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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.

Large, severe wildfires continue to burn in frequent-fire adapted forests but the mechanisms that contribute to them and their predictability are important questions. Using a combination of ground based and remotely sensed data we analyzed the behavior and patterns of the 2020 Creek Fire where drought and bark beetles had previously created substantial levels of tree mortality in the southern Sierra Nevada. We found that dead biomass and live tree densities were the most important variables predicting fire severity; high severity fire encompassed 41% of the area and the largest high severity patch (19,592 ha) comprised 13% of total area burned. Areas with the highest amounts of dead biomass and live tree densities were also positively related to high severity fire patch size indicating that larger, more homogenous conditions of this forest characteristic resulted in adverse, landscape-scale fire effects. The first two days of the Creek Fire were abnormally hot and dry but weather during the days of the greatest fire growth was largely within the normal range of variation for that time of year with one day with lower windspeeds. From September 5 to 8th the fire burned almost 50% of its entire area and fire intensity patterns inferred from remotely sensed brightness-temperature data were typical except on September 6th when heat increased towards the interior of the fire. Not only was the greatest heat concentrated away from the fire perimeter, but a significant amount of heat was still being generated within the fire perimeter from the previous day. This is a classic pattern for a mass fire and the high amount of dead biomass created from the drought and bark beetles along with high live tree densities were critical factors in developing mass fire behavior. Operational fire behavior models were not able to predict this behavior largely because they do not include post-frontal combustion and fire-atmosphere interactions. An important question regarding this mass fire is if the tree mortality event that preceded it could have been avoided or reduced or was it within the natural range of variation for these forests? We found that the mortality episode was outside of historical analogs and was exacerbated by past management decisions. The Creek Fire shows us how vulnerable of our current frequent-fire forest conditions are to suffering high tree mortality and offering fuel conditions capable of generating mass fires from which future forest recovery is questionable because of type conversion and probable reoccurring high severity fire.

Restoration of fire-prone forests can promote resiliency to disturbances, yet such activities may reduce biomass stocks to levels that conflict with climate mitigation goals. Using a set of large-scale historical inventories across the Sierra Nevada/southern Cascade region, we identified underlying climatic and biophysical drivers of historical forest characteristics and projected how restoration of these characteristics manifest under future climate. Historical forest conditions varied with climate and site moisture availability but were generally characterized by low tree density (53 trees ha-1), low live basal area (22 m2 ha-1), low biomass (34 Mg ha-1), and high pine dominance. Our predictions reflected broad convergence in forest structure, frequent fire is the most likely explanation for this convergence. Under projected climate (2040-2069), hotter sites become more prevalent, nearly ubiquitously favoring low tree densities, low biomass, and high pine dominance. Based on these projections, this region may be unable to support aboveground biomass >40 Mg ha-1 by 2069, a value approximately 25% of current average biomass stocks. Ultimately, restoring resilient forests will require adjusting carbon policy to match limited future aboveground carbon stocks in this region.

Responsible stewardship of temperate forests can address key challenges posed by climate change through sequestering carbon, producing low-carbon products, and mitigating climate risks. Forest thinning and fuel reduction can mitigate climate-related risks like catastrophic wildfire. These treatments are often cost prohibitive, though, in part because of low demand for low-value wood "residues." Where treatment occurs, this low-value wood is often burned or left to decay, releasing carbon. In this study, we demonstrate that innovative use of low-value wood, with improved potential revenues and carbon benefits, can support economical, carbon-beneficial forest management outcomes in California. With increased demand for wood residues, forest health-oriented thinning could produce up to 7.3 million (M) oven-dry tonnes of forest residues per year, an eightfold increase over current levels. Increased management and wood use could yield net climate benefits between 6.4 and 16.9 million tonnes of carbon dioxide equivalent (M tCO2e) per year when considering impacts from management, wildfire, carbon storage in products, and displacement of fossil carbon-intensive alternatives over a 40-y period. We find that products with durable carbon storage confer the greatest benefits, as well as products that reduce emissions in hard-to-decarbonize sectors like industrial heat. Concurrently, treatment could reduce wildfire hazard on 4.9 M ha (12.1 M ac), a quarter of which could experience stand-replacing effects without treatment. Our results suggest that innovative wood use can support widespread fire hazard mitigation and reduce net CO2 emissions in California.

