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Predictions of raven occurrence in the absence of anthropogenic environmental effects. Raven point counts were related to landscape covariates using Bayesian hierarchical occupancy models and the means of the posterior distributions for relevant effects were used to generate the predictions.
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Lidar-derived digital elevation models often contain a vertical bias due to vegetation. In areas with tidal influence the amount of bias can be ecologically significant, for example, by decreasing the expected inundation frequency. We generated a corrected digital elevation mode (DEM) for tidal marsh areas around San Francisco Bay using the Lidar Elevation Adjustment with NDVI (LEAN) technique (Buffington et al. 2016). Survey-grade GPS survey data (6614 points), NAIP-derived Normalized Difference Vegetation Index, and original 1 m lidar DEM from 2010 were used to generate a model of predicted bias across tidal marsh areas. The predicted bias was then subtracted from the original lidar DEM and merged with the NOAA...
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Lidar-derived digital elevation models often contain a vertical bias due to vegetation. In areas with tidal influence the amount of bias can be ecologically significant, for example, by decreasing the expected inundation frequency. We generated a corrected digital elevation model (DEM) for wetlands throughout Collier county using a modification of the Lidar Elevation Adjustment with NDVI (LEAN) technique (Buffington et al. 2016). GPS survey data (15,223 points), NAIP-derived Normalized Difference Vegetation Index (2010), a 10 m lidar DEM from 2007, and a 10 m canopy surface model were used to generate a model of predicted bias across marsh, mangrove, and cypress habitats. The predicted bias was then subtracted from...
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This dataset is comprised of four different zip files. Zip File 1: A combined wildfire polygon dataset ranging in years from 1878-2019 (142 years) that was created by merging and dissolving fire information from 12 different original wildfire datasets to create one of the most comprehensive wildfire datasets available. Attributes describing fires that were reported in the various source data, including fire name, fire code, ignition date, controlled date, containment date, and fire cause, were included in this product’s attribute table. Zip Files 2-4: The fire polygons were turned into 30 meter rasters with the values representing area burned in each year (128 yearly rasters total, as some years in the 1800s had...
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This feature estimates the geographic extent of the sagebrush biome in the United States. It was created for the Western Association of Fish and Wildlife Agency’s (WAFWA) Sagebrush Conservation Strategy publication as a visual for the schematic figures. This layer does not represent the realized distribution of sagebrush and should not be used to summarize statistics about the distribution or precise location of sagebrush across the landscape. This layer is intended to generalize the sagebrush biome distribution using Landsat derived classified vegetation rasters (Rigge at al. 2019), Bureau of Land Management-designated Habitat Management Areas, state-designated Priority Areas for Conservation for sage-grouse, the...
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These data depict reptile species richness within the range of the Greater Sage-grouse. Species boundaries were defined as the total extent of a species geographic limits. This raster largely used species range data from "U.S. Geological Survey - Gap Analysis Project Species Range Maps CONUS_2001", however in order for a more complete picture of species richness, additional sources were used for species missing from the Gap Analysis program.
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Predictions of raven occurrence in the absence of natural environmental effects. Raven point counts were related to landscape covariates using Bayesian hierarchical occupancy models and the means of the posterior distributions for relevant effects were used to generate the predictions.
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A raster identifying previously burned areas as being 1) recovered (to sagebrush-dominant ecosystem), 2) recovering, or 3) transitioned to annual grass-dominated.
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Lidar-derived digital elevation models often contain a vertical bias due to vegetation. In areas with tidal influence the amount of bias can be ecologically significant, for example, by decreasing the expected inundation frequency. We generated a corrected digital elevation model (DEM) for the area surrounding Blackwater National Wildlife Refuge in Chesapeake Bay using a modification of the Lidar Elevation Adjustment with NDVI (LEAN) technique (Buffington et al. 2016). GPS survey data (3699 points, collected across four tidal marsh sites in Chesapeake Bay (Eastern Neck, Martin, Bishops Head, and Blackwater) in 2010 and 2017. Normalized Difference Vegetation Index (NDVI) derived from an airborne multispectral image...
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This habitat model was developed to delineate suitable habitat for coastal cactus wren (Campylorhynchus brunneicapillus) in southern California. A primary purpose of the model is to identify potential restoration sites that may not currently support cactus patches required by wrens, but which are otherwise highly suitable. These are areas that could be planted with cactus to increase wren populations, an important management objective for many land managers. We used the Partitioned Mahalanobis D2 modeling technique to construct alternative models with different combinations of environmental variables. Variables were calculated at each point in the center of a 150 m x 150 m cell in a grid of points across the landscape....
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In 2019, dye tracing investigations were conducted near Manitou Cave in Dekalb County, northeast Alabama. The purpose of the dye tracing was to delineate a recharge area for the stream in Manitou Cave, a 1.7-kilometer-long stream cave and the only known habitat for the Manitou Cavesnail (Antroribus breweri). In 2010, the U.S. Fish and Wildlife Service was petitioned by the Center for Biological Diversity to federally list the Manitou Cavesnail. However, before any listing or vulnerability designation can occur, more knowledge was required, specifically regarding potential threats to the snail. With regards to the Manitou Cavesnail, this required delineating a recharge for the stream in Manitou Cave in order to determine...
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This raster portrays the distribution of sagebrush within the geographic extent of the sagebrush biome in the United States. It was created for the Western Association of Fish and Wildlife Agency’s (WAFWA) Sagebrush Conservation Strategy publication as a visual for the schematic figures and to calculate summary statistics. This distribution incorporates the most recently available sagebrush cover mapping (Xian et al. 2015, Rigge et al. 2019) and classified LANDFIRE EVT (Department of Ecosystem Science, University of Wyoming 2016). Both datasets were rigorously evaluated and extensive ground measurements taken to evaluate accuracy by the respective authors. We created a combined binary sagebrush distribution by classifying...
