Forest Carbon Management Research Articles

Combining multiple feature selection methods and structural equation modelling for exploring factors affecting stand biomass of natural coniferous-broad leaved mixed forests

Recognition of biotic and abiotic factors affecting biomass of natural mixed forests is of great importance for forest carbon estimation and management. When estimating stand biomass using models, different variable selection methods often yield inconsistent results, and there is lack of systematic analysis. This study aimed to combine multiple feature selection methods with structural equation modelling (SEM) to identify a set of variables affecting stand biomass more reasonably. Eight methods were applied for feature selection based on data from 286 permanent sample plots in natural coniferous-broad leaved mixed forests in northeast China. These methods included Pearson correlation analysis, two methods derived from principal component analysis (PCA), stepwise regression, redundancy analysis (RDA), generalized additive model (GAM), random forest (RF), and boosted regression tree (BRT). A total of 56 candidate variables were considered, covering stand, biodiversity, climate and soil features. Significant variability was observed in the variables selected, however, there were 6 variables consistently identified across all methods, including tree species diversity (N_Sp_Div), stand structural diversity (N_ Size_ Div), nearest taxon index (NRI), community weighted mean based on dry matter mass of leaves (CWM.LDMC), soil pH, and degree-days above 18 °C (DD18). Then, these variables were included in the SEM with stand average age and additive stand density index (aSDI) to explore the direction and magnitude of their impacts on stand biomass. The SEM results showed that aSDI and average age had the greatest positive effects on stand biomass, and structural diversity also had a significant positive effect. DD18 affected stand biomass both directly and indirectly, with the total negative effect. Soil pH indirectly affected stand biomass via aSDI. Our findings demonstrated that combining multiple feature selection methods with SEM was an effective approach for understanding multiple factors affecting stand biomass, and provided valuable insights for forest biomass estimation and carbon management.

Forest structure explains spatial heterogeneity of decadal carbon dynamics in a cool-temperate forest

Abstract Accurate evaluation of forest biomass distribution and its long-term change over wide areas is required for effective forest carbon management and prediction of landscape-scale forest dynamics. We evaluated a landscape-scale (225 km2) decadal forest carbon budget at a 1 ha spatial resolution in a cool-temperate forest, by repeating airborne laser observations 10 years apart and partitioning net forest biomass change (FBC) into growth and mortality. Using >10 000 samples, we revealed that naturally regenerated forests have large spatial heterogeneity in net biomass change, and 3/4 of the photosynthetically acquired carbon stock moved to necromass even without anthropogenic disturbances. Actual carbon residence time as living tree biomass was estimated by dividing biomass by growth or mortality rates. The residence time was 107 and 106 years, respectively with large spatial variation among stands (48 and 42 years, respectively, as the difference between 25 and 75 percentile), although studied forest stands have small variation in the forest functional type in a landscape-scale. The best predictors of subsequent decadal biomass changes were two forest structural factors, mean canopy height and canopy height variation in addition to one environmental factor, elevation. Considering the long lifetime of trees, these structural factors may be an indicator of forest soundness rather than a cause of forest growth or mortality. However, in any cases, these structural factors can be powerful predictors of subsequent FBC.

Environmental correlates of the forest carbon distribution in the Central Himalayas.

Understanding the biophysical limitations on forest carbon across diverse ecological regions is crucial for accurately assessing and managing forest carbon stocks. This study investigates the role of climate and disturbance on the spatial variation of two key forest carbon pools: aboveground carbon (AGC) and soil organic carbon (SOC). Using plot-level carbon pool estimates from Nepal's national forest inventory and structural equation modelling, we explore the relationship of forest carbon stocks to broad-scale climatic water and energy availability and fine-scale terrain and disturbance. The forest AGC and SOC models explained 25% and 59% of the observed spatial variation in forest AGC and SOC, respectively. Among the evaluated variables, disturbance exhibited the strongest negative correlation with AGC, while the availability of climatic energy demonstrated the strongest negative correlation with SOC. Disturbances such as selective logging and firewood collection result in immediate forest carbon loss, while soil carbon changes take longer to respond. The lower decomposition rates in the high-elevation region, due to lower temperatures, preserve organic matter and contribute to the high SOC stocks observed there. These results highlight the critical role of climate and disturbance regimes in shaping landscape patterns of forest carbon stocks. Understanding the underlying drivers of these patterns is crucial for forest carbon management and conservation across diverse ecological zones including the Central Himalayas.

