The attached files were used to estimate the population size of golden-cheeked warblers in 2018 and develop a habitat model for the breeding range in Texas.

This is a raster file with predicted densities of male golden-cheeked warblers as depicted in Figure 6 of Sesnie et al. (2016). The resolution is 10x10m pixels. The predicted densities are based on relationships with canopy cover, proportion of canopy composed of juniper, and annual solar radiation.

This is a raster file with predicted densities of male golden-cheeked warblers as depicted in Figure 6 of Sesnie et al. (2016). The resolution is 10x10m pixels. The predicted densities are based on relationships with canopy cover, proportion of canopy composed of juniper, and annual solar radiation.

Informed wildlife management requires robust information regarding population status, habitat requirements, and likely responses to changing resource conditions. Growing evidence indicates single species management may inadequately conserve communities and result in undesired effects to non-target species. Thus, management can benefit from habitat relationship information for multiple species within, and across, ecosystems. Using 13 years of point count data (2008-2020) collected across the western United States and a suite of relevant covariates for habitat, we fit hierarchical models to characterize and predict songbird densities and evaluate population trends for 11 species of interest: Bewick’s Wren (Thryomanes bewickii; BEWR), Brewer’s Sparrow (Spizella breweri; BRSP), Black-throated Gray Warblers (Setophaga nigrescens; BTYW), Gray Flycatcher (Empidonax wrightii; GRFL), Gray Vireo (Vireo vicinior; GRVI), Green-tailed Towhee (Pipilo chlorurus; GTTO), Juniper Titmouse (Baeolophus ridgwayi; JUTI), Loggerhead Shrike (Lanius ludovicianus; LOSH), Sagebrush Sparrow (Amphispiza belli; SABS), Sage Thrasher (Oreoscoptes montanus; SATH), and Townsend’s Solitaire (Myadestes townsendi; TOSO). The resulting maps include density (birds/km2) for each species (BEWR_2020_PredictedDensity.tif, BRSP_2020_PredictedDensity.tif, BTYW_2020_PredictedDensity.tif, GRFL_2020_PredictedDensity.tif, GRVI_2020_PredictedDensity.tif, GTTO_2020_PredictedDensity.tif, JUTI_2020_PredictedDensity.tif, LOSH_2020_PredictedDensity.tif, SABS_2020_PredictedDensity.tif, SATH_2020_PredictedDensity.tif, and TOSO_2020_PredictedDensity.tif), given 2020 environmental conditions, as well as masks representing all raster cells where one or more covariate pixel value(s) fell outside of the 2.5 and 97.5 percent quantiles of the covariate sample used when fitting the model (BEWR_mask_raster_2020.tif, BRSP_mask_raster_2020.tif, BTYW_mask_raster_2020.tif, GRFL_mask_raster_2020.tif, GRVI_mask_raster_2020.tif, GTTO_mask_raster_2020.tif, JUTI_mask_raster_2020.tif, LOSH_mask_raster_2020.tif, SABS_mask_raster_2020.tif, SATH_mask_raster_2020.tif, and TOSO_mask_raster_2020.tif). Values of one within the mask layers indicate there may be considerable uncertainty associated with the predicted values and/or that values may be unusually high or low.

Informed wildlife management requires robust information regarding population status, habitat requirements, and likely responses to changing resource conditions. Growing evidence indicates single species management may inadequately conserve communities and result in undesired effects to non-target species. Thus, management can benefit from habitat relationship information for multiple species within, and across, ecosystems. Using 13 years of point count data (2008-2020) collected across the western United States and a suite of relevant covariates for habitat, we fit hierarchical models to characterize and predict songbird densities and evaluate population trends for 11 species of interest: Bewick’s Wren (Thryomanes bewickii; BEWR), Brewer’s Sparrow (Spizella breweri; BRSP), Black-throated Gray Warblers (Setophaga nigrescens; BTYW), Gray Flycatcher (Empidonax wrightii; GRFL), Gray Vireo (Vireo vicinior; GRVI), Green-tailed Towhee (Pipilo chlorurus; GTTO), Juniper Titmouse (Baeolophus ridgwayi; JUTI), Loggerhead Shrike (Lanius ludovicianus; LOSH), Sagebrush Sparrow (Amphispiza belli; SABS), Sage Thrasher (Oreoscoptes montanus; SATH), and Townsend’s Solitaire (Myadestes townsendi; TOSO). The resulting maps include density (birds/km2) for each species (BEWR_2020_PredictedDensity.tif, BRSP_2020_PredictedDensity.tif, BTYW_2020_PredictedDensity.tif, GRFL_2020_PredictedDensity.tif, GRVI_2020_PredictedDensity.tif, GTTO_2020_PredictedDensity.tif, JUTI_2020_PredictedDensity.tif, LOSH_2020_PredictedDensity.tif, SABS_2020_PredictedDensity.tif, SATH_2020_PredictedDensity.tif, and TOSO_2020_PredictedDensity.tif), given 2020 environmental conditions, as well as masks representing all raster cells where one or more covariate pixel value(s) fell outside of the 2.5 and 97.5 percent quantiles of the covariate sample used when fitting the model (BEWR_mask_raster_2020.tif, BRSP_mask_raster_2020.tif, BTYW_mask_raster_2020.tif, GRFL_mask_raster_2020.tif, GRVI_mask_raster_2020.tif, GTTO_mask_raster_2020.tif, JUTI_mask_raster_2020.tif, LOSH_mask_raster_2020.tif, SABS_mask_raster_2020.tif, SATH_mask_raster_2020.tif, and TOSO_mask_raster_2020.tif). Values of one within the mask layers indicate there may be considerable uncertainty associated with the predicted values and/or that values may be unusually high or low.

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).

Data used in: "Misleading prioritizations from modeling range shifts under climate change" by H.R. Sofaer, C.S. Jarnevich, and C.H. Flather. Breeding Bird Survey data (version 2014.0) for songbirds were summarized over historical (1977-1979) and recent (2012-2014) time periods at routes in the conterminous U.S. Avian occurrence data were combined with information on climate and land cover at each survey route.

Data used in: "Misleading prioritizations from modeling range shifts under climate change" by H.R. Sofaer, C.S. Jarnevich, and C.H. Flather. Breeding Bird Survey data (version 2014.0) for songbirds were summarized over historical (1977-1979) and recent (2012-2014) time periods at routes in the conterminous U.S. Avian occurrence data were combined with information on climate and land cover at each survey route.