Geology topics

Daniel Rodolphe Schlaepfer

Publications and source records attributed to Daniel Rodolphe Schlaepfer.

At least 19 recordsLinked to original sources

USGS2025

Aridity reduces lag times between aquatic and terrestrial dry-down among watersheds and across years in the northwest US

Landscapes encompass both aquatic and terrestrial ecosystems that experience the same climate but may respond to climate in divergent ways. For example, the time lag between seasonal dry-down of terrestrial soil moisture and decline in streamflow has important implications for species and ecosystem processes across the aquatic–terrestrial interface. How these lags between aquatic and terrestrial hydrology vary with climate and spatial location within watersheds remains largely unexplored. Here, we examine seasonal patterns of aquatic–terrestrial dry-down across seven watersheds in the northwestern USA, spanning a wide range of aridity. We compared daily streamflow data from USGS gages at watershed outlets with simulated daily soil moisture (1979–2020) from multiple locations within each watershed. In all watersheds, annual dry cycles progressed sequentially through the following features: evapotranspiration, precipitation, shallow soil moisture, deep soil moisture, and finally streamflow. Seasonal streamflow minima lagged behind soil moisture minima for shorter durations in more arid watersheds and drier years. Within watersheds, lag times varied spatially due to interactions between elevation and aridity, with short lags in low-elevation soils near streams in arid watersheds and longer lags in less arid watersheds. Collectively, these results indicate shorter lags between seasonal aquatic and terrestrial dry periods in drier watersheds and years, and show that these tighter linkages are spatially aggregated in drier watersheds. The co-occurrence of seasonally dry conditions in both aquatic and terrestrial systems under increasing aridification is likely to intensify stressors on ecosystems and services. Recognizing these patterns may be critical for predicting ecosystem vulnerabilities and informing adaptation strategies to mitigate the impacts of seasonally dry conditions.

Montana, Oregon, Wyoming↗

USGS2025

Supporting dryland restoration success with applied ecological forecasting of seeding outcomes

Introduction Ecological restoration is increasingly used to sustain biodiversity and ecosystem services. In drylands of the western United States (US), post-disturbance restoration often involves seeding treatments to promote the recovery of native plant communities. Spatial and temporal variability in environmental conditions influences plant establishment and contributes to low restoration success in certain locations and years. Objectives Here, we discuss how forecasts for plant establishment can be developed and delivered to help land managers anticipate the impacts of near-term (months to years) environmental conditions on restoration. Methods We developed an ecological forecast system that predicts the outcome of restoration seeding by integrating weather forecasts, an ecosystem water balance model, and plant establishment models. Results In this article, we focus on a conceptual approach to developing, delivering, and applying ecological forecasts for restoration. We illustrate the potential of this approach by adapting existing ecological models to build an initial version of a decision support tool that delivers a species-specific ecological forecast for big sagebrush ( Artemisia tridentata ) establishment. Integrating ecological forecasts into plans for restoration seeding presents opportunities to anticipate and account for environmental variability. Conclusions Finally, we discuss how connecting research, forecast delivery, and management can maximize the impact of ecological forecasts on restoration success.

Idaho, Nevada↗

USGS2025

Climate change impacts on plant communities in the sagebrush region—A science synthesis to inform Bureau of Land Management resource management

This report synthesizes current (2024) science-based knowledge related to the impacts of climate change on big sagebrush vegetation in Western North America. This effort was conducted through the U.S. Geological Survey working with the Bureau of Land Management as part of multiple science syntheses to aid management agencies developing environmental impacts assessments in response to human-related or caused events. This report reviews the potential impacts climate change may have on sagebrush vegetation and related management decisions. The body of the synthesis introduces the diverse impacts of climate change across the region by first focusing directly on what climate change may entail in terms of altered temperature and precipitation patterns. The report then discusses how these changes could likely affect individual plant species based on experimental results and scale the impacts to species distributions and community composition. The synthesis section ends by surveying efforts to model potential future changes in habitat. The report goes on to link the synthesis conclusions to individual land uses or land management decisions, such as forage resources, restoration or fuel treatment. Finally, the report provides a section that discusses the pros and cons of available datasets that model the potential future of vegetation in the sagebrush region.

