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This release contains Active Layer Thickness (ALT) and Organic Layer Thickness (OLT) measurements measured along transects in Alaska, 2015. Site condition information in terms of wildfire burns is also included.
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Monthly Standardize Precipitation Evapotranspiration Index (SPEI), Daily soil-water potential (MPa) and soil temperature (degree C) data for plots from SageSuccess. The SageSuccess Project is a joint effort between USGS, BLM, and FWS to understand how to establish big sagebrush and ultimately restore functioning sagebrush ecosystems. Improving the success of land management treatments to restore sagebrush-steppe is important for reducing the long-term impacts of rangeland fire on sage-grouse and over 350 other wildlife species that use these habitats.
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These are model input and comparative data derived from pre-fire aerial LiDAR acquired in May 2012 for a small basin in the Valles Caldera, Northern New Mexico to represent canopy characteristics pre-fire. These characteristics include, (1) canopy closure, (2) edginess to the north, (3) edginess to the south, (4) leaf area index, (5) maximum tree height, (6) mean distance to canopy, (7) mean tree height, and (8) total gap area. These input data are intended to accompany a published report (The effects of wildfire on snow water resources estimated from canopy disturbance patterns and meteorological conditions [Moeser, Broxton and Harpold, 2019]). Each characteristic is provided in an individual ascii file. All data...
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First, we would like to thank the wildland fire advisory group. Their wisdom and guidance helped us build the dataset as it currently exists. This dataset is comprised of two different zip files. Zip File 1: The data within this zip file are composed of two wildland fire datasets. (1) A merged dataset consisting of 40 different wildfire and prescribed fire layers. The original 40 layers were all freely obtained from the internet or provided to the authors free of charge with permission to use them. The merged layers were altered to contain a consistent set of attributes including names, IDs, and dates. This raw merged dataset contains all original polygons many of which are duplicates of the same fire. This dataset...
Electrical resistivity tomography (ERT) measurements were collected by the U.S. Geological Survey (USGS) at two sites in Interior Alaska in September 2019 for the purposes of imaging permafrost structure and quantifying variations in subsurface moisture content in relation to thaw features. First, ERT data were collected at Big Trail Lake, a thermokarst lake outside of Fairbanks, Alaska, to quantify permafrost characteristics beneath the lake and across its shorelines. Three 222 m ERT survey lines were collected perpendicular to the North, East, and South shorelines, and two 110 m lines were collected parallel to the southeast and northeast shorelines. Models of electrical resistivity produced from these data revealed...
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This tabular, machine-readable CSV file contains annual phenometrics at locations in ponderosa pine ecosystems across Arizona and New Mexico that experienced stand-clearing, high-severity fire. The locations represent areas of vegetative recovery towards pre-fire (coniferous/pine) vegetation communities or towards novel grassland, shrubland, or deciduous replacements. Each sampled area is associated with the point location (latitude/longitude) as well as multiple calendar year phenometrics derived from the time-series of normalized difference vegetation index (NDVI) values in the phenology software package Timesat v3.2.
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These are Snow Water Equivalent (SWE) SnowPALM model output data for an area in the Valles Caldera, northern New Mexico. These pre-fire model output data are intended to accompany a published report (The effects of wildfire on snow water resources estimated from canopy disturbance patterns and meteorological conditions [Moeser, Broxton and Harpold, 2019]). All data are in a gridded format where the lower left hand corner is located at 3979325 north, and 371710 east in Zone 13N with a map datum of NAD83. The grid is comprised of 1000 rows by 1100 columns with a grid cell size of 1m for a total domain size of 1.0km x 1.1km. Data output is on a daily time step and ranges between the 1st of September 1981 (labeled:...
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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...
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This dataset provides a near-real-time estimate of 2018 herbaceous annual cover with an emphasis on annual grass (Boyte and Wylie. 2016. Near-real-time cheatgrass percent cover in the Northern Great Basin, USA, 2015. Rangelands 38:278-284.) This estimate was based on remotely sensed enhanced Moderate Resolution Imaging Spectroradiometer (eMODIS) Normalized Difference Vegetation Index (NDVI) data gathered through July 1, 2018. This is the second iteration of an early estimate of herbaceous annual cover for 2018 over the same geographic area. The previous dataset used eMODIS NDVI data gathered through May 1 (https://doi.org/10.5066/P9KSR9Z4). The pixel values for this most recent estimate ranged from 0 to100% with...
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This is a spatially-explicit state-and-transition simulation model of buffelgrass dynamics in Saguaro National Park. Buffelgrass is an invasive grass spreading in the park. The model represents uninvaded and invaded parts of the desert ecosystem including transition pathways related to management activities and includes a connection to a fire behavior model. The model was built using the ST-Sim software platform linked to the FARSITE fire behavior model. The St-SIM file structure includes three components: 1) Buffelgrass.ssim.input folder that houses the input files used by St-SIM, 2) the Buffelgrass.ssim.output folder which houses the scenario outputs used by St-SIM for visualization and export of data, and 3)...
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***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...
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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...
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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...
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These data were generated with MAXENT 3.3.3k freeware (Phillips et al. 2011) using climate data and fire probability data for for three time periods: reference (1900-1929), mid-century (2040-2069) and late century (2070-2099), and community occurrence point data extracted from LANDFIRE Environmental Site Potential (ESP). Future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. In MAXENT, we used the logistic output format (generating presence probabilities between 0 and 1), a random test percentage of 30 (using 70 % of the occurrence points to generate the suitability model and 30 % of the occurrence points to validate it), and a jackknife test to measure variable importance....
