Data includes functional group cover of annual grasses, perennial grasses and shrubs, and model predicted fire behavior for the years of 2018-2021.

Data includes field observed cover of several vegetation functional groups, e.g. annual herbaceous, perennial herbaceous, exotic annual grasses, perennial bunch grasses, shrubs, sagebrush shrubs, non-sagebrush shrubs, bare mineral soil, rocks, and litter. Additionally, if tree canopy was present within field plots, tree canopy cover was estimated, forest type recorded, and the number of individual trees rooted within the plot counted. Standard fire behavior fuel models were classified for each plot. Available data from remotely sensed models estimating soil properties, topographic features, solar radiation indices, and vegetation cover by functional group are also included.

These data were compiled so that annual wildfire could be modelled across the sagebrush region in the western United States. Our goal was to understand how wildfire probability relates to climate and fuel conditions across the entire sagebrush region. To do this we developed a statistical model that represents the relationship between annual wildfire probability and a small number of climate and fuel variables. Specifically, created predictions of wildfire probability using a biologically plausible logistic regression model that related wildfire probability to mean temperature, annual precipitation, the proportion summer precipitation (PSP), and aboveground biomass of annual herbaceous plants and perennial herbaceous plants. The biomass variables were used as proxies for fine fuel availability. These data represent annual fire occurrence in 1 km pixels (i.e. did a given pixel burn that year), predicted wildfire probability, as well as the three year running average (i.e. average across the current and previous two years) of climate and vegetation variables. These data were collected across the sagebrush region (the extent of the study area is provided by the cell_number_ids.tif file). The climate and vegetation data were compiled using a existing gridded dataset (Daymet) of daily precipitation and temperature, and vegetation data were summaries of annual estimates of aboveground biomass of annual and perennial herbaceous plants from the Rangeland Analysis Platform (https://rangelands.app/). These data can be used to understand spatial and temporal variability in wildfire occurrence and modelled wildfire probability between 1988 and 2019 and how that variability relates to spatial and temporal variability in climate and vegetation.

These data were compiled so that annual wildfire could be modelled across the sagebrush region in the western United States. Our goal was to understand how wildfire probability relates to climate and fuel conditions across the entire sagebrush region. To do this we developed a statistical model that represents the relationship between annual wildfire probability and a small number of climate and fuel variables. Specifically, created predictions of wildfire probability using a biologically plausible logistic regression model that related wildfire probability to mean temperature, annual precipitation, the proportion summer precipitation (PSP), and aboveground biomass of annual herbaceous plants and perennial herbaceous plants. The biomass variables were used as proxies for fine fuel availability. These data represent annual fire occurrence in 1 km pixels (i.e. did a given pixel burn that year), predicted wildfire probability, as well as the three year running average (i.e. average across the current and previous two years) of climate and vegetation variables. These data were collected across the sagebrush region (the extent of the study area is provided by the cell_number_ids.tif file). The climate and vegetation data were compiled using a existing gridded dataset (Daymet) of daily precipitation and temperature, and vegetation data were summaries of annual estimates of aboveground biomass of annual and perennial herbaceous plants from the Rangeland Analysis Platform (https://rangelands.app/). These data can be used to understand spatial and temporal variability in wildfire occurrence and modelled wildfire probability between 1988 and 2019 and how that variability relates to spatial and temporal variability in climate and vegetation.

