Forest Carbon Storage Research Articles

Toward high-integrity forest carbon market of ethnic minority groups in Dak Lak province, Vietnam

Forest carbon markets have demonstrated numerous benefits across economic, social, and environmental dimensions, while also advancing sustainable development goals. This study examines the primary policy mechanisms and conditions related to the development of high-integrity forest carbon markets in Dak Lak province, Vietnam. Utilizing a combination of SWOT analysis and the DPSIR framework, the study provides a comprehensive evaluation of the opportunities, challenges, driving forces, pressures, potential impacts, and responses associated with developing these markets. The Gold Standard method was also employed to estimate the potential contribution to carbon emission reductions through the new forest planting programs in the province. Data analysis from 202 households and in-depth interviews with fifteen experts revealed that local residents have limited information about the forest carbon market. While forest management officials at various levels are aware of the market, there is a lack of specific guidance, limited participation in training sessions and workshops, and insufficient instructional materials. Dak Lak holds significant potential for carbon emission reductions, with an estimated average forest carbon storage capacity of 7.5 tCO2/ha/year for an afforestation/reforestation (A/R) carbon project. This initiative is projected to contribute approximately $753,972 annually to the province’s GRDP and generate 280 jobs for local communities. However, the technical and financial resources are challenging in the province. The study identifies critical issues and proposes appropriate solutions to support Dak Lak in developing high-integrity forest carbon markets in alignment with the national roadmap, ultimately contributing to the achievement of sustainable development goals.

Increased microbial carbon use efficiency and turnover rate drive soil organic carbon storage in old-aged forest on the southeastern Tibetan Plateau

Increased microbial carbon use efficiency and turnover rate drive soil organic carbon storage in old-aged forest on the southeastern Tibetan Plateau

The Effect of Transition to Close-to-Nature Forestry on Growing Stock, Wood Increment and Harvest Possibilities of Forests in Slovakia

The aim of the study is to quantify the impacts of a possible transition to close-to-nature forestry in Slovakia and to compare the expected development of the total volume production, growing stock, merchantable wood increment and harvesting possibilities of forests in Slovakia with current conventional management using the FCarbon forest-growth model and available data from the Information System of Forest Management. The subject of the study was all forest stands available for wood supply (FAWS). The simulations were run in annual iterations using tree input data aggregated over 10-year-wide age classes. The calculation of wood increments was based on available growth models. In the business-as-usual (BAU) scenario, stock losses were based on the actual intensity of wood harvesting in the reference period 2013–2022. In the scenario of the transition to close-to-nature forest management, the losses were specifically modified from the usual harvesting regime at the beginning, to the target harvesting mode in selective forest at the end of the simulated period. With the modelling method used, a gradual increase in forest stocks occurred in both evaluated scenarios in the monitored period, namely by 10% in the case of BAU and by 23% in the case of close-to-nature forest management until 2050. In absolute mining volume, CTNF is by 5–10% lower than BAU management, with the difference gradually decreasing. The results show that the introduction of close-to-nature forest management will temporarily reduce the supply of wood to the market, but this reduction will not be significant and will be compensated by a higher total volume production, and thus also by increased carbon storage in forests.

Overlooked branch turnover creates a widespread bias in forest carbon accounting

Most measurements and models of forest carbon cycling neglect the carbon flux associated with the turnover of branch biomass, a physiological process quantified for other organs (fine roots, leaves, and stems). Synthesizing data from boreal, temperate, and tropical forests (184,815 trees), we found that including branch turnover increased empirical estimates of aboveground wood production by 16% (equivalent to 1.9 Pg Cy-1 globally), of similar magnitude to the observed global forest carbon sinks. In addition, reallocating carbon to branch turnover in model simulations reduced stem wood biomass, a long-lasting carbon storage, by 7 to 17%. This prevailing neglect of branch turnover suggests widespread biases in carbon flux estimates across global datasets and model simulations. Branch litterfall, sometimes used as a proxy for branch turnover, ignores carbon lost from attached dead branches, underestimating branch C turnover by 38% in a pine forest. Modifications to field measurement protocols and existing models are needed to allow a more realistic partitioning of wood production and forest carbon storage.

