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This dataset depicts Wolf (Canis lupus) habitat in the Northern Appalachians predicted using the spatially explicit population model PATCH under the projected habitat effectiveness for 2025 plus moderate US mortality plus low Canadian mortality scenario (Carroll 2003). This dataset represents one of several scenarios testing the effects of habitat effectiveness and mortality rates on wolf populations. Static habitat suitability models for wolf were fed through PATCH to predict source and sink habitat areas across the landscape. The static models for wolf were created based on current and projected habitat effectiveness, which were based in part on road density and human population density. Wolf fecundity rates were...
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This dataset depicts Wolf (Canis lupus) habitat in the Northern Appalachians predicted using the spatially explicit population model PATCH under the current habitat effectiveness plus low US mortality plus moderate Canadian mortality scenario (Carroll 2003). This dataset represents one of several scenarios testing the effects of habitat effectiveness and mortality rates on wolf populations. Static habitat suitability models for wolf were fed through PATCH to predict source and sink habitat areas across the landscape. The static models for wolf were created based on current and projected habitat effectiveness, which were based in part on road density and human population density. Wolf fecundity rates were based on...
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This dataset depicts Lynx (Lynx canadensis) habitat in the Northern Appalachians predicted using the spatially explicit population model PATCH under the population cycling across the region plus trapping plus climate change scenario (FC2; Carrol 2007). This dataset represents one of several scenarios testing the interacting effects of population cycling, trapping, territory size, and climate change on lynx populations. Static habitat suitability models for lynx were fed through PATCH to predict source and sink habitat areas across the landscape. The static models for lynx were created based on a logistic regression model of reported lynx locations against the proportion of the landscape in deciduous forest cover...
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This dataset depicts Marten (Martes americana) habitat in the Northern Appalachians predicted using the spatially explicit population model PATCH under the increased trapping intensity scenario (B4; Carrol 2007). This dataset represents one of several scenarios testing the interacting effects of trapping, timber harvest, habitat restoration, and climate change on marten populations. Static habitat suitability models for marten were fed through PATCH to predict source and sink habitat areas across the landscape. The static models for marten were created based on annual snowfall and percentage of older conifer and mixed forest. Demographic parameters were obtained from the literature and from calibration of the model....
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The capacity of ecosystems to provide services such as carbon storage, clean water, and forest products is determined not only by variations in ecosystem properties across landscapes, but also by ecosystem dynamics over time. ForWarn is a system developed by the U.S. Forest Service to monitor vegetation change using satellite imagery for the continental United States. It provides near real-time change maps that are updated every eight days, and summaries of these data also provide long-term change maps from 2000 to the present.Based on the detection of change in vegetation productivity, the ForWarn system monitors the effects of disturbances such as wildfires, insects, diseases, drought, and other effects of weather,...
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WaSSI (Water Supply Stress Index) predicts how climate, land cover, and human population change may impact water availability and carbon sequestration at the watershed level (about the size of a county) across the lower 48 United States. WaSSI users can select and adjust temperature, precipitation, land cover, and water use factors to simulate change scenarios for any timeframe from 1961 through the year 2100.Simulation results are available as downloadable maps, graphs, and data files that users can apply to their unique information and project needs. WaSSI generates useful information for natural resource planners and managers who must make informed decisions about water supplies and related ecosystem services...
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Systematic conservation planning is well suited to address the many large-scale biodiversity conservation challenges facing the Appalachian region. However, broad, well-connected landscapes will be required to sustain many of the natural resources important to this area into the future. If these landscapes are to be resilient to impending change, it will likely require an orchestrated and collaborative effort reaching across jurisdictional and political boundaries. The first step in realizing this vision is prioritizing discrete places and actions that hold the greatest promise for the protection of biodiversity. Five conservation design elements covering many critical ecological processes and patterns across the...
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All Conservation Design Elements identified through a multi-year conservation planning effort undertaken by the Appalachian Landscape Conservation Cooperative (LCC). These elements were identified by the program Marxan as meeting collective conservation targets. Datasets include a merged design of all five elements, individual element shapefiles, and a prioritization shapefile (Conservation Design elements outlined by the NatureScape Design that were then placed into a prioritization framework based on Margulis and Pressy 2000).
