Despite the vast area and large numbers of trees affected by drought- and bark beetle-induced tree mortality worldwide, relatively little is known about how post-mortality management practices affect forest recovery, particularly in forests historically adapted to frequent fire. Cutting and removing dead trees after a mass-mortality event provides an opportunity to salvage timber and lessen wildfire risk by reducing fuel loads, but the ecological impacts of this strategy extend beyond fuel reduction. A severe drought in California, USA (2012–2016) precipitated a mass die-off of conifers in the Sierra Nevada range. We examined how the management treatment of removing dead trees affected mixed-conifer forests in four key areas: fuels, tree regeneration, carbon stocks, and future fire behavior and severity. We collected data in 122 paired plots (22 m diameter) in treated and adjacent untreated areas spanning 300 km of the Sierra Nevada, one to 5 years after the removal of recently dead trees. We found that sound coarse woody debris mass was 51% higher with removal, but rotten coarse woody debris was not different. Litter depth and 1-h and 10-h fuel mass decreased with removal. Combined Pinus ponderosa and P. jeffreyi (shade-intolerant) seedling densities were 349% higher with removal, while P. lambertiana (moderately shade-tolerant) and Abies concolor (shade-tolerant) seedling densities were 64 and 55% lower with removal. Sapling density was 56% lower in treated plots but did not differ by species. Total forest carbon was 32% lower in treated sites, predominantly driven by dead-tree removal. Using the Forest Vegetation Simulator, we simulated future fire severity (% basal area mortality) and behavior (torch potential) over 100 years at 10-year intervals and predicted that after a 20-year lag, treatment persistently reduced simulated fire severity and behavior. Removal of dead trees initially enhanced regeneration of fire-adapted yellow pine species but negatively affected sugar pine regeneration, had varying effects on different fuel types, had predictable effects on on-site carbon stores, and lowered modeled future wildfire severity.

Forests are ecologically complex, and trees play a structural and functional role in ecosystem dynamics. Tree height–DBH (diameter at breast height) relationships serve as a key indicator of forest productivity, competition, and succession, fundamental to sustainable forest management. This study develops height–DBH models for eight ecologically important tree species in boreal and mixed forests by applying nonlinear mixed-effects modelling approach to improve the predictive accuracy of height estimations. We evaluate height–DBH functions, including the two-parameter power function and Chapman–Richards function, incorporating stand-level variables—stand height based on dominant or co-dominant trees (SHT), basal area (BAH), and tree density (TPH) to refine predictions. Results indicate that mixed-effects models significantly improved model performance, with M4 (Chapman–Richards with mixed-effects) and M5 (Chapman–Richards function with mixed-effects and stand-level variables)–showing lowest AIC (Akaike Information Criterion) across species. Incorporating stand-level variables significantly enhanced performance, though improvements varied by species. The high accuracy of model M5 was further confirmed by validation process. Among stand-level variables, SHT contributed the most to height predictions (25.3 – 53.0%), while BAH (≤ 0.36%) and TPH (≤ 0.01%) had negligible effects. Still M4 can be a reliable alternative when stand-level variables are unavailable. This study highlights the effectiveness of a mixed-effects modelling framework complemented by stand-level variables in improving tree height estimation. Our research improves decision-making in growth and yield estimations of mixed stands and enhances the reliability of forest vegetation simulator outputs, thereby supporting ecological integrity.

Abstract Local calibration methods were evaluated for diameter at breast height (dbh) growth predictions in 11 tree species in Virginia, USA, using a model form based on the Forest Vegetation Simulator Southern Variant (FVS-Sn) large tree dbh regression model. Data from 1090 remeasured forest inventory plots from the USDA Forest Service’s Forest Inventory and Analysis (FIA) database were used to calibrate FVS dbh growth predictions to local conditions and evaluate four calibration methods based on the following information: 1) median prediction errors calculated from locally observed dbh pairs before and after a five-year remeasurement period; 2) a random intercept estimated from locally observed dbh using mixed-effects regression; 3) a simple linear regression (SLR) model fitted to observed and predicted dbh at the local scale; and 4) an SLR model with regression through the origin. Calibration methods were assessed using leave-one-out cross-validation, comparing model predictions to observed dbh growth from withheld trees. Equivalence testing indicated median or regression-based local calibration methods achieved prediction-error tolerances over 5–7 year growth intervals as small as 0.11 cm (0.03 cm for two regression-based methods) for all species, whereas the random-intercept approach only achieved a minimum tolerance of 0.2 cm. Compared to uncalibrated models, local calibration substantially reduced prediction errors, demonstrating efficacy in increasing prediction accuracy, even with sparse FIA dbh growth data used for local-calibration.

