The Gulf Sturgeon is a federally listed, anadromous species, inhabiting Gulf Coast rivers, estuaries, and coastal waters from Louisiana to Florida. The U.S. Geological Survey partnered with the U.S. Fish and Wildlife Service (USFWS), U.S. Army Corps of Engineers, University of Georgia, and their conservation partners to support adaptive management of Gulf Sturgeon (Acipenser oxyrinchus desotoi) by developing a quantitative, spatial model. The model is a Bayesian network that predicts the probability of habitat availability (days) per winter month for age-0 Gulf Sturgeon at a 30-m pixel scale in estuarine critical habitat. The model predicts habitat availability (days) for 75 alternative physiological and habitat scenarios, which were the unique combination of river discharge, winter month, and month of arrival to the estuary. The probability of habitat availability (days) is predicted from habitat characteristics that could be influenced by management actions. The model's structure was defined by empirical data, expert elicitation, and simplifying assumptions.

This USGS data release represents 35 geospatial datasets that were the Gulf Sturgeon Bayesian network model's outputs. The Gulf Sturgeon is a federally listed, anadromous species, inhabiting Gulf Coast rivers, estuaries, and coastal waters from Louisiana to Florida. The U.S. Geological Survey partnered with the U.S. Fish and Wildlife Service (USFWS), U.S. Army Corps of Engineers, University of Georgia, and their conservation partners to support adaptive management of Gulf Sturgeon (Acipenser oxyrinchus desotoi) by developing a quantitative, spatial model. The model is a Bayesian network that predicts the probability of habitat availability (days) per winter month for age-0 Gulf Sturgeon at a 30-m pixel scale in estuarine critical habitat. The model predicts habitat availability (days) for 75 alternative physiological and habitat scenarios, which were the unique combination of river discharge, winter month, and month of arrival to the estuary. The probability of habitat availability (days) is predicted from habitat characteristics that could be influenced by management actions. The model's structure was defined by empirical data, expert elicitation, and simplifying assumptions.

This USGS data release represents 35 geospatial datasets that were the Gulf Sturgeon Bayesian network model's outputs. The Gulf Sturgeon is a federally listed, anadromous species, inhabiting Gulf Coast rivers, estuaries, and coastal waters from Louisiana to Florida. The U.S. Geological Survey partnered with the U.S. Fish and Wildlife Service (USFWS), U.S. Army Corps of Engineers, University of Georgia, and their conservation partners to support adaptive management of Gulf Sturgeon (Acipenser oxyrinchus desotoi) by developing a quantitative, spatial model. The model is a Bayesian network that predicts the probability of habitat availability (days) per winter month for age-0 Gulf Sturgeon at a 30-m pixel scale in estuarine critical habitat. The model predicts habitat availability (days) for 75 alternative physiological and habitat scenarios, which were the unique combination of river discharge, winter month, and month of arrival to the estuary. The probability of habitat availability (days) is predicted from habitat characteristics that could be influenced by management actions. The model's structure was defined by empirical data, expert elicitation, and simplifying assumptions.

This USGS data release represents tabular and geospatial data for the Gulf Sturgeon Bayesian Network Model. The Gulf Sturgeon is a federally listed, anadromous species, inhabiting Gulf Coast rivers, estuaries, and coastal waters from Louisiana to Florida. The data release was produced in compliance with 'open data' requirements as way to make the scientific products associated with USGS research efforts and publications available to the public. The dataset consists of 2 separate items: 1. Bayesian network model that predicts the probability of habitat availability (days) per winter month for age-0 Gulf Sturgeon at a 30-m pixel scale in Apalachicola Bay, FL (Tabular datasets) 2. Bayesian network model outputs of the probability of habitat availability (days) per winter month for age-0 Gulf Sturgeon at a 30-m pixel scale in Apalachicola Bay, FL for 35 physiological and habitat scenarios (Raster datasets)

This USGS data release represents tabular and geospatial data for the Gulf Sturgeon Bayesian Network Model. The Gulf Sturgeon is a federally listed, anadromous species, inhabiting Gulf Coast rivers, estuaries, and coastal waters from Louisiana to Florida. The data release was produced in compliance with 'open data' requirements as way to make the scientific products associated with USGS research efforts and publications available to the public. The dataset consists of 2 separate items: 1. Bayesian network model that predicts the probability of habitat availability (days) per winter month for age-0 Gulf Sturgeon at a 30-m pixel scale in Apalachicola Bay, FL (Tabular datasets) 2. Bayesian network model outputs of the probability of habitat availability (days) per winter month for age-0 Gulf Sturgeon at a 30-m pixel scale in Apalachicola Bay, FL for 35 physiological and habitat scenarios (Raster datasets)

This U.S. Geological Survey (USGS) data release represents tabular data that were used to develop the Biological Objectives for the Gulf Coast Project’s Beach Mice Bayesian network model. The USGS partnered with the U.S. Fish and Wildlife Service (USFWS), the Florida Fish and Wildlife Conservation Commission, and their conservation partners to develop a Bayesian Network model that predicts the annual probability of beach mouse presence at a local (30-m) scale. The model was used to predict the annual probability of presence across a portion of the USFWS's Central Gulf and Florida Panhandle Coast Biological Planning Unit. This spatial extent included critical habitat for three endangered subspecies of beach mice (Peromyscus polionotus ssp). The annual probability of beach mouse presence is predicted from both local and neighborhood habitat characteristics that could be influenced by management actions. When coupled with established population objectives, this study can provide insight into how much habitat is available, how much more is needed, and where conservation or restoration efforts can most efficiently achieve established objectives. The results could be used to help guide strategic habitat conservation and adaptive management of beach mice.

