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The Virginia Department of Conservation and Recreation – Natural Heritage Program (DCRDNH) and the Florida Natural Areas Inventory (FNAI) at Florida State University (collectively, Project Partners) were funded by the South Atlantic Landscape Conservation Cooperative (SALCC) in April 2015 to develop ten species distribution models (SDM) of priority at-risk and range-restricted species (Ambystoma cingulatum, Echinacea laevigata, Heterodon simus, Lindera melissifolia, Lythrum curtissii, Notophthalmus perstriatus, Phemeranthus piedmontanus, Rhus michauxii, and Schwalbea americana) for the purposes of incorporating the models and supporting information on the conservation and management needs of the species into the...
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The Virginia Department of Conservation and Recreation – Natural Heritage Program (DCRDNH) and the Florida Natural Areas Inventory (FNAI) at Florida State University (collectively, Project Partners) were funded by the South Atlantic Landscape Conservation Cooperative (SALCC) in April 2015 to develop ten species distribution models (SDM) of priority at-risk and range-restricted species (Ambystoma cingulatum, Echinacea laevigata, Heterodon simus, Lindera melissifolia, Lythrum curtissii, Notophthalmus perstriatus, Phemeranthus piedmontanus, Rhus michauxii, and Schwalbea americana) for the purposes of incorporating the models and supporting information on the conservation and management needs of the species into the...
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This data product contains estimates of habitat quality for black bear. The analysis area was a 236,000 square kilometers that encompassed the Navajo Nation, which includes portions of Arizona, New Mexico, and Utah. The estimates of habitat quality were created with spatially explicit habitat variables and either an expert-based linear combination process (for mountain lion and mule deer) or a generalized linear mixed model-based estimation that used radio-collar telemetry data (for desert bighorn sheep, black bear, and pronghorn; collected between 2005-2011). Habitat variables varied among species but included vegetation type, terrain ruggedness, topographic position index (TPI), road density, distance to water,...
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Our objective was to model specific mean daily flow (mean daily flow divided by drainage area [cubic feet per second per square mile]) on small, ungaged streams in the Upper Colorado River Basin. Modeling streamflows is an important tool for understanding landscape-scale drivers of flow and estimating flows where there are no gaged records. We focused our study in the Upper Colorado River Basin, a region that is not only critical for water resources but also projected to experience large future climate shifts toward a drier climate.We used a random forest modeling approach to model the relation between specific mean daily flow on gaged streams (115 gages) and environmental variables. We then projected specific mean...
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Our objective was to model specific minimum flow (mean of the annual minimum flows divided by drainage area [cubic feet per second per square mile]) on small, ungaged streams in the Upper Colorado River Basin. Modeling streamflows is an important tool for understanding landscape-scale drivers of flow and estimating flows where there are no gaged records. We focused our study in the Upper Colorado River Basin, a region that is not only critical for water resources but also projected to experience large future climate shifts toward a drier climate. We used a random forest modeling approach to model the relation between specific minimum flow on gaged streams (115 gages) and environmental variables. We then projected...
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An estimated value for the ability of managers to dirct actions to protect, restore, or mitigate species and habitats. We recognize that our preliminary estimates are arbitrary and fairly approximate, but argue that making these explicit within a framework will enable stakeholders and managers to conduct subsequent analyses to better support their decision making.
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Our objective was to model the risk of becoming intermittent under drier climate conditions on small, ungaged streams in the Upper Colorado River Basin. Modeling streamflows is an important tool for understanding landscape-scale drivers of flow and estimating flows where there are no gaged records. We focused our study in the Upper Colorado River Basin, a region that is not only critical for water resources but also projected to experience large future climate shifts toward a drier climate. We used a conditional inference modeling approach to model the relation between intermittency status on gaged streams (115 gages) and selected mean and minimum flow metrics. We then projected intermittency status and if a stream...
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This project will conduct a synthesis of marine spatial data. An OPS staff will be hired to work with marine/coastal experts – to develop a Technical Advisory Group and gather data and input on the processes used in the marine assessment. Additionally, this project will identify key inland (terrestrial and freshwater) areas that currently have or may have in the future direct and indirect impacts on the health of the marine environment. Results of this project will be the basis for the marine component of the Landscape Conservation Design being developed by the Peninsular Florida Landscape Conservation Cooperative. Every effort will be made to build upon existing science and other ongoing projects that may be developing...
