Aims
Our objectives were to study the spatial distribution of soil organic carbon (SOC) density and its influencing factors in the main forest ecosystems in Guangxi.
Methods
A total of 345 sample plots were established in Guangxi, and the size of each plot was 50 m × 20 m. Based on the forest resource inventory data and field investigation, the SOC storage of the main forests in Guangxi was estimated. Geostatistics was applied to analyze the spatial pattern of SOC density and the main influencing factors on SOC density were also explored by principal component analysis and stepwise regression.
Important findings
The total SOC storage in the main forests in Guangxi was 1686.88 Tg, and the mean SOC density was 124.70 Mg·hm^-2, which is lower than that of China. The best fitted semivariogram model of SOC density was exponential model, and the spatial autocorrelation was medium. The contour map based on Kriging indicated that northeastern Guangxi had high SOC density and northwestern Guangxi had low SOC density, which corresponded to high SOC density in non-karst region and low SOC density in karst region. The SOC density followed the sequence of bamboo forest > deciduous broadleaf forest > warm coniferous forest > mixed evergreen and deciduous broadleaf forest > evergreen broadleaf forest, and yellow soil > red soil > lateritic red soil > limestone soil. The dominant environment factors affecting SOC density included soil depth, longitude, latitude, and altitude. Soil depth was the most influential factor, which was mainly attributed to the karst landscape.

Aims
Estimating soil organic carbon (SOC) density and influence factors of tropical virgin forests in Hainan Island provide new insight in basic data for SOC pool estimation and its dynamics study.
Methods
The main distribution areas of tropical virgin forests in Jianfengling (JFL), Bawangling (BWL), Wu- zhishan (WZS), Diaoluoshan (DLS), Yinggeling (YGL) of Hainan Island were selected, and soil samples (0-100 cm) were sampled and analyzed. SOC density was estimated by soil vertical fitting method and soil stratification method to discover the distribution characteristics of soil organic carbon in tropical virgin forests of Hainan Island.
Important findings
Results showed that: (1) The average SOC density using soil vertical fitting method in JFL, BWL, WZS, DLS and YGL was 14.98, 18.46, 16.48, 18.81, 16.66 kg·m^-2, respectively, which was significantly higher (p < 0.05) than the estimated average SOC density using soil stratification method in these areas (14.73, 16.24, 15.50, 16.91, 15.03 kg·m^-2, respectively). It is better to use soil vertical fitting method for SOC density estimation when the soil was natural without disturbance. (2) The proportion of SOC content in the first 0-30 cm depth interval out of SOC in the whole 0-100 cm soil profiles in JFL, BWL, WZS, DLS and YGL was 50.50%, 48.56%, 43.49%, 47.37%, 42.88%, respectively. (3) SOC density was significantly negative correlated with Shannon-Wiener index, Simpson index, species richness, and soil bulk density; and was significantly positive correlated with altitude, soil porosity, and soil nitrogen. However, SOC density was not significantly correlated to slope, biomass, average diameter at breast height, or average height. (4) Our study area Hainan was located in low latitude area with high rainfall and high temperature, which accelerated the decomposition of organic matter and nutrient recycling, resulting in significantly lower SOC densities in this tropical virgin forests of Hainan Island than the average value in China.