Assessing ensemble models for carbon sequestration and storage estimation in forests using remote sensing data

Forests play a crucial role in storing much of the world's carbon (C). Accurately estimating C sequestration is essential for addressing and mitigating the impacts of global warming. While many studies have used machine learning models to estimate carbon storage (CS) in forests based on remote sensing data, this research further examines C sequestration (i.e., the annual carbon uptake by trees; CSE). The objectives of this study are two-fold: firstly, to identify the best models for estimating CSE and CS by testing various methods, and secondly, to examine the effect of climatic data and the canopy height model (CHM) on the estimation of CSE. To achieve the first objective, we will compare the performance of fourteen models, including twelve machine learning models, one deep learning model, and an ensemble model that combines the top four independent models. For the second objective, we study the effect of four input configurations: the first is a baseline configuration based solely on attributes extracted from satellite images (Sentinel-2) and geomorphology; the second combines satellite features with climatic data; the third uses a CHM derived from LiDAR instead of climatic data; and the fourth combines all available features: satellite images, climatic data, and CHM. The results show that adding climatic data does not improve the estimation of CSE and CS. However, adding CHM features significantly improves the models' performance for both targets. The implemented ensemble model demonstrated the best performance across all configurations.

Carbon sink of forest ecosystems: Concept, time effect and improvement approaches.

The widespread utilization of fossil fuels has emitted large amounts of CO2 into the atmosphere since the Industrial Revolution, leading to climate warming and frequent occurrence of extreme climate events. To effectively alleviate climate change, the international community has made various efforts to reduce carbon emissions and eliminate CO2 from the atmosphere. In 2020, the Chinese government announced that carbon emission peaking and carbon neutrality will be achieved by 2030 and 2060, respectively. According to the current forecast, by the time carbon neutrality is achieved in 2060, even under the minimum conditions of fossil energy use, production, and living emissions, China will still have to emit about 1/4 of the current total emissions. These carbon must primarily be absorbed by ecosystems. Furthermore, approximately 140 ppm increase in CO2 in the atmosphere since the Industrial Revolution still needs to be removed by ecosystems. Forests are the main component of terrestrial ecosystems, contributing more than 80% of the carbon sequestration capacity of all terrestrial ecosystems. However, due to the long periodicity, complexity and dynamic variability of forests, the basic concepts of ecosystem carbon sink and its time effect are still unclear, leading to problems, such as lacking technologies for improving carbon sink capacity and disorganized rules in the carbon sink trading market. In this review, we introduced carbon sink concept according to the processes of absorbing and fixing CO2 by plant photosynthesis in forest ecosystems. Then, we analyzed the processes of time-scale-dependent carbon sinks of forest ecosystems, discussed the time effects of forest carbon sinks, and suggested using "t-year" as the unit of carbon sink (taking 3-6 months as the minimum measurement time, i.e., the beginning of carbon sequestration). Third, we proposed the approaches to improve the carbon sink capacity of forest ecosystems. One way is to improve the carbon sink capacity (expanding forest area, improving forest quality, and increasing forest soil carbon storage) of forest ecosystems. Another approach is to maintain the carbon sink of forest ecosystems as long as possible, i.e., to reduce temporary carbon sink (definition: carbon in the forest ecosystems emit into the atmosphere for a certain period) and to increase persistent carbon sink (definition: carbon in the forest ecosystems no longer emit into the atmosphere for a certain period; according to the relevant provisions of the Paris Agreement, the upper time limit for carbon sink measurement can be considered to be the year 2100. In order to maintain the persistent carbon sink, strateges such as efficient use of wood products (replace steel, cement, plastic with wood), control of forest fires or other disturbances-induced emissions, and turning forest biomass into biochar should be taken. Finally, we proposed to develop climate-smart forestry driven by artificial intelligence (AI), which would provide new theoretical and technical support for improving the carbon sink of forest ecosystems and facilitating sustainable forest management.

