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Region(s) of distribution of Hamecon (Artediellus scaber) Knipowitsch, 1907 in the Arctic as digitized for U.S. Geological Survey Scientific Investigations Report 2016-5038. For details on the project and purpose, see the report at https://doi.org/10.3133/sir20165038. Complete metadata for the collection of species datasets is in the metadata document "Dataset_for_Alaska_Marine_Fish_Ecology_Catalog.xml" at https://doi.org/10.5066/F7M61HD7. Source(s) for this digitized data layer are listed in the metadata Process Steps section. Note that the original source may show an extended area; some datasets were limited to the published map boundary. Distributions of marine fishes are shown in adjacent Arctic seas where reliable...
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Region(s) of distribution of Saffron Cod (Eleginus gracilis) (Tilesius, 1810) in the Arctic as digitized for U.S. Geological Survey Scientific Investigations Report 2016-5038. For details on the project and purpose, see the report at https://doi.org/10.3133/sir20165038. Complete metadata for the collection of species datasets is in the metadata document "Dataset_for_Alaska_Marine_Fish_Ecology_Catalog.xml" at https://doi.org/10.5066/F7M61HD7. Source(s) for this digitized data layer are listed in the metadata Process Steps section. Note that the original source may show an extended area; some datasets were limited to the published map boundary. Distributions of marine fishes are shown in adjacent Arctic seas where...
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Region(s) of distribution of Fourhorn Poacher (Hypsagonus quadricornis) (Valenciennes, 1829) in the Arctic as digitized for U.S. Geological Survey Scientific Investigations Report 2016-5038. For details on the project and purpose, see the report at https://doi.org/10.3133/sir20165038. Complete metadata for the collection of species datasets is in the metadata document "Dataset_for_Alaska_Marine_Fish_Ecology_Catalog.xml" at https://doi.org/10.5066/F7M61HD7. Source(s) for this digitized data layer are listed in the metadata Process Steps section. Note that the original source may show an extended area; some datasets were limited to the published map boundary. Distributions of marine fishes are shown in adjacent Arctic...
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Region(s) of distribution of Fourhorn Sculpin (Myoxocephalus quadricornis) (Linnaeus, 1758) in the Arctic as digitized for U.S. Geological Survey Scientific Investigations Report 2016-5038. For details on the project and purpose, see the report at https://doi.org/10.3133/sir20165038. Complete metadata for the collection of species datasets is in the metadata document "Dataset_for_Alaska_Marine_Fish_Ecology_Catalog.xml" at https://doi.org/10.5066/F7M61HD7. Source(s) for this digitized data layer are listed in the metadata Process Steps section. Note that the original source may show an extended area; some datasets were limited to the published map boundary. Distributions of marine fishes are shown in adjacent Arctic...
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Region(s) of distribution of Eyeshade Sculpin (Nautichthys pribilovius) (Jordan & Gilbert, 1898) in the Arctic as digitized for U.S. Geological Survey Scientific Investigations Report 2016-5038. For details on the project and purpose, see the report at https://doi.org/10.3133/sir20165038. Complete metadata for the collection of species datasets is in the metadata document "Dataset_for_Alaska_Marine_Fish_Ecology_Catalog.xml" at https://doi.org/10.5066/F7M61HD7. Source(s) for this digitized data layer are listed in the metadata Process Steps section. Note that the original source may show an extended area; some datasets were limited to the published map boundary. Distributions of marine fishes are shown in adjacent...
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Region(s) of distribution of Chinook Salmon (Oncorhynchus tshawytscha) (Walbaum, 1792) in the Arctic as digitized for U.S. Geological Survey Scientific Investigations Report 2016-5038. For details on the project and purpose, see the report at https://doi.org/10.3133/sir20165038. Complete metadata for the collection of species datasets is in the metadata document "Dataset_for_Alaska_Marine_Fish_Ecology_Catalog.xml" at https://doi.org/10.5066/F7M61HD7. Source(s) for this digitized data layer are listed in the metadata Process Steps section. Note that the original source may show an extended area; some datasets were limited to the published map boundary. Distributions of marine fishes are shown in adjacent Arctic seas...