Qualifying gaps between scientific prescriptions and social perceptions about the role of forest management practices for increasing carbon stocks on family forestlands in the US South

Aligning scientific and public views on forest management is crucial for increasing the participation of family forest landowners in voluntary forest carbon programs. We compared the results from a systematic literature review of forty research articles in the US South with the perceptions of the stakeholder groups. We quantified perceptions of stakeholder groups regarding the potential of different forest management practices to enhance the carbon stocks in family forestlands by undertaking surveys in a total of two workshops conducted in the South and North Carolinas. We found a clear divergence regarding the carbon potential of the use of genetically advanced species for enhancing carbon. The workshop attendees did not rank this option high, although it is highly prioritized in the scientific literature. Convergence in using improved forest management to increase carbon stocks was observed. Although extended rotation was favored as the second-to-last option for enhancing carbon (before better genetics) by workshop respondents, non-landowners ranked it a higher priority than landowners. All workshop attendees ranked afforestation overall highest, corroborating the systematic review studies in the US South. The workshop attendees suggested conservation-based forest carbon management as a potential option to enhance the carbon stocks in family forestlands; however, we did not find much scientific literature on this option. This study is beneficial to both forest landowners and managers of forest carbon programs as well as to the scientific community at large. It brings all stakeholder groups together to craft new carbon programs for broader participation and carbon stock enhancement in the US South (and beyond).

Benchmarking Geometry-Based Leaf-Filtering Algorithms for Tree Volume Estimation Using Terrestrial LiDAR Scanners

Terrestrial LiDAR scanning (TLS) has the potential to revolutionize forestry by enabling the precise estimation of aboveground biomass, vital for forest carbon management. This study addresses the lack of comprehensive benchmarking for leaf-filtering algorithms used in TLS data processing and evaluates four widely recognized geometry-based leaf-filtering algorithms (LeWoS, TLSeparation, CANUPO, and a novel random forest model) across openly accessible TLS datasets from diverse global locations. Multiple evaluation dimensions are considered, including pointwise classification accuracy, volume comparisons using a quantitative structure model applied to wood points, computational efficiency, and visual validation. The random forest model outperformed the other algorithms in pointwise classification accuracy (overall accuracy = 0.95 ± 0.04), volume comparison (R-squared = 0.96, slope value of 0.98 compared to destructive volume), and resilience to reduced point cloud density. In contrast, TLSeparation exhibits the lowest pointwise classification accuracy (overall accuracy = 0.81 ± 0.10), while LeWoS struggles with volume comparisons (mean absolute percentage deviation ranging from 32.14 ± 29.45% to 49.14 ± 25.06%) and point cloud density variations. All algorithms show decreased performance as data density decreases. LeWoS is the fastest in terms of processing time. This study provides valuable insights for researchers to choose appropriate leaf-filtering algorithms based on their research objectives and forest conditions. It also hints at future possibilities for improved algorithm design, potentially combining radiometry and geometry to enhance forest parameter estimation accuracy.