Exploring the role of canopy cover and environmental factors in shaping carbon storage in Desa’a forest, Ethiopia

BackgroundDry Afromontane forests play a vital role in mitigating climate change by sequestering and storing carbon, as well as reducing greenhouse gas emissions. Despite previous research highlighting the importance of carbon stocks in these ecosystems, the influence of canopy cover and environmental factors on carbon storage in dry Afromontane forests has been barely assessed. This study addresses this knowledge gap by investigating the effects of environmental factors and vegetation cover on carbon stocks in Desa’a forest, a unique and threatened Afromontane dry forest ecosystem in northern Ethiopia. Data on woody vegetation, dead litter, grass biomass, and soil samples were collected from 57 plots. A one-way analysis of variance (ANOVA) was performed at a 95% confidence level (α = 0.05) to examine the influence of canopy cover and environmental factors on the carbon stocks of various pools.ResultsAmong the 35 woody species identified, Juniperus procera was the most dominant, while Carissa edulis Vahl and Eucalyptus globulus were the least dominant. The average total carbon stock was 92.89 Mg ha−1, with contributions from aboveground carbon, below-ground carbon, litter carbon, grass carbon, and soil organic carbon. Among the carbon pools, soil organic carbon had the highest carbon stock, accounting for 76.8% of the total, followed by above-ground biomass carbon at 17.7%. Significant variations in carbon stocks were found across altitude class and canopy level but not slope and aspect factors.ConclusionsIn summary, altitude and canopy level were found to significantly influence carbon stocks in Desa’a forest, providing valuable insights for conservation and climate change mitigation efforts in dry Afromontane forests. Forest intervention planning and management strategies should consider the influence of different environmental variables and tree canopy levels.

Topography and life stage regulate species aboveground biomass distribution in combination in a tropical montane rainforest.

Understanding the correlation between topography, species biomass and species life stage would allow forest managers to better foster carbon storage in forests. Using census data from a 60-ha plot in south China, we first quantified aboveground biomass (AGB) and how much it varied among different topographies. Next, the specific contribution of 42 dominant species to total aboveground biomass was analyzed for each of the different topographies. We also explored whether these species-topography associations changed, in terms of species' AGB distribution, during each of the three life stages (sapling, juvenile, adult) for these 42 species. Our results showed that the average AGB was 368.79 Mg ha-1 and that it varied noticeably among the four topographies (Low valley, Slope, High valley and Ridge, which were classified by using fuzzy C-mean clustering based on elevation, convexity, and slope). AGB was significantly lower in the two valleys than in the two other topographies. Of the 42 species, 88.1% showed topographic preferences, and 78.6% appeared to exhibit topographic preferences that changed with life stage. Our work highlights the importance of topography and life stage in species biomass distribution and suggests that different combinations of species and life stages, based on species topographic preferences across life stages, may be better suited in different tropical rainforest topographies to maximize carbon storage overall.

Linking forest carbon opportunity costs and greenhouse gas emission substitution effects of wooden buildings: The climate optimum concept

Forests play a crucial role in achieving net-zero greenhouse gas emission targets in the coming decades, as they can act as natural carbon sinks by removing carbon dioxide from the Earth's atmosphere. The use of wood as a building material leads to lower GHG emissions throughout its life cycle compared to other building materials and is therefore considered a valid climate change mitigation strategy. However, the impact of wood harvesting on the potential carbon storage in forests has largely been ignored. In this study, we investigated whether the use of wood as a building material is beneficial for climate change mitigation when considering carbon opportunity costs, which represent the amount of carbon prevented from accumulating in forests due to wood extraction. We introduce the climate optimum concept, which links both GHG emission substitution and associated carbon opportunity cost of wooden buildings. Application of the concept to a case study building shows that the GHG substitution benefits of wooden buildings for climate change mitigation are overshadowed by carbon opportunity costs in forests. In our analysis, no wooden scenario achieves sufficient life cycle embodied GHG emission substitution in order to compensate for the unrealized carbon storage potential in the forest system due to harvest. Wood-based GHG mitigation strategies in the building sector and beyond need to consider this unrealized carbon storage potential of forests expressed via carbon opportunity costs, in order to obtain a more comprehensive picture of the climate impact of forests and wood-based products.

Phosphorus limitation promotes soil carbon storage in a boreal forest exposed to long‐term nitrogen fertilization

