Wildland fire activity has increased across many regions of the United States, raising concerns about smoke exposure and the health impacts of fine particulate matter (PM2.5). Former studies on environmental disparities show smoke impacts vary across communities and regions, but most studies focus on non-spatial factors (e.g., income, race/ethnicity), potentially overlooking the spatial dimension of smoke exposure disparities. We advance this literature by assessing a location's resilience with spatial aspects of wildland fire smoke exposure for two spatial variables: wildland urban interface (WUI) category and land ownership. We have four research objectives: 1) to identify areas with higher exposure to wildland fire PM2.5, 2) to identify areas with greater demographic or socioeconomic vulnerability, 3) to calculate increases in unhealthy air quality days, and 4) to measure the size of the population with high smoke exposure and high vulnerability. We found Native American reservations experience 0.15-0.32 mu g/m(3) higher average daily PM2.5 from wildland fire smoke, along with lower adaptive capacity, higher sensitivity, and higher vulnerability than other land ownership areas. WUI areas also showed at least 60 % higher increase in moderate air quality days (12-35 mu g/m(3)) and greater sensitivity than non-WUI areas. Most importantly, higher vulnerability areas, defined by the lowest adaptive capacity (>= 95th percentile), highest sensitivity (>= 95th percentile), and highest overall vulnerability (>= 95th percentile), had a higher increase in the number of moderate (12-35 mu g/m(3)) and unhealthy air quality days (>35 mu g/m(3)) compared to their counterparts. These findings provide insights for community-led decision-making, resource allocation, fire management strategies, and public health interventions.

Anticipating plausible future ecosystem states is necessary for effective ecosystem management. We use climate analog-based impact models and a co-production process with land managers to project future vegetation changes for the state of Oregon, United States, (2041–2070, RCP 8.5) at a management-relevant spatial resolution (270-m). We explore multiple analog-based methodologies, evaluate analog model performance with contemporary validation, and leverage climate analogs to assess projection uncertainty by quantifying areas where multiple vegetation trajectories are plausible under a single climate scenario. We find that analog-based models performed well at reproducing landscape-level vegetation composition, and moderately well at reproducing vegetation at the pixel level. Our results suggest that 64% of the study area will experience future climate conditions that support different potential natural vegetation types and 59% will experience climates corresponding with different potential plant physiognomic types, compared to reference-period conditions. We project a 60% reduction of mesic conifer-dominated forests with transitions to mixed evergreen forest types. We also project losses to dry forests, cold forests and parklands, with commensurate expansions of shrublands, grasslands, and geographic redistribution of dry forest types. We find that in many areas, several vegetation trajectories are plausible under a single climate scenario. Finally, we provide guidance for using future vegetation projections and uncertainty outputs in management decisions using the Resist-Accept-Direct (RAD) adaptation framework.

Increased understanding of how mechanical thinning, prescribed burning, and wildfire affect subsequent wildfire severity is urgently needed as people and forests face a growing wildfire crisis. In response, we reviewed scientific literature for the US West and completed a meta-analysis that answered three questions: (1) How much do treatments reduce wildfire severity within treated areas? (2) How do the effects vary with treatment type, treatment age, and forest type? (3) How does fire weather moderate the effects of treatments? We found overwhelming evidence that mechanical thinning with prescribed burning, mechanical thinning with pile burning, and prescribed burning only are effective at reducing subsequent wildfire severity, resulting in reductions in severity between 62% and 72% relative to untreated areas. In comparison, thinning only was less effective – underscoring the importance of treating surface fuels when mitigating wildfire severity is the management goal. The efficacy of these treatments did not vary among forest types assessed in this study and was high across a range of fire weather conditions. Prior wildfire had more complex impacts on subsequent wildfire severity, which varied with forest type and initial wildfire severity. Across treatment types, we found that effectiveness of treatments declined over time, with the mean reduction in wildfire severity decreasing more than twofold when wildfire occurred greater than 10 years after initial treatment. Our meta-analysis provides up-to-date information on the extent to which active forest management reduces wildfire severity and facilitates better outcomes for people and forests during future wildfire events.