Collaborative Utilization of Sentinel-1/2 and DEM Data for Mapping the Soil Organic Carbon in Forested Areas Based on the Random Forest

Optical remote sensing data are widely used for constructing soil organic carbon (SOC) mapping models. However, it is challenging to map SOC in forested areas because atmospheric water vapor affects the results derived from optical remote sensing data. To address this issue, we utilized Sentinel-1, Sentinel-2, and digital elevation model (DEM) data to obtain a comprehensive feature set (including S1-based textural indices, S2-based spectral indices, and DEM-derived indices) to map the SOC content in forested areas. The features set were the predictor variables, and the measured SOC content was the dependent variable. The random forest algorithm was used to establish the SOC model. The ratio of performance to inter-quartile range (RPIQ) was 2.92 when the S2-based spectral indices were used as predictor variables. When the comprehensive feature set was utilized as the model input, the model achieved an RPIQ of 4.13 (R2 = 0.91, root mean square error (RMSE) = 9.18), representing a 41.44% improvement in model accuracy. The average SOC content in the Greater Khingan Mountains was 43.75 g kg−1. The northern and southwestern parts had higher SOC contents (>54.93 g kg−1), while the southeastern and northwestern parts had lower contents (<39.83 g kg−1). This discrepancy was primarily attributed to agricultural activities. The results indicate that using a comprehensive feature set and the random forest algorithm is a reliable approach for estimating the spatial distribution of the SOC content in forested areas and is suitable for forest ecology and carbon management studies.

Tree species composition, growing stock and biomass carbon dynamics of the major timber species in Hindu Kush regions of Pakistan.

Using inventory data, this study evaluates the species composition, growing stock volume (GSV), and biomass carbon (BMC) of the five major timber species in the sub-tropical, and temperate/sub-alpine regions of Pakistan. It was found that the stem density varies between 50 and 221 trees ha -1, with a mean of 142 trees ha-1 (13.68 million trees for entire forest area). Among the species, Pinus wallichiana showed a high species composition (27.80%) followed by Picea smithiana (24.64%). The GSV was found in the range of 67.81 to 425.94 m3 ha-1, with a total GSV value of 20.68 million m3 for the entire region. Similarly, The BMC ranged from 27.04 to 169.86 Mg ha-1, with a mean BMC value of 86.80 Mg ha-1. The total amount of stored carbon was found at 8.69 million tons for a total of 95842 ha of commercially managed forest. Furthermore, the correlation analysis between the basal area (BA) and GSV and BMC showed that BA is the best predictor of GSV and BMC. The findings provide insights to the policy makers and forest managers regarding the sustainable commercial forest management as well as forest carbon management in the recent global carbon management for climate change mitigation.

Realistic potential increases in carbon storage via timber rotation extensions: an analysis of the Pacific Northwest

Extensions of harvest rotation length are a commonly proposed method to increase carbon sequestration in forests that are managed for timber. However, several limitations constrain realistic storage potential in intensively managed forests. We present an analysis of the realistic potential for additional carbon sequestration via rotation extension across the Pacific Northwest of the United States, an important timber-producing region, taking into account specific limitations. We first assess the limitations on rotation length imposed by the stand age at which wood production would decline over the long term, and then incorporate the age at which trunk diameter surpasses a reasonable threshold for logging. Using publicly available forest survey data, we empirically model growth parameters across this region for use in this analysis. Despite uncertainties, we find some opportunities for rotation length extension in western Washington with variation by sub-region and timber species, emphasizing the importance of geography- and species-specific growth parameters for forest carbon management even within a general region. However, the total realistic potential for sequestration under this improved forest management scenario is small relative to gross emissions: the estimated cumulative additional sequestration in aboveground live biomass would offset one year of gross emissions in the case of Washington state, while a decadal-scale rotation extension implemented gradually over the landscape to avoid a total pause on commercial timber production would take on the scale of a century to achieve. Overall, practical considerations greatly limit the realistic potential of this carbon sequestration strategy.