LANDFIRE's (LF) 2022 13 Anderson Fire Behavior Fuel Models (FBFM13) product represents distinct distributions of fuel loadings found among surface fuel components (live and dead), size classes, and fuel types (Anderson 1982). The fuel models are described by the most common fire carrying fuel type (grass, brush, timber, or slash), loading and surface area-to-volume ratio by size class and component, fuel bed depth, and moisture of extinction. LF FBFM13 can be used for fire spread related characteristic models. To create this product, expert rulesets were developed to understand how different types of disturbance would change pre-disturbance fuel models to post disturbance fuels, based on the severity and time since disturbance. These rulesets are represented in the LF Total Fuel Change Tool and Database. In the LF 2022 update, non-disturbed fuels are the same as LF 2016 Remap for natural vegetation. To designate disturbed areas where FBFM13 is modified, the aggregated Annual Disturbance products from 2013 to 2022 in the Fuel Disturbance (FDist) product are used. All existing disturbances between 2013-2022 are represented in the LF 2022 update, and the products are intended to be used in 2023 (the year of release). The "capable" year terminology used in LF 2020 and LF 2016 Remap is no longer specified, due to reduction in latency from when a disturbance occurs to the release date of fuel products accounting for that disturbance. However, users should still consider adjusting fuel layers for disturbances that occurred after the end of the 2022 fiscal year (after October 1st, 2022) when using the LF 2022 fuel products. Because those changes would not be accounted for. Learn more about LF 2022 at https://landfire.gov/lf_230.php

LANDFIRE's (LF) 2022 13 Anderson Fire Behavior Fuel Models (FBFM13) product represents distinct distributions of fuel loadings found among surface fuel components (live and dead), size classes, and fuel types (Anderson 1982). The fuel models are described by the most common fire carrying fuel type (grass, brush, timber, or slash), loading and surface area-to-volume ratio by size class and component, fuel bed depth, and moisture of extinction. LF FBFM13 can be used for fire spread related characteristic models. To create this product, expert rulesets were developed to understand how different types of disturbance would change pre-disturbance fuel models to post disturbance fuels, based on the severity and time since disturbance. These rulesets are represented in the LF Total Fuel Change Tool and Database. In the LF 2022 update, non-disturbed fuels are the same as LF 2016 Remap for natural vegetation. To designate disturbed areas where FBFM13 is modified, the aggregated Annual Disturbance products from 2013 to 2022 in the Fuel Disturbance (FDist) product are used. All existing disturbances between 2013-2022 are represented in the LF 2022 update, and the products are intended to be used in 2023 (the year of release). The "capable" year terminology used in LF 2020 and LF 2016 Remap is no longer specified, due to reduction in latency from when a disturbance occurs to the release date of fuel products accounting for that disturbance. However, users should still consider adjusting fuel layers for disturbances that occurred after the end of the 2022 fiscal year (after October 1st, 2022) when using the LF 2022 fuel products. Because those changes would not be accounted for. Learn more about LF 2022 at https://landfire.gov/lf_230.php

LANDFIRE's 2023 Update (LF 2023) 13 Anderson Fire Behavior Fuel Models (FBFM13) product represents distinct distributions of fuel loadings found among surface fuel components (live and dead), size classes, and fuel types (Anderson 1982). The fuel models are described by the most common fire carrying fuel type (grass, brush, timber, or slash), loading and surface area-to-volume ratio by size class and component, fuel bed depth, and moisture of extinction. LF FBFM13 can be used for fire spread related characteristic models. To create the FBFM13 product, expert rulesets were developed to understand how different types of disturbance would change pre-disturbance fuel models to post disturbance fuels, based on the severity and time since disturbance. These rulesets are represented in the LF Total Fuel Change (LFTFC) Tool and Database. In LF 2023, non-disturbed fuels are the same as LF 2016 Remap for natural vegetation. To designate disturbed areas where FBFM13 is modified, the aggregated Annual Disturbance products from 2014 to 2023 in the LF Fuel Disturbance (FDist) product are used. All existing disturbances between 2014-2023 are represented in LF 2023, and the products are intended to be used in 2024 (the year of release). When using any product from the LF 2023 fuel product suite, users should consider adjusting fuel layers for disturbances that occurred after the end of the 2023 fiscal year (after October 1st, 2023). Disturbances that occurred after the end of the 2023 fiscal year are not accounted for within LF 2023 fuel products. Learn more about LF 2023 at https://landfire.gov/data/lf2023

