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At least 289 records · Page 16Linked to original sources
USGS2009

Fire rehabilitation effectiveness: a chronosequence approach for the Great Basin

Federal land management agencies have invested heavily in seeding vegetation for emergency stabilization and rehabilitation (ES&R) of non-forested lands. ES&R projects are implemented to reduce post-fire dominance of non-native annual grasses, minimize probability of recurrent fire, quickly recover lost habitat for sensitive species, and ultimately result in plant communities with desirable characteristics including resistance to invasive species and resilience or ability to recover following disturbance. Land managers lack scientific evidence to verify whether seeding non-forested lands achieves their desired long-term ES&R objectives. The overall objective of our investigation is to determine if ES&R projects increase perennial plant cover, improve community composition, decrease invasive annual plant cover and result in a more desirable fuel structure relative to no treatment following fires while potentially providing habitat for Greater Sage-Grouse, a species of management concern. In addition, we provide the locations and baseline vegetation data for further studies relating to ES&R project impacts. We examined effects of seeding treatments (drill and broadcast) vs. no seeding on biotic and abiotic (bare ground and litter) variables for the dominant climate regimes and ecological types within the Great Basin. We attempted to determine seeding effectiveness to provide desired plant species cover while restricting non-native annual grass cover relative to post-treatment precipitation, post-treatment grazing level and time-since-seeding. Seedings were randomly sampled from all known post-fire seedings that occurred in the four-state area of Idaho, Nevada, Oregon and Utah. Sampling locations were stratified by major land resource area, precipitation, and loam-dominated soils to ensure an adequate spread of locations to provide inference of our findings to similar lands throughout the Great Basin. Nearly 100 sites were located that contained an ES&R project. Of these sites, 61 were seeded by using a drill, 27 were broadcast aerially, and 12 had a combination of both. We randomly sampled three burned and seeded, burned and unseeded, and unburned and unseeded locations in the vicinity of the fire, each within the same ecological site. We measured foliar cover of all plant functional groups (perennial or annual, shrub, grass, forb, native or introduced), biological soil crusts, and abiotic (bare soil and litter) variables using the line-point intercept protocol. Fuel loads and horizontal fuel continuity were measured. We applied linear mixed models to response variables (cover and density of plant groups) relative to the dependent variables (seeding treatments and precipitation/temperature relationships. Post-fire strengths with native perennial grasses or shrubs in mixes did not increase density or cover of these groups significantly relative to unseeded, burned areas. Seeded non-native perennial grasses and the shrub Bassia prostrata were effective in providing more cover in aerial and drill seedings. Seeded non-native perennial grass cover increased with increased annual precipitation regardless of seeding type. Seeding native shrubs, particularly Artemisia tridentata, did not significantly increase shrub cover in burned areas. Cover of undesirable non-native annual grasses was lower in drill seedings relative to unseeded areas but only at higher elevations. Seeding effectiveness after wildfire is unpredictable in drier, low elevation environments, and our findings indicate management objectives are more likely met when focusing efforts on higher elevation or higher precipitation locations where establishment of perennial grasses is more likely. On sites where potential for invasion and dominance of non-native annuals is high, such as lower and drier sites, intensive methods of restoration that include invasive plant control before seeding may be required. Where establishment of native perennial plants is the goal, managers might consider using native-only seed mixtures, because we found that the non-native perennials typically used in Great Basin restoration efforts are selected for their competitive nature and may reduce establishment of less competitive native species. Although we attempted to include information on livestock grazing history after seedings, we were unable to extract sufficient data from files to address this topic that may play an additional role in understanding native plant abundance post-fire seeding. Evaluation of drill and aerial seeding effects on fuel characteristics focused on two metrics that are standard inputs for fire behavior models, fuel load and fuel continuity. Fuel loads were evaluated separately for total fuel load biomass, and the individual components that sum to total biomass, namely herbaceous, shrub, shrub:herbaceous ratio, litter, 10-hour, and 100-hour fuel biomasses. Fuel continuity was evaluated using the following cover categories, total, annual grass, annual forb, perennial forb perennial grass, shrub, litter, vegetative interspace, and perennial interspace. Drill seeding did not affect fuel loads, except to reduce 10-hour fuels, probably due to mechanical destruction of dead and down fuels by the drill seeding equipment. Drill seeding did affect fuel continuity, specifically decreasing total plant cover by increasing perennial grass cover which suppressed annual grass and litter production resulting in a net decrease in continuity, but only at the elevations above approximately 1500m. Aerial seeding had no effect on any fuel load or fuel continuity category. For the Greater Sage-Grouse habitat study, we developed multi-scale empirical models of sage-grouse occupancy in 211 randomly located plots within a 40 million ha portion of the species’ range. We then used these models to predict sage-grouse habitat quality at 101 ES&R seeding projects. We compared conditions at restoration sites to published habitat guidelines. Sage-grouse occupancy was positively related to plot- and landscape-level dwarf sagebrush (Artemisia arbuscula, A. nova, A. tripartita) and big sagebrush steppe, and negatively associated with non-native grass and human development. The predicted probability of sage-grouse occupancy at treated plots was low on average (0.07–0.09) and was not significantly different from burned areas that had not been treated. Restoration was more often successful at higher elevation sites with low annual temperatures, high spring precipitation, and high plant diversity. No plots seeded after fire (n=313) met all overstory guidelines for breeding habitats, but approximately 50% met understory guidelines, particularly for perennial grasses. This trend was similar for summer habitat. Ninety-eight percent of treated plots did not meet winter habitat guidelines. Restoration actions in burned areas did not increase the probability of meeting most guideline criteria. The probability of meeting guidelines was influenced by a latitudinal gradient, local climate, and topography. Post-fire seeding treatments in Great Basin sagebrush shrublands generally have not created high quality habitat for sage-grouse. Understory conditions are more likely to be adequate than those of overstory, but in unfavorable climates, establishing forbs and reducing cheatgrass dominance is unlikely. Reestablishing sagebrush cover will require more than 20 years using the restoration methods of the past two decades. Given current fire frequencies and restoration capabilities, protection of landscapes containing a mix of dwarf sagebrush and big sagebrush steppe, minimal human development, and low non-native plant cover may provide the best opportunity for conservation of sage-grouse habitats. Our database of ES&R locations has used the Land Treatment Digital Library to archive data and location information regarding our study (see Pilliod and Welty 2013). This has contributed to two additional studies. One examined the potential spread of Bassia prostrata (aka Kochia prostrata; forage kochia) from ES&R project locations (Gray and Muir 2013). The second used remote sensing to determine the phenology of vegetation green-up on post-fire seeded sites (Sankey et al. 2013).

