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Background: It is always a challenging job to compare forest resources as there is not a standardized spatial unit with location information. Google Plus Code, the newest alphanumeric geocoding system, uses 20 specifically selected letters and numbers to assign a unique global ID to every cell at different levels of a hierarchical grid system which is established based on latitude and longitude. It can be used as a standardized, unique global geospatial unit to segment, locate, quantitate, evaluate, and compare natural resources with area, boundary, and location information embedded. Results: For this proof-of-concept case study, forest inventory data from 1987, 2002, and 2019 for the Zijin Mountain National Forest Park in Jiangsu Province, China was analyzed based on Google Plus Code grid/cell. This enabled the quantification of carbon storage at each cell allowing for the comparison of estimated carbon storage at same or different locations over time. Conclusions: This methodology is used to quantify the impacts of changing forest conditions and forest management activities on carbon storage with high spatial accuracy through the 32-year study period. Furthermore, this technique could be used for providing technical support and validation of carbon credit quantification and management. [ABSTRACT FROM AUTHOR]

Harvested wood/bamboo products (HWP/HBP) constitute a large global carbon stock. However, the contribution of HBP to carbon stocks has been neglected in mixed wood and bamboo data, especially in China. Therefore, the production approach and the first-order decay method were used to estimate the spatiotemporal carbon stock change in HWP/HBP based on provincial production data from the China Forestry Statistical Yearbooks for 1987–2020. The results showed that China's total carbon stocks of HWP and HBP were 328.7 teragram carbon (TgC) and 129.7 TgC between 1987 and 2020. Of this, the HWP carbon stock was mainly sourced from three provinces across the north and south: Guangxi (60.8 TgC), Heilongjiang (37.2 TgC), and Fujian (24.2 TgC), and HBP carbon stock was mainly sourced from three southern provinces: Fujian (33.4 TgC), Guangxi (20.3 TgC), and Zhejiang (13.7 TgC). The proportion of the HBP carbon stock in the total carbon stock increased from 20% in 2010 to 28% in 2020, indicating that bamboo products play an important role in the accumulation of carbon stocks in China. The differences in contributions to spatiotemporal trends between the provinces provide more specific information to make precise decisions about forest management and carbon sequestration. [ABSTRACT FROM AUTHOR]

Due to a series of human activities like deforestation and land degradation, the concentration of greenhouse gases has risen significantly. Forest vegetation is an important part of forest ecosystems with high carbon sequestration potential. Estimates of the carbon sequestration rate of forest vegetation in various provinces and districts are helpful to the regional and global Carbon cycle. How to build an effective carbon sequestration potential model and reveal the spatiotemporal evolution trend and driving factors of carbon sequestration potential is an urgent challenge to be solved in carbon cycle simulation and prediction research. This study characterized the carbon sequestration status of forest vegetation using the modified CASA (Carnegie-Ames Stanford Approach) model and estimated the carbon sequestration potential from 2010 to 2060 using the FCS (Forest Carbon Sequestration) model combined with forest age and biomass under the four future Shared Socioeconomic Pathways (SSP) scenarios: SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5, then proposes natural, social, and economic perspectives. This study found that the average NPP of the forest vegetation in Chongqing from 2000 to 2020 was 797.95 g C/m2, and the carbon storage by 2060 was 269.94 Tg C. The carbon sequestration rate varied between <0.01 Tg C/a and 0.20 Tg C/a in various districts and counties. Over time, forest growth gradually slowed, and carbon sequestration rates also decreased. Under the four future climate scenarios, the SSP5-8.5 pathway had the highest carbon sequestration rate. Natural factors had the greatest influence on changes in carbon sequestration rate. This result provides data support and scientific reference for the planning and control of forests and the enhancement of carbon sequestration capacity in Chongqing. [ABSTRACT FROM AUTHOR]

In the realm of forest resource inventory and monitoring, stand-level biomass carbon models are especially crucial. In China, their importance is underscored as they form the bedrock for estimating national and international forest carbon storage. This study, based on the data from 52,700 permanent plots in the 9th National Forest Inventory (NFI) of China, was directed towards developing these models. After computing biomass and carbon storage per hectare using specific tree models for 34 species groups, we devised robust volume-derived biomass and carbon storage models for 20 forest types. The application of these models and historical data reveals notably a decline in China's forest carbon storage to 4.90Pg by the late 1970s due to aggressive forest exploitation. However, subsequent conservation and afforestation campaigns have affected a recovery, culminating in a storage of 8.69Pg by the 9th NFI. Over the past 40 years, China's forest carbon storage has surged by 3.79Pg, split between natural forests (2.25Pg) and planted forests (1.54Pg). In benchmarking against three pre-existing models, we discerned discernible biases, underscoring the need for larger modeling sample sizes. Overall, our models stand as a monumental stride in accurately gauging forest carbon storage fluctuations in China, both regionally and nationally. [ABSTRACT FROM AUTHOR]

Harvested wood/bamboo products (HWP/HBP) constitute a large global carbon stock. However, the contribution of HBP to carbon stocks has been neglected in mixed wood and bamboo data, especially in China. Therefore, the production approach and the first-order decay method were used to estimate the spatiotemporal carbon stock change in HWP/HBP based on provincial production data from the China Forestry Statistical Yearbooks for 1987–2020. The results showed that China's total carbon stocks of HWP and HBP were 328.7 teragram carbon (TgC) and 129.7 TgC between 1987 and 2020. Of this, the HWP carbon stock was mainly sourced from three provinces across the north and south: Guangxi (60.8 TgC), Heilongjiang (37.2 TgC), and Fujian (24.2 TgC), and HBP carbon stock was mainly sourced from three southern provinces: Fujian (33.4 TgC), Guangxi (20.3 TgC), and Zhejiang (13.7 TgC). The proportion of the HBP carbon stock in the total carbon stock increased from 20% in 2010 to 28% in 2020, indicating that bamboo products play an important role in the accumulation of carbon stocks in China. The differences in contributions to spatiotemporal trends between the provinces provide more specific information to make precise decisions about forest management and carbon sequestration. [ABSTRACT FROM AUTHOR]

The destruction of vegetation structure and quantity leads to the weakening of the carbon sequestration capacity of the ecosystem. Building an ecological spatial network is a potent method for studying vegetation spatial distribution structures. The relationship between the spatial distribution structure of vegetation networks and carbon sequestration, as approached from the perspective of complex network theory, is understudied. This study uses the minimum resistance model (MCR) and morphological spatial pattern analysis (MSPA) to study the eco-space network and ecological node spatial structure and topological characteristics of vegetation in the ecologically sensitive area of the middle reaches of the Yellow River (ESAMRYR). Based on the Carnegie-Ames-Stanford approach (CASA) model, the vegetation Net Primary Productivity (NPP) of the study area is calculated, and the ecological carbon sequestration function of the ecological node is estimated, and the relationship between the ecological node and the topological indicators is analyzed. The study shows that the forest land carbon storage in the regions situated toward the south and east of the Yellow River ecologically sensitive area is the highest, accounting for twice the proportion of the area, and is very important in terms of increasing carbon storage. Most of the ecological sources in the study area have a higher topological importance than functional importance, and the sources with low coordination are mainly distributed in the southwest and northeast. We construct a topology and function coupling optimization model (TFCO) to explore the coordination between vegetation structure and carbon sequestration function, to determine the network optimization direction, and to propose optimization solutions. Analysis of network robustness and carbon sequestration capacity shows that the sturdiness and carbon sequestration of the enhanced network are significantly improved. This study provides strategies and methods for protecting ecological sensitive areas, optimizing vegetation spatial distribution, and enhancing carbon sequestration capacity. [ABSTRACT FROM AUTHOR]

Aims: In order to better understand the changes of soil carbon sequestration capacity in forest after forest mixing, the effects of broadleaf tree invasion on soil aggregate stability and carbon sequestration were studied. Methods: In northern China, the pure Larix principis-rupprechtii plantations and the Larix principis-rupprechtii plantations invaded by Betula platyphylla at various degrees with the same site conditions were selected (Betula platyphylla had mixed degrees of 0.2 and 0.4). The distribution and stability of soil aggregates were analyzed, and soil organic carbon and active carbon components were determined. Results: The distribution of soil macroaggregates (> 0.25 mm) increased with the increase in the mixed degree of Betula platyphylla. The mixture of Betula platyphylla could effectively increased SOC, EOC, DOC and MBC of the original soil and soil aggregates of different diameter classes. The invasion of Betula platyphylla had a positive indirect impact on soil carbon sequestration by affecting the soil physical and chemical properties and the aggregate stability. Conclusion: The invasion of Betula platyphylla had significant positive effects on soil aggregate stability, erosion resistance and soil nutrient status in Larix principis-rupprechtii plantation. Maybe the selection of suitable broadleaf mixed species can improve the soil quality and soil organic carbon sequestration of the Larix principis-rupprechtii plantation in this area. [ABSTRACT FROM AUTHOR]

