Geology topics

Research about western United States

Source-linked reports with geographic coverage including western United States.

At least 19 recordsLinked to original sources

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↗

USGS2026

Diverging wildfire regimes and doubling of burn area in western United States water supply watersheds

Recent increases in western United States wildfire activity are raising concerns for regional water supplies. Analyzing the wildfire histories (1940-2024) of 3,100 watersheds, we identify a significant regime shift in the late 20th century. Watersheds with higher runoff ratios, critical for regional water provisioning, have significantly increasing burn area trends. The burned areas double following the late 20th century changepoints. Analysis of 17,000 watersheds reveals a diverging fire regime: a transition from moderate burns (1-20% area) towards minimal (<1%) and extensive (> 20%) events. Vulnerability is greatest in forested and mountainous regions, specifically those providing water to 100,000 or more downstream consumers. An integrated watershed management approach, one that considers land management and downstream water operations, may help secure water supplies and mitigate the cascading hazards from wildfire.

western United States↗

USGS2026

Testing characteristic magnitude distributions in modern PSHA models

The characteristic magnitude distribution hypothesis predicts a higher rate of large earthquakes than a Gutenberg–Richter extrapolation of the small‐earthquake rate would imply. Characteristic magnitude distributions have been commonly applied to faults in probabilistic seismic hazard analysis (PSHA), and in modern models they can emerge from the way short‐term seismicity constraints are combined with long‐term geologic and geodetic constraints. We test the characteristic magnitude distribution hypothesis by comparing the fault‐based magnitude distributions from the 2023 update to the National Seismic Hazard Model (NSHM23) in the Western United States with observed seismicity over the past 93 yr. We find that observed magnitude distributions fall outside the model‐predicted confidence bounds in regions where NSHM23 produces characteristic magnitude distributions: in these regions, the model predicts higher rates of large earthquakes than are observed. An analysis of the earlier California model (Uniform California Earthquake Rupture Forecast, version 3) also reveals discrepancies between the modeled and observed magnitude distributions. In addition, we find that observed magnitude distributions near modeled faults are not significantly different from those in background regions. These results challenge the prevalence of characteristic magnitude distributions in fault‐based seismic hazard models and call for a reassessment of how disparate data sets are integrated in PSHA.

western United States↗

USGS2026

How to determine an earthquake rate budget? A comparison of geodetic, geologic, and seismologic moment rates

How much tectonic geodetic strain is accommodated as earthquakes? Can estimates of tectonic geodetic strain be used in probabilistic seismic hazard analyses? Understanding the balance of moment accumulation (i.e., geodetic moment) and accommodation (i.e., geologic and seismologic moment) is a necessary step toward leveraging corrected geodetic strain rates to quantify earthquake budgets. We investigate these questions using updated geodetic, geologic, and seismologic datasets compiled for the western United States (WUS) portion of the 2023 U.S. National Seismic Hazard Model (NSHM23‐WUS) to provide new views of moment rates across the WUS. We compare moment rates using a floating footprint approach across the extent of the NSHM23‐WUS fault sections database. We make these comparisons using “moment rate deviation (MRD),” which is defined as a surplus or deficit of geodetic moment rate relative to the sum of geologic and seismologic moment rates. We find that, in general, higher strain rate areas of the WUS (i.e., plate boundary) have smaller values of MRD, meaning that geodetic moment rates approximate the earthquake record preserved by geologic and seismologic moment rates well. In contrast, the lower strain rate, eastern portions of our analysis domain (i.e., intraplate) have very high values of MRD, with geodetic moment rates exceeding measured geologic and seismologic moment rates. We find that geodetic moment rates appear to be representative of the earthquake budget in relatively well‐characterized, interplate regions, and geodetic estimates of off‐fault deformation could be considered in seismic hazard analyses where MRD is minimized.