Evaluating Forest Vegetation Simulator (FVS) calibration options for predicting biomass accumulation across diverse Oregon landscapes

Increasing wildfire activity in mesic, temperate Pacific Northwest forests west of the Cascade Range crest has stimulated interest in understanding whether alternative forest management practices could reduce risk of stand-replacing fire. To explore how management can enhance fire resistance in these forests and assess tradeoffs among resistance enhancement, carbon sequestration and storage, and economic returns, we conducted 40-year simulations of stand development with BioSum, a framework for conducting landscape analysis with the Forest Vegetation Simulator (FVS), utilizing a statistically representative and spatially balanced sample of Forest Inventory and Analysis (FIA) plots. Simulation outcomes under business-as-usual silviculture were contrasted with fire-aware silviculture, and treatment optimization logic was developed and applied to represent landscape-scale outcomes under business-as-usual and fire-focused management scenarios. Simulation results indicate that fire-aware prescriptions and fire-focused management can meaningfully enhance stand- and landscape-scale fire resistance of westside forests under less than extreme fire weather, but at the cost of lower economic returns and reduced net carbon storage and sequestration over the 40-year analysis window. Shifting from business-as-usual regeneration harvests with short rotations to fire-aware, episodic selection harvest improved fire resistance the most, especially in young privately-owned forests, and with only modest tradeoffs in carbon and economic outcomes. While fire-aware treatments generally reduced net present value from forest operations over business-as-usual, most treatments still generated positive net present value and could be implemented without subsidy. Fire-aware prescriptions that removed and utilized non-merchantable harvest residues instead of burning them, via either pile or broadcast burning, partially mitigated carbon emissions associated with fire-aware treatments, with about the same improvement in fire resistance. Given the currently limited institutional and financial capacity to implement fire resistance enhancing treatments at scale, the insights from this analysis may aid managers seeking to elevate fire resistance to prioritize where and how to manage.

Selection forestry sustains timber production and stand structural complexity via partial harvesting. However, regeneration initiated by harvesting may function as fuel ladders, providing pathways for fire to reach the forest canopy. We sought potential mitigation approaches by simulating stand growth and potential wildfire behavior over a century in stands dominated by coast redwood (Sequoia sempervirens (Lamb. ex. D. Don) Endl.) on California’s north coast. We used the fire and fuels extension to the forest vegetation simulator (FFE-FVS) to compare group selection (GS) to single-tree selection silviculture with either low-density (LD) or high-density (HD) retention on a 20-year harvest return interval. These three approaches were paired with six options involving vegetation management (i.e., hardwood control or pre-commercial thinning (PCT)) with and without fuels treatments (i.e., prescribed fire or pile burning), or no subsequent vegetation or fuel treatment applied after GS, HD, or LD silviculture. Fuel treatment involving prescribed fire reduced hazardous fuel loading but lowered stand density and hence productivity. Hardwood control followed by prescribed fire mitigated potential wildfire behavior and promoted dominance of merchantable conifers. PCT of small young trees regenerating after selection harvests, followed by piling and burning of these cut trees, sustained timber production while reducing potential wildfire behavior by approximately 40% relative to selection silviculture without vegetation/fuel management, which exhibited the worst potential wildfire behavior.