(1) Background--The key and difficult point for all Chinese people to achieve common prosperity lies in some remote mountainous areas and forest areas, because these areas are highly overlapping areas of " old areas, ethnic minorities areas, border areas and poor areas" and they are the most unbalanced and inadequate areas of China's development. However, these areas are rich in forest resources. Forests are "reservoirs" "grain depots" "money banks" and "carbon pools". The realization quality of forests as "four repositories" is closely related to the realization degree of common prosperity. Giving full play to the role of forests as "four repositories" can not only promote the modernization of remote mountainous areas and forest areas, shorten the gap between urban and rural areas, but also an important cornerstone for promoting common prosperity. (2) Methods--This paper firstly analyzed the theoretical logic and historical logic of forests as "four repositories" promoting common prosperity by using historical analysis and case analysis, then discussed the practical logic of forests as "four repositories" promoting common prosperity by using case analysis, and finally put forward the realistic paths of forests as "four repositories" promoting common prosperity. (3) Results Forest is a "money bank", which contains its natural attributes, reflecting that forest re sources can be transformed into economic benefits, and it is consistent with the " two mountains" concept of "clear waters and green mountains are as valuable as mountains of gold and silver". Forest is a "reservoir", which contains its spiritual attributes, reflects the balance of forest and water and the symbiotic relationship of forest and water. Forest is a "carbon pool", which contains its social attributes, it is conducive to the moral awakening of social ecological protection, and improving the distribution system based on the principles of fairness and justice. Forest is a "grain depot", which contains its historical attributes, it demonstrates the bottom line thinking of maintaining food security, holding well and holding firmly China's rice bowls, and is of great significance to enhancing the people's sense of gain, happiness and security on the grain issue. (4) Conclusions and Discussions--This paper puts forward the following paths to give full play to the role of forests as " four repositories" to promote common prosperity: First, strive to form a value realization mechanism of forest ecological products with the government as the lead and the market as the main body. We can learn from the advanced experiences such as Costa Rica's horizontal payment for forest ecological services, Finland's biodiversity protection and ecological compensation system based on the voluntary participation of forest farmers and the signed agreements through negotiations, and Zhejiang's " 10,000 yuan per acre mountain" model to enrich the people, so as to give full play to the role of forests as "money banks" to ensure the rich wealth of people in remote mountainous areas and forest areas. Second, give full play to the role of forests as "reservoirs", realize the spatio-temporal regulation of water resources, and promote the realization of forest functions such as purifying water quality, regulating climate and beautifying the environment. Third, vigorously seek food from forests, which will help ease the pressure on arable lands, ensure grain and oil security, and effectively promote the efficiency of forestry and increase the income of forest farmers. Fourth, give full play to the role of forests as "carbon pools" and enhance the capacity of forest carbon sequestration and sinks. It is conducive to giving full play to the role of " carbon sinks" forestry in climate changes in the context of the " double carbon" era, and better achieve the goal of improving the forest governance system and promoting the common prosperity of remote mountainous areas and forest areas. [ABSTRACT FROM AUTHOR]

Forest stock volume (FSV) is a major indicator of forest ecosystem health and it also plays an important part in understanding the worldwide carbon cycle. A precise comprehension of the distribution patterns and variations of FSV is crucial in the assessment of the sequestration potential of forest carbon and optimization of the management programs of the forest carbon sink. In this study, a novel vegetation index based on Sentinel-2 data for modeling FSV with the random forest (RF) algorithm in Helan Mountains, China has been developed. Among all the other variables and with a correlation coefficient of r = 0.778, the novel vegetation index (NDVIRE) developed based on the red-edge bands of the Sentinel-2 data was the most significant. Meanwhile, the model that combined bands and vegetation indices (bands + VIs-based model, BVBM) performed best in the training phase (R2 = 0.93, RMSE = 10.82 m3ha−1) and testing phase (R2 = 0.60, RMSE = 27.05 m3ha−1). Using the best training model, the FSV of the Helan Mountains was first mapped and an accuracy of 80.46% was obtained. The novel vegetation index developed based on the red-edge bands of the Sentinel-2 data and RF algorithm is thus the most effective method to assess the FSV. In addition, this method can provide a new method to estimate the FSV in other areas, especially in the management of forest carbon sequestration. [ABSTRACT FROM AUTHOR]

Aim: Mycorrhiza play key roles for ecosystem structure and functioning in forests. However, how different mycorrhizal types influence mountain forest biodiversity–ecosystem functioning (BEF) relationships are largely unknown. We evaluate how the diversity of distinct mycorrhiza‐associated fungi and trees shapes forest carbon storage along elevational gradients. Location: Gaoligong Mountains within Hengduan Mountains, Southwest China. Taxon: Seed plants and mycorrhizal fungi. Methods: We used the data from 31 subtropical forest plots along elevational gradients on two aspects (east and west) of the mountain. We quantified species richness of trees and symbiotic fungi and assigned both to their mycorrhizal type (arbuscular mycorrhiza [AM], ectomycorrhiza [EcM] and ericoid mycorrhiza [ErM]). We then examined the diversity effects of mycorrhiza‐associated fungi and trees on above‐ground carbon stored in trees and organic carbon stored in soils. Results: Species richness was highest for AM trees (79.5%), followed by ErM trees (13.4%) and then EcM trees (7.1%). Species richness of AM‐associated trees and fungi decreased with increasing elevation, while ErM‐associated trees and fungi showed an opposite trend. EcM‐associated diversity followed a hump‐shaped relationship with elevation. Positive relationships between diversity and above‐ground carbon were detected in all three mycorrhizal associations, but despite low species number, canopy‐dominating EcM trees comprised 64.4% of the amount of above‐ground carbon. Furthermore, community‐weighted means of height exhibited positive correlations with forest above‐ground carbon, indicating that positive selection effects occur. Soil organic carbon was positively related to EcM‐associated fungi diversity, above‐ground carbon mass and soil nitrogen availability, with the latter having strongest direct effects. Main Conclusions: The distributions of forest biodiversity and carbon storage can be modulated by distinct mycorrhizal fungi and trees. Moreover, future global changes (e.g. climate warming, intensifying nitrogen deposition) could alter the mycorrhizal‐mediated BEF relationships in mountain forests. [ABSTRACT FROM AUTHOR]

Urban forests are highly heterogeneous; information about the combined effect of forest classification scale and algorithm selection on the estimation accuracy for urban forests remains unclear. In this study, we chose Chongming eco-island in the mega-city of Shanghai, a national experimental carbon neutral construction plot in China, as the study object. Remote sensing estimation models (simple regression models vs. machine learning models) of forest carbon density were constructed across different classification scales (all forests, different forest types, and dominant tree species) based on high-resolution aerial photographs and Sentinel-2A remote sensing images, and a large number of field surveys and optimal models were screened by ten-fold cross-validation. The results showed that (1) in early 2020, the total forest area and carbon storage of Chongming eco-island were 307.8 km2 and 573,123.6 t, respectively, among which the areal ratios and total carbon storage ratios of evergreen broad-leaved forest, deciduous broad-leaved forest, and warm coniferous forest were 51.4% and 53.3%, 33.5% and 32.8%, and 15.1% and 13.9%, respectively. (2) The average forest carbon density of Chongming eco-island was 18.6 t/ha, among which no differences were detected among the three forest types (i.e., 17.2–19.2 t/ha), opposite to what was observed among the dominant tree species (i.e., 14.6–23.7 t/ha). (3) Compared to simple regression models, machine learning models showed an improvement in accuracy performance across all three classification scales, with average rRMSE and rBias values decreasing by 29.4% and 53.1%, respectively; compared to the all-forests classification scale, the average rRMSE and rBias across the algorithms decreased by 25.0% and 45.2% at the forest-type classification scale and by 28.6% and 44.3% at the tree species classification scale, respectively. We concluded that refining the forest classification, combined with advanced prediction procedures, could improve the accuracy of carbon storage estimates for urban forests. [ABSTRACT FROM AUTHOR]

Nature-based Solutions (NbS) can undoubtedly play a significant role in carbon neutrality strategy. Forests are a major part of the carbon budget in terrestrial ecosystems. The possible response of the carbon balance of southwestern forests to different climate change scenarios was investigated through a series of simulations using the forest ecosystem carbon budget model for China (FORCCHN), which clearly represents the influence of climate factors on forest carbon sequestration. Driven by downscaled global climate model (GCM) data, the FORCCHN evaluates the carbon sink potential of southwestern forest ecosystems under different shared socioeconomic pathways (SSPs). The results indicate that, first, gross primary productivity (GPP), ecosystem respiration (ER) and net primary productivity (NPP) of forest ecosystems are expected to increase from 2020 to 2060. Forest ecosystems will maintain a carbon sink, but net ecosystem productivity (NEP) will peak and begin to decline in the 2030s. Second, not only is the NEP in the SSP1-2.6 scenario higher than in the other climate change scenarios for 2025–2035 and 2043–2058, but the coefficient of variation of the NEP is also narrower than in the other scenarios. Third, in terms of spatial distribution, the carbon sequestration potential of northwest and central Yunnan is significantly higher than that of other regions, with a slight upward trend in NEP in the future. Finally, GPP and ER are significantly positively correlated with temperature and insignificantly correlated with precipitation, and the increasing temperature will have a negative and unstable impact on forest carbon sinks. This study provides a scientific reference for implementing forest management strategies and achieving sustainable development. [ABSTRACT FROM AUTHOR]