western United States↗

USGS2026

Characterizing changes in postfire debris-flow hazard as burned areas recover

Emergency assessments of postfire debris-flow hazards that are performed by the U.S. Geological Survey (USGS) provide estimates of debris-flow likelihood and rainfall triggering conditions that are used for evaluating and managing runoff-generated debris-flow hazards in recently burned areas throughout the western United States. Although the immediate postfire period, within roughly one year after fire, is typically the most susceptible to runoff-generated debris flows, the hazard evolves in time and space as the burned area recovers. The recovery trajectory a given burned area will take depends on local climate and weather and can be difficult to predict. Some burned areas recover quickly, whereas others experience debris flows for multiple years after fire. As a result, extending our ability to update debris-flow likelihood estimates and rainfall thresholds based on observed recovery of the burned area would be beneficial. We present a method for multi-year runoff-generated debris-flow hazard assessment that leverages the USGS “M1” debris-flow likelihood model and integrates updated, satellite-derived, normalized burn ratio data to estimate vegetation recovery. We predict recovery-aware rainfall thresholds and validate them against a multi-year debris-flow hazard prediction and could be adapted for use with other debris-flow models that incorporate burn severity data.

Arizona, California, Colorado, New Mexico, Washing↗

USGS2026

A review and synthesis of post-wildfire shifts in hydrologic processes and streamflow generation mechanisms

Critical water supply watersheds in the western United States (WUS) are impacted by wildfires, with potential negative effects on water quality and quantity. Scientific understanding is currently insufficient to deliver estimates of wildfire consequences for water quantity that are regionally accurate. Regional variability in the directionality and magnitude of post-wildfire shifts in streamflow generation fuels uncertainty in estimates of wildfire effects on water supply. In this work we provide a narrative review of wildfire effects on hydrologic processes and the resulting changes in streamflow generation mechanisms with a focus on the WUS, incorporating other global regions when pertinent. A conceptual model summary of wildfire effects on streamflow generation emphasizes: (1) precipitation seasonality, (2) synchrony of precipitation and potential evapotranspiration, (3) net shifts in interception, evaporation, and transpiration relative to total annual precipitation, (4) vegetation changes, including compensatory uptake and type conversion, (5) degree of overlap in rainfall rates and infiltration, (6) fire extent and severity, (7) burn scar positioning (e.g. in headwaters or proximal to watershed outlet), (8) scale-dependent groundwater leakage, (9) near-surface water storage reduction, and (10) soil to groundwater connectivity. Ongoing gaps and challenges include separating the influences of precipitation variability, water withdrawals, and post-fire land management; compound and overlapping disturbances; and lack of pre-fire data. Notable future opportunities include: harnessing ever-improving gridded and remotely sensed precipitation and fire-effects data; linking geophysical, isotopic tracer, and geochemical signatures to diagnose hydrologic changes; leveraging physically based and data-driven model advancements; and analyzing streamflow generation recovery trajectories across diverse watersheds.

western United States↗

USGS2026

Annual grass invasion is transforming the sagebrush biome’s songbird communities

Novel stressors like climate change and biological invasions alter ecological communities, resulting in changes to ecosystem services and biodiversity (that is, ecological transformation). Most ecological transformation research focuses on plants, but animals are likely affected by and plausibly mediate the extent, impact, and pace of transformations. In western North America, where invasive annual grasses are transforming sagebrush-steppe ecosystems, we quantified how transformation in vegetation drives songbird community change. We hypothesized that transformation of vegetation communities via invasion alters wildlife communities by favoring generalists over specialists, albeit with extinction debts that may temporarily obscure transformations’ consequences. Although local-scale songbird diversity increased with grass invasion, we found that this shift was accompanied by ongoing reorganization of songbird communities at larger scales (across the sagebrush biome), driven by heterogeneous impacts of invasion among species and guilds. Through our biome-wide analysis, we were also able to identify high-priority regions for conservation of sensitive songbird species. Our research provides evidence that wildlife communities are transforming alongside vegetation communities and offers insight into the approaches required to quantify nascent community turnover.

western United States↗

USGS2026

Spatial variation in effectiveness and costs of sagebrush restoration treatments across the western United States

