Restoration and fuel hazard reduction result in equivalent reductions in crown fire behavior in dry conifer forests

Over the past several decades, the management of historically frequent-fire forests in the western United States has received significant attention due to the linked ecological and social risks posed by the increased occurrence of large, contiguous patches of high-severity fire. As a result, efforts are underway to simultaneously reduce potential fire and fuel hazards and restore characteristics indicative of historical forest structures and ecological processes that enhance the diversity and quality of wildlife habitat across landscapes. Despite widespread agreement on the need for action, there is a perceived tension among scientists concerning silvicultural treatments that modify stands to optimally reduce potential fire behavior (fuel hazard reduction) versus those that aim to emulate historical forest structures and create structurally complex stands (restoration). In this work, we evaluated thinning treatments in the Black Hills National Forest that exemplify the extremes of a treatment continuum that ranges from fuel hazard reduction to restoration. The goal of this work was to understand how the differing three-dimensional stand structures created by these treatment approaches altered potential fire behavior. Our results indicate that restoration treatments created higher levels of vertical and horizontal structural complexity than the fuel hazard reduction treatments but resulted in similar reductions to potential crown fire behavior. There were some trade-offs identified as the restoration treatments created larger openings, which generated faster mean rates of fire spread; however, these increased spread rates did not translate to higher levels of canopy consumption. Overall, our results suggest that treatments can create vertical and horizontal complexity desired for restoration and wildlife habitat management while reducing fire hazard and that they can be used in concert with traditional fuel hazard reduction treatments to reduce landscape scale fire risk. We also provide some suggestions to land managers seeking to design and implement prescriptions that emulate historical structures and enhance forest complexity.

Does the legacy of historical thinning treatments foster resilience to bark beetle outbreaks in subalpine forests?

Promoting ecological resilience to increasing disturbance activity is a key management priority under warming climate. Across the Northern Hemisphere, tree mortality from widespread bark beetle outbreaks raises concerns for how forest management can foster resilience to future outbreaks. Density reduction (i.e., thinning) treatments can increase vigor of remaining trees, but the longevity of treatment efficacy for reducing susceptibility to future disturbance remains a key knowledge gap. Using one of the longest-running replicated experiments in old-growth subalpine forests, we measured stand structure following a recent (early 2000s) severe mountain pine beetle (MPB; Dendroctonus ponderosae) outbreak to examine the legacy of historical (1940s) thinning treatments on two components of resilience. We asked: 'How did historical thinning intensity affect (1) tree-scale survival probability and stand-scale survival proportion (collectively "resistance" to outbreak) for susceptible trees (lodgepole pine [Pinus contorta] ≥ 12 cm diameter) and (2) post-outbreak stand successional trajectories?' Overall outbreak severity was high (MPB killed 59% of susceptible individuals and 78% of susceptible basal area), and historical thinning had little effect on tree-scale and stand-scale resistance. Tree-scale survival probability decreased sharply with increasing tree diameter and did not differ from the control (uncut stands) in the historical thinning treatments. Stand-scale proportion of surviving susceptible trees and basal area did not differ from the control in historically thinned stands, except for treatments that removed nearly all susceptible trees, in which survival proportion approximately doubled. Despite limited effects on resistance to MPB outbreak, the legacy of historical treatments shifted dominance from large-diameter to small-diameter lodgepole pine by the time of outbreak, resulting in historically thinned stands with ~2× greater post-outbreak live basal area than control stands. MPB-driven mortality of large-diameter lodgepole pine in control stands and density-dependent mortality of small-diameter trees in historically thinned stands led to convergence in post-outbreak live tree stand structure. One exception was the heaviest historical thinning treatments (59-77% basal area removed), for which sapling dominance of shade-tolerant, unsusceptible conifers was lower than control stands. After six decades, thinning treatments have had minimal effect on resistance to bark beetle outbreaks, but leave persistent legacies in shaping post-outbreak successional trajectories.

