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For a description of each map layer, select the Details tab, then select a Layer Name. This GIS dataset is part of a suite of wildlife habitat connectivity data produced by the Washington Wildlife Habitat Connectivity Working Group (WHCWG). The WHCWG is a voluntary public-private partnership between state and federal agencies, universities, tribes, and non-governmental organizations. The WHCWG is co-led by the Washington Department of Fish and Wildlife (WDFW) and the Washington Department of Transportation (WSDOT). This dataset quantifies current wildlife habitat connectivity patterns for the Columbia Plateau Ecoregion in Washington, Oregon, and Idaho. Available WHCWG raster data include model base layers, resistance,...
Winter (January – March) precipitation averaged over 2046-2065 from the general circulation model PCM1 (Washington et al. 2000; Meehl et al. 2003) under the A2 emission scenario with a grid cell size of 10 km x 10km. References: Meehl, G.A., W.M. Washington, T.M.L. Wigley, J.M. Arblaster, and A. Dai. 2003. Solar and greenhouse gas forcing and climate response in the twentieth century. J Climate 16:426–444. Washington, W.M., J.W. Weatherly, G.A. Meehl, A.J. Semtner, T.W. Bettge, A.P. Craig, W.G. Stran, J. Arblaster, V.B. Wayland, R. James , and Y. Zhang. 2000. Parallel climate model (PCM) control and transient simulations. Clim Dyn 16: 755–774.
This map shows the predicted area of high fire potential for the current year up to the end of the forecast period as simulated by a modified version of the MC1 Dynamic General Vegetation Model (DGVM). Different colors indicate the level of consensus among five different MC1 simulations (i.e., one for each forecast provided by five different weather models), ranging from one of five to five of five simulations predicting high fire potential. The area of high fire potential is where PDSI and MC1-calculated values of potential fire behavior (fireline intensity for forest and shrubland and rate of spread of spread for grassland) exceed calibrated threshold values. Potential fire behavior in MC1 is estimated using...
The Palmer Drought Severity Index (PDSI) is a measure of drought derived from both precipitation and temperature. Negative (i.e., dry) values of PDSI are closely associated with a high potential for wildland fire. PDSI is based on a supply-and-demand model of soil moisture originally developed by Wayne Palmer, who published his method in the 1965 paper Meteorological Drought for the Office of Climatology of the U.S. Weather Bureau.The index has proven to be most effective in indicating long-term drought (or wetness) over a matter of several months. PDSI calculations are standardized for an individual station (or grid cell) based on the long-term variability of precipitation and temperature at that location....
Winter (January – March) precipitation (mm) averaged over 2046-2065 from the general circulation model Hadley CM3 (Gordon et al. 2000, Pope et al. 2000) downscaled to a grid cell size of 10 km x 10km. References: Gordon C., C. Cooper , C.A. Senior, H. Banks, J.M. Gregory, T.C. Johns , J.F.B. Mitchell, and R.A. Wood. 2000. The simulation of SST, sea ice extents and ocean heat transports in a version of the Hadley Centre coupled model without flux adjustments. Clim Dyn 16:147–168. Pope, V.D., M.L. Gallani, P.R. Rowntree, and R.A. Stratton. 2000. The impact of new physical parameterisations in the Hadley Centre climate model – HadAM3. Clim Dyn 16:123–146.
Future (2046-2065) predicted probability of fisher year-round occurrence projected under the A1fi emissions scenario with the Hadley CM3 GCM model (Gordon et al. 2000, Pope et al. 2000). Projected fisher distribution was created with Maxent (Phillips et al. 2006) using fisher detections (N = 102, spanning 1993 – 2011) and seven predictor variables: mean winter (January – March) precipitation, mean summer (July – September) precipitation, mean summer temperature amplitude, mean daily low temperature for the month of the year with the warmest mean daily low temperature, mean fraction of vegetation carbon burned, mean vegetation carbon (g C m2), and modal vegetation class. Predictor variables had a grid cell size of...