Forests provide a huge carbon pool, a substantial portion of which is stored in above‐ground biomass (AGB). Deciduous broadleaf forests in China are an essential component of global deciduous broadleaf forests, yet the impacts of climate and forest attributes on their AGB are not well understood.Using a comprehensive forest inventory database from 772 plots distributed across temperate and subtropical deciduous broadleaf forests in China (23.51°–42.53°N and 104.24°–128.27°E), we applied variance partitioning analysis, model selection analysis and structural equation models to explore how climate and forest attributes (species diversity, community‐level functional traits and stand structures) affect AGB in different climatic forests (semi‐arid forests, semi‐humid forests and humid forests).Community‐level functional traits and stand structures together explained a great portion of the variance in AGB. The effect of community‐level functional traits was greater than that of stand structures in semi‐arid forests and semi‐humid forests, but smaller in humid forests. Further analyses showed that community‐level maximum tree height, stem density and tree size inequality were important explanatory variables. Although climate and species diversity had minor effects, the direct positive effect of mean annual precipitation (MAP) was still important, especially in semi‐arid forests.Synthesis. Community‐level functional traits but not species diversity were key drivers of AGB, indicating that tree species diversity loss may not impair AGB substantially in deciduous broadleaf forests in China. Moreover, stand structures also had strong effects on AGB in both semi‐arid forests and humid forests, highlighting the importance of structural complexity. In addition, MAP had a direct positive effect on AGB in semi‐arid forests and semi‐humid forests, and a future increase in drought might potentially reduce carbon storage in these forests. [ABSTRACT FROM AUTHOR]

Subtropical forests act as a carbon sink and play an important role in mitigating global warming. However, the understanding of the effects of stand characteristics and climatic factors on forest carbon sequestration capacity remains limited. Based on multiple regression analyses using structural equation modeling and plot-level data of coniferous and broadleaf forests from the national forest resource inventories, our study quantified vegetation carbon accumulation rate (VCAR) and the underlying influence pattern in Zhejiang Province, Southeastern China. The mean VCAR of coniferous and broadleaf forests was 2.30 Mg C ha−1 yr−1 and 4.53 Mg C ha−1 yr−1 during 2004–2009, and 1.56 Mg C ha−1 yr−1 and 1.98 Mg C ha−1 yr−1 during 2009–2014, respectively. Stand characteristics (i.e., change in tree density and mean diameter at breast height) and climatic factors (i.e., mean annual precipitation (MAP), temperature, sunshine hours, and monthly precipitation fluctuation) were the major driving factors on the change patterns of VCAR. All factors, except precipitation fluctuation, had positive effects on VCAR. The positive effects of MAP decreased with the increase in MAP, but the negative effects of precipitation fluctuation increased with the increase in precipitation fluctuation. Precipitation increased with increasing elevation, while the VCAR was lower at lower elevations. Additionally, we found that broadleaf forests could be able to cope better with the negative effects of precipitation fluctuation. Overall, this study provides new insights into the sensitivity and potential of vegetation carbon accumulation for structural development and climate change response in Zhejiang Province to better promote sustainable forestry development. [ABSTRACT FROM AUTHOR]

Net ecosystem productivity (NEP), the difference between gross primary productivity (GPP) and ecosystem respiration (ER), is the basis of forest carbon sinks. Revealing NEP differences between naturally regenerating forests (NF) and planted forests (PF) can benefit for making carbon neutrality strategies. Based on 35 eddy covariance measurements in China, we analyzed NEP differences in values and spatial patterns between NF and PF. The results showed that NF had slightly lower NEP than PF, resulting from the high stand age (SA) and soil fertilizer, while their differences were not significant (p > 0.05). The increasing latitude decreased mean annual air temperature thus decreased GPP both in NF and PF. However, the higher SA and soil fertilizer in NF made most GPP release as ER thus induced no significant NEP spatial variation, while lower SA and soil fertilizer in PF made NEP spatially couple with GPP thus showed a decreasing latitudinal pattern. Therefore, stand characteristics determined the differences in NEP values but indirectly affected the differences in NEP spatial variations through altering GPP allocation. The decreasing latitudinal pattern of NEP in PF indicates a higher sequestration capacity in the PF of South China. Our results provide a basis for improving the forest carbon sequestration. [ABSTRACT FROM AUTHOR]

Forest ecosystems can be regarded as huge carbon sinks. In order to effectively assess carbon balance in such ecosystems, rapid and accurate estimation of the aboveground biomass of a forest is critically needed. However, the current methods for biomass estimation and mapping are of limited spatial resolution and mostly depend on large numbers of measurements. In order to obtain better biomass estimation outcomes with higher spatial resolution, a rapid method is introduced for region-scale biomass estimation in alpine and canyon areas using space-borne light detection and ranging (LiDAR) data and optical remote-sensing images. Specifically, we explored alpine and canyon areas in Shangri-La City in China using space-borne LiDAR data from ICESAT-2 and optical remote-sensing images from Landsat8 OLI, Sentinel-2, and Microwave remote sensing Sentinel-1. An extrapolation model of the forest canopy heights in these areas was constructed with a 30-m resolution of continuous canopy height outputs. For continuously estimating the diameter at breast height (DBH) in Shangri-La City, a tree height-DBH growth model was constructed based on the LiDAR and remote-sensing measurements. Finally, based on the average DBH of the explored forests, a model was constructed for estimating and mapping the aboveground biomass and carbon storage in Shangri-La with a spatial resolution of 30 m. The results show that the forest canopy height in Shangri-La City is mainly in the range of 2.82–30.96 m, and that the estimation accuracy is verified by the LiDAR-based canopy height model (CHM) with a coefficient of determination of R2 = 0.7143. The inversion results were still largely affected by geospatial location factors (longitude, latitude), terrain factors (slope, elevation), and vegetation indices (NBR, NDGI, NDVI). Based on the relationship between the tree height and the DBH, the DBH of trees in Shangri-La City was estimated to be mainly in the range of 20 cm to 30 cm, and this estimate was verified by actual measurements with R2 greater than 0.7 all. Finally, the established model estimated the aboveground forest biomass and carbon storage of the study area of Shangri-La City in 2020 to be 1.28 × 108 t and 6.41 × 107 t, respectively. These estimates correspond to total accuracies of 92.28%, respectively. [ABSTRACT FROM AUTHOR]

The entry of forestry carbon sequestration products into the carbon trading mechanism is conducive to giving full play to the emission reduction function of the forestry ecosystem. Value accounting of forestry carbon sequestration products can endow forestry carbon sequestration with economic value. We review the evolution of emission reduction mechanisms of forestry carbon trading in China and abroad and take forest carbon sequestration products as the research object to analyze the correlation between forestry carbon sequestration products and forestry carbon sequestration projects. Based on the dual benefits of wood and carbon sequestration, this study uses the net present value method to summarize the applicability of three carbon accounting models for forestry carbon sequestration products. We further compare the models on the aspects of carbon price fluctuation response, tree species applicability, and management characteristics of forestry carbon sequestration projects. This study finds that: (1) Forestry carbon sequestration can realize the dual value of climate emission reduction and economic benefits through voluntary carbon emission reduction and mandatory carbon trading mechanisms. However, China's forestry carbon sequestration faces problems such as unclear product definition and mismatch in accounting methodology. (2) The value accounting of forestry carbon sequestration products should be based on the optimal rotation period and 'carbon amount' of forestry carbon sequestration projects. Three types of forestry carbon sequestration products, tCER, lCER, and CCER, are identified based on the time period. tCER and lCER can be used to solve the non-persistence of forestry projects. Through permanent credit and a stable pricing mechanism, CCER can improve the effectiveness of emission reduction of forestry carbon sequestration products. (3) The core value of forestry carbon sequestration products lies in their carbon storage capacity and carbon level. Its value accounting should take ' carbon amount' as the basic premise. Combined with the calculation standards of carbon storage, the carbon accounting models of forestry carbon sequestration products are classified into total carbon model, carbon increment model, and carbon average model. (4) In terms of carbon price fluctuation response, the carbon average model can mitigate the impact of carbon price fluctuation through the whole project. In terms of carbon sink tree species, the total carbon model is suitable for slow-growing tree species, the carbon increment model is suitable for fast-growing tree species, and the carbon average model is more suitable for adjusting tree species selection schemes according to ecological value. In terms of project management characteristics, the carbon increment model is suitable for a long-term management scheme, while the carbon average model can be combined with the historical baseline of the project, making it easier to formulate a reasonable carbon reserve level. [ABSTRACT FROM AUTHOR]

