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Relative potential for stand persistence of riparian and upland aspen stands of a semi-arid montane landscape of the Southern Rocky Mountains

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We investigated the relationship between aspen regeneration and site moisture availability potential using ecosystem type as a proxy. We hypothesized that aspen stands growing along perennial-flowing streams would support higher aspen regeneration densities than upland aspen stands. We compared stand structure, groundcover composition, and regeneration densities of nine riparian aspen stands with nine paired upland aspen stands in the Caribou-Targhee National Forest. Aspen regeneration densities were significantly higher in the riparian aspen stands (845. 3 + 318.7 stems ha-1) compared to the upland aspen stands (249.1 + 74.1 stems ha-1) for regeneration shorter than one meter (p = 0.0391). Riparian stands also exhibited significantly higher forb (p< 0.001) and graminoid (p < 0.001) cover compared to upland aspen stands, suggesting that riparian sites provided higher site moisture availability. We suggest that riparian areas may provide refugia for aspen in the future considering projections of increased incidence of acute drought.

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Phenology forecasting models for detection and management of invasive annual grasses

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We created range-wide phenology forecasts for two problematic invasive annual grasses: cheatgrass, and red brome . We tested a suite of 18 mechanistic phenology models using observations from monitoring experiments, volunteer science, herbarium records, timelapse camera imagery, and downscaled gridded climate data to identify the models that best predicted the dates of flowering and senescence of the two invasive grass species. We found that the timing of flowering and senescence of cheatgrass and red brome were best predicted by photothermal time models that had been adjusted for topography using gridded continuous heat-insolation load index values. Phenology forecasts based on these models can help managers make decisions about when to schedule management actions such as grazing to reduce undesirable invasive grasses and promote forage production, quality, and biodiversity in grasslands; to predict the timing of greatest fire risk after annual grasses dry out; and to select remote sensing imagery to accurately map invasive grasses across topographic and latitudinal gradients. These phenology models also have the potential to be operationalized for within-season or within-year decision support.

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Ventenata dubia projected to expand in the western US despite future novel conditions

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Distributions of both native and invasive species are expected to shift under future climate. Species distribution models (SDMs) are often used to explore future habitats, but sources of uncertainty including novel climate conditions may reduce the reliability of future projections. We explore the potential spread of the invasive annual grass ventenata (Ventenata dubia) in the western United States under both current and future climate scenarios using boosted regression tree models and 30 global climate models (GCMs). We quantify novel climate conditions, prediction variability arising from both the SDMs and GCMs, and the agreement among GCMs. Results demonstrate that currently suitable habitat is concentrated inside the invaded range of the northwest, but substantial habitat exists outside the invaded range in the Southern Rockies and southwestern US mountains. Future suitability projections vary greatly among GCMs, but GCMs commonly projected decreased suitability in the invaded range and increased suitability along higher elevations of interior mountainous areas.

 

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Lightning-ignited wildfires in the western US: Ignition precipitation and associated environmental conditions

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Cloud-to-ground lightning with minimal rainfall (“dry” lightning) is a major wildfire ignition source in the western United States (WUS). Although dry lightning is commonly defined as occurring with <2.5 mm of daily-accumulated precipitation, a rigorous quantification of precipitation amounts concurrent with lightning-ignited wildfires (LIWs) is lacking. We combine wildfire, lightning and precipitation data sets to quantify these ignition precipitation amounts across ecoprovinces of the WUS. The median precipitation for all LIWs is 2.8 mm but varies with vegetation and fire characteristics. “Holdover” fires not detected until 2–5 days following ignition occur with significantly higher precipitation (5.1 mm) compared to fires detected promptly after ignition (2.5 mm), and with cooler and wetter environmental conditions. Further, there is substantial variation in precipitation associated with promptly-detected (1.7–4.6 mm) and holdover (3.0–7.7 mm) fires across ecoprovinces. Consequently, the widely-used 2.5 mm threshold does not fully capture lightning ignition risk and incorporating ecoprovince-specific precipitation amounts would better inform WUS wildfire prediction and management.

