Research and Publications
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Invasive annual grasses (IAG) continue to spread within the sagebrush biome of the western United States, degrading plant communities and wildlife habitat, decreasing forage for ranching livelihoods, and heightening wildre risk. Effective management of IAGs requires action and long-term strategic planning across the sage-brush biome, but the cumulative effects of IAG treatments over time and space are not well understood, espe-cially over broad extents dened for strategies like the Sagebrush Conservation Design. We developed a simulation model and sampling framework that allow local-scale actions to be ‘scaled up’ to evaluate large-scale regional and biome-wide management strategy outcomes. We worked with natural resource managers and ex-perts to co-develop a spatially explicit state-and-transition simulation model of IAG dynamics in sagebrush landscapes that can be used to evaluate alternative management strategies. We evaluated our framework by contrasting two baseline scenarios in terms of their long-term effects on the sagebrush biome. We show that focusing management efforts on moderate to high IAG cover was effective at reducing full conversion to IAGs but failed to prevent widespread establishment of IAGs in core sagebrush areas, exposing them to increased risk of wildre and wildlife habitat degradation. The results of our model help quantify the extent of the problem that IAGs pose to sagebrush ecosystems given current knowledge and management efforts. Our framework provides a platform to explore alternative management strategy outcomes and can help managers develop informed con-servation plans with realistic expectations for return on investment of resources committed to sagebrush landscapes.
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Both commercial and wild mixtures suppressed B. tectorum relative to control mesocosms without native plants. The commercial mixture produced more aboveground volume than wild mixtures in both seasons, but was less effective at suppressing B. tectorum, which accumulated 67% more biomass in commercial mesocosms than in wild ones. Commercial communities shrank following invasion. In contrast, several wild communities had near-complete B. tectorum suppression, despite smaller aboveground volume, and all wild communities increased in size in the second season. Highly competitive wild mixtures are promising for restoration and suggest a potential trade-off between rapid aboveground growth and invasion resistance. Commercially available native plants selected for agronomic traits like large size and high seed yield may lack characteristics desirable in invaded dryland restoration settings, such as weed suppression and low biomass production to reduce fuel for wildfires.
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Models using both field collected and remotely sensed vegetation indices estimated increases in exotic annual grass cover over time following mowed fuel break installation, and higher exotic annual grass cover closer to mowed fuel breaks. These increases in exotic annual grass occurred within, at 500 m and at 1000 m from mowed fuel breaks. However, we found variable patterns of exotic annual grass after green strip fuel break installation depending on the data source. No increase in exotic annual grass was indicated by either analysis at distances greater than 500 m from green strip fuel breaks. However, our remotely sensed and field data analyses disagreed on the direction of the association of exotic annual grass cover and green strip fuel breaks. Although fuel breaks are an important tool in managing wildland fire, our analysis underscores the importance of planting fire-resistant vegetation, rather than mowing alone, to reduce invasion by annual grasses within and around fuel breaks in sagebrush ecosystems. In addition, site characteristics that hinder the proliferation of exotic annual grasses could be evaluated when installing fuel breaks to minimize unintended effects of exotic annual grass on surrounding sagebrush habitat.
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This brief distills the collective experience of 250+ fire and wildlife professionals into nine of the most persistent challenges—and provides 36+ practical approaches that are already working on the ground. Drawn from a regional workshop and follow-up webinar series, it highlights field-tested strategies that help align wildlife conservation and fire management through shared tools, proactive planning, and stronger collaboration.
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Coniferous forests account for 78% of the western US forests and store a substantial amount of carbon. Wildfires significantly alter vegetation structure and associated forest carbon stocks. This study evaluates postfire biomass recovery trajectories (1984–2017) and total biomass accumulation in conifer forests that historically experienced low-severity, high-frequency fire regimes in the western US using recently launched Global Ecosystem Dynamic Investigations (GEDI) mission lidar data. All three ecoregions studied, including the Pacific Northwest (PNW), Southern Rockies (SR), and Northern Rockies (NR), show site-specific biomass recovery trajectories shaped by fire severity. The recovery trajectories were characterized by an initial decline and a variable gain with time since fire across the three ecoregions. Regions with low burn severity recovered to the unburned background state within the first three decades, while regions with higher burn severity only recovered in the Northern Rockies after five decades without fire. Moderate- and high-severity burned areas in both SR and PNW exhibited slow declines or sustained low biomass periods following fires, implying potential ecosystem transformation or an arrested state of lower biomass. Time since fire and fire severity were identified as the most significant drivers of postfire biomass recovery, likely because they reflect both reduced seed availability and the process of seedling establishment and regeneration. In addition, distance to unburned area, drought (measured using the Standardized Precipitation Evapotranspiration Index (SPEI)), elevation, and fire size were important drivers of biomass recovery. Our results demonstrate that all three ecoregions experienced a loss of overall biomass (15–23% (+/−40%)), with the largest losses occurring in the areas with high-severity burns (59% (+/−23%)) in the Southern Rockies compared to unburned forests within the first three decades. This study thus confirms GEDI’s ability to assess disturbance-driven vegetation biomass dynamics and provides an open-science methodology that could be utilized for other regions. In conclusion, our study indicates that an increase in fire severity within low-severity, high-frequency fire regimes, beyond historically observed levels, results in greater carbon losses. It is therefore important to consider the effects of increases in fire severity on vegetation recovery trajectories to infer the future carbon potential in these ecosystems.