A significant expansion of prescribed fire activity will be necessary to mitigate growing wildfire hazard in California forests. Forest managers can facilitate this expansion by promoting forest structures that allow for more effective implementation of prescribed fire, for both initial-entry and repeat burns. We analyzed changes in surface fuel during a series of three burns in replicated mixed-conifer stands following a period of over 100 years of fire suppression and exclusion. Total fuel load, proportion of pine present, canopy cover and basal area of live trees were relevant forest-structure components that influenced plot-scale fuel consumption. The study highlighted the importance of pre-fire fuel load and the relative proportion of pine in the overstory, which both led to greater amounts of fuel consumption. The initial-entry burn dramatically reduced all fuel categories (fine fuel, coarse wood and duff). Following each burn, fuel recovered until the next burn reduced loads enough to maintain low fuel levels. We apply the results to provide an example of how to determine the timing of prescribed fires.

We used Landsat-based measures of annual evapotranspiration (ET) to explore the effects of wildfires on vegetation water use across California’s Sierra Nevada. Wildfires decreased ET relative to unburned and pre-fire controls, in many areas this reduction persisted for at least 15 years. The ET reduction averaged 265 mm yr-1 (36% of pre-fire ET) during the first year after fire, and 169 mm yr-1 (23%) over the first 15 years after fire. The ET reduction varied with burn severity, pre-fire canopy density, and hydro-topographic environment. In areas burned at low severity the ET reduction in the first year after fire averaged 224 mm yr-1 (31% of pre-fire ET) whereas high severity were reduced a 362 mm yr-1 (50% ) for the first year. Forest stands that were denser pre-fire had a larger ET reduction across all burn severities. Evapotranspiration reduction following moderate-to-high-severity burns was greatest at 900-1300 m asl elevation. The combination of pre-fire canopy density and burn severity explained 70% of the spatial variation in first-year ET reduction. Forest restoration and a reintroduction of low-intensity fire have been proposed as management practices to mitigate fire risk and improve ecosystem health. Our findings illustrate that restoration and fire reintroduction may reduce the current total ET by up to 9%, with potential benefits for downstream water supply in a globally important food-producing region.

Strategically placed landscape area treatments (SPLATs) are landscape fuel reduction treatments designed to reduce fire severity across an entire landscape with only a fraction of the landscape treated. Though SPLATs have gained attention in scientific and policy arenas, they have rarely been empirically tested. This study takes advantage of a strategically placed landscape fuel treatment network that was implemented and monitored before being burned by a wildfire. We evaluated treatment efficacy in terms of resistance, defined here as the capacity to withstand disturbance, and recovery, defined here as regeneration following disturbance. We found that the treated landscape experienced lower fire severity than an adjacent control landscape: in the untreated control landscape, 26% of land area was burned with >90% basal area mortality, according to the remote-sensing-derived relative differenced Normalized Burn Ratio (RdNBR), while in the treated landscape only 11% burned at the same severity. This difference was despite greater pre-treatment fire risk in the treatment landscape, as indicated by FARSITE fire behavior modeling. At a more local scale, monitoring plots within the treatments themselves saw greater regeneration of conifer seedlings two years following the fire than plots outside the treatments. Mean seedling densities for all conifer species were 7.8 seedlings m −2 in treated plots and only 1.4 seedlings m −2 in control plots. These results indicate that SPLATs achieved their objective of increasing forest resistance and recovery.