Arizona, California, Colorado, Idaho, Montana, Nev↗

USGS2025

Flexible phenology of a C4 grass linked to resiliency to seasonal and multiyear drought events in the American southwest

Rising temperatures are predicted to further limit dryland water availability as droughts become more intense and frequent and seasonal precipitation patterns shift. Vegetation drought stress may increase mortality and cause declines and delays in phenological events, thereby impacting species' capacity to persist and recover from extreme drought conditions. We compare phenological responses of two common dryland perennial grass species, Achnatherum hymenoides (C 3 ) and Pleuraphis jamesii (C 4 ), to 4 years of experimentally imposed precipitation drought treatments (cool season, warm season, ambient), followed by 2 years of recovery on the Colorado Plateau, United States of America. Tagged individual grasses from both species were monitored biweekly and assessed for phenological metrics and mortality. The C 3 grass exhibited less phenological flexibility to both seasonal and interannual drought conditions and experienced high rates of mortality, thus reducing resiliency. Conversely, the C 4 grass showed more phenological plasticity during imposed drought treatments, with treatment effects diminishing in the two-year recovery period during a severe ambient drought. Synthesis: Results suggest that plant photosynthetic strategies may impact plant resistance and resiliency to drought. Here, C 3 grass populations may decline, potentially shifting cool dryland ecosystems into a system comprised predominantly of warm-season adapted species.

Utah↗

USGS2025

Management and natural regeneration in multiple ponderosa pine forests of the southwestern United States

Management treatments in ponderosa pine forests of the southwestern United States (SWUS) are largely done for wildfire mitigation and restoration to lower tree densities. However, lack of natural ponderosa pine regeneration in undisturbed forests (i.e., no occurrence of stand-replacing events) may require management treatments to promote regeneration. We conducted a field and modeling study in 77 ponderosa pine forests across 7 SWUS locations, with the goal of evaluating management impacts on recent natural regeneration ( ∼ "> ∼ 20 y). We categorized management into 3 broad categories: unmanaged, thinned from above and/or below (thinning), and thinned + "> + understory burned (burning). Although climate suitability declined from 1981-2020, management treatments – especially burning – promoted natural regeneration. High density regeneration, an undesirable outcome, occurred in 21 % "> % of managed sites. In addition to effects on near-surface temperature and soil moisture, management conducive to natural regeneration was associated with the density of competing tree species, understory litter and debris cover, and adult tree cone production. Natural regeneration occurred ∼ "> ∼ 5-10 y following management, underscoring sustained effects of management treatments on tree reproduction success. Our results show that forest management treatments have the potential to promote natural ponderosa pine regeneration in the SWUS, sometimes at undesirable high densities. Study Implications: Natural ponderosa pine regeneration is declining in forests of the southwestern United States (SWUS), and may increasingly be incorporated as a goal of forest management treatments. Across a diverse set of managed and unmanaged SWUS forest sites, we found that contemporary management treatments – especially thinning + "> + prescribed understory burning – supported natural ponderosa pine regeneration over the past two decades, which were climatically unfavorable in much of the region. Our results show that existing forest management treatments have the potential to promote natural ponderosa pine regeneration in the SWUS, but will require assessment and modification through time to remain effective.

Forest Science↗

USGS2025

Filling the gaps: A Bayesian mixture model for imputing missing soil water content data

Soil water content (SWC) data are central to evaluating how soil moisture varies over time and space and influences critical plant and ecosystem functions, especially in water-limited drylands. However, sensors that record SWC at high frequencies often malfunction, leading to incomplete timeseries and limiting our understanding of dryland ecosystem dynamics. We developed an analytical approach to impute missing SWC data, which we tested at six eddy flux tower sites along an elevation gradient in the southwestern United States. We impute missing data as a mixture of linearly interpolated SWC between the observed endpoints of a missing data gap and SWC simulated by an ecosystem water balance model (SOILWAT2). Within a Bayesian framework, we allowed the relative utility (mixture weight) of each component (linearly interpolated vs. SOILWAT2) to vary by depth, site and gap characteristics. We explored “fixed” weights versus “dynamic” weights that vary as a function of cumulative precipitation, average temperature, and time since the start of the gap. Both models estimated missing SWC data well (R2 = 0.70–0.88 vs. 0.75–0.91 for fixed vs. dynamic weights, respectively), but the utility of linearly interpolated versus SOILWAT2 values depended on site and depth. SOILWAT2 was more useful for more arid sites, shallower depths, longer and warmer gaps and gaps that received greater precipitation. Overall, the mixture model reliably gap-fills SWC, while lending insight into processes governing SWC dynamics. This approach to impute missing data could be adapted to accommodate more than two mixture components and other types of environmental timeseries.

