AndreaBozzo/ceres-open-data-index huggingface dataset:
Greater sage-grouse betweenness centrality of fully connected population structure in the western United States

The betweenness (bc; grsg_lcp_betweenness_centrality) defines the importance of a node in a graph based on how many times it occurs in the shortest path between all pairs of nodes. In other words, a node is important if it is included in many shortest paths between other nodes because it serves as a bridge between different parts of the graph. The data were defined from least-cost paths (LCPs) constructed into minimum spanning trees (MSTs). The bc identified major corridors spanning the sage-grouse range where nodes had a larger number of connections with other nodes, reflecting regions where leks potentially play larger roles of sage-grouse continuity based on graph theory analytics. We identified a threshold of the bc normalized value (&gt;0.028) where patterns of network connectivity occurred in our graph. Leks identified with a bc value greater than our threshold were buffered by 15 km (inter-patch movement distance and distance of genetic flow), resulting in this dataset. Betweenness centrality captured corridors of leks with a higher density of sage-grouse, which we used to evaluate our derived population structure.
Understanding wildlife population structure and connectivity can help managers identify conservation strategies, as structure can facilitate the study of population changes and habitat connectivity can provide information on dispersal and biodiversity. We developed an approach to define hierarchical population structure (in other words, demarcation of subpopulations) using graph theory (in other words, connectivity) from an amalgamation of biological inferences encompassing dispersal capabilities based on movements and genetic flow, seasonal habitat conditions, and functional processes (for example, selection of habitat at multiple scales) affecting movements. We applied our approach to greater sage-grouse (Centrocercus urophasianus), an upland gamebird species of conservation concern in western United States. We defined sage-grouse population structure by creating a cost surface, informed from functional processes of habitat characteristics to account for the resistance of inter-patch movements, and developing least-cost paths (LCP) between breeding habitat sites (leks). The least-cost paths were combined into a multi-path graph construct for which we then used information on potential connectivity (dispersal distances) and functional connectivity (permeability of fragmented landscapes based on selection preferences) to decompose the graph into structures of subpopulations.

Tags: betweenness, biota, california, centrality-measures, centrocercus-urophasianus, colorado, connectivity-structural-functional-potential, greater-sage-grouse, idaho, least-cost-paths, montana, nevada, north-dakota, oregon, population-structure, south-dakota, united-states, usgs-62ba23e1d34e8f4977cc9fd6, utah, washington, western-united-states, wyoming
Organization: Department of the Interior
Greater sage-grouse population structure (finest-scaled, tier one) in the western United States

This data, grsg_lcp_ThiessenPoly_mst1, is one of five hierarchical delineations of greater sage-grouse population structure. The data represent Thiessen polygons of graph constructs (least-cost path minimum spanning tree [LCP-MST]) that defined our population structure of sage-grouse breeding sites in the western United States. This data was developed by applying dispersal and genetic rules to decompose the fully connected population structure (graph) into the product presented here.
Understanding wildlife population structure and connectivity can help managers identify conservation strategies, as structure can facilitate the study of population changes and habitat connectivity can provide information on dispersal and biodiversity. We developed an approach to define hierarchical population structure (in other words, demarcation of subpopulations) using graph theory (in other words, connectivity) from an amalgamation of biological inferences encompassing dispersal capabilities based on movements and genetic flow, seasonal habitat conditions, and functional processes (for example, selection of habitat at multiple scales) affecting movements. We applied our approach to greater sage-grouse (Centrocercus urophasianus), an upland gamebird species of conservation concern in western United States. We defined sage-grouse population structure by creating a cost surface, informed from functional processes of habitat characteristics to account for the resistance of inter-patch movements, and developing least-cost paths between breeding habitat sites (leks). The least-cost paths were combined into a multi-path graph construct for which we then used information on potential connectivity (dispersal distances) and functional connectivity (permeability of fragmented landscapes based on selection preferences) to decompose the graph into structures of subpopulations.