The monitoring and assessment of forest conditions has traditionally relied on continuous forest inventory (CFI) plots, where all plot trees are regularly measured at discrete locations, then plots are grouped as representative samples of forested areas via stand-based inventory expectations. Remote sensing data acquisitions, such as airborne laser scanning (ALS), are becoming more widely applied to operational forestry to derive similar stand-based inventories. Although ALS systems are widely applied to assess forest metrics associated with crowns and canopies, limited studies have compared ALS-derived digital inventories to CFI datasets. In this study, we conducted an analysis of over 1000 CFI plot locations on ~611,000 acres and compared it to a single-tree derived inventory. Inventory metrics from CFI data were forward modeled from 2016 to 2019 using the USDA Forest Service Forest Vegetation Simulator (FVS) to produce estimates of trees per acre (TPA), basal area (BA) per tree or per plot, basal area per acre (BAA), and volume per acre (VPA) and compared to the ALS-derived Digital Inventory® (DI) of 2019. The CFI data provided greater on-plot tree counts, BA, and volume compared to the DI when limited to trees ≥5 inches DBH. On-plot differences were less significant for taller trees and increasingly diverged for shorter trees (<20 feet tall) known to be less detectable by ALS. The CFI volume was found to be 44% higher than the ALS-derived DI suggesting mean volume per acre as derived from plot sampling methods may not provide accurate results when expanded across the landscape given variable forest conditions not captured during sampling. These results provide support that when used together, CFI and DI datasets represent a powerful set of tools within the forest management toolkit.

Integrating the physical harvesting of dead wood into fuel treatments to reduce wildfire hazards and enhance carbon benefits.

Background In response to increasing risk of extreme wildfire across western North America, forest managers are proactively implementing fuel treatments. Aims We assessed the efficacy of alternative combinations of thinning, pruning and residue fuel management to mitigate potential fire behaviour and effects in seasonally dry forests of interior British Columbia, Canada. Methods Across five community forests, we measured stand attributes before and after fuel treatments in 2021 and 2022, then modelled fire behaviour and effects using the Fire and Fuels Extension to the Forest Vegetation Simulator. Key results For our study area, field measurements combined with fire behaviour modelling indicated: (1) low-intensity thinning from below reduced potential of passive crown fire, whereas high-intensity thinning reduced potential of passive and active crown fire; (2) pruning after thinning from below did not further reduce potential of passive crown fire; and (3) chipping or pile burning of residue fuel mitigated potential of passive crown fire, but fire effects associated with chipping remain a concern. Conclusions and implications There is limited prior research on the impacts of fuel treatments in western Canada. This research contributes to better understanding the potential impacts of fuel treatments in the fire-prone forests of interior British Columbia.

Increasing wildfire activity in mesic, temperate Pacific Northwest forests west of the Cascade Range crest has stimulated interest in understanding whether alternative forest management practices could reduce risk of stand-replacing fire. To explore how management can enhance fire resistance in these forests and assess tradeoffs among resistance enhancement, carbon sequestration and storage, and economic returns, we conducted 40-year simulations of stand development with BioSum, a framework for conducting landscape analysis with the Forest Vegetation Simulator (FVS), utilizing a statistically representative and spatially balanced sample of Forest Inventory and Analysis (FIA) plots. Simulation outcomes under business-as-usual silviculture were contrasted with fire-aware silviculture, and treatment optimization logic was developed and applied to represent landscape-scale outcomes under business-as-usual and fire-focused management scenarios. Simulation results indicate that fire-aware prescriptions and fire-focused management can meaningfully enhance stand- and landscape-scale fire resistance of westside forests under less than extreme fire weather, but at the cost of lower economic returns and reduced net carbon storage and sequestration over the 40-year analysis window. Shifting from business-as-usual regeneration harvests with short rotations to fire-aware, episodic selection harvest improved fire resistance the most, especially in young privately-owned forests, and with only modest tradeoffs in carbon and economic outcomes. While fire-aware treatments generally reduced net present value from forest operations over business-as-usual, most treatments still generated positive net present value and could be implemented without subsidy. Fire-aware prescriptions that removed and utilized non-merchantable harvest residues instead of burning them, via either pile or broadcast burning, partially mitigated carbon emissions associated with fire-aware treatments, with about the same improvement in fire resistance. Given the currently limited institutional and financial capacity to implement fire resistance enhancing treatments at scale, the insights from this analysis may aid managers seeking to elevate fire resistance to prioritize where and how to manage.

