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On August 25, 2015 speaker Matt Germino presented on his work restoring sagebrush in the Great Basin. Shrubs are ecosystem foundation species in most of the Great Basin’s landscapes. Most of the species, including sagebrush, are poorly adapted to the changes in fire and invasive pressures that are compounded by climate change. This presentation gives an overview of challenges and opportunities regarding restoration of sagebrush and blackbrush, focusing on climate adaptation, selection of seeds and achieving seeding and planting success. Results from Great Basin LCC supported research on seed selection and planting techniques are presented.
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.
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: burn probability,
fire,
future climate,
gis,
rio grande,
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...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: burn probability,
fire,
fireline intensity,
future climate,
gis,
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...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: burn probability,
fire,
fireline intensity,
future climate,
gis,
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...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: burn probability,
fire,
fireline intensity,
future climate,
gis,
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...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: burn probability,
fire,
fireline intensity,
future climate,
gis,
Wildfire and fuel treatment locations for the USFWS Pacific Southwest Region (California, Nevada, Klamath Basin OR) extracted from the Fire Management Information System (FMIS) on October 23, 2015, for fiscal years 1980-2015.
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Citation,
Downloadable,
Map Service;
Tags: California,
Inventory and Monitoring,
Natural Resources,
Nevada,
Oregon,
This data release includes time-series data from a monitoring site located in a small drainage basin in the Arroyo Seco watershed in Los Angeles County, CA, USA (N3788964 E389956, UTM Zone 11, NAD83). The site was established after the 2009 Station Fire and recorded a series debris flows in the first winter after the fire. The data include three types of time-series: (1) 1-minute time series of rainfall, soil water content, channel bed pore pressure and temperature, and flow stage recorded by radar and laser distance meters (ArroyoSecoContinuous.csv); (2) 10-Hz time series of flow stage recorded by the laser distance meter during rain storms (ArroyoSecoStormLaser.csv), and (3) 2-second time series of rainfall and...
Categories: Data;
Types: Citation,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Arroyo Seco, California,
GHSC,
Geologic Hazards Science Center,
Landslides Hazards Program,
Los Angeles County, California,
First, we would like to thank the wildland fire advisory group. Their wisdom and guidance helped us build the dataset as it currently exists. Currently, there are multiple, freely available wildland fire datasets that identify wildfire and prescribed fire areas across the United States. However, these datasets are all limited in some way. Time periods, spatial extents, attributes, and maintenance for these datasets are highly variable, and none of the existing datasets provide a comprehensive picture of wildfires that have burned since the 1800s. Utilizing a series of both manual processes and ArcGIS Python (arcpy) scripts, we merged 40 of these disparate datasets into a single dataset that encompasses the known...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: Fire,
North America,
Prescribed Burn,
Prescribed Fire,
Raster,
Globally, changing fire regimes due to climate is one of the greatest threats to ecosystems and society. This dataset presents projections of historic and future fire probability for the southcentral U.S. using downscaled climate projections and the Physical Chemistry Fire Frequency Model (PC2FM, Guyette et al., 2012). Climate data from 1900-1929 and projected climate data for 2040-2069 and 2070-2099 were used as model inputs to the Physical Chemistry Fire Frequency Model (Guyette et al. 2012) to estimate fire probability. Baseline and future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. The nine associated data sets (tiffs) represent estimated change in mean fire probability...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: New Mexico,
Oklahoma,
Texas,
climate change,
mean fire interval,
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...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: conditional flame length,
fire,
future climate,
gis,
rio grande,
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...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: fire,
fire type,
future climate,
gis,
rio grande,
Burn probability (BP) raster dataset predicted for the 2020-2040 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.
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: burn probability,
fire,
future climate,
gis,
rio grande,
Burn probability (BP) for Fireline Intensity Class 1 (FIL1) with flame lengths in the range of 0-0.6 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...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: burn probability,
fire,
fireline intensity,
future climate,
gis,
This data release presents measurements and derived parameters for attributes of bulk density, loss on ignition, soil-water retention, and hydraulic conductivity for a site (Richardson) near Hess Creek in interior Alaska, USA. These measurements are useful for hydrologic modeling and predictions of water availability in this region.
This product releases data on soil physical and hydraulic properties in the area affected by the 2011 Las Conchas Fire in New Mexico, USA. Soil samples were collected in the summer of 2015 to assess the state of the watershed following the 2011 wildfire. Data include soil-hydraulic properties of field-saturated hydraulic conductivity and sorptivity from tension infiltrometer measurements on soil cores. Soil physical properties include bulk density, as-sampled volumetric soil-water content, and saturated volumetric soil-water content for 6-cm length soil cores. Soil properties of soil-particle size, bulk density, and soil organic matter content from loss on ignition for soil core splits of 0-1. 1-3, and 3-6 cm depth....
Categories: Data,
Data Release - Revised;
Types: Citation;
Tags: Jemez Mountains,
Las Conchas Fire,
New Mexico,
Santa Fe National Forest,
USGS Science Data Catalog (SDC),
***This data set is superseded by Welty, J.L., and Jeffries, M.I., 2021, Combined wildland fire datasets for the United States and certain territories, 1800s-Present: U.S. Geological Survey data release, https://doi.org/10.5066/P9ZXGFY3.*** This dataset is comprised of four different zip files. Zip File 1: A combined wildfire polygon dataset ranging in years from 1878-2019 (142 years) that was created by merging and dissolving fire information from 12 different original wildfire datasets to create one of the most comprehensive wildfire datasets available. Attributes describing fires that were reported in the various source data, including fire name, fire code, ignition date, controlled date, containment date, and...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: Botany,
Ecology,
Forestry,
Land Use Change,
North America,
This data release includes time-series data from a monitoring site located in a small (0.12 km2) drainage basin in the Las Lomas watershed in Los Angeles County, CA, USA. The site was established after the 2016 Fish Fire and recorded a series debris flows in the first winter after the fire. The station is located along the channel at the outlet of the study area (34 9’18.50”N, 117 56’41.33”W, WGS84). The data were collected between November 15, 2016 and February 23, 2017. The data include two types of time series: (1) continuous 1-minute time series of rainfall and flow stage recorded by a laser distance meter suspended over the channel (LasLomasContinuous.csv), and (2) 50-Hz time series of flow stage and flow-induced...
Categories: Data;
Tags: Ecology,
GHSC,
Geologic Hazards Science Center,
Landslides Hazards Program,
Las Lomas watershed,
First, we would like to thank the wildland fire advisory group. Their wisdom and guidance helped us build the dataset as it currently exists. Currently, there are multiple, freely available fire datasets that identify wildfire and prescribed fire burned areas across the United States. However, these datasets are all limited in some way. Their time periods could cover only a couple of decades or they may have stopped collecting data many years ago. Their spatial footprints may be limited to a specific geographic area or agency. Their attribute data may be limited to nothing more than a polygon and a year. None of the existing datasets provides a comprehensive picture of fires that have burned throughout the last...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: Fire,
North America,
Prescribed Burn,
Prescribed Fire,
United States,
This map shows areas that have experienced fire between 1999 and 2010, including fire severity information where available. Determination of "change" due to fire is not possible due to the lack of highly accurate pre- and post-fire maps of vegetation conditions, and the wide range of possible interpretations of what constitutes a change. Instead, the focus was placed on mapping the location of fires and severity; the overall likelihood of significant change in short term vegetation conditions increases with fire severity.
Categories: Data,
Map;
Types: ArcGIS REST Map Service,
Map Service;
Tags: Colorado Plateau,
change,
wildfire
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