Colorado Plateau REA Change Agents - Development - Current, Near-Term, and Long-Term Potential High Landscape Development
This map shows areas of high current, near-term, and long-term potential landscape development, based on factors such as urban areas, agriculture, roads, and energy development.
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.
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.
Colorado Plateau REA MQ J4: Where are aquatic/riparian areas with potential to change from climate change?
This map shows naturalized flow change for April-July for 3 periods: 1951-1965 (historic), 2016-2030, and 2046-2060 simulated by the Bureau of Reclamation across 112 GCM scenarios.
This map shows long-term potential for climate change, which was calculated using a logic model to integrate the factors of: vegetation change summer & winter temperature change annual precipitation change runoff change.
This map shows climate parameters and MAPSS biogeography model data for the western US from PRISM (1968-1999), and future climate projections from the regional climate model RegCM3 using ECHAM5, GENMOM, and GFDL projections as boundary conditions for 2015-2030, and 2045-2060.
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...
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...
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.