New Mexico↗

USGS2025

Beyond optimality: Dryland ecosystems infrequently use water efficiently for carbon gain

Optimality theory assumes plants maximize carbon gain per unit water lost and is often implemented to scale leaf-level carbon gain and water use to regional and global scales. Optimality theory is often mathematically represented by assuming plant water-use efficiency (WUE) scales with VPD k , where k = ½ represents expected optimal behavior. It is unclear, however, if this relationship holds in arid and semi-arid ecosystems that are strongly impacted by soil and atmospheric moisture status. We used data from seven flux tower sites along an aridity gradient in New Mexico to answer: how does the relationship between WUE and VPD compare to expectations based on optimality theory? To address this question, we integrated the Dynamic Evapotranspiration Partitioning Approach for Rapid Timescales with a stochastic antecedent model to estimate ecosystem-level WUE (GPP/T) and the net sensitivity of WUE to VPD, or k Dynamic , which we compare to the theoretical optimal sensitivity of k = ½. Our results show that optimality theory is not always appropriate, and k Dynamic often deviates from ½, especially at some of the more arid sites or during periods of low soil moisture. At less arid, higher elevation sites, k Dynamic is most consistent with optimality theory at moderate VPD levels, but not at high VPD. In general, the sensitivity of WUE to VPD is highly variable such that k Dynamic exhibits notable daily and seasonal variability, suggesting highly dynamic stomatal behavior. These results emphasize that representing plant water-use strategies as dynamic in time and space is critical to improving large-scale estimates of plant water use.

New Mexico↗

USGS2025

Shifts in suitability of pinyon-juniper communities: A climate adaptation framework for range-wide management of arid woodland resources

Pinyon-juniper (PJ) woodlands are a diverse ecosystem type providing a wealth of ecosystem services across western North America. Managing PJ woodlands in the 21st century entails balancing multiple conservation objectives, and resource managers and policy-makers working to sustain PJ woodlands need spatially explicit information about current PJ woodland conditions and how they may be impacted in coming decades in the context of wildfire risk and changing climate. Here, we address knowledge gaps and provide information that improves the long-term value of conservation and restoration actions in PJ woodlands. To this end, we merged projections of future environmental suitability for nine PJ species with wildfire risk and locations of mature and old-growth (MOG) woodlands to assess spatial variation in PJ woodlands with differing threats and management opportunities. We identified potential climate refugia with enduring high community suitability and low burn probability (3 % of study area ) that may persist with relatively little management. We found promising locations of PJ-MOG forest type with high future suitability (12 % of areas) that could be prioritized for fire risk reduction to maintain high-value woodlands. Despite a 38 % mean community suitability decline under future climate conditions, some locations (7 % of areas) may act as climate refugia where future climate conditions can support current PJ woodland composition and structure. We conclude by demonstrating how this information can be integrated into a conceptual framework to help prioritize conservation and climate adaptation in PJ woodlands.

western North America↗

USGS2025

Most pinyon-juniper woodland species distributions are projected to shrink rather than shift under climate change