Light detection and ranging (Lidar) data can be used to create wall-to-wall forest structure and fuel products that are required for wildfire behavior simulation models. We know that Lidar-derived forest parameters have a non-negligible error associated with them, yet we do not know how this error influences the results of fire behavior modeling that use these layers as inputs. Here, we evaluated the influence of error associated with two Lidar data products-canopy height (CH) and canopy base height (CBH)-on simulated fire behavior in a case study in the Sierra Nevada, California, USA.We used a Monte Carlo simulation approach with expected randomized error added to each model input. Model 1 used the original, unmodified data, Model 2 incorporated error in the CH layer, and Model 3 incorporated error in the CBH layer. This sensitivity analysis showed that error in CH and CBH did not greatly influence the modeled conditional burn probability, fire size, or fire size distribution. We found that the expected error associated with CH and CBH did not greatly influence modeled results: conditional burn probability, fire size, and fire size distributions were very similar between Model 1 (original data), Model 2 (error added to CH), and Model 3 (error added to CBH). However, the impact of introduced error was more pronounced with CBH than with CH, and at lower canopy heights, the addition of error increased modeled canopy burn probability. Our work suggests that the use of Lidar data, even with its inherent error, can contribute to reliable and robust estimates of modeled forest fire behavior, and forest managers should be confident in using Lidar data products in their fire behavior modeling workflow.

Fire suppression in many dry forest types has left a legacy of dense, homogeneous forests. Such landscapes have high water demands and fuel loads, and when burned can result in catastrophically large fires. These characteristics are undesirable in the face of projected warming and drying in the western US. Alternative forest and fire treatments based on managed wildfireâa regime in which fires are allowed to burn naturally and only suppressed under defined management conditionsâoffer a potential strategy to ameliorate the effects of fire suppression. Understanding the long-term effects of this strategy on vegetation, water, and forest resilience is increasingly important as the use of managed wildfire becomes more widely accepted. The Illilouette Creek Basin in Yosemite National Park has experienced 40 years of managed wildfire, reducing forest cover by 22%, and increasing meadow areas by 200% and shrublands by 24%. Statistical upscaling of 3300 soil moisture observations made since 2013 suggests that large increases in wetness occurred in sites where fire caused transitions from forests to dense meadows. The runoff ratio (ratio of annual runoff to precipitation) from the basin appears to be increasing or stable since 1973, compared to declines in runoff ratio for nearby, unburned watersheds. Managed wildfire appears to increase landscape heterogeneity, and likely improves resilience to disturbances, such as fire and drought, although more detailed analysis of fire effects on basin-scale hydrology is needed.

Background: Since 2010, all non‐VA hospitals performing cardiac surgeries and percutaneous interventions in Washington State have participated in the Cardiac Care Outcomes Assessment Program (COAP), a data‐driven, physician‐led collaborative quality improvement (QI) collaborative. Prior literature has demonstrated QI programs such as COAP can avert avoidable utilization such as hospital readmissions. However, it is unknown whether such improvements translate into economic benefits. Hypothesis: This study compared downstream healthcare costs between patients undergoing cardiac interventions for coronary artery disease (CAD) at hospitals that were and were not participating in COAP. Methods: Post hoc analysis of Medicare administrative and claims data examined 2.5 million randomly selected deidentified beneficiaries receiving a percutaneous coronary intervention or coronary artery bypass grafting between 2013 and 2020. Total costs were defined as all reimbursements paid by Medicare for up to 5 years following cardiac intervention. Because all non‐VA hospitals in Washington State participated in COAP, we compared respective groups of patients receiving intervention in Washington State with all non‐Washington states, adjusting for patient demographics and comorbidity. To model costs, we applied a multipart estimator, which distinguishes the impact of QI program participation due to survival and utilization while accounting for censoring. Results: Total 5‐year downstream costs were $3861 lower (95% confidence interval [CI] = $1794 to $5741) among patients receiving cardiac intervention at COAP‐exposed hospitals. Lower costs were largely driven by lower utilization during calendar quarters where death was not observed. Conclusions: Participation in this state‐wide cardiac quality improvement program was associated with economic benefits in patients receiving intervention for CAD. [ABSTRACT FROM AUTHOR]