Description: Predicted probability of fisher year-round occurrence created with Maxent (Phillips et al. 2006) using fisher detections (N = 102, spanning 1993 – 2011) and seven predictor variables: mean winter (January – March) precipitation, mean summer (July – September) precipitation, mean summer temperature amplitude, mean daily low temperature for the month of the year with the warmest mean daily low temperature, mean fraction of vegetation carbon burned, mean vegetation carbon (g C m2), and modal vegetation class. Predictor variables had a grid cell size of 10 km, vegetation variables were simulated with MC1 (Hayhoe et al. 2004) and climate variables were provided by the PRISM GROUP (Daly et al. 1994). This...
The Palmer Drought Severity Index (PDSI) is a measure of drought derived from both precipitation and temperature. Negative (i.e., dry) values of PDSI are closely associated with a high potential for wildland fire. PDSI is based on a supply-and-demand model of soil moisture originally developed by Wayne Palmer, who published his method in the 1965 paper Meteorological Drought for the Office of Climatology of the U.S. Weather Bureau.The index has proven to be most effective in indicating long-term drought (or wetness) over a matter of several months. PDSI calculations are standardized for an individual station (or grid cell) based on the long-term variability of precipitation and temperature at that location....
This map shows the predicted area of high fire potential for the current year up to the end of the forecast period as simulated by a modified version of the MC1 Dynamic General Vegetation Model (DGVM). Different colors indicate the level of consensus among five different MC1 simulations (i.e., one for each forecast provided by five different weather models), ranging from one of five to five of five simulations predicting high fire potential. The area of high fire potential is where PDSI and MC1-calculated values of potential fire behavior (fireline intensity for forest and shrubland and rate of spread of spread for grassland) exceed calibrated threshold values. Potential fire behavior in MC1 is estimated using...
The Palmer Drought Severity Index (PDSI) is a measure of drought derived from both precipitation and temperature. Negative (i.e., dry) values of PDSI are closely associated with a high potential for wildland fire. PDSI is based on a supply-and-demand model of soil moisture originally developed by Wayne Palmer, who published his method in the 1965 paper Meteorological Drought for the Office of Climatology of the U.S. Weather Bureau.The index has proven to be most effective in indicating long-term drought (or wetness) over a matter of several months. PDSI calculations are standardized for an individual station (or grid cell) based on the long-term variability of precipitation and temperature at that location....
This dataset shows the predicted area of high fire potential for the current year up to the end of the forecast period as simulated by a modified version of the MC1 Dynamic General Vegetation Model (DGVM). The area of high fire potential is where PDSI and MC1-calculated values of potential fire behavior (fireline intensity for forest and shrubland and rate of spread of spread for grassland) exceed calibrated threshold values. Potential fire behavior in MC1 is estimated using National Fire Danger Rating System (NFDRS) formulas, monthly climatic (temperature, precipitation, and relative humidity) data, and fuel moisture and loading estimates. Monthly climatic data includes recorded values up to the last observed...
Annual precipitation (mm) averaged over 1986 – 2005, simulated by the MC1 dynamic global vegetation model (Bachelet et al. 2001) at a 4 km x 4 km spatial resolution using PRISM climate for the historical period. This effort is part of a pilot project to apply and evaluate the Yale Framework (Yale Science Panel for Integrating Climate Adaptation and Landscape Conservation Planning). Note: The MC1 model is described in data basin (http://databasin.org/climate-center/features/mc1-dynamic-global-vegetation-model).
Historical disturbance regimes are often considered a critical element in maintaining native plant communities. However, the response of plant communities to disturbance may be fundamentally altered as a consequence of invasive plants, climate change, or prior disturbances. The appropriateness of historical disturbance patterns under modern conditions and the interactions among disturbances are issues that ecologists must address to protect and restore native plant communities. We evaluated the response of Artemisia tridentata ssp. wyomingensis (Beetle & A. Young) S.L. Welsh plant communities to their historical disturbance regime compared to other disturbance regimes. The historical disturbance regime of these...