Aims
Carbon sequestration is the basic function and most primary service of forest ecosystems, and plays a vital role in mitigating the global climate change. However, carbon storage and allocation in forest ecosystems have been less studied at regional scales than at forest stand levels, and the results are subject to uncertainty due to inconsistent methodologies. In this study we aim to obtain relatively accurate estimates of forest carbon stocks and sequestration rate at a provincial scale (regional) based on plot surveys of plants and soils.
Methods
In consideration of the areas and distributions of major forest types, 212 sampling plots, covering different age classes and origins (natural forests vs. planted forests), were surveyed in Gansu Province in northern China. Field investigations were conducted for vegetation layers (trees, shrubs, herbs and litter), soil profiles, and sampling of both plant materials and soils for laboratory analyses. Regional carbon stocks were calculated by up-scaling the carbon densities of all forest types with their corresponding areas. Carbon sequestration rate was estimated by referencing the reports of national forest inventory data for different periods.
Important findings Forest carbon stocks at the provincial scale were estimated at 612.43 Tg C, including 179.04 Tg C in biomass and 433.39 Tg C in soil organic materials. Specifically, natural forests stored 501.42 Tg C, approximately 4.52 times than that of the plantations. Biomass carbon density in both natural forests and plantations showed an increasing trend with stand age classes, and was greater in natural forests than in plantations within the same age classes. Soil carbon density also increased with stand age classes in natural forests, but the highest value occurred at the pre-mature stage in plantations. The weighted average of regional biomass carbon density was at 72.43 Mg C·hm^-2, with the average value of 90.52 Mg C·hm^-2 in natural forests and 33.79 Mg C·hm^-2 in plantations, respectively. In 1996, vegetation stored 132.47 Tg C in natural forests and 12.81 Tg C in plantations, respectively, and the values increased to 152.41 and 26.63 Tg C in 2011, with the mean carbon sequestration rates of 1.33 and 0.92 Tg C·a^-1. Given that young and middle-aged forests account for a large proportion (62.28%) of the total forest areas, the region is expected to have substantial potential of carbon sequestration.

Aims
Sparse Ulmus pumila forest is an intrazonal vegetation in Onqin Daga Sandy Land, while Populus simonii has been widely planted for windbreak and sand dune stabilization in the same region. Our objective was to compare the differences in carbon (C) density of these two forests and their relationships with stand age.
Methods
We measured the C content of tree organs (leaf, twig, stem, and root), herb layers (above ground vegetation and below ground root) and soil layers (up to 100 cm) in sparse Ulmus pumila forests and Populus simonii plantations of different stand ages, and then computed C density and their proportions in total ecosystem carbon density. In addition, we illustrated the variation in carbon density-stand age relationship for tree layer, soil layer and whole ecosystem. We finally estimated the C sequestration rates for these two forests by the space-for-time substitution approach.
Important findings
The average C contents of tree layer and soil layer for sparse Ulmus pumila forests were lower than those for Populus simonii plantations. The total C density of sparse Ulmus pumila forests was half of that of Populus simonii plantations. The carbon density of soil and tree layers accounted for more than 98% of ecosystem C density in the two forests. Irrespective of forest type, the C density ratios of soil to vegetation decreased with stand age. This ratio was 1.66 for sparse Ulmus pumila forests and 1.87 for Populus simonii plantations when they were over-matured. The C density of tree layer, soil layer, and total ecosystem in both forests increased along forest development. There were significantly positive correlations between tree layer’s C density and stand age in both forests and between the total ecosystem C density of sparse Ulmus pumila forests and stand age. The C sequestration rate of tree layer was 5-fold higher in Populus simonii plantation than in sparse Ulmus pumila forest. The ecosystem-level C sequestration rate was 0.81 Mg C·hm^-2·a^-1 for sparse Ulmus pumila forest and 5.35 Mg C·hm^-2·a^-1 for Populus simonii plantation. These findings have implications for C stock estimation of sandy land forest ecosystems and policy-making of ecological restoration and C sink enhancement in the studied area.

Aims
Forest carbon storage in Nei Mongol plays a significant role in national terrestrial carbon budget due to its large area in China. Our objectives were to estimate the carbon storage in the forest ecosystems in Nei Mongol and to quantify its spatial pattern.
Methods
Field survey and sampling were conducted at 137 sites that distributed evenly across the forest types in the study region. At each site, the ecosystem carbon density was estimated thorough sampling and measuring different pools of soil (0-100 cm) and vegetation, including biomass of tree, grass, shrub, and litter. Regional carbon storage was calculated with the estimated carbon density for each forest type.
Important findings
Carbon storage of vegetation layer in forests in Nei Mongol was 787.8 Tg C, with the biomass of tree, litter, herbaceous and shrub accounting for 93.5%, 3.0%, 2.7% and 0.8%, respectively. Carbon density of vegetation layer was 40.4 t·hm^-2, with 35.6 t·hm^-2 in trees, 2.9 t·hm^-2 in litter, 1.2 t·hm^-2 in herbaceous and 0.6 t·hm^-2 in shrubs. In comparison, carbon storage of soil layer in forests in Nei Mongol was 2449.6 Tg C, with 79.8% distributed in the first 30 cm. Carbon density of soil layer was 144.4 t·hm^-2. Carbon storage of forest ecosystem in Nei Mongol was 3237.4 Tg C, with vegetation and soil accounting for 24.3% and 75.7%, respectively. Carbon density of forest ecosystems in Nei Mongol was 184.5 t·hm^-2. Carbon density of soil layer was positively correlated with that of vegetation layer. Spatially, both carbon storage and carbon density were higher in the eastern area, where the climate is more humid. Forest reserves and artificial afforestations can significantly improve the capacity of regional carbon sink.