Large trees are important to a wide variety of wildlife, including many species of conservation concern, such as the California spotted owl (Strix occidentalis occidentalis). Light detection and ranging (LiDAR) has been successfully utilized to identify the density of large-diameter trees, either by segmenting the LiDAR point cloud into individual trees, or by building regression models between variables extracted from the LiDAR point cloud and field data. Neither of these methods is easily accessible for most land managers due to the reliance on specialized software, and much available LiDAR data are being underutilized due to the steep learning curve required for advanced processing using these programs. This study derived a simple, yet effective method for estimating the density of large-stemmed trees from the LiDAR canopy height model, a standard raster product derived from the LiDAR point cloud that is often delivered with the LiDAR and is easy to process by personnel trained in geographic information systems (GIS). Ground plots needed to be large (1 ha) to build a robust model, but the spatial accuracy of plot center was less crucial to model accuracy. We also showed that predicted large tree density is positively linked to California spotted owl nest sites.

Current U.S. forest fire policy emphasizes short-term outcomes versus long-term goals. This perspective drives managers to focus on the protection of high-valued resources, whether ecosystem-based or developed infrastructure, at the expense of forest resilience. Given these current and future challenges posed by wildland fire and because the U.S. Forest Service spent >50% of its budget on fire suppression in 2015, a review and reexamination of existing policy is warranted. One of the most difficult challenges to revising forest fire policy is that agency organizations and decision making processes are not structured in ways to ensure that fire management is thoroughly considered in management decisions. Current resource-specific policies are so focused on individual concerns that they may be missing the fact that there are “endangered landscapes” that are threatened by changing climate and fire. We propose that forest restoration should be at least equal to other land management priorities because large-scale restoration is necessary for the sake of forest ecosystem integrity now and into the future. Another proposal is to switch the “default” rule in federal planning documents that currently have to “justify” managed wildland fire; instead, U.S. federal agencies should be required to disclose the long-term ecological impacts of continued fire suppression. Proposed legislation that identifies the most expensive 2% of wildfires annually to be funded from emergency funding instead of by the federal land management agencies. If increases in forest restoration fail to accompany the change in how large wildfires are funded, then U.S. fire suppression costs will remain high while resilience will continue to decline. Expansion of the wildland–urban interface will continue to drive suppression costs higher; new federal partnerships with States and local governments are needed to address this problem. Given the legacy of fire suppression and a future of climate change, management for other values in forests will be, in the long run, futile without also managing for long-term forest resilience.

Increasingly, objectives for forests with moderate- or mixed-severity fire regimes are to restore successionally diverse landscapes that are resistant and resilient to current and future stressors. Maintaining native species and characteristic processes requires this successional diversity, but methods to achieve it are poorly explained in the literature. In the Inland Pacific US, large, old, early seral trees were a key historical feature of many young and old forest successional patches, especially where fires frequently occurred. Large, old trees are naturally fire-tolerant, but today are often threatened by dense understory cohorts that create fuel ladders that alter likely post-fire successional pathways. Reducing these understories can contribute to resistance by creating conditions where canopy trees will survive disturbances and climatic stressors; these survivors are important seed sources, soil protectors, and critical habitat elements. Historical timber harvesting has skewed tree size and age class distributions, created hard edges, and altered native patch sizes. Manipulating these altered forests to promote development of larger patches of older, larger, and more widely-spaced trees with diverse understories will increase landscape resistance to severe fires, and enhance wildlife habitat for underrepresented conditions.Closed-canopy, multi-layered patches that develop in hot, dry summer environments are vulnerable to droughts, and they increase landscape vulnerability to insect outbreaks and severe wildfires. These same patches provide habitat for species such as the northern spotted owl, which has benefited from increased habitat area. Regional and local planning will be critical for gauging risks, evaluating trade-offs, and restoring dynamics that can support these and other species. The goal will be to manage for heterogeneous landscapes that include variably-sized patches of (1) young, middle-aged, and old, closed-canopy forests growing in upper montane, northerly aspect, and valley bottom settings, (2) a similar diversity of open-canopy, fire-tolerant patches growing on ridgetops, southerly aspects, and lower montane settings, and (3) significant montane chaparral and grassland areas. Tools to achieve this goal include managed wildfire, prescribed burning, and variable density thinning at small to large scales. Specifics on "how much and where?" will vary according to physiographic, topographic and historical templates, and regulatory requirements, and be determined by means of a socio-ecological process.