Pinyon–juniper (PJ) woodlands are among the most widespread ecosystems in rangelands of western North America, supporting diverse wildlife habitat, recreation, grazing, and cultural/spiritual enrichment. Anticipating future distribution shifts under changing climate will be critical to climate adaptation and conservation efforts in these ecosystems. Here, we evaluate drivers of PJ tree species’ distributions and project changes in response to future climate change. We developed species distribution models with dryland-focused predictors to project environmental suitability changes across the entirety of three pinyon and six juniper species ranges. We identify areas of robust suitability change by combining suitability projections from multiple emissions scenarios and time periods. PJ species’ suitabilities respond to many temperature and moisture covariates expected to change in the future. Projected responses among PJ species are highly variable, ranging from modest declines with concurrent gains for overall little net change to wide-ranging declines with no gains for overall range contractions. Environmental suitability is projected to decline broadly across the arid United States Southwest and remain relatively stable across the northern Great Basin and Colorado Plateau. Our results suggest unique responses of PJ species to future climate change. We found that species were projected to experience more losses than gains in suitability, for overall range shrinks rather than shifts. Land managers have the capacity to increase woodland resilience to drought, and our results can inform rangeland-wide management planning and conservation efforts in PJ woodlands.

Rangeland Ecology & Management↗

USGS2024

Managing to survive despite the weather: Seeding decisions affecting simulated dryland restoration outcomes

Limited favorable weather windows for post-germination early seedling survival are associated with low restoration success in drylands. We examined whether post-fire seeding decisions could alter early seedling emergence and restoration success across western North American sagebrush ecosystems with a simulation approach. Seedling emergence estimates were based on germination of a specified percentile of sown seeds followed by favorable conditions for seedling development. We asked how three categories of seeding decisions affected emergence: post-fire seeding year, seasonal seeding delay (via seed coating technologies or later seeding timing), or native perennial grass seed source (via differing germination behavior). We also tested potential effects of mean annual precipitation on seeding decision outcomes (interactive effect) and included topographic microclimate and site (random effect) in models. Emergence was highest when the best seed source (of 10) was seeded in the best post-fire year (of 5). High emergence also resulted from seeding in the best post-fire year with an average seed source or seeding with the best source in the first post-fire year. Emergence was higher overall with higher mean precipitation. Seeding decision outcomes were sensitive to annual mean precipitation, with greater differences observed due to decisions at lower precipitation levels. While sensitive to assumptions related to seedling development and germination speed, these results suggest that restoration approaches linked to germination behavior and weather variability could improve restoration success rates in variable drylands like sagebrush ecosystems.

California, Idaho, Nevada, Oregon, Utah↗

USGS2024

Increasing soil water drought in response to altered precipitation timing across the western United States

Recent trends of rising temperatures and longer droughts between precipitation events are impacting water-limited dryland ecosystems in the western United States. Although ecosystem drought response depends directly on soil moisture, trends in soil moisture (e.g., edaphic drought) remain more poorly explored than precipitation (e.g., meteorological drought), representing an important knowledge gap. Here, we applied the SOILWAT2 ecosystem water balance model to quantify long-term trends of soil moisture and edaphic drought using observed daily weather from 1976 to 2019 at 337 stations across the western United States. We assessed edaphic drought for different plant community types (grass dominated vs. shrub dominated), and explored variations with soil depth and texture. The duration of the longest edaphic drought in a given year increased by 1.5 ± 0.2 days/decade for grassy and 1.7 ± 0.2 days/decade for woody vegetation. Importantly, these trends in edaphic drought were consistent with but greater in magnitude compared with meteorological drought indicating more severe water stress for both plants and ecosystems. The correlation between meteorological drought and edaphic drought was greater under woody vegetation (0.45) compared with grass (0.34) and greater at surface soil depths (0–20 cm; 0.46) compared with the deeper soil (20–100 cm; 0.34). Among soil textures, the correlation between meteorological and edaphic drought was highest on sandy soils and lowest on finer textured silty soils. Using the biogeographic domains (eight western NEON domains), we found that the Pacific Northwest, Pacific Southwest, and Desert Southwest exhibited the strongest increases in edaphic drought through time, but lower correlation between meteorological and edaphic droughts. These findings characterize strong but variable connections between edaphic drought and meteorological drought across the western United States and demonstrate the critical influences of vegetation type, soil depth, and soil properties in mediating the magnitude and spatial distribution of edaphic drought.

western United States↗

USGS2024

Restoration treatments enhance tree growth and alter climatic constraints during extreme drought