California;Idaho;Oregon;Utah↗
USGS2014

Forecasting distribution of numbers of large fires

Systems to estimate forest fire potential commonly utilize one or more indexes that relate to expected fire behavior; however they indicate neither the chance that a large fire will occur, nor the expected number of large fires. That is, they do not quantify the probabilistic nature of fire danger. In this work we use large fire occurrence information from the Monitoring Trends in Burn Severity project, and satellite and surface observations of fuel conditions in the form of the Fire Potential Index, to estimate two aspects of fire danger: 1) the probability that a 1 acre ignition will result in a 100+ acre fire, and 2) the probabilities of having at least 1, 2, 3, or 4 large fires within a Predictive Services Area in the forthcoming week. These statistical processes are the main thrust of the paper and are used to produce two daily national forecasts that are available from the U.S. Geological Survey, Earth Resources Observation and Science Center and via the Wildland Fire Assessment System. A validation study of our forecasts for the 2013 fire season demonstrated good agreement between observed and forecasted values.

Book↗
USGS2022

Effect of repeated fire on annual brome invasion at Badlands National Park

Prescribed fire is used to combat exotic plant species in mixed-grass prairie of Northern Great Plains parks. However, prescribed fires rarely occur at a frequency likely to maintain any gains against exotic species. The unusual circumstance of experimental plots being burned twice in 2 years provides a unique opportunity to investigate the effect of more frequent fire on invasive annual brome grasses. I established 40 plots on Sheep Mountain Table at Badlands National Park in 2015 to examine the relative effectiveness of prescribed fire alone or in combination with imazapic (an herbicide) application or with native seeding. Ten of the 40 plots were controls, with no experimental treatment; the remainder were burned with a prescribed fire in November 2016, and the herbicide and seeding treatments were applied soon thereafter to 10 plots each. In the 2018 growing season, annual brome abundance remained lower in the burned plots than in the controls, but monitoring by the National Park Service’s Northern Great Plains Fire Effects programs suggests that, by 5 years (or perhaps earlier) following a prescribed fire, annual brome abundance will return to its pre-fire level. Repeated fires may prevent this return if they sufficiently reduce the annual brome seedbank or produce conditions less conducive to annual brome growth (reduced litter layer or increased competition, for example). All plots in this experiment burned as part of a larger prescribed fire in fall 2018. This extension of the original study measures plant community composition (to species level) in the experimental plots (original control and burn only) after the 2018 prescribed fire; this report provides the results from the fourth growing season after that fire.