AbstractForests play a crucial role in global carbon cycling by absorbing and storing significant amounts of atmospheric carbon dioxide. Although boreal forests contribute to approximately 45% of the total forest carbon sink, tree growth and soil carbon sequestration are constrained by nutrient availability. Here, we examine if long‐term nutrient input enhances tree productivity and whether this leads to carbon storage or whether stimulated microbial decomposition of organic matter limits soil carbon accumulation. Over six decades, nitrogen, phosphorus, and calcium were supplied to a Pinus sylvestris‐dominated boreal forest. We found that nitrogen fertilization alone or together with calcium and/or phosphorus increased tree biomass production by 50% and soil carbon sequestration by 65% compared to unfertilized plots. However, the nonlinear relationship observed between tree productivity and soil carbon stock across treatments suggests microbial regulation. When phosphorus was co‐applied with nitrogen, it acidified the soil, increased fungal biomass, altered microbial community composition, and enhanced biopolymer degradation capabilities. While no evidence of competition between ectomycorrhizal and saprotrophic fungi has been observed, key functional groups with the potential to reduce carbon stocks were identified. In contrast, when nitrogen was added without phosphorus, it increased soil carbon sequestration because microbial activity was likely limited by phosphorus availability. In conclusion, the addition of nitrogen to boreal forests may contribute to global warming mitigation, but this effect is context dependent.

Landsat-based spatiotemporal estimation of subtropical forest aboveground carbon storage using machine learning algorithms with hyperparameter tuning.

The aboveground carbon storage (AGC) in forests serves as a crucial metric for evaluating both the composition of the forest ecosystem and the quality of the forest. It also plays a significant role in assessing the quality of regional ecosystems. However, current technical limitations introduce a degree of uncertainty in estimating forest AGC at a regional scale. Despite these challenges, remote sensing technology provides an accurate means of monitoring forest AGC. Furthermore, the implementation of machine learning algorithms can enhance the precision of AGC estimates. Lishui City, with its rich forest resources and an approximate forest coverage rate of 80%, serves as a representative example of the typical subtropical forest distribution in Zhejiang Province. Therefore, this study uses Landsat remote sensing images, employing backpropagation neural network (BPNN), random forest (RF), and categorical boosting (CatBoost) to model the forest AGC of Lishui City, selecting the best model to estimate and analyze its forest AGC spatiotemporal dynamics over the past 30 years (1989-2019). The study shows that: (1) The texture information calculated based on 9×9 and 11×11 windows is an important variable in constructing the remote sensing estimation model of the forest AGC in Lishui City; (2) All three machine learning techniques are capable of estimating forest AGC in Lishui City with high precision. Notably, the CatBoost algorithm outperforms the others in terms of accuracy, achieving a model training accuracy and testing accuracy R2 of 0.95 and 0.83, and RMSE of 2.98 Mg C ha-1 and 4.93 Mg C ha-1, respectively. (3) Spatially, the central and southwestern regions of Lishui City exhibit high levels of forest AGC, whereas the eastern and northeastern regions display comparatively lower levels. Over time, there has been a consistent increase in the total forest AGC in Lishui City over the past three decades, escalating from 1.36×107 Mg C in 1989 to 6.16×107 Mg C in 2019. This study provided a set of effective hyperparameters and model of machine learning suitable for subtropical forests and a reference data for improving carbon sequestration capacity of subtropical forests in Lishui City.

Enhanced Carbon Storage in Mixed Coniferous and Broadleaf Forest Compared to Pure Forest in the North Subtropical–Warm Temperate Transition Zone of China

Enunciating the carbon storage across various types of forests is a precondition for comprehending forest ecosystem carbon cycling. However, previous studies regarding forest carbon storage were primarily conducted in the general temperature zones, with a limited understanding of carbon storage in different forest types within climate transition zones. In this study, we employed biomass models to explore the carbon storage in three types of natural secondary forests (Pinus armandii forest, Quercus aliena forest, and Q. aliena–P. armandii mixed forest) in the transition zone between the northern subtropical and warm temperate regions of China. Furthermore, we used the variance decomposition analysis and random forest model to determine the key factors influencing carbon storage in three types of natural secondary forests. Our results indicated that the carbon storage of wood and soil layers in the Q. aliena–P. armandii mixed forest was significantly higher than that in the P. armandii and Q. aliena forests. Total carbon storage was ranked as follows: Q. aliena–P. armandii mixed forest (266.09 t/ha) > P. armandii forest (222.89 t/ha) > Q. aliena forest (212.46 t/ha). Our results also revealed that carbon storage of the wood layer was jointly regulated by environmental factors, plant physiological characteristics, and soil properties, while soil carbon storage was mainly affected by soil properties. These results highlight the significant advantages of mixed conifer–broadleaf forests in carbon storage, emphasizing the importance of mixed natural secondary forests in carbon cycling and ecosystem services. This study provides scientific evidence for enhancing forest carbon sink functions and developing forest conservation and management policies to combat climate change.