The frequency and severity of drought events are predicted to increase due to anthropogenic climate change, with cascading effects across forested ecosystems. Management activities such as forest thinning and prescribed burning, which are often intended to mitigate fire hazard and restore ecosystem processes, may also help promote tree resistance to drought. However, it is unclear whether these treatments remain effective during the most severe drought conditions or whether their impacts differ across environmental gradients. We used tree-ring data from a system of replicated, long-term (>20 years) experiments in the southwestern United States to evaluate the effects of forest restoration treatments (i.e., evidence-based thinning and burning) on annual growth rates (i.e., basal area increment; BAI) of ponderosa pine ( Pinus ponderosa ), a broadly distributed and heavily managed species in western North America. The study sites were established at the onset of the most extreme drought event in at least 1200 years and span much of the climatic niche of Rocky Mountain ponderosa pine. Across sites, tree-level BAI increased due to treatment, where trees in treated units grew 133.1% faster than trees in paired, untreated units. Likewise, trees in treated units grew an average of 85.6% faster than their pre-treatment baseline levels (1985 to ca. 2000), despite warm, dry conditions in the post-treatment period (ca. 2000–2018). Variation in the local competitive environment promoted variation in BAI, and larger trees were the fastest-growing individuals, irrespective of treatment. Tree thinning and prescribed fire altered the climatic constraints on growth, decreasing the effects of belowground moisture availability and increasing the effects of atmospheric evaporative demand over multi-year timescales. Our results illustrate that restoration treatments can enhance tree-level growth across sites spanning ponderosa pine's climatic niche, even during recent, extreme drought events. However, shifting climatic constraints, combined with predicted increases in evaporative demand in the southwestern United States, suggest that the beneficial effects of such treatments on tree growth may wane over the upcoming decades.

Arizona, Colorado, Nevada, New Mexico, Texas↗

USGS2024

Declining ecological resilience and invasion resistance under climate change in the sagebrush region, United States

In water-limited dryland ecosystems of the Western United States, climate change is intensifying the impacts of heat, drought, and wildfire. Disturbances often lead to increased abundance of invasive species, in part, because dryland restoration and rehabilitation are inhibited by limited moisture and infrequent plant recruitment events. Information on ecological resilience to disturbance (recovery potential) and resistance to invasive species can aid in addressing these challenges by informing long-term restoration and conservation planning. Here, we quantified the impacts of projected future climate on ecological resilience and invasion resistance (R&R) in the sagebrush region using novel algorithms based on ecologically relevant and climate-sensitive predictors of climate and ecological drought. We used a process-based ecohydrological model to project these predictor variables and resulting R&R indicators for two future climate scenarios and 20 climate models. Results suggested widespread future R&R decreases (24%–34% of the 1.16 million km 2 study area) that are generally consistent among climate models. Variables related to rising temperatures were most strongly linked to decreases in R&R indicators. New continuous R&R indices quantified responses to climate change; particularly useful for areas without projected change in the R&R category but where R&R still may decrease, for example, some of the areas with a historically low R&R category. Additionally, we found that areas currently characterized as having high sagebrush ecological integrity had the largest areal percentage with expected declines in R&R in the future, suggesting continuing declines in sagebrush ecosystems. One limitation of these R&R projections was relatively novel future climatic conditions in particularly hot and dry areas that were underrepresented in the training data. Including more data from these areas in future updates could further improve the reliability of the projections. Overall, these projected future declines in R&R highlight a growing challenge for natural resource managers in the region, and the resulting spatially explicit datasets provide information that can improve long-term risk assessments, prioritizations, and climate adaptation efforts.

western United States↗

USGS2024

Temperature-driven convergence and divergence of ecohydrological dynamics in the ecosystems of a sky island mountain range

