Forest Carbon Sequestration Research Articles

Carbon Cycle–Climate Feedbacks in the Post-Paris World

The Paris Agreement calls for emissions reductions to limit climate change, but how will the carbon cycle change if it is successful? The land and oceans currently absorb roughly half of anthropogenic emissions, but this fraction will decline in the future. The amount of carbon that can be released before climate is mitigated depends on the amount of carbon the ocean and terrestrial ecosystems can absorb. Policy is based on model projections, but observations and theory suggest that climate effects emerging in today's climate will increase and carbon cycle tipping points may be crossed. Warming temperatures, drought, and a slowing growth rate of CO2 itself will reduce land and ocean sinks and create new sources, making carbon sequestration in forests, soils, and other land and aquatic vegetation more difficult. Observations, data-assimilative models, and prediction systems are needed for managing ongoing long-term changes to land and ocean systems after achieving net-zero emissions. ▪International agreements call for stabilizing climate at 1.5° above preindustrial, while the world is already seeing damaging extremes below that.▪If climate is stabilized near the 1.5° target, the driving force for most sinks will slow, while feedbacks from the warmer climate will continue to cause sources.▪Once emissions are reduced to net zero, carbon cycle-climate feedbacks will require observations to support ongoing active management to maintain storage.

Tropical forest above‐ground productivity is maintained by nutrients cycled in litter

Abstract Tropical forest productivity represents an important global carbon sink, but many tropical forests grow on infertile soils. Efficient nutrient cycling by litterfall has long been assumed to maintain tropical tree growth, but there is no direct evidence that the nutrients cycled in litterfall are essential for tropical forest productivity. To test whether nutrient cycling by litterfall maintains tropical forest above‐ground productivity, we established large‐scale long‐term litter removal (L−) and litter addition (L+) treatments in a mature lowland tropical forest. We hypothesised that the removal of nutrients in litter would reduce tree growth, survival and litter production in L− plots. By contrast, the addition of nutrients in litter would enhance tree growth, survival and litter production in L+ plots. To test our hypotheses, we recorded tree growth and survival every 2 years, and measured litterfall monthly during 17 years of treatments. Tree growth and litterfall declined over time in L− plots, with consistently lower growth rates compared to controls after 8 years, and lower litter production after 4 years of treatments. By contrast, although litterfall was higher in the L+ plots relative to the controls, there was only a minor transient increase in tree growth immediately after the start of treatments. Tree survival declined over time in all treatments but was not affected by litter manipulation. The long‐term decline in tree growth and litterfall in the L− plots provides the first empirical evidence that nutrient cycling by litterfall plays a key role in maintaining above‐ground productivity in this tropical forest. By contrast, the transient increase in growth in the L+ plots can be attributed to the large inputs of nutrients with the addition of the entire litter standing crop at the start of treatments. The addition of nutrients in litter over the long term was nonetheless sufficient to enhance litter production, possibly by accelerating leaf turnover. Synthesis: Efficient nutrient cycling by litterfall makes an important contribution to the annual nutrient requirements of mature tropical forest trees, compensating for infertile soils. Disturbances that disrupt this finely balanced cycle could therefore reduce biomass carbon sequestration in tropical forests.

A regime shift between soil moisture and temperature in the 1950s over the permafrost region of Northeast China