Review of Remote Sensing-Based Methods for Forest Aboveground Biomass Estimation: Progress, Challenges, and Prospects

Quantifying forest aboveground biomass (AGB) is essential for elucidating the global carbon cycle and the response of forest ecosystems to climate change. Over the past five decades, remote-sensing techniques have played a vital role in forest AGB estimation at different scales. Here, we present an overview of the progress in remote sensing-based forest AGB estimation. More in detail, we first describe the principles of remote sensing techniques in forest AGB estimation: that is, the construction and use of parameters associated with AGB (rather than the direct measurement of AGB values). Second, we review forest AGB remotely sensed data sources (including passive optical, microwave, and LiDAR) and methods (e.g., empirical, physical, mechanistic, and comprehensive models) alongside their limitations and advantages. Third, we discuss possible sources of uncertainty in resultant forest AGB estimates, including those associated with remote sensing imagery, sample plot survey data, stand structure, and statistical models. Finally, we offer forward-looking perspectives and insights on prospective research directions for remote sensing-based forest AGB estimation. Remote sensing is anticipated to play an increasingly important role in future forest AGB estimation and carbon cycle studies. Overall, this comprehensive review may (1) benefit the research communities focused on carbon cycle, remote sensing, and climate change elucidation, (2) provide a theoretical basis for the study of the carbon cycle and global climate change, (3) inform forest ecosystems and carbon management, and (4) aid in the elucidation of forest feedbacks to climate change.

Climate-Change-Driven Droughts and Tree Mortality: Assessing the Potential of UAV-Derived Early Warning Metrics

Protecting and enhancing forest carbon sinks is considered a natural solution for mitigating climate change. However, the increasing frequency, intensity, and duration of droughts due to climate change can threaten the stability and growth of existing forest carbon sinks. Extreme droughts weaken plant hydraulic systems, can lead to tree mortality events, and may reduce forest diversity, making forests more vulnerable to subsequent forest disturbances, such as forest fires or pest infestations. Although early warning metrics (EWMs) derived using satellite remote sensing data are now being tested for predicting post-drought plant physiological stress and mortality, applications of unmanned aerial vehicles (UAVs) are yet to be explored extensively. Herein, we provide twenty-four prospective approaches classified into five categories: (i) physiological complexities, (ii) site-specific and confounding (abiotic) factors, (iii) interactions with biotic agents, (iv) forest carbon monitoring and optimization, and (v) technological and infrastructural developments, for adoption, future operationalization, and upscaling of UAV-based frameworks for EWM applications. These UAV considerations are paramount as they hold the potential to bridge the gap between field inventory and satellite remote sensing for assessing forest characteristics and their responses to drought conditions, identifying and prioritizing conservation needs of vulnerable and/or high-carbon-efficient tree species for efficient allocation of resources, and optimizing forest carbon management with climate change adaptation and mitigation practices in a timely and cost-effective manner.

Carbon pool dynamics after variable retention harvesting in Nothofagus pumilio forests of Tierra del Fuego

BackgroundIt is necessary to determine the implications for managing forest stands using variable retention harvesting for maintaining carbon and for calculating the effects of different harvesting practices on above- and below-ground carbon balance in forest ecosystems. In this context, forest carbon management has gained more attention among managers and policy-makers during recent years. The aim of this study was to determine carbon pool dynamics in different forest ecosystem components after variable retention harvesting (VRH) to characterize the ecological stability and quantify the recovery rate through the years-after-harvesting (YAH).MethodsCarbon pool compartmentalization of 14 different components was determined in 60 harvested and primary unmanaged forests during the first 18 YAH in Tierra del Fuego (Argentina). We compared them using uni- and multi-variate methods, relativizing the outputs with primary unmanaged forests.ResultsWe determined the effectiveness to retain carbon components in post-harvested stands under different retention strategies (aggregated vs. dispersed). The balance among carbon pool components changed between managed and unmanaged stands across the YAH, and was directly related to the impact magnitude. Aggregated retention improved the ecological stability of the harvested areas, where the below-ground components were more stable than the above-ground components. The recovery rate was directly related to the post-harvesting natural dynamics of the stands. The studied period was not enough to fully recover the C levels of primary unmanaged forests, but VRH showed advantages to increase the C pools in the managed stands.ConclusionsPromoting VRH can improve sustainable forestry at the landscape level and in the long term, generating positive synergies with biodiversity and the provision of ecosystem services. This study provides important new insights into forest carbon management, in particular to setting standards in carbon projects and sets the groundwork for analysing the economics of the mentioned harvesting systems.