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This data product contains estimates of habitat connectivity for desert bighorn sheep. The analysis area was a 236,000 square kilometers that encompassed the Navajo Nation, which includes portions of Arizona, New Mexico, and Utah. The estimates of habitat quality were created with spatially explicit habitat variables and either an expert-based linear combination process (for mountain lion and mule deer) or a generalized linear mixed model-based estimation that used radio-collar telemetry data (for desert bighorn sheep, black bear, and pronghorn; collected between 2005-2011). Habitat variables varied among species but included vegetation type, terrain ruggedness, topographic position index (TPI), road density, distance...
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The Virginia Department of Conservation and Recreation – Natural Heritage Program (DCRDNH) and the Florida Natural Areas Inventory (FNAI) at Florida State University (collectively, Project Partners) were funded by the South Atlantic Landscape Conservation Cooperative (SALCC) in April 2015 to develop ten species distribution models (SDM) of priority at-risk and range-restricted species (Ambystoma cingulatum, Echinacea laevigata, Heterodon simus, Lindera melissifolia, Lythrum curtissii, Notophthalmus perstriatus, Phemeranthus piedmontanus, Rhus michauxii, and Schwalbea americana) for the purposes of incorporating the models and supporting information on the conservation and management needs of the species into the...
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The Virginia Department of Conservation and Recreation – Natural Heritage Program (DCRDNH) and the Florida Natural Areas Inventory (FNAI) at Florida State University (collectively, Project Partners) were funded by the South Atlantic Landscape Conservation Cooperative (SALCC) in April 2015 to develop ten species distribution models (SDM) of priority at-risk and range-restricted species (Ambystoma cingulatum, Echinacea laevigata, Heterodon simus, Lindera melissifolia, Lythrum curtissii, Notophthalmus perstriatus, Phemeranthus piedmontanus, Rhus michauxii, and Schwalbea americana) for the purposes of incorporating the models and supporting information on the conservation and management needs of the species into the...
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The Virginia Department of Conservation and Recreation – Natural Heritage Program (DCRDNH) and the Florida Natural Areas Inventory (FNAI) at Florida State University (collectively, Project Partners) were funded by the South Atlantic Landscape Conservation Cooperative (SALCC) in April 2015 to develop ten species distribution models (SDM) of priority at-risk and range-restricted species (Ambystoma cingulatum, Echinacea laevigata, Heterodon simus, Lindera melissifolia, Lythrum curtissii, Notophthalmus perstriatus, Phemeranthus piedmontanus, Rhus michauxii, and Schwalbea americana) for the purposes of incorporating the models and supporting information on the conservation and management needs of the species into the...
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An estimated value for the ability of managers to dirct actions to protect, restore, or mitigate species and habitats. We recognize that our preliminary estimates are arbitrary and fairly approximate, but argue that making these explicit within a framework will enable stakeholders and managers to conduct subsequent analyses to better support their decision making.
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This data product contains estimates of habitat quality for pronghorn. The analysis area was a 236,000 square kilometers that encompassed the Navajo Nation, which includes portions of Arizona, New Mexico, and Utah. The estimates of habitat quality were created with spatially explicit habitat variables and either an expert-based linear combination process (for mountain lion and mule deer) or a generalized linear mixed model-based estimation that used radio-collar telemetry data (for desert bighorn sheep, black bear, and pronghorn; collected between 2005-2011). Habitat variables varied among species but included vegetation type, terrain ruggedness, topographic position index (TPI), road density, distance to water,...
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The Virginia Department of Conservation and Recreation – Natural Heritage Program (DCRDNH) and the Florida Natural Areas Inventory (FNAI) at Florida State University (collectively, Project Partners) were funded by the South Atlantic Landscape Conservation Cooperative (SALCC) in April 2015 to develop ten species distribution models (SDM) of priority at-risk and range-restricted species (Ambystoma cingulatum, Echinacea laevigata, Heterodon simus, Lindera melissifolia, Lythrum curtissii, Notophthalmus perstriatus, Phemeranthus piedmontanus, Rhus michauxii, and Schwalbea americana) for the purposes of incorporating the models and supporting information on the conservation and management needs of the species into the...