AbstractPermafrost is one of the essential carbon pools in the world. Due to limited studies on historical soil moisture changes and the coupling relationship between soil moisture and temperature in permafrost regions, significant uncertainty exists in the carbon loss in permafrost predicted by different models under global warming scenarios. Based on the tree‐ring width chronology of Pinus sylvestris var. mongholica Litv. growing in the southern edge of the Eurasian continuous permafrost zone, we reconstructed the summer (June–September) 0–1 m soil moisture variations from 1705 to 2009, which could explain 45.6% of the variance in the observed soil moisture. Overall, local precipitation and temperature exhibited statistically significant positive feedback (p < 0.001) to soil moisture before the 1950s, indicating that the warm/humid climate pattern was conducive to soil moisture conservation before the Anthropocene Epoch. However, the effect of temperature on soil moisture has shifted suddenly to negative since the 1950s, implying that the positive soil moisture‐temperature relationship during the past three centuries has been disrupted by the unprecedented warming in the Modern Warm Period. Furthermore, we found that the temporal relationship of the soil moisture‐temperature (15‐year sliding correlation) in the study area is negatively regulated by the global mean temperature variations (p < 0.01). The regime shift between soil moisture and temperature might be attributed to the superimposed influence of natural and anthropogenic factors since the 1950s. Although the warming leads to the melting of the permafrost layer, and thus the increase in soil moisture content, the enhanced evapotranspiration caused by warming up results in more water loss and drier soil. This study provides historical evidence of shifted soil moisture‐temperature coupling in the permafrost zone, warning that soil moisture in the permafrost region may further decline under global warming scenarios, thereby affecting vegetation growth and forest carbon sequestration potential.

Aboveground carbon sequestration of Cunninghamia lanceolata forests: Magnitude and drivers

Understanding the spatial variation, temporal changes, and their underlying driving forces of carbon sequestration in various forests is of great importance for understanding the carbon cycle and carbon management options. How carbon density and sequestration in various Cunninghamia lanceolata forests, extensively cultivated for timber production in subtropical China, vary with biodiversity, forest structure, environment, and cultural factors remain poorly explored, presenting a critical knowledge gap for realizing carbon sequestration supply potential through management. Based on a large-scale database of 449 permanent forest inventory plots, we quantified the spatial-temporal heterogeneity of aboveground carbon densities and carbon accumulation rates in Cunninghamia lanceolate forests in Hunan Province, China, and attributed the contributions of stand structure, environmental, and management factors to the heterogeneity using quantile age-sequence analysis, partial least squares path modeling (PLS-PM), and hot-spot analysis. The results showed lower values of carbon density and sequestration on average, in comparison with other forests in the same climate zone (i.e., subtropics), with pronounced spatial and temporal variability. Specifically, quantile regression analysis using carbon accumulation rates along an age sequence showed large differences in carbon sequestration rates among underperformed and outperformed forests (0.50 and 1.80 ​Mg⋅​ha−1·yr−1). PLS-PM demonstrated that maximum DBH and stand density were the main crucial drivers of aboveground carbon density from young to mature forests. Furthermore, species diversity and geo-topographic factors were the significant factors causing the large discrepancy in aboveground carbon density change between low- and high-carbon-bearing forests. Hotspot analysis revealed the importance of culture attributes in shaping the geospatial patterns of carbon sequestration. Our work highlighted that retaining large-sized DBH trees and increasing shade-tolerant tree species were important to enhance carbon sequestration in C. lanceolate forests.

Forest carbon sequestration on the west coast, USA: Role of species, productivity, and stockability.

Forest ecosystems store large amounts of carbon and can be important sources, or sinks, of the atmospheric carbon dioxide that is contributing to global warming. Understanding the carbon storage potential of different forests and their response to management and disturbance events are fundamental to developing policies and scenarios to partially offset greenhouse gas emissions. Projections of live tree carbon accumulation are handled differently in different models, with inconsistent results. We developed growth-and-yield style models to predict stand-level live tree carbon density as a function of stand age in all vegetation types of the coastal Pacific region, US (California, Oregon, and Washington), from 7,523 national forest inventory plots. We incorporated site productivity and stockability within the Chapman-Richards equation and tested whether intensively managed private forests behaved differently from less managed public forests. We found that the best models incorporated stockability in the equation term controlling stand carrying capacity, and site productivity in the equation terms controlling the growth rate and shape of the curve. RMSEs ranged from 10 to 137 Mg C/ha for different vegetation types. There was not a significant effect of ownership over the standard industrial rotation length (~50 yrs) for the productive Douglas-fir/western hemlock zone, indicating that differences in stockability and productivity captured much of the variation attributed to management intensity. Our models suggest that doubling the rotation length on these intensively managed lands from 35 to 70 years would result in 2.35 times more live tree carbon stored on the landscape. These findings are at odds with some studies that have projected higher carbon densities with stand age for the same vegetation types, and have not found an increase in yields (on an annual basis) with longer rotations. We suspect that differences are primarily due to the application of yield curves developed from fully-stocked, undisturbed, single-species, "normal" stands without accounting for the substantial proportion of forests that don't meet those assumptions. The carbon accumulation curves developed here can be applied directly in growth-and-yield style projection models, and used to validate the predictions of ecophysiological, cohort, or single-tree style models being used to project carbon futures for forests in the region. Our approach may prove useful for developing robust models in other forest types.