Aims
Forests represent the most important component of the terrestrial biological carbon pool and play an important role in the global carbon cycle. The regional scale estimation of carbon budgets of forest ecosystems, however, have high uncertainties because of the different data sources, estimation methods and so on. Our objective was to accurately estimate the carbon storage, density and sequestration rate in forest vegetation in Jilin Province of China, in order to understand the role of the carbon sink and to better manage forest ecosystems.
Methods
Vegetation survey data were used to determine forest distribution, size of area and vegetation types regionally. In our study, 561 plots were investigated to build volume-biomass models; 288 plots of shrubs and herbs were harvested to calculate the biomass of understory vegetation, and samples of trees, shrubs and herbs were collected to analyze carbon content. Carbon storage, density and sequestration rate were estimated by two forest inventory data (2009 and 2014), combined with volume-biomass models, the average biomass of understory vegetation and carbon content of vegetation. Finally, the distribution patterns of carbon pools were presented using ArcGIS soft ware.
Important findings
Understory vegetation biomass overall was less than 3% of the tree layer biomass, varying greatly among different forest types and even among the similar types. The carbon content of trees was between 45.80%-52.97%, and that of the coniferous forests was higher than that of the broadleaf forests. The carbon content of shrub and herb layers was about 39.79%-47.25% and 40%, respectively. Therefore, the vegetation carbon conversion coefficient was 0.47 or 0.48 in Jilin Province, and the conventional use of 0.50 or 0.45 would cause deviation of ±5.26%. The vegetation carbon pool of Jilin Province was at the upper range of regional carbon pool and had higher capacity of carbon sequestration. The value in 2009 and 2014 was 471.29 Tg C and 505.76 Tg C, respectively, and the total increase was 34.47 Tg C with average annual growth of 6.89 Tg C·a^-1. The corresponding carbon sequestration rate was 0.92 t·hm^-2·a^-1. The carbon density rose from 64.58 t·hm^-2 in 2009 to 66.68 t·hm^-2 in 2014, with an average increase of 2.10 t·hm^-2. In addition, the carbon storage of the Quercus mongolica forests and broadleaved mixed forests, accounted for 90.34% of that of all forests. The carbon increment followed the order of young > over-mature > near mature > middle-aged > mature forests. The carbon sequestration rate of followed the order of over-mature > young > near mature > middle-aged > mature forests. Both the carbon increment and the carbon sequestration rate of mature forests were negative. Furthermore, spatially the carbon storage and density were higher in the east than in the west of Jilin province, while the carbon increment was higher in northeast and middle east than in the west. The carbon sequestration rate was higher in Tonghua and Baishan in the south, followed by Jinlin in the middle and Yanbian in the east, while Baicheng and Songyuan, etc. in west showed negative values.

