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.
Normal 0 false false false EN-US X-NONE X-NONE The Earth’s plants and animals are facing unprecedented extinction rates due to two types of human impacts: (1) Losses of natural habitat to agriculture, forestry, urbanization, and industrial development (2) Climate change, which for many species is making their current locations untenable, e.g., too hot or too dry; or too wet, or too prone to disease. To avoid extinction, threatened species must find new places to live. In doing so, organisms must move through areas where they cannot survive indefinitely. However, during such movements they also encounter areas of suitable habitat, what ecologist call "habitat patches". Thus, species on the move encounter an arrangement of suitable habitat patches, or stepping stones, located within a background of unsuitable habitat. Their ability to find these patches is reflective of how far they can move through unsuitable areas. Some species, like birds, can travel long distances between patches. Other species, like amphibians, move only short distances. Ecologists refer to the ability of organisms to move from stepping stone to stepping stone as "habitat connectivity". The spatial arrangement of such stepping stones is known as a "habitat network". Wetlands are one habitat type acutely threatened by human development and climate change. In the U.S. Great Plains, wetlands are especially vulnerable; e.g., settlement of the Corn, Wheat, and Cotton Belts eliminated more than 50% of pre-settlement wetlands. Under climate change, the Great Plains is projected to become appreciably warmer. This threat of wetlands drying out due to climate change is compounded by land use change where farmers are converting remnant grasslands to crops, and in the process often draining wetlands. The Great Plains occupies a transitional zone between moist forests to the east and the more arid American West. As a result, the region experiences dramatic weather variabiilty. Many years are dry and hot, but many are wet and comparatively cool. Consequently, Great Plains wetlands are also highly variable. Some years they contain water, some years they dry out. Thus, wetland-dependent organisms in the Great Plains must be constantly on the move. Here, with respect to the concept of habitat connectivity, we have an arrangement of stepping stones that is constantly changing; some wetlands (stepping stones) are disappearing while others are reappearing. Changes in land use add additional complexity. With agricultural intensification, some wetlands (stepping stones) disappear permanently through drainage. Loss of grassland also makes it difficult for some species, like amphibians, to move between wetlands through comparatively inhospitable cropland. We used the highly dynamic nature of Great Plains wetlands as a model system for exploring general questions related to habitat connectivity. Specifically, we were interested in how climate change and land use change might influence future wetland habitat networks. This project was a pilot study where we buitl an interdisciplinary team and developed methods to test within a focal area in the Prairie Pothole Region (PPR) of North Dakota. Our hydrologic modeling group at Ohio State University developed the Prairie Complex Hydrologic Model (PCHM) which simulates weather-driven responses of hundreds of thousands of wetlands. In terms of Intellectual Merit, the PCHM represents a substantial advance over previous methods requiring significantly more computing power. We used approaches from the study of social networks to measure important attributes of wetland habitat networks. With respect to Intellectual Merit in the field of Complex Network Analysis (CNA), this project resulted in a unique case study of complex networks that vary in both space and time, a topic that has not been well-studied in CNA. Next, we compiled the most up-to-date estimates of grassland loss rates in the PPR. Our atmospheric science collaborators at Texas Tech generated climate change projections under low and high greenhouse gas scenarios. Resulting PCHM simulations projected fewer wetlands in the PPR under climate change, but wetlands projected to persist tended to have a degree of habitat connectivity comparable to historical values. This raises the possibility of targeted wetland conservation focused on "resilient" wetland networks. However, if current rates of grassland conversion continue, many of these wetlands may become effectively isolated for species unable to move through intervening cropland. In sum, we moved the newly-emerging field of Macrosystems Biology forward through a novel synthesis of CNA, hydrologic modeling, climate change projections, and land use change analysis. In terms of Broader Impacts, this project advanced the careers of two postdoctoral scientists, one the lead investigator. Our results led to a follow-up NSF proposal expanding our approach across nearly the entire Great Plains. In terms of public policy influence, our finding of rapid grassland loss rates, reported in an article in the Proceedings of the National Academy of Sciences, spurred a constructive public debate, and was used to inform conservation provisions in the 2014 Farm Bill specifically targeted at grassland and wetland protection in the PPR.