The effects of environmental factors and plant diversity on forest carbon sequestration vary between eastern and western regions of China

Forest ecosystems play a crucial role in global carbon sequestration, with the majority of forest carbon being stored in biomass. However, it remains unclear at the national scale to what extent forest biomass depends on soil and climatic conditions, as well as tree species diversity. In this study, we identified and grouped these factors using a classical geographical dividing line, the Hu-line, which divides China into East and West regions characterized by obvious differences in natural conditions and vegetation distribution. We assessed the possible effects of forest species diversity, climatic conditions, and soil environment on the magnitude of forest biomass and carbon sequestration potential by integrating China's 2009–2018 forest inventory data with environmental information. We tested these effects using a structural equation model. Forest biomass was mainly influenced by environmental factors in the West (effect sizes soil N, soil pH, soil P, mean annual precipitation and temperature: −0.50, 0.41, 0.10, 0.04, 0.34) and by species diversity in the East (effect sizes −0.26 and 0.44 in the west and east, respectively). Our results demonstrated the non-negligible influence of forest species diversity on forest biomass. Therefore, through a comprehensive consideration of the interactions between climate, soil, and water resource availability, forest management and cleaner production plans will assist policymakers in designing a rational framework for future forest conservation measures.

Pursuing the goal of carbon neutrality in china: path for realization of carbon sequestration in planted forests

Pursuing the goal of carbon neutrality in china: path for realization of carbon sequestration in planted forests

Assessment of land use cover changes, carbon sequestration and carbon stock in dry temperate forests of Chilas watershed, Gilgit-Baltistan

Abstract Land use and land cover change are affecting the global environment and ecosystems of the different biospheres. Monitoring, reporting and verification (MRV) of these changes is of utmost importance as they often results in several global environmental consequences such as land degradation, mass erosion, habitat deterioration as well as micro and macro climate of the regions. The advance technologies like remote sensing (RS) and geographical information system (GIS) are helpful in determining/ identifying these changes. In the current study area, changes in carbon stocks, notably in forest areas, are resulting in considerable dynamics of carbon stocks as a result of climate change and carbon sequestration. This study was carried out in the Diamer district of the Gilgit Baltistan (GB) Pakistan to investigate the change in cover change/land use change (particularly Forest Land use) as well as carbon sequestration potential of the forests in the district during almost last 25years. The land cover, temporal Landsat data (level 1, LIT) were downloaded from the USGS EROS (2016), for 1979-1989, 1990-2000 and 2001-2012. Change in land uses, particularly forest cover was investigated using GIS techniques. Forest inventory was carried out using random sampling techniques. A standard plot of size 0.1 ha (n=80) was laid out to determine the tree density, volume, biomass and C stocks. Simulation of C stocks was accomplished by application of the CO2FIX model with the data input from inventory. Results showed a decrease in both forest and snow cover in the region from 1979-2012. Similarly decrease was seen in tree volume, tree Biomass, dynamics of C Stocks and decrease was in occur tree density respectively. It is recommended we need further more like project such as BTAP (Billion Tree Afforestation Project) and green Pakistan project to increase the forest cover, to control on land use change, protect forest ecosystem and to protect snow cover.