South Dakota↗
USGS2010

Establishing a nationwide baseline of historical burn-severity data to support monitoring of trends in wildfire effects and national fire policies

There is a need to provide agency leaders, elected officials, and the general public with summary information regarding the effects of large wildfires. Recently, the Wildland Fire Leadership Council (WFLC), which implements and coordinates National Fire Plan (NFP) and Federal Wildland Fire Management Policies adopted a strategy to monitor the effectiveness and effects of the National Fire Plan and the Healthy Forests Restoration Act. One component of this strategy is to assess the environmental impacts of large wildland fires and identify the trends of burn severity on all lands across the United States. To that end, WFLC has sponsored a 6-year project, Monitoring Trends in Burn Severity (MTBS), which requires the U.S. Department of Agriculture, Forest Service (USDA-FS) and the U.S. Geological Survey (USGS) to map and assess the burn severity for all large current and historical fires. Using Landsat data and the differenced Normalized Burn Ratio (dNBR) algorithm, the USGS/EROS Data Center and USDA-FS/ Remote Sensing Applications Center will map burn severity of all fires occurring from 1984 to 2010. Only fires that are greater than 500 ac in the East, and 1,000 ac in the West will be included. We anticipate mapping a total of more than 9,000 historical fires and fires that occur during the course of the study. The MTBS project will generate burn-severity data, maps, and reports, which will be available for use at local, State, and national levels to evaluate trends in burn severity and help develop and assess the effectiveness of land management decisions. Additionally, the information developed will provide a baseline from which to monitor the recovery and health of fire-affected landscapes over time. Spatial and tabular data quantifying burn severity will augment existing information used to estimate risk associated with a range of current and future resource threats. For example, fire severity data along with associated biophysical characteristics provide an analytical basis for assessing risk from invasive species as well as native insects and pathogens. All data and results will be distributed to the public via a Web interface.

General Technical Report↗
USGS2004

Impact of antecedent climate on fire regimes in coastal California

Severe fire weather is a major determinant of fire size in coastal California; however, it is unclear to what extent antecedent climate also controls fire activity. This study investigates the relationship between fire activity and climate in central coastal and southern California. Climate variables included the Palmer Drought Severity Index (PDSI), total monthly precipitation, mean monthly maximum temperature and the autumn and winter Southern Oscillation Indices (SOI). For both the central coast and the south coast regions there was no significant relationship between growing season PDSI, precipitation or temperature and number of fires. When examined by season, summer temperatures were positively correlated with number of fires in the central coast and autumn PDSI and precipitation were negatively correlated with fire occurrence in the south coast region. Area burned was not correlated with any current year climate variables in southern California although, in the central coast, drought during spring and autumn were correlated, but explained less than 10% of the variation in the area burned. Although there was a modest relationship between the Southern Oscillation Index (SOI) and local climate parameters, there was only a relatively weak relationship with fire activity. The importance of autumn foehn winds is illustrated by the observation that large fires occur most commonly during the autumn, regardless of PDSI. Antecedent climate, however, does appear to play some role in determining the length of the fire season on these landscape as PDSI is consistently related to the occurrence of large fires that occur before or after the autumn months.

International Journal of Wildland Fire↗
USGS2007

Impact of prescribed fire and other factors on cheatgrass persistence in a Sierra Nevada ponderosa pine forest

Following the reintroduction of fire Bromus tectorum has invaded the low elevation ponderosa pine forests in parts of Kings Canyon National Park, California. We used prescribed burns, other field manipulations, germination studies, and structural equation modelling, to investigate how fire and other factors affect the persistence of cheatgrass in these forests. Our studies show that altering burning season to coincide with seed maturation is not likely to control cheatgrass because sparse fuel loads generate low fire intensity. Increasing time between prescribed fires may inhibit cheatgrass by increasing surface fuels (both herbaceous and litter), which directly inhibit cheatgrass establishment, and by creating higher intensity fires capable of killing a much greater fraction of the seed bank. Using structural equation modelling, postfire cheatgrass dominance was shown to be most strongly controlled by the prefire cheatgrass seedbank; other factors include soil moisture, fire intensity, soil N, and duration of direct sunlight. Current fire management goals in western conifer forests are focused on restoring historical fire regimes; however, these frequent fire regimes may enhance alien plant invasion in some forest types. Where feasible, fire managers should consider the option of an appropriate compromise between reducing serious fire hazards and exacerbating alien plant invasions.