Review of the Current Status and Development Trend of Global Forest Carbon Storage Research Based on Bibliometrics

Forests are one of the largest terrestrial ecosystems on Earth, absorbing carbon dioxide from the atmosphere through photosynthesis and storing it as organic carbon, thereby mitigating global warming. Conducting bibliometric analysis of forest carbon storage can identify current research trends and hot issues in this field, providing data support for researchers and policy makers. This review article provides a comprehensive bibliometric analysis of global forest carbon storage research, using databases from the Web of Science Core Collection. CiteSpace software (6.2.6 version) was employed to visualize and analyze the data, focusing on key researchers, institutions, and countries, as well as major research themes and emerging trends. The main findings are as follows: (1) Since the 21st century, the publication volume in this field has been increasing, with the United States and China being the top contributors. (2) There is active collaboration among key authors, institutions, and countries, with a notable close-knit network centered around French author Philippe Ciais. This group includes nearly half of the field’s authors and many of them are crucial for advancing research in this field. (3) Cluster and citation burst analyses suggest that future research will focus more on the impact of forest management policies on carbon stocks, with particular attention to the roles of northern temperate forests and mangroves in global carbon storage. These findings provide valuable insights into the current state and future directions of forest carbon storage research. This article is instrumental in elucidating the role of forest ecosystems within the global carbon cycle, evaluating the impacts of anthropogenic activities on forest carbon stocks, and informing the development of effective climate change mitigation strategies.

Potential Carbon Content and Inorganic Carbon Sequestration in the Karst Area of Silokek Geopark, Sijunjung Regency

Climate change caused by increasing greenhouse gas emissions, especially CO2, and deforestation, is an urgent global issue. The REDD+ program initiated by the UN aims to reduce carbon emissions and increase carbon storage in forests. One of the forests that can reserve carbon is the karst area with the ability to reserve carbon dioxide (CO2). This study aims to determine the potential carbon content and carbon dioxide (CO2) sequestration. This study was conducted using the chip sampling method and the XRF (X-ray Fluorescence) method analysis. Based on the research results, it is known that the Silokek Geopark karst area has three different limestone rock characteristics, and sample 3 is the type of rock with the highest CaO percentage. The potential inorganic carbon content is 4,908.07 tons/ha and carbon absorption is 18,012.60 tons/ha, categorized as high. The inorganic carbon content in the Silokek Geopark area is lower than the Biduk-biduk Karst area which is influenced by the area volume area and type of rock composition.

Impact of Nitrogen Fertilizer Application on Soil Organic Carbon and Its Active Fractions in Moso Bamboo Forests

Soil organic carbon (SOC) is a crucial indicator of soil quality and fertility. However, excessive nitrogen (N) application, while increasing Moso bamboo yield, may reduce SOC content, potentially leading to soil quality issues. The impact of N on SOC and its active fraction in Moso bamboo forests remains underexplored. Investigating these effects will elucidate the causes of soil quality decline and inform effective N management strategies. Four N application gradients were set: no nitrogen (0 kg·hm−2·yr−1, N0), low nitrogen (242 kg·hm−2·yr−1, N1), medium nitrogen (484 kg·hm−2·yr−1, N2), and high nitrogen (726 kg·hm−2·yr−1, N3), with no fertilizer application as the control (CK). We analyzed the changes in SOC, active organic carbon components, and the Carbon Pool Management Index (CPMI) under different N treatments. The results showed that SOC and its active organic carbon components in the 0~10 cm soil layer were more susceptible to N treatments. The N0 treatment significantly increased microbial biomass carbon (MBC) content but had no significant effect on SOC, particulate organic carbon (POC), dissolved organic carbon (DOC), and readily oxidizable organic carbon (ROC) contents. The N1, N2, and N3 treatments reduced SOC content by 29.36%, 21.85%, and 8.67%, respectively. Except for POC, N1,N2 and N3 treatments reduced MBC, DOC, and ROC contents by 46.29% to 71.69%, 13.98% to 40.4%, and 18.64% to 48.55%, respectively. The MBC/SOC ratio can reflect the turnover rate of SOC, and N treatments lowered the MBC/SOC ratio, with N1 < N2 < N3, indicating the slowest SOC turnover under the N1 treatment. Changes in the Carbon Pool Management Index (CPMI) illustrate the impact of N treatments on soil quality and SOC sequestration capacity. The N1 treatment increased the CPMI, indicating an improvement in soil quality and SOC sequestration capacity. The comprehensive evaluation index of carbon sequestration capacity showed N3 (−0.69) < N0 (−0.13) < CK (−0.05) < N2 (0.24) < N1 (0.63), with the highest carbon sequestration capacity under the N1 treatment and a gradual decrease with increasing N fertilizer concentration. In summary, although the N1 treatment reduced the SOC content, it increased the soil CPMI and decreased the SOC turnover rate, benefiting soil quality and SOC sequestration capacity. Therefore, the reasonable control of N fertilizer application is key to improving soil quality and organic carbon storage in Moso bamboo forests.