Effects of a Forest Carbon Sequestration Project on Grassroots Democracy in China

Effects of a Forest Carbon Sequestration Project on Grassroots Democracy in China

Carbon reserves in deltaic mangroves of the Colombian Pacific across different disturbance degrees

Mangrove forests occupy less than 1% of tropical forest areas, but account for approximately 3% of global tropical forest carbon sequestration and act as a natural atmospheric CO2 sequestration mechanism, which gives them an important role in climate change mitigation. However, different anthropogenic disturbances continue to negatively impact the structure and function of mangrove ecosystems; therefore, it is important to investigate the effect of specific anthropogenic alterations on the capacity of mangroves to store carbon. The present study aimed to test the hypothesis of a direct relationship between the degree of anthropogenic intervention and the reduction of mangrove carbon stocks. Eight edge forest types with different degrees of anthropogenic intervention and multiple uses were selected. Six 100 m2 plots were established in each forest to determine its structure and evaluate the concentration of sedimentary organic carbon and biomass. The anthropogenic disturbance index (ADI) was used to quantify the degree of specific disturbances in the studied forests. The results supported the proposed hypothesis, showing that the mangroves with the highest anthropogenic disturbance measured through the ADI registered the lowest values in blue carbon. However, it is evident that in addition to anthropogenic disturbances, impacts such as coastal erosion pose a very important threat to some of these forests. Estimated organic carbon losses in the study area were between 8.4% and 49.3%, corresponding to 158 and 929 Mg CO2 eq ha−1, respectively. Logging is one of the main disturbances that affects forests differently according to their structural development. Forests with higher structural development are subject to greater pressure. Carbon losses from logging are not only reflected in aboveground carbon, but are also evident in sedimentary carbon.

Incorporating high-resolution climate, remote sensing and topographic data to map annual forest growth in central and eastern Europe

To enhance our understanding of forest carbon sequestration, climate change mitigation and drought impact on forest ecosystems, the availability of high-resolution annual forest growth maps based on tree-ring width (TRW) would provide a significant advancement to the field. Site-specific characteristics, which can be approximated by high-resolution Earth observation by satellites (EOS), emerge as crucial drivers of forest growth, influencing how climate translates into tree growth. EOS provides information on surface reflectance related to forest characteristics and thus can potentially improve the accuracy of forest growth models based on TRW. Through the modelling of TRW using EOS, climate and topography data, we showed that species-specific models can explain up to 52 % of model variance (Quercus petraea), while combining different species results in relatively poor model performance (R2 = 13 %). The integration of EOS into models based solely on climate and elevation data improved the explained variance by 6 % on average. Leveraging these insights, we successfully generated a map of annual TRW for the year 2021. We employed the area of applicability (AOA) approach to delineate the range in which our models are deemed valid. The calculated AOA for the established forest-type models was 73 % of the study region, indicating robust spatial applicability. Notably, unreliable predictions predominantly occurred in the climate margins of our dataset. In conclusion, our large-scale assessment underscores the efficacy of combining climate, EOS and topographic data to develop robust models for mapping annual TRW. This research not only fills a critical void in the current understanding of forest growth dynamics but also highlights the potential of integrated data sources for comprehensive ecosystem assessments.