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Region(s) of distribution of Inconnu (Stenodus leucichthys) (Güldenstadt, 1772) in the Arctic as digitized for U.S. Geological Survey Scientific Investigations Report 2016-5038. For details on the project and purpose, see the report at https://doi.org/10.3133/sir20165038. Complete metadata for the collection of species datasets is in the metadata document "Dataset_for_Alaska_Marine_Fish_Ecology_Catalog.xml" at https://doi.org/10.5066/F7M61HD7. Source(s) for this digitized data layer are listed in the metadata Process Steps section. Note that the original source may show an extended area; some datasets were limited to the published map boundary. Distributions of marine fishes are shown in adjacent Arctic seas where...
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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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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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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 location and class density of potential annual grass risk within the Central Great Basin and Mojave Basin Ecoregion for the 2010 time period. This model represent a composite of multiple inductive (Maximum Entropy) models of varying annual grass cover using non-spectral landscape variables. Input Variables: elevation, aspect, distance to fire, geology, distance to hydric soils, distance to intermitant streams, landform, ombrotype, distance to perrenial streams, soil pH, density of primary roads, density of secondary/local roads, percent sandy soil, slope, thermotype. Classification of Model 0-No/Low Risk 1- < 5% Cover Risk 2- 5%-15% Cover Risk 3 - 15%-25% Cover Risk 4 - 25%-45% Cover...
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This simple assessment raster is used to answer management questions (MQs) about where change agents (CAs) overlap with BLM high biodiversity sites (HBS) in the Central Great Basin and Range Ecoregion. This is a basic footprint assessment of anthropogenic features (urban development, roads, etc) intersect with the areas of HBS. The HBS were derived from source data characterizing locations with concentrated at-risk biodiversity or existing source data of a prioritization exercise that identified areas of high conservation significance. It does not model actual response or condition of the HBS to the CAs. The data intersects two primary classes of information: The CAs consist of 19 classes which represent different...
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The dataset represents the work of multiple states and Federal agencies as part of the US Gap Analysis and LandFire programs. Multi-season satellite imagery (Landsat ETM+) from 1999-2001 were used in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-natural vegetation. The minimum mapping unit for this dataset is approximately 1 acre. Landcover classes are drawn from NatureServe's Ecological System concept. Five-hundred and fourty-four land cover classes composed of 12 cultural and 532 Natural/Semi-natural types are described. Land cover classes were mapped with a variety of techniques including decision tree classifiers, terrian modeling, inductive...
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The dataset represents the work of multiple states and Federal agencies as part of the US Gap Analysis and LandFire programs. Multi-season satellite imagery (Landsat ETM+) from 1999-2001 were used in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-natural vegetation. The minimum mapping unit for this dataset is approximately 1 acre. Landcover classes are drawn from NatureServe's Ecological System concept. Five-hundred and fourty-four land cover classes composed of 12 cultural and 532 Natural/Semi-natural types are described. Land cover classes were mapped with a variety of techniques including decision tree classifiers, terrian modeling, inductive...
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Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including...
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This raster is used to answer management questions (MQs) about where conservation elements (CEs) overlap with areas of high wind energy potential in the Mojave Basin and Range Ecoregion. The value indicated in the raster represents a normalized score between 0-1, the lower the value the few species and poorer modeled landscape condition (ecological integrity) expected. The higher the score, the more species and higher condition are expected. This layer seeks to address an article in the BLM Statement of Work 1.1.1 stated, Areas with High Potential for Renewable Energy Development (Required) (The Contractor shall a) locate areas identified (e.g., by DOE, USGS) as suitable for wind, solar, geothermal, and biomass...
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The dataset represents the work of multiple states and Federal agencies as part of the US Gap Analysis and LandFire programs. Multi-season satellite imagery (Landsat ETM+) from 1999-2001 were used in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-natural vegetation. The minimum mapping unit for this dataset is approximately 1 acre. Landcover classes are drawn from NatureServe's Ecological System concept. Five-hundred and fourty-four land cover classes composed of 12 cultural and 532 Natural/Semi-natural types are described. Land cover classes were mapped with a variety of techniques including decision tree classifiers, terrian modeling, inductive...
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This simple assessment raster is used to answer management questions (MQs) about where change agents (CAs) overlap with BLM Herd Management Areas (HMAs) in the Central Great Basin and Range Ecoregion. This is a basic footprint assessment of anthropogenic features (urban development, roads, etc) intersect with areas managed for wild horses and burros in the western US. It does not model actual response or condition of the HMAs to the CAs. The data intersects two primary classes of information: The CAs consist of 19 classes which represent different types of human infrastructure on the landscape. Some types are easily defined, precise footprints (pipelines, roads, energy development areas) while others are broader...