International Journal of Wildland Fire↗
USGS2011

Late Holocene geomorphic record of fire in ponderosa pine and mixed-conifer forests, Kendrick Mountain, northern Arizona, USA

Long-term fire history reconstructions enhance our understanding of fire behaviour and associated geomorphic hazards in forested ecosystems. We used 14 C ages on charcoal from fire-induced debris-flow deposits to date prehistoric fires on Kendrick Mountain, northern Arizona, USA. Fire-related debris-flow sedimentation dominates Holocene fan deposition in the study area. Radiocarbon ages indicate that stand-replacing fire has been an important phenomenon in late Holocene ponderosa pine ( Pinus ponderosa ) and ponderosa pine–mixed conifer forests on steep slopes. Fires have occurred on centennial scales during this period, although temporal hiatuses between recorded fires vary widely and appear to have decreased during the past 2000 years. Steep slopes and complex terrain may be responsible for localised crown fire behaviour through preheating by vertical fuel arrangement and accumulation of excessive fuels. Holocene wildfire-induced debris flow events occurred without a clear relationship to regional climatic shifts (decadal to millennial), suggesting that interannual moisture variability may determine fire year. Fire-debris flow sequences are recorded when (1) sufficient time has passed (centuries) to accumulate fuels; and (2) stored sediment is available to support debris flows. The frequency of reconstructed debris flows should be considered a minimum for severe events in the study area, as fuel production may outpace sediment storage.

Arizona↗
USGS2019

Evaluating the factors responsible for post-fire water quality response in forests of the western USA

Wildfires commonly increase nutrient, carbon, sediment, and metal inputs to streams yet the factors responsible for the type, magnitude and duration of water quality effects are poorly understood. Prior work by the current authors found increased nitrogen, phosphorus and cation exports were common the first five post-fire years from a synthesis of 159 wildfires across the western United States. In the current study, an analysis is undertaken to determine factors that best explain post-fire streamwater responses observed in those watersheds. Increased post-fire total nitrogen and phosphorus loading were proportional to the catchment extent of moderate and high burn severity. Post-fire dissolved metal concentrations increased in catchments with < 2% pre-fire soil organic matter. In contrast, in catchments with > 2% soil organic matter, post-fire dissolved metal concentrations decreased compared to pre-fire conditions. Where post-fire normalized difference vegetation index (NDVI), a remote sensing indicator of live green vegetation, was low, total metal concentrations increased by 25% on average and by > 100% in some cases. When pre-fire soil field capacity exceeded 17%, there was a 750% median increase in total metals export to streams. Overall, the current analysis identified burn severity, post-fire vegetation cover, and several soil properties as the key variables explaining extended post-fire water quality response across a broad range of conditions found in the western US.

Arizona, California, Colorado, Idaho, Montana, New↗
USGS2020

A large database supports the use of simple models of post-fire tree mortality for thick-barked conifers, with less support for other species

