Skip to main content
Advanced Search

Filters: Types: Downloadable (X) > Tags: {"scheme":"ISO 19115 Topic Category","name":"biota"} (X)

1,023 results (10ms)   

View Results as: JSON ATOM CSV
thumbnail
This dataset is a component of a complete package of products from the Connect the Connecticut project. Connect the Connecticut is a collaborative effort to identify shared priorities for conserving the Connecticut River Watershed for future generations, considering the value of fish and wildlife species and the natural ecosystems they inhabit. Click here to download the full data package, including all documentation. This dataset depicts the potential capability of the landscape throughout the Connecticut River Watershed to provide habitat for Ruffed Grouse (Bonasa umbellus) based on environmental conditions existing in approximately 2010. Landscape capability integrates factors influencing climate suitability,...
thumbnail
This project had two primary goals: 1) To develop a process for integrating data from multiple sources to improve predictions of climate impacts for wildlife species; and 2) To provide data on climate and related hydrological change, fire behavior under future climates, and species’ distributions for use by researchers and resource managers.We present within this report the process used to integrate species niche models, fire simulations, and vulnerability assessment methods and provide species’ reports that summarize the results of this work. Species niche model analysis provides information on species’ distributions under three climate scenarios and time periods. Niche model analysis allows us to estimate the...
thumbnail
For the Green River Basin Landscape Conservation Design (GRB LCD) assessment, we mapped the vulnerability of the sagebrush ecosystem to oil and gas development for each 12-digit hydrologic unit. Using a vulnerability framework, we defined Sensitivity (S) as the multi-scale average of sagebrush ecosystem land cover derived from LANDFIRE Existing Vegetation Type (LANDFIRE 2014). Exposure (E) to oil and gas development was quantified as the average kernel density of active oil and gas wells at multiple scales. Potential Impact (PI) is the square root transformed product of oil and gas development exposure and sagebrush ecosystem sensitivity. Adaptive Capacity (AC) for sagebrush ecosystem was quantified as the inverse...
thumbnail
For the Green River Basin Landscape Conservation Design (GRB LCD) assessment, we mapped the vulnerability of the critical habitat for threatened and endangered fish species to oil and gas development for each 12-digit hydrologic unit. The following threatened and endangered fish species were included in this vulnerability assessment: Colorado pikeminnow (Ptychocheilus lucius), Bonytail Chub (Gila elegans), Humpback chub (Gila cypha), and razorback sucker (Xyrauchen texanus). Using a vulnerability framework, we defined Sensitivity (S) as the average combined area of critical fish habitat within HUC12 polygons. Exposure (E) to oil and gas development was quantified the log transformed upstream flow accumulation of...
Categories: Data; Types: ArcGIS REST Map Service, ArcGIS Service Definition, Downloadable, Map Service; Tags: Colorado, Colorado, EARTH SCIENCE > LAND SURFACE > LANDSCAPE, Green River Basin, Green River Basin, All tags...
thumbnail
For the Green River Basin Landscape Conservation Design (GRB LCD) assessment, we mapped the vulnerability of riparian habitat for terrestrial species and process. Using a vulnerability framework, we defined Sensitivity (S) as the percent riparian vegetation within the valley bottom and Exposure (E) as the amount of human modification within the valley bottom. For each 12-digit hydrologic unit code within the GRB LCD we summarized the riparian sensitivity and exposure to human modification. We also computed Potential Impact (PI), and Adaptive Capacity (AC) metrics at the HUC12 level. PI is the square root transformed product of human modification exposure and riparian sensitivity. AC for riparian exposure to human...
thumbnail
Data on 17 metrics of shale gas development in the Pennsylvania portion of the Upper Susquehanna River basin that was collated from a variety of sources and summarized at the upstream catchment scale. Data were also standardized by upstream area and transformed into rank scores based on metric distribution and then summarized into a Disturbance Intensity Index (DII). See Maloney et al. 2018 for detailed descriptions of each data sets and limitations of data. (Maloney, K. O., J. A. Young, S. P. Faulkner, A. Hailegiorgis, E. T. Slonecker, and L. E. Milheim. 2018. A detailed risk assessment of shale gas development on headwater streams in the Pennsylvania portion of the Upper Susquehanna River Basin, U.S.A. Science...
thumbnail
The NABat sampling frame is a grid-based finite-area frame spanning Canada, the United States, and Mexico consisting of N total number of 10- by 10-km (100-km2) grid cell sample units for the continental United States, Canada, and Alaska and 5- by 5-km (25km2) for Hawaii and Puerto Rico. This grain size is biologically appropriate given the scale of movement of most bat species, which routinely travel many kilometers each night between roosts and foraging areas and along foraging routes. 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/P9M00P17). This dataset represents the final 2018 NABat Sampling grid with...