Multi-objective optimisation model of a low-cost path to peaking carbon dioxide emissions and carbon neutrality in China

A low-cost path system for achieving carbon neutrality in China was modelled using multi-objective programming by integrating industrial production, electric power, heating, transportation, and forest carbon sequestration. We aimed to minimise the total system cost, CO2 emissions, and air pollutants. The constraints included China's targets of peaking CO2 emissions before 2030; achieving carbon neutrality before 2060; ensuring industry, power, heating, and transportation supplies; promoting green energy; and implementing emission control. The model accounted for industries with high coal consumption, such as steel and chemical industries. Various power sources were considered, including coal-fired, nuclear, wind, and solar energy. Forest carbon sink and carbon capture and storage technologies were employed to achieve the emission reduction goals. The model, which was validated using available research data, offered cost-effective path schemes and exhibited high validity. Our findings emphasise the importance of structural adjustments and emission control, with electric power, heating, and transportation sectors showing higher feasibility and providing greater contributions to achieving carbon neutrality than other industries. Conversely, industrial transformation in sectors such as iron and steel, chemical, and construction materials had low feasibility and limited contribution. The modelling outcomes provide valuable insights for developing low-cost, carbon emission-targeted transportation structures in China's complex system. The results presented here demonstrate the global applicability of this method in contributing to plans aimed at meeting key carbon reduction targets.

FOREST LITTER PRODUCTION VARIES WITH SEASON AND ELEVATION GRADIENT IN CHIAPAS, MEXICO

<p><strong>Background.</strong> Forest litterfall is a fundamental process of ecosystem nutrient cycling, also, it is a source of energy for the development and propagation of wildfire. Understanding the temporal dynamics of litter production and storage is critical for sustainable management and conservation of forest ecosystems. <strong>Objective. </strong>To quantify<strong> </strong>the monthly production and storage of forest litter in an elevation gradient. <strong>Methodology.</strong> We selected forest sites at three elevations: 670, 775, and 1010 masl, corresponding to pine, oak, and tropical lowland forest ecosystems in Nambiyugua hill, Chiapas, Mexico. Sixteen sampling sites with a radius of 11.28 m were established for tree measurements, and 48 litter traps of 0.50 m<sup>2 </sup>were installed to collect monthly litterfall for a year. To sample ground litter eight 30 by 30 cm<sup>2</sup> quadrats were used in each site. The fallen woody material was measured with the planar intersection method. Litter samples were oven-dried at 60 °C for 72 h and separated into leaves and other plant parts. One-way ANOVA was used to test the significant differences between forests.<strong> Results.</strong> The highest total loads of litter and fallen woody material were obtained in the pine forests of upper elevation with 29.01 t ha<sup>-1</sup>. The highest litter production was obtained in January and April, with a mean of 1.34 ± 0.19 and 0.74 ± 0.13 t ha<sup>-1</sup> respectively in pine forests. In the oak forest, the highest production occurred in March, with 1.08 ± 0.25 t ha<sup>-1</sup>; while the lowland forest reached the highest production in January with 0.85 ± 0.26 t ha<sup>-1</sup>, with a decreasing trend in June. <strong>Implications.</strong> Understanding the seasonal variability in litter production and forest fuel loads is crucial for forest productivity, carbon sequestration, and wildfire prevention <strong>Conclusions.</strong> The production of forest fuels was different among the ecosystems representing the elevation gradients. The highest monthly production of litter was registered during the January-May period for the pine and oak ecosystems but in November - January in tropical lowland forests.</p>

Cost Valuation and Climate Mitigation Impacts of Forest Management: A Case Study from Piatra Craiului National Park, Romania

With the intensification of the effects of climate change, the urgent need to address their drivers, especially greenhouse gas emissions, has become essential. In this context, forests offer a robust solution, with their potential to store and mitigate carbon emissions. However, striking a balance is critical given the significant economic contribution of the forestry and wood-based industries, which account for about 5% of Romania’s GDP and employ 6% (around 300 thousand) of its active workforce. This study, conducted in the Piatra Craiului National Park located in Romania’s Southern Carpathians, we utilize the EFISCEN application to generate three distinct 50-year forest evolution scenarios based on harvest intensity, namely Business As Usual (BAU), Maximum Intensity (MAX), and No Harvest (MIN), on two historical different managed forests, i.e., conservation and production. The study aims to guide forest owners in decision making with scenario modeling tools, with the objectives of assessing the forest carbon sequestration potential and evaluating the economic feasibility. In the most probable scenario, the BAU scenario, the growing stock increases from 2.6 million m3 to 3.8 million m3 over 50 years, with a more than 40% increase. Comparing the carbon stock change for all tree harvest scenario types indicates that the MIN scenario has the highest carbon sink capacity in the next 50 years; the BAU scenario is a well-balanced option between carbon sink and wood provision and has an optimal EUR 3.7 million in annual revenue. The MAX scenario can boost the growth and increase the annual revenue from wood by 35% but is effective only for a short time and thus has the smallest calculated revenue in time. Achieving a win–win relationship between carbon sequestration and wood supply is imperative, as well as good planning and scenarios to contribute to climate mitigation and also as provisions for local communities and to sustain the local economy.

