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Federal
BLM Natl WesternUS GRSG ROD HabitatMgmtAreas Feb 2025
Department of the Interior —
This dataset represents the consolidated submissions of GRSG habitat management areas from each individual BLM ARMP & ARMPA/Records of Decision (ROD) and for... -
Federal
2019 Annual Data Files: Centennial Valley Arctic Grayling Adaptive Management Project, 2011-present
Department of the Interior —
2019's Annual Data files have been uploaded as several digital holdings with data used to support the creation of the Centennial Valley Arctic Grayling Adaptive... -
Federal
Gunnison sage-grouse predicted gene flow (conductance) surfaces, Colorado, United States
Department of the Interior —
Habitat fragmentation and degradation impacts an organism's ability to navigate the landscape, ultimately resulting in decreased gene flow and increased extinction... -
Federal
Horizontal and vertical accuracy assessments of digital surface model (DSM) and digital elevation model (DEM) data for the Colorado River corridor in Grand Canyon National Park and Glen Canyon National Recreation Area (2002, 2009, 2013 and 2021)
Department of the Interior —
The horizontal accuracy assessment dataset consists of spatial coordinate and elevation values of “hard points” identified in each digital surface model (DSM) dataset... -
Federal
Various Lake Powell data used for predicting smallmouth bass entrainment rates and population growth based on thermal suitability below and downstream of Glen Canyon Dam
Department of the Interior —
These data were compiled to create models that estimate entrainment rates and population growth rates of smallmouth bass below Glen Canyon Dam. Objective(s) of our... -
Federal
Trends and a Targeted Annual Warning System for Greater Sage-Grouse in the Western United States (ver. 4.0, November 2025)
Department of the Interior —
Greater sage-grouse (Centrocercus urophasianus; hereafter sage-grouse) are at the center of state and national land-use policies largely because of their unique life-... -
Federal
Climate Change Vulnerability Index Release 4.0: Excel Workbook
Department of the Interior —
The Climate Change Vulnerability Index (CCVI) uses a scoring system that integrates a species’ exposure to projected climate change within an assessment area,... -
Federal
Data for Gull-billed Tern and Black Skimmer Bayesian Network Model - Soil Textures and Topography Index
Department of the Interior —
This U.S. Geological Survey (USGS) data release represents tabular and geospatial data for characterizing the soil texture and topography that may be relevant to... -
Federal
Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Nevada and Wyoming, Interim
Department of the Interior —
We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring... -
Federal
Digital surface model (DSM) data for the Colorado River corridor in Grand Canyon National Park and Glen Canyon National Recreation Area (2013)
Department of the Interior —
The 2013 Digital Surface Model (DSM) dataset consists of single band rasters at 1-meter pixel resolution that were generated to orthorectify a four band ortho imagery... -
Federal
Digital Elevation Model
Department of the Interior —
Bathymetric, topographic, and grain-size data were collected in April 2011 along a 27-mi (43.5 – km) reach of the Colorado River in Grand Canyon National Park,... -
Federal
Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Nevada and Wyoming, Interim
Department of the Interior —
We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring... -
Federal
Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Nevada and Wyoming, Interim
Department of the Interior —
We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring... -
Federal
Data for Gulf Sturgeon Bayesian Network Model
Department of the Interior —
This USGS data release represents tabular and geospatial data for the Gulf Sturgeon Bayesian Network Model. The Gulf Sturgeon is a federally listed, anadromous... -
Federal
Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Nevada and Wyoming, Interim
Department of the Interior —
We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring... -
Federal
Data for Brown Pelican Bayesian Network Model
Department of the Interior —
This U.S. Geological Survey (USGS) data release represents data for the creation of a spatially explicit Bayesian network model that predicts Brown Pelican nests on... -
Federal
Martin & Johnson - Supplementary data
U.S. Environmental Protection Agency —
This dataset includes: (i) all sample removal rate predictions for each advanced on-site wastewater treatment system technology we analyzed; and (ii) all sample total... -
Federal
Hierarchically nested and biologically relevant range-wide monitoring frameworks for greater sage-grouse, western United States
Department of the Interior —
We produced 13 hierarchically nested cluster levels that reflect the results from developing a hierarchical monitoring framework for greater sage-grouse across the... -
Federal
Bayesian network model detection casefile
Department of the Interior —
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... -
Federal
Data from: Decision science as a framework for combining geomorphological and ecological modeling for the management of coastal systems
Department of the Interior —
Coastal management decisions are complex and include challenging tradeoffs. Decision science offers a useful framework to address such complex problems. We illustrate...