Tags: biota, california, centrality-measures, centrocercus-urophasianus, colorado, connectivity-structural-functional-potential, greater-sage-grouse, hierarchical-population-structure, idaho, least-cost-paths, montana, nevada, north-dakota, oregon, population-structure, south-dakota, united-states, usgs-62ba2694d34e8f4977cc9fe9, utah, washington, western-united-states, wyoming
Organization: Department of the Interior
Greater sage-grouse population structure (fine-scaled, tier two) in the western United States

This data, grsg_lcp_ThiessenPoly_mst2, is one of five hierarchical delineations of greater sage-grouse population structure. The data represent Thiessen polygons of graph constructs (least-cost path minimum spanning tree [LCP-MST]) that defined our population structure of sage-grouse breeding sites in the western United States. This data was developed by applying dispersal and genetic rules to decompose the fully connected population structure (graph) into the product presented here.
Understanding wildlife population structure and connectivity can help managers identify conservation strategies, as structure can facilitate the study of population changes and habitat connectivity can provide information on dispersal and biodiversity. We developed an approach to define hierarchical population structure (in other words, demarcation of subpopulations) using graph theory (in other words, connectivity) from an amalgamation of biological inferences encompassing dispersal capabilities based on movements and genetic flow, seasonal habitat conditions, and functional processes (for example, selection of habitat at multiple scales) affecting movements. We applied our approach to greater sage-grouse (Centrocercus urophasianus), an upland gamebird species of conservation concern in western United States. We defined sage-grouse population structure by creating a cost surface, informed from functional processes of habitat characteristics to account for the resistance of inter-patch movements, and developing least-cost paths between breeding habitat sites (leks). The least-cost paths were combined into a multi-path graph construct for which we then used information on potential connectivity (dispersal distances) and functional connectivity (permeability of fragmented landscapes based on selection preferences) to decompose the graph into structures of subpopulations.

Tags: biota, california, centrality-measures, centrocercus-urophasianus, colorado, connectivity-structural-functional-potential, greater-sage-grouse, hierarchical-population-structure, idaho, least-cost-paths, montana, nevada, north-dakota, oregon, population-structure, south-dakota, united-states, usgs-62ba26f9d34e8f4977cc9ff0, utah, washington, western-united-states, wyoming
Organization: Department of the Interior
Greater sage-grouse population structure (moderate-scaled, tier three) in the western United States

This data, grsg_lcp_ThiessenPoly_mst3, is one of five hierarchical delineations of greater sage-grouse population structure. The data represent Thiessen polygons of graph constructs (least-cost path minimum spanning tree [LCP-MST]) that defined our population structure of sage-grouse breeding sites in the western United States. This data was developed by applying dispersal and genetic rules to decompose the fully connected population structure (graph) into the product presented here.
Understanding wildlife population structure and connectivity can help managers identify conservation strategies, as structure can facilitate the study of population changes and habitat connectivity can provide information on dispersal and biodiversity. We developed an approach to define hierarchical population structure (in other words, demarcation of subpopulations) using graph theory (in other words, connectivity) from an amalgamation of biological inferences encompassing dispersal capabilities based on movements and genetic flow, seasonal habitat conditions, and functional processes (for example, selection of habitat at multiple scales) affecting movements. We applied our approach to greater sage-grouse (Centrocercus urophasianus), an upland gamebird species of conservation concern in western United States. We defined sage-grouse population structure by creating a cost surface, informed from functional processes of habitat characteristics to account for the resistance of inter-patch movements, and developing least-cost paths between breeding habitat sites (leks). The least-cost paths were combined into a multi-path graph construct for which we then used information on potential connectivity (dispersal distances) and functional connectivity (permeability of fragmented landscapes based on selection preferences) to decompose the graph into structures of subpopulations.

