Southeast Regional Assessment Project (SERAP): Assessing Global Change Impacts on Natural and Human Systems in the Southeast
The Southeastern United States spans a broad range of physiographic settings and maintains exceptionally high levels of faunal diversity. Unfortunately, many of these ecosystems are increasingly under threat due to rapid human development, and management agencies are increasingly aware of the potential effects that climate change will have on these ecosystems. Natural resource managers and conservation planners can be effective at preserving ecosystems in the face of these stressors only if they can adapt current conservation efforts to increase the overall resilience of the system. Climate change, in particular, challenges many of the basic assumptions used by conservation planners and managers. Previous conservation planning efforts identified and prioritized areas for conservation based on the current environmental conditions, such as habitat quality, and assumed that conditions in conservation lands would be largely controlled by management actions (including no action). Climate change, however, will likely alter important system drivers (temperature, precipitation, and sea-level rise) and make it difficult, if not impossible, to maintain recent historic conditions in conservation lands into the future. Climate change will also influence the future conservation potential of non-conservation lands, further complicating conservation planning. Therefore, there is a need to develop and adapt effective conservation strategies to cope with the effects of climate and landscape change on future environmental conditions.
SERAP included the following subprojects:
Researchers from North Carolina State University and the USGS integrated models of urbanization and vegetation dynamics with the regional climate models to predict vegetation dynamics and assess how landscape change could impact priority species, including North American land birds. This integrated ensemble of models can be used to predict locations where responses to climate change are most likely to occur, expressing results in terms of species persistence to help resource managers understand the long-term sustainability of bird populations.
The broad range of complex factors influencing coastal systems contribute to large uncertainties in predicting long-term sea level rise impacts. Researchers demonstrated the capabilities of a Bayesian network (BN) to predict long-term shoreline change associated with sea level rise and make quantitative assessments for predicting uncertainty. A BN was used to define relationships between driving forces, geologic constraints, and coastal response for the U.S. Atlantic coast that include observations of local rates of relative sea level rise, wave height, tide range, geomorphic classification, coastal slope, and shoreline change rate. The BN was used to make probabilistic predictions of shoreline retreat in response to different future sea level rise rates.
A team of USGS and academic researchers developed a comprehensive web-based dataset of high-resolution (or ‘downscaled’) climate change projections, enabling scientists and decision-makers to better assess climate related ecosystem impacts. The research team implemented a three-part plan to provide high resolution climate data for the impact modeling community. First, a database was developed of up-to-date and state-of-the-art downscaled climate projections for the U.S., using a range of plausible future greenhouse gas emission scenarios. Second, a series of workshops were held to solicit input about climate-related data needs and to discuss best practices for accessing and using downscaled climate projections. Finally, downscaled projections are now being made available as an enterprise-level web-based source. Users are able to freely access the data via an interactive, easily manageable interface, in formats which are familiar to ecosystem and impact modelers. The work enables impact assessments to be based on the same common data set, allowing researchers and resource managers to compare results and projections across regions and ecosystems.
Additionally, a research team developed the core climatic datasets necessary to project regional ecosystem impacts resulting from 21st century climate change. They adhered to an approach that carefully assessed and propagated model uncertainty, downscaled climate projections to the scale of important ecosystem processes, and focused on the most impact-relevant climatic variables. They worked on addressing three questions: (1) What is the magnitude and direction of climate change expected in the U.S. Southeast over the next 100 years? (2) How do the projected changes in climate relate to those parameters that most affect ecosystem processes specific to the Southeast? and (3) What is the level of uncertainty associated these projections?
Traditional urban growth models are very localized and data-intensive and lack the capability to be applied across large regions. In response to these limitations the North Carolina Cooperative Research Unit began using the USGS SLEUTH urban growth model to develop urbanization scenarios as part of the Southeast Regional Assessment Project (SERAP). Extensive modifications of the model framework and calibration were undertaken that resulted in the ability to rapidly develop urbanization scenarios for very large regions, such as the Appalachian, Caribbean, and Gulf Coastal Plain Landscape Conservation Cooperatives (LCCs). This new modeling effort allows LCC’s to address fundamental questions that affect conservation planning over decadal time scales.
A hydrologic model was developed as part of the Southeast Regional Assessment Project using the Precipitation Runoff Modeling System (PRMS), a deterministic, distributed-parameter, process-based system that simulates the effects of precipitation, temperature, and land use on basin hydrology. Streamflow and other components of the hydrologic cycle simulated by PRMS were used to inform other types of simulations such as water-temperature, hydrodynamic, and ecosystem-dynamics simulations.
USGS researchers assessed how climate change can affect land cover and flow in river systems, examining a variety of resolutions for detecting and projecting the conditions of aquatic habitats and species.
The USGS and South Atlantic LCC worked with stakeholders and managers across the Southeast to identify and assess landscape-level strategies for conserving multiple species. These strategies incorporated predictions from downscaled climate models, sea level rise, and changes to aquatic and terrestrial habitats.