AbstractInterruption of frequent burning in dry forests across western North America and the continued impacts of anthropogenic climate change have resulted in increases in fire size and severity compared to historical fire regimes. Recent legislation, funding, and planning have emphasized increased implementation of mechanical thinning and prescribed burning treatments to decrease the risk of undesirable ecological and social outcomes due to fire. As wildfires and treatments continue to interact, managers require consistent approaches to evaluate treatment effectiveness at moderating burn severity. In this study, we present a repeatable, remote sensing–based, analytical framework for conducting fire‐scale assessments of treatment effectiveness that informs local management while also supporting cross‐fire comparisons. We demonstrate this framework on the 2021 Bootleg Fire in Oregon and the 2021 Schneider Springs Fire in Washington. Our framework used (1) machine learning to identify key bioclimatic, topographic, and fire weather drivers of burn severity in each fire, (2) standardized workflows to statistically sample untreated control units, and (3) spatial regression modeling to evaluate the effects of treatment type and time since treatment on burn severity. The application of our framework showed that, in both fires, recent prescribed burning treatments were the most effective at reducing burn severity relative to untreated controls. In contrast, thinning‐only treatments only produced low/moderate‐severity effects under the more moderate fire weather conditions in the Schneider Springs Fire. Our framework offers a robust approach for evaluating treatment effects on burn severity at the scale of individual fires, which can be scaled up to assess treatment effectiveness across multiple fires. As climate change brings increased uncertainty to dry forest ecosystems of western North America, our framework can support more strategic management actions to reduce wildfire risk and foster resilience.

Increasing fire severity and warmer, drier postfire conditions are making forests in the western United States (West) vulnerable to ecological transformation. Yet, the relative importance of and interactions between these drivers of forest change remain unresolved, particularly over upcoming decades. Here, we assess how the interactive impacts of changing climate and wildfire activity influenced conifer regeneration after 334 wildfires, using a dataset of postfire conifer regeneration from 10,230 field plots. Our findings highlight declining regeneration capacity across the West over the past four decades for the eight dominant conifer species studied. Postfire regeneration is sensitive to high-severity fire, which limits seed availability, and postfire climate, which influences seedling establishment. In the near-term, projected differences in recruitment probability between low- and high-severity fire scenarios were larger than projected climate change impacts for most species, suggesting that reductions in fire severity, and resultant impacts on seed availability, could partially offset expected climate-driven declines in postfire regeneration. Across 40 to 42% of the study area, we project postfire conifer regeneration to be likely following low-severity but not high-severity fire under future climate scenarios (2031 to 2050). However, increasingly warm, dry climate conditions are projected to eventually outweigh the influence of fire severity and seed availability. The percent of the study area considered unlikely to experience conifer regeneration, regardless of fire severity, increased from 5% in 1981 to 2000 to 26 to 31% by mid-century, highlighting a limited time window over which management actions that reduce fire severity may effectively support postfire conifer regeneration.

Wildland fire smoke risks are not uniformly distributed across people and places, and the most vulnerable communities are often disproportionately impacted. This study develops a county level community health vulnerability index (CHVI) for the Contiguous United States (CONUS) using three major vulnerability components: adaptive capacity, sensitivity, and exposure at the national and regional level. We first calculated sensitivity and adaptive capacity sub-indices using nine sensitivity and twenty adaptive capacity variables. These sub-indices were then combined with an exposure sub-index, which is based on the Community Multiscale Air Quality data (2008-2018), to develop CHVI. Finally, we conducted several analyses with the derived indices to: 1) explore associations between the level of fine particulate matter from wildland fires (fire-PM2.5) and the sub-indices/CHVI; 2) measure the impact of fire-PM2.5 on the increase in the annual number of days with 12-35 μg/m3 (moderate) and >35 μg/m3 (at or above unhealthy for sensitive groups) based on the US EPA Air Quality Index categories, and 3) calculate population size in different deciles of the sub-indices/CHVI. This study has three main findings. First, we showed that the counties with higher daily fire-PM2.5 concentration tend to have lower adaptive capacity and higher sensitivity and vulnerability. Relatedly, the counties at high risk tended to experience a greater increase in the annual number of days with 12-35 μg/m3 and >35 μg/m3 than their counterparts. Second, we found that 16.1, 12.0, and 17.6 million people out of 332 million in CONUS reside in the counties in the lowest adaptive capacity decile, highest sensitivity decile, and highest vulnerability decile, respectively. Third, we identified that the US Northwest, California, and Southern regions tended to have higher vulnerability than others. Accurately identifying a community's vulnerability to wildfire smoke can help individuals, researchers, and policymakers better understand, prepare for, and respond to future wildland fire events.