Tags: biota, california, centrality-measures, centrocercus-urophasianus, colorado, connectivity-structural-functional-potential, greater-sage-grouse, hierarchical-population-structure, idaho, least-cost-paths, montana, nevada, north-dakota, oregon, population-structure, south-dakota, united-states, usgs-62ba276bd34e8f4977cc9ff2, utah, washington, western-united-states, wyoming
Organization: Department of the Interior
Greater sage-grouse population structure (coarsest-scaled, tier four) in the western United States

This data, grsg_lcp_ThiessenPoly_mst4, is one of five hierarchical delineations of greater sage-grouse population structure. The data represent Thiessen polygons of graph constructs (least-cost path minimum spanning tree [LCP-MST]) that defined our population structure of sage-grouse breeding sites in the western United States. This data was developed by applying dispersal and genetic rules to decompose the fully connected population structure (graph) into the product presented here.
Understanding wildlife population structure and connectivity can help managers identify conservation strategies, as structure can facilitate the study of population changes and habitat connectivity can provide information on dispersal and biodiversity. We developed an approach to define hierarchical population structure (in other words, demarcation of subpopulations) using graph theory (in other words, connectivity) from an amalgamation of biological inferences encompassing dispersal capabilities based on movements and genetic flow, seasonal habitat conditions, and functional processes (for example, selection of habitat at multiple scales) affecting movements. We applied our approach to greater sage-grouse (Centrocercus urophasianus), an upland gamebird species of conservation concern in western United States. We defined sage-grouse population structure by creating a cost surface, informed from functional processes of habitat characteristics to account for the resistance of inter-patch movements, and developing least-cost paths between breeding habitat sites (leks). The least-cost paths were combined into a multi-path graph construct for which we then used information on potential connectivity (dispersal distances) and functional connectivity (permeability of fragmented landscapes based on selection preferences) to decompose the graph into structures of subpopulations.

Tags: biota, california, centrality-measures, centrocercus-urophasianus, colorado, connectivity-structural-functional-potential, greater-sage-grouse, hierarchical-population-structure, idaho, least-cost-paths, montana, nevada, north-dakota, oregon, population-structure, south-dakota, united-states, usgs-62ba27cdd34e8f4977cc9ff6, utah, washington, western-united-states, wyoming
Organization: Department of the Interior
Nearshore surface sediment metals, grain size, and organic carbon content, Sinclair Inlet near the Bremerton Naval Complex, 2021

Between May 24 and 26, 2020, five sediment samples were collected with a pre-cleaned (acid-washed) hand-push corer into WhirlPak bags for analysis of grain size and organic carbon at the USGS Pacific Coastal Marine Science Center and Whirlpack bags for drying at the USGS Washington Water Science Center before analysis for metals and ions at AGAT Labs.

Tags: chemical-analysis, environment, heavy-metal-pollution, sediment-geochemistry, sediment-pollutant-interaction, usgs-62bf2e3bd34e82c548ced901
Organization: Department of the Interior
Greater sage-grouse population structure (fully connected, tier five) in the western United States

This data, grsg_lcp_ThiessenPoly_mst5, is one of five hierarchical delineations of greater sage-grouse population structure. The data represent Thiessen polygons of graph constructs (least-cost path minimum spanning tree [LCP-MST]) that defined our population structure of sage-grouse breeding sites in the western United States. This data was developed by applying dispersal and genetic rules to decompose the fully connected population structure (graph) into the product presented here.
Understanding wildlife population structure and connectivity can help managers identify conservation strategies, as structure can facilitate the study of population changes and habitat connectivity can provide information on dispersal and biodiversity. We developed an approach to define hierarchical population structure (in other words, demarcation of subpopulations) using graph theory (in other words, connectivity) from an amalgamation of biological inferences encompassing dispersal capabilities based on movements and genetic flow, seasonal habitat conditions, and functional processes (for example, selection of habitat at multiple scales) affecting movements. We applied our approach to greater sage-grouse (Centrocercus urophasianus), an upland gamebird species of conservation concern in western United States. We defined sage-grouse population structure by creating a cost surface, informed from functional processes of habitat characteristics to account for the resistance of inter-patch movements, and developing least-cost paths between breeding habitat sites (leks). The least-cost paths were combined into a multi-path graph construct for which we then used information on potential connectivity (dispersal distances) and functional connectivity (permeability of fragmented landscapes based on selection preferences) to decompose the graph into structures of subpopulations.