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Provisional Tennessee State Wildlife Action Plan (TN-SWAP) terrestrial habitat priorities versus results of the population growth model developed by the Tennessee Chapter of The Nature Conservancy, 2008, converted to percent projected developed landcover in the year 2040. Spatial growth model was developed using population growth projections from the University of Tennessee Center for Business and Economic Research (UT-CBER), county urban growth boundaries, 2000 census blocks, and various ancillary datasets.
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The Appalachians are a landscape filled with globally-significant biological diversity and cultural resources that provides essential benefits to large cities and surrounding human communities. The region is also rich in energy resources that meet national and regional demands for energy. As wind, natural gas, and oil energy development expand along with traditional coal, there is an increasing need for research to inform discussions on how to meet immediate and future energy needs while sustaining the health of natural systems. To help address this need, the Appalachian LCC awarded a grant to The Nature Conservancy to assess current and future energy development across the entire region. Assessing Future Energy...
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This dataset depicts Wolf (Canis lupus) habitat in the Northern Appalachians predicted using the spatially explicit population model PATCH under the current habitat effectiveness plus high US mortality plus moderate Canadian mortality scenario (Carroll 2003). This dataset represents one of several scenarios testing the effects of habitat effectiveness and mortality rates on wolf populations. Static habitat suitability models for wolf were fed through PATCH to predict source and sink habitat areas across the landscape. The static models for wolf were created based on current and projected habitat effectiveness, which were based in part on road density and human population density. Wolf fecundity rates were based...
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This dataset depicts Marten (Martes americana) habitat in the Northern Appalachians predicted using the spatially explicit population model PATCH under the increased trapping Area scenario (B3; Carrol 2007). This dataset represents one of several scenarios testing the interacting effects of trapping, timber harvest, habitat restoration, and climate change on marten populations. Static habitat suitability models for marten were fed through PATCH to predict source and sink habitat areas across the landscape. The static models for marten were created based on annual snowfall and percentage of older conifer and mixed forest. Demographic parameters were obtained from the literature and from calibration of the model....
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The Forest Health Technology Enterprise Team (FHTET) was created by the Deputy Chief for State and Private Forestry in February 1995 to develop and deliver forest health technology services to field personnel in public and private organizations in support of the Forest Service’s land ethic, to “promote the sustainability of ecosystems by ensuring their health, diversity, and productivity.” This dataset shows the total basal area of all tree species as square feet per acre.For more information: http://www.fs.fed.us/foresthealth/technology/nidrm2012.shtml
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The National Cohesive Wildland Fire Management Strategy, initiated in 2009 and finalized in 2014, provides a national vision for wildland fire management. This highly collaborative effort establishes three overarching goals, and describes stakeholder-driven processes for achieving them: (1) resilient landscapes; (2) fire-adapted communities; and (3) safe and effective wildfire response. The scientific rigor of this program was ensured with the establishment of the National Science and Analysis Team (NSAT). The main tasks of NSAT were to compile credible scientific information, data, and models to help explore national challenges and opportunities, identify a range of management options, and help set national priorities...
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This dataset depicts Lynx (Lynx canadensis) habitat in the Northern Appalachians predicted using the spatially explicit population model PATCH under the population cycling only in Gaspe (core area) plus trapping scenario (B2; Carroll 2007). This dataset represents one of several scenarios testing the interacting effects of population cycling, trapping, territory size, and climate change on lynx populations. Static habitat suitability models for lynx were fed through PATCH to predict source and sink habitat areas across the landscape. The static models for lynx were created based on a logistic regression model of reported lynx locations against the proportion of the landscape in deciduous forest cover and annual...
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Information about economic activity was obtained from the National Cohesive Wildland Fire Management Strategy (cohesivefire.nemac.org). Data were derived from the USDA Economic Research Service to create a county-level measure of Dominant Economic Activity (county economic dependence). This describes the most prevalent kind of economic activity, which includes activities from farming, mining, and manufacturing to government employment and the service industry. The Appalachian economy is diverse and geographically variable; for example, manufacturing is spread throughout the region, whereas mining activities are located more centrally. Data are from 2004.The mission of the USDA Economic Research Service is to inform...
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Efforts to model and predict long-term variations in climate-based on scientific understanding of climatological processes have grown rapidly in their sophistication to the point that models can be used to develop reasonable expectations of regional climate change. This is important because our ability to assess the potential consequences of a changing climate for particular ecosystems or regions depends on having realistic expectations about the kinds and severity of change to which a region may be exposed.The fifth phase of the Coupled Model Intercomparison Project (CMIP5) is a collaborative climate modeling research effort coordinated by the World Climate Research Programme (WCRP). This is the most recent phase...