Wildfires and fire seasons are commonly rated largely on the simple metric of area burned (more hectares: bad). A seemingly paradoxical narrative frames large fire seasons as a symptom of a forest health problem (too much fire), while simultaneously stating that firedependent forests lack sufficient fire to maintain system resilience (too little fire). One key to resolving this paradox is placing contemporary fire years in the context of historical fire regimes, considering not only total fire area but also burn severity distributions. Historical regimes can also inform forest restoration efforts by illuminating the pace and scale at which fires historically maintained (i.e., 'treated') fire-resilient landscapes. Here we ask, for a broad extent of the inland Pacific Northwest (eastern Oregon and Washington, USA), a region predominated by drier forest types and recently experiencing recordbreaking fire years: 1) How much annual fire area would have been needed to support historical fire regimes?; and 2) How do contemporary fire years (1985-2020) compare to historical fire amounts and severities?To meet historical fire frequencies for each forest type, annual area burned would have averaged at least 224,000-291,000 ha per year regionally prior to the 20th century (notwithstanding interannual variability) - presumably arising from both indigenous-cultural and lightning-ignited fires. Drier forests would account for 82-88% of annual burn area. In contrast, despite the seemingly fiery contemporary era, contemporary fire years average just -49,100 ha.yr(-1) (-17-22% of historical), with only one year approximating historical area burned. Contemporary years average well under historical rates for virtually all severity classes across dry and moist (but not cold) forests. Annualized fire deficits relative to historical rates are especially conspicuous for low-severity area in dry forests (on average missing 127,000-161,000 ha.y(-1) regionally) and moderate-severity area in both dry (missing 34,000-44,000 ha.yr(-1)) and moist (missing 900012,000 ha.y 1) forests. Ten-year moving averages in burn area are increasing in recent years, but remain below historical levels. Trends are similar across states and major land ownerships.With current forest restoration efforts occurring at a fraction of historical fire rates, our findings highlight that successful restoration and maintenance will require a) increasing active treatment rates, and b) incorporating managed wildfire to attain substantially more treated area. As such, beneficial fire years may be those not with less, but rather more, area burned - with characteristic severity and patch distributions, minimal clearly-negative impacts (e.g. loss of life and property), and contribution to restoration/maintenance objectives.

The escalating climate and wildfire crises have generated worldwide interest in using proactive forest management (e.g. forest thinning, prescribed fire, cultural burning) to mitigate the risk of wildfire-caused carbon loss in forests. To estimate the risk of wildfire-caused carbon loss in western United States (US) conifer forests, we used a generalizable framework to evaluate interactions among wildfire hazard and carbon exposure and vulnerability. By evaluating where high social adaptive capacity for proactive forest management overlaps with carbon most vulnerable to wildfire-caused carbon loss, we identified opportunity hot spots for reducing the risk of wildfire-caused carbon loss. We found that relative to their total forest area, California, New Mexico, and Arizona contained the greatest proportion of carbon highly vulnerable to wildfire-caused loss. We also observed widespread opportunities in the western US for using proactive forest management to reduce the risk of wildfire-caused carbon loss, with many areas containing opportunities for simultaneously mitigating the greatest risk from wildfire to carbon and human communities. Finally, we highlighted collaborative and equitable processes that provide pathways to achieving timely climate- and wildfire-mitigation goals at opportunity hot spots.