Accurate vegetation mapping is critical for natural resources management, ecological analysis, and hydrological modeling, among other tasks. Remotely sensed multispectral and hyperspectral imageries have proved to be valuable inputs to the vegetation mapping process, but they can provide only limited vegetation structure characteristics, which are critical for differentiating vegetation communities in compositionally homogeneous forests. Light detection and ranging (LiDAR) can accurately measure the forest vertical and horizontal structures and provide a great opportunity for solving this problem. This study introduces a strategy using both multispectral aerial imagery and LiDAR data to map vegetation composition and structure over large spatial scales. Our approach included the use of a Bayesian information criterion algorithm to determine the optimized number of vegetation groups within mixed conifer forests in two study areas in the Sierra Nevada, California, and an unsupervised classification technique and post hoc analysis to map these vegetation groups across both study areas. The results show that the proposed strategy can recognize four and seven vegetation groups at the two study areas, respectively. Each vegetation group has its unique vegetation structure characteristics or vegetation species composition. The overall accuracy and kappa coefficient of the vegetation mapping results are over 78% and 0.64 for both study sites. Résumé. La cartographie précise de la végétation est essentielle entre autres pour la gestion des ressources naturelles, l’analyse écologique, et la modélisation hydrologique. Les approches d’imagerie multispectrale et hyperspectrale par télédétection se sont avérées de précieuses contributions au processus de la cartographie de la végétation, mais elles ne peuvent fournir qu’un nombre limité de caractéristiques sur la structure de la végétation, qui sont essentielles pour différencier les communautés végétales dans les forêts de composition homogènes. La télédétection par laser «light detection and ranging» (LiDAR) peut mesurer avec précision les structures verticales et horizontales de la forêt, et fournit une formidable opportunité de résoudre ce problème. Cette étude présente une stratégie qui utilise à la fois l’imagerie multispectrale aérienne et des données LiDAR pour cartographier la composition et la structure de la végétation à grandes échelles spatiales. Notre approche comprenait l’utilisation d’un algorithme du critère d’information Bayésien pour déterminer le nombre optimal de groupes de végétation dans les forêts mixtes de conifères sur deux zones d’étude dans les Sierra Nevada, en Californie, ainsi qu’une technique de classification non supervisée et une analyse post hoc pour cartographier ces groupes de végétation dans les deux zones d’étude. Les résultats montrent que la stratégie proposée peut reconnaitre quatre et sept groupes de végétation dans les deux zones d’étude respectivement. Chaque groupe de végétation a des caractéristiques uniques de structure de la végétation ou de composition des espèces de la végétation. La précision globale et le coefficient kappa des résultats de la cartographie de la végétation sont de plus de 78% et 0,64 pour les deux sites d’étude.