“Forest carbon sequestration mapping and economic quantification infusing MLPnn-Markov chain and InVEST carbon model in Askot Wildlife Sanctuary, Western Himalaya”

Due to the expeditious rise in anthropogenic activities and rapid extractive pressure, protected areas in the Indian Himalayan Region (IHR) are experiencing significant losses in ecological diversity and a substantial decline in the potential for carbon sequestration and climate change mitigation. The quantification of carbon sequestration and the understanding of its corresponding economic gain/loss are crucial for raising strict preservative concerns in protected areas with rich ecological and economic values. Transitions in land use land cover (LULC) trajectories from historical to future scenarios impact the dynamics of carbon storage and sequestration in terrestrial ecosystems. The present study extends a comprehensive 40-year (1995–2035) assessment of carbon mapping (gain/loss) as well as an economic approximation of carbon sequestration in the Askot Wildlife Sanctuary (AWLS), Western Himalaya, using satellite data. This investigation presents a novel hybrid approach by infusing machine learning algorithms and a spatial-temporal technique-based MLPnn-Markov chain model for future LULC simulation with the InVEST model that incorporates carbon mapping and economic valuation. The results show that among all the land use classes, dense forest has the highest carbon density; however, it exhibits a decreasing trend from 1995 (5,695,878.41 Mg/ha) to 2035 (4,378,439.81 Mg/ha). The economic quantification of carbon sequestration was performed by applying sensitivity analysis combined with different carbon prices and discount rates from 2020 to 2035. The observed outcomes reveal significant economic losses due to rapid forest cover decline, as indicated by a negative net present value (NPV) ranging from a minimum of ∼US$ -8 million to a maximum of ∼US$ -53 million. This study develops a valuable database by providing evidence-based decision-making and guidance for the sustainable preservation of ecosystems in the Western Himalayas and similar regions worldwide, where forest carbon sequestration is of paramount importance. The findings of the study suggest sound provisions for the conservation of forested landscapes and the development of efficient voluntary and regulatory carbon trading markets to achieve stability in forest carbon stocks. In doing so, this interdisciplinary approach addresses the growing imperative of integrating ecological and economic aspects in the context of biodiversity conservation and climate change mitigation.

Carbon Sequestration Through Forestry: A Differential Equation Approach

Carbon sequestration through forestry represents a promising approach to partially counteract anthropogenic greenhouse gas emissions driving climate change. Tree growth naturally removes carbon dioxide from the atmosphere, storing it as biomass. Sustainably managed forests can effectively function as carbon sinks. However, determining optimal forestry policies involves balancing complex ecological dynamics with economic constraints. This study develops differential equation models quantitatively capturing forest growth, timber harvesting, and carbon sequestration dynamics. Logistic models are first adapted to simulate biomass accumulation of representative tree species. Lifecycle growth patterns spanning juvenile to mature phases are incorporated, along with climate effects. Biomass levels are proportionally related to carbon dioxide removal rates from the atmosphere. Deforestation impacts are analyzed by incorporating harvesting-induced biomass reductions. Sustainability constraints are implemented to ensure minimum viable tree densities across harvest rotations. Optimization techniques then identify management guidelines maximizing economic returns given ecological stability considerations. The goal is providing quantitative insights into rotation lengths, planting densities, and allowable cuts upholding both climate change mitigation and commercial demands. Findings can inform science-based forestry policies to leverage forests as sustainable natural carbon sinks.