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Elevated soil temperatures resulting from reintroduction of prescribed fire into long unburnt stands have been associated with unintended tree mortality. Several models exist to predict soil temperatures resulting from soil heating by fire; however, data to develop and validate these models are limited. A model to predict soil temperature at depths up to 25 inches (0.63 m) was developed from a data set from 46 prescribed burns in coniferous forests in national forests and parks in Arizona and California. Soil temperature was less than 140 °F (60 °C) at depths greater than 6 inches (0.15 m) and constant below 10 inches (0.25 m). Using a Bayesian generalized nonlinear additive model, nine models formed from combinations of soil and humus moisture contents, fuel consumption and tree species were fit to soil temperature data for Pinus ponderosa, P. lambertiana, and Sequoiadendron gigantea. Bayesian R2 for the full model and the reduced model containing tree species and fuel consumption was 0.70 and 0.67, respectively. The Bayesian model predicted higher maximum temperatures than two soil heating models in the First Order Fire Effects Model. Based on parsimony, the model using fuel consumption and tree species is recommended for use.
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Extreme fire weather (hot, dry, and windy conditions) has intensified globally, yet formally attributing this trend to anthropogenic climate change remains challenging. Here, we analyze global trends in extreme fire weather days (FWI95d, annual count of days with Fire Weather Index above the 95th percentile) over 1980–2023, using climate model ensembles, observational data, and fingerprint detection techniques. We find that the observed increase in extreme fire weather bears a clear externally forced signal, detectable at 99% confidence above natural variability and attributable to human-induced climate change. This emerging human-induced fingerprint on extreme fire weather highlights a benchmark for climate science and underscores the urgency of integrating these insights into wildfire risk management and adaptation strategies.
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Forest treatments such as prescribed burns, mastication, and thinning are widely implemented across the western USA to reduce fuels and enhance wildfire resilience. These practices also influence snow accumulation and melt, which, in turn, affect snow storage and duration. Since many regions depend on seasonal snow for water resources, it is essential that forest management practices preserve or even enhance snow storage as a buffer against the impacts of climate change. To test the hypothesis that thinning and canopy gap creation can maximize snow storage, particularly on north-facing slopes, experimental forest treatments representing a range of thinning intensities were implemented on Cle Elum Ridge in the headwaters of the Yakima River Basin, Washington, USA. Ground-based snow observations, combined with pre-treatment (2021) and post-treatment (2023) snow-on lidar, show that canopy thinning increased snow depth and storage by 30% on north-facing slopes and by 16% on south-facing slopes. Snow depth was positively related to canopy openness, as measured by sky view fraction and canopy edge metrics, with stronger effects on north-facing slopes. In contrast, there was no clear relationship between snow depth and degree of thinning as measured by forest basal area, a common forestry metric used to plan treatment prescriptions. Using canopy edge metrics and sky view fraction relationships, we estimated the hydrologic benefit of thinning during 2023 at 12.3 acre-feet of water storage per 100 acres of north-facing forest and 5.1 acre-feet on south-facing slopes. These findings highlight the potential to incorporate hydrologic resilience as a co-benefit when planning fuel reduction strategies.
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When the Black Fire ignited in southwestern New Mexico in 2022, it had all the ingredients for disaster: record-high winds, extremely low humidity, and over 131,000 hectares (323,708 acres) of forest fuels to feed on. But something unexpected happened. Instead of becoming another catastrophic megafire, it burned mostly at low to moderate severity. The secret? The landscape had already experienced dozens of previous fires, both planned and natural, that helped tame the beast.
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To restore ecosystem health and reduce the negative impacts of wildfire, scientists and land managers argue that more prescribed fire is needed on the land. However, a lack of effectively trained personnel in the role of “burn boss” is a barrier to increasing safe and effective prescribed burning. Burn bosses are responsible for planning and implementing prescribed burns. There are two key contributors to the shortage of these positions: the first is retirement without replacing personnel, and the second is insufficient training mechanisms necessary to increase the number of personnel capable of responding to the challenges of conducting prescribed burns. This research brief summarizes a case study on the redesign of federal prescribed fire training, utilizing up-to-date understanding of adult learning to enhance training effectiveness.