Forecasting climate change impacts on the distribution of wetland habitat in the Midwestern United states |
| |
Authors: | Heath W. Garris Randall J Mitchell Lauchlan H. Fraser Linda R. Barrett |
| |
Affiliation: | 1. Department of Biology, Auburn Science Center, University of Akron, Akron, OH, USA;2. Department of Natural Resources and Biological Sciences, Thompson Rivers University, Kamloops, British Columbia, Canada;3. Department of Geoscience, University of Akron, Akron, OH, USA |
| |
Abstract: | Shifting precipitation patterns brought on by climate change threaten to alter the future distribution of wetlands. We developed a set of models to understand the role climate plays in determining wetland formation on a landscape scale and to forecast changes in wetland distribution for the Midwestern United States. These models combined 35 climate variables with 21 geographic and anthropogenic factors thought to encapsulate other major drivers of wetland distribution for the Midwest. All models successfully recreated a majority of the variation in current wetland area within the Midwest, and showed that wetland area was significantly associated with climate, even when controlling for landscape context. Inferential (linear) models identified a consistent negative association between wetland area and isothermality. This is likely the result of regular inundation in areas where precipitation accumulates as snow, then melts faster than drainage capacity. Moisture index seasonality was identified as a key factor distinguishing between emergent and forested wetland types, where forested wetland area at the landscape scale is associated with a greater seasonal variation in water table depth. Forecasting models (neural networks) predicted an increase in potential wetland area in the coming century, with areas conducive to forested wetland formation expanding more rapidly than areas conducive to emergent wetlands. Local cluster analyses identified Iowa and Northeastern Missouri as areas of anticipated wetland expansion, indicating both a risk to crop production within the Midwest Corn Belt and an opportunity for wetland conservation, while Northern Minnesota and Michigan are potentially at risk of wetland losses under a future climate. |
| |
Keywords: | artificial neural network climate projections isothermality midwest modeling wetlands WorldClim |
|
|