Privately-owned forests in the Pacific Northwest (PNW) are important potential carbon sinks and play a large role in carbon sequestration and storage. Non-industrial private forest (NIPF) owners constitute a substantial portion of overall forest landownership in productive regions of the PNW; however, little is known about their preferences for non-market incentive programs aimed at increased carbon storage and sequestration, specifically by limiting timber harvest, and how those preferences might impact the outcome of forest carbon programs. We simulated landscape-scale outcomes of hypothetical forest carbon incentive programs in western Oregon (USA) by combining empirical models of NIPF owners' participation with spatially explicit forest carbon storage and sequestration data. We surveyed landowners to determine their willingness to enroll in various hypothetical forest management incentive programs that varied in terms of harvest restrictions, contract length, annual payment and incentive payment amounts, and cost-share percentages, as well as the program framing (e.g., carbon versus forest health). We used multinomial logistic regression to model whether landowners might enroll based on program attributes, landowners' attitudes toward climate change and forest management, past and planned future forest harvest activities, and socio-demographics. We found that 36% of respondents stated that they would probably or definitely enroll in at least one of the hypothetical programs they were shown while 21% of respondents refused all programs that they were offered. Our final model of landowner willingness to enroll indicated that higher annual and higher cost-share payments were the strongest positive predictors of whether landowners would enroll vs. not enroll. Landowners' willingness to enroll was not influenced by program framing as either a "forest carbon" or a "forest health"; however, landowner attitudes toward climate change were the next strongest positive predictor of enrollment after annual and cost-share payments. By simulating landowner enrollment in six policy relevant program scenarios, we illustrate that carefully designed forest carbon incentive programs for NIPF owners could have tangible carbon protection benefits (16.25 to 50.31 MMT CO2e cumulative) at relatively low costs per MT CO2e ($3.60 to $7.70). We highlight tradeoffs between maximizing enrollment in forest carbon incentive programs and providing longer term protection of carbon. This research contributes to the literature on the design of potential forest carbon incentive programs and communication about forest carbon management, as well as aims to aid policy makers and program administrators that seek ways to engage private landowners in carbon-oriented forest management.

Purpose of Review Increasing wildfire size and severity across the western United States has created an environmental and social crisis that must be approached from a transdisciplinary perspective. Climate change and more than a century of fire exclusion and wildfire suppression have led to contemporary wildfires with more severe environmental impacts and human smoke exposure. Wildfires increase smoke exposure for broad swaths of the US population, though outdoor workers and socially disadvantaged groups with limited adaptive capacity can be disproportionally exposed. Exposure to wildfire smoke is associated with a range of health impacts in children and adults, including exacerbation of existing respiratory diseases such as asthma and chronic obstructive pulmonary disease, worse birth outcomes, and cardiovascular events. Seasonally dry forests in Washington, Oregon, and California can benefit from ecological restoration as a way to adapt forests to climate change and reduce smoke impacts on affected communities. Recent Findings Each wildfire season, large smoke events, and their adverse impacts on human health receive considerable attention from both the public and policymakers. The severity of recent wildfire seasons has state and federal governments outlining budgets and prioritizing policies to combat the worsening crisis. This surging attention provides an opportunity to outline the actions needed now to advance research and practice on conservation, economic, environmental justice, and public health interests, as well as the trade-offs that must be considered. Summary Scientists, planners, foresters and fire managers, fire safety, air quality, and public health practitioners must collaboratively work together. This article is the result of a series of transdisciplinary conversations to find common ground and subsequently provide a holistic view of how forest and fire management intersect with human health through the impacts of smoke and articulate the need for an integrated approach to both planning and practice.