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 data release supports interpretations of field-observed root distributions within a shallow landslide headscarp (CB1) located below Mettman Ridge within the Oregon Coast Range, approximately 15 km northeast of Coos Bay, Oregon, USA. (Schmidt_2021_CB1_topo_far.png and Schmidt_2021_CB1_topo_close.png). Root species, diameter (greater than or equal to 1 mm), general orientation relative to the slide scarp, and depth below ground surface were characterized immediately following landsliding in response to large-magnitude precipitation in November 1996 which triggered thousands of landslides within the area (Montgomery and others, 2009). The enclosed data includes: (1) tests of root-thread failure as a function of...
thumbnail
This data release provides digital flight line data for a high-resolution airborne radiometric survey over parts of Montana in the vicinity of the Boulder Batholith. The airborne survey was jointly funded by the Earth Mapping Resources Initiative and Kennecott Exploration Company. The survey was designed to meet complementary needs related to geologic mapping and characterization of mineral resource potential. A total of 34,041 line km of magnetic and radiometric data were acquired over an irregular-shaped area of 6178 km2. Data were collected from a helicopter flown at a nominal terrain clearance of 100 meters (m) above topography along E-W flight lines spaced at 200 m intervals. Tie lines were flown in an N-S...
Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: AASG, Aeroradiometric survey, Airborne geophysical survey, Association of State Geologists, Boulder Mountains, All tags...
thumbnail
We developed spatial summary (GIS) layers for a study of factors influencing the distribution of cave and karst associated fauna within the Appalachian Landscape Conservation Cooperative region, one of 22 public-private partnerships established by the United States Fish and Wildlife Service to aid in developing landscape scale solutions to conservation problems (https://lccnetwork.org/lcc/appalachian). We gathered occurrence data on cave-limited terrestrial and aquatic troglobiotic species from a variety of sources within the Appalachian LCC region covering portions of 15 states. Occurrence records were developed from the scientific literature, existing biodiversity databases, personal records of the authors, museum...
thumbnail
We developed spatial summary (GIS) layers for a study of factors influencing the distribution of cave and karst associated fauna within the Appalachian Landscape Conservation Cooperative region, one of 22 public-private partnerships established by the United States Fish and Wildlife Service to aid in developing landscape scale solutions to conservation problems (https://lccnetwork.org/lcc/appalachian). We gathered occurrence data on cave-limited terrestrial and aquatic troglobiotic species from a variety of sources within the Appalachian LCC region covering portions of 15 states. Occurrence records were developed from the scientific literature, existing biodiversity databases, personal records of the authors, museum...
thumbnail
We developed spatial summary (GIS) layers for a study of factors influencing the distribution of cave and karst associated fauna within the Appalachian Landscape Conservation Cooperative region, one of 22 public-private partnerships established by the United States Fish and Wildlife Service to aid in developing landscape scale solutions to conservation problems (https://lccnetwork.org/lcc/appalachian). We gathered occurrence data on cave-limited terrestrial and aquatic troglobiotic species from a variety of sources within the Appalachian LCC region covering portions of 15 states. Occurrence records were developed from the scientific literature, existing biodiversity databases, personal records of the authors, museum...
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
This study uses growth in vegetation during the monsoon season measured from LANDSAT imagery as a proxy for measured rainfall. NDVI values from 26 years of pre- and post-monsoon season Landsat imagery were derived across Yuma Proving Ground (YPG) in southwestern Arizona, USA. The LANDSAT imagery (1986-2011) was downloaded from USGS’s GlobeVis website (http://glovis.usgs.gov/). Change in NDVI was calculated within a set of 2,843 Riparian Area Polygons (RAPs) up to 1 km in length defined in ESRI ArcMap 10.2.
thumbnail
Active channel as defined by remote sensing before (2010 and after (2011) a 40 year return period flood (December 2010) within the lower Virgin River, Nevada.
thumbnail
Digital flood-inundation maps for a 9.3-mile reach of the Iowa River along the Meskwaki Settlement, Iowa, were created by the U.S. Geological Survey (USGS) in cooperation with the Sac and Fox Tribe of the Mississippi River in Iowa. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science web site at https://water.usgs.gov/osw/flood_inundation/ depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage 05451770 on the Iowa River at County Highway E49 near Tama, Iowa. Near-real-time stages at this streamgage may be obtained on the internet from the USGS National Water Information System at https://waterdata.usgs.gov/...