Natural resource managers strive to improve restoration efficiency across the vast network of public lands of the United States, seeking the best return on investment through innovation, geographic prioritization, and adaptive management. This challenge is exemplified by ecosystems dominated by sagebrush ( Artemisia spp.), which occur across the western United States and have been degraded by increasing wildfire frequency driven by invasive plant spread, among other factors. However, both costs and effectiveness of sagebrush restoration can vary spatially due to management practices in addition to biotic and abiotic factors, and characterizing this variation could inform broad-scale planning. We leveraged published models of sagebrush recovery and treatment costs to predict and evaluate cost-effectiveness of aerial and drill seeding Artemisia spp. across 429 718 km 2 that overlapped 12 US states. Compared to natural recovery, effectiveness for both methods was generally low, yet effectiveness was often greater, and costs were always greater, for drill than aerial seeding, resulting in slightly higher cost-effectiveness on average for drill seeding. Cost-effectiveness for both treatments increased near major roads and in areas with more repeated burns. Cost-effectiveness also increased with predisturbance cover of sagebrush but decreased with herbaceous cover. However, we also identified areas where aerial seeding was more cost-effective than drill seeding, particularly with greater slope. Our results provide spatially explicit estimates and potential mechanisms of cost-effectiveness for two common seeding methods for sagebrush, which can help prioritize limited resources, guide land use, and improve restoration efficiency and effectiveness across public rangelands of the western United States.

western United States↗

USGS2026

Basal area loss from fire using field-calibrated remote sensing refines western US fire severity measurements

The spatial patterns of fire effects and tree mortality have profound consequences for forest resilience. Cost-effective, medium-resolution, and spatiotemporally extensive fire severity measurements are essential for informing post-fire restoration and improving our understanding of wildfires—from forest stands to continents and from days to decades. Remote sensing advancements have improved burn severity mapping, but methods vary in interpretability, scalability, generalizability, and alignment with field measurements. One meaningful metric of fire effects on forests is proportion basal area loss, but existing methods are limited by a lack of region-specific field reference data and a scalable mapping framework. To address these issues, we compiled 3280 field reference plots from 123 fires in forests across the Western US to calculate the proportion of fire-induced basal area loss. We then used spatially cross-validated machine learning models with concurrent hyperparameter tuning to select a skillful, parsimonious model from a large candidate set of remotely-sensed, climatic, and topographic predictors. Spectral-only measures of severity over- or underestimated basal area loss in dry versus wet years and across aspects, demonstrating the value of incorporating climatic and topographic context. We also tested model performance on a separate holdout dataset in the Southwest US as a demonstration of reproducibility and transparency. We provide a Google Earth Engine tool for estimating proportional basal area loss for any fire perimeter in the Western US, enabling rapid map creation for land management and ecological modeling. All code, model parameters, and training data are released to support reproducibility, community adoption, regional refinement, and adaptation to new regions.

western United States↗

USGS2025

Seed coating treatments alter emergence windows of native Intermountain West U.S. grasses under different regimes of water availability

Introduction Seed-based restoration is widely implemented to recover degraded lands but often fails. Seed enhancement technologies may improve outcomes by shifting emergence to target favorable climate windows and serving as a bet-hedging strategy against increasingly variable precipitation patterns. Objectives To test the potential benefit of these technologies, we applied seed coatings designed to accelerate or delay emergence to four native Intermountain West perennial grasses that are commonly used for restoration. Methods We subjected seeds to six different watering regimes in the greenhouse that represented variation in precipitation timing and amount and compared the emergence, growth, and biomass of coated and uncoated seedlings. Results Seed coating designed to accelerate germination strongly increased emergence in species with high dormancy requirements, while seed coating designed to delay germination decreased emergence in species with low dormancy by about half and postponed emergence by up to 15 days. These coatings altered emergence timing regardless of watering regime, suggesting that seed coating could expand emergence windows under variable precipitation regimes. Seedling growth and total biomass were less dependent on seed coating and were more driven by the average amount of soil moisture provisioned to the developing plant. While seed coating designed to accelerate germination increased the emergence of two grass species, growth decreased during late periods of water availability, suggesting a trade-off in seedling performance. Conclusions Our results show promise for seed coatings to shift windows of emergence, but further field testing could improve our understanding of their effects in restoration settings.

