This dataset provides the plot-level data of the relative cover of ten different plant associations derived from a structural topic model and resistance and resilience metrics for predicting their abundances. Data comes from four different fires across the Great Basin: the 2007 Murphy Fire, 2012 Rush Fire, 2012 Holloway Fire, and the 2015 Soda Fire. Additional data utilized in the cross referenced paper from the Orchard Combat Training Center was redacted due to military rules but can be requested through the Idaho National Guard Environmental Management Office. Bureau of Land Management data (Murphy, Holloway, and Rush) species cover data was collected using line-point intercept methods on plots with between one and three transects of 25m or 50m in length. An additional small set of data (<1%) was collected by the Idaho Fish and Game using Daubenmire cover grids. Soda fire species cover data was collected with overhead photos and a grid-point intercept technique using Samplepoint software (Booth et al. 2006). Structural topic modelling was run to get the relative cover of ten different plant associations at each plot (Applestein et al. 2024).

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These data were compiled to provide a quantitative, spatially explicit estimate of ecological resilience and resistance (R&R) under ambient and projected future climate conditions. Objective of our study was to understand where and why climate change will alter the distribution of ecological resilience and resistance in the sagebrush biome throughout the 21st century. To accomplish this, we pursued four specific objectives: we estimated the new R&R indicators under future climate conditions and quantified changes from historical conditions; we developed a continuous R&R index that integrates probability information from the underlying predictive R&R models; we assessed the robustness of projected changes in R&R to uncertainty in future climate conditions. These data represent spatially-explicit estimates of ecological resilience and resistance (R&R; categorical indicators, probabilities, continuous indices) under ambient and downscaled projected historical and future climate conditions (historical, RCP 4.5, and RCP 8.5 CMIP5 scenarios). These data were created in rangelands and open woodlands across the sagebrush biome in 2023. These data were created by a collaboration between Northern Arizona University and the U.S. Geological Survey, Southwest Biological Science Center based on modeling which utilized predictive R&R models utilizing ecological and climate metrics which were based on soil properties (NRCS), ambient climate data (gridMET), and downscaled climate projections (MACAv2-METDATA). These data can be used to assess geographic patterns in resilience and resistance under ambient and projected future climate conditions.

These data were compiled to provide a quantitative, spatially explicit estimate of ecological resilience and resistance (R&R) under ambient and projected future climate conditions. Objective of our study was to understand where and why climate change will alter the distribution of ecological resilience and resistance in the sagebrush biome throughout the 21st century. To accomplish this, we pursued four specific objectives: we estimated the new R&R indicators under future climate conditions and quantified changes from historical conditions; we developed a continuous R&R index that integrates probability information from the underlying predictive R&R models; we assessed the robustness of projected changes in R&R to uncertainty in future climate conditions. These data represent spatially-explicit estimates of ecological resilience and resistance (R&R; categorical indicators, probabilities, continuous indices) under ambient and downscaled projected historical and future climate conditions (historical, RCP 4.5, and RCP 8.5 CMIP5 scenarios). These data were created in rangelands and open woodlands across the sagebrush biome in 2023. These data were created by a collaboration between Northern Arizona University and the U.S. Geological Survey, Southwest Biological Science Center based on modeling which utilized predictive R&R models utilizing ecological and climate metrics which were based on soil properties (NRCS), ambient climate data (gridMET), and downscaled climate projections (MACAv2-METDATA). These data can be used to assess geographic patterns in resilience and resistance under ambient and projected future climate conditions.

Land management treatments in sagebrush steppe are an important opportunity to break the annual-grass fire cycle, provided they offer long-lasting resistance to annual-grass invasion and do not burn. However, for BLM areas seeded as part of the Emergency Stabilization and Rehabilitation (ESR) program, one of the largest programs for land management treatments, about 1/4 have at least partially reburned over the last 30 years, according to a recent study. Reburning of treatments can cause a loss of investment if fire-intolerant perennials do not recover and/or significant invasions occur, in which case the risks of wildfire are compounded by increased potential for ecological degradation. Alternatively, recovery of fire-tolerant perennials occurs naturally or due to treatments would represent a significant return on prior investment and the occurrence of fire would thus pose reduced ecological hazard risks. Fire risks are highly variable across sagebrush landscapes, owing to variability in fuel loading, ignition potential, and fire transmission. Information is needed on predicting future risks related to reburning - including post-fire hazards related to ecological degradation - for past land management investments to a) identify protection measures that could be applied now, and b) help design and positioning of future treatment investments to minimize their risk of reburning in ways that cause ecological degradation. This dataset was compiled in order to predict reburn risk to areas that had previously burned and were retreated.