Identification of potential forest thinning locations to mitigate water deficits in drylands

AbstractAppropriate forest thinning measures can mitigate the conflicting relationship between past excessive afforestation and current increasing regional water deficiency in dryland ecosystems. However, since blind intervention in forest landscapes may incur additional economic costs and cause the loss of ecosystem services, forest thinning in drylands mostly exists in scientific discussions and is seldom implemented in reality. In this study, we propose an advanced technical route to predict the spatial arrangement of potential forest thinning locations under different policy scenarios. Taking Shanxi Province in China as a case study, we simulated eight policy scenarios for different stakeholders to assess the benefits and costs after forest thinning in the future. The results show that a water deficit of 533 million m3 exists in Shanxi Province that could potentially be mitigated by means of forest thinning. Under different policy scenarios, the thinned area ranged from 1142.91 to 1195.47 km2, which would result in an additional soil loss of 1.77–3.02 million m3/year and a loss of carbon sequestration of 3.15–3.24 million t/year. Considering both soil conservation and food security scenarios can help minimize the direct costs and loss of forest carbon sequestration capacity and maintain a sustainable landscape pattern. The method can be used as a decision support tool to identify the potential locations of forest thinning and resulting consequences under water scarcity conditions in drylands and to support stakeholders in making scientific adaptive forest landscape optimization decisions.

Temporal and Spatial Changes and Trend Predictions of Forest Carbon Sequestration Efficiency in China Based on the Carbon Neutrality Goal

Forestry’s high-quality development is crucial for China’s sustainable ecological, economic, and social progress. To elevate the efficiency of carbon sequestration in forestry, continuously improve the increment of carbon sinks, and contribute to achieving carbon neutrality, it is crucial to accurately assess the level of carbon sequestration efficiency in China’s forestry and explore its long-term evolution trend. In this paper, a super-efficiency SBM model, which combines the SBM model with the super-efficiency method and considers the relaxation variables, was selected to evaluate the forestry carbon sequestration efficiency of 31 provinces in China; likewise, the temporal development features of the efficacy of Chinese forests in sequestering carbon were examined using the nuclear density estimation method. Secondly, the study constructed traditional and spatial Markov probability transfer matrices to further explore the spatiotemporal evolution of carbon sequestration efficiency within Chinese forestry. Finally, combined with the Markov chain infinite distribution matrix, the future trajectory of carbon sequestration efficiency in China’s forestry was scientifically forecasted. The findings indicate that: (1) The average carbon sequestration efficiency of forestry in China showed a stable increase with fluctuations and reached the optimal state in 2018. The carbon sequestration efficiency level of various forest regions was always portrayed as southwest forest region > southern forest region > northeast forest region > northern forest region. From 2003 to 2018, there were significant differences in forestry carbon sequestration efficiency among provinces. The distribution of forestry carbon sequestration efficiency exhibited a “three-pillar” distribution pattern with Xizang, Zhejiang, and Heilongjiang as the core, and the marginal regions continuously promoted the carbon sequestration efficiency to the inland. (2) The type of transfer of forestry carbon sequestration efficiency in China is stable, and it is difficult to achieve cross-stage transfer in the short term. Moreover, the forestry carbon sequestration efficiency of each province tended to converge to a high (low) level over time, showing a “bimodal distribution” of low efficiency and high efficiency, indicating the existence of the obvious “club convergence phenomenon”. (3) Forecasting from a long-term evolution trend perspective, the outlook for the future evolution of forestry carbon sequestration efficiency in China is optimistic, and the overall trend was concentrated in the high-value area. Therefore, future forestry development in China should contemplate both internal structure optimization and coordinated regional development. Attention should be placed on forestry carbon sequestration’s role while considering the distinctive endowments of each region and developing reasonable, differentiated, and collaborative forestry management strategies.

