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Data

Our interdisciplinary, integrated science teams develop various data sets in support of the USGS mission areas. This information then aids natural resource managers in decision making and support of the complex issues they face in today's world. The data and tools listed here are official USGS data releases.

Filter Total Items: 291

A neutral landscape approach to evaluating the umbrella species concept for greater sage-grouse in northeast Wyoming, USA

Greater sage-grouse (Centrocercus urophasianus) has been identified as a potential umbrella species with the assumption that conservation of their habitats in sagebrush ecosystems may benefit multiple other wildlife species, but co-occurrence with an umbrella species does not necessarily guarantee species will respond positively to management for sage-grouse. This may be particularly true for ecot

Percent vegetation cover, bare ground and presence of erosional features on managed Conservation Reserve Program fields across central and western United States, 2016-2019

Data included in this data set are from edge-of-field surveys of managed fields that recorded the presence of erosional features and cover of vegetation and bare ground on 320 Conservation Reserve Program (CRP) fields across central and western United States. Field sampling data was recorded across six US Department of Agriculture Farm Production Regions (Corn belt, Lake states, Mountain, Northern

Gunnison sage-grouse predicted gene flow (conductance) surfaces, Colorado, United States

Habitat fragmentation and degradation impacts an organism's ability to navigate the landscape, ultimately resulting in decreased gene flow and increased extinction risk. Understanding how landscape composition impacts gene flow (i.e., connectivity) and interacts with scale is essential to conservation decision-making. We used a landscape genetics approach implementing a recently developed statisti

Circuit-based potential fire connectivity and relative flow patterns in the Great Basin, United States, 270 meters

The rasters in this dataset represent modeled outputs of potential fire connectivity and relative flow patterns in the Great Basin. We define ‘fire connectivity’ as the landscape’s capacity to facilitate fire transmission from one point on the landscape to another. We applied an omnidirectional circuit theory algorithm (Omniscape) to model fire connectivity in the Great Basin of the western United

Attributed North American Grid-Based Offshore Sampling Frames

This sampling frame is a set of grid-based, finite-area frames spanning the offshore areas surrounding Canada, the United States, and Mexico, and is intended for use with the North American Bat Monitoring Program (NABat). A Generalized Random-Tessellation Stratified (GRTS) Survey Design draw was added to the sample units from the raw sampling grids (https://doi.org/10.5066/P9XBOCVV). The GRTS surv

Brown treesnake movement following snake suppression in the Habitat Management Unit on Northern Guam from 2015

Animals move to locate important resources such as food, water, and mates. Therefore, movement patterns can reflect temporal and spatial availability of resources as well as when, where, and how individuals access such resources. To test these relationships for a predatory reptile, we quantified the effects of prey abundance on the spatial ecology of invasive brown treesnakes (Boiga irregularis).

Genotypes and cluster definitions for a range-wide greater sage-grouse dataset collected 2005-2017 (ver 1.1, January 2023)

Monitoring change in genetic diversity in wildlife populations across multiple scales could facilitate prioritization of conservation efforts. We used microsatellite genotypes from 7,080 previously collected genetic samples from across the greater sage-grouse (Centrocercus urophasianus) range to develop a modelling framework for estimating genetic diversity within a recently developed hierarchical

Greater sage-grouse genetic warning system, western United States (ver 1.1, January 2023)

Genetic variation is a well-known indicator of population fitness yet is not typically included in monitoring programs for sensitive species. Additionally, most programs monitor populations at one scale, which can lead to potential mismatches with ecological processes critical to species’ conservation. Recently developed methods generating hierarchically nested population units (i.e., clusters of

Predicted Pinyon Jay (Gymnorhinus cyanocephalus) densities across the western United States, 2008-2020

Management intended to benefit a target species may also affect non-target species that co-occur over space and time. Pinyon jay (Gymnorhinus cyanocephalus) populations experienced long-term declines and rely on habitat that could be lost to conifer removal programs for greater sage-grouse (Centrocercus urophasianus). Using 13 years of point count data (2008-2020) collected across the western Unit

Greater sage-grouse network-prioritized functional connectivity cumulative current map (raster)

Conserving genetic connectivity is fundamental to species persistence, yet rarely is made actionable into spatial planning for imperiled species. Climate change and habitat degradation have added urgency to embrace connectivity into networks of protected areas. Our two-step process integrates a network model with a functional connectivity model, to identify population centers important to maintain

Landscape and connectivity metrics based on invasive annual grass cover from 2016-2018 summarized at 15 kilometer grid cells in the Great Basin, USA

The spatial context of invasions is increasingly recognized as important for the success and efficiency of management actions. This information can be key for managing invasive grasses that threaten native ecosystems. We calculated landscape metrics and circuit-based centrality for invasive grasses using a source input raster of weighted-average annual herbaceous cover from 2016-2018 (Maestas et a

Metabarcode sequencing of aquatic environmental DNA from the Potomac River Watershed, 2015-2020

Biological indicator taxa have long been used for integrative assessments of water quality, particularly benthic invertebrate groups such as arthropods. While standardized protocols have been developed to calculate 'biological index' scores based on the abundances of these taxa, such systems are challenging to implement at large scales due to the sampling effort required, taxonomic expertise neede