Research Highlights: We used airborne lidar to assess the multi-scalar patterns of forest structure across a large (471,000 hectare), multi-owner landscape of the Oregon Coast Range, USA. The results of this study can be used in the development and evaluation of conservation strategies focused on forest management. Background and Objectives: Human management practices reflect policy and economic decisions and shape forest structure through direct management and modification of disturbance regimes. Previous studies have found that land ownership affects forest cover, patch dynamics, structure, and ecosystem function and services. However, prior assessments of forest structure across landscapes and ownerships have been limited by a lack of high-fidelity forest structure measurements across a large spatial extent. We addressed three research questions: (1) What distinct classes of forest structure exist across our study area? (2) How does the distribution and pattern of forest structure vary among types of owners at scales of patches, ownership types, and subregion, and is this independent of property size? and (3) What implications do the fine and sub-regional scale patterns have for landscape configuration goals under recent updates to the Northwest Forest Plan? Materials and Methods: We examined forest structure patterns by identifying six statistically distinct classes of forest structure and then examining their distribution across and within ownership types. We used these structure classes to examine their area within each ownership class, mean patch size, and intermixing at multiple scales. Results and Conclusion: We found that the six different forest structure classes in the study area can be interpreted as two assemblages: production-style forests, principally on private lands, and structurally complex forests, principally on public lands. We found that land ownership objectives resulted in distinct landscape patterns of forest structure as measured by mean structure class patch size and intermixing of different structure class patches. Finally, we found that forest structure differed between public and private lands but differed comparatively little among ownership types within those two broad categories.

Increasing concentrations of greenhouse gases (GHGs) are causing global climate change and decreasing the stability of the climate system. Long-term solutions to climate change will require reduction in GHG emissions as well as the removal of large quantities of GHGs from the atmosphere. Natural climate solutions (NCS), i.e., changes in land management, ecosystem restoration, and avoided conversion of habitats, have substantial potential to meet global and national greenhouse gas (GHG) reduction targets and contribute to the global drawdown of GHGs. However, the relative role of NCS to contribute to GHG reduction at subnational scales is not well known. We examined the potential for 12 NCS activities on natural and working lands in Oregon, USA to reduce GHG emissions in the context of the state's climate mitigation goals. We evaluated three alternative scenarios wherein NCS implementation increased across the applicable private or public land base, depending on the activity, and estimated the annual GHG reduction in carbon dioxide equivalents (CO2e) attributable to NCS from 2020 to 2050. We found that NCS within Oregon could contribute annual GHG emission reductions of 2.7 to 8.3 MMT CO2e by 2035 and 2.9 to 9.8 MMT CO2e by 2050. Changes in forest-based activities including deferred timber harvest, riparian reforestation, and replanting after wildfires contributed most to potential GHG reductions (76 to 94% of the overall annual reductions), followed by changes to agricultural management through no-till, cover crops, and nitrogen management (3 to 15% of overall annual reductions). GHG reduction benefits are relatively high per unit area for avoided conversion of forests (125-400 MT CO2e ha-1). However, the existing land use policy in Oregon limits the current geographic extent of active conversion of natural lands and thus, avoided conversions results in modest overall potential GHG reduction benefits (i.e., less than 5% of the overall annual reductions). Tidal wetland restoration, which has high per unit area carbon sequestration benefits (8.8 MT CO2e ha-1 yr-1), also has limited possible geographic extent resulting in low potential (< 1%) of state-level GHG reduction contributions. However, co-benefits such as improved habitat and water quality delivered by restoration NCS pathways are substantial. Ultimately, reducing GHG emissions and increasing carbon sequestration to combat climate change will require actions across multiple sectors. We demonstrate that the adoption of alternative land management practices on working lands and avoided conversion and restoration of native habitats can achieve meaningful state-level GHG reductions.