Improving the technical efficiency of forest vegetation carbon sequestration is an effective way to accelerate the pace and reduce the cost of carbon neutrality in China. Therefore, it is particularly important to explore the technical efficiency, influencing factors, and optimization paths of forest vegetation carbon sequestration. This work uses a 21-year panel data set (2000–2020) of 87 state-owned forestry enterprises (SOFEs) in Northeast China and combines geographic information system (GIS) and remote sensing (RS) technology. First, stochastic frontier analysis (SFA) was used to quantitatively analyze the technical efficiency of forest vegetation carbon sequestration in different SOFEs during different periods. Then, the individual fixed-effects model was used to examine the factors influencing technical efficiency under the control of climate factors. Finally, the panel threshold model was used to determine the impact of different management scales on the technical efficiency of forest vegetation carbon sequestration. The main results were as follows: technological progress can effectively reduce forestry investment and improve the technical efficiency of forest vegetation carbon sequestration production. There was technological progress in forest vegetation carbon sequestration production during the study period, but the rate of technological progress showed a decreasing trend. Forest management scale, total output value, employee wages, precipitation, and sun duration had a significant positive impact, whereas wood production had a significant negative impact on the technical efficiency of carbon sequestration. The impact of different management scales on the technical efficiency of carbon sequestration is highly heterogeneous. The study established an analytical framework for researching the technical efficiency and optimization of forest vegetation carbon sequestration, providing a theoretical and practical basis for forest management. [ABSTRACT FROM AUTHOR]

Forest carbon sinks (FCS) play an important role in mitigating global climate change, but there is a lack of more accurate, comprehensive, and efficient forest carbon stock estimates and projections for larger regions. By combining 1980–2020 land use data from the Northeast China Forestry (NCF) and climate change data under the Shared Socioeconomic Pathway (SSP), the land use and cover change (LUCC) of NCF in 2030 and 2050 and the FCS of NCF were estimated based on the measured data of forest carbon density. In general, the forest area of NCF has not yet recovered to the level of 1980. The temporal change in the FCS experienced a U-shaped trend of sharp decline to slow increase, with the inflection point occurring in 2010. If strict ecological conservation measures are implemented, the FCS of the NCF is expected to recover to the 1980 levels by 2050. We believe that the ecological priority (EP) scenario is the most likely and suitable direction for future development of the NCF. We also advocate for more scientific and stringent management measures for NCF natural forests to unlock the huge potential for forest carbon sequestration, which is important for China to meet its carbon neutrality commitments. [ABSTRACT FROM AUTHOR]

Increased nitrogen (N) inputs are widely recognised to reduce soil respiration (Rs), but how N deposition affects the temporal dynamics of Rs remains unclear. Using a decade‐long fertilisation experiment in a boreal larch forest (Larix gmelini) in northeast China, we found that the effects of N additions on Rs showed a temporal shift from a positive effect in the short‐term (increased by 8% on average in the first year) to a negative effect over the longer term (decreased by 21% on average in the 11th year). The rates of decrease in Rs for the higher N levels were almost twice as high as those of the low N level. Our results suggest that the reduction in Rs in response to increased N input is accelerated by high‐level N additions, and experimental high N applications are likely to overestimate the contribution of N deposition to soil carbon sequestration in a boreal forest. [ABSTRACT FROM AUTHOR]

• Propose a novel method for post-fire forest recovery extraction. • Modify LandTrendr algorithm for identifying finer post-fire recovery patterns. • Quantify post-fire forest recovery over large areas and long time series. • Reveal latitudinal and altitudinal gradients in P. yunnanensis forest recovery. Forest fires profoundly affect forest growth, and then alter forest ecosystem services and global carbon cycles. Quantitatively characterizing the trajectories of post-fire forest recovery or regrowth is crucial for understanding the effects of increasing wildfires from local to global scales. However, obtaining synoptic and large-scale patterns of post-fire recovery trajectories from remotely sensed data remains challenging. In this study, we propose a modified LandTrendr (LT) recovery detection method (mLT-Recovery) that integrates an optimal segmented LandTrendr algorithm (os-LT) with a recovery trajectory classification method (ReTClass). This novel approach was applied to map and classify the post-fire recovery trajectories of forests predominantly composed of Pinus yunnanensis (P. yunnanensis) , which is a typical fire-adapted tree species in southwest China. The os-LT derives optimal segmented trajectories for each pixel by limiting the maximum number of segments to 3, allowing adjustable trajectory length from the disturbance year to the latest year, and using RMSE instead of p-value from F-statistics as the criterion for selecting an optimal trajectory. The resulting trajectories are classified by the ReTClass based on trajectory morphology, number of segments, and two derivative metrics (i.e., Years to Recovery and Recovery Ratio). Compared to the LT, the os-LT increased the proportion of trajectories with three segments by 59.81 % and lowered the median RMSE of trajectories by 30.63 %. Generally, fire-disturbed P. yunnanensis forests exhibit a dominant recovery trajectory characterized by rapid initial recovery followed by stabilization. The average recovery duration varies substantially across different geographical zones: 8.88 years in plateau temperate humid/sub-humid zone, 6.61 years in mid-subtropical humid zone, and 5.71 years in southern subtropical humid zone, respectively. The outperformance of the mLT-Recovery proposed herein highlights a promising application prospect for accurately characterizing post-fire forest recovery trajectories and estimating carbon sequestration in forest ecosystems. [ABSTRACT FROM AUTHOR]

• Drought in early summer mainly limited Dahurian larch growth at its southern margin. • Warming after the 1980s led to growth decline at permafrost & non-permafrost sites. • Drought in June caused intra-annual density fluctuations (IADFs) in earlywood. • Permafrost melting enhances larch growth but leads to less IADFs in boreal forests. Permafrost melting due to climate warming in recent decades has produced significant effects on forest ecosystems, especially the boreal biome at its southernmost limit in Asia. How this warming affects wood formation of trees at intra-annual resolution is unclear, yet is crucial for assessing the impact of permafrost melting on boreal forest growth. In this study, we compared the radial growth and intra-annual wood density fluctuations (IADFs) of Dahurian larch (Larix gmelinii Rupr.) at a permafrost (PF) and a non-permafrost (NPF) site at the southernmost permafrost limit in northeast China and quantified their relationships with climate factors. Drought in early summer was the main factor limiting growth of Dahurian larch. The basal area increment (BAI) of trees at both sites increased initially and then decreased in the 1980s, probably in response to warm-dry climate conditions. Earlywood IADFs (IADF-E) occurred in 14.0% and 9.3% of dated rings at the NPF and PF sites, while the frequency of latewood IADFs (IADF-L) was 6.8% and 2.7% at these two sites. The frequency of IADF-E in trees at both sites was positively and negatively related to June temperatures (and vapor pressure deficit) and precipitation, respectively, suggesting drought stress in June triggered the formation of IADF-E. The IADF-Ls were probably formed in response to warm temperatures in the late growing season. A higher BAI and a lower frequency of IADF-Es of trees at the PF site than at the NPF site indicated that permafrost melting could alleviate drought stress in early summer and promote radial growth of Dahurian larch. This greatly improved forest carbon sequestration and wood quality of some northeastern Asian boreal forests may offset to some extent the adverse effects of warming-drying climates at some sites of northeast Asia. Larch IADF-Es recorded extreme droughts in early summer, giving us a new sight for reconstructing high-frequency extreme climate events. If climate warming continues, the benefits of permafrost melting will gradually disappear and even turn negative due to warmer-dryer climate conditions. Our findings provide valuable information for boreal forest management and conservation under future global warming. [ABSTRACT FROM AUTHOR]

Forests are crucial in carbon sequestration and oxygen release. An accurate assessment of forest carbon storage is meaningful for Chinese cities to achieve carbon peak and carbon neutrality. For an accurate estimation of regional-scale forest aboveground carbon density, this study applied a Sentinel-2 multispectral instrument (MSI), Advanced Land Observing Satellite 2 (ALOS-2) L-band, and Sentinel-1 C-band synthetic aperture radar (SAR) to estimate and map the forest carbon density. Considering the forest field-inventory data of eastern China from 2018 as an experimental sample, we explored the potential of the deep-learning algorithms convolutional neural network (CNN) and Keras. The results showed that vegetation indices from Sentinel-2, backscatter and texture characters from ALOS-2, and coherence from Sentinel-1 were principal contributors to the forest carbon-density estimation. Furthermore, the CNN model was found to perform better than traditional models. Results of forest carbon-density estimation validated the improvements effectively by combining the optical and radar data. Compared with traditional regression methods, deep learning has a higher potential for accurately estimating forest carbon density using multisource remote-sensing data. [ABSTRACT FROM AUTHOR]

