We review science-based adaptation strategies for western North American (wNA) forests that include restoring active fire regimes and fostering resilient structure and composition of forested ...landscapes. As part of the review, we address common questions associated with climate adaptation and realignment treatments that run counter to a broad consensus in the literature. These include the following: (1) Are the effects of fire exclusion overstated? If so, are treatments unwarranted and even counterproductive? (2) Is forest thinning alone sufficient to mitigate wildfire hazard? (3) Can forest thinning and prescribed burning solve the problem? (4) Should active forest management, including forest thinning, be concentrated in the wildland urban interface (WUI)? (5) Can wildfires on their own do the work of fuel treatments? (6) Is the primary objective of fuel reduction treatments to assist in future firefighting response and containment? (7) Do fuel treatments work under extreme fire weather? (8) Is the scale of the problem too great? Can we ever catch up? (9) Will planting more trees mitigate climate change in wNA forests? And (10) is post-fire management needed or even ecologically justified? Based on our review of the scientific evidence, a range of proactive management actions are justified and necessary to keep pace with changing climatic and wildfire regimes and declining forest heterogeneity after severe wildfires. Science-based adaptation options include the use of managed wildfire, prescribed burning, and coupled mechanical thinning and prescribed burning as is consistent with land management allocations and forest conditions. Although some current models of fire management in wNA are averse to short-term risks and uncertainties, the long-term environmental, social, and cultural consequences of wildfire management primarily grounded in fire suppression are well documented, highlighting an urgency to invest in intentional forest management and restoration of active fire regimes.
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BFBNIB, FZAB, GIS, IJS, INZLJ, KILJ, NLZOH, NMLJ, NUK, OILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK, ZRSKP
► We quantified stand-level pattern in terms of individual trees, clumps, and openings. ► We used AET and Deficit to develop climate analog reference conditions. ► We developed a method to translate ...reference patterns into prescription guidelines. ► Our ICO method created patterns in agreement with reference conditions. ► Reference spatial patterns offer a proven resilience strategy.
Stand-level spatial pattern influences key aspects of resilience and ecosystem function such as disturbance behavior, regeneration, snow retention, and habitat quality in frequent-fire pine and mixed-conifer forests. Reference sites, from both pre-settlement era reconstructions and contemporary forests with active fire regimes, indicate that frequent-fire forests are complex mosaics of individual trees, tree clumps, and openings. There is a broad scientific consensus that restoration treatments should seek to restore this mosaic pattern in order to restore resilience and maintain ecosystem function. Yet, methods to explicitly incorporate spatial reference information into restoration treatments are not widely used. In addition, targets from reference conditions must be critically evaluated in light of climate change. We used a spatial clump identification algorithm to quantify reference patterns based on a specified inter-tree distance that defines when trees form clumps. We used climatic water balance parameters, downscaled climate projections, and plant associations to assess our historical reference sites in the context of projected future climate and identify climate analog reference conditions. Spatial reference information was incorporated into a novel approach to prescription development, tree marking, and monitoring based on viewing stand structure and pattern in terms of individuals, clumps, and openings (ICO) in a mixed-conifer forest restoration case study. We compared the results from the ICO approach with simulations of traditional basal area and spacing-based thinning prescriptions in terms of agreement with reference conditions and functional aspects of resilience. The ICO method resulted in a distribution of tree clumps and openings within the range of reference patterns, while the basal area and spacing approaches resulted in uniform patterns inconsistent with known reference conditions. Susceptibility to insect mortality was lower in basal area and spacing prescriptions, but openings and corresponding opportunities for regeneration and in situ climate adaptation were fewer. Operationally, the method struck a balance between providing clear targets for spatial pattern directly linked to reference conditions, sufficient flexibility to achieve other restoration objectives, and implementation efficiency. The need to track pattern targets during implementation and provide immediate feedback to marking crews was a key lesson. The ICO method, especially when used in combination with climate analog reference targets, offers a practical approach to restoring spatial patterns that are likely to enhance resilience and climate adaptation.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Abstract
For over 20 years, forest fuel reduction has been the dominant management action in western US forests. These same actions have also been associated with the restoration of highly altered ...frequent-fire forests. Perhaps the vital element in the compatibility of these treatments is that both need to incorporate the salient characteristics that frequent fire produced—variability in vegetation structure and composition across landscapes and the inability to support large patches of high-severity fire. These characteristics can be achieved with both fire and mechanical treatments. The possible key to convergence of fuel reduction and forest restoration strategies is integrated planning that permits treatment design flexibility and a longer-term focus on fire reintroduction for maintenance. With changing climate conditions, long-term forest conservation will probably need to be focused on keeping tree density low enough (i.e., in the lower range of historic variation) for forest conditions to adapt to emerging disturbance patterns and novel ecological processes.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Background
In explaining and predicting spatial vegetation patterns, ecologists have increasingly favoured the use of climatic water balance variables, including actual evapotranspiration (AET) and ...climatic water deficit (CWD), for representing the hydrologic and energetic environment experienced by plants. Much of the interest in these variables lies in their hypothesized potential to characterize biologically relevant environmental variation more directly than simple climate variables, such as precipitation and temperature. Practically, obtaining AET and CWD values across space requires hydrologic process models that involve assumptions, including assumptions about vegetation transpiration rates. However, transpiration parameter values are rarely known with precision and can vary several‐fold within and among vegetation types.
