Skip to main content
Advanced Search

Filters: Tags: biota (X) > partyWithName: Peter S Coates (X)

65 results (42ms)   

View Results as: JSON ATOM CSV
thumbnail
wy_lvl7_coarsescale: Wyoming hierarchical cluster level 7 (coarse-scale) for Greater sage-grouse We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the Greater sage-grouse range, 3) be used to track the outcomes of local and regional populations by comparing population changes across scales, and 4) be used to inform where to best spatially target studies that identify the processes and mechanisms causing population trends to change among spatial scales. The spatial variability in the amount and quality of habitat resources can affect local population success and result in different...
thumbnail
wy_lvl2_finescale: Wyoming hierarchical cluster level 2 (fine-scale) for Greater sage-grouse We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the Greater sage-grouse range, 3) be used to track the outcomes of local and regional populations by comparing population changes across scales, and 4) be used to inform where to best spatially target studies that identify the processes and mechanisms causing population trends to change among spatial scales. The spatial variability in the amount and quality of habitat resources can affect local population success and result in different...
thumbnail
This USGS data release represents geospatial data for the sage-grouse habitat mapping project. This study provides timely and highly useful information about greater sage-grouse over a large area of the Great Basin. USGS researchers and their colleagues created a template for combining landscape-scale occurrence or abundance data with habitat selection data in order to identify areas most critical to sustaining populations of species of conservation concern. The template also identifies those areas where land use changes have minimal impact. To inform greater sage-grouse conservation planning, the researchers developed greater sage-grouse habitat management categories based on habitat selection indices (HSI) and...
thumbnail
This raster represents a continuous surface of sage-grouse habitat suitability index (HSI,created using ArcGIS 10.2.2) values for Nevada during the breeding season.
thumbnail
Sage-grouse habitat areas divided into proposed management categories within Nevada and California project study boundaries. HABITAT CATEGORY DETERMINATION The process for category determination was directed by the Nevada Sagebrush Ecosystem Technical team. Sage-grouse habitat was determined from a statewide resource selection function model and first categorized into 4 classes: high, moderate, low, and non-habitat. The standard deviations (SD) from a normal distribution of RSF values created from a set of validation points (10% of the entire telemetry dataset) were used to categorize habitat ‘quality’ classes. 1) High quality habitat comprised pixels with RSF values < 0.5 SD. 2) Moderate > 0.5 and < 1.0 SD. 3)...
thumbnail
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.
thumbnail
Average and standard deviation of annual predicted common raven (Corvus corax) density (ravens per square kilometer) derived from random forest models given field site unit-specific estimates of raven density that were obtained from hierarchical distance sampling models at 43 field site units within the Great Basin region, USA. Fifteen landscape-level predictors summarizing climate, vegetation, topography and anthropogenic footprint were used to predict average raven density at each unit. These data support the following publication: Coates, P.S., O'Neil, S.T., Brussee, B.E., Ricca, M.A., Jackson, P.J., Dinkins, J.B., Howe, K.B., Moser, A.M., Foster, L.J. and Delehanty, D.J., 2020. Broad-scale impacts of an invasive...
thumbnail
Predicted common raven (Corvus corax) impacts within greater sage-grouse (Centrocercus urophasianus) concentration areas across the Great Basin, USA, 2007–2016. Predicted impacts were based on a raven density of great than or equal to 0.40 (ravens per square kilometer) which corresponded to below-average survival rates of sage-grouse nests. These data support the following publication: Coates, P.S., O'Neil, S.T., Brussee, B.E., Ricca, M.A., Jackson, P.J., Dinkins, J.B., Howe, K.B., Moser, A.M., Foster, L.J. and Delehanty, D.J., 2020. Broad-scale impacts of an invasive native predator on a sensitive native prey species within the shifting avian community of the North American Great Basin. Biological Conservation,...
thumbnail
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.
thumbnail
nv_lvl6_coarsescale: Nevada hierarchical cluster level 6 (coarse-scale) for Greater sage-grouse We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the Greater sage-grouse range, 3) be used to track the outcomes of local and regional populations by comparing population changes across scales, and 4) be used to inform where to best spatially target studies that identify the processes and mechanisms causing population trends to change among spatial scales. The spatial variability in the amount and quality of habitat resources can affect local population success and result in different...
thumbnail
wy_lvl8_coarsescale: Wyoming hierarchical cluster level 8 (coarse-scale) for Greater sage-grouse We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the Greater sage-grouse range, 3) be used to track the outcomes of local and regional populations by comparing population changes across scales, and 4) be used to inform where to best spatially target studies that identify the processes and mechanisms causing population trends to change among spatial scales. The spatial variability in the amount and quality of habitat resources can affect local population success and result in different...
thumbnail
We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the Greater sage-grouse range, 3) be used to track the outcomes of local and regional populations by comparing population changes across scales, and 4) be used to inform where to best spatially target studies that identify the processes and mechanisms causing population trends to change among spatial scales. The spatial variability in the amount and quality of habitat resources can affect local population success and result in different population growth rates among smaller clusters. Equally so, the spatial structure and ecological...
thumbnail
wy_lvl5_coarsescale: Wyoming hierarchical cluster level 5 (coarse-scale) for Greater sage-grouse We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the Greater sage-grouse range, 3) be used to track the outcomes of local and regional populations by comparing population changes across scales, and 4) be used to inform where to best spatially target studies that identify the processes and mechanisms causing population trends to change among spatial scales. The spatial variability in the amount and quality of habitat resources can affect local population success and result in different...
thumbnail
wy_lvl4_moderatescale: Wyoming hierarchical cluster level 4 (moderate-scale) for Greater sage-grouse We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the Greater sage-grouse range, 3) be used to track the outcomes of local and regional populations by comparing population changes across scales, and 4) be used to inform where to best spatially target studies that identify the processes and mechanisms causing population trends to change among spatial scales. The spatial variability in the amount and quality of habitat resources can affect local population success and result...
thumbnail
wy_lvl1_finescale: Wyoming hierarchical cluster level 1 (fine-scale) for Greater sage-grouse We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the Greater sage-grouse range, 3) be used to track the outcomes of local and regional populations by comparing population changes across scales, and 4) be used to inform where to best spatially target studies that identify the processes and mechanisms causing population trends to change among spatial scales. The spatial variability in the amount and quality of habitat resources can affect local population success and result in different...
thumbnail
Spatial associations between marked sage-grouse and existing PMU boundaries were used as an initial starting point for delineating subregions for habitat selection analyses and naming conventions across Nevada and northeastern California. Ultimately, the data were partitioned into 19 subregions based on movement patterns of individual radio-marked sage-grouse for habitat analyses, with each grouse occupying one subregion only. Some subregions contained too few marked sage-grouse for sufficient training data to develop a habitat model, which resulted in the exclusion of seven subregions with fewer than 20 marked sage-grouse or less than 100 telemetry locations. However, data from these excluded ‘non-RSF’ subregions...
thumbnail
These data represent predicted common raven (Corvus corax) density (ravens/square-km) derived from random forest models given field site unit-specific estimates of raven density that were obtained from hierarchical distance sampling models at 43 field site units within the Great Basin region, USA. Fifteen landscape-level predictors summarizing climate, vegetation, topography and anthropogenic footprint were used to predict average raven density at each unit. A raven density of greater than or equal to 0.40 ravens/square-km corresponds to below-average survival rates of sage-grouse (Centrocercus urophasianus) nests. We mapped areas which exceed this threshold within sage-grouse concentration areas to determine where...
thumbnail
This shapefile represents habitat suitability categories (High, Moderate, Low, and Non-Habitat) derived from a composite, 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.
thumbnail
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.


