Forest Biomass Carbon Storage Research Articles

Spatial and Temporal Patterns of Forest Biomass Carbon Sink in China from 1990 to 2021

China’s forests act as a large carbon sink and play a vital role in achieving the carbon neutrality goal by the 2060s. To achieve this goal, the magnitude and spatial patterns of forest carbon sinks must be accurately quantified. In this study, we aim to provide the longest estimate of forest biomass carbon storage and sinks in China at a 1 km spatial resolution from 1990 to 2021 by merging long-term observations from optical and microwave remote sensing datasets with a field-validated benchmark map. We explored the spatial characteristics of aboveground biomass (AGB) and belowground biomass (BGB) carbon in China’s forests, as well as variations in AGB carbon sinks. The average AGB and BGB carbon storage from 1990 to 2021 in China’s forests were 8.42 ± 0.96 Pg C and 1.9 ± 0.21 Pg C, respectively. The average annual AGB carbon sink during this period was approximately 0.083 ± 0.023 Pg C yr−1. Forests in the southwest region contributed 31.15% of the forest AGB carbon sink in China and contributed 41.01% of the forest AGB carbon storage. Our study presents an effective tool for assessing changes in forest biomass carbon by leveraging comprehensive multi-source remote sensing data and highlights the importance of obtaining large-scale, high-quality, consistent, and accessible plot survey data to validate the earth observation of biomass.

Tree richness increased biomass carbon sequestration and ecosystem stability of temperate forests in China: Interacted factors and implications

Biodiversity loss and forest degradation have received increasing attention worldwide, and their effects on forest biomass carbon storage and stability have not yet been well defined. This study examined 1275 tree plots using the field survey method to quantify the effects of tree diversity, tree sizes, and mycorrhizal symbiont abundance on biomass carbon storages (Cs) and NDVI (Normalized Difference Vegetation Index)-based ecosystem stability (standard deviation/mean NDVI = NDVI_S) during the field survey period from 2008 to 2018. Our data showed Cs and NDVI_S averaged at 31–108 t ha−1 and 32.04–49.28, respectively, and positive relations between Cs and NDVI_S were observed (p < 0.05). Large forest-type and regional variations were found in these two parameters. Broadleaf forests had 74% of Cs (p < 0.05) of the conifer forests, but no differences were in NDVI_S. Cold regions at high latitudes had 71% of NDVI_S in the warm regions at low latitudes, while no differences were in Cs. Moist regions at high longitudes had 2.04 and 1.28-fold higher Cs and NDVI_S (p < 0.05). The >700 m a.s.l. regions had 1.24-fold higher Cs (p < 0.01) than the <700 m a.s.l. regions, but similar NDVI_S (p > 0.05). Nature Reserves had 1.94-fold higher Cs but 30% lower NDVI_S than outside Reserves (p < 0.001). > 40-year-old forests had 1.3- and 2-fold higher Cs and NDVI_S than the young forests. Structural equation modeling and hierarchical partitioning revealed the driving paths responsible for these variations. Tree richness was positively associated with Cs and ecosystem stability, contributing 21.6%–30.6% to the total effects on them; tree sizes significantly promoted the Cs, but had negligible impacts on NDVI_S. MAT's total effects on NDVI_S of conifer forests were 40% higher than that of broadleaf forests, MAP's total effects on Cs varied with forest types; arbuscular mycorrhizal tree dominance exhibited a smaller positive impact on Cs and ecosystem stability in comparison to other factors. Our findings underscore that the significance of climatic-adapted forest management, diversity conservation, and big-sized tree protections can support the achievement of carbon neutrality in China from biomass carbon sequestration and ecosystem stability.

Storing Carbon in Forest Biomass and Wood Products in Poland—Energy and Climate Perspective