Background Predictive models of post-fire tree and stem mortality are vital for management planning and understanding fire effects. Post-fire tree and stem mortality have been traditionally modeled as a simple empirical function of tree defenses ( e.g., bark thickness) and fire injury ( e.g., crown scorch). We used the Fire and Tree Mortality database (FTM)—which includes observations of tree mortality in obligate seeders and stem mortality in basal resprouting species from across the USA—to evaluate the accuracy of post-fire mortality models used in the First Order Fire Effects Model (FOFEM) software system. The basic model in FOFEM, the Ryan and Amman (R-A) model, uses bark thickness and percentage of crown volume scorched to predict post-fire mortality and can be applied to any species for which bark thickness can be calculated (184 species-level coefficients are included in the program). FOFEM (v6.7) also includes 38 species-specific tree mortality models (26 for gymnosperms, 12 for angiosperms), with unique predictors and coefficients. We assessed accuracy of the R-A model for 44 tree species and accuracy of 24 species-specific models for 13 species, using data from 93 438 tree-level observations and 351 fires that occurred from 1981 to 2016. Results For each model, we calculated performance statistics and provided an assessment of the representativeness of the evaluation data. We identified probability thresholds for which the model performed best, and the best thresholds with either ≥80% sensitivity or specificity. Of the 68 models evaluated, 43 had Area Under the Receiver Operating Characteristic Curve (AUC) values ≥0.80, indicating excellent performance, and 14 had AUCs <0.7, indicating poor performance. The R-A model often over-predicted mortality for angiosperms; 5 of 11 angiosperms had AUCs <0.7. For conifers, R-A over-predicted mortality for thin-barked species and for small diameter trees. The species-specific models had significantly higher AUCs than the R-A models for 10 of the 22 models, and five additional species-specific models had more balanced errors than R-A models, even though their AUCs were not significantly different or were significantly lower. Conclusions Approximately 75% of models tested had acceptable, excellent, or outstanding predictive ability. The models that performed poorly were primarily models predicting stem mortality of angiosperms or tree mortality of thin-barked conifers. This suggests that different approaches—such as different model forms, better estimates of bark thickness, and additional predictors—may be warranted for these taxa. Future data collection and research should target the geographical and taxonomic data gaps and poorly performing models identified in this study. Our evaluation of post-fire tree mortality models is the most comprehensive effort to date and allows users to have a clear understanding of the expected accuracy in predicting tree death from fire for 44 species.

Fire Ecology↗
USGS2008

Responses in bird communities to wildland fires in southern California

There is a growing body of literature covering the responses of bird species to wildland fire events. Our study was unique among these because we investigated the effects of large-scale wildland fires on entire bird communities across multiple vegetation types. We conducted avian point counts during the breeding seasons for two years before and two years after the Cedar and Otay Fires in 2003 in southern California. Our balanced sampling effort took place at two sites, one low-elevation and one high-elevation, each containing replicate stations (burned and unburned) within five vegetation types: chaparral, coastal sage scrub, grassland, oak woodland, and riparian. Although fire caused some degree of change in the vegetation structure at all of our impacted survey points, we found that the post-fire shrub and tree cover was significantly lower in only two of the vegetation types within the low-elevation site, coastal sage scrub and chaparral. We found no significant changes in cover at the high-elevation site. Using univariate and multivariate analyses, we tested whether the fires were associated with a change in bird species diversity, community structure, and the relative abundance of individuals within a species. We found that species diversity changed in only one circumstance: it increased in coastal sage scrub at the low-elevation site. Multivariate analyses revealed significant differences in the post-fire bird community structure in the low-elevation chaparral, low-elevation coastal sage scrub, and the high-elevation grassland communities. Vegetation characteristics altered by fire, such as decreases in shrub and tree cover, influenced the changes we observed in the bird communities. The relative abundance of some species (lazuli bunting [ Passerina amoena ] and horned lark [ Eremophila alpestris ]) significantly increased after the fires, while other species declined significantly (Anna's hummingbird [ Calypte anna ], wrentit [ Chamaea fasciata ], and bushtit [ Psaltriparus minimus ]). We detected mixed results for the spotted towhee ( Pipilo maculatus ), which increased in burned chaparral and declined in burned coastal sage scrub within the low-elevation site. We suggest that the observed responses of birds to these fires may be attributed to: (1) the availability of nearby unburned refugia, (2) the continued suitability of post-fire vegetation at the study sites, and (3) the generally high mobility of this taxon.

California↗
USGS2017

Contributions of wildland fire to terrestrial ecosystem carbon dynamics in North America from 1990 to 2012