降解剂对森林凋落物可溶性有机碳含量的影响及凋落物降解模式比较研究

PDF HTML阅读 XML下载 导出引用 引用提醒 降解剂对森林凋落物可溶性有机碳含量的影响及凋落物降解模式比较研究 DOI: 10.5846/stxb202111153207 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 吉林农业大学人才引进科研启动经费项目（2021002） Effects of degrading agents on dissolved organic carbon content of forest litter and comparative study on litter degradation modes Author: Affiliation: Fund Project: Scientific Research Start-up Fund for Talent Introduction of Jilin Agricultural University(2021002) 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:森林凋落物是森林生态系统中可溶性有机碳（DOC）的主要来源，在生态系统碳循环过程中起重要作用。以帽儿山地区胡桃楸、兴安落叶松以及胡桃楸-兴安落叶松人工林凋落物为研究对象，通过液体发酵培养将纤维素高效降解真菌Peniophora intranata与Sarocladium strictum制成单一（A菌剂、B菌剂）及混合菌剂（C菌剂），测定野外条件下经降解剂处理的凋落物基质在不同时期的DOC含量，分析降解剂对不同类型森林凋落物DOC动态变化的影响，并比较各凋落物基质降解模式异同。结果表明：（1）凋落物基质DOC含量在降解剂处理后均随降解时间增加呈下降趋势，且下降幅度大小表现为混合基质 > 胡桃楸基质 > 落叶松基质；在最初的1个月，各凋落物基质DOC含量均显著高于其他降解时期DOC含量。（2）经混合菌剂处理后的胡桃楸基质DOC含量相较于2种单一菌剂处理后的胡桃楸基质DOC含量低，而经混合菌剂处理后的兴安落叶松基质与胡桃楸-兴安落叶松基质的DOC含量未表现出相同的显著性。（3）经3种菌剂处理后的胡桃楸基质降解模式均相同，经B菌剂与C菌剂处理的落叶松基质降解模式相同，经A菌剂与C菌剂处理的混合基质降解模式相同。研究表明森林凋落物类型影响DOC的释放能力；具协同效应的两菌种制得的混合菌剂较单一菌种制得菌剂降解凋落物能力强，从而促进DOC的释放，同时也受凋落物基质成分组成的影响。通过比较降解剂处理下不同类型凋落物DOC动态变化与降解模式的差异，为帽儿山地区森林凋落物分解及碳管理提供科学依据。 Abstract:Forest litter is the main source of dissolved organic carbon (DOC) in forest ecosystem and plays an important role in the process of ecosystem carbon cycle. In this study, the litter of Juglans mandshurica, Larix gmelinii and their mixed plantation in Maoer Mountain were taken as research objects. The high-efficiency cellulose degrading fungi Peniophora intranata and Sarocladium strictum were made into single (agent A, agent B) and mixed fungal agent (agent C) by liquid fermentation culture. The DOC content of forest litters treated with agents in different periods under field conditions was measured. The effects of degrading agents on the dynamic changes of DOC content of different types of litters were analyzed, and the similarities and differences of degradation modes of each litter substrate were compared. Results showed that DOC contents of the three litter substrates showed a downward trend with the increase of degradation time after treatment, and the decreasing range was in the order of mixture > J. mandshurica > L. gmelinii. In the first month, the DOC content of each litter substrate was significantly higher than that of other degradation periods. The DOC content of J. mandshurica substrate treated with the mixed fungal agent was lower than that treated with the two single fungal agents, but the DOC content of L. gmelinii and mixed substrate treated with mixed fungal agent did not show the same significance. The degradation modes of J. mandshurica substrate treated with the three kinds of agent were same. The degradation mode of L. gmelinii substrate treated with agent B was the same as that treated with agent C, and the mode of mixed substrate treated with agent A was the same as that treated with agent C. This study shows that the types of litter affect the release capacity of DOC. The mixed fugal agent made of two strains with synergistic effect has stronger ability to degrade litters than that made of single strain, so as to promote the release of DOC. At the same time, it is also affected by the composition of litter substrates. This study provides a scientific basis for forest litter decomposition and carbon management in Maoer Mountain area by comparing the dynamic changes of DOC and degradation modes of different types of litter under the treatment of degrading agents. 参考文献 相似文献 引证文献