Conservation planning efforts for sagebrush ecosystems of western North America increasingly focus on enhancing operational resilience though decision-support tools that link spatially explicit variation in soil and plant processes to outcomes of biotic and abiotic disturbances spanning large spatial extents. However, failure to consider higher trophic-level fauna (e.g. wildlife) in these tools can hinder efforts to operationalize resilience owing to spatiotemporal lags between slower reorganization of plant and soil processes following disturbance, and faster behavioral and demographic responses of fauna to disturbance. These spatial products provide additional examples for managers of sagebrush ecosystems and greater sage-grouse (Centrocercus urophasianus) populations in the Great Basin to aid with decisions regarding: 1) wildfire prevention, suppression, and management; and 2) removal of encroaching conifers. These products integrate models of ecological resilience mapped to variation in soil moisture and temperature regimes, wildlife risk and recovery processes, and potential ecological traps with measures of sage-grouse habitat selection and abundance. Please refer to Ricca and Coates (2019) and examples within for further details on methodology.

Conservation planning efforts for sagebrush ecosystems of western North America increasingly focus on enhancing operational resilience though decision-support tools that link spatially explicit variation in soil and plant processes to outcomes of biotic and abiotic disturbances spanning large spatial extents. However, failure to consider higher trophic-level fauna (e.g. wildlife) in these tools can hinder efforts to operationalize resilience owing to spatiotemporal lags between slower reorganization of plant and soil processes following disturbance, and faster behavioral and demographic responses of fauna to disturbance. These spatial products provide additional examples for managers of sagebrush ecosystems and greater sage-grouse (Centrocercus urophasianus) populations in the Great Basin to aid with decisions regarding: 1) wildfire prevention, suppression, and management; and 2) removal of encroaching conifers. These products integrate models of ecological resilience mapped to variation in soil moisture and temperature regimes, wildlife risk and recovery processes, and potential ecological traps with measures of sage-grouse habitat selection and abundance. Please refer to Ricca and Coates (2019) and examples within for further details on methodology.

Arid ecosystems are often vulnerable to transformation to invasive-dominated states following fire, but data on persistence of these states are sparse. The grass/fire cycle is a feedback process between invasive annual grasses and fire frequency that often leads to the formation of alternative vegetation states dominated by the invasive grasses. However, other components of fire regimes, such as burn severity, also have the potential to produce long-term vegetation transformations. Our goal was to evaluate the influence of both fire frequency and burn severity on the transformation of woody-dominated communities to communities dominated by invasive grasses in major elevation zones of the Mojave Desert of western North America. We used a chronosequence design to collect data on herbaceous and woody cover at 229 unburned reference plots and 578 plots that burned between 1972 and 2010. We stratified the plots by elevation zone (low, mid, high), fire frequency (1 to 3 times), and years postfire (YPF; 1 - 5, 6 - 10, 11 - 20, and 21 - 40 YPF). Burn severity for each plot was estimated by the difference normalized burn ratio (dNBR). A Geographic Positioning System (GPS) was used to match the plots as closely as possible with the corner of a dNBR pixel. Each plot was 0.1 ha (32 m x 32 m) and contained three randomly positioned 25-m transects. Point intercept sampling was conducted at 0.5 m intervals along each transect (N = 50 points per transect, 150 points per plot). All plants intercepted by a wooden rod (1mm diameter) were recorded to species at each point. Species cover in each plot was estimated as the sum of point intercepts for each species divided by 150.

Arid ecosystems are often vulnerable to transformation to invasive-dominated states following fire, but data on persistence of these states are sparse. The grass/fire cycle is a feedback process between invasive annual grasses and fire frequency that often leads to the formation of alternative vegetation states dominated by the invasive grasses. However, other components of fire regimes, such as burn severity, also have the potential to produce long-term vegetation transformations. Our goal was to evaluate the influence of both fire frequency and burn severity on the transformation of woody-dominated communities to communities dominated by invasive grasses in major elevation zones of the Mojave Desert of western North America. We used a chronosequence design to collect data on herbaceous and woody cover at 229 unburned reference plots and 578 plots that burned between 1972 and 2010. We stratified the plots by elevation zone (low, mid, high), fire frequency (1 to 3 times), and years postfire (YPF; 1 - 5, 6 - 10, 11 - 20, and 21 - 40 YPF). Burn severity for each plot was estimated by the difference normalized burn ratio (dNBR). A Geographic Positioning System (GPS) was used to match the plots as closely as possible with the corner of a dNBR pixel. Each plot was 0.1 ha (32 m x 32 m) and contained three randomly positioned 25-m transects. Point intercept sampling was conducted at 0.5 m intervals along each transect (N = 50 points per transect, 150 points per plot). All plants intercepted by a wooden rod (1mm diameter) were recorded to species at each point. Species cover in each plot was estimated as the sum of point intercepts for each species divided by 150.