Burn area and the frequency of extreme fire events have been increasing during recent decades in North America, and this trend is expected to continue over the 21st century. While many aspects of the North American carbon budget have been intensively studied, the net contribution of fire disturbance to the overall net carbon flux at the continental scale remains uncertain. Based on national scale, spatially explicit and long-term fire data, along with the improved model parameterization in a process-based ecosystem model, we simulated the impact of fire disturbance on both direct carbon emissions and net terrestrial ecosystem carbon balance in North America. Fire-caused direct carbon emissions were 106.55 ± 15.98 Tg C/yr during 1990–2012; however, the net ecosystem carbon balance associated with fire was −26.09 ± 5.22 Tg C/yr, indicating that most of the emitted carbon was resequestered by the terrestrial ecosystem. Direct carbon emissions showed an increase in Alaska and Canada during 1990–2012 as compared to prior periods due to more extreme fire events, resulting in a large carbon source from these two regions. Among biomes, the largest carbon source was found to be from the boreal forest, primarily due to large reductions in soil organic matter during, and with slower recovery after, fire events. The interactions between fire and environmental factors reduced the fire-caused ecosystem carbon source. Fire disturbance only caused a weak carbon source as compared to the best estimate terrestrial carbon sink in North America owing to the long-term legacy effects of historical burn area coupled with fast ecosystem recovery during 1990–2012.

Global Biogeochemical Cycles↗
USGS2014

Life-history traits predict perennial species response to fire in a desert ecosystem

The Mojave Desert of North America has become fire-prone in recent decades due to invasive annual grasses that fuel wildfires following years of high rainfall. Perennial species are poorly adapted to fire in this system, and post-fire shifts in species composition have been substantial but variable across community types. To generalize across a range of conditions, we investigated whether simple life-history traits could predict how species responded to fire. Further, we classified species into plant functional types (PFTs) based on combinations of life-history traits and evaluated whether these groups exhibited a consistent fire-response. Six life-history traits varied significantly between burned and unburned areas in short (up to 4 years) or long-term (up to 52 years) post-fire datasets, including growth form, lifespan, seed size, seed dispersal, height, and leaf longevity. Forbs and grasses consistently increased in abundance after fire, while cacti were reduced and woody species exhibited a variable response. Woody species were classified into three PFTs based on combinations of life-history traits. Species in Group 1 increased in abundance after fire and were characterized by short lifespans, small, wind-dispersed seeds, low height, and deciduous leaves. Species in Group 2 were reduced by fire and distinguished from Group 1 by longer lifespans and evergreen leaves. Group 3 species, which also decreased after fire, were characterized by long lifespans, large non-wind dispersed seeds, and taller heights. Our results show that PFTs based on life-history traits can reliably predict the responses of most species to fire in the Mojave Desert. Dominant, long-lived species of this region possess a combination of traits limiting their ability to recover, presenting a clear example of how a novel disturbance regime may shift selective environmental pressures to favor alternative life-history strategies.

California;Nevada↗
USGS2024

Non-native plant invasion after fire in western USA varies by functional type and with climate

Invasions by non-native plant species after fire can negatively affect important ecosystem services and lead to invasion-fire cycles that further degrade ecosystems. The relationship between fire and plant invasion is complex, and the risk of invasion varies greatly between functional types and across geographic scales. Here, we examined patterns and predictors of non-native plant invasion following fire across the western United States. We specifically analyzed how the abundance of non-native plants after fire was related to fire characteristics and environmental conditions, such as climate, soil, and topography, in 26,729 vegetation plots from government networks and individual studies. Non-native plant cover was higher in plots measured after wildfires compared to prescribed burns or unburned plots. The post-fire cover of non-native species varied by plant functional type, and only the cover of short-lived (i.e., annual and biennial) forbs and short-lived C3 grasses was significantly higher in burned plots compared to unburned plots. Cool-season short-lived grasses composed most of the non-native post-fire vegetation, with cheatgrass ( Bromus tectorum ) being the most recorded species in the dataset. Climate variables were the most influential predictors of the cover of non-native short-lived grasses and forbs after fires, with invasion being more common in areas with drier summers and a higher proportion of yearly precipitation falling in October through March. Models using future projected climate for mid (2041–2070) and end (2071–2100) of century showed a potential for increasing post-fire invasion risk at higher elevations and latitudes. These findings highlight priorities for mitigation, monitoring, and restoration efforts to reduce post-fire plant invasion risk across the western United States.