Natural Resource Manager Perceptions of Forest Carbon Management and Carbon Market Participation in Minnesota

Forests and wood products, through the mechanisms of carbon sequestration and storage, can slow the rate of global climate change that results from greenhouse gas emissions. In recent years, both natural resource managers and the public have placed greater focus on the role of forests and wood products as a solution to help mitigate the effects of climate change. Little is known about the perceptions and viability of carbon sequestration and storage as a management goal for natural resource managers of public agencies. We explored these perceptions in Minnesota, USA. Minnesota has 7.2 million hectares of forest land managed by a diverse array of landowners, from public agencies (55% of forest land) to private (45%) owners. We sought to (1) understand natural resource managers’ and forest owners’ perspectives on forest carbon opportunities and (2) understand the feasibility of management strategies that could be implemented to increase forest carbon sequestration and storage at a state level. We conducted two focus groups with 15 mid- and upper-level natural resource managers and non-industrial private forest landowners, representing both rural and urban perspectives and a variety of agencies and organizations. Minnesota natural resource managers and non-industrial private forest landowners indicated that they thought managing forests for carbon was compatible with other management goals but nonetheless represented a trade-off. However, they viewed the carbon credit market as the “Wild West” and noted several barriers to entering the carbon market, such as inconsistent carbon accounting protocols and a lack of connection between the price of carbon credits and the cost of managing forest land for carbon sequestration and storage.

Integrating spaceborne LiDAR and Sentinel-2 images to estimate forest aboveground biomass in Northern China

BackgroundFast and accurate forest aboveground biomass (AGB) estimation and mapping is the basic work of forest management and ecosystem dynamic investigation, which is of great significance to evaluate forest quality, resource assessment, and carbon cycle and management. The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2), as one of the latest launched spaceborne light detection and ranging (LiDAR) sensors, can penetrate the forest canopy and has the potential to obtain accurate forest vertical structure parameters on a large scale. However, the along-track segments of canopy height provided by ICESat-2 cannot be used to obtain comprehensive AGB spatial distribution. To make up for the deficiency of spaceborne LiDAR, the Sentinel-2 images provided by google earth engine (GEE) were used as the medium to integrate with ICESat-2 for continuous AGB mapping in our study. Ensemble learning can summarize the advantages of estimation models and achieve better estimation results. A stacking algorithm consisting of four non-parametric base models which are the backpropagation (BP) neural network, k-nearest neighbor (kNN), support vector machine (SVM), and random forest (RF) was proposed for AGB modeling and estimating in Saihanba forest farm, northern China.ResultsThe results show that stacking achieved the best AGB estimation accuracy among the models, with an R2 of 0.71 and a root mean square error (RMSE) of 45.67 Mg/ha. The stacking resulted in the lowest estimation error with the decreases of RMSE by 22.6%, 27.7%, 23.4%, and 19.0% compared with those from the BP, kNN, SVM, and RF, respectively.ConclusionCompared with using Sentinel-2 alone, the estimation errors of all models have been significantly reduced after adding the LiDAR variables of ICESat-2 in AGB estimation. The research demonstrated that ICESat-2 has the potential to improve the accuracy of AGB estimation and provides a reference for dynamic forest resources management and monitoring.