Aims
The concentration of CO₂ and other greenhouse gases in the atmosphere has considerably increased over last century and is set to rise further. Forest ecosystems play a key role in reducing CO₂ concentration in the atmosphere and mitigating global climate change. Our objective is to understand carbon storage and its distribution in forest ecosystems in Zhejiang Province, China.
Methods
By using the 8th forest resource inventory data and 2011-2012 field investigation data, we estimated carbon storage, density and its distribution in forest ecosystems of Zhejiang Province.
Important findings
The carbon storage of forest ecosystems in Zhejiang Province was 602.73 Tg, of which 122.88 Tg in tree layer, 16.73 Tg in shrub-herb layer, 11.36 Tg in litter layer and 451.76 Tg in soil layer accounting for 20.39%, 2.78%, 1.88% and 74.95% of the total carbon storage, respectively. The carbon storage of mixed broadleaved forests was 138.03 Tg which ranked the largest (22.90%) among all forest types. The young and middle aged forests which accounted for 70.66% of the total carbon storage were the main body of carbon storage in Zhejiang Province. The carbon density of forest ecosystems in Zhejiang Province was 120.80 t·hm^-2 and that in tree layer, shrub-herb layer, litter layer and soil layer were 24.65 t·hm^-2, 3.36 t·hm^-2, 2.28 t·hm^-2 and 90.51 t·hm^-2, respectively. The significant relationship between soil organic carbon storage and forest ecosystem carbon storage indicated that soil carbon played an important role in shaping forest ecosystem carbon density. Carbon density of tree layer increased with age in natural forests, but decreased in the order over-mature > near-mature > mature > middle-aged > young forest in plantations. The proportions of young and middle aged forests were larger than any other age classes. Thereby, the carbon storage of forest ecosystems in Zhejiang Province could be increased through a proper forest management.

Aims
Accurate estimation of carbon density and storage is among the key challenges in evaluating ecosystem carbon sink potentials for reducing atmospheric CO₂ concentration. It is also important for developing future conservation strategies and sustainable practices. Our objectives were to estimate the ecosystem carbon density and storage of Picea schrenkiana forests in Tianshan region of Xinjiang, and to analyze the spatial distribution and influencing factors.
Methods
Based on field measurements, the forest resource inventories, and laboratory analyses, we studied the carbon storage, its spatial distribution, and the potential influencing factors in Picea schrenkiana forest of Tianshan. Field surveys of 70 sites, with 800 m² (28.3 m × 28.3 m) for plot size, was conducted in 2011 for quantifying arbor biomass (leaf, branch, trunk and root), grass and litterfall biomass, soil bulk density, and other laboratory analyses of vegetation carbon content, soil organic carbon content, etc.
Important findings
The carbon content of the leaf, branch, trunk and root of Picea schrenkiana is varied from 46.56% to 52.22%. The vegetation carbon content of arbor and the herbatious/litterfall layer was 49% and 42%, respectively. The forest biomass of Picea schrenkiana was 187.98 Mg·hm^-2, with 98.93% found in the arbor layer. The biomass in all layers was in the order of trunk (109.81 Mg·hm^-2) > root (39.79 Mg·hm^-2) > branch (23.62 Mg·hm^-2) > leaf (12.76 Mg·hm^-2). From the age-group point of view, the highest and the lowest biomass was found at the mature forest (228.74 Mg·hm^-2) and young forest (146.77 Mg·hm^-2), respectively. The carbon density and storage were 544.57 Mg·hm^-2 and 290.84 Tg C, with vegetation portion of 92.57 Mg·hm^-2 and 53.14 Tg C, and soil portion of 452.00 Mg·hm^-2 and 237.70 Tg C, respectively. The spatial distribution of carbon density and storage appeared higher in the western areas than those in the eastern regions. In the western Tianshan Mountains (e.g., Ili district), carbon density was the highest, whereas the central Tianshan Mountains (e.g., Manas County, Fukang City, Qitai County) also had high carbon density. In the eastern Tianshan Mountains (e.g., Hami City), it was low. This distribution seemed consistent with the changes in environmental conditions. The primary causes of carbon density difference might be a combined effects of multiple environmental factors such as terrain, precipitation, temperature, and soil.

