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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.
Categories: Data;
Types: Citation;
Tags: Active layer,
Active layer thickness,
Alaska,
Borehole nuclear magnetic resonance,
Chatanika,
The point data file ("Soda Fire Point and Pasture Data (2016).Point Data.csv") includes 2016 vegetative cover values of exotic annual grass and perennial grass measured within three different types of plots for 75 pastures in the Soda Fire, which burned in 2015: 6m² plot using a grid-point intercept photo software, SamplePoint (Booth et al. 2006), 1m² quadrat using an unguided rapid ocular estimate in the field, 531m² circular plot using an unguided rapid ocular estimate in the field. Smaller plots were nested within larger plots. The pasture data file ("Soda Fire Point and Pasture Data (2016).Pasture Data.csv") includes pasture level metrics of area, elevation, precipitation, slope, heatload, soils, and herbicide...
Prescribed burning is a critical tool for managing wildfire risks and meeting ecological objectives, but its safe and effective application requires that specific meteorological criteria are met. This dataset contains results from a study examining the potential impacts of projected climatic change on prescribed burning in the southeastern United States. A set of burn window criteria (suitable weather conditions within which burning may occur based on maximum daily temperature, daily average relative humidity, and daily average wind speed), were applied to projections from an ensemble of Global Climate Models (GCM) under two greenhouse gas emission scenarios, as well as past observations for comparison. Data are...
Prescribed burning is a critical tool for managing wildfire risks and meeting ecological objectives, but its safe and effective application requires that specific meteorological criteria are met. This dataset contains results from a study examining the potential impacts of projected climatic change on prescribed burning in the southeastern United States. A set of burn window criteria (suitable weather conditions within which burning may occur based on maximum daily temperature, daily average relative humidity, and daily average wind speed), were applied to projections from an ensemble of Global Climate Models (GCM) under two greenhouse gas emission scenarios, as well as past observations for comparison. Data are...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Alabama,
Arkansas,
Florida,
Georgia,
Kentucky,
Prescribed burning is a critical tool for managing wildfire risks and meeting ecological objectives, but its safe and effective application requires that specific meteorological criteria are met. This dataset contains results from a study examining the potential impacts of projected climatic change on prescribed burning in the southeastern United States. A set of burn window criteria (suitable weather conditions within which burning may occur based on maximum daily temperature, daily average relative humidity, and daily average wind speed), were applied to projections from an ensemble of Global Climate Models (GCM) under two greenhouse gas emission scenarios, as well as past observations for comparison. Data are...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Alabama,
Arkansas,
Florida,
Georgia,
Kentucky,
LANDFIRE's (LF) 2022 update (LF 2022) Existing Vegetation Cover (EVC) represents the vertically projected percent cover of the live canopy for a 30-m cell. EVC is produced separately for tree, shrub, and herbaceous lifeforms. Training data depicting percentages of canopy cover are obtained from plot-level ground-based visual assessments and lidar observations. These are combined with Landsat imagery (from multiple seasons), to inform models built independently for each lifeform. Tree, shrub, and herbaceous lifeforms each have a potential range from 10% to 100% (cover values less than 10% are binned into the 10% value). The three independent lifeform datasets are merged into a single product based on the dominant...
LANDFIRE (LF) disturbance products are developed to provide temporal and spatial information related to landscape change. Historical Disturbance (HDist) is developed from the base annual LF disturbance products, and attribute code system, to represent the history of disturbance for a 10-year span. Each year's disturbance scenarios are checked against time relevant LF vegetation products to check for logical inconsistencies. Errant codes are flagged and updated to a discard code with the remaining disturbance types cross-walked/aggregated to Fuel Disturbance (FDist) types. HDist includes the year of disturbance that is recorded for that pixel. In LF 2022, the time since disturbance code is the same for both HDist...
LANDFIRE (LF) 2022 Fuel Vegetation Type (FVT) represents the LF Existing Vegetation Type Ecological Systems (EVT) product, modified to represent pre-disturbance EVT in areas where disturbances have occurred over the past 10 years. Due to shifting EVT codes and labels throughout the years, the FVT codes are based on an early version of EVT codes translated from the current version. FVT is an input for fuel transitions related to disturbance. Fuel products in LF 2022 were created with LF 2016 Remap vegetation in non-disturbed areas. To designate disturbed areas where FVT is modified, the aggregated Annual Disturbance products from 2013 to 2022 in the Fuel Disturbance (FDist) product are used. All existing disturbances...
LANDFIRE's (LF) 2022 Forest Canopy Cover (CC) describes the percent cover of the tree canopy in a stand. CC is a vertical projection of the tree canopy cover onto an imaginary horizontal plane. CC supplies information for fire behavior models to determine the probability of crown fire initiation, provide input in the spotting model, calculate wind reductions, and to calculate fuel moisture conditioning. To create this product, plot level CC values are calculated using the canopy fuel estimation software, Forest Vegetation Simulator (FVS). Pre-disturbance CC and Canopy Height (CH) are used as predictors of disturbed CC using a linear regression equation per Fuel Vegetation Type (FVT), disturbance type/severity, and...
LANDFIRE (LF) 2022 Fuel Vegetation Cover (FVC) represents the LF Existing Vegetation Cover (EVC) product, modified to represent pre-disturbance EVC in areas where disturbances have occurred over the past 10 years. EVC is mapped as continuous estimates of canopy cover for tree, shrub, and herbaceous lifeforms with a potential range from 10% to 100%. Continuous EVC values are binned to align with fuel model assignments when creating FVC. FVC is an input for fuel transitions related to disturbance. Fuel products in LF 2022 were created with LF 2016 Remap vegetation in non-disturbed areas. To designate disturbed areas where FVC is modified, the aggregated Annual Disturbance products from 2013 to 2022 in the Fuel Disturbance...