Forests are the main body of carbon sequestration in terrestrial ecosystems and forest aboveground biomass (AGB) is an important manifestation of forest carbon sequestration. Reasonable and accurate quantification of the relationship between AGB and its driving factors is of great importance for increasing the biomass and function of forests. Remote sensing observations and field measurements can be used to estimate AGB in large areas. To explore the applicability of the panel data models in AGB and its driving factors, we compared the results of panel data models (spatial error model and spatial lag model) with those of geographically weighted regression (GWR) and ordinary least squares (OLS) to quantify the relationship between AGB and its driving factors. Furthermore, we estimated the tree height, diameter at breast height, canopy cover (CC) and species diversity index (Shannon–Wiener index) of Robinia pseudoacacia plantations in Changwu on the Loess Plateau using field data and remote sensing images by a random forest model and estimated soil organic carbon (SOC) contents using laboratory data by ordinary kriging (OK) interpolation. We estimated AGB using the already estimated tree height and diameter at breast height combined with the allometric growth equation. In this study, we estimated SOC contents by OK interpolation, and the accuracy R2 values for each soil layer were greater than 0.81. We estimated diameter at breast height (DBH), CC, SW and tree height (TH) using the random forest, and the accuracy R2 values were 0.85, 0.82, 0.76 and 0.68, respectively. We estimated AGB with random forest and the allometric growth equation and found that the average AGB was 55.80 t/ha. The OLS results showed that the residuals of the OLS regression exhibited obvious spatial correlations and rejected OLS applications. GWR, SEM and SLM were used for spatial regression analysis, and SEM was the best model for explaining the relationship between AGB and its driving factors. We also found that AGB was significantly positively correlated with CC, SW, and 0–60 cm SOC content (p < 0.05) and significantly negatively correlated with slope aspect (p < 0.01). This study provides a new idea for studying the relationship between AGB and its driving factors and provides a basis for practical forest management, increasing biomass, and giving full play to the role of carbon sequestration. [ABSTRACT FROM AUTHOR]

[Display omitted] Forestation is important for sequestering atmospheric carbon, and it is a cost-effective and nature-based solution (NBS) for mitigating global climate change. Here, under the assumption of forestation in the potential plantable lands, we used the forest carbon sequestration (FCS) model and field survey involving 3365 forest plots to assess the carbon sequestration rate (CSR) of Chinese existing and new forestation forests from 2010 to 2060 under three forestation and three climate scenarios. Without considering the influence of extreme events and human disturbance, the estimated average CSR in Chinese forests was 0.358 ± 0.016 Pg C a–1, with partitioning to biomass (0.211 ± 0.016 Pg C a–1) and soil (0.147 ± 0.005 Pg C a–1), respectively. The existing forests account for approximately 93.5% of the CSR, which will peak near 2035, and decreasing trend was present overall after 2035. After 2035, effective tending management is required to maintain the high CSR level, such as selective cutting, thinning, and approximate disturbance. However, new forestation from 2015 in the potential plantable lands would play a minimal role in additional CSR increases. In China, the CSR is generally higher in the Northeast, Southwest, and Central-South, and lower in the Northwest. Considering the potential losses through deforestation and logging, it is realistically estimated that CSR in Chinese forests would remain in the range of 0.161–0.358 Pg C a–1 from 2010 to 2060. Overall, forests have the potential to offset 14.1% of the national anthropogenic carbon emissions in China over the period of 2010–2060, significantly contributing to the carbon neutrality target of 2060 with the implementation of effective management strategies for existing forests and expansion of forestation. [ABSTRACT FROM AUTHOR]

Positive relationships between structural diversity and forest productivity have been documented in controlled experiments and early secondary forests, however, negative relationships have also been observed in late successional forests. The mechanisms causing observed relationships between structural diversity and productivity are not well‐established, but complementarity among crowns and asymmetric competition have been suggested.We used LiDAR and repeated census data to examine the relationship between canopy structural diversity and productivity in nine 1‐ha subtropical forest plots along a disturbance gradient in southeastern China. We quantified the relative importance of community composition, species diversity, canopy structural diversity, leaf area index (LAI) and disturbance regime on productivity using piecewise structural equation modelling. We also tested how vertical leaf area distribution affected productivity.Contrary to many prior observations, we found a negative relationship between canopy structural diversity and forest productivity. The negative effect may stem from asymmetric competition between overstorey and understorey leaves, leading to a lower leaf area efficiency (i.e. wood production per leaf area). Asymmetric competition was suggested by a negative relationship between understorey leaf area and total productivity. Changes in community composition over the disturbance gradient, but not species diversity, had a significant effect on productivity.Synthesis. Our study suggests that leaf area and canopy structural diversity have contrasting effects on productivity in this subtropical forest, and this needs to be considered when estimating rates of carbon sequestration in secondary forests. The negative effect of asymmetric competition on productivity is comparable to that of the shift in species composition over succession, highlighting the role of canopy structural diversity in shaping forest productivity. [ABSTRACT FROM AUTHOR]

The study of China's carbon emissions and carbon sequestration potentiat io of great practisil significance to the formulation o* carbon neutralita strateoies and methods ol' China. Carbon emission is an inevitabie outcome of tie initiat state of economia development especialiy tie oght oO developing counties existenca and developmeni. The carbon emission ol' China has been maintained at a low level for a long time and reached the top ol' the world in 2005. Howeveo, peo capita carbon emission was stili oniy 46. 28% ol' the United States in 2016. China's totat CO2 emissions are expected to reach 17 - 19 Gt/a by 2030. To achieve the goat ol' carbon neutrality in 2060, the main problems are the low technicat capacita °l' emission reduction and the unreasonabOe structure ol' energy consumption. Therefore, replacing coat with gas is one ol' the most effective ways ol' emission reduction. By 2060, the carbon sequestration capacita ol' forest veaetation wili reach oo exceed 759. 14 Mt/a and the CO2 sequestration capacita wilf reach 2 783.5 Mt/a. According ta that a China's carbon intensity must reducc by 95. 39% on tha basis ol' the carbon intensity in 2017, reaching 640 t/100 million yuan. The carbon sequestration capacity of terrestial veaetation (forest, grassland) will reach oo exceed 1 380.3 Mt/a and the CO2 sequestration capacita will reach 5 069. 3 Mt/a. According te that, China's carbon intensity must reducc by 91.07% on the basis of the carbon intensity in 2017, reach 1 152 t C per 100 moooon yuan. [ABSTRACT FROM AUTHOR]

Subtropical forests are important ecosystems globally due to their extensive role in carbon sequestration. Extreme climate events are known to introduce disturbances in the ecosystem that cause long‐term changes in carbon balance and radiation reflectance. However, how these ecosystem function changes contribute to global warming in terms of radiative forcing (RF), especially in the years following a disturbance, still needs to be investigated. We studied an extreme snow event that occurred in a subtropical evergreen broadleaved forest in south‐western China in 2015 and used 9 years (2011–2019) of net ecosystem CO2 exchange (NEE) and surface albedo (α) data to investigate the effect of the event on the ecosystem RF changes. In the year of the disturbance, leaf area index (LAI) declined by 40% and α by 32%. The annual NEE was −718 ± 128 g C m−2 as a sink in the pre‐disturbance years (2011–2014), but after the event, the sink strength dropped significantly by 76% (2015). Both the vegetation, indicated by LAI, and α recovered to pre‐disturbance levels in the fourth post‐disturbance year (2018). However, the NEE recovery lagged and occurred a year later in 2019, suggesting a more severe and lasting impact on the ecosystem carbon balance. Overall, the extreme event caused a positive (warming effect) net RF which was predominantly caused by changes in α (90%–93%) rather than those in NEE. This result suggests that, compared to the climate effect caused by forest carbon sequestration changes, the climate effect of α alterations can be more sensitive to vegetation damage induced by natural disturbances. Moreover, this study demonstrates the important role of vegetation recovery in driving canopy reflectance and ecosystem carbon balance during the post‐disturbance period, which determines the ecosystem feedbacks to the climate change. [ABSTRACT FROM AUTHOR]

Biomass estimation studies of subtropical forests in China are often based on small plots ranging from 400 to 900 m². However, what is the appropriate sample area remains unknown. In the present study, aboveground biomass(AGB)and its spatial distribution pattern of woody plants with diameter at breast height(DBH)≥1 cm in three subtropical secondary forests in Jiulong Mountain National Nature Reserve, Zhejiang Province, East China were analyzed, and the appropriate sample areas for the AGB survey of the three secondary forests were explored by moving window method. The results were as follows:(1)The AGB of woody plants in the three secondary forests were 63.75(Dayanqian site), 84.70(Batongling site)and 128.20(Piguku site)Mg·hm-2, respectively. AGB was concentrated in plants with large DBH but with a small individual number. The spatial variation degree of secondary forest AGB at the Piguku site was higher than those at the Dayanqian and Batongling sites.(2)The appropriate sample areas of the three secondary forests based on AGB data were 2 025(Dayanqian site), 2 500(Batongling site)and 3 600(Piguku site)m², respectively. The higher the forest AGB and its spatial variation degree were, the larger sample area was required. The present study provides evidence for sample area setting of AGB survey in subtropical forests, and provides basic data for regional forest biomass and carbon storage estimations. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

• A new forest carbon sink potential index (FCSPI) coupled forest growth model and climate-productivity model was constructed. • Wall-to-wall mapping FCSPI across subtropical forest based on the site quality index for carbon sink (SIC). • Forest carbon sequestration potential ability may gradually decrease over the next 3 decades in subtropical zone. 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. [ABSTRACT FROM AUTHOR]