Aims
Our objective was to explore the vegetation carbon storages and their variations in the broad-leaved forests in the alpine region of the Qinghai-Xizang Plateau that includes Qinghai Province and Xizang Autonomous Region.
Methods
Based on forest resource inventory data and field sampling, this paper studied the carbon storage, its sequestration rate, and the potentials in the broad-leaved forests in the alpine region of the Qinghai-Xizang Plateau.
Important findings
The vegetation carbon storage in the broad-leaved forest accounted for 310.70 Tg in 2011, with the highest value in the broad-leaved mixed forest and the lowest in Populus forest among the six broad-leaved forests that include Quercus, Betula, Populus, other hard broad-leaved species, other soft broad-leaved species, and the broadleaved mixed forest. The carbon density of the broad-leaved forest was 89.04 Mg·hm^-2, with the highest value in other hard broad-leaved species forest and the lowest in other soft broad-leaved species forest. The carbon storage and carbon density in different layers of the forests followed a sequence of overstory layer > understory layer > litter layer > grass layer > dead wood layer, which all increased with forest age. In addition, the carbon storage of broad-leaved forest increased from 304.26 Tg in 2001 to 310.70 Tg in 2011. The mean annual carbon sequestration and its rate were 0.64 Tg·a^-1 and 0.19 Mg·hm^-2·a^-1, respectively. The maximum and minimum of the carbon sequestration rate were respectively found in other soft broad-leaved species forest and other hard broad-leaved species forest, with the highest value in the mature forest and the lowest in the young forest. Moreover, the carbon sequestration potential in the tree layer of broad-leaved forest reached 19.09 Mg·hm^-2 in 2011, with the highest value found in Quercus forest and the lowest in Betula forest. The carbon storage increased gradually during three inventory periods, indicating that the broad-leaved forest was well protected to maintain a healthy growth by the forest protection project of Qinghai Province and Xizang Autonomous Region.

Aims
Monitoring and quantifying the biomass and its distribution in urban trees and forests are crucial to understanding the role of vegetation in an urban environment. In this paper, an estimation method for biomass of urban forests was developed for the Shanghai metropolis, China, based on spatial analysis and a wide variety of data from field inventory and remote sensing.
Methods
An optimal regression model between forest biomass and auxiliary variables was established by stepwise regression analysis. The residual value of regression model was computed for each of the sites sampled and interpolated by Inverse-distance weighting (IDW) to predict residual errors of other sites not subjected to sampling. Forest biomass in the study area was estimated by combining the regression model based on remote sensing image data and residual errors of spatial distribution map. According to the distribution of plantations and management practices, a total of 93 sample plots were established between June 2011 and June 2012 in the Shanghai metropolis. To determine a suitable model, several spectral vegetation indices relating to forest biomass and structure such as normalized difference vegetation index (NDVI), ratio vegetation index (RVI), difference vegetation index (DVI), soil-adjusted vegetation index (SAVI), and modified soil-adjusted vegetation index (MSAVI), and new images synthesized through band combinations such as the sum of TM2, TM3 and TM4 (denoted Band 234), and the sum of TM3, TM4 and TM5 (denoted Band 345) were used as alternative auxiliary parameters .
Important findings
The biomass density in urban forests of the Shanghai metropolis varied from 15 to 120 t·hm^-2. The higher densities of forest biomass concentrated mostly in the urban areas, e.g. in districts of Jing’an and Huangpu, mostly ranging from 35 to 70 t·hm^-2. Suburban localities such as the districts of Jiading and Qingpu had lower biomass densities at around 15 to 50 t·hm^-2. The biomass density of Cinnamomum camphora trees across the Shanghai metropolis varied between 20 and 110 t·hm^-2. The spatial biomass distribution of urban forests displayed a tendency of higher densities in northeastern areas and lower densities in southwestern areas. The total biomass was 3.57 million tons (Tg) for urban forests and 1.33 Tg for C. camphora trees. The overall forest biomass was also found to be distributed mostly in the suburban areas with a fraction of 93.9%, whereas the urban areas shared a fraction of only 6.1%. In terms of the areas, the suburban and urban forests accounted for 95.44% and 4.56%, respectively, of the total areas in the Shanghai metropolis. Among all the administrative districts, the Chongming county and the new district of Pudong had the highest and the second highest biomass, accounting for 20.1% and 19.18% of the total forest biomass, respectively. In contrast, the Jing’an district accounted for only 0.11% of the total forest biomass. The root-mean-square error (RMSE), mean absolute error (MAE) and mean relative error (MRE) of the model for estimating urban forest biomass in this study were 8.39, 6.86 and 24.22%, respectively, decreasing by 57.69%, 55.43% and 64.00% compared to the original simple regression model and by 62.21%, 58.50%, 65.40% compared to the spatial analysis method. Our results indicated that a more efficient way to estimate urban forest biomass in the Shanghai metropolis might be achieved by combining spatial analysis with regression analysis. In fact, the estimated results based on the proposed model are also more comparable to the up-scaled forest inventory data at a city scale than the results obtained using regression analysis or spatial analysis alone.