Forest and woodland decline is predicted to be increasingly influenced by meteorological variation and climate change in the future. By determining how meteorological variation leads to similar versus differing ecohydrological dynamics of forest and woodland ecosystems, we can gain insight on how future climate-driven declines may be realized. We characterized 23 mixed conifer forest (MC), ponderosa pine forest (PP) and piñon pine–juniper woodland (PJ) sites with different canopy covers in southern Nevada, USA. We compared meteorological variation between these sites and employed water balance modelling and information theory to estimate similarity in the density distributions of soil temperature (Ts), soil water potential (SWP) and transpiration partitioning into total evapotranspiration (T/ET) within and across ecosystems in wetter and drier seasons and in cooler and warmer decades. From 1941 to 2020, this location experienced declines in meteorological water deficit due to higher precipitation, although temperatures increased over more recent time periods (1981–2020). From 1981 to 2020, we generally found greater similarity in SWP and T/ET distributions within MC sites and PP sites in the cool season and in the warm season generally found greater similarity in Ts and T/ET distributions within and between PP and PJ sites (excepting T/ET between PJ sites and higher canopy cover PP sites). Recent warm decades promoted convergence in warm and cool season Ts dynamics, such that Ts dynamics generally became more similar between higher elevation MC sites and lower elevation PP–PJ sites. At the same time, warmer decades initiated divergence of SWP and T/ET dynamics within groups of MC–PP and PP–PJ sites that were formerly more similar to each other (excepting SWP in wet seasons). Although their dynamics will remain strongly coupled to precipitation, warming temperatures have the potential to promote divergence in the ecohydrological dynamics of ecosystems at lower and higher elevations in this sky island system and may also promote novel within-ecosystem divergence associated with variation in vegetation structural attributes.

Nevada↗

USGS2024

A semi-mechanistic model for partitioning evapotranspiration reveals transpiration dominates the water flux in drylands

Popular evapotranspiration (ET) partitioning methods make assumptions that might not be well-suited to dryland ecosystems, such as high sensitivity of plant water-use efficiency (WUE) to vapor pressure deficit (VPD). Our objectives were to (a) create an ET partitioning model that can produce fine-scale estimates of transpiration (T) in drylands, and (b) use this approach to evaluate how climate controls T and WUE across ecosystem types and timescales along a dryland aridity gradient. We developed a novel, semi-mechanistic ET partitioning method using a Bayesian approach that constrains abiotic evaporation using process-based models, and loosely constrains time-varying WUE within an autoregressive framework. We used this method to estimate daily T and weekly WUE across seven dryland ecosystem types and found that T dominates ET across the aridity gradient. Then, we applied cross-wavelet coherence analysis to evaluate the temporal coherence between focal response variables (WUE and T/ET) and environmental variables. At yearly scales, we found that WUE at less arid, higher elevation sites was primarily limited by atmospheric moisture demand, and WUE at more arid, lower elevation sites was primarily limited by moisture supply. At sub-yearly timescales, WUE and VPD were sporadically correlated. Hence, ecosystem-scale dryland WUE is not always sensitive to changes in VPD at short timescales, despite this being a common assumption in many ET partitioning models. This new ET partitioning method can be used in dryland ecosystems to better understand how climate influences physically and biologically driven water fluxes.

New Mexico↗

USGS2024

Estimating multivariate ecological variables at high spatial resolution using a cost-effective matching algorithm

Simulation models are valuable tools for estimating ecosystem response to environmental conditions and are particularly relevant for investigating climate change impacts. However, because of high computational requirements, models are often applied over a coarse grid of points or for representative locations. Spatial interpolation of model output can be necessary to guide decision-making, yet interpolation is not straightforward because the interpolated values must maintain the covariance structure among variables. We present methods for two key steps for utilizing limited simulations to generate detailed maps of multivariate and time series output. First, we present a method to select an optimal set of simulation sites that maximize the area represented for a given number of sites. Then, we introduce a multivariate matching approach to interpolate simulation results to detailed maps for the represented area. This approach links simulation output to environmentally analogous matched sites according to user-defined criteria. We demonstrate the methods with case studies using output from (1) an individual-based plant simulation model to illustrate site selection, and (2) an ecosystem water balance simulation model to illustrate interpolation. For the site selection case study, we identified 200 simulation sites that represented 96% of a large study area (1.12 × 10 6 km 2 ) at a ~1-km resolution. For the interpolation case study, we generated ~1-km resolution maps across 4.38 × 10 6 km 2 of drylands in North America from a 10 × 10 km grid of simulated sites. Estimates of interpolation errors using cross validation were low (less than 10% of the range of each variable). Our point selection and interpolation methods, which are available as an easy-to-use R package, provide a means of cost-effectively generating detailed maps of expensive, complex simulation output (e.g., multivariate and time series) at scales relevant for local conservation planning. Our methods are flexible and allow the user to identify relevant matching criteria to balance interpolation uncertainty with areal coverage to enhance inference and decision-making at management-relevant scales across large areas.

