This raster represents a continuous surface of sage-grouse habitat suitability index (HSI) values for northeastern California. HSIs were calculated for spring (mid-March to June), summer (July to mid-October), and winter (November to March) sage-grouse seasons, and then multiplied together to create this composite dataset.
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...
Map of cumulative 38-day nest survival predicted from a Bayesian hierarchical shared frailty model of sage-grouse nest fates. The midpoint of coefficient conditional posterior distributions of 38-day nest survival were used for prediction at each 30 meter pixel across the landscape.
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.
Estimated habitat suitability for the American burying beetle using land cover classes in the Southern Plains (ver. 1.1, June 2020)
Potentially suitable habitat for the American burying beetle (Nicrophorus americanus) was identified within the Southern Plains. The American burying beetle (ABB) is listed as endangered under the Endangered Species Act, but in 2019 the U.S. Fish and Wildlife Service proposed to reclassify this species as threatened. We applied a deductive model for the ABB that identified potentially suitable habitat using LANDFIRE Existing Vegetation Types (EVT). The habitat model ranked each EVT using one of four categories: (1) favorable; suitable vegetation to support all or critical portions of the ABB life cycle, (2) conditional; favorable only under certain conditions including seasonality of flooding and land management...
This raster represents a continuous surface of sage-grouse habitat suitability index (HSI) values for northeastern California during summer (July to mid-October), which is a surrogate for habitat conditions during the sage-grouse brood-rearing period.
Ranked index of model-projected nest site selection integrated with nesting productivity (i.e., nest survival), demonstrating the spatial distribution of adaptive vs. maladaptive habitat selection at each 30 m pixel. Hierarchical models of nest selection and survival were fit to landscape covariates within a Bayesian modeling framework in Nevada and California from 2009 through 2017 to develop spatially explicit information about nest site selection and survival consequences across the landscape. Habitat was separated into 16 classes ranking from high (1) to low (16). Habitat ranked highest where the top nest selection and survival classes intersected (adaptive selection), whereas the lowest rank occurred where...
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....
This raster represents a continuous surface of sage-grouse habitat suitability index (HSI) values for northeastern California during the winter season (November to March), and is a surrogate for habitat conditions during periods of cold and snow.
This raster represents a continuous surface of sage-grouse habitat suitability index (HSI) values for northeastern California during spring (mid-March to June), which is a surrogate for habitat conditions during the sage-grouse breeding and nesting period.
A raster surface identifying hotspots of conservation priority based on 375 location records (89 unique geographic locations) of 28 species of Carnivora in Peninsular Malaysia. Hotspot analysis was conducted by calculating the Getis-Ord Gi* (pronounced G-i-star) statistic, using IUCN Red List status rank for each species as a weighting variable. Raster cell values represent a kernel density of z-scores measuring the statistical significance of clustering or dispersion of species of conservation concern. Areas of high clustering (high z-scores) correspond to areas on Peninsular Malaysia where carnivore communities of conservation concern are more likely to persist, and delineate priority regions for carnivore conservation....
Map of nesting habitat selection scores predicted from a resource selection function (RSF) developed from sage-grouse nest locations. Nest site selection was modeled using a generalized linear mixed model of used and random locations in a Bayesian modeling environment, and the midpoint of coefficient conditional posterior distributions were used for prediction. Continuous values were reclassified and ranked using a percent isopleth approach with respect to observed nest locations.
This data was used in the analysis for the article “Burn Severity Controls on Post-fire Araucaria-Nothofagus Regeneration in the Andean Cordillera” by T. Assal, M. Gonzalez and J. Sibold. The aim of the study was to investigate post-fire regeneration patterns of forests on the west slope of the Andes; to evaluate the relationship between remotely sensed burn severity and forest mortality; and to assess controls of burn severity on forest response at local spatio-temporal scales. This dataset reflects the burn severity calculated from Landsat data as part of the analysis.