Forest ecosystems can act as sinks of carbon and thus mitigate anthropogenic carbon emissions. When forests are actively managed, treatments can alter forests carbon dynamics, reducing their sink strength and switching them from sinks to sources of carbon. These effects are generally characterized by fast temporal dynamics. Hence this study monitored for over a decade the impacts of management practices commonly used to reduce fire hazards on the carbon dynamics of mixed-conifer forests in the Sierra Nevada, California, USA. Soil CO2 efflux, carbon pools (i.e. soil carbon, litter, fine roots, tree biomass), and radial tree growth were compared among un-manipulated controls, prescribed fire, thinning, thinning followed by fire, and two clear-cut harvested sites. Soil CO2 efflux was reduced by both fire and harvesting (ca. 15%). Soil carbon content (upper 15 cm) was not significantly changed by harvest or fire treatments. Fine root biomass was reduced by clear-cut harvest (60-70%) but not by fire, and the litter layer was reduced 80% by clear-cut harvest and 40% by fire. Thinning effects on tree growth and biomass were concentrated in the first year after treatments, whereas fire effects persisted over the seven-year post-treatment period. Over this period, tree radial growth was increased (25%) by thinning and reduced (12%) by fire. After seven years, tree biomass returned to pre-treatment levels in both fire and thinning treatments; however, biomass and productivity decreased 30%-40% compared to controls when thinning was combined with fire. The clear-cut treatment had the strongest impact, reducing ecosystem carbon stocks and delaying the capacity for carbon uptake. We conclude that post-treatment carbon dynamics and ecosystem recovery time varied with intensity and type of treatments. Consequently, management practices can be selected to minimize ecosystem carbon losses while increasing future carbon uptake, resilience to high severity fire, and climate related stresses.

Fuels-reduction treatments are commonly implemented in the western U.S. to reduce the risk of high-severity fire, but they may have negative short-term impacts on species associated with older forests. Therefore, we modeled the effects of a completed fuels-reduction project on fire behavior and California Spotted Owl (Strix occidentalis occidentalis) habitat and demography in the Sierra Nevada to assess the potential short- and long-term trade-offs. We combined field-collected vegetation data and LiDAR data to develop detailed maps of forest structure needed to parameterize our fire and forest-growth models. We simulated wildfires under extreme weather conditions (both with and without fuels treatments), then simulated forest growth 30 years into the future under four combinations of treatment and fire: treated with fire, untreated with fire, treated without fire, and untreated without fire. We compared spotted owl habitat and population parameters under the four scenarios using a habitat suitability index developed from canopy cover and large-tree measurements at nest sites and from previously derived statistical relationships between forest structure and fitness (λ) and equilibrium occupancy at the territory scale. Treatments had a positive effect on owl nesting habitat and demographic rates up to 30 years after simulated fire, but they had a persistently negative effect throughout the 30-year period in the absence of fire. We conclude that fuels-reduction treatments in the Sierra Nevada may provide long-term benefits to spotted owls if fire occurs under extreme weather conditions, but can have long-term negative effects on owls if fire does not occur. However, we only simulated one fire under the treated and untreated scenarios and therefore had no measures of variation and uncertainty. In addition, the net benefits of fuels treatments on spotted owl habitat and demography depends on the future probability that fire will occur under similar weather and ignition conditions, and such probabilities remain difficult to quantify. Therefore, we recommend a landscape approach that restricts timber harvest within territory core areas of use (∼125 ha in size) that contain critical owl nesting and roosting habitat and locates fuels treatments in the surrounding areas to reduce the potential for high-severity fire in territory core areas.

The balance between ecosystem emissions of carbon to the atmosphere and removals from the atmosphere indicates whether ecosystems are exacerbating or reducing climate change. Forest ecosystems in the State of California, USA, contain carbon that reaches the highest densities (mass per unit area) in the world, but it has been unresolved whether California ecosystems currently comprise a net sink or source of carbon. The California Global Warming Solutions Act of 2006 established greenhouse gas reduction targets for fossil fuel-burning sectors and ecosystems, underscoring the importance of tracking ecosystem carbon. Here, we conduct statewide spatial inventories of the aboveground live carbon stocks of forests and other terrestrial ecosystems of California, excluding agricultural and urban areas. We analyzed biomass data from field measurements of the Forest Inventory and Analysis program, published biomass information and remote sensing data on non-forest vegetation, and spatial distributions of vegetation types, height, and fractional cover derived by the Landfire program from Landsat remote sensing at 30m spatial resolution. We conducted Monte Carlo analyses of the uncertainty of carbon stock change estimates from errors in tree biomass estimates, remote sensing, and estimates of the carbon fraction of biomass. The carbon stock in aboveground biomass was 850±230 Tg (mean±95% confidence interval) in 2010. We found a net aboveground live carbon stock change of −69±15 Tg from 2001 to 2010, a rate of change of −0.8±0.2%y−1. Due to slow decay of some dead wood, all of the live carbon stock change does not immediately generate emissions. Wildfires on 6% of the state analysis area produced two-thirds of the live carbon stock loss. This suggests that increased tree densities from a century of fire suppression have allowed the accumulation of fuel for carbon losses in recent wildfires. Remote sensing errors in vegetation classification accounted for most of the uncertainty in the carbon stock change estimates. Improvements are also needed to track spatial patterns of growth and dead wood. Our results establish the beginning of a time series for the state greenhouse gas inventory and provide information on the role of forest conservation and management in California in mitigating global climate change.

