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Our objective was to develop a species-distribution model using habitat associations that represent probability of suitable habitat for the species historical range and the range under climate change scenarios including a hot/dry prediction (MIROC3.2) and a cool/wet prediction (ECHAM5) and 1-m and 2-m sea level rise scenarios; urban growth was also inlcuded. Future model predictions were based on extrapolated data for two time steps in the 21st century: mid (2046-2064) and late (2081-2100). Species distributions were modeled with Maxent (Maximum Entropy presence-only algorithm); climate change scenarios were based on precipitation and temperature changes as applied to stream conditions (e.g., flow) modeled with...
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The LANDFIRE existing vegetation layers describe the following elements of existing vegetation for each LANDFIRE mapping zone: existing vegetation type, existing vegetation canopy cover, and existing vegetation height. Vegetation is mapped using predictive landscape models based on extensive field reference data, satellite imagery, biophysical gradient layers, and classification and regression trees.DATA SUMMARY: The existing vegetation type (EVT) data layer represents the current distribution of the terrestrial ecological systems classification developed by NatureServe for the western Hemisphere (http://www.natureserve.org/publications/usEcologicalsystems.jsp). A terrestrial ecological system is defined as a group...
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Burn probability (BP) raster dataset predicted for the 2080-2100 period in the Rio Grande area was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the 8.5 Representative Concentration Pathway.
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Burn probability (BP) for Fireline Intensity Class 6 (FIL6) with flame lengths in the range of 3.7-15 m predicted for the 2080-2100 period in the Rio Grande area. This raster dataset was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the 8.5...
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Burn probability (BP) for Fireline Intensity Class 2 (FIL2) with flame lengths in the range of 0.6-1.2 m predicted for the 2050-2070 period in the Rio Grande area. This raster dataset was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the...
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The SRLCC provided funds to the states of Arizona and New Mexico to support development of the states Crucial Habitat Assessment Tools (CHATs) which provide a decision support system to better incorporate wildlife values, sensitive animals and plants, and important ecosystem features into land use decision-making to reduce conflicts and surprises.Several states have released wildlife mapping tools that are the foundation for displaying crucial wildlife and corridor information. The state and regional CHATs are non-regulatory, and give project planners and the general public access to credible scientific data on a broad scale for use in project analysis, siting and planning. This includes large-scale development...
Categories: Data, Project; Types: ArcGIS REST Map Service, ArcGIS Service Definition, Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: AZ-01, AZ-02, AZ-03, AZ-04, AZ-05, All tags...
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Burn probability (BP) for Fireline Intensity Class 5 (FIL5) with flame lengths in the range of 2.4-3.7 m predicted for the 2080-2100 period in the Rio Grande area. This raster dataset was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the...
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Burn probability (BP) for Fireline Intensity Class 4 (FIL4) with flame lengths in the range of 1.8-2.4 m predicted for the 2050-2070 period in the Rio Grande area. This raster dataset was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the...
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The Central Mojave Vegetation Map (mojveg.e00) displays vegetation and other land cover types in the eastern Mojave of California. Map labels represent alliances and groups of alliances as described by the National Vegetation Classification. The nominal minimum mapping unit is 5 hectares. Each map unit is labeled by a primary land cover type and a secondary type where applicable. In addition, the source of data for labeling each map unit is also identified in the attribute table for each map unit. Data were developed using field visits, 1:32,000 aerial photography, SPOT satellite imagery, and predictive modeling.
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Conditional Flame Length (CFL) is an estimate of the mean flame lengths for each pixel, and was predicted for the 2050-2070 period in the Rio Grande area using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the 8.5 Representative Concentration Pathway. CFL...
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Fire type predicted for the 2020-2040 period in the Rio Grande area with five classes: 1) shrub vegetation with torching flames; 2) shrub vegetation without torching flames; 3) forest with torching flames; 4) forest without torching flames; 5) grass or non-vegetation. This raster dataset was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model...


map background search result map search result map LANDFIRE - Existing vegetation type for the Oregon Portion of the North Pacific LCC, USA (version 1.1.0) Support to Western States Crucial Habitat Assessment Tools Western Painted Turtle: Current Habitat Suitability Consensus of All Models Occult Bat: Current Habitat Suitability Consensus of All Models Long-legged Bat: Current Habitat Suitability Consensus of All Models Yuma Bat: 2090 Habitat Suitability Consensus of All Models American Bullfrog: 2030 Habitat Suitability Consensus of All Models American Bullfrog: 2090 Habitat Suitability Consensus of All Models Northern Leopard Frog: Current Habitat Suitability Consensus of All Models Northern Leopard Frog: 2030 Habitat Suitability Consensus of All Models Central Mojave Vegetation Map Burn Probability for Fireline Intensity Class 2, predicted for 2050 to 2070 for Rio Grande study area Burn Probability for Fireline Intensity Class 4, predicted for 2050 to 2070 for Rio Grande study area Burn Probability for Fireline Intensity Class 5, predicted for 2080 to 2100 for Rio Grande study area Burn Probability for Fireline Intensity Class 6, predicted for 2080 to 2100 for Rio Grande study area Burn Probability predicted for 2080 to 2100 for Rio Grande study area Conditional Flame Length predicted for 2050 to 2070 for Rio Grande study area Fire type predicted for 2020 to 2040 for Rio Grande study area Parking Areas, Tule Lake NWR apalachicola_Floater.mxd apalachicola_Floater.mxd Central Mojave Vegetation Map Long-legged Bat: Current Habitat Suitability Consensus of All Models Western Painted Turtle: Current Habitat Suitability Consensus of All Models Occult Bat: Current Habitat Suitability Consensus of All Models Yuma Bat: 2090 Habitat Suitability Consensus of All Models American Bullfrog: 2030 Habitat Suitability Consensus of All Models American Bullfrog: 2090 Habitat Suitability Consensus of All Models Northern Leopard Frog: Current Habitat Suitability Consensus of All Models Northern Leopard Frog: 2030 Habitat Suitability Consensus of All Models Burn Probability for Fireline Intensity Class 2, predicted for 2050 to 2070 for Rio Grande study area Burn Probability for Fireline Intensity Class 4, predicted for 2050 to 2070 for Rio Grande study area Burn Probability for Fireline Intensity Class 5, predicted for 2080 to 2100 for Rio Grande study area Burn Probability for Fireline Intensity Class 6, predicted for 2080 to 2100 for Rio Grande study area Conditional Flame Length predicted for 2050 to 2070 for Rio Grande study area Fire type predicted for 2020 to 2040 for Rio Grande study area Burn Probability predicted for 2080 to 2100 for Rio Grande study area LANDFIRE - Existing vegetation type for the Oregon Portion of the North Pacific LCC, USA (version 1.1.0) Support to Western States Crucial Habitat Assessment Tools Parking Areas, Tule Lake NWR