Approach
We evaluate the extent to which assumptions about vegetation physiology in water balance models affect (a) relative spatial variation in modelled water balance values and (b) ecological inferences that are derived from analyses using water balance variables. We demonstrate an approach for identifying inferences that are robust to these assumptions.
Results
Assumptions about vegetation physiology can substantially affect relative spatial variation in modelled water balance values. More importantly, such assumptions can also substantially affect the inferences (e.g., expected vegetation distributions) drawn from ecological analyses that use water balance variables as predictors. Water balance variables are less sensitive to assumptions in environmental settings with abundant water supply, where AET variation is driven primarily by available energy (e.g., temperature and insolation), but they can be highly sensitive to assumptions in drier environments.
Conclusion
Because of their sensitivity to assumptions, water balance variables are not unambiguously superior to simpler climatic and topographic variables, such as precipitation and temperature. However, they retain some advantages, primarily related to their mechanistic incorporation of interactions between water and energy, which may support their use in applications where sensitivity to hydrologic modelling assumptions is low or of minor concern.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
This paper presents a prototype Carbon Monitoring System (CMS) developed to produce regionally unbiased annual estimates of aboveground biomass (AGB). Our CMS employed a bottom-up, two-step modeling ...strategy beginning with a spatially and temporally biased sample: project datasets collected and contributed by US Forest Service (USFS) and other forestry stakeholders in 29 different project areas in the northwestern USA. Plot-level AGB estimates collected in the project areas served as the response variable for predicting AGB primarily from lidar metrics of canopy height and density (R2 = 0.8, RMSE = 115 Mg ha−1, Bias = 2 Mg ha−1). This landscape model was used to map AGB estimates at 30 m resolution where lidar data were available. A stratified random sample of AGB pixels from these landscape-level AGB maps then served as training data for predicting AGB regionally from Landsat image time series variables processed through LandTrendr. In addition, climate metrics calculated from downscaled 30 year climate normals were considered as predictors in both models, as were topographic metrics calculated from elevation data; these environmental predictors allowed AGB estimation over the full range of observations with the regional model (R2 = 0.8, RMSE = 152 Mg ha−1, Bias = 9 Mg ha−1), including higher AGB values (>400 Mg ha−1) where spectral predictors alone saturate. For both the landscape and regional models, the machine-learning algorithm Random Forests (RF) was consistently applied to select predictor variables and estimate AGB. We then calibrated the regional AGB maps using field plot data systematically collected without bias by the national Forest Inventory and Analysis (FIA) Program. We found both our project landscape and regional, annual AGB estimates to be unbiased with respect to FIA estimates (Biases of 1% and 0.7%, respectively) and conclude that they are well suited to inform forest management and planning decisions by our contributing stakeholders. Social media abstract Lidar-based biomass estimates can be upscaled with Landsat data to regionally unbiased annual maps.
•Mixed severity fire regime forests have been strongly impacted by a century of management.•Current climate change and wildfire impacts are entwined with past management.•We review decades of applied ...research that is relevant to restoring these forests.•We recommend nine strategies that emerge from that research.•We discuss their usefulness as a framework for conservation and restorative management.
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.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Abstract
LiDAR individual tree detection (ITD) is a promising tool for measuring forests at a scale that is meaningful ecologically and useful for forest managers. However, most ITD research ...evaluates methods over small homogeneous areas, while many forest managers work over large, complex landscapes. We investigated how ITD results varied across diverse structural conditions in California’s Sierra Nevada mixed-conifer forests and what this taught us about when and how to apply ITD. Our results suggest that it is advantageous to use ITD when it improves analysis interpretability, when measuring horizontal patterns, or when field data are unavailable. In the latter case, it is best to focus on measures dominated by large trees, like basal area and biomass. Thinking of ITD results as “tree-approximate objects” including one dominant tree and up to a few subordinate tree respects LiDAR’s strengths and limitations; we illustrate how this concept keeps analyses consistent across varying structural conditions.
•Examined importance of controls on mixed-severity burn patterns.•Biophysical environment and fire history best explained burn severity patterns.•Spatial autocorrelation important factor when ...modeling burn severity patterns.•Pre-fire airborne LiDAR measurements of forest structure did not improve results.•Methods provide means to estimate likely burn severity patterns across landscapes.