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The fastest-growing and most destructive fires in the US (2001 to 2020)

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The most destructive and deadly wildfires in US history were also fast. Using satellite data, we analyzed the daily growth rates of more than 60,000 fires from 2001 to 2020 across the contiguous US. Nearly half of the ecoregions experienced destructive fast fires that grew more than 1620 hectares in 1 day. These fires accounted for 78% of structures destroyed and 61% of suppression costs($18.9 billion). From 2001 to 2020, the average peak daily growth rate for these fires more than doubled (+249% relative to 2001) in the Western US. Nearly 3 million structures were within 4 kilometers of a fast fire during this period across the US. Given recent devastating wildfires, understanding fast fires is crucial for improving firefighting strategies and community preparedness

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Annual grass invasions and wildfire deplete ecosystem carbon storage by >50% to resistant base levels

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Ecological disturbance can affect carbon storage and stability and is a key consideration for managing lands to preserve or increase ecosystem carbon to ameliorate the global greenhouse gas problem. Dryland soils are massive carbon reservoirs that are increasingly impacted by species invasions and altered fire regimes, including the exotic-grass-fire cycle in the extensive sagebrush steppe of North America. Direct measurement of total carbon in 1174 samples from landscapes of this region that differed in invasion and wildfire history revealed that their impacts depleted soil carbon by 42-49%, primarily in deep horizons, which could amount to 17.1-20.0 Tg carbon lost across the ~400,000 ha affected annually. Disturbance effects on soil carbon stocks were not synergistic, suggesting that soil carbon was lowered to a floor-i.e. a resistant base-level-beneath which further loss was unlikely. Restoration and maintenance of resilient dryland shrublands/rangelands could stabilize soil carbon at magnitudes relevant to the global carbon cycle.

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Nontarget effects of herbicides on annual forbs and seeded grass in the Great Basin, US, partially offset by planting depth and application rate

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We seeded perennial grass (Elymus elymoides) at multiple depths to determine susceptibility and resistance. Herbicides were applied at full and reduced rates to mimic the effect of litter in natural systems. We observed reductions in most non-native species in all treatments, but also extensive reductions of native annual forbs, although these were offset at lower application rates, and some species (e.g. Amsinckia tessellata and Microsteris gracilis) were less susceptible than others. Herbicides, particularly indaziflam, reduced E. elymoides emergence, but planting seeds at 2–3 cm depths improved emergence, particularly for imazapic, with 15–68% greater emergence than seeds planted at 1 cm. We suggest surveys for native annual forbs and resistant invaders before applying herbicides and field testing to determine whether reduced rates could provide weed control while maintaining annual forbs. We suggest planting E. elymoides at 2–3 cm when applying herbicides, an approach that may be effective for other species. Herbicide use can be an effective tool, but our results indicate that mitigation of nontarget effects will be needed to maintain native plant diversity.

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Patchy response of cheatgrass and nontarget to indaziflam and imazapic applied after wildfire in sagebrush

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Overall, indaziflam + imazapic had greater initial control of cheatgrass, but by 2023, both treatments led to similar ∼17 percentage-point reductions in cheatgrass cover. Cheatgrass individuals that “escaped” the herbicide treatment grew exceptionally large and fecund. There were no reductions in cover in any native vegetation type, including biocrusts, and nontarget increases in cover were observed for 1) deep-rooted perennial grasses treated with indaziflam + imazapic in the 2011 burn subregion and 2) the shallow-rooted Sandberg bluegrass (Poa secunda) treated with either herbicide in the 2011 or 2011 + 2019 burn subregions. Consideration of burn legacies, pretreatment landscape condition, and evenness of treatment application may improve restoration outcomes and help prioritize management allocation, timing, and treatment expectations.

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Naturalized species drive functional trait shifts in plant communities

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Our research shows that across deserts, grasslands, and forests, plant communities with higher abundance of naturalized species are more acquisitive above and belowground, shorter, more shallowly rooted, and less dependent on mycorrhizal symbionts for resource acquisition. These functional shifts likely drive observed changes in carbon storage, litter decomposition, and nutrient and water cycling in invaded ecosystems. This mechanistic understanding of functional community change is a crucial step toward predicting and mitigating impacts of naturalized and invasive species.

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Leveraging local habitat suitability models to enhance restoration benefits for species of conservation concern

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Using the Gunnison sage-grouse as a case study, we leveraged existing resource selection function models to identify areas of high restoration potential across landscapes with variable habitat conditions and habitat-use responses. We also tested how this information could be used to improve restoration planning. We simulated change in model covariates across crucial habitats for a suite of restoration actions to generate heatmaps of relative habitat suitability improvement potential, then assessed the degree to which use of these heatmaps to guide placement of restoration actions could improve suitability outcomes. We also simulated new or worsening plant invasions and projected the resulting loss or degradation of habitats across space. We found substantial spatial variation in projected changes to habitat suitability and new habitat created, both across and among crucial habitats. Use of our heatmaps to target placement of restoration actions improved habitat suitability nearly fourfold and increased new habitat created more than 15-fold, compared to placements unguided by heatmaps. Our decision-support products identified areas of high restoration potential across landscapes with variable habitat conditions and habitat-use responses. We demonstrate their utility for strategic targeting of habitat restoration actions, facilitating optimal allocation of limited management resources to benefit species of conservation concern.

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