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This data set includes geospatial data and tables providing location, environmental, and vegetation data collected in 2017 and 2018 at the Little Saint Francis River chat pile restoration site, Fredericktown, Madison County, Missouri. Restoration actions are being implemeneted as part of the settlement for the Madison County Mines Superfund site to compensate the public for losses of natural resources and the services they provide as part of the Natural Resource Damage Assessment and Restoration Southeast Missouri Lead Mining District case. Data were collected prior to and during the early stages of restoration actions to restore bottomland forest habitat, reduce invasive plant species abundance, and improve upland...
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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...
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This dataset represents the variety (unique structural classes: water, bare, herbaceous, short shrubs, medium shrubs, short trees, tall trees) within 1 ha of bottomland areas. Traditional image interpretation cues were used to develop the polygons, such as shape, size, pattern, tone, texture, color, and shadow, from high resolution, true color, aerial imagery (0.3m resolution), acquired for the project. Additional, public available aerial photos (NAIP, 2011) were used to cross-reference cover classes. As with any digital layer, this layer is a representation of what is actually occurring on the ground. Errors are inherent in any interpretation of ground qualities. Due to the "snapshot" nature of the aerial photos,...
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This dataset represents the relative average amount of non-woody cover within 2 ha) of bottomland along the Colorado River from the Colorado state line (San Juan and Grand Counties, Utah) to the southern Canyonlands NP boundary, as of September 2010. Traditional image interpretation cues were used to develop the polygons, such as shape, size, pattern, tone, texture, color, and shadow, from high resolution, true color, aerial imagery (0.3m resolution), acquired for the project. Additional, public available aerial photos (NAIP, 2011) were used to cross-reference cover classes. As with any digital layer, this layer is a representation of what is actually occurring on the ground. Errors are inherent in any interpretation...
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This dataset represents ease of access to bottomland areas for vegetation treatments. Access may be by road, 4x4 near road, hike in by field crews or requiring overnight camping or raft access. Access is considered for each side of the river separately.
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This data set shows the extent of the Colorado River Conservation Planning project bottomland area as delineated by topography and vegetation, The bottomland area is subdivided into 1 km polygons measured from the upstream project boundary. Reach breaks were determined by large topographic shifts and/or tributary junctions by John Dohrenwend. Please see the project report for more details.
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This is a model showing general habitat diversity, including both the structural and cover type diversity. See Open File Report, Rasmussen and Shafroth, Colorado River Conservation Planning for geoprocessing details.
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This map shows the channel boundary (2011) of the Colorado River mainstem between the Utah Colorado border and the upper pool of Lake Powell, Utah (146 miles). The channel boundary was mapped from public available NAIP imagery flown on June 28, 2011, when the river flow was 886 m3/s at the Cisco gage. The channel is subdivided into channel types: fast water (main channel, secondary channel), and still water types (backwater, isolated pool and tributary channel).
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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...
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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.
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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...
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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.
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We used the 1981 historical imagery of the Escalante River, Utah in ArcGIS to quantify channel area and average width and quantify woody riparian vegetation cover in two reaches of the river. Reach 1 was approximately 15 river kilometers (rkms) long and located between Sand and Boulder creeks within Grand Staircase Escalante National Monument. Reach 2 was approximately 16 rkms in length, extending from the Glen Canyon National Recreation Area boundary to just upstream of Choprock Canyon. We delineated the extent of active channel. Active channel was defined as the portion of the channel free of vegetation. We also delineated fluvial geomorphic features such as point bars, mid-channel bars, lateral bars and floodplain....
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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...
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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...