map background search result map search result map Sage-grouse Habitat Categories in Nevada and NE California (August 2014) Integrating spatially explicit indices of abundance and habitat quality: an applied example for greater sage-grouse management Sub regions for Greater Sage-grouse in Nevada and NE California (August 2014) Spring Season Habitat Suitability Index raster dataset Predictions of raven occurrence in the absence of anthropogenic environmental effects in the Great Basin, 2007-2016 (Fig. 4B) Prediction of raven occurrence intersected with high impact areas for sage-grouse populations in the Great Basin, 2007-2016 (Fig. 5A) Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Nevada and Wyoming, Interim Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Cluster Level 6 (Nevada), Interim Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Cluster Level 1 (Wyoming), Interim Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Cluster Level 2 (Wyoming), Interim Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Cluster Level 4 (Wyoming), Interim Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Cluster Level 5 (Wyoming), Interim Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Cluster Level 7 (Wyoming), Interim Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Cluster Level 8 (Wyoming), Interim Composite Habitat Suitability Index Raster Dataset Winter Season Habitat Categories Shapefile Data maps of predicted raven density and areas of potential impact to nesting sage-grouse within sagebrush ecosystems of the North American Great Basin Raven impacts within greater sage-grouse concentration areas within the Great Basin region of the United States 2007 - 2016 Average and standard deviation of annual predicted raven density in the Great Basin, Western U.S. Greater Sage-grouse Nest Survival, Nevada and California 2019 Composite Habitat Suitability Index Raster Dataset Winter Season Habitat Categories Shapefile Sub regions for Greater Sage-grouse in Nevada and NE California (August 2014) Integrating spatially explicit indices of abundance and habitat quality: an applied example for greater sage-grouse management Spring Season Habitat Suitability Index raster dataset Greater Sage-grouse Nest Survival, Nevada and California 2019 Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Cluster Level 1 (Wyoming), Interim Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Cluster Level 2 (Wyoming), Interim Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Cluster Level 4 (Wyoming), Interim Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Cluster Level 5 (Wyoming), Interim Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Cluster Level 7 (Wyoming), Interim Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Cluster Level 8 (Wyoming), Interim Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Cluster Level 6 (Nevada), Interim Sage-grouse Habitat Categories in Nevada and NE California (August 2014) Raven impacts within greater sage-grouse concentration areas within the Great Basin region of the United States 2007 - 2016 Prediction of raven occurrence intersected with high impact areas for sage-grouse populations in the Great Basin, 2007-2016 (Fig. 5A) Data maps of predicted raven density and areas of potential impact to nesting sage-grouse within sagebrush ecosystems of the North American Great Basin Average and standard deviation of annual predicted raven density in the Great Basin, Western U.S. Predictions of raven occurrence in the absence of anthropogenic environmental effects in the Great Basin, 2007-2016 (Fig. 4B) Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Nevada and Wyoming, Interim