Soil carbon in the South Atlantic United States: Land use change, forest management, and physiographic context

Evidence-based forest carbon (C) management requires identifying baseline patterns and drivers of soil organic carbon (SOC) stocks, and their responses to land use change and management, at scales relevant to landowners and resource professionals. The growth of datasets related to SOC, which is the largest terrestrial C pool, facilitates use of synthesis techniques to assess SOC stocks and changes at management-relevant scales. We report results from a synthesis using meta-analysis of published studies, as well as two large databases, in which we identify baseline patterns and drivers, quantify influences of land use change and forest management, and provide ecological context for distinct management regimes and their SOC impacts. We conducted this, the fourth in a series of ecoregional SOC assessments, for the South Atlantic States, which are disproportionately important to the national-scale forest C sink and forest products industry in the U.S. At the ecoregional level, baseline SOC stocks vary with climatic, topographic, and soil physical factors such as temperature and precipitation, slope gradient and aspect, and soil texture. Land use change and forest management modestly influence SOC stocks. Reforestation on previously cultivated lands increases SOC stocks, while deforestation for cultivation has the opposite effect; for continuously forested lands, harvesting is associated with SOC increases and prescribed fire with SOC declines. Effects of reforestation are large and positive for upper mineral soils (+30%) but not detectable in lower mineral soils. Negative effects of prescribed fire are due to significant C losses from organic horizons (-46%); fire and harvest have no impacts on upper mineral soils but both increase SOC in lower mineral soils (+8.2 and +46%, respectively, with high uncertainty in the latter). Inceptisols are generally more negatively impacted by prescribed fire or harvest than Ultisols, and covariance between inherent factors (including soil taxonomy) and management impacts indicates how interior vs. coastal physiographic sections differ in their management regimes and SOC trends. In the cooler, wetter, topographically rugged interior hardwood forests, which have larger baseline SOC stocks, prescribed fire and even light harvesting generally decrease SOC; in contrast, intensively managed coastal plain pine plantations begin with small initial SOC stocks, but exhibit rapid gains over even a single rotation. This covariance between place (physiography) and practice (management regime) suggests that distinct approaches to forest C management may be complementary to other ecological or production goals, when implemented as part of wider (e.g., state-level) forest C or climate policy.

Forest carbon incentive programs for non-industrial private forests in Oregon (USA): Impacts of program design on willingness to enroll and landscape-scale program outcomes

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

Fire after clear-cut harvesting minimally affects the recovery of ecosystem carbon pools and fluxes in a Great Lakes forest

Effective forest carbon (C) management requires an understanding of how stand-replacing disturbances affect C pools and fluxes over successional timescales, and how the growth of secondary forests compares with that of undisturbed forests. In the upper Great Lakes region, fires that followed clear-cut harvesting shaped a century-old cohort of secondary forests, but the long-term effects of fire on C cycling in this relatively fire-averse landscape remain poorly understood. We examined how two different stand-replacing disturbances – one with and the other without fire – influenced C pools and fluxes through a century of stand development, comparing secondary aspen-dominated (Populus) forests with legacy late successional stands encompassing the ages and species compositions that would be prevalent today in the absence of stand replacement. Our work at the University of Michigan Biological Station (UMBS) used experimental forest chronosequences established following clear-cut harvesting or clear-cut harvesting followed by fire, along with three > 130-yr-old late successional deciduous broadleaf (DBF), evergreen needleleaf (ENF), and mixed (MIX) forest functional types. The successional trajectories and values of total (above- and belowground) ecosystem C mass, net primary production (NPP), and net ecosystem production (NEP) were similar regardless of whether fires occurred following clear-cut harvesting. Moreover, 80 + year old secondary forests’ C pools and fluxes were comparable to late successional ENF and MIX, but were at times lower than DBF. While the century-old secondary forests and legacy stands served as consistent C sinks over the last century, more extreme temperatures in recent years may be eroding NEP by accelerating C losses from soils. We conclude that the compounding effects of fire and clear-cut harvesting were similar to those from clear-cut harvesting alone, possibly because of the disturbance-adapted properties of pioneer species, most notably aspen; however, our results also suggest that changing climate rather than prior disturbance may jeopardize the future of this long-term terrestrial C sink.