Western U.S. wildfire area burned has increased dramatically over the last half‐century. How contemporary extent and severity of wildfires compare to the pre‐settlement patterns to which ecosystems are adapted is debated. We compared large wildfires in Pacific Northwest forests from 1984 to 2015 to modeled historic fire regimes. Despite late twentieth‐century increases in area burned, we show that Pacific Northwest forests have experienced an order of magnitude less fire over 32 yr than expected under historic fire regimes. Within fires that have burned, severity distributions are disconnected from historical references. From 1984 to 2015, 1.6 M ha burned; this is 13.3–18.9 M ha less than expected. Deficits were greatest in dry forest ecosystems adapted to frequent, low‐severity fire, where 7.2–10.3 M ha of low‐severity fire was missing, compared to a 0.2–1.1 M ha deficit of high‐severity fire. When these dry forests do burn, we observed that 36% burned with high‐severity compared to 6–9% historically. We found smaller fire deficits, 0.3–0.6 M ha, within forest ecosystems adapted to infrequent, high‐severity fire. However, we also acknowledge inherent limitations in evaluating contemporary fire regimes in ecosystems which historically burned infrequently and for which fires were highly episodic. The magnitude of contemporary fire deficits and disconnect in burn severity compared to historic fire regimes have important implications for climate change adaptation. Within forests characterized by low‐ and mixed‐severity historic fire regimes, simply increasing wildfire extent while maintaining current trends in burn severity threatens ecosystem resilience and will potentially drive undesirable ecosystem transformations. Restoring natural fire regimes requires management that facilitates much more low‐ and moderate‐severity fire.

Ecological departure, or how much landscapes have changed from a natural range of variation (NRV), has become a key metric in forest planning and restoration efforts. In this study we define forest restoration need as the specific change in structural stage abundance necessary to move landscapes into the NRV. While most restoration projects in the forested ecosystems of the Pacific Northwest, USA (Oregon and Washington) have embraced this paradigm, our understanding of what treatments to apply where, when, and at what magnitude is evolving and continues to be refined. We build on a body of existing LANDFIRE/Fire Regime Condition Class (FRCC) work on ecological departure to assess the ecological departure of all forested landscapes in the region. Moreover, we assess departure in moister forests west of the Cascade crest, and compare them with fire-dependent forests east of the crest and in southwest Oregon. These "moister Westside" forests have received relatively less attention in a fire ecology context, and we hypothesize restoration needs there are quite different. We show a substantial need for disturbance-related treatments in the drier fire-dependent portion of this region (east of the Cascade crest plus southwest Oregon), with over half of this treatment type falling on Federally-administered land. On the Westside the need for succession is more pronounced. The lack of pronounced disturbance need west of the Cascade crest suggests restoration there may require strategies more nuanced than in the fire-dependent zone.

Globally, environmental disasters impact billions of people and cost trillions of dollars in damage, and their impacts are often felt most acutely by minority and poor communities. Wildfires in the U.S. have similarly outsized impacts on vulnerable communities, though the ethnic and geographic distribution of those communities may be different than for other hazards. Here, we develop a social-ecological approach for characterizing fire vulnerability and apply it to >70,000 census tracts across the United States. Our approach incorporates both the wildfire potential of a landscape and socioeconomic attributes of overlying communities. We find that over 29 million Americans live with significant potential for extreme wildfires, a majority of whom are white and socioeconomically secure. Within this segment, however, are 12 million socially vulnerable Americans for whom a wildfire event could be devastating. Additionally, wildfire vulnerability is spread unequally across race and ethnicity, with census tracts that were majority Black, Hispanic or Native American experiencing ca. 50% greater vulnerability to wildfire compared to other census tracts. Embracing a social-ecological perspective of fire-prone landscapes allows for the identification of areas that are poorly equipped to respond to wildfires.