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The Denver fossil algae database were gathered from the inception of Denver Region in 1953 by Richard Rezak. His specialty was algae, carbonate platforms, and off-shore modern reefs. He developed a very useful litho-stratigraphic tool while studying Proterozoic algae and stromatolites in Glacier National Park. This lead to his studies of modern analogs in the Caribbean and South Seas. His catalogs were converted into digital form, Excel and Filemaker Pro database. The Catalog consist of 1001 fossil localities. His supplementary data has been added whenever possible - sources field map locality points, E&R files with enhanced faunal lists, as well as formal publications
Mule deer in the South Tuscarora herd are part of the larger “Area 6” deer population that reside in the southern and eastern portion of this big game Management Area (MA 6). The winter range for this sub population is located along the western slopes of the Tuscarora Mountains and the Dunphy Hills. The spring migration route for this deer herd traverses north along the toe slopes of the Tuscarora Mountains on the east side and narrows to approximately 600 meters at one pinch point near the Carlin -Pete Mine area. The migration route generally spans about 30 miles to the northeast to higher elevations in the northern Tuscarora Mountains. Important stopover areas include Richmond Mountain, Jack and Little Jack Creeks,...
Mule deer in the Izzenhood herd are part of a larger population known in Nevada as the “Area 6” mule deer population. They primarily reside on winter ranges in the Izzenhood Basin and upper Rock Creek drainages in western Elko County and northern Lander County. From their winter range, mule deer in this sub population migrate approximately 70 miles to summer ranges in the northern Independence Mountains and Bull Run Basin area. Some of the most important stopover areas are located near upper Rock Creek, Toe Jam Mountain, and Chicken Creek Summit. Challenges to this deer herd include past wildfires on winter range, conversion of native shrub habitats to exotic annual grasses, and lower primary production in some...


map background search result map search result map Mean of the Top Ten Percent of NDVI Values in the Yuma Proving Ground during Monsoon Season, 1986-2011 Conservation Planning for the Colorado River in Utah - Stillness of water for Bat Watering Model Conservation Planning for the Colorado River in Utah - General Diversity Model Output Data for Colorado River in Utah Conservation Planning for the Colorado River in Utah - Diversity of All Structural Types for General Diversity Model Conservation Planning for the Colorado River in Utah - Open Areas for Open Land Species Model Conservation Planning for the Colorado River in Utah - Access to the Site for Relative Cost of Restoration Model Cottonwood Lake Study Area-Wetland Vegetation Zones-1986 Cottonwood Lake Study Area-Wetland Vegetation Zones-1990 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 Conservation Planning for the Colorado River in Utah - Bottomland Boundary of the Colorado River Divided at Homogeneous River Reaches A polygon shapefile of bottomland vegetation cover and geomorphic features of the Escalante River, Utah mapped from 1981 aerial imagery Attributed North American Bat Monitoring Program (NABat) Master Sample and Grid-Based Sampling Frame: Mexico Pre-restoration vegetation data, Little Saint Francis River chat pile site, Missouri, USA, 2017 and 2018 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 USGS Denver Micro-fossil collection: Fossil Algae 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: Smith Island, VA, 2014 Migration Routes of Mule Deer in the Izzenhood Herd in Nevada Migration Routes of Mule Deer in the South Tuscarora Mountains in Nevada Cottonwood Lake Study Area-Wetland Vegetation Zones-1986 Pre-restoration vegetation data, Little Saint Francis River chat pile site, Missouri, USA, 2017 and 2018 Cottonwood Lake Study Area-Wetland Vegetation Zones-1990 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 A polygon shapefile of bottomland vegetation cover and geomorphic features of the Escalante River, Utah mapped from 1981 aerial imagery 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 Conservation Planning for the Colorado River in Utah - Stillness of water for Bat Watering Model Conservation Planning for the Colorado River in Utah - Open Areas for Open Land Species Model Conservation Planning for the Colorado River in Utah - General Diversity Model Output Data for Colorado River in Utah Conservation Planning for the Colorado River in Utah - Diversity of All Structural Types for General Diversity Model Conservation Planning for the Colorado River in Utah - Access to the Site for Relative Cost of Restoration Model Conservation Planning for the Colorado River in Utah - Bottomland Boundary of the Colorado River Divided at Homogeneous River Reaches Migration Routes of Mule Deer in the South Tuscarora Mountains in Nevada Migration Routes of Mule Deer in the Izzenhood Herd in Nevada 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 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 Attributed North American Bat Monitoring Program (NABat) Master Sample and Grid-Based Sampling Frame: Mexico USGS Denver Micro-fossil collection: Fossil Algae