western United States↗

USGS2025

Sentinel-2 based estimates of rangeland fractional cover and canopy gap class for the western United States

Rangelands are extensive ecosystems, providing important ecosystem services while undergoing continuous change. As a result, improved monitoring technologies can help better characterize vegetation change. Satellite remote sensing has proven effective in this regard, tracking vegetation dynamics at broad and fine scales. We leveraged the spatial, spectral, and temporal resolution of Sentinel-2 satellites to estimate fractional cover and canopy gap across rangelands of the western United States. We produced annual, 10 m spatial resolution estimates of fractional cover and canopy gap size class for years 2018 to 2024. Fractional cover estimates include that of common plant functional types (annual forb and grass, bareground, littler, perennial forb and grass, shrub, tree) and select genera (including invasive annual grass species, pinyon-juniper species, and sagebrush species); canopy gap size classes include gap sizes 25 to 50, 51 to 100, 101 to 200, and greater than 200 cm. We make these data available as Cloud Optimized GeoTIFFs, organized as 75 × 75 km tiles covering the 17 western states of the United States.

western United States↗

USGS2025

Sentinel-1 SAR estimates of snowmelt onset coincide with SNOTEL soil moisture pulses across the western U.S.

While there have been recent advancements in synthetic aperture radar (SAR)-based snow water equivalent (SWE) retrievals, obtaining accurate estimates of SWE requires knowledge of the amount of liquid water content (LWC) in the snowpack given its strong impact on radar velocity. Recent studies have utilised Sentinel-1 SAR to identify snowmelt runoff onset in complex, high-elevation terrain based on a seasonal minimum backscatter time-series; however, detailed investigations into the snowpack state before and after snowmelt runoff onset are lacking. In this study, we integrated repeat field measurements at five sites, SNOw TELemetry (SNOTEL) station data ( n = 260) from across the Western United States, and paired Sentinel-1 SAR estimates of snowmelt runoff onset to (1) assess the snowpack state prior to and after Sentinel-1 SAR-derived runoff onset estimates, and (2) evaluate Sentinel-1 SAR estimates of runoff onset with SNOTEL-derived estimates of melt output via soil moisture ‘pulses’. We found that on the date of minimum backscatter, the snowpack was isothermal at three of the five field sites, and snow pit-measured LWC was increasing at all field sites relative to previous survey dates. SNOTEL soil moisture pulses preceded Sentinel-1 SAR estimates of snowmelt runoff onset by a median of 3 days (standard deviation = ±25.3 days) and post-dated peak SWE by a median of 3 days (standard deviation = ±18.2 days). Snow density and the number of positive degree days on soil moisture pulse date increased with latitude and longitude and decreased with elevation. Although satellite-based estimates of snowmelt runoff onset provide a promising approach for improving spaceborne retrievals of SWE, local climatological conditions exert significant influence on meltwater runoff onset signal clarity for both in situ and satellite-based estimates.

western United States↗

USGS2025

Near real-time indicators of burn severity in the western U.S. from active fire tracking