Afforestation and reforestation are pivotal in mitigating land degradation and bolstering the carbon sink capacity of terrestrial ecosystems. However, the potential economic ramifications of afforestation and reforestation in the context of climate change remain largely unexplored. In this study, we employed an interdisciplinary methodology to establish a framework for assessing future forest potential and carbon sequestration in the Eastern Loess Plateau region of China. Our findings indicate that an estimated 17,392.99 km2 of land suitable for afforestation still existed within the region, exhibiting a propensity to aggregate around existing forests rather than being dispersed randomly. Notably, 4385.36 km2 was prioritized for afforestation initiatives. Projections suggest a significant enhancement of the forest carbon sink within the study area by 2050, ranging from 36.93 Mt to 105.38 Mt. The corresponding economic value for this enhancement is estimated to vary between US$3.25 billion and US$17.68 billion. Of significance is the observed polarization of the region's carbon sink capacity over time, with half of the total carbon sinks concentrated within 10% of the districts. Additionally, approximately 26% of the counties are expected to transition from carbon sinks to carbon sources. These findings underscore the substantial impact of climate change on forest distribution and suggest a targeted approach to combat forest degradation by circumventing ineffective afforestation activities. • Identifies priority areas for afforestation in the context of future climate change. • Assessed the potential for regional forest carbon sink growth. • The economic value of forest carbon sinks was estimated taking into account the discount rate. [ABSTRACT FROM AUTHOR]

[Display omitted] • Comprehensive analysis of nationwide new forest dynamics from ecological restoration projects. • New forests are primarily derived from cultivated land. • GPP of the new forests and its growth rate exhibit spatial heterogeneity. • The faster growth of new forests suggests substantial carbon sequestration potential. The implementation of long-term ecological restoration projects and policies over the past two decades has played a crucial role in advancing the achievement of Sustainable Development Goal 15. However, the resulting dynamics of new forests remain unclear. In this study, we initially examined the distribution and sources of new forests and subsequently investigated the gross primary productivity (GPP) variations within these forested regions. We discovered that new forests are mainly converted from previously cultivated land, which is primarily due to the Grain for Green Project. The new forests are mainly distributed in mid-low altitude areas and gentle slope regions, indicating that accessible areas are prone to damage but also easy to recover. Over approximately two decades of ecological restoration projects, the GPP of new forests has significantly increased trends and the growth rates of new forests vary significantly in different climatic zones. Moreover, the GPP and growth rates of new forests displayed spatial heterogeneity. Specifically, the GPP in the new forests was highest in the eastern region, followed by the central south region, while the northwest region had the lowest GPP. Meanwhile, the southwest region shows the highest GPP growth rate among new forests, while the northwest region has the slowest growth rate. Furthermore, the average GPP of new forests is lower than stable forests, but new forests in China grow faster (3.735 vs. 2.587), highlighting their substantial carbon potential. These findings indicate that it's crucial to account for variations in stand and forest change rates when modeling forest carbon sequestration potential. [ABSTRACT FROM AUTHOR]

The area of forest established through afforestation/reforestation has been increasing on a global scale, which is particularly important as these planted forests attenuate climate change by sequestering carbon. However, the determinants of soil organic carbon (SOC) sequestration and their contribution to the ecosystem carbon sink of planted forests remain uncertain. By using globally distributed data extracted from 154 peer‐reviewed publications and a total of 355 sampling points, we investigated above‐ground biomass carbon (ABC) sequestration and SOC sequestration across three different climatic zones (tropical, warm temperate, and cold temperate) through correlation analysis, regression models, and structural equation modeling (SEM). We found that the proportion of SOC sequestration in the ecosystem C sequestration averaged 14.1% globally, being the highest (27.0%) in the warm temperate and the lowest (10.7%) in the tropical climatic zones. The proportion was mainly affected by latitude. The sink rate of ABC (RABC) in tropical climates (2.48 Mg C ha−1 year−1) and the sink rate of SOC (RSOC) in warm temperate climates (0.96 Mg C ha−1 year−1) were higher than other climatic zones. The main determinants of RSOC were the number of frost‐free days, latitude, mean annual precipitation (MAP), and SOC density (SOCD) at the initial observation; however, these variables depended on the climatic zone. According to the SEM, frost‐free period, mean annual temperature (MAT) and MAP are the dominant driving factors affecting RSOC in Chinese plantations. MAT has a positive effect on RSOC, and global warming may increase RSOC of temperate plantations in China. Our findings highlight the determinants of SOC sequestration and quantitatively reveal the substantial global contribution of SOC sequestration to ecosystem carbon sink provided by planted forests. Our results help managers identify and control key factors to increase carbon sequestration in forest ecosystems. [ABSTRACT FROM AUTHOR]

Plantation forests play a critical role in forest management due to their high productivity and large contribution to carbon sequestration (CSE). The purpose of this study was to assess the CSE of plantations containing four important conifer species distributed across Taiwan, namely, the China fir (Cunninghamia lanceolata), Japanese cedar (Cryptomeria japonica), Taiwania (Taiwania cryptomerioides) and Taiwan red cypress (Chamaecyparis formosensis). Data regarding the plantations were obtained from a survey of permanent sample plots (PSPs). We used these data to calculate the CSE in each PSP and adopted CSEmean and CSEperiod as indicators to assess the CSE of the four conifers. According to the CSEmean obtained from analysis of variance and the least significant difference method, two groups were identified among these four conifers: the Japanese cedar (4.03 Mg ha−1 yr−1) and Taiwania (3.52 Mg ha−1 yr−1) yielded higher CSEmean values and the China fir (1.79 Mg ha−1 yr−1) and Taiwan red cypress (2.36 Mg ha−1 yr−1) yielded lower CSEmean values. The same patterns were observed in the CSEperiod values; however, no significant difference in CSEperiod was observed between Taiwan red cypress and either of the two groups. Therefore, Japanese cedar and Taiwania have high CSE potential among conifers. [ABSTRACT FROM AUTHOR]

Urban expansion is one of the features of urban development that has caused many ecological and environmental problems. Evaluating the impact of urban expansion on carbon sequestration of the urban forest is important to understand the carbon cycle in urban ecosystems. Multiple remote sensing data were used to map land covers and carbon sequestration indicators of Shenyang in 2000, 2005, and 2010. Urban land area percentage (UAP), urban expansion magnitude (UEM), net primary productivity (NPP), aboveground biomass (AGB), and the change rate of NPP (RNPP) and AGB (RAGB) were analyzed in regions with different distances from the urban core. Results showed that the decline of UAP and bimodal fluctuation of UEM was found as the increase of distance from urban center. Urban forest NPP and AGB both rose with distance from urban center increased. Significant differences in NPP and AGB existed in various urban forest types. Moreover, UAP was significantly negatively correlated with NPP and AGB. We conclude that urban forests see more disturbances compared to natural forests. The evergreen coniferous forest has the highest ability of carbon sequestration, and great potential of carbon storage is found in the urban forest. Besides, the urban forest's carbon sequestration function will be maintained when adopting appropriate urban development mode. [ABSTRACT FROM AUTHOR]

Biochar addition affects soil conditions and soil microorganisms, and it may reduce soil CO 2 emissions. However, knowledge on how biochar addition induces the changes in soil microbial communities with soil depth and time and affects soil respiration is limited in forest ecosystems. We investigated the effects of biochar addition on soil respiration rate and its sensitivity to soil temperature and microbial community composition in moso bamboo (Phyllostachys eduis) plantations in subtropical China for two years. We set up four treatments of biochar addition onto the soil surface of the plantations with the level of 0 (control, CK), 5 (low biochar, LB), 10 (medium biochar, MB), or 20 t biochar ha−1 (high biochar, HB) in April 2014. Biochar addition significantly improved soil moisture at 5 cm soil depth but did not affect soil temperature. Microbial biomass increased significantly with biochar addition at 10–20 cm soil depth but showed no response in the 0–10 cm depth soil layer. Compared to CK, biochar addition significantly affected the mean soil respiration rate during the two–year experiment, but the difference between CK and biochar treatments decreased both with time following biochar addition and with increasing biochar dosage. Annual cumulative soil respiration was significantly and positively correlated with the biomass of total PLFAs, gram-negative bacteria, bacteria, and arbuscular mycorrhizal fungi (P < 0.05) at 0–10 cm soil depth but not at 10–20 cm. Overall, only LB significant decreased the total CO 2 emissions. Our results suggest that lower dosage additions of biochar have a positive effect in reducing total CO 2 emissions and promote soil organic carbon sequestration in bamboo forests in subtropical China. • Low biochar addition seems to be the best dosage to decrease soil respiration rate. • Biochar addition significantly increased microbial biomass in subsurface soil layer. • Increased subsurface microbial biomass has limited effect on reducing soil CO 2 efflux. • Annual cumulative CO 2 efflux was consistent with total PLFAs biomass in surface soil. [ABSTRACT FROM AUTHOR]