The datasets used in the creation of the predicted Habitat Suitability models includes the CWHR range maps of Californias regularly-occurring vertebrates which were digitized as GIS layers to support the predictions of the CWHR System software. These vector datasets of CWHR range maps are one component of California Wildlife Habitat Relationships (CWHR), a comprehensive information system and predictive model for Californias wildlife. The CWHR System was developed to support habitat conservation and management, land use planning, impact assessment, education, and research involving terrestrial vertebrates in California. CWHR contains information on life history, management status, geographic distribution, and habitat relationships for wildlife species known to occur regularly in California. Range maps represent the maximum, current geographic extent of each species within California. They were originally delineated at a scale of 1:5,000,000 by species-level experts and have gradually been revised at a scale of 1:1,000,000. For more information about CWHR, visit the CWHR webpage (https://www.wildlife.ca.gov/Data/CWHR). The webpage provides links to download CWHR data and user documents such as a look up table of available range maps including species code, species name, and range map revision history; a full set of CWHR GIS data; .pdf files of each range map or species life history accounts; and a User Guide.The models also used the CALFIRE-FRAP compiled "best available" land cover data known as Fveg. This compilation dataset was created as a single data layer, to support the various analyses required for the Forest and Rangeland Assessment, a legislatively mandated function. These data are being updated to support on-going analyses and to prepare for the next FRAP assessment in 2015. An accurate depiction of the spatial distribution of habitat types within California is required for a variety of legislatively-mandated government functions. The California Department of Forestry and Fire Protections CALFIRE Fire and Resource Assessment Program (FRAP), in cooperation with California Department of Fish and Wildlife VegCamp program and extensive use of USDA Forest Service Region 5 Remote Sensing Laboratory (RSL) data, has compiled the "best available" land cover data available for California into a single comprehensive statewide data set. The data span a period from approximately 1990 to 2014. Typically the most current, detailed and consistent data were collected for various regions of the state. Decision rules were developed that controlled which layers were given priority in areas of overlap. Cross-walks were used to compile the various sources into the common classification scheme, the California Wildlife Habitat Relationships (CWHR) system.CWHR range data was used together with the FVEG vegetation maps and CWHR habitat suitability ranks to create Predicted Habitat Suitability maps for species. The Predicted Habitat Suitability maps show the mean habitat suitability score for the species, as defined in CWHR. CWHR defines habitat suitability as NO SUITABILITY (0), LOW (0.33), MEDIUM (0.66), or HIGH (1) for reproduction, cover, and feeding for each species in each habitat stage (habitat type, size, and density combination). The mean is the average of the reproduction, cover, and feeding scores, and can be interpreted as LOW (less than 0.34), MEDIUM (0.34-0.66), and HIGH (greater than 0.66) suitability. Note that habitat suitability ranks were developed based on habitat patch sizes >40 acres in size, and are best interpreted for habitat patches >200 acres in size. The CWHR Predicted Habitat Suitability rasters are named according to the 4 digit alpha-numeric species CWHR ID code. The CWHR Species Lookup Table contains a record for each species including its CWHR ID, scientific name, common name, and range map revision history (available for download at https://www.wildlife.ca.gov/Data/CWHR).