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This dataset was derived from 'NatureServe L48 ESLF V2.7'. See process steps for additional information. The dataset represents the work of multiple states and Federal agencies as part of the US Gap Analysis and LandFire programs. Multi-season satellite imagery (Landsat ETM+) from 1999-2001 were used in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-natural vegetation. The minimum mapping unit for this dataset is approximately 1 acre. Landcover classes are drawn from NatureServe's Ecological System concept. Five-hundred and fourty-four land cover classes composed of 12 cultural and 532 Natural/Semi-natural types are described. Land cover classes...
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Both tabular and spatial models were used to predict fire regime departure at the sub-watershed scale (i.e., HUC 10 units). Integrating the fire regime models with predicted changes in climate envelopes provides a clearer understanding of how these ecological systems are likely to respond to multiple stresses. The natural range of variability for each CE was initially derived from LANDFIRE Vegetation Dynamics Development Tool (VDDT) models. The VDDT allows for the development of probabilistic quantitative model of CEs consisting of multiple ecological states with both deterministic and probabilistic drivers. For any defined suite of drivers, the models predict the relative abundance of each state within a defined...


map background search result map search result map Marine Arctic point distribution of Fourhorn Poacher (Hypsagonus quadricornis) (Valenciennes, 1829) Marine Arctic polygon distribution of Eyeshade Sculpin (Nautichthys pribilovius) (Jordan & Gilbert, 1898) Marine Arctic polygon distribution of Chinook Salmon (Oncorhynchus tshawytscha) (Walbaum, 1792) Marine Arctic polygon distribution of Inconnu (Stenodus leucichthys) (Güldenstadt, 1772) DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Edwin B. Forsythe NWR, NJ, 2013–2014 BLM REA COP 2010 NatureServe National Landcover (v27) ColoradoPlateauMixedBedrockCanyonTableland_NatureServe_DIST_30m BLM REA COP 2010 NatureServe National Landcover (v27) InterMountainBasinsBigSagebrushShrubland_NatureServe_DIST_30m BLM REA SOD 2010 USA EPA LevelIV Ecoregions Poly BLM REA MAR 2012 NatureServe Terrestrial Ecosystems v2.9  - MAR BLM REA MBR 2010 CBR Footprint Assessment Change Agent/High Biodiversity Sites Intersect BLM REA MBR 2010 Footprint Assessment Change Agent/Herd Management Areas Intersect BLM REA MBR 2010 Assessment Landscape Species and Wind Renewable Energy Potential Suitability BLM REA MBR 2010 Risk Model of Invasive Annual Grasses BLM REA CBR 2010 Ecological System Fire Regime Departure - 2025 Great Basin Pinyon-Juniper Woodland BLM REA CBR 2010 NatureServe COPMixedLowSagbrushShrublnd Terrestrial Ecological Systems 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 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 DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Edwin B. Forsythe NWR, NJ, 2013–2014 BLM REA MBR 2010 Footprint Assessment Change Agent/Herd Management Areas Intersect BLM REA MAR 2012 NatureServe Terrestrial Ecosystems v2.9  - MAR BLM REA MBR 2010 Assessment Landscape Species and Wind Renewable Energy Potential Suitability BLM REA MBR 2010 CBR Footprint Assessment Change Agent/High Biodiversity Sites Intersect BLM REA MBR 2010 Risk Model of Invasive Annual Grasses BLM REA COP 2010 NatureServe National Landcover (v27) ColoradoPlateauMixedBedrockCanyonTableland_NatureServe_DIST_30m BLM REA COP 2010 NatureServe National Landcover (v27) InterMountainBasinsBigSagebrushShrubland_NatureServe_DIST_30m BLM REA CBR 2010 Ecological System Fire Regime Departure - 2025 Great Basin Pinyon-Juniper Woodland BLM REA CBR 2010 NatureServe COPMixedLowSagbrushShrublnd Terrestrial Ecological Systems Marine Arctic polygon distribution of Inconnu (Stenodus leucichthys) (Güldenstadt, 1772) BLM REA SOD 2010 USA EPA LevelIV Ecoregions Poly Marine Arctic point distribution of Fourhorn Poacher (Hypsagonus quadricornis) (Valenciennes, 1829) Marine Arctic polygon distribution of Eyeshade Sculpin (Nautichthys pribilovius) (Jordan & Gilbert, 1898) Marine Arctic polygon distribution of Chinook Salmon (Oncorhynchus tshawytscha) (Walbaum, 1792)