Chronic anthropogenic disturbance causes prolific resprouting and dwarfing – A case study of a widely distributed subtropical tree

Chronic anthropogenic disturbance (CAD) comprises the additive effect of multiple anthropogenic stressors that lead to subtle but continuous alterations to the structure, composition and functioning of natural ecosystems. However, this effect has been little studied at the tree species level. Here, we examined CAD effects on Chinese beech (Fagus engleriana), a common species in northern subtropical forests that utilizes both vegetative resprouting and seeding as regenerative modes. We computed an index of CAD for each plot based on livestock grazing intensity, wood extraction and miscellaneous resource use. Over 60 20 × 20 m plots, we measured the height and DBH of a total of 1261 Chinese beech individuals (21.02 ± 13.06 per plot, [mean ± SD]), including 593 adults (9.88 ± 4.89), 576 saplings (9.60 ± 8.91) and 92 seedlings (1.53 ± 3.91), and assessed the proportions of each that exhibited resprouting (0.91 ± 0.11, 0.69 ± 0.29, and 0.09 ± 0.25, respectively). CAD was associated with a greater number of individual trees and a proliferation of stems, and with a greater proportion of resprouting seedlings, but had no effect on adult-sized stem DBH. Chinese beech thus appears generally tolerant of CAD, which may ultimately result in its increasing contribution to the maintenance of forest biomass. CAD was also associated with shorter adult and sapling stems, but taller resprouting seedling stems, implying that CAD induced dwarfism as Chinese beech matures. Further analysis showed that the proportion of resprouting was related to small scale wood extraction and miscellaneous resource use, but not to grazing. In the context of better understanding cryptic effects of CAD, our findings show that CAD can alter tree morphology and regenerative processes. These coppicing-type effects of CAD on tree morphology structure are typically associated with higher community biodiversity in managed forest coppice, and future work should investigate the biodiversity consequences of CAD at our study site. Our study shows that CAD has important implications for forest resource utilization, planning, and management, with effects on forest biomass and carbon storage in human-modified landscapes.

Experimental warming and drying increase older carbon contributions to soil respiration in lowland tropical forests

Tropical forests account for over 50% of the global terrestrial carbon sink, but climate change threatens to alter the carbon balance of these ecosystems. We show that warming and drying of tropical forest soils may increase soil carbon vulnerability, by increasing degradation of older carbon. In situ whole-profile heating by 4 °C and 50% throughfall exclusion each increased the average radiocarbon age of soil CO2 efflux by ~2–3 years, but the mechanisms underlying this shift differed. Warming accelerated decomposition of older carbon as increased CO2 emissions depleted newer carbon. Drying suppressed decomposition of newer carbon inputs and decreased soil CO2 emissions, thereby increasing contributions of older carbon to CO2 efflux. These findings imply that both warming and drying, by accelerating the loss of older soil carbon or reducing the incorporation of fresh carbon inputs, will exacerbate soil carbon losses and negatively impact carbon storage in tropical forests under climate change.