BackgroundFire suppression, timber harvesting, and the forced removal of Indigenous burning have fundamentally changed conditions in coast redwood forests. The contemporary approach of forest preservation and fire exclusion has produced high densities of small trees, elevated fuel loads, and increased vulnerability to wildfire and climate change. Prescribed broadcast burning presents a viable treatment option to meet forest management goals, especially where mechanical treatments are not feasible. Forest and fire managers utilizing fire modeling software such as the Fire and Fuels Extension of Forest Vegetation Simulator (FFE) to predict prescribed fire effects in redwoods are limited by model accuracy due to a lack of empirical research and model verification across a breadth of site conditions.ResultsWe compared the difference between pre- and post-treatment conditions for two fall-season prescribed burns in Sonoma and Santa Cruz counties in California to quantify changes to forest structure, fuel loads, and modeled wildfire hazard. Observed data was used to analyze the accuracy of FFE modeled prescribed fire treatment outputs for post-treatment forest and fuel conditions. Observed burn treatments were low intensity and resulted in no significant change to forest structure and composition, but there was a reduction in seedling and sapling densities and an increase in resprout density. There was a reduction in duff and litter fuels, and litter and fine woody debris reduction was driven by pre-treatment total fuel loads. The modeled probability of torching was very low pre- and post-treatment. FFE underpredicted scorch height, duff fuel reduction, and redwood regeneration, but slightly overpredicted tree mortality and significantly overpredicted reduction of litter and fine woody debris.ConclusionOur results highlight a need for model refinement in regard to species-specific mortality, tree regeneration dynamics, fuel recruitment and deposition, and moisture-dependent fuel consumption. In order to achieve desired forest management goals, fire practitioners may need to burn at moderate to high intensities, and potentially pair burning with mechanical thinning. Long-term health of coast redwood forests also relies on the restoration of cultural fire and stewardship partnerships that equally share decision making power between western science and Indigenous knowledge bearers.

Forest restoration thinning may accelerate the development of structural complexity toward old-growth conditions faster than a natural forest, yet associated changes in forest carbon (C) are poorly understood. Old-growth forests are characterized by high levels of sequestered C in aboveground biomass and soil C pools, yet active management has well-recognized negative impacts on stored C. Effects of forest restoration thinning on forest C can be determined using longitudinal measurements and modeling based on stand conditions and tree growth. At Ellsworth Creek Preserve in Southwest Washington, forest restoration efforts in a second-growth temperate rainforest have been monitored using permanent plots since 2007. Here, we compare repeat measurements from 2020, modeled forest C, and measurements of O-horizon C pools from 2022 to determine C impacts of silvicultural treatments for old-growth restoration. We found good general agreement between empirical measurements and models of forest C using the Forest Vegetation Simulator (FVS). However, treatment alone was not a strong indicator for C conditions; rather, forest age and age–treatment interactions better predicted soil C responses to restoration treatments. These data may indicate that “light” forest restoration thinning can accelerate old-growth development with minimal effects on soil carbon—a win-win conservation strategy for old-growth forests and the climate.

Life-cycle impact assessment of hardwood forest resources in the eastern United States

Forest management decisions affect carbon stock and rates of sequestration. One subject of debate is the rotation age that will optimize sequestration over extended periods. Some argue that shorter rotations facilitate greater sequestration rates due to the accelerated growth rates of younger trees compared to mature or old-growth trees. Others maintain that frequent harvesting will not allow forest carbon to rebound after each subsequent rotation, and thus more extended periods between clearcutting is the superior choice. These contrasting viewpoints are mirrored regarding the impact of thinning treatments, in that either thinning will enhance forest carbon uptake by facilitating improved and sustained r growth of residual trees or removing any above-ground biomass will outweigh the yields. This study aims to compare the different suites of management decisions and identify practical combinations of rotation ages and thinning applications that will optimize carbon sequestration while meeting other objectives over a 240-year projection timeframe. Stand development under different harvest rotations and thinning specifications was modeled using a Forest Vegetation Simulator (FVS). We found that site productivity was the primary determinant in stand-above-ground carbon dynamics under various management scenarios. Thus, the optimal rotation age/thinning treatment combinations differed between site classes. High productivity stands were estimated to sequester the most above-ground live carbon with 60-year rotations with a low-intensity thin at age 40. Moderately productive stands performed the best with 80-year rotations when two low-intensity thinning treatments were applied between harvests. For high and moderate productivity stands, estimates of gross carbon increased when two low or moderate-intensity thinning treatments were applied within 80- or 120-year rotations. High-intensity thinning treatments reduced total carbon sequestered over the 240-year projection timeframe for all productivity levels and rotation ages, except for low productivity stands under 120-year rotations.