Western United States↗
USGS2026

Leveraging time-series remote sensing to predict post-fire invasive annual grass response in western US rangelands

Context Understanding the relationship between Exotic Annual Grass (EAG) expansion, drought, and fire frequency across western US rangelands is complex, but critical for maintaining ecological integrity. Objectives We quantified the impacts of wildfire on EAGs, with emphasis on understanding the factors driving the spatial and temporal variability of those impacts, highlighting the role of drought. Methods We investigate two study periods using 1985–2024 and 2016–2024 EAG cover datasets to better understand EAG dynamics in relation to fire. We, 1) leverage mapped EAG cover responses to fire in the context of various biophysical variables to model expected change in EAG cover (ΔG) given a fire in a specific location, even if no fire has occurred in that location in the period of record; 2) evaluate the influence of drought and other biophysical variables on the ΔG; 3) combine our ΔG values with burn probability and ecological integrity data to evaluate the profile of EAG risk due to fire in sagebrush habitats. Results Our results show that fire impacts on EAG are often delayed, with limited effects in the first post-fire year followed by increasing cover over subsequent years. Importantly, areas with low pre-fire EAG cover exhibited the greatest potential for post-fire increases, whereas heavily invaded sites showed lower incremental responses, suggesting saturation or carrying-capacity constraints. Conclusions Understanding the connections among EAGs, drought, and wildfire is critical for maintaining the ecological integrity of western rangelands. Identifying the magnitude of fire impacts to EAG cover provides critical insight for land managers.

western United States↗
USGS2018

Fire changes the spatial distribution and sources of soil organic carbon in a grassland-shrubland transition zone

Aims In many mixed grass-shrub ecosystems, increased shrub biomass tends to promote overall carbon storage, but the distribution of carbon pools may be complicated by disturbances such as wildfires. We investigated the spatial distribution of surface soil organic carbon (SOC) and its relative contribution from grasses and shrubs after fires in a grass-shrub transition zone in the northern Chihuahuan Desert, USA. Methods We used a prescribed fire to create a burned treatment, then collected soil and plant samples. The biogeochemical approaches, geostatistical analyses, and carbon partitioning analyses were used to quantify the SOC and soil δ 13 C spatial patterns. Results Before the prescribed fire, up to 98% of the spatial dependence of SOC was autocorrelated at a distance of 1.91 m, corresponding to the approximate average shrub canopy diameter, but the spatial dependence dropped to 81% at a larger autocorrelation distance (3.74 m) two windy seasons after the fire. C 4 grasses and C 3 shrubs contributed approximately equal amounts of carbon to the surface SOC pool before the prescribed fire. However, C 4 grasses became the dominant source of SOC two windy seasons following the fire. For individual microsites, a substantially increased proportion of SOC was derived from C 4 grasses at the shrub microsites following the fire. Conclusions The higher proportion of C 4 grasses-derived SOC at the shrub microsites post-fire suggests that SOC may have preferred pathways to move among different microsites following fire disturbance. The distinct spatial distribution patterns of δ 13 C, and the increased contribution of SOC from grasses may be explained by the rapid recovery of grasses following the fire. Overall, our results provide insights into how fire might be used as a management tool to alter soil carbon pools in the context of shrub encroachment.

Plant and Soil↗
USGS2026

Quantifying post-fire live tree presence and spatial variation using Sentinel-2 time series

Accurate mapping of post-fire surviving trees is important for tracking forest recovery and prioritizing land management decisions. Satellite-based remote sensing is an effective method to assess post-fire forest conditions. Traditionally, differenced satellite-derived burn severity indices are computed by differencing one year pre- and post-fire spectral reflectance values. Differenced burn severity indices are useful for quantifying and mapping the magnitude of ecological change, but their application to detecting and mapping post-fire live trees may not be as appropriate, particularly for delayed tree mortality. Delayed tree mortality (“delayed mortality”) is a phenomenon where trees that initially survive fire then die over an extended period (between one and five years), and it can be challenging to measure and predict. In this study, we demonstrate the potential of mapping delayed mortality using readily available remotely sensed imagery alone. We used random forest models to detect post-fire live trees using 10-m resolution Sentinel-2 data at one-, three-, and five-years post-fire for four fires in the southern Sierra Nevada, California, USA. Using imagery from the National Agriculture Imagery Program (NAIP; 60-cm resolution), we manually classified live tree presence in 6000 Sentinel-2 pixels (500 pixels for each fire-year combination) to calibrate and validate models. Sentinel-2 based model accuracies ranged from 65 % to 86 % with F-scores ranging from 0.52 to 0.86, and their predictions of live pixel area were on average 44 % lower than inferred from more traditional indices such as relative differenced normalized burn ratio (RdNBR). This work represents a promising first step in using freely available post-fire spectral reflectance imagery to detect live trees over an extended period to support post-fire management.