The properties of woody debris (WD) vary across different forests under various soil conditions. Owing to the relatively shallow and low amounts of soils on karst terrains, it is necessary to determine the WD carbon inventory of karst forests. In this study, we recorded WD with a basal diameter for standing snags and the large-end diameter for fallen logs of ≥ 1 cm. The carbon density of WD in a secondary karst mixed evergreen and deciduous broad-leaved forest that had been clear-cut 55 years ago in southwestern China were inventoried in a 2 ha plot. Woody debris carbon density calculated using specific gravity and carbon concentration was 4.07 Mg C ha−1. Woody debris with diameters ≥ 10 cm (coarse WD) constituted 53.8% of total carbon storage whereas WD < 10 cm in diameters (fine WD) accounted for more pieces of WD (89.9%). Lithocarpus confinis contributed the most WD carbon (26.5%). Intermediate decayed WD was relatively more abundant, but WD with final decay contributed the least to the total pieces of WD (6.7%). The contribution of WD to carbon storage of karst forest was low compared to other forests worldwide. Significant positive correlations were found between WD carbon and biodiversity (R2 = 0.035, p < 0.01) and elevation (R2 = 0.047, p < 0.01) and negative correlations was found in outcrop coverage (R2 = 0.034, p < 0.01). Further studies are needed to elucidate the ecological functions of WD to better understand their roles in maintaining biodiversity, enhancing productivity, and controlling vegetation degradation in karst forest ecosystems. [ABSTRACT FROM AUTHOR]

Understanding spatio-temporal dynamics of UF and its above-ground carbon storage (CS) is important for mitigating urban CO 2 emissions under China's rapid urban expansion and greening. In our study, vegetation index (VI) data obtained from TM image and CS derived from field-based surveys were amalgamated to develop a regression model to predict spatio-temporal patterns of CS. VI correction model was established by normalizing previous imagery (1984, 1995, and 2005) to 2014 image data. NDVI is better than other VIs for predicting urban forest CS. Both UF area and its CS increased gradually from 1984 to 2014, especially in outer rings of the city. CS showed a definite decreasing trend from outer rings to downtown. Due to urban greening policies, landscape patches of UF or CS recently became larger and more aggregated. The CS by UF class distribution was skewed toward low values in all the years, but the skew gradually decreased over time. It was estimated that the average annual increase of CS by UF could offset 3.9% of the average annual increase in urban carbon emissions. Our study proposes that spatio-temporal changes in UF patterns dramatically affected the amount of CS and carbon capture. The increase in UF coverage and quality would mitigate more urban carbon emissions, especially in outer rings. • The linear normalization models were established to correct multi-date imagery. • Vegetation index from TM image and carbon storage(CS) from field surveys were used to develop a predicting model for spatio-temporal CS. • Both urban forest(UF) area and CS increased gradually from 1984 to 2014, especially in outer rings of the city. • The average annual increase of CS by UF could offset 3.9% of the average annual increase in urban carbon emissions. [ABSTRACT FROM AUTHOR]

A large amount of stable soil organic matter (SOM) is derived from microbial necromass, which can be assessed by quantifying amino sugar biomarkers. Pinus massoniana Lamb. Plantations are widely distributed in China and play a vital role in forest carbon sequestration. However, the patterns of soil microbial residue remain poorly understood. In this study, amino sugars were used to characterize patterns of soil microbial residues at three soil depths (0–10, 10–20, and 20–30 cm) in P. massoniana plantations of different ages (young, middle-aged, near-mature, mature, and over-mature; denoted as YG, MD, NM, MT, and OM, respectively). In the topsoil (0–10 cm), the total nitrogen (TN) content of the OM forest was the highest, whereas the soil organic carbon (SOC) content of the MT forest was the highest. Consistent with changes in SOC and TN, total microbial residue content decreased with increasing soil depth. However, the total microbial residues C to SOC contribution increased considerably with increasing depth, suggesting that more SOC was derived from microbial residues in the subsoil than that from the topsoil. The fungal residue C to SOC contribution was higher than that of bacterial residue C. Total amino sugar content in the topsoil increased with increasing age, and MT and OM had a significantly higher content than that of other forests. At all soil depths, SOC and TN content predominantly determined microbial necromass, whereas soil microbial biomass content predominantly determined microbial necromass in the topsoil; soil pH predominantly determined microbial necromass in the 10–20 cm soil layer; and soil pH and Ca2+ content were the primary factors in the soil layer below 20 cm. The study provides valuable insights into controls of microbial-derived organic C could be applied in Earth system studies for predicting SOC dynamics in forests. • Soil organic carbon (SOC) and amino sugars decreased with soil depth. • The microbial residual content in topsoil showed an increasing trend with the increase of forest age. • A stronger mineral protection ability for amino sugar content in the subsoil than that in topsoil. [ABSTRACT FROM AUTHOR]

Carbon sink is an effective measure to balance the contradiction between economic development and mitigating climate change in China. This paper reveals that environmental performance of forest carbon sinks reflects in economic value by reducing the emissions abatement cost. The carbon trading system is used to demonstrate the environmental and economic value of forests. The forest carbon sequestrations are estimated and predicted in different regions of China. Furthermore, a market model has been established to assess how the emission reduction costs can be reduced among all regions by the year 2030 to achieve the goal of carbon emissions intensity in China. The results show that carbon sequestration trades can reduce the emissions reduction costs and it can represent the value of forest carbon sinks. In particular, when economic growth is maintained in moderate and low level in China, the national carbon trading market with carbon sequestration will decrease the carbon emissions reduction costs more effectively. Besides, carbon sink can bring economic benefits to under-developed regions where there are rich forest resources. Image 1 • Carbon sinks are coordination between the environment and the economy. • Carbon sinks can be valued by emissions trading market. • Forest carbon sinks help to achieve carbon emissions reduction targets. • Forest carbon sinks promote economic development in some backward areas. [ABSTRACT FROM AUTHOR]

• Little is known whether wood production is limited by growth rate. • Xylem production under drought environments is mainly explained by growth rate. • Under drier conditions, a longer growing season will not benefit xylem formation. • Warming-induced drought may limit carbon sequestration by reducing growth rate. • Do not extrapolate results of this study to drought-prone deciduous tree species. A number of studies have suggested that growing season length determines carbon sequestration of forest ecosystems. Given the possibility that drought-induced growth decline will be caused by a prolonged growing season under a warming climate, we investigated the effect of growth rate and duration of xylem production on annual wood biomass in drought-prone environments. We analyzed the intra-annual dynamics of wood formation in Qilian junipers (Juniperus przewalskii) from the semi-arid north-eastern Tibetan Plateau, China (2009–2014) and in ponderosa pine (Pinus ponderosa) from the hyperarid Mojave Desert in Nevada, USA (2015–2016). Most variability in the number of xylem cells (N cell) was related to growth rate (r m) rather than duration of cell production (D cell). At the Tibetan sites, 69.9% and 54.7% of variability in N cell was attributable to r m for the lower and upper treeline, respectively. Within the Mojave Desert site, 53.9% of the variability in N cell was related to r m. The growth rate in the Tibetan Plateau forest is affected by minimum temperature and precipitation. Thus, r m is a primary control on wood biomass in conifer species of semi-arid forests. Under warmer and drier conditions, a longer growing season will not benefit xylem formation of conifers, and in turn warming-induced drought could limit carbon sequestration by reducing the rate of cell production. [ABSTRACT FROM AUTHOR]

It is critical to accurately estimate carbon (C) turnover time as it dominates the uncertainty in ecosystem C sinks and their response to future climate change. In the absence of direct observations of ecosystem C losses, C turnover times are commonly estimated under the steady state assumption (SSA), which has been applied across a large range of temporal and spatial scales including many at which the validity of the assumption is likely to be violated. However, the errors associated with improperly applying SSA to estimate C turnover time and its covariance with climate as well as ecosystem C sequestrations have yet to be fully quantified. Here, we developed a novel model‐data fusion framework and systematically analyzed the SSA‐induced biases using time‐series data collected from 10 permanent forest plots in the eastern China monsoon region. The results showed that (a) the SSA significantly underestimated mean turnover times (MTTs) by 29%, thereby leading to a 4.83‐fold underestimation of the net ecosystem productivity (NEP) in these forest ecosystems, a major C sink globally; (b) the SSA‐induced bias in MTT and NEP correlates negatively with forest age, which provides a significant caveat for applying the SSA to young‐aged ecosystems; and (c) the sensitivity of MTT to temperature and precipitation was 22% and 42% lower, respectively, under the SSA. Thus, under the expected climate change, spatiotemporal changes in MTT are likely to be underestimated, thereby resulting in large errors in the variability of predicted global NEP. With the development of observation technology and the accumulation of spatiotemporal data, we suggest estimating MTTs at the disequilibrium state via long‐term data assimilation, thereby effectively reducing the uncertainty in ecosystem C sequestration estimations and providing a better understanding of regional or global C cycle dynamics and C‐climate feedback. Underestimated ecosystem carbon turnover time and sequestration under the steady state assumption (SSA) written summary: Considerable biases may arise when improperly invoking the SSA to estimate carbon turnover time at realistic dynamic disequilibrium state. This issue has not yet been carefully examined. Our finding provides a better understanding of the SSA‐induced uncertainty and the global carbon cycle dynamics and carbon‐climate feedback for future research. The SSA significantly underestimates the carbon turnover time by 29% and its sensitivity to temperature and precipitation by 22% and 42%, respectively, thereby leading to a 4.83‐fold underestimation of NEP in China's monsoonal forests, a principal C sink globally. These biases are negatively associated with forest age. [ABSTRACT FROM AUTHOR]

