Ecological Modeling

The Biscayne Bay and Southeastern Everglades Ecosystem Restoration (BBSEER) project will use Bayesian networks developed within the Everglades Vulnerability Analysis framework but with an expanded set of predicted vegetation types to build a spatially explicit model predicting annual probability of vegetation types in response to hydrologic and other landscape factors.

USGS scientists are working with partners at the Puget Sound Partnership and the State of Washington’s Department of Ecology to develop two new tools to help us understand how human disturbance affects life at the top of Puget Sound: a Marine Benthic Index and a graphical causal model.

Researchers at WARC will use data and models to produce probabilistic maps of current and future wetland inundation, coastal wetland extent, and coastal and wetland trangression.

USGS researchers will examine how hydrology and landscape vegetation changes impact Cape Sable Seaside Sparrow survival and population growth.

USGS will collaborate with the Miccosukee and Seminole Tribes to co-design a dashboard mock-up for a real-time web application that monitors tree island health in the Everglades.

USGS will compare the EverForecast hydrologic forecast, the South Florida Water Management District's Position Analysis, and observed water level recordings from gages located across the Everglades landscape to examine which forecast performs better during the wet and dry seasons; wet, dry, or average years; or in different areas of the Everglades.

The Joint Ecosystem Modeling team will be running a suite of ecological models to evaluate scenarios and provide insight into how alternative restorations plans compare, indicate whether alternatives could lead to unintended consequences, and determine effects of alternatives that could conflict with other goals.

WARC researchers partnered with Gulf Sturgeon decision makers and biologists to develop a Bayesian network model that uses habitat characteristics to predict the quantity of juvenile winter foraging habitat under alternative river discharge and timing of juvenile arrival scenarios.

WARC researchers partnered with managers and species experts to develop a Bayesian network model and a geospatial habitat characteristics dataset to predict the number of Brown Pelican breeding pairs on islands in the northern Gulf of Mexico.

WARC researchers partnered with managers and species experts to develop a Bayesian network model and a geospatial habitat characteristics dataset to predict the number of breeding pairs of Black Skimmer and Gull-billed Tern along the northern Gulf of Mexico.

WARC researchers partnered with beach mice managers and biologists to estimate habitat objectives and the amount of effort needed to achieve the habitat objective (i.e., management efficiency) for three beach mice subspecies in Florida’s panhandle.

WARC Researchers are comparing tree and root growth, soil CO2 flux, and surface elevation change between fertilized and unfertilized mangrove forests to assess the potential impact of increased nutrient loading and to help rate mangrove stand vulnerability.