This pilot project will address climate change effects on wetlands in the Great Plains of the United States and focuses on habitat connectivity, or the ability of wetland dependent animal species to move between individual wetlands. Maintaining such connectivity is vitally important in balancing agricultural production with wildlife conservation in this agriculturally dominant region. Graph theory is a branch of mathematics useful for describing how objects are connected in space, whether they are social networks, the global air transportation network, or the World Wide Web. This project will use graph theory to determine historical relationships between wetland habitat connectivity and bird populations in three focus areas, the Prairie Pothole region in the northern plains, the Rainwater Basin in central Nebraska, and the Playa Lakes region in the southern plains. Projections of future climate and a computer simulation model of surface water dynamics will be used to predict the locations of future wetlands and determine the resulting impacts on wetland habitat connectivity. Graph theory will also be used to identify wetlands critical to maintaining connectivity as climatic shifts occur.
Climate change is forcing plant and animal species to find new places to live as existing habitats become too hot, or too dry, or too wet. Finding a place that is just right thus requires a suitable degree of habitat connectivity. The Great Plains is an ideal laboratory for studying potential impacts of climate change on such connectivity. Approaches developed here should be broadly applicable to the global challenge of enabling biological adaptation to climate change. This collaborative project will also build a research network combining expertise in landscape ecology at South Dakota State University, climate modeling and ornithology at Texas Tech University, and hydrologic modeling at Ohio State University. A workshop will be held with the goal of broadening participation in this network. Results from exploratory focus areas will be used to prepare a future proposal to do climate change and connectivity research across the entire Great Plains.
Habitat connectivity is critical to the long-term viability of many wildlife species. Climate projections suggest increased risk of drought in future, which is likely to limit the availability of wetlands across the Great Plains (Fig. 1). Climate change has the potential to affect habitat connectivity among wetlands within and across the three main wetland complexes of the Great Plains: the prairie potholes of the northern plains, the Rainwater Basin of Nebraska, and the playas of the southern plains. Wetland density affects connectivity (Fig. 2). A key question is therefore how organisms moving through these wetland complexes (like migratory birds) will cope with landscapes in the Great Plains of the future that resemble configurations currently only found in drought years. We found that wetland habitat networks under projected climate scenarios will exhibit constrained connectivity, and dispersal capacity will be as important as wet/dry conditions to an organism’s ability to traverse the wetland network (Fig. 3). Organisms with dispersal capabilities limited to <10 km (e.g. amphibians) routinely experienced effective isolation during our study. Using monthly precipitation, potential evapotranspiration, and average temperature as inputs, we constructed a hydrological model of the prairie pothole complex that simulates surface water dynamics; this model allowed us to re-construct the spatio-temporal dynamics of wetland networks and relate these to the occurrence of several wetland bird species. We have found that bird abundance is closely associated with this climate-driven fluctuation in wetland availability (Fig. 4). Because of the coupling of climate, wetland density, and bird abundance, connectivity through the wetland habitat network is constantly in flux. This poses a significant challenge for conservation, for very few individual wetlands were consistently important in maintaining connectivity (Fig. 5).