Background Timely information on wildfire burn severity is critical to assess and mitigate potential post-fire impacts on soils, vegetation, and hillslope stability. Tracking individual fire spread and intensity using satellite active fire data provides a pathway to near real-time (NRT) information. Here, we generated a large database ( n = 2177) of wildfire events in the western United States (U.S.) between 2012 and 2021 using active fire detections from the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership (SNPP) satellite and the Fire Events Data Suite (FEDS) algorithm to track large fire growth every 12 h. We integrated fire tracking data with final fire perimeters and burn severity data from the Monitoring Trends in Burn Severity (MTBS) program to evaluate the relationship between burn severity and fire behavior metrics derived from the fire tracking approach, including the rate of fire spread and average fire radiative power (FRP) of fire detections for each 12-h growth increment. Results When stratified by vegetation type, FRP and rate of spread metrics were positively correlated with classified burn severity for each 12-h growth increment, highlighting the potential to rapidly identify areas of high and low severity burning. In forests, integrated measures of FRP over the fire lifetime captured persistent flaming and smoldering that compensated for initial differences between AM (01:30) and PM (13:30) fire detections. Predictive modeling of these relationships based on multiple fire behavior indicators and vegetation type from the LANDFIRE program yielded an accuracy of 78% for the separation of unburned/low and moderate/high burn severity classes. Conclusions These results demonstrate the ability to capture within-fire differences in burn severity using NRT indicators from fire tracking to assist with emergency management and disaster preparedness for post-fire hazards, such as landslides, debris flows, or changes in stream flow and water quality. As VIIRS data are available within minutes of each satellite overpass in the U.S., rapid estimates of burn severity based on fire tracking can be made days or weeks before a large wildfire is fully contained.

western United States↗

USGS2025

The influence of human presence and footprint on animal space use in US national parks

Given the importance of protected areas for biodiversity, the growth of visitation to many areas has raised concerns about the effects of humans on wildlife. In 2020, the COVID-19 pandemic led to temporary closure of national parks in the United States, offering a pseudonatural experiment to tease apart the effects of permanent infrastructure and transient human presence on animals. We compiled GPS tracking data from 229 individuals of 10 mammal species in 14 parks and used third-order hierarchical resource selection functions to evaluate the influence of the human footprint on animal space use in 2019 and 2020. Averaged across all parks and species, animals avoided the human footprint, whether the park was open or closed. However, although animals in remote areas showed consistent avoidance, on average those in more developed areas switched from avoidance to selection when protected areas were closed. Findings varied across species: some responded consistently negatively to the footprint (wolves, mountain goats), some positively (mule deer, red fox) and others had a strong exposure-mediated response (elk, mountain lion). Furthermore, some species responded more strongly to the park closure (black bear, moose). This study advances our understanding of complex interactions between recreation and wildlife in protected areas.

western United States↗

USGS2025

Suturing fragmented landscapes: Mosaic hybrid zones in plants may facilitate ecosystem resiliency

Many widespread plant taxa of western North America have diversified into phenotypically and genetically divergent lineages due to complex biogeographic histories across heterogeneous landscapes. Mosaic hybrid zones can form when geographically co-occurring, yet environmentally distinct, lineages cross-pollinate and form hybrids that occupy unique environmental niches absent of a geographic cline. This expands the total environmental space across which parental and hybrid individuals grow, resulting in larger, less fragmented geographic distributions. Here, we highlight hybridization mosaics across three study systems containing taxa critical to widespread plant communities in western North America: Ericameria nauseosa , Artemisia tridentata , and Sphaeralcea fendleri . The systems contain diverged taxa that co-occur across the landscape and hybridize readily. Hybridization among taxa has facilitated niche expansion into intermediate environments consistent with unique combinations of adaptive genetic variation, creating more continuity within each study system—study systems occupy ~820 to 270,000 km 2 more geographic area by virtue of hybridization. Furthermore, hybrids are predicted to play important roles in future climates, as they may occupy 8 to 475% larger distributions compared to present. Convergent patterns signal mosaic hybridization as an underappreciated mechanism with broad ecological and evolutionary ramifications. Leveraging mosaic hybridization may assist the creation of restoration management plans that aim to mitigate the deleterious effects of habitat fragmentation on ecosystems in the context of climate change.

western United States↗

USGS2025

Optimizing sampling across transect-based methods improves the power of agroecological monitoring data