The datasets used in the creation of the predicted Habitat Suitability models includes the CWHR range maps of Californias regularly-occurring vertebrates which were digitized as GIS layers to support the predictions of the CWHR System software. These vector datasets of CWHR range maps are one component of California Wildlife Habitat Relationships (CWHR), a comprehensive information system and predictive model for Californias wildlife. The CWHR System was developed to support habitat conservation and management, land use planning, impact assessment, education, and research involving terrestrial vertebrates in California. CWHR contains information on life history, management status, geographic distribution, and habitat relationships for wildlife species known to occur regularly in California. Range maps represent the maximum, current geographic extent of each species within California. They were originally delineated at a scale of 1:5,000,000 by species-level experts and have gradually been revised at a scale of 1:1,000,000. For more information about CWHR, visit the CWHR webpage (https://www.wildlife.ca.gov/Data/CWHR). The webpage provides links to download CWHR data and user documents such as a look up table of available range maps including species code, species name, and range map revision history; a full set of CWHR GIS data; .pdf files of each range map or species life history accounts; and a User Guide.The models also used the CALFIRE-FRAP compiled "best available" land cover data known as Fveg. This compilation dataset was created as a single data layer, to support the various analyses required for the Forest and Rangeland Assessment, a legislatively mandated function. These data are being updated to support on-going analyses and to prepare for the next FRAP assessment in 2015. An accurate depiction of the spatial distribution of habitat types within California is required for a variety of legislatively-mandated government functions. The California Department of Forestry and Fire Protections CALFIRE Fire and Resource Assessment Program (FRAP), in cooperation with California Department of Fish and Wildlife VegCamp program and extensive use of USDA Forest Service Region 5 Remote Sensing Laboratory (RSL) data, has compiled the "best available" land cover data available for California into a single comprehensive statewide data set. The data span a period from approximately 1990 to 2014. Typically the most current, detailed and consistent data were collected for various regions of the state. Decision rules were developed that controlled which layers were given priority in areas of overlap. Cross-walks were used to compile the various sources into the common classification scheme, the California Wildlife Habitat Relationships (CWHR) system.CWHR range data was used together with the FVEG vegetation maps and CWHR habitat suitability ranks to create Predicted Habitat Suitability maps for species. The Predicted Habitat Suitability maps show the mean habitat suitability score for the species, as defined in CWHR. CWHR defines habitat suitability as NO SUITABILITY (0), LOW (0.33), MEDIUM (0.66), or HIGH (1) for reproduction, cover, and feeding for each species in each habitat stage (habitat type, size, and density combination). The mean is the average of the reproduction, cover, and feeding scores, and can be interpreted as LOW (less than 0.34), MEDIUM (0.34-0.66), and HIGH (greater than 0.66) suitability. Note that habitat suitability ranks were developed based on habitat patch sizes >40 acres in size, and are best interpreted for habitat patches >200 acres in size. The CWHR Predicted Habitat Suitability rasters are named according to the 4 digit alpha-numeric species CWHR ID code. The CWHR Species Lookup Table contains a record for each species including its CWHR ID, scientific name, common name, and range map revision history (available for download at https://www.wildlife.ca.gov/Data/CWHR).

The datasets used in the creation of the predicted Habitat Suitability models includes the CWHR range maps of Californias regularly-occurring vertebrates which were digitized as GIS layers to support the predictions of the CWHR System software. These vector datasets of CWHR range maps are one component of California Wildlife Habitat Relationships (CWHR), a comprehensive information system and predictive model for Californias wildlife. The CWHR System was developed to support habitat conservation and management, land use planning, impact assessment, education, and research involving terrestrial vertebrates in California. CWHR contains information on life history, management status, geographic distribution, and habitat relationships for wildlife species known to occur regularly in California. Range maps represent the maximum, current geographic extent of each species within California. They were originally delineated at a scale of 1:5,000,000 by species-level experts and have gradually been revised at a scale of 1:1,000,000. For more information about CWHR, visit the CWHR webpage (https://www.wildlife.ca.gov/Data/CWHR). The webpage provides links to download CWHR data and user documents such as a look up table of available range maps including species code, species name, and range map revision history; a full set of CWHR GIS data; .pdf files of each range map or species life history accounts; and a User Guide.The models also used the CALFIRE-FRAP compiled "best available" land cover data known as Fveg. This compilation dataset was created as a single data layer, to support the various analyses required for the Forest and Rangeland Assessment, a legislatively mandated function. These data are being updated to support on-going analyses and to prepare for the next FRAP assessment in 2015. An accurate depiction of the spatial distribution of habitat types within California is required for a variety of legislatively-mandated government functions. The California Department of Forestry and Fire Protections CALFIRE Fire and Resource Assessment Program (FRAP), in cooperation with California Department of Fish and Wildlife VegCamp program and extensive use of USDA Forest Service Region 5 Remote Sensing Laboratory (RSL) data, has compiled the "best available" land cover data available for California into a single comprehensive statewide data set. The data span a period from approximately 1990 to 2014. Typically the most current, detailed and consistent data were collected for various regions of the state. Decision rules were developed that controlled which layers were given priority in areas of overlap. Cross-walks were used to compile the various sources into the common classification scheme, the California Wildlife Habitat Relationships (CWHR) system.CWHR range data was used together with the FVEG vegetation maps and CWHR habitat suitability ranks to create Predicted Habitat Suitability maps for species. The Predicted Habitat Suitability maps show the mean habitat suitability score for the species, as defined in CWHR. CWHR defines habitat suitability as NO SUITABILITY (0), LOW (0.33), MEDIUM (0.66), or HIGH (1) for reproduction, cover, and feeding for each species in each habitat stage (habitat type, size, and density combination). The mean is the average of the reproduction, cover, and feeding scores, and can be interpreted as LOW (less than 0.34), MEDIUM (0.34-0.66), and HIGH (greater than 0.66) suitability. Note that habitat suitability ranks were developed based on habitat patch sizes >40 acres in size, and are best interpreted for habitat patches >200 acres in size. The CWHR Predicted Habitat Suitability rasters are named according to the 4 digit alpha-numeric species CWHR ID code. The CWHR Species Lookup Table contains a record for each species including its CWHR ID, scientific name, common name, and range map revision history (available for download at https://www.wildlife.ca.gov/Data/CWHR).