Huge amounts of carbon being sequestered in forest ecosystems make them an important land carbon sink at the global scale. Their ability to withdraw carbon dioxide (CO2) from the atmosphere, whose concentration is gradually increasing due to anthropogenic emissions, renders them important natural climate-mitigation solutions. The urgent need for transition from high to zero net emission on country, continental, and global scales, to slow down the warming to an acceptable level, calls for the analysis of different economic sectors’ roles in reaching that ambitious goal. Here, we examine changes in CO2 emission and sequestration rates during recent decades focusing on the coal-dominated energy sector and Land Use, Land-Use Change, and Forestry (LULUCF) as well as wood production at the country level. The main purpose of the presented study is to examine the potential of storing carbon in standing forest biomass and wood products in Poland as well as the impact of disturbances. The ratio of LULUCF absorption of CO2 to its emission in Poland has ranged from about 1% in 1992 to over 15% in 2005. From a climate-change mitigation point of view, the main challenge is how to maximize the rate and the duration of CO2 withdrawal from the atmosphere by its storage in forest biomass and wood products. Enhancing carbon sequestration and storage in forest biomass, via sustainable and smart forestry, is considered to be a nature-based climate solution. However, not only forests but also wood-processing industries should be included as important contributors to climate-change mitigation, since harvested wood products substitute materials like concrete, metal, and plastic, which have a higher carbon footprint. The energy perspective of the paper embraces two aspects. First, CO2 sequestration in forests and subsequently in harvested wood products, is an effective strategy to offset a part of national CO2 emissions, resulting largely from fossil fuel burning for energy-production purposes. Second, wood as biomass is a renewable energy source itself, which played an important role in sustaining energy security for many individual citizens of Poland during the unusual conditions of winter 2022/2023, with a scarce coal supply.

The Carbon Neutral Potential of Forests in the Yangtze River Economic Belt of China

Prediction of forest carbon sink in the future is important for understanding mechanisms concerning the increase in carbon sinks and emission reduction, and for realizing the climate goals of the Paris Agreement and global carbon neutrality. Based on stand volume data of permanent monitoring plots of the successive national forest inventories from 2004 to 2018, and combined with multiple variables, such as climatic factors, soil properties, stand attributes, and topographic features, the random forest algorithm was used to predict the stand volume growth-loss and then calculated the forest biomass and its carbon sink potential between 2015 to 2060 in the Yangtze River Economic Belt of China. From 2015 to 2060, the predicted forest biomass carbon storage and density increased from 3053.27 to 6721.61 Tg C and from 33.75 to 66.12 Mg C hm−2, respectively. The predicted forest biomass carbon sink decreased from 90.58 to 73.98 Tg C yr−1, and the average forest biomass carbon storage and sink were ranked in descending order: Yunnan, Sichuan, Jiangxi, Hunan, Guizhou, Hubei, Zhejiang, Chongqing, Anhui, Jiangsu, and Shanghai. The forest biomass carbon storage in the Yangtze River Economic Belt will increase by 3.67 Pg C from 2015 to 2060. The proportion of forest C sinks on the regional scale to C emissions on the national scale will increase from 2.9% in 2021–2030 to 4.3% in 2041–2050. These results indicate higher forest carbon sequestration efficiency in the Yangtze River Economic Belt in the future. Our results also suggest that improved forest management in the upper and middle reaches of the Yangtze River will help to enhance forest carbon sink in the future.

Plant phosphorus-use and -acquisition strategies in Amazonia.

In the tropical rainforest of Amazonia, phosphorus (P) is one of the main nutrients controlling forest dynamics, but its effects on the future of the forest biomass carbon (C) storage under elevated atmospheric CO2 concentrations remain uncertain. Soils in vast areas of Amazonia are P-impoverished, and little is known about the variation or plasticity in plant P-use and -acquisition strategies across space and time, hampering the accuracy of projections in vegetation models. Here, we synthesize current knowledge of leaf P resorption, fine-root P foraging, arbuscular mycorrhizal symbioses, and root acid phosphatase and organic acid exudation and discuss how these strategies vary with soil P concentrations and in response to elevated atmospheric CO2 . We identify knowledge gaps and suggest ways forward to fill those gaps. Additionally, we propose a conceptual framework for the variations in plant P-use and -acquisition strategies along soil P gradients of Amazonia. We suggest that in soils with intermediate to high P concentrations, at the plant community level, investments are primarily directed to P foraging strategies via roots and arbuscular mycorrhizas, whereas in soils with intermediate to low P concentrations, investments shift to prioritize leaf P resorption and mining strategies via phosphatases and organic acids.

Preliminary Estimation of Soil Carbon Sequestration of China's Forests during 1999–2008