Abstract White oak is a major commercial tree species and an important timber resource in Kentucky. However, current forest inventory trends from the Central Hardwood Forest Region (CHFR) reveal a sustainability threat from declining white oak regeneration and recruitment leading to a disproportionate inventory structure. Using Forest Inventory and Analysis (FIA) data together with the Forest Vegetation Simulator (FVS), we performed a base run analysis of projected inventory levels of white oak sawlogs to better understand whether the inventory level is sustainable to support the current harvest level of white oak in the future. The projections were further examined by tree grades to provide a general outlook on the quality of white oak timber growing in Kentucky’s forests in posterity. By doing so, we generated results that indicate that projected inventory levels of white oak sawlogs cannot be considered sustainable to support current harvest levels from 2058 onwards. In addition, the long-term trends in inventory levels of high-quality white oak sawlogs would be continuously declining whereas that of low-quality sawlogs would be steadily increasing. On the brink of these significant inventory shifts, our study calls for proactive forest management approaches to stabilize the white oak timber resource supply in Kentucky and beyond.

In the past, the dry mixed conifer forests of California’s Sierra Nevada mountains experienced frequent low to mixed severity fires. However, due to fire suppression and past management, forest structure has changed, and the new fire regimes are characterized by large, high severity fires which kill a majority of the overstory trees. These new disturbance patterns require novel approaches to regenerate the forest as they are not adapted to large, high severity fires. We forecasted growth and fire behavior of young plantations for 100 years into the future using the Forest Vegetation Simulator (FVS) and its Fire and Fuels Extension (FFE). In these simulations, we tested combinations of different fuel treatments (mastication only, mastication with prescribed burning, and no fuels treatments) with different overstory thinning intensities (residual densities of 370 SDI (stand density index), 495 SDI, 618 SDI (TPH), and no overstory thinning) on stand growth and potential fire behavior using analysis of variance. We compared growth and crowning index at the end of the simulation and the simulation age when the flame length, basal area mortality, and fire type reached low severity between fuel treatment, thinning intensity, and original management of stands (plantation with PCT [precommercial thinning], plantation without PCT, and natural regenerating stands). These comparisons are essential to identify which fuel treatment categories reduce fire risk. We found an overall pattern of decreasing crown fire occurrence and fire induced mortality across all simulations due to increasing canopy base height and decreasing canopy bulk density. In particular, stands with mastication and prescribed burning transitioned from crown fire types to surface fires 10 years earlier compared to mastication only or no fuel treatment. Furthermore, pre-commercially thinned stands transitioned from crown fire states to surface fires 10 years earlier in the simulations compared to un-thinned and naturally regenerating stands. Stands with mastication and burning went below 25% reference threshold of basal area mortality 11 and 17 years earlier before the mastication only and no fuel treatment, respectively. In addition, pre-commercially thinned stands went below 25% basal area mortality 9 and 5 years earlier in the simulation compared to un-thinned or naturally regenerated stands, respectively. Mastication with prescribed burning (MB) was the most effective treatment for quickly reducing fire behavior by consuming surface fuels, thus drastically lowing flame length (e.g., surface flame length of MB was 0.6 m compared to mastication only [1.3 m] and no treatment [1.4 m]). Furthermore, intensive thinning reduced risk of active crown fires spreading through the stand. Prioritizing prescribed burning, when possible, and thinning (both pre-commercially and from below) are the most effective ways to quickly improve fire resistance in mixed conifer plantations. Our results highlight the different stressors that post-fire planted forests experience and how different silvicultural treatments interact over time to reduce fire risk, which demonstrates the importance of treating stands early and the effectiveness of surface fuel treatments.