We analyzed historical timber inventory data collected systematically across a large mixed-conifer-dominated landscape to gain insight into the interaction between disturbances and vegetation structure and composition prior to 20th century land management practices. Using records from over 20 000 trees, we quantified historical vegetation structure and composition for nine distinct vegetation groups. Our findings highlight some key aspects of forest structure under an intact disturbance regime: (1) forests were low density, with mean live basal area and tree density ranging from 8-30 m2 /ha and 25-79 trees/ha, respectively; (2) understory and overstory structure and composition varied considerably across the landscape; and (3) elevational gradients largely explained variability in forest structure over the landscape. Furthermore, the presence of large trees across most of the surveyed area suggests that extensive stand-replacing disturbances were rare in these forests. The vegetation structure and composition characteristics we quantified, along with evidence of largely elevational control on these characteristics, can provide guidance for restoration efforts in similar forests.

Many managers today are tasked with restoring forests to mitigate the potential for uncharacteristically severe fire. One challenge to this mandate is the lack of large-scale reference information on forest structure prior to impacts from Euro-American settlement. We used a robust 1911 historical dataset that covers a large geographic extent (>10,000 ha) and has unbiased sampling locations to compare past and current forest conditions for ponderosa pine and mixed conifer forests in the southern Sierra Nevada. The 1911 dataset contained records from 18,052 trees in 378 sampled transects, totaling just over 300 ha in transect area. Forest structure was highly variable in 1911 and shrubs were found in 54% of transects. Total tree basal area ranged from 1 to 60 m2 ha-1 and tree density from 2 to 170 ha-1 (based on trees >30 cm dbh). K-means cluster analysis divided transects into four groups: mixed conifer-high basal area (MC High BA), mixed conifer-average basal area (MC Ave BA), mixed conifer-average basal area-high shrubs (MC Ave BA Shrubs), and ponderosa pine (Pond Pine). The percentage of this 1911 landscape that experienced high severity fire was low and varied from 1-3% in mixed conifer forests and 4-6% in ponderosa pine forests. Comparing forest inventory data from 1911 to the present indicates that current forests have changed drastically, particularly in tree density, canopy cover, the density of large trees, dominance of white fir in mixed conifer forests, and the similarity of tree basal area in contemporary ponderosa pine and mixed conifer forests. Average forest canopy cover increased from 25-49% in mixed conifer forests, and from 12-49% in ponderosa pine forests from 1911 to the present; canopy cover in current forest types is similar but in 1911 mixed conifer forests had twice the canopy cover as ponderosa pine forests. Current forest restoration goals in the southern Sierra Nevada are often skewed toward the higher range of these historical values, which will limit the effectiveness of these treatments if the objective is to produce resilient forest ecosystems into the future.