Assessment of Carbon Sequestration in Private Forests across Two Different Physiographic Regions of Nepal: Implications for Conservation and Climate Change Mitigation

Private forests offer diverse ecosystem services, including carbon sequestration and biodiversity conservation, which are crucial for Nepal. However, there is a notable absence of comprehensive research on these services. Assessing carbon sequestration in private forests can have economic advantages for forest owners by promoting resource conservation and contributing to greenhouse gas reduction. This study aims to estimate and compare carbon stocks in private forests located in two distinct physiographic regions of Nepal while also identifying the factors influencing these carbon stocks. The analysis focuses on 16 private forests (with 0.1 to 0.5 hectares) each from Chitwan district (Terai region) and Kavrepalanchok district (Hilly region). Field data collection involved direct measurements of tree and sapling diameter at breast height (DBH), as well as height and class of trees and poles, utilizing a total enumeration method. These collected values were utilized to calculate aboveground biomass (AGTB), aboveground sapling biomass (AGSB), belowground biomass, and carbon stock. Private forests of Terai region were dominated by Shorea borneensis, Tectona grandis, and Dalbergia sissoo, whereas the Hilly region was dominated by Pinus patula, Alnus nepalensis, Schima wallichii, and Quercus leucotrichophora. The aboveground biomass carbon in the Terai region’s private forests was estimated to be 83.53 t·ha−1, while in the Hilly region, it was 37.32 t·ha−1. The belowground biomass carbon in the Terai region’s private forests was found to be 21.72 t·ha−1, compared to 9.70 t·ha−1 in the Hilly region. Consequently, the estimated total carbon stock in the Terai and Hilly regions’ private forests was 105.25 t·ha−1 (386.26 t·ha−1 CO2-eq) and 47.02 t·ha−1 (172.57 t·ha−1 CO2-eq), respectively. Carbon sequestration in the Terai region’s private forests was discovered to be 2.24 times higher than that in the Hilly region. These findings underscore the significant potential of private forests, which can generate economic benefits through carbon trading and leverage mechanisms such as REDD+/CDM to promote sustainable conservation practices.

A new index integrating forestry and ecology models for quantitatively characterizing forest carbon sequestration potential ability in a subtropical region

Due to the important role of forests in carbon neutrality, it is a big task in accurately calculating and predicting forest carbon storage and carbon sink capacity in recent years. However, considering the factors on the capacity of forest carbon sequestration, ecologists and foresters consider different models to evaluate the forest carbon sink ability at different scales, with foresters focusing more on forest growth models, while ecologists adding more climate and environmental factors, which may result in inconsistent results in carbon storage. Therefore, constructing an integrated model by combining the forestry and ecology models is essential for accurately quantifying and characterizing the forest carbon sink potential at the regional scale. Here, we proposed a new forest carbon sink potential index (FCSPI), which is defined as fractional deficiency of the current forest carbon to its maximum level, based on forest permanent plots, climate, and edaphic data to evaluate the forest sink potential ability from stand level to zonal scale across the northern subtropical zone in Hubei province, China, which coupled the stand growth model and climate-productivity model. The results at stand level showed that the R2 and RMSE of FCSPI were 0.78 and 0.072 respectively, which indicated that the FCSPI is an intuitive, highly practical, straightforward, easy, and rapid to implement methodology for forest carbon sequestration assessment. Moreover, FCSPI can conveniently extended from stand scale to zonal scale based on the site quality index for carbon sink (SIC) and stand age variables, which were derived from the opened climate, edaphic, and topographic data. The results of wall-to-wall FCSPI across the subtropical forest in Hubei province reveal the current and future carbon potential sequestration, which can help managers to focus on forest management for climate-smart actions and planning in forest ecosystem services framework.