Tags: biota, california, centrality-measures, centrocercus-urophasianus, colorado, connectivity-structural-functional-potential, greater-sage-grouse, hierarchical-population-structure, idaho, least-cost-paths, montana, nevada, north-dakota, oregon, population-structure, south-dakota, united-states, usgs-62ba2881d34e8f4977cc9ffc, utah, washington, western-united-states, wyoming
Organization: Department of the Interior
USGS occupancy surveys for Dixie Valley Toads, Anaxyrus williamsi, in Churchill County, Nevada from April 2018 to May 2021

Desert spring wetlands host many endemic species that require aquatic habitat and are isolated by the surrounding xeric terrestrial habitat. The Dixie Valley Toad (Anaxyrus williamsi) is a recently described anuran species endemic to desert spring wetlands in the Dixie Valley, Churchill County, Nevada, USA. Given this species was only recently recognized as distinct from Anaxyrus boreas, little is known about its ecology and habitat requirements. These data represent the results of surveys for Dixie Valley Toads conducted from April 2018 to May 2021 in Churchill County, Nevada, USA and associated covariates from surveys and study sites. The potential wetland habitat for the Dixie Valley Toad was divided into 20 meter by 20 meter cells, and 60 cells were selected for sampling using a Generalized Random Tessellation Stratified design. The data were collected following an occupancy study design, with repeated (secondary) surveys of each cell during each primary period (6 total periods). For each cell in each survey, the detection or nondetection of adult and larval Dixie Valley Toads was recorded. Adult Dixie Valley Toads were detected in 75 percent of cells during at least one survey, and larval Dixie Valley Toads were detected in 20 percent of cells during at least one survey. Data on water temperature, air temperature, percent of the cell with surface water, water depth, and emergent vegetation cover were also recorded during surveys.

Tags: amphibians, bayesian, biota, ecology, modeling, occupancy, population-dynamics, usgs-62ba2f7cd34e8f4977cca02e
Organization: Department of the Interior
Pre-mining environmental baseline characterization of the Balkhab copper deposit: 2019 field season

These data include geochemical analyses of rock, mine waste, soil, sediment, and water samples collected from the Balkhab copper deposit, Sar-e Pol Province, Afghanistan in 2019.

Tags: environmental-chemistry, geochemistry, usgs-62baebb1d34ee89031625e5e
Organization: Department of the Interior
Stable isotope and video observational data from the RL1905 EXPRESS expedition in 2019

Data to support the site characterization of locations sampled along the continental shelf and slope of the western U.S. coast off Washington, Oregon and California during the EXPRESS RL1905 expedition in 2019. Data consisted of tissue samples from fauna, sediments and particulate organic matter. These samples were analyzed for stable carbon and nitrogen isotopes to examine food web ecology. Additional observational data were collected through video analyses with efforts focused on documenting counts of fauna other than corals, sponges and fishes, as well as general habitat characteristics.

Tags: benthic-ecosystems, benthos, biota, california, corals, food-web, isotopic-analysis, oregon, pacific-ocean, usgs-62baf2aad34ee89031625e6c, washington
Organization: Department of the Interior
Historical genetic resources for Northwestern Atlantic and Caribbean populations of Roseate Tern Sterna dougallii, 1879-1940

Here we provide public access to UCE DNA sequences for all genetic samples in Byerly et al. 2022.