As approaches to ecological restoration become increasingly large scale and collaborative, there is a need to better understand social aspects of restoration and how they influence land management. In this article, we examine social perspectives that influence the determination of ecological reference conditions in restoration. Our analysis is based on in‐depth interviews with diverse stakeholders involved in collaborative restoration of fire‐adapted forest landscapes. We conducted interviews with 86 respondents from six forest collaboratives that are part of the U.S. Forest Service's Collaborative Forest Landscape Restoration Program. Collaboratives use a variety of approaches to develop reference conditions, including historic, contemporary, and future scenarios. Historical conditions prior to European settlement (nineteenth century or “pre‐settlement” conditions), or prior to more recent grazing, logging, and exclusion of fire, were the predominant type of reference used in all sites. Stakeholders described benefits and limitations of reference conditions. Primary benefits include (1) providing a science‐based framework for bringing stakeholders together around a common vision; (2) gaining social understanding and acceptance of the underlying need for restoration; and (3) serving to neutralize otherwise value‐laden discussions about multiple, sometimes competing, resource objectives. Limitations stem from (1) concerns over social conflict when reference conditions are perceived to contradict other stakeholder values and interests, (2) differing interpretations of reference condition science, (3) inappropriate application or over‐generalization of reference information, and (4) limited relevance of historical references for current and future conditions in some ecosystems. At the same time, collaboratives are adopting innovative strategies to address conceptual and methodological limitations of reference conditions.

Ecological restoration has become an overarching management paradigm for sustaining the health and resilience of forests across western North America. Restoration often involves mechanical thinning to promote development of complex habitats in moist, productive forests and mechanical thinning with prescribed fire to reduce fuels and restore natural disturbance regimes in dry, fire prone forests. This systematic review quantified the impact of restoration treatments on forest ecosystem carbon (C) stocks and identified factors that moderate treatment effects across spatial and temporal scales. Our review process identified 73 studies to be included for analysis, from which we calculated 482 estimates of treatment effect size. We found that restoration treatments significantly reduce C. Prescribed fire had larger impacts on belowground than aboveground carbon pools, while thinning and combined treatments had larger impacts on aboveground pools. The available literature is highly skewed toward shorter timescales (<25 years after treatment), small spatial scales, and is geographically concentrated: 41% of estimated effect sizes came from studies in the Sierra Nevada. Thinning had similar effects on forest carbon in dry forests and moist forests. The relative magnitude of total C losses was significantly less from simulation than empirical studies, although simulations also mostly evaluated long-term impacts (>75 years after treatment) while empirical studies mostly looked at short term (<25 year) effects. Post-treatment wildfire significantly reduced the percentage of carbon lost relative to controls in the aboveground pool. Long-term, treated stands only recovered to control levels of carbon when wildfire was present. Returns on the carbon debt imposed by thinning and prescribed fire depend on the nuances of the treatments themselves but may also depend upon treatment intensity and the frequency and intensity of future wildfire. Ecological restoration in forests across the western US has to carefully balance the budget of ecosystem carbon with competing objectives such as improved wildlife habitat, reduced risk of severe wildfire, and other ecosystem services.

Collaborative approaches to natural resource management are becoming increasingly common on public lands. Negotiating a shared vision for desired conditions is a fundamental task of collaboration and serves as a foundation for developing management objectives and monitoring strategies. We explore the complex socio-ecological processes involved in developing a shared vision for collaborative restoration of fire-adapted forest landscapes. To understand participant perspectives and experiences, we analyzed interviews with 86 respondents from six collaboratives in the western U.S., part of the Collaborative Forest Landscape Restoration Program established to encourage collaborative, science-based restoration on U.S. Forest Service lands. Although forest landscapes and group characteristics vary considerably, collaboratives faced common challenges to developing a shared vision for desired conditions. Three broad categories of challenges emerged: meeting multiple objectives, collaborative capacity and trust, and integrating ecological science and social values in decision-making. Collaborative groups also used common strategies to address these challenges, including some that addressed multiple challenges. These included use of issue-based recommendations, field visits, and landscape-level analysis; obtaining support from local agency leadership, engaging facilitators, and working in smaller groups (sub-groups); and science engagement. Increased understanding of the challenges to, and strategies for, developing a shared vision of desired conditions is critical if other collaboratives are to learn from these efforts.