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Results of the population growth model developed by the Tennessee Chapter of The Nature Conservancy, 2008, converted to percent projected developed landcover in the year 2040. Spatial growth model was developed using population growth projections from the University of Tennessee Center for Business and Economic Research (UT-CBER), county urban growth boundaries, 2000 census blocks, and various ancillary datasets.
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This dataset depicts Marten (Martes americana) habitat in the Northern Appalachians predicted using the spatially explicit population model PATCH under the increased trapping area plus timber harvest scenario (L3; Carrol 2007). This dataset represents one of several scenarios testing the interacting effects of trapping, timber harvest, habitat restoration, and climate change on marten populations. Static habitat suitability models for marten were fed through PATCH to predict source and sink habitat areas across the landscape. The static models for marten were created based on annual snowfall and percentage of older conifer and mixed forest. Demographic parameters were obtained from the literature and from calibration...


map background search result map search result map Predicted Marten Habitat in the Northern Appalachians: Increased Trapping Intensity Scenario Predicted Marten Habitat in the Northern Appalachians: Increased Trapping Area + Timber Harvest Scenario Predicted Wolf Habitat in the Northern Appalachians: 2025 Habitat Effectiveness + Moderate US Mortality + Low Canadian Mortality Scenario Predicted Wolf Habitat in the Northern Appalachians: Current Habitat Effectiveness + Low US Mortality + Moderate Canadian Mortality Scenario Predicted Wolf Habitat in the Northern Appalachians: Current Habitat Effectiveness + High US Mortality + Moderate Canadian Mortality Scenario Predicted Marten Habitat in the Northern Appalachians: Increased Trapping Area Scenario Predicted Lynx Habitat in the Northern Appalachians: Population Cycling + Trapping + Climate Change Scenario Predicted Lynx Habitat in the Northern Appalachians: Cycling in Gaspe + Trapping Scenario Appalachian LCC Landscape Conservation Design Phase 1 Local Build-outs WASSI Future Change in Water Supply Stress Index 1991-2010 ForWarn Mean Summer National Difference Vegetation Index 2009-2013 Total Basal Area of All Tree Species 2012 U.S. Forest Service National Cohesive Fire Strategy Dataset Forest Product Production Amount of inflow stored in upstream dams-rivers NatureScape, Design Dominant Economic Activity USDA Economic Research Service CMIP5 Future Average Annual Temperature 2031-2060 Future Energy Development Tool Public Tennessee Projected Percent Developed in 2040 Provisional Tennessee State Wildlife Action Plan Potential Urban Growth Tennessee Projected Percent Developed in 2040 Provisional Tennessee State Wildlife Action Plan Potential Urban Growth Predicted Marten Habitat in the Northern Appalachians: Increased Trapping Area + Timber Harvest Scenario Predicted Marten Habitat in the Northern Appalachians: Increased Trapping Intensity Scenario Predicted Marten Habitat in the Northern Appalachians: Increased Trapping Area Scenario Predicted Lynx Habitat in the Northern Appalachians: Population Cycling + Trapping + Climate Change Scenario Predicted Lynx Habitat in the Northern Appalachians: Cycling in Gaspe + Trapping Scenario Predicted Wolf Habitat in the Northern Appalachians: 2025 Habitat Effectiveness + Moderate US Mortality + Low Canadian Mortality Scenario Predicted Wolf Habitat in the Northern Appalachians: Current Habitat Effectiveness + Low US Mortality + Moderate Canadian Mortality Scenario Predicted Wolf Habitat in the Northern Appalachians: Current Habitat Effectiveness + High US Mortality + Moderate Canadian Mortality Scenario U.S. Forest Service National Cohesive Fire Strategy Dataset Forest Product Production WASSI Future Change in Water Supply Stress Index 1991-2010 Dominant Economic Activity USDA Economic Research Service NatureScape, Design Future Energy Development Tool Public Appalachian LCC Landscape Conservation Design Phase 1 Local Build-outs CMIP5 Future Average Annual Temperature 2031-2060 Amount of inflow stored in upstream dams-rivers ForWarn Mean Summer National Difference Vegetation Index 2009-2013 Total Basal Area of All Tree Species 2012