Twenty quadrats within the burn perimeter of a September 2021 wildfire outside of Boise, Idaho were surveyed for the abundance of fire effects, biocrusts and vascular plants immediately post-fire. The fire was too small to be named. Char was measured as a proxy for fire intensity. Biocrusts were surveyed by morphogroup (crustose lichens, cup lichens, fruticose lichens, gelatinous lichens, short moss, tall moss) and vascular plants were surveyed by functional group (annual forbs, perennial grasses). Char was measured ocularly and biocrust/plant abundance was measured via point-vertex intercept at 40 points per quadrat. These data support the following publication: Condon, L.A., Shinneman, D.J., Rosentreter, R. and...
This dataset records mortality-- including involvement of bark beetles-- and burn severity information for trees in long term forest dynamics plots in Sequoia National Park and Yosemite National Park that experienced fire. These data support the following publication: Furniss, T.J., Das, A.J., van Mantgem, P.J., Stephenson, N.L. and Lutz, J.A., 2021. Crowding, climate, and the case for social distancing among trees. Ecological Applications, p.e2507, https://doi.org/10.1002/eap.2507
Categories: Data;
Tags: California,
Forestry,
Sequoia National Park,
Sierra Nevada,
USGS Science Data Catalog (SDC),
This portion of the data release presents a digital surface model (DSM) and hillshade of Whiskeytown Lake and the surrounding area derived from Structure from Motion (SfM) processing of aerial imagery acquired on 2018-12-02. Unlike a digital elevation model (DEM), the DSM represents the elevation of the highest object within the bounds of a cell. Vegetation, buildings and other objects have not been removed from the data. In addition, data artifacts resulting from noise and vegetation in the original imagery have not been removed. However, in unvegetated areas such as reservoir shorelines and deltas, the DSM is equivalent to a DEM because it represents the ground surface elevation. The raw imagery used to create...
The LANDFIRE (LF) Canadian Forest Fire Danger Rating System (CFFDRS) product depicts fuel types as an identifiable association of fuel elements of distinctive species, form, size, arrangement, and continuity. CFFDRS exhibits characteristic fire behavior under the specified burn conditions. In LF 2022 Canadian fuel models are derived from the Fuel Model Guide to Alaska Vegetation (Alaska Fuel Model Guide Task Group, 2018) and subsequent updates. The LF CFFDRS product contains the fuel models used for the Fire Behavior Prediction (FBP) system fuel type inputs. Default values assigned to the Canadian Fuel Models required to run the Prometheus fire behavior software (Prometheus, 2021) are added as attributes to the...
LANDFIRE's (LF) 2022 Forest Canopy Height (CH) describes the average height of the top of the canopy for a stand. CH is used in the calculation of Canopy Bulk Density (CBD) and Canopy Base Height (CBH). CH supplies information for fire behavior models, such as FARSITE (Finney 1998), that can determine the starting point of embers in the spotting model, wind reductions, and the volume of crown fuels. To create this product, plot level CH values are calculated using the canopy fuel estimation software, Forest Vegetation Simulator (FVS). Pre-disturbance Canopy Cover and CH are used as predictors of disturbed CH using a linear regression equation per Fuel Vegetation Type (FVT), disturbance type/severity, and time since...
LANDFIRE (LF) disturbance products are developed to provide temporal and spatial information related to landscape change. LF 2022 Fuel Disturbance (FDist) uses the latest Annual Disturbance products from the effective disturbance years of 2013 to 2022. FDist is created from LF 2022 Historical Disturbance (HDist) which in turn aggregates the Annual Disturbance products. FDist groups similar disturbance types, severities and time since disturbance categories which represent disturbance scenarios within the fuel environment. FDist is used in conjunction with Fuel Vegetation Type (FVT), Cover (FVC), and Height (FVH) to calculate Canopy Cover (CC), Canopy Height (CH), Canopy Bulk Density (CBD), Canopy Base Height (CBH),...
Seventy six parent and alkylated polycyclic aromatic compounds, including polycyclic aromatic hydrocarbons (PAHs), were quantified in watershed and reef sediment from Olowalu, Maui, in February 2022 to explore urban and wildfire effects. Sample locations and total organic carbon contents (OC) are available in the accompanying file OlowaluWatershedReef2022_compositions.csv.
Categories: Data;
Tags: CMHRP,
Coastal and Marine Hazards and Resources Program,
Kealaloloa Ridge,
Kihei,
Kulanihakoi Gulch,
We used a hierarchical Bayesian modeling framework to estimate resource selection functions and survival for early and late brood-rearing stages of sage-grouse in relation to a broad suite of habitat characteristics evaluated at multiple spatial scales within the Great Basin from 2009 to 2019. Sage-grouse selected for greater perennial grass cover, higher relative elevations, and areas closer to springs and wet meadows during both early and late brood-rearing. Terrain characteristics, including heat load and aspect, were important in survival models, as was variation in shrub height. We also found strong evidence for higher survival for both early and late broods within previously burned areas, but survival within...
Ranked habitat classes for sage-grouse brood-rearing productivity at each 90 m pixel. Habitat classes represent areas where high brood selection and high brood survival intersected, whereas the lowest ranks represent areas where high brood habitat selection intersected with the low brood survival. Hierarchical models of brood selection and survival were fit to landscape covariates within a Bayesian modeling framework in Nevada and California from 2009 - 2017 to develop spatially explicit information about brood habitat selection and survival.
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...
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