There are 8 indices representing different aspects of human well-being measured for 139 coastal and watershed counties in Alabama, Florida, Louisiana, Mississippi and Texas. The indices are derived from 41 collected secondary variables for 5 separate time periods spanning from 2000 through 2012. This complete data set creates a holistic, county level method to anlayze changes in societal structure using the human well-being construct as proxy.

There are 8 indices representing different aspects of human well-being measured for 139 coastal and watershed counties in Alabama, Florida, Louisiana, Mississippi and Texas. The indices are derived from 41 collected secondary variables for 5 separate time periods spanning from 2000 through 2012. This complete data set creates a holistic, county level method to anlayze changes in societal structure using the human well-being construct as proxy.

There are 8 indices representing different aspects of human well-being measured for 139 coastal and watershed counties in Alabama, Florida, Louisiana, Mississippi and Texas. The indices are derived from 41 collected secondary variables for 5 separate time periods spanning from 2000 through 2012. This complete data set creates a holistic, county level method to anlayze changes in societal structure using the human well-being construct as proxy.

Projected land cover land use (LCLU) coverage for 2030 was generated using the Prescott Spatial Growth Model. The 2001 LCLU data was used as an existing baseline. Model assumptions included a continuation of existing population and spatial growth patterns. Growth rules allowed developed land areas to be attracted to coastal areas. Wetlands were preserved from development. The year 2030 LCLU model projection provides results for the same classification system used to develop the 1948, 1992, and 2001 land cover land use coverages.

These Bathymetric Digital Elevation Models (DEM) were generated from original point soundings collected during hydrographic surveys conducted by the National Ocean Service and its predecessors. Mean High Water shoreline as defined by NOAA nautical charts was used as a constraining boundary and assigned its local elevation relative to the local datum (typically Mean Low Water). DEM grid values outside the shoreline (on land) were assigned null values (-32676). In the event of multiple surveys in a region, the most recent survey soundings were retained.

Atlantic bluefin tuna are a highly migratory species with two known main populations that spawn in the Gulf of Mexico (western stock) and the Mediterranean Sea (eastern stock), but feed mainly in the North Atlantic. A habitat model, developed by the Joint Research Centre of the European Commission and partner scientists, has identified the preferred feeding and spawning habitats of small (5-25 kg) and large (>25kg) in the Mediterranean Sea, North Atlantic and the Gulf of Mexico.

These data represent the geographic area described in Title 50 CFR Part 622.35(d), Fisheries of the Caribbean, Gulf of Mexico, and South Atlantic, Subpart B - Reef Fish Resources of the Gulf of Mexico, Gear resticted areas, Alabama SMZ as of 07/01/13.

These data represent the critical habitat for elkhorn coral (Acropora palmata) and staghorn coral (A. cervicornis) as designated by 73 FR 72210, November 26, 2008, Rules and Regulations.

The data represent predicted habitat suitability for several taxa of deep-sea corals. Predictions were modeled using a statistical machine-learning algorithm called maximum entropy (MaxEnt). NOAA National Centers for Coastal Ocean Science (NCCOS) combined databases of known deep-sea coral locations provided by the NOAA Deep-Sea Coral Research and Technology Program (DSCRTP) and other contributors with environmental and oceanographic data to generate the predictive models of deep-sea coral distribution. These models are used to produce regional maps of deep-sea coral habitat.

The data represent predicted habitat suitability for several taxa of deep-sea corals. Predictions were modeled using a statistical machine-learning algorithm called maximum entropy (MaxEnt). NOAA National Centers for Coastal Ocean Science (NCCOS) combined databases of known deep-sea coral locations provided by the NOAA Deep-Sea Coral Research and Technology Program (DSCRTP) and other contributors with environmental and oceanographic data to generate the predictive models of deep-sea coral distribution. These models are used to produce regional maps of deep-sea coral habitat.