This data set includes the relative production scenarios for bufflaograss [0.72(Temp) - 0.12(Precip) - 0.04(Sand) + 3.08]; this is the model from Epstein, et al. (1998). Soil texture (percent by weight) came from the Earth Systems Science Center (2008) which provided processed soils data from NRCS (gSSURGO), mean annual temperature (Celsius) and/or mean annual precipitation (millimeters) came from contemporary (1981 - 2010) estimates (Maurer et al. 2002) or a GCM. Global Climate Models (GCM) providing scenarios included: warmer-wetter scenario (CESM1-BGC, RCP4.5, Neale et al., 2010), warmer drier scenario (GISS-E2-R, RCP4.5, Schmidt, 2014), hotter-wetter scenario (Miroc-ESM, RCP8.5, Watanabe et al., 2011), and hotter-drier...
thumbnail
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
thumbnail
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...


map background search result map search result map Landscape Capability for Ruffed Grouse, CT River Watershed Cave and Karst Biota Modeling in the Appalachian LCC - Predicted Amphipods in sampled 20km grid cells Cave and Karst Biota Modeling in the Appalachian LCC - Predicted spiders in all 20km grid cells in karst Cave and Karst Biota Modeling in the Appalachian LCC - Predicted endemics in sampled 20km grid cells Mean of the Top Ten Percent of NDVI Values in the Yuma Proving Ground during Monsoon Season, 1986-2011 Shale gas data used in development of the Disturbance Intensity Index for the Pennsylvania portion of the Upper Susquehanna River basin in Maloney et al. 2018 Final Report: Vulnerability of Riparian Obligate Species in the Rio Grande to the Interactive Effects of Fire, Hydrological Variation and Climate Change Vulnerability of Riparian Habitat to Land Uses in the Green River Basin Vulnerability of Critical Fish Habitat to Oil and Gas Development in the Green River Basin Vulnerability of Sagebrush Ecosystem to Oil and Gas Development for the Green River Basin Attributed North American Bat Monitoring Program (NABat) Master Sample and Grid-Based Sampling Frame: Mexico 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 7 (Wyoming), Interim Flood-inundation depth grids for the Iowa River at the Meskwaki Settlement in Iowa, 2019 Active channel in the Lower Virgin River before and after a 40 yr flood (December 2010) DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Myrtle Island, VA, 2014 DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Smith Island, VA, 2014 Root thread strength, landslide headscarp geometry, and observed root characteristics at the monitored CB1 landslide, Oregon, USA Airborne radiometric survey, Boulder Batholith region, Montana, 2022 Root thread strength, landslide headscarp geometry, and observed root characteristics at the monitored CB1 landslide, Oregon, USA DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Myrtle Island, VA, 2014 Flood-inundation depth grids for the Iowa River at the Meskwaki Settlement in Iowa, 2019 DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Smith Island, VA, 2014 Active channel in the Lower Virgin River before and after a 40 yr flood (December 2010) Mean of the Top Ten Percent of NDVI Values in the Yuma Proving Ground during Monsoon Season, 1986-2011 Airborne radiometric survey, Boulder Batholith region, Montana, 2022 Shale gas data used in development of the Disturbance Intensity Index for the Pennsylvania portion of the Upper Susquehanna River basin in Maloney et al. 2018 Landscape Capability for Ruffed Grouse, CT River Watershed Final Report: Vulnerability of Riparian Obligate Species in the Rio Grande to the Interactive Effects of Fire, Hydrological Variation and Climate Change Vulnerability of Critical Fish Habitat to Oil and Gas Development in the Green River Basin Vulnerability of Sagebrush Ecosystem to Oil and Gas Development for the Green River Basin Vulnerability of Riparian Habitat to Land Uses in the Green River Basin 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 7 (Wyoming), Interim Cave and Karst Biota Modeling in the Appalachian LCC - Predicted endemics in sampled 20km grid cells Cave and Karst Biota Modeling in the Appalachian LCC - Predicted Amphipods in sampled 20km grid cells Cave and Karst Biota Modeling in the Appalachian LCC - Predicted spiders in all 20km grid cells in karst Attributed North American Bat Monitoring Program (NABat) Master Sample and Grid-Based Sampling Frame: Mexico