Regularized Regression: A New Tool for Investigating and Predicting Tree Growth

Neighborhood models have allowed us to test many hypotheses regarding the drivers of variation in tree growth, but require considerable computation due to the many empirically supported non-linear relationships they include. Regularized regression represents a far more efficient neighborhood modeling method, but it is unclear whether such an ecologically unrealistic model can provide accurate insights on tree growth. Rapid computation is becoming increasingly important as ecological datasets grow in size, and may be essential when using neighborhood models to predict tree growth beyond sample plots or into the future. We built a novel regularized regression model of tree growth and investigated whether it reached the same conclusions as a commonly used neighborhood model, regarding hypotheses of how tree growth is influenced by the species identity of neighboring trees. We also evaluated the ability of both models to interpolate the growth of trees not included in the model fitting dataset. Our regularized regression model replicated most of the classical model’s inferences in a fraction of the time without using high-performance computing resources. We found that both methods could interpolate out-of-sample tree growth, but the method making the most accurate predictions varied among focal species. Regularized regression is particularly efficient for comparing hypotheses because it automates the process of model selection and can handle correlated explanatory variables. This feature means that regularized regression could also be used to select among potential explanatory variables (e.g., climate variables) and thereby streamline the development of a classical neighborhood model. Both regularized regression and classical methods can interpolate out-of-sample tree growth, but future research must determine whether predictions can be extrapolated to trees experiencing novel conditions. Overall, we conclude that regularized regression methods can complement classical methods in the investigation of tree growth drivers and represent a valuable tool for advancing this field toward prediction.

Forest Resistance to Extended Drought Enhanced by Prescribed Fire in Low Elevation Forests of the Sierra Nevada

Prescribed fire reduces fire hazards by removing dead and live fuels (small trees and shrubs). Reductions in forest density following prescribed fire treatments (often in concert with mechanical treatments) may also lessen competition so that residual trees might be more likely to survive when confronted with additional stressors, such as drought. The current evidence for these effects is mixed and additional study is needed. Previous work found increased tree survivorship in low elevation forests with a recent history of fire during the early years of an intense drought (2012 to 2014) in national parks in the southern Sierra Nevada. We extend these observations through additional years of intense drought and continuing elevated tree mortality through 2017 at Sequoia and Kings Canyon National Parks. Relative to unburned sites, we found that burned sites had lower stem density and had lower proportions of recently dead trees (for stems ≤47.5 cm dbh) that presumably died during the drought. Differences in recent tree mortality among burned and unburned sites held for both fir (white fir and red fir) and pine (sugar pine and ponderosa pine) species. Unlike earlier results, models of individual tree mortality probability supported an interaction between plot burn status and tree size, suggesting the effect of prescribed fire was limited to small trees. We consider differences with other recent results and discuss potential management implications including trade-offs between large tree mortality following prescribed fire and increased drought resistance.

Effects of Bark Beetle Outbreaks on Forest Landscape Pattern in the Southern Rocky Mountains, U.S.A

Since the late 1990s, extensive outbreaks of native bark beetles (Curculionidae: Scolytinae) have affected coniferous forests throughout Europe and North America, driving changes in carbon storage, wildlife habitat, nutrient cycling, and water resource provisioning. Remote sensing is a crucial tool for quantifying the effects of these disturbances across broad landscapes. In particular, Landsat time series (LTS) are increasingly used to characterize outbreak dynamics, including the presence and severity of bark beetle-caused tree mortality, though broad-scale LTS-based maps are rarely informed by detailed field validation. Here we used spatial and temporal information from LTS products, in combination with extensive field data and Random Forest (RF) models, to develop 30-m maps of the presence (i.e., any occurrence) and severity (i.e., cumulative percent basal area mortality) of beetle-caused tree mortality 1997–2019 in subalpine forests throughout the Southern Rocky Mountains, USA. Using resultant maps, we also quantified spatial patterns of cumulative tree mortality throughout the region, an important yet poorly understood concept in beetle-affected forests. RF models using LTS products to predict presence and severity performed well, with 80.3% correctly classified (Kappa = 0.61) and R2 = 0.68 (RMSE = 17.3), respectively. We found that ≥10,256 km2 of subalpine forest area (39.5% of the study area) was affected by bark beetles and 19.3% of the study area experienced ≥70% tree mortality over the twenty-three year period. Variograms indicated that severity was autocorrelated at scales < 250 km. Interestingly, cumulative patch-size distributions showed that areas with a near-total loss of the overstory canopy (i.e., ≥90% mortality) were relatively small (<0.24 km2) and isolated throughout the study area. Our findings help to inform an understanding of the variable effects of bark beetle outbreaks across complex forested regions and provide insight into patterns of disturbance legacies, landscape connectivity, and susceptibility to future disturbance.