Using regression-based, bootstrapped equivalence tests, and remeasured inventory plot data from thousands of plots across California, we found that the Forest Vegetation Simulator (FVS), as typically used out-of-the-box, overpredicts carbon sequestration in live trees that remain alive ten years later by 27%, on average. We found FVS growth prediction sensitive to forest type and FVS variant, with the largest overpredictions occurring in stands within the North Coast variant, growing on the lowest site class, having ages that are unknown or between 50 and 100 years, and that are within governmentally designated reserved areas or on national forests. Direction and magnitude of errors are related to the stand attributes; these relationships point the way towards opportunities to improve the underlying growth models or calibrate the system to improve prediction accuracy. Our findings suggest that forest managers relying on out-of-the-box FVS growth models to forecast carbon sequestration implications of their management of California forests will obtain estimates that overstate the carbon that can be sequestered under light-touch or caretaker management, potentially leading to management decisions that fail to deliver the expected carbon sequestration benefits—a failure that could take a long time to recognize.

Abstract There has been increasing interest among foresters and landowners in modifying existing even-aged forest structures to multi-aged or uneven-aged structures. Maintaining a continuous forest structure often provides a wider array of forest values over the long term. The conversion process is challenging in regions of the Northeast United States characterized by forests composed of dense diseased beech thickets and low-vigor deformed overstory trees. Abundance of noncommercial beech may result in negative cash flows during the conversion process to achieve a desired balanced uneven-aged structure. The Forest Vegetation Simulator was used to model growth and yield. Given the possibility of negative cash flows, a least-cost dynamic program with a penalty function was used to determine least-cost time paths for two management scenarios, one characterized by the successful removal of beech and the other simulating the continued presence of beech. Incorporating a penalty function allowed creating a continuum of least-cost paths from a zero penalty with the greatest weight given to net revenue goals to the largest penalty with the greatest weight given to ecological goals. Sensitivity analyses revealed least-cost paths were more stable given changes in prices and wages when greater emphasis was placed on the ecological goals associated with the target structure.

The capacity of forests to store carbon, combined with time-tested approaches to managing forests, make forests a useful tool for atmospheric carbon mitigation. The primary goals of this study are to determine the amount of unrealized mitigation available from Improved Forest Management (IFM) in the Acadian Forest of New England in the northeastern U.S., and to demonstrate how this mitigation can feasibly be attained. This study used the Forest Vegetation Simulator (FVS) to model the impacts of IFM practices articulated by the New England Forestry Foundation on carbon storage in the Acadian Forest. Our results, together with empirical data from well-managed forests, show that if the modeled improved management is employed on privately owned timberland across the Acadian Forest of New England, carbon storage could be increased by 488 Tg CO2e. Our financial modeling shows that IFM could be funded in this region by combining income from carbon markets with the philanthropic funding of conservation easements, timber revenues, and capital investments from private investors who prioritize social and economic goals alongside financial returns. This study adds to the body of evidence from around the world that the potential for managed forests to contribute to climate change mitigation has not been fully realized.

Salvage logging is a controversial tool for post-wildfire management that removes fire-killed trees. We use a generalized randomized experimental design to fulfill two main objectives: (1) quantify the immediate (1-year post-harvest) effects of salvage logging on stand structure, fine and coarse woody fuel loadings; and (2) use pre- and post-empirical field data and the Fire and Fuels Extension to the Forest Vegetation Simulator (Reinhardt and Crookston 2003) to simulate post-wildfire dead woody fuel succession and snag dynamics. We compared the effects on woody fuel loadings of two salvage logging prescriptions: (1) seed tree harvest, thin to 3.4 m2·ha−1; and (2) full salvage of all merchantable timber, relative to unlogged controls. There was substantial block-level variability in the implementation of the treatments and in their immediate effects on fine fuel loading, complicating comparison of the two prescriptions. Overall, salvage logging did reduce snag basal area and, relative to unlogged controls, significantly increased measured fine woody fuel loading (10 and 100 h). Simulated snag fall was rapid, with a mean predicted snag basal area loss of 61% within 10 years. Future long-term monitoring of permanent field plots will supplement model predictions and provide valuable data to inform post-wildfire management decisions.