California↗
USGS2021

Resilience to fire and resistance to annual grass invasion in sagebrush ecosystems of US National Parks

Western North American sagebrush shrublands and steppe face accelerating risks from fire-driven feedback loops that transition these ecosystems into self-reinforcing states dominated by invasive annual grasses. In response, sagebrush conservation decision-making is increasingly done through the lens of resilience to fire and annual grass invasion resistance. Operationalizing resilience and resistance concepts requires place-based understanding of resilience and resistance variation among landscapes over time. Place-based insights allow for landscape prioritization in targeted areas of significance such as protected-area sagebrush ecosystems that exhibit inherently low resilience and are therefore at high risk of loss. We used a multi-scale approach to evaluate sagebrush resiliency and strategic planning across 1) the US National Park system, 2) a regional suite of five parks, and 3) for two specific park case studies. First, we summarized broad patterns of relative resilience to fire and resistance to annual grass invasion across all parks with sagebrush ecosystems. We found that national parks represented ~11% of US protected-area sagebrush ecosystems and reflected a similar low-resilience bias that occurs across the biome, broadly. Climate change is likely to shift both low- and high-resilience park sagebrush ecosystems towards moderate resiliency, creating new opportunities and constraints for park conservation. Approximately seventy park units include at least some sagebrush shrublands or steppe, but we identified 40 parks with substantial amounts (>20% of park area) that can be included in an agency-wide conservation strategy. Second, we examined detailed patterns of resilience and resistance, fire history and fire risk, cheatgrass ( Bromus tectorum ) invasion, and sagebrush shrub ( Artemisia spp.) persistence in five national park units in Columbia Basin and Snake River Plain sagebrush steppe, contextualized by the broader summary. In these five parks, fire frequency and size increased in recent decades. Cheatgrass invasion and sagebrush persistence correlated strongly with resilience, burn frequency (0–3 fires since ~1940), and burn probability, but with important variation, in part mediated by local-scale topography. Third, we used these insights to assemble strategic sagebrush ecosystem fire protection mapping scenarios in two additional parks – Lava Beds National Monument and Great Basin National Park. Readily available and periodically updated geospatial data including soil surveys, fire histories, vegetation inventories, and long-term monitoring support resiliency-based adaptive management through tactical planning of pre-fire protection, post-fire restoration, and triage. Our assessment establishes the precarious importance of the US national park system to sagebrush ecosystem conservation and an operational strategy for place-based and science-supported conservation.

Arizona, California, Colorado, Idaho, Montana, New↗
USGS2018

Use of imaging spectroscopy and LIDAR to characterize fuels for fire behavior prediction

To protect ecosystem services and the increasing wildland urban interface in a world with fire, comprehensive maps of wildland fuels are needed to predict fire behavior and effects. Traditionally, fuels have been categorized into a classification scheme whereby a single metric represents vegetation composition and structure, which can then be parameterized based on variable vegetation amount and condition. Remote sensing has been used to extrapolate between known field plots across the landscape, however until recently, those technologies have had limited ability to characterize fuels (e.g., composition, horizontal and vertical connectivity). Using new technologies (imaging spectroscopy and LIDAR), the objectives of this study are to assess: 1) how fuel characteristics observed from remote sensing affect categorical fuel classifications, and 2) how fuel characteristics affect landscape-scale fire behavior (spread rate, areal extent and perimeter). The analysis was conducted over the 2014 California King Fire that burned ~40,000 ha over lands with varying use and history and has unique remote sensing observations from before and after the fire. This analysis compares fuel classifications from a synergistic field, model, and Landsat approach (LANDFIRE) and products derived from the Airborne Visible/Infrared Imaging Spectrometer and LIDAR (MapFUELS). Each classification focuses on different fuel characteristics, which were then used to compare differences in a fire simulation model (CAWFE) and actual fire behavior. The results show that fuel characteristic inputs such as horizontal connectivity or fuel type and vertical structure affect fire spread rate and final fire extent (respectively). These results present the opportunity for future integration of fuel characteristics observed at coarser resolutions (900 m 2 ) into predictions of fire behavior a similar spatial resolutions (as opposed to the current standard based on empirical relationships between fuel and fire behavior at ~12 m 2 resolution).

Remote Sensing Applications: Society and Environme↗