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The Virginia Department of Conservation and Recreation – Natural Heritage Program (DCRDNH) and the Florida Natural Areas Inventory (FNAI) at Florida State University (collectively, Project Partners) were funded by the South Atlantic Landscape Conservation Cooperative (SALCC) in April 2015 to develop ten species distribution models (SDM) of priority at-risk and range-restricted species (Ambystoma cingulatum, Echinacea laevigata, Heterodon simus, Lindera melissifolia, Lythrum curtissii, Notophthalmus perstriatus, Phemeranthus piedmontanus, Rhus michauxii, and Schwalbea americana) for the purposes of incorporating the models and supporting information on the conservation and management needs of the species into the...
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Sum of all conservation focus areas (CFA) for a particular area (UPDATED TO INCLUDE CONSERVATION PRIORITIES DELINEATED IN LATEST STATE WILDLIFE ACTION PLANS (ca. 2015/2016)). These focus areas include both those delineated at the state scale as well as regionally. States focus areas are included for all states in the Mississippi River Basin that have delineated focus/opportunity areas. States that are not included either have not delineated focus areas or were in the process of developing them at the time of data collection. States where CFA are pending: Texas and Wyoming. States where CFA have not been identified: Georgia; Maryland; Michigan; New Mexico; New York; and Oklahoma. Regional focus area include those...


map background search result map search result map Riparian Impact Combined, RCP 4.5 Terrestrial Impact Combined, RCP 4.5 Adaptive Capacity, Low Range Adaptive Capacity, Preliminary Bighorn Sheep Habitat Connectivity Black Bear Habitat Quality Pronghorn Habitat Quality Predicted specific mean daily flow Predicted specific minimum flow Predicted hydrology (intermittency) under drier climate conditions Sum - Conservation Focus Areas (2016) Determining Priority Amphibian and Reptile Conservation Areas (PARCAs) in the South Atlantic landscape, and assessing their efficacy for cross-taxa conservation: Geographic Dataset At-risk and range restricted species models: Geographic Datasets for Lindera melissifolia (Pondberry) At-risk and range restricted species models: Geographic Datasets for Ambystoma cingulatum (Frosted Flatwoods Salamander) At-risk and range restricted species models: Geographic Datasets for Heterodon simus (Southern Hognose Snake) At-risk and range restricted species models: Geographic Datasets for Echinacea laevigata (Smooth coneflower) At-risk and range restricted species models: Geographic Datasets for Notophthalmus perstriatus (Striped Newt) At-risk and range restricted species models: Geographic Datasets for Schwalbea americana (American Chaffseed) At-risk and range restricted species models: Geographic Datasets for Rhus michauxii (Michaux’s Sumac) Marine Priority Resources Map Bighorn Sheep Habitat Connectivity Black Bear Habitat Quality Pronghorn Habitat Quality Predicted hydrology (intermittency) under drier climate conditions Predicted specific mean daily flow Predicted specific minimum flow Marine Priority Resources Map Determining Priority Amphibian and Reptile Conservation Areas (PARCAs) in the South Atlantic landscape, and assessing their efficacy for cross-taxa conservation: Geographic Dataset Riparian Impact Combined, RCP 4.5 Terrestrial Impact Combined, RCP 4.5 At-risk and range restricted species models: Geographic Datasets for Lindera melissifolia (Pondberry) At-risk and range restricted species models: Geographic Datasets for Ambystoma cingulatum (Frosted Flatwoods Salamander) At-risk and range restricted species models: Geographic Datasets for Notophthalmus perstriatus (Striped Newt) At-risk and range restricted species models: Geographic Datasets for Schwalbea americana (American Chaffseed) At-risk and range restricted species models: Geographic Datasets for Heterodon simus (Southern Hognose Snake) At-risk and range restricted species models: Geographic Datasets for Echinacea laevigata (Smooth coneflower) At-risk and range restricted species models: Geographic Datasets for Rhus michauxii (Michaux’s Sumac) Adaptive Capacity, Low Range Adaptive Capacity, Preliminary Sum - Conservation Focus Areas (2016)