Transect-based monitoring has long been a valuable tool in ecosystem monitoring to measure multiple ecosystem attributes. The line-point intercept (LPI), vegetation height, and canopy gap intercept methods comprise a set of core methods, which provide indicators of ecosystem condition. However, users often struggle to design a sampling strategy that optimizes the ability to detect ecological change using transect-based methods. We assessed the sensitivity of each of these core methods to transect length, number, and sampling interval in 1-ha plots to determine: (1) minimum sampling required to describe ecosystem characteristics and detect change; and (2) optimal transect length and number to make recommendations for future analyses and monitoring efforts. We used data from 13 National Wind Erosion Research Network locations, including five LTAR sites, spanning the western United States, which included 151 plot sampling events over time across five biomes. We found that longer and increased replicates of transects were more important for reducing sampling error than increased sample intensity along fewer transects per plot. For all methods and indicators across biomes plots, three 100-m transects reduced sampling error such that indicator estimates fell within a 95% confidence interval of ±5% for canopy gap intercept and LPI-total foliar cover, ±5 cm for height, and ±2 species for LPI-species counts. For the same criteria at 80% confidence intervals, two 100-m transects are needed. Site-scale inference was strongly affected by sample design, consequently our understanding of ecological dynamics may be influenced by sampling decisions.

western United States↗

USGS2025

Are wildfire risk mitigators more prepared to evacuate? Insights from communities in the western United States

As the realized experiences of wildfires threatening communities increase, the importance of proactive evacuation preparation and wildfire risk mitigation on private property to reduce the loss of lives and property is shaping wildfire policy and programs. To date, research has focused on pre-wildfire evacuation preparation and risk mitigation independently. This paper examines the substitutability or complementarity of these proactive risk-reducing actions. If mitigation and evacuation preparedness are substitutes, wildfire education programs may take a life-over-property approach. However, if proactive risk-reducing efforts are complements, wildfire education programs can confidently encourage residents to prepare for evacuation while also mitigating wildfire risk on their properties. This complementarity may also demonstrate that poorly mitigated households are less prepared to evacuate, compounding their risks. Using household survey data from 25 wildland-urban interface (WUI) communities across five Western states, we explore how wildfire risk mitigation actions affect evacuation preparedness. We find that improving household wildfire mitigation is associated with an improvement in wildfire evacuation preparedness. This complementary relationship between wildfire mitigation and evacuation preparedness actions highlights the potential benefits of a wildfire education approach that encourages residents to simultaneously prepare for evacuation and reduce wildfire risk on their properties before they are threatened by a wildfire.

western United States↗

USGS2025

Spatial scale dependence of error in fractional component cover maps

Geospatial products such as fractional vegetation cover maps often report overall, pixel-wise accuracy, but decision-making with these products often occurs at coarser scales. As such, data users often desire guidance on the appropriate spatial scale to apply these data. We worked toward establishing this guidance by assessing RCMAP (Rangeland Condition Monitoring Assessment and Projection) accuracy relative to a series of high-resolution predictions of component cover. We scale the 2-m and RCMAP predictions to various focal window sizes scales ranging from 30 to 1 500 m using focal averaging. We also evaluated variation in scaling effects on error at ecoregion and pasture (mean area of 1 050 ha) scales. Our results demonstrate increased accuracy at broader windows, across all components, and most increases in accuracy level off at ∼200–600 m scales. At the scale with highest accuracy, cross-component average correlation ( r ) increased by 6.5%, and root mean square error (RMSE) was reduced 46.4% relative to 30-m scale data. Scaling-related improvements to accuracy were greatest in components such as shrub and tree with more spatially heterogeneous cover and in ecoregions with more spatially heterogenous cover. When components were aggregated at the pasture scale, r increased 10% and RMSE decreased 34.3% on average relative to the 30-m scale. Our results provide empirical data on the scale dependence of error, which fractional cover data users may consider alongside their needs when using these data. Although the general principle remains that remotely sensed products are intended to address landscape-scale questions, our analysis indicates that applying data at finer than landscape spatial scales and grouping even a handful of pixels resulted in lowered error compared to pixel-level comparisons. Our results quantify the trade-offs between data granularity and error related to scale for fractional vegetation cover.

western United States↗