Recent and projected increases in the frequency and severity of large wildfires in the western U.S. makes understanding the factors that strongly affect landscape fire patterns a management priority for optimizing treatment location. We compared the influence of variations in the local environment on burn severity patterns on the large 2013 Rim fire that burned under extreme drought with those of previous smaller fires for a study area in the Sierra Nevada, California, USA. Although much of the Rim fire burned during plume-dominated conditions resulting in large high-severity patches, our study area burned under milder fire weather resulting in a mix of fire severities. In our study area the Rim fire produced a higher proportion of moderate- and high-severity effects than occurred in previous fires. Random forest modeling explained up to 63% of the Rim fire burn variance using seven predictors: time since previous fire, actual evapotranspiration (AET), climatic water deficit (Deficit), previous maximum burn severity, burning index, slope position, and solar radiation. Models using only a subset of biophysical predictors (AET, Deficit, slope position and steepness, and solar radiation) explained 55% of the Rim fire and 58% of the maximum fire burn severity of previous fires. The relationship of burn severity to patterns of AET, however, reversed for the Rim fire (positive) compared to earlier fires (negative). Measurements of pre-Rim fire forest structure from LiDAR did not improve our ability to explain burn severity patterns. We found that accounting for spatial autocorrelation in burn severity and biophysical environment was important to model quality and stability. Our results suggest water balance and topography can help predict likely burn severity patterns under moderate climate and fire weather conditions, providing managers with general guidance for prioritizing fuel treatments and identifying where fire is less likely to burn with higher severities even for locations with higher forest density and canopy cover.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
CONTEXT: More than a century of forest and fire management of Inland Pacific landscapes has transformed their successional and disturbance dynamics. Regional connectivity of many terrestrial and ...aquatic habitats is fragmented, flows of some ecological and physical processes have been altered in space and time, and the frequency, size and intensity of many disturbances that configure these habitats have been altered. Current efforts to address these impacts yield a small footprint in comparison to wildfires and insect outbreaks. Moreover, many current projects emphasize thinning and fuels reduction within individual forest stands, while overlooking large-scale habitat connectivity and disturbance flow issues. METHODS: We provide a framework for landscape restoration, offering seven principles. We discuss their implication for management, and illustrate their application with examples. RESULTS: Historical forests were spatially heterogeneous at multiple scales. Heterogeneity was the result of variability and interactions among native ecological patterns and processes, including successional and disturbance processes regulated by climatic and topographic drivers. Native flora and fauna were adapted to these conditions, which conferred a measure of resilience to variability in climate and recurrent contagious disturbances. CONCLUSIONS: To restore key characteristics of this resilience to current landscapes, planning and management are needed at ecoregion, local landscape, successional patch, and tree neighborhood scales. Restoration that works effectively across ownerships and allocations will require active thinking about landscapes as socio-ecological systems that provide services to people within the finite capacities of ecosystems. We focus attention on landscape-level prescriptions as foundational to restoration planning and execution.
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EMUNI, GEOZS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UL, UM, UPUK, VKSCE, ZAGLJ
•Examined effects of the mountainous environmental mosaic in Yosemite, USA.•Examined environment effects on fire number, burn severity, and forest structure.•Environmental mosaic predicted majority ...of fire and forest structure pattern.•Forest structure continued to vary with environmental conditions following fire.•Site water balance explained most of variation in fire and structure.
Mountainous topography creates fine-scale environmental mosaics that vary in precipitation, temperature, insolation, and slope position. This mosaic in turn influences fuel accumulation and moisture and forest structure. We studied these the effects of varying environmental conditions across a 27,104ha landscape within Yosemite National Park, California, USA, on the number of fires and burn severity (measured from Landsat data for 1984–2010) and on canopy cover at two heights (>2m and 2–8m) and dominant tree height (measured with airborne LiDAR data). We used site water balance (actual evapotranspiration and climatic water deficit) and topography (slope position, slope, and insolation) as environmental predictors. Random forest modeling showed that environmental conditions predicted substantial portions of the variations in fire and forest structure: e.g., 85–93% of the variation in whether a location did not burn, burned once, or burned twice; 64% of the variation in the burn severity; and 72% of the variation in canopy cover >2m for unburned forests, 64% for once-burned forests, and 59% for twice-burned forests. Environmental conditions also predicted a substantial portion of forest structure following one and two fires, even though the post-fire forest structures were substantially different than pre-fire structures. This suggests a feedback mechanism in which local fire regimes and pre-fire forest structures are related to local environments, and their interaction produces post-fire structures also related to local environments. Among environmental predictors, water balance had the greatest explanatory power, followed by slope position, and then by slope and insolation. Managers could use our methods to help select reference areas that match environmental conditions, identify areas at risk for fires that endanger critical habitat or other resources, and identify climate analog areas to help anticipate and plan for climate change.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
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