LANDFIRE's 2023 Update (LF 2023) 13 Anderson Fire Behavior Fuel Models (FBFM13) product represents distinct distributions of fuel loadings found among surface fuel components (live and dead), size classes, and fuel types (Anderson 1982). The fuel models are described by the most common fire carrying fuel type (grass, brush, timber, or slash), loading and surface area-to-volume ratio by size class and component, fuel bed depth, and moisture of extinction. LF FBFM13 can be used for fire spread related characteristic models. To create the FBFM13 product, expert rulesets were developed to understand how different types of disturbance would change pre-disturbance fuel models to post disturbance fuels, based on the severity and time since disturbance. These rulesets are represented in the LF Total Fuel Change (LFTFC) Tool and Database. In LF 2023, non-disturbed fuels are the same as LF 2016 Remap for natural vegetation. To designate disturbed areas where FBFM13 is modified, the aggregated Annual Disturbance products from 2014 to 2023 in the LF Fuel Disturbance (FDist) product are used. All existing disturbances between 2014-2023 are represented in LF 2023, and the products are intended to be used in 2024 (the year of release). When using any product from the LF 2023 fuel product suite, users should consider adjusting fuel layers for disturbances that occurred after the end of the 2023 fiscal year (after October 1st, 2023). Disturbances that occurred after the end of the 2023 fiscal year are not accounted for within LF 2023 fuel products. Learn more about LF 2023 at https://landfire.gov/data/lf2023

LANDFIRE's (LF) 2022 13 Anderson Fire Behavior Fuel Models (FBFM13) product represents distinct distributions of fuel loadings found among surface fuel components (live and dead), size classes, and fuel types (Anderson 1982). The fuel models are described by the most common fire carrying fuel type (grass, brush, timber, or slash), loading and surface area-to-volume ratio by size class and component, fuel bed depth, and moisture of extinction. LF FBFM13 can be used for fire spread related characteristic models. To create this product, expert rulesets were developed to understand how different types of disturbance would change pre-disturbance fuel models to post disturbance fuels, based on the severity and time since disturbance. These rulesets are represented in the LF Total Fuel Change Tool and Database. In the LF 2022 update, non-disturbed fuels are the same as LF 2016 Remap for natural vegetation. To designate disturbed areas where FBFM13 is modified, the aggregated Annual Disturbance products from 2013 to 2022 in the Fuel Disturbance (FDist) product are used. All existing disturbances between 2013-2022 are represented in the LF 2022 update, and the products are intended to be used in 2023 (the year of release). The "capable" year terminology used in LF 2020 and LF 2016 Remap is no longer specified, due to reduction in latency from when a disturbance occurs to the release date of fuel products accounting for that disturbance. However, users should still consider adjusting fuel layers for disturbances that occurred after the end of the 2022 fiscal year (after October 1st, 2022) when using the LF 2022 fuel products. Because those changes would not be accounted for. Learn more about LF 2022 at https://landfire.gov/lf_230.php

LANDFIRE's (LF) 2022 13 Anderson Fire Behavior Fuel Models (FBFM13) product represents distinct distributions of fuel loadings found among surface fuel components (live and dead), size classes, and fuel types (Anderson 1982). The fuel models are described by the most common fire carrying fuel type (grass, brush, timber, or slash), loading and surface area-to-volume ratio by size class and component, fuel bed depth, and moisture of extinction. LF FBFM13 can be used for fire spread related characteristic models. To create this product, expert rulesets were developed to understand how different types of disturbance would change pre-disturbance fuel models to post disturbance fuels, based on the severity and time since disturbance. These rulesets are represented in the LF Total Fuel Change Tool and Database. In the LF 2022 update, non-disturbed fuels are the same as LF 2016 Remap for natural vegetation. To designate disturbed areas where FBFM13 is modified, the aggregated Annual Disturbance products from 2013 to 2022 in the Fuel Disturbance (FDist) product are used. All existing disturbances between 2013-2022 are represented in the LF 2022 update, and the products are intended to be used in 2023 (the year of release). The "capable" year terminology used in LF 2020 and LF 2016 Remap is no longer specified, due to reduction in latency from when a disturbance occurs to the release date of fuel products accounting for that disturbance. However, users should still consider adjusting fuel layers for disturbances that occurred after the end of the 2022 fiscal year (after October 1st, 2022) when using the LF 2022 fuel products. Because those changes would not be accounted for. Learn more about LF 2022 at https://landfire.gov/lf_230.php