Association of Carbon Pool with Vegetation Composition along the Elevation Gradients in Subtropical Forests in Pakistan

As the most important way to mitigate climate change, forest carbon storage has been the subject of extensive research. A comprehensive study was carried out to investigate the influence of elevation gradients and diameter classes on the forest growth, composition, diversity, and carbon pools of the Bagh Drush Khel Forest area. Research revealed that elevation gradients significantly influenced the composition, diversity, and carbon pools in forests. At lower elevations, Eucalyptus camaldulensis was the dominant species, with Olea ferruginea as a co-dominant species, whereas at higher elevations, Pinus roxburghii was the dominant species with Quercus incana as a co-dominant species. Regeneration was higher at higher elevations with the maximum number of saplings and seedlings of P. roxburghii. Species diversity association with elevation was negative (R2 = −0.44; p < 0.05—Shannon Index). Soil organic carbon (SOC association with elevation was non-significant while positive with DBH classes (R2 = 0.37; p < 0.05). Overall, carbon pool association with elevation and diameter at breast height (DBH) were negative (R2 = −0.73; p < 0.05) and (R2 = −0.45; p < 0.05). Litter biomass correlated positively with elevation (R2 = 0.25; p < 0.05) and DBH (R2 = 0.11; p < 0.05), while deadwood biomass correlated negatively with elevation gradients (R2 = −0.25; p < 0.05), and no effect was observed for DBH classes. The highest carbon stock (845.89 t C/ha) was calculated at low elevations, which decreased to (516.27 t C/ha) at high elevations. The overall carbon stock calculated was (2016.41 t C/ha) respectively. A total of six tree species were found at the study site. Future research is essential for forest health monitoring and understanding fine-scale impacts. This study offers a methodological framework for similar investigations in unexplored yet potentially significant forest regions worldwide.

China's future forest carbon sequestration potential under different management scenarios

Enhancing forest carbon storage and carbon sequestration capacity is crucial for achieving carbon neutrality. Scientific forest management can maintain a high level of carbon sequestration capacity in forests, and considering the carbon pool of wood products can extend the time of carbon fixation. However, current predictions of large-scale forest carbon storage and carbon sequestration capacity have overlooked changes in forest carbon absorption with forest age and the buffering effect of wood product carbon pools in the carbon release process. In this paper, we used the Forest Simulation and Optimization System model (FSOS) to analyze the wood supply and carbon sequestration capacities of different management scenarios based on data from the Forest Resources Inventory (2014–2018). The results showed that China's forests could export significant amounts of timber in the future; According to the 9th forest survey report, China's forests produce only 88 million m3 yr-1. Among them, the harvested objects were mainly planted forests, and if all forests (planted forests and natural forests) are involved in forest management planning, the maximum sustainable annual wood supply will reach 286 million m3 yr-1. Moreover, due to the current large proportion of younger forests in China, 358 million m3 of annual wood supply will be achievable in the future (as of the year 2039). Forest management can increase the carbon sequestration capacities in forest ecosystems as well as the wood supply compared to the no management options. In summary, the carbon sequestration potential of unmanaged forests is limited. Appropriate forest management can increase the carbon sequestration potential of forests. The substitution of carbon emission reduction of wood products and bioenergy can also greatly reduce the pressure to achieve carbon neutral strategies.

Earthworm influence on soil aggregate distribution and protected carbon at managed forest sites in Vermont, USA

The long-term effect of non-native earthworm species on forest soil carbon storage is not clear. While initial invasion into earthworm-free soils stimulates carbon losses, there is evidence that carbon stabilization in soil aggregates is enhanced. Fourteen managed forest sites throughout Vermont were sampled to identify and enumerate earthworms, and determine soil aggregate distribution and physically protected carbon. Most of these sites were northern hardwoods reforested in the mid-20th century after agricultural land use. Soil at six 50 × 50 cm subplots at each site was sampled to a depth of 20 cm below the Oe horizon and the mineral soil fractionated into free microaggregates (<250 μm), small macroaggregates (250–2000 μm), and large macroaggregates (>2000 μm). Microaggregates were then isolated from the macroaggregates and organic carbon determined. Mean earthworm numbers below the Oe horizon at each site ranged from 0 to 313 individuals m−2 and ten different species were identified, representing all earthworm ecotypes. Four sites had no earthworms in the soil layer sampled, three sites had earthworms in every subplot with up to six different species, and seven sites had subplots both with and without earthworms. When subplots were grouped by number of species present, there was a trend towards a greater fraction of the mineral soil in macroaggregates containing greater protected carbon, and a lower fraction of free microaggregates. A paired t-test of subplots from the seven sites with variable earthworm presence showed significant differences in the same trends and there was significantly greater mineral soil total carbon and protected carbon in the subplots with earthworms. These results are consistent with recent research into earthworm effects on soil carbon stabilization. While initial invasion likely resulted in a negative carbon balance, our findings suggest that earthworms can enhance transfer of carbon into physically protected pools in these forest soils.