Forest ecosystems are an integral component of the global carbon cycle as they take up and release large amounts of C over short time periods (C flux) or accumulate it over longer time periods (C stock). However, there remains uncertainty about whether and in which direction C fluxes and in particular C stocks may differ between forests of high versus low species richness. Based on a comprehensive dataset derived from field-based measurements, we tested the effect of species richness (3-20 tree species) and stand age (22-116 years) on six compartments of above- and below-ground C stocks and four components of C fluxes in subtropical forests in southeast China. Across forest stands, total C stock was 149+12 Mg ha-1 with richness explaining 28.5% and age explaining 29.4% of variation in this measure. Species-rich stands had higher C stocks and fluxes than stands with low richness; and, in addition, old stands had higher C stocks than young ones. Overall, for each additional tree species, the total C stock increased by 6.4%. Our results provide comprehensive evidence for diversity-mediated above- and below-ground C sequestration in species-rich subtropical forests in southeast China. Therefore, afforestation policies in this region and elsewhere should consider a change from the current focus on monocultures to multi-species plantations to increase C fixation and thus slow increasing atmospheric CO2 concentrations and global warming. [ABSTRACT FROM AUTHOR]

Abstract: The Grain for Green Program (GGP) was the most all‐embracing program of ecological reconstruction implemented in China. To estimate carbon storages and carbon sequestration potentials of the GGP forests, the study presented in the paper collected data spanning from 1999 to 2010, such as tree species, tree planting area relevant to the GGP, empirical growth curves suitable for different planted tree species in China, as well as wood density (WD), biomass expansion factor (BEF), carbon fraction (CF) of different trees species, and estimated the carbon storages of the biomasses of GGP forests from 1999 to 2050. It showed that the total carbon storage of the biomass of GGP forests was 320.29 Tg upon the GGP completion in 2010; the total carbon sequestration is higher during the early GGP‐implementation stage than at the late GGP‐implementation stage, and the annual mean carbon sequestration of GGP forests was 26.69 Tg/year. The potential of GGP forests as carbon sink presented an increasing increment. In China, the potential increments of GGP forests as carbon sinks were estimated to be 397.34, 604.00, 725.53, and 808.90 Tg in 2020, 2030, 2040, and 2050, respectively, and the carbon sequestration rates were 1.72, 0.89, 0.52, and 0.36 Mg ha−1 year−1, respectively, corresponding to 2010s, 2020s, 2030s, and 2040s. Therefore, the GGP forests had bigger carbon sequestration capacities and potentials in China. [ABSTRACT FROM AUTHOR]

Spatially continuous mapping forest aboveground biomass (AGB) is crucial for better understanding the capacities of carbon sequestration capacities of forest ecosystems at both individual tree and landscape levels. Collecting field data is one of the most labor-intensive and time-consuming tasks in biomass mapping using airborne laser scanning (ALS) data. Building on a LiDAR biomass index (LBI) developed for use with terrestrial laser scanning (TLS) data, we successfully developed an improved and robust LBI-based approach to estimate forest AGB at both individual tree and plot levels while minimizing the effort required for field data collection. This approach was tested for larch, birch, and eucalyptus over three forest farms in Northeast China and one in Southern China. The results showed that LBI was highly correlated with the diameter, height, and AGB of larch trees. AGB estimates derived using LBI-based models for the three tree species were close to ground measurements at the individual tree level. They explained 81% to 95% of the variance of independent test data not used to calibrate those models. Tree level AGB estimates are required by many applications, but they could not be provided by commonly used plot-based biomass mapping approaches like LiDAR metrics-based regression (LMR) or Random Forest (RF). Calibrated with small fractions of the trees needed to calibrate LMR and RF models, LBI-based biomass models produced plot level biomass estimates comparable to or better than those produced using the two plot-based methods. More importantly, the LBI-based models generalized far better than LMR and RF among the three larch forest farms located hundreds of kilometers apart. These promising results warrant more research on the effectiveness of the LBI-based approach for other forest types and tree species not considered in this study. As LiDAR technology and related algorithms are evolving rapidly, further improvements to this approach might be feasible. A robust LBI-based approach applicable to a wide range of tree species and forest types across the globe will greatly facilitate the use of increasingly better and more affordable ALS data to support REDD+ (Reducing Emissions from Deforestation and Forest Degradation) and other forest-based climate mitigation initiatives. • An improved LBI was developed for mapping AGB using ALS data. • It was tested over 4 forest farms located in temperate and subtropical ecoregions. • Only 30+ trees were required to calibrate the AGB-LBI model for each species. • The calibrated models produced accurate estimates at both tree and plot levels. • The developed approach can greatly improve biomass mapping for forest farms. [ABSTRACT FROM AUTHOR]

• A dynamic estimation model (FCM model) for forest carbon storage at tree stand scale was established according to data of forest growth and degradation. • Simulation process and result of FCM model well reflected the growth of Aibes chensiensis species with a few input data. • geo-FCM model was a suitable and accurately estimation model for forest carbon storage at regional scale. • geo-FCM model can predict temporal changes of forest carbon storage at the regional scale. Accurate estimation of carbon storage of forest ecosystem has significant implication for mitigating global warming. In order to get accurate estimation of carbon storage of forest ecosystem at the regional scale and temporal dynamics in the Qinling Mountains, this study established a dynamic estimation model (FCM model) for forest carbon storage at tree stand scale according to the data of forest growth and degradation characteristics of Aibes chensiensis , and constructed a regional and temporal estimation model (geo-FCM model) based on FCM model and Aibes chensiensis spatial distribution data from 3S technology. The results showed that carbon density of Aibes chensiensis forest at tree age of 80 years from FCM model were 245.56 t ha−1, which was similar to the measured carbon densities from field investigation. The simulation process of the FCM model could well reflect the growth characteristic of Aibes chensiensis. The simulated result of geo-FCM model showed carbon storage of Abies chensiensis forest in study region were 5.23 × 105 t in year 2018 with the average carbon density of 222.26 t ha−1 and increased to 5.60 × 105 t in year 2028 along with tree growth. Its carbon storage increased 7.11% compared to the state of year 2018. The constructed model provided a robust method to estimate forest carbon storage of different tree species at different age stages at the regional scale, which can provide an important reference for forest management and selection of plantation tree species. [ABSTRACT FROM AUTHOR]

Despite evidence from experimental grasslands that plant diversity increases biomass production and soil organic carbon (SOC) storage, it remains unclear whether this is true in natural ecosystems, especially under climatic variations and human disturbances. Based on field observations from 6,098 forest, shrubland, and grassland sites across China and predictions from an integrative model combining multiple theories, we systematically examined the direct effects of climate, soils, and human impacts on SOC storage versus the indirect effects mediated by species richness (SR), aboveground net primary productivity (ANPP), and belowground biomass (BB). We found that favorable climates (high temperature and precipitation) had a consistent negative effect on SOC storage in forests and shrublands, but not in grasslands. Climate favorability, particularly high precipitation, was associated with both higher SR and higher BB, which had consistent positive effects on SOC storage, thus offsetting the direct negative effect of favorable climate on SOC. The indirect effects of climate on SOC storage depended on the relationships of SR with ANPP and BB, which were consistently positive in all biome types. In addition, human disturbance and soil pH had both direct and indirect effects on SOC storage, with the indirect effects mediated by changes in SR, ANPP, and BB. High soil pH had a consistently negative effect on SOC storage. Our findings have important implications for improving global carbon cycling models and ecosystem management: Maintaining high levels of diversity can enhance soil carbon sequestration and help sustain the benefits of plant diversity and productivity. [ABSTRACT FROM AUTHOR]

Characteristics of carbon storage and density in different layers of forest ecosystems should be studied comprehensively and in more detail. Using forest inventory data in combination with field survey data, we explored the characteristics of carbon storage and density in different layers of forest ecosystems in Liaoning Province of China. Results showed that total carbon storage was 813.034 Tg C. The carbon storage of soil layer accounted for 81.0% of the total storage with 658.783 Tg C, followed by those of arbor, litter and shrub layers with 128.403 Tg C (15.8%), 22.723 Tg C (2.8%) and 3.125 Tg C (0.4%), respectively. The average carbon density for the forest ecosystems were 183.571 Mg C ha-1, with soil layer (148.744 Mg C ha-1) being the highest one, followed by arbor layer (28.992 Mg C ha-1), litter layer (5.131 Mg C ha-1) and shrub-grass layer (0.706 Mg C ha-1). Carbon storage in different forest ecosystems varied from 1.595 to 319.161 Tg C, while C density ranged from 165.067 to 235.947Mg C ha-1, with the highest and lowest values being observed in soil layer and shrub-grass layers, respectively, implying that soil is the main body of forest carbon storage. Young-aged forests accounted for a greater proportion of forests in the Province than forests in other age classes; and proper management of forests could increase the carbon sequestration in the forest ecosystems. The comparison with previous estimations of carbon storage for forest ecosystem implied that methods and data used for forest carbon storage estimation affected the results of estimates obviously. [ABSTRACT FROM AUTHOR]