Ecosphere↗

USGS2024

Wildfire probability estimated from recent climate and fine fuels across the big sagebrush region

Background Wildfire is a major proximate cause of historical and ongoing losses of intact big sagebrush ( Artemisia tridentata Nutt.) plant communities and declines in sagebrush obligate wildlife species. In recent decades, fire return intervals have shortened and area burned has increased in some areas, and habitat degradation is occurring where post-fire re-establishment of sagebrush is hindered by invasive annual grasses. In coming decades, the changing climate may accelerate these wildfire and invasive feedbacks, although projecting future wildfire dynamics requires a better understanding of long-term wildfire drivers across the big sagebrush region. Here, we integrated wildfire observations with climate and vegetation data to derive a statistical model for the entire big sagebrush region that represents how annual wildfire probability is influenced by climate and fine fuel characteristics. Results Wildfire frequency varied significantly across the sagebrush region, and our statistical model represented much of that variation. Biomass of annual and perennial grasses and forbs, which we used as proxies for fine fuels, influenced wildfire probability. Wildfire probability was highest in areas with high annual forb and grass biomass, which is consistent with the well-documented phenomenon of increased wildfire following annual grass invasion. The effects of annuals on wildfire probability were strongest in places with dry summers. Wildfire probability varied with the biomass of perennial grasses and forbs and was highest at intermediate biomass levels. Climate, which varies substantially across the sagebrush region, was also predictive of wildfire probability, and predictions were highest in areas with a low proportion of precipitation received in summer, intermediate precipitation, and high temperature. Conclusions We developed a carefully validated model that contains relatively simple and biologically plausible relationships, with the goal of adequate performance under novel conditions so that useful projections of average annual wildfire probability can be made given general changes in conditions. Previous studies on the impacts of vegetation and climate on wildfire probability in sagebrush ecosystems have generally used more complex machine learning approaches and have usually been applicable to only portions of the sagebrush region. Therefore, our model complements existing work and forms an additional tool for understanding future wildfire and ecological dynamics across the sagebrush region.

Fire Ecology↗

USGS2024

Disentangling drivers of annual grass invasion: Abiotic susceptibility vs. fire-induced conversion to cheatgrass dominance in the sagebrush biome

Invasive annual grasses are often facilitated by fire, yet they can become ecologically dominant in susceptible locations even in the absence of fire. We used an extensive vegetation plot database to model susceptibility to the invasive annual grass cheatgrass ( Bromus tectorum L.) in the sagebrush biome as a function of climate and soil water availability variables. We built random forest models predicting cheatgrass presence or dominance (greater than 15 % relative cover) under unburned (37,219 plots) and burned conditions (6340 plots). We mapped predicted probability of cheatgrass presence and dominance, conditional on burning. We combined predicted susceptibility with burn probability to quantify the 10-year total risk of cheatgrass dominance. Finally, we identified portions of the landscape (1) at risk of fire-induced conversion to cheatgrass dominance, (2) consistently susceptible to cheatgrass dominance, or (3) consistently resistant to cheatgrass dominance. At the scale of the sagebrush biome, we found that abiotic susceptibility to cheatgrass dominance drives total risk, regardless of fire. At local scales (i.e., individual 30 m pixels), burning increased the probability of cheatgrass dominance by a median of 14 %. Threshold-based analyses indicate that 10–31 % of the sagebrush biome was at risk of fire-induced dominance, with 55 % exhibiting abiotic resistance and 5 % exhibiting abiotic susceptibility to dominance regardless of fire. Burn probability was higher in areas predicted to be susceptible to dominance, illustrating how cheatgrass invasion can cause ecosystem conversions that are then sustained by grass-fire cycles. Disentangling the influence of abiotic conditions and fire contributes to our understanding of the mechanisms driving invasion dynamics, and modeling the probability of dominance can help anticipate where ecological transformations are at risk of occurring. Our approach can facilitate the prioritization of management actions in the sagebrush biome and be used as a framework for modeling invasion risk in other disturbance-prone ecosystems.

Biological Conservation↗