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Predictions of an anthropogenic influence on raven occurrence index intersected with sage-grouse concentration areas. The anthropogenic influence index indicates where resource subsidies are contributing the most to raven occurrence.
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An index of anthropogenic influences on raven populations. Raven point counts were related to landscape covariates using Bayesian hierarchical occupancy models and the means of the posterior distributions for relevant effects were used to generate the predictions.
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This habitat model was developed to identify suitable habitat for the federally-endangered least Bell’s vireo (Vireo bellii pusillus) across its current and historic range in California. The vireo disappeared from most of its range by the 1980s, remaining only in small populations in southern California. Habitat protection and management since the mid-1980s has led to an increase in southern California vireo populations with small numbers of birds recently expanding into the historic range. Predictions from this model will be used to focus surveys in the historic range to determine where vireos are recolonizing and to track the status and distribution of populations over time. We used the Partitioned Mahalanobis...
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Lidar-derived digital elevation models often contain a vertical bias due to vegetation. In areas with tidal influence the amount of bias can be ecologically significant, for example, by decreasing the expected inundation frequency. We generated a corrected digital elevation model (DEM) for the area surrounding the Eastern Neck National Wildlife Refuge in Chesapeake Bay using a modification of the Lidar Elevation Adjustment with NDVI (LEAN) technique (Buffington et al. 2016). GPS survey data (3699 points, collected across four tidal marsh sites in Chesapeake Bay (Eastern Neck, Martin, Bishops Head, and Blackwater) in 2010 and 2017. Normalized Difference Vegetation Index (NDVI) derived from an airborne multispectral...
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Lidar-derived digital elevation models often contain a vertical bias due to vegetation. In areas with tidal influence the amount of bias can be ecologically significant, for example, by decreasing the expected inundation frequency. We generated a corrected digital elevation model (DEM) for area surrounding the Martin National Wildlife Refuge in Chesapeake Bay using a modification of the Lidar Elevation Adjustment with NDVI (LEAN) technique (Buffington et al. 2016). GPS survey data (3699 points, collected across four tidal marsh sites in Chesapeake Bay (Eastern Neck, Martin, Bishops Head, and Blackwater) in 2010 and 2017. Normalized Difference Vegetation Index (NDVI) derived from an airborne multispectral image (2013)...


    map background search result map search result map Predictions of raven occurrence in the absence of natural environmental effects in the Great Basin, 2007-2016 (Fig. 4A) Predictions of raven occurrence in the absence of anthropogenic environmental effects in the Great Basin, 2007-2016 (Fig. 4B) Anthropogenic influence index for raven populations in the Great Basin, 2007-2016 (Fig. 4C) Prediction of raven occurrence intersected with high impact areas for sage-grouse populations in the Great Basin, 2007-2016 (Fig. 5A) Anthropogenic influence on raven occurrence index within sage-grouse concentration areas in the Great Basin, 2007-2016 (Fig. 5B) LEAN-corrected San Francisco Bay digital elevation model, 2018 Reptile Richness in the Range of the Sage-grouse, Derived From Species Range Maps The Sagebrush Biome Range Extent, as Derived from Classified Landsat Imagery Sagebrush Distribution within the Biome Range Extent, as Derived from Classified Landsat Imagery Blackwater LEAN-Corrected Chesapeake Bay Digital Elevation Models, 2019 Eastern Neck LEAN-Corrected Chesapeake Bay Digital Elevation Models, 2019 Martin LEAN-Corrected Chesapeake Bay Digital Elevation Models, 2019 LEAN-Corrected Collier County DEM for wetlands Least Bell's Vireo Habitat Suitability Model for California (2019) State transition model of cumulative burned area to annual grass in the Great Basin region of the Western U.S. Use of dye-tracing to delineate the recharge area of Manitou Cave, Alabama, towards assessing sensitive stygobiont habitat Combined wildfire datasets for the United States and certain territories, 1878-2019 Coastal Cactus Wren Habitat Suitability Model for Southern California (2015) Use of dye-tracing to delineate the recharge area of Manitou Cave, Alabama, towards assessing sensitive stygobiont habitat Martin LEAN-Corrected Chesapeake Bay Digital Elevation Models, 2019 Eastern Neck LEAN-Corrected Chesapeake Bay Digital Elevation Models, 2019 LEAN-corrected San Francisco Bay digital elevation model, 2018 LEAN-Corrected Collier County DEM for wetlands Coastal Cactus Wren Habitat Suitability Model for Southern California (2015) Least Bell's Vireo Habitat Suitability Model for California (2019) Prediction of raven occurrence intersected with high impact areas for sage-grouse populations in the Great Basin, 2007-2016 (Fig. 5A) Anthropogenic influence on raven occurrence index within sage-grouse concentration areas in the Great Basin, 2007-2016 (Fig. 5B) Predictions of raven occurrence in the absence of natural environmental effects in the Great Basin, 2007-2016 (Fig. 4A) Predictions of raven occurrence in the absence of anthropogenic environmental effects in the Great Basin, 2007-2016 (Fig. 4B) Anthropogenic influence index for raven populations in the Great Basin, 2007-2016 (Fig. 4C) State transition model of cumulative burned area to annual grass in the Great Basin region of the Western U.S. Reptile Richness in the Range of the Sage-grouse, Derived From Species Range Maps Sagebrush Distribution within the Biome Range Extent, as Derived from Classified Landsat Imagery The Sagebrush Biome Range Extent, as Derived from Classified Landsat Imagery Combined wildfire datasets for the United States and certain territories, 1878-2019