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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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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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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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The 2006 National Insect and Disease Risk Map (NIDRM) Project integrates 188 individual risk models constructed within a common, consistent framework that accounts for regional variations in current and future forest health. The 2006 risk assessment, conducted within the contiguous United States and Alaska, provides a consistent, repeatable, transparent process through which interactive spatial and temporal risk assessments can be conducted at various scales to aid in the allocation of resources for forest health management. This modeling process is intended to increase the utilization of forest health risk maps within and outside the National Forest System and encourage development of future risk maps. NIDRM...
Habitat selection studies can make important contributions to habitat prioritization efforts for species of conservation concern. We present a large-scale collaborative effort to develop habitat selection models for Greater Sage-grouse (Centrocercus urophasianus) across large landscapes (Wyoming, USA) and multiple seasons. Greater Sage-grouse are limited to western semi-arid landscapes in North America, range-wide population declines have been documented, and the species is currently listed a “warranted but precluded” from listing under the U.S. Endangered Species Act. Wyoming is predicted to remain a stronghold for Sage-grouse populations and contains approximately 37% of the remaining birds. We developed Resource...
Habitat selection studies can make important contributions to habitat prioritization efforts for species of conservation concern. We present a large-scale collaborative effort to develop habitat selection models for Greater Sage-grouse (Centrocercus urophasianus) across large landscapes (Wyoming, USA) and multiple seasons. Greater Sage-grouse are limited to western semi-arid landscapes in North America, range-wide population declines have been documented, and the species is currently listed a “warranted but precluded” from listing under the U.S. Endangered Species Act. Wyoming is predicted to remain a stronghold for Sage-grouse populations and contains approximately 37% of the remaining birds. We developed Resource...
Habitat selection studies can make important contributions to habitat prioritization efforts for species of conservation concern. We present a large-scale collaborative effort to develop habitat selection models for Greater Sage-grouse (Centrocercus urophasianus) across large landscapes (Wyoming, USA) and multiple seasons. Greater Sage-grouse are limited to western semi-arid landscapes in North America, range-wide population declines have been documented, and the species is currently listed a “warranted but precluded” from listing under the U.S. Endangered Species Act. Wyoming is predicted to remain a stronghold for Sage-grouse populations and contains approximately 37% of the remaining birds. We developed Resource...
Habitat selection studies can make important contributions to habitat prioritization efforts for species of conservation concern. We present a large-scale collaborative effort to develop habitat selection models for Greater Sage-grouse (Centrocercus urophasianus) across large landscapes (Wyoming, USA) and multiple seasons. Greater Sage-grouse are limited to western semi-arid landscapes in North America, range-wide population declines have been documented, and the species is currently listed a “warranted but precluded” from listing under the U.S. Endangered Species Act. Wyoming is predicted to remain a stronghold for Sage-grouse populations and contains approximately 37% of the remaining birds. We developed Resource...
Habitat selection studies can make important contributions to habitat prioritization efforts for species of conservation concern. We present a large-scale collaborative effort to develop habitat selection models for Greater Sage-grouse (Centrocercus urophasianus) across large landscapes (Wyoming, USA) and multiple seasons. Greater Sage-grouse are limited to western semi-arid landscapes in North America, range-wide population declines have been documented, and the species is currently listed a “warranted but precluded” from listing under the U.S. Endangered Species Act. Wyoming is predicted to remain a stronghold for Sage-grouse populations and contains approximately 37% of the remaining birds. We developed Resource...
Habitat selection studies can make important contributions to habitat prioritization efforts for species of conservation concern. We present a large-scale collaborative effort to develop habitat selection models for Greater Sage-grouse (Centrocercus urophasianus) across large landscapes (Wyoming, USA) and multiple seasons. Greater Sage-grouse are limited to western semi-arid landscapes in North America, range-wide population declines have been documented, and the species is currently listed a “warranted but precluded” from listing under the U.S. Endangered Species Act. Wyoming is predicted to remain a stronghold for Sage-grouse populations and contains approximately 37% of the remaining birds. We developed Resource...
Habitat selection studies can make important contributions to habitat prioritization efforts for species of conservation concern. We present a large-scale collaborative effort to develop habitat selection models for Greater Sage-grouse (Centrocercus urophasianus) across large landscapes (Wyoming, USA) and multiple seasons. Greater Sage-grouse are limited to western semi-arid landscapes in North America, range-wide population declines have been documented, and the species is currently listed a “warranted but precluded” from listing under the U.S. Endangered Species Act. Wyoming is predicted to remain a stronghold for Sage-grouse populations and contains approximately 37% of the remaining birds. We developed Resource...
Habitat selection studies can make important contributions to habitat prioritization efforts for species of conservation concern. We present a large-scale collaborative effort to develop habitat selection models for Greater Sage-grouse (Centrocercus urophasianus) across large landscapes (Wyoming, USA) and multiple seasons. Greater Sage-grouse are limited to western semi-arid landscapes in North America, range-wide population declines have been documented, and the species is currently listed a “warranted but precluded” from listing under the U.S. Endangered Species Act. Wyoming is predicted to remain a stronghold for Sage-grouse populations and contains approximately 37% of the remaining birds. We developed Resource...
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The acquisition of forest parameters by host species distributions is a significant factor in the identification of areas at risk of mortality to a particular agent. The most readily-available forest type maps do not contain enough location-specific information for insect and disease risk assessments, in particular species' age and stocking. Estimates for total and individual species' basal area (BA), quadratic mean diameter (QMD), stand density index (SDI), percent host composition, and predominant canopy position were developed for all 57 tree species and species groups modeled for the National Insect and Disease Risk Map. After extensively testing various interpolation methods, the Risk Map Integration Team...
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The 2006 National Insect and Disease Risk Map (NIDRM) Project integrates 188 individual risk models constructed within a common, consistent framework that accounts for regional variations in current and future forest health. The 2006 risk map assessment, utilized within the contiguous United States and Alaska, provides a consistent, repeatable, transparent process through which interactive spatial and temporal risk assessments can be conducted at various scales to aid in the allocation of resources for forest health management. This modeling process is intended to increase the utilization of forest health risk maps within and outside the National Forest System and encourage development of future risk maps. NIDRM...


map background search result map search result map Modeled western pine beetle basal area loss - 2006 Estimated total basal area (BA) - 2006 Modeled fir engraver beetle basal area loss - 2006 DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Cedar Island, VA, 2012–2013 ElevMHW: Elevation adjusted to local mean high water: Cedar Island, VA, 2014 DisOcean: Distance to the ocean: Monomoy Island, MA, 2014 ElevMHW: Elevation adjusted to local mean high water: Cape Lookout, NC, 2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Assawoman Island, VA, 2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fisherman Island, VA, 2014 ElevMHW: Elevation adjusted to local mean high water: Parramore Island, VA, 2014 DisOcean: Distance to the ocean: Smith Island, VA, 2014 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Wreck Island, VA, 2014 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Wreck Island, VA, 2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fisherman Island, VA, 2014 ElevMHW: Elevation adjusted to local mean high water: Cedar Island, VA, 2014 DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Cedar Island, VA, 2012–2013 DisOcean: Distance to the ocean: Smith Island, VA, 2014 ElevMHW: Elevation adjusted to local mean high water: Parramore Island, VA, 2014 DisOcean: Distance to the ocean: Monomoy Island, MA, 2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Assawoman Island, VA, 2014 ElevMHW: Elevation adjusted to local mean high water: Cape Lookout, NC, 2014 Modeled western pine beetle basal area loss - 2006 Modeled fir engraver beetle basal area loss - 2006 Estimated total basal area (BA) - 2006