Aims
This study was conducted to investigate carbon stocks in forest ecosystems of different stand ages in Anhui Province, and to identify the carbon sequestration potential of climax forests controlled by the natural environment conditions.
Methods
Data were collected based on field investigations and simulations were made with the BIOME4 carbon cycle model.
Important findings
Currently, the total forest carbon stocks in Anhui Province amounts to 714.5 Tg C: 402.1 Tg C in vegetation and 312.4 Tg C in soil. Generally, both the total and vegetation carbon density exhibit an increasing trend with the natural growth of forest stands. Soil carbon density increases from young to near mature forests, and then gradually decreases thereafter. Young and middle-aged forests account for 75% of the total forest area in Anhui Province, with potentially an additional 125.4 Tg C to be gained after the young and middle-aged forests reach near mature stage. Results of BIOME4 simulations show that potentially an additional 245.7 Tg C, including 153.7 Tg C in vegetation and 92 Tg C in soil, could be gained if the current forests are transformed into climax forest ecosystems in Anhui Province.

Aims
Plantations play important roles in modifying regional carbon budget and maintaining regional carbon balance. In this study, we assessed larch plantation (Larix gmelinii var. principis-rupprechtii) carbon dynamics in Weichang County from a perspective of the forest biomass-soil-wood-products chain. Our objectives were to elucidate the carbon sink capacity of larch plantation and the influences of biomass, soil and wood product pools on carbon balance.
Methods
CO2FIX model was used to evaluate the carbon storage and flow of larch plantation over a time span of 120 years. Input data for model were derived from practical investigations and published papers. We validated the simulated results and found that this model was suitable in the region and the simulated results were reliable.
Important findings
(1) Soil was the largest carbon pool for larch plantation and the wood product pool had the smallest carbon storage. Meanwhile, carbon storage in wood products gradually increased with time. (2) In a rotation of 50 years from secondary poplar-birch forest to larch plantation, 250 t C·hm^-2 was sequestrated by the larch plantation. 70% of the carbon was transferred into soil in the form of litter and logging slash and the other 30% was transferred into wood products. (3) Larch plantation was a carbon sink during most of its growing period and turned to temporary carbon source when it was harvested. Larch plantation could sequestrate about 0.3 t C·hm^-2·a^-1 in the long term. Our results indicated the importance of wood product carbon pool in carbon dynamics of plantation, which facilitated our understanding in the carbon dynamics and capacity of plantation.

Aims
This study aims to evaluate the impacts of future climate change on vegetation and soil carbon accumulation rate in China’s forests.
Methods
The vegetation and soil carbon storage were predicted by the atmosphere-vegetation interaction model (AVIM2) based on B2 climate change scenario during the period of 1981-2040. This study focused on mature forests in China and the forested area maintained constant over the study period. The carbon accumulation rate in year t is defined as the carbon storage of year t minus that of year t-1.
Important findings
Under B2 climate change scenario, mean air temperature in China’s forested area was projected to rise from 7.8 °C in 1981 to 9.0 °C in 2040. The total vegetation carbon storage was then estimated to increase from 8.56 Pg C in 1981 to 9.79 Pg C in 2040, meanwhile total vegetation carbon accumulation rate was estimated to fluctuate between -0.054-0.076 Pg C·a^-1, with the average of 0.022 Pg C·a^-1. The total soil carbon storage was estimated to increase from 30.2 Pg C in 1981 to 30.72 Pg C in 2040, and total soil carbon accumulation rate was estimated to vary in the range of -0.035-0.072 Pg C·a^-1, with the mean of 0.010 Pg C·a^-1. The response of vegetation and soil carbon accumulation rate to climate change had significant spatial difference in China although the two time series did not show significant trend over the study period. Our results also showed warming was not in favor of forest carbon accumulation, so in the northeastern and southeastern forested area, especially in the Changbai Mountain, with highest temperature increase in the future, the vegetation and soil carbon accumulation rate were estimated to decrease greatly. However, in the southern of southwestern forested area and other forested area, with relatively less temperature increase, the vegetation and soil carbon accumulation rate was estimated to increase in the future.