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Fire can be a significant driver of permafrost change in boreal landscapes, altering the availability of soil carbon and nutrients that have important implications for future climate and ecological succession. However, not all landscapes are equally susceptible to fire-induced change. As fire frequency is expected to increase in the high latitudes, methods to understand the vulnerability and resilience of different landscapes to permafrost degradation are needed. Geophysical and other field observations reveal details of both near-surface (less than 1 m) and deeper (greater than 1 m) impacts of fire on permafrost along 14 transects that span burned-unburned boundaries in different landscape settings within interior...
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Fire can be a significant driver of permafrost change in boreal landscapes, altering the availability of soil carbon and nutrients that have important implications for future climate and ecological succession. However, not all landscapes are equally susceptible to fire-induced change. As fire frequency is expected to increase in the high latitudes, methods to understand the vulnerability and resilience of different landscapes to permafrost degradation are needed. Geophysical and other field observations reveal details of both near-surface (less than 1 m) and deeper (greater than 1 m) impacts of fire on permafrost along 14 transects that span burned-unburned boundaries in different landscape settings within interior...
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Management of transportation networks is affected by, and has effects on, natural and cultural resources through direct and indirect interactions. Until recently, the availability of such spatially explicit information has been limited; however, the data released here to the public will prove valuable for comparing existing networks and planning options with respect to potential impact to, or from, environmental factors across broad areas, for example, States and Agency Planning Regions. Integrated network and resource analyses can provide insights into potential construction and maintenance costs as well as safety risks and environmental impacts during project planning and assessment. A cooperative project was...
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Fire can be a significant driver of permafrost change in boreal landscapes, altering the availability of soil carbon and nutrients that have important implications for future climate and ecological succession. However, not all landscapes are equally susceptible to fire-induced change. As fire frequency is expected to increase in the high latitudes, methods to understand the vulnerability and resilience of different landscapes to permafrost degradation are needed. Geophysical and other field observations reveal details of both near-surface (less than 1 m) and deeper (greater than 1 m) impacts of fire on permafrost along 14 transects that span burned-unburned boundaries in different landscape settings within interior...
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The dataset provides a spatially explicit estimate of 2019 herbaceous annual percent cover predicted on May 1st with an emphasis on annual grasses. The estimate is based on the mean output of two regression-tree models. For one model, we include, as an independent variable amongst other independent variables, a dataset that is the mean of 17-years of annual herbaceous percent cover (https://doi.org/10.5066/F71J98QK). This model's test mean error rate (n = 1670), based on nine different randomizations, equals 4.9% with a standard deviation of +/- 0.15. A second model was developed that did not include the mean of 17-years of annual herbaceous percent cover, and this model's test mean error rate (n = 1670), based...


map background search result map search result map Fire impacts on permafrost in Alaska: Geophysical and other field data collected in 2015 Compilation and Assessment of Resource Values and Hazards to Inform Transportation and Associated Land-use Planning Borehole Nuclear Magnetic Resonance Inverted Models; Alaska, 2015 Electrical Resistivity Tomography Inverted Models; Alaska, 2015 Permafrost Soil Measurements; Alaska, 2015 Permafrost Vegetation Measurements; Alaska, 2015 Reference period and projected environmental suitability scores Near-real-time Herbaceous Annual Cover in the Sagebrush Ecosystem, USA, July 2018 Post-wildfire debris-flow monitoring data, Las Lomas, 2016 Fish Fire, Los Angeles County, California, November 2016 to February 2017 State-and-Transition Simulation Model of Buffelgrass in Saguaro National Park (2014-2044) Early Estimates of Herbaceous Annual Cover in the Sagebrush Ecosystem (May 1, 2019) Pre-Fire Input Data Snow Water Equivalent Phenology pattern data indicating recovery trajectories of ponderosa pine forests after high-severity fires Ecological Drought for Sagebrush Seedings in the Great Basin Combined wildfire datasets for the United States and certain territories, 1878-2019 Alaska permafrost characterization: Electrical Resistivity Tomography Data & Models from 2019 Combined wildland fire datasets for the United States and certain territories, 1800s-Present Post-wildfire debris-flow monitoring data, Las Lomas, 2016 Fish Fire, Los Angeles County, California, November 2016 to February 2017 Pre-Fire Input Data Snow Water Equivalent State-and-Transition Simulation Model of Buffelgrass in Saguaro National Park (2014-2044) Alaska permafrost characterization: Electrical Resistivity Tomography Data & Models from 2019 Borehole Nuclear Magnetic Resonance Inverted Models; Alaska, 2015 Permafrost Soil Measurements; Alaska, 2015 Permafrost Vegetation Measurements; Alaska, 2015 Fire impacts on permafrost in Alaska: Geophysical and other field data collected in 2015 Electrical Resistivity Tomography Inverted Models; Alaska, 2015 Ecological Drought for Sagebrush Seedings in the Great Basin Phenology pattern data indicating recovery trajectories of ponderosa pine forests after high-severity fires Near-real-time Herbaceous Annual Cover in the Sagebrush Ecosystem, USA, July 2018 Early Estimates of Herbaceous Annual Cover in the Sagebrush Ecosystem (May 1, 2019) Reference period and projected environmental suitability scores Compilation and Assessment of Resource Values and Hazards to Inform Transportation and Associated Land-use Planning Combined wildland fire datasets for the United States and certain territories, 1800s-Present Combined wildfire datasets for the United States and certain territories, 1878-2019