Spatial variation in soil respiration is determined by forest canopy structure through soil water content in a mature beech forest

For accurate estimation of soil respiration (SR) in forest ecosystems, temporal and spatial variation in SR and the factors that control these variations must be considered. Although some of the factors underlying temporal variation in SR have been elucidated in recent decades, a large part of spatial variation in SR remains unexplained especially in forest ecosystems with complex structures. Our objectives were to demonstrate spatial variation in daily summed SR (SRdaily) and to examine if spatial variation in SRdaily can be explained by canopy openness which is one of the indexes of forest structure. We conducted simultaneous measurements of SRdaily, soil temperature (ST), and soil water content (SWC) at 121 points. We also measured canopy openness and some forest stand structure indexes in different seasons in 2012 and 2013. The coefficient of variation (CV) of SRdaily ranged from 25 % to 28 %, which was similar to that of SWC (21 % to 28 %). We also found that the spatial variation in SR in other forest ecosystems ranged widely (CV = 14 % to 62 %), and that in our site fell within the range. There was no significant relationship between ST and spatial variation in SRdaily; however, a significant relationship was observed between SWC and spatial variation in SRdaily (P < 0.01) excepted for the measurement conducted in June 2013. Multiple linear regression analysis indicated that canopy openness showed significant positive correlations with SWC during the growing season. And there was no significant relationships between SWC and forest stand structure indexes.In this study, we found that canopy structure influenced SWC, which in turn determined the spatial variation in SR in this mature beech forest. The possible connections could give us new insight for adequate forest carbon management.

Ageing forests and carbon storage: a case study in boreal balsam fir stands

AbstractThe pattern of change in carbon (C) accumulation with forest ageing can vary greatly amongst different forest types. Documenting how C accumulates in various forest ecosystems in the absence of logging makes it possible to predict what would be the outcome of extending forest rotations or in dedicating more land to conservation on C storage. This study was conducted in boreal balsam fir (Abies balsamea (L.) Mill.) forests of Quebec, in eastern Canada. We compared carbon stocks in forest pools (aboveground (live) biomass, deadwood, FH horizon and mineral soil) of mature (70 years after harvest) vs old-growth stands (stands with no signs or history of human disturbance). Total ecosystem C stocks were not significantly different between mature and old-growth stands. However, as mature stands transition to old-growth stage, there appears to be a shift of C from live biomass pools towards deadwood and soil FH horizons. Coarse woody debris in old-growth stands were also found to be at more advanced stages of decay. The variability of C stocks was also high amongst old-growth stands; however, there was no obvious difference in structural diversity between mature and old-growth stands. Results suggest that ageing balsam fir stands through the lengthening of forest rotations (e.g. past the maturity age of 70 years) or by placing them under conservation, while not creating an important C sink, still contributes to maintain large forest C stocks across landscapes. Preserving or increasing the presence of old-growth forests is an important aspect of ecosystem-based forest management; our study concludes that it could also be compatible with sustainable forest carbon management.

How large is the difference in large-scale forest biomass estimations based on new climate-modified stand biomass models?

Accurate forest carbon service accounting is essential for climate change mitigation. At present, the knowledge about whether and how climate-sensitive stand biomass models could reduce the uncertainty of forest biomass/carbon estimation is lacking. Hence, the aim of this study is to develop climate-sensitive stand biomass models and quantify their differences. Data containing 539 sample plots of larch plantations in northern and northeastern China were utilized to develop two basic and the corresponding climate-sensitive stand biomass models. Owing to the uncertainty from predictors, the forecast combination method was used to combine the two basic models (FCMs) and the two climate-sensitive models (CS-FCMs) and to quantify the difference in biomass estimations at the plot and regional scales. Results showed that the adjusted R2 values of the stand biomass models were greater than 0.85 and the relative root mean square errors ranged from 5.51% to 22.62%. The CS-FCMs produced more accurate biomass estimates than the FCMs. The difference in biomass estimations derived from biomass models with and without climatic variables was 411,549 tons or 0.27% at the regional scale, but the carbon value difference amounted to about $8.3 million. This study underlined the importance of accurate carbon accounting based on climate-modified stand biomass models for forest carbon management.