We investigated the relationship between LiDAR and ladder fuels in the northern Sierra Nevada, California USA. Ladder fuels are often targeted in hazardous fuel reduction treatments due to their role in propagating fire from the forest floor to tree crowns. Despite their importance, ladder fuels are difficult to quantify. One common approach is to calculate canopy base height, but this has many potential sources of error. LiDAR may be a way forward to better characterize ladder fuels, but has only been used to address this question peripherally and in only a few instances. After establishing that landscape fuel treatments reduced canopy and ladder fuels at our site, we tested which LiDAR-derived metrics best differentiated treated from untreated areas. The percent cover between 2 and 4 m had the most explanatory power to distinguish treated from untreated pixels across a range of spatial scales. When compared to independent plot-based measures of ladder fuel classes, this metric differentiated between high and low levels of ladder fuels. These findings point to several immediate applications for land managers and suggest new avenues of study that could lead to possible improvements in the way that we model wildfire behavior across forested landscapes in the US.

Inventories of greenhouse gas (GHG) emissions from wildfire provide essential information to the state of California, USA, and other governments that have enacted emission reductions. Wildfires can release a substantial amount of GHGs and other compounds to the atmosphere, so recent increases in fire activity may be increasing GHG emissions. Quantifying wildfire emissions however can be difficult due to inherent variability in fuel loads and consumption and a lack of field data of fuel consumption by wildfire. We compare a unique set of fuel data collected immediately before and after six wildfires in coniferous forests of California to fuel consumption predictions of the first-order fire effects model (FOFEM), based on two different available fuel characterizations. We found strong regional differences in the performance of different fuel characterizations, with FOFEM overestimating the fuel consumption to a greater extent in the Klamath Mountains than in the Sierra Nevada. Inaccurate fuel load inputs caused the largest differences between predicted and observed fuel consumption. Fuel classifications tended to overestimate duff load and underestimate litter load, leading to differences in predicted emissions for some pollutants. When considering total ground and surface fuels, modeled consumption was fairly accurate on average, although the range of error in estimates of plot level consumption was very large. These results highlight the importance of fuel load input to the accuracy of modeled fuel consumption and GHG emissions from wildfires in coniferous forests. ©2014. American Geophysical Union. All Rights Reserved.

In Mediterranean environments in western North America, historic fire regimes in frequent-fire conifer forests are highly variable both temporally and spatially. This complexity influenced forest structure and spatial patterns, but some of this diversity has been lost due to anthropogenic disruption of ecosystem processes, including fire. Information from reference forest sites can help management efforts to restore forests conditions that may be more resilient to future changes in disturbance regimes and climate. In this study, we characterize tree spatial patterns using four-ha stem maps from four old-growth, Jeffrey pine-mixed conifer forests, two with active-fire regimes in northwestern Mexico and two that experienced fire exclusion in the southern Sierra Nevada. Most of the trees were in patches, averaging six to 11 trees per patch at 0.007 to 0.014 ha−1, and occupied 27–46% of the study areas. Average canopy gap sizes (0.04 ha) covering 11–20% of the area were not significantly different among sites. The putative main effects of fire exclusion were higher densities of single trees in smaller size classes, larger proportion of trees (≥56%) in large patches (≥10 trees), and decreases in spatial complexity. While a homogenization of forest structure has been a typical result from fire exclusion, some similarities in patch, single tree, and gap attributes were maintained at these sites. These within-stand descriptions provide spatially relevant benchmarks from which to manage for structural heterogeneity in frequent-fire forest types.

Many US forest managers have used historical ecology information to assist in the development of desired conditions. While there are many important lessons to learn from the past, we believe that we cannot rely on past forest conditions to provide us with blueprints for future management. To respond to this uncertainty, managers will be challenged to integrate adaptation strategies into plans in response to changing climates. Adaptive strategies include resistance options, resilience options, response options, and realignment options. Our objectives are to present ideas that could be useful in developing plans under changing climates that could be applicable to forests with Mediterranean climates. We believe that managing for species persistence at the broad ecoregion scale is the most appropriate goal when considering the effects of changing climates. Such a goal relaxes expectations that current species ranges will remain constant, or that population abundances, distribution, species compositions and dominances should remain stable. Allowing fundamental ecosystem processes to operate within forested landscapes will be critical. Management and political institutions will have to acknowledge and embrace uncertainty in the future since we are moving into a time period with few analogs and inevitably, there will be surprises.