Tags: biota, caribbean-islands, dna-sequencing, evolution, florida, genotype, maine-coastal, massachusetts-rhode-island-coastal, new-york, nova-scotia, usgs-62bb5d44d34ee89031625fb2
Organization: Department of the Interior
Data for Brown Pelican Bayesian Network Model

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 islands across the U.S. portion of the Gulf of Mexico.
Well-targeted management plans are needed to achieve Brown Pelican population objectives (number of breeding pairs) because conservation and restoration opportunities are limited and costly. To aid the design of such plans, we estimated population objectives for 10 U.S. Fish and Wildlife Service Gulf Coast Biological Planning Units (BPUs). We then developed a Bayesian network model that uses an island’s characteristics to predict pelican nest count, a proxy measure for breeding pairs. We used the model and 2000-2015 bird survey data to estimate each BPU’s total nest count given the existing islands’ characteristics. We then used the model to hypothesize island-specific actions and simulate management scenarios that implemented these actions opportunistically (randomly selected islands) or strategically (target islands with the highest nest count) until the population objective was met. We then estimated each BPU’s (1) total number of islands; (2) total nesting, roosting, and loafing habitat needed to achieve its population objective (habitat objective); and (3) the effort required to achieve the habitat objective (management efficiency).

Tags: adaptive-management, barrier-island, bayesian-network, coastal-ecosystems, conceptual-modeling, environment, gulf-of-mexico, habitats, natural-resource-management, population-and-community-ecology, recovery-objectives, species-conservation, strategic-habitat-conservation, united-states, usgs-62bb5e3bd34ee89031625fe3, wildlife-population-management
Organization: Department of the Interior
2. Fiber Optic Distributed Temperature Sensing survey along the unwalled shoreline of Operable Unit A, Bremerton Naval Complex, WA, July 30 - August 11, 2020

This data release child item contains fiber-optic distributed temperature sensor (FO-DTS) data collected along the western unwalled shoreline of the Bremerton Naval Complex, Bremerton, Washington, USA from July 30, 2020, to August 11, 2020. Continuous profiles of water temperature   were collected along a spatially georeferenced fiber optic cable deployed in an out-and-back U-shape with approximately 2- meter distance between the parallel cable lengths by a Sensornet® Oryx DTS FO-DTS (Fiber-optic distributed temperature sensor). Data were collected in a single ended configuration with two channels, Channel_1 and Channel_2, where water temperature was spatially averaged over 1.01- meter linear intervals by the Oryx instrument and collected at 15-minute intervals. Only the Channel_1 data were used for hydrologic interpretation and are contained in this release. Independent water-temperature data was collected at four locations by Hobo® Water Temp Pro v2 data-logging thermistors. Water-temperature data from thermistors were used as an independent water-temperature data calibration-check that was collected by data-logging thermistors verified by a National Institute of Standards and Technology (NIST)-certified thermistor with an accuracy of ±0.1 °C. A subset consisting of Channel_1 data from July 30, 2020 to August 7, 2020 was used for data visualization. This data was used to identify cold-water locations where groundwater, potentially containing elevated levels of metals and other toxic contaminants, may be discharging to Sinclair Inlet. The three zip folders contain: 
1. "RAW_Data", which are the Oryx machine data text files (.ddf) from the fiber-optic temperature sensing tool measured with a time-series. These files include all data collected on Channel_1 by the fiber-optic distributed temperature sensor during its deployment along the longitudinal profile and internal instrument noise.
2. "Independant_Temperature_Data", which contains data collected independently by temperature data loggers during deployment. 
3. "Visualization_Data", which contains geospatial data of points along the fiber-optic cable and USGS-DTSGUI (Domanski, et al., 2019) output files of FO-DTS temperature profiles by time and location.

Tags: contaminants, environment, groundwater, pathways, seepage, temperature, usgs-62bb7c99d34e88efc5245d18
Organization: Department of the Interior
Mercury Isotopes, total mercury, and supporting data in particulate samples from the Bremerton Naval Complex or surface sediment from Sinclair Inlet or representative bays, Puget Sound, Washington, 2008-09 and 2018-19

Twenty-eight samples of new (2018-19) or archived (2008-09) particulate material from the Bremerton Naval Complex or surface sediment from Sinclair Inlet or representative bays in Puget Sound were analyzed for total mercury and mercury isotopes.

Tags: biota, mercury, usgs-62bb7d34d34e88efc5245d1b
Organization: Department of the Interior