and distance to roads (surrogate for propagule pressure) using a maximum entropy based SDM (MaxEnt). Our second objective was to use the model to create maps for future potential distribution of B. tectorum based on combining predictions from three future climate global circulation models (ensemble model). Finally, principle component analysis was used to further evaluate niche conservatism of B. tectorum between current and future potential climates.

Results/Conclusions

The ensemble model maps we created from the SDM showed areas of RMNP currently habitable by B. tectorum and future areas where the occurrence of this species is predicted to remain constant, decrease or increase based in its environmental niche. Mean annual temperature was the variable with the strongest effect on B. tectorum distribution in RMNP, indicating future climate change may alter this niche. Principle component analysis indicated significant niche overlap for B. tectorum in RMNP between current and future potential climate regimes. Modeling climate change at a small spatial scale (1,076 km2) and at a high spatial resolution (90 m) is a novel approach in species distribution modeling that may provide inference for microclimates not captured in coarse scale models. The ensemble maps we created are valuable tools that will be available to land managers to prioritize specific areas in Rocky Mountain National Park for surveys and removal of invasive species and the approach may be useful for managers of other national parks and land management units.