"USDA has purchased a Enterprise Premium license for this Orthoimagery dataset from DigitalGlobe, Inc. Any government, education, not-for-profit agency and public/individuals not engaged in using the "Product for Commercial Exploitation or Commercial Purposes" can use this licensed data. Use of this product for Commercial Purposes by a person/company/organization for a profit or fee is strictly prohibited. Please refer to the separately attached license from DigitalGlobe, Inc. for additional information. Digital orthoimagery combines the image characteristics of a digital image with the geometric qualities of a map. The primary dynamic digital orthophoto is a 60 centimeter ground resolution, image cast to the customer...
"USDA has purchased a Enterprise Premium license for this Orthoimagery dataset from DigitalGlobe, Inc. Any government, education, not-for-profit agency and public/individuals not engaged in using the "Product for Commercial Exploitation or Commercial Purposes" can use this licensed data. Use of this product for Commercial Purposes by a person/company/organization for a profit or fee is strictly prohibited. Please refer to the separately attached license from DigitalGlobe, Inc. for additional information. Digital orthoimagery combines the image characteristics of a digital image with the geometric qualities of a map. The primary dynamic digital orthophoto is a 60 centimeter ground resolution, image cast to the customer...
"USDA has purchased a Enterprise Premium license for this Orthoimagery dataset from DigitalGlobe, Inc. Any government, education, not-for-profit agency and public/individuals not engaged in using the "Product for Commercial Exploitation or Commercial Purposes" can use this licensed data. Use of this product for Commercial Purposes by a person/company/organization for a profit or fee is strictly prohibited. Please refer to the separately attached license from DigitalGlobe, Inc. for additional information. Digital orthoimagery combines the image characteristics of a digital image with the geometric qualities of a map. The primary dynamic digital orthophoto is a 60 centimeter ground resolution, image cast to the customer...
"USDA has purchased a Enterprise Premium license for this Orthoimagery dataset from DigitalGlobe, Inc. Any government, education, not-for-profit agency and public/individuals not engaged in using the "Product for Commercial Exploitation or Commercial Purposes" can use this licensed data. Use of this product for Commercial Purposes by a person/company/organization for a profit or fee is strictly prohibited. Please refer to the separately attached license from DigitalGlobe, Inc. for additional information. Digital orthoimagery combines the image characteristics of a digital image with the geometric qualities of a map. The primary dynamic digital orthophoto is a 60 centimeter ground resolution, image cast to the customer...
"USDA has purchased a Enterprise Premium license for this Orthoimagery dataset from DigitalGlobe, Inc. Any government, education, not-for-profit agency and public/individuals not engaged in using the "Product for Commercial Exploitation or Commercial Purposes" can use this licensed data. Use of this product for Commercial Purposes by a person/company/organization for a profit or fee is strictly prohibited. Please refer to the separately attached license from DigitalGlobe, Inc. for additional information. Digital orthoimagery combines the image characteristics of a digital image with the geometric qualities of a map. The primary dynamic digital orthophoto is a 60 centimeter ground resolution, image cast to the customer...
"USDA has purchased a Enterprise Premium license for this Orthoimagery dataset from DigitalGlobe, Inc. Any government, education, not-for-profit agency and public/individuals not engaged in using the "Product for Commercial Exploitation or Commercial Purposes" can use this licensed data. Use of this product for Commercial Purposes by a person/company/organization for a profit or fee is strictly prohibited. Please refer to the separately attached license from DigitalGlobe, Inc. for additional information. Digital orthoimagery combines the image characteristics of a digital image with the geometric qualities of a map. The primary dynamic digital orthophoto is a 60 centimeter ground resolution, image cast to the customer...
"USDA has purchased a Enterprise Premium license for this Orthoimagery dataset from DigitalGlobe, Inc. Any government, education, not-for-profit agency and public/individuals not engaged in using the "Product for Commercial Exploitation or Commercial Purposes" can use this licensed data. Use of this product for Commercial Purposes by a person/company/organization for a profit or fee is strictly prohibited. Please refer to the separately attached license from DigitalGlobe, Inc. for additional information. Digital orthoimagery combines the image characteristics of a digital image with the geometric qualities of a map. The primary dynamic digital orthophoto is a 60 centimeter ground resolution, image cast to the customer...
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