The National Forest Inventory (NFI) is an important resource for estimating the national carbon balance (These data were unpublished data, and we could only obtain the data before 2008 through data search by now). Based on the data from sample plots, the literature, and NFI, as well as the relationships between volume, biomass, annual litterfall and soil respiration of different forest types, the net ecosystem production (NEP), changes in forest biomass carbon storage (ΔCbiomass) and non-respiratory losses (NR) of China's forests during 1999–2008 were estimated, and the forest soil carbon sequestration (ΔCsoil) was assessed according to the carbon balance principle of the forest ecosystem (ΔCsoil = NEP – NR – ΔCbiomass). The results showed that the total NEP, ΔCbiomass, NR and ΔCsoil values for China's forests were 157.530, 48.704, 31.033 and 77.793 Tg C yr–1 respectively, and average NEP, ΔCbiomass, NR, and ΔCsoil values were 101.247, 31.303, 19.945 and 49.999 g C m–2 yr–1 respectively. There were large spatial differences in forest soil carbon sequestration in different parts of China. The forest soil in Jiangxi, Hunan, Zhejiang, Fujian, Anhui, Shanxi, Shaanxi, Guangxi and Liaoning served as carbon sources and the carbon released was about 25.507 Tg C yr–1. The other 22 provinces served as carbon sinks and the average carbon sequestration by forest soil came to 103.300 Tg C yr–1. This research established a method for evaluating soil carbon sequestration by China's forests based on the NFI, which is a useful supplement to current statistical data-based studies on the forest ecosystem carbon cycle, and can promote comparable studies on forest soil carbon sequestration with consistent research methods at the regional scale.

Climate warming-induced replacement of mesic beech by thermophilic oak forests will reduce the carbon storage potential in aboveground biomass and soil

Key messageClimate-warming related replacement of beech by oak forests in the course of natural forest succession or silvicultural decisions may considerably reduce ecosystem carbon storage of central European woodlands.ContextClimate warming may change the carbon (C) storage in forest biomass and soil through future shifts in tree species composition. With a projected warming by 2–3 K over the twenty-first century, silvicultural adaptation measures and natural succession might lead to the replacement of European beech forests by thermophilic oak forests in drought- and heat-affected regions of central and south-eastern Europe, but the consequences for ecosystem C storage of this species shift are not clear.AimsTo quantify the change in C storage in biomass and soil with a shift from beech (Fagus sylvatica) to oak forest (Quercus petraea, Q. frainetto, Q. cerris), we measured the aboveground biomass (AGC) and soil C pools (SOC).MethodsAGC pools and SOC stocks to − 100 cm depth were calculated from forest inventory and volume-related SOC content data for beech, mixed beech-oak and oak forests in three transects in the natural beech-oak ecotone of western Romania, where beech occurs at its heat- and drought-induced distribution limit.ResultsFrom the cooler, more humid beech forests to the warmer, more xeric oak forests, which are 1–2 K warmer, AGC and SOC pools decreased by about 22% (40 Mg C ha−1) and 20% (17 Mg C ha−1), respectively. The likely main drivers are indirect temperature effects acting through tree species and management in the case of AGC, but direct temperature effects for SOC.ConclusionIf drought- and heat-affected beech forests in Central Europe are replaced by thermophilic oak forests in future, this will lead to carbon losses of ~ 50–60 Mg ha−1, thus reducing ecosystem carbon storage substantially.

Forest biomass carbon pool dynamics in Tibet Autonomous Region of China: Inventory data 1999-2019.

According to the forest resources inventory data for different periods and the latest estimation parameters of forest carbon reserves in China, the carbon reserves and carbon density of forest biomass in the Tibet Autonomous Region from 1999 to 2019 were estimated using the IPCC international carbon reserves estimation model. The results showed that, during the past 20 years, the forest area, forest stock, and biomass carbon storage in Tibet have been steadily increasing, with an average annual increase of 1.85×104 hm2, 0.033×107 m3, and 0.22×107 t, respectively. Influenced by geographical conditions and the natural environment, the forest area and biomass carbon storage gradually increased from the northwest to the southeast, particularly in Linzhi and Changdu, where there are many primitive forests, which serve as important carbon sinks in Tibet. In terms of the composition of tree species, coniferous forests are dominant in Tibet, particularly those containing Abies fabri, Picea asperata, and Pinus densata, which comprise approximately 45% of the total forest area in Tibet. The ecological location of Tibet has resulted in the area being dominated by shelter forest, comprising 68.76% of the total area, 64.72% of the total forest stock, and 66.34% of the total biomass carbon reserves. The biomass carbon storage was observed to first increase and then decrease with increasing forest age, which is primarily caused by tree growth characteristics. In over-mature forests, trees’ photosynthesis decreases along with their accumulation of organic matter, and the trees can die. In addition, this study also observed that the proportion of mature and over-mature forest in Tibet is excessively large, which is not conducive to the sustainable development of forestry in the region. This problem should be addressed in future management and utilization activities.

Community Forest Carbon Assessment in Eastern Thailand from Forest Conservation Management by Local People

One measure of increasing carbon sequestration areas is community forest conservation, which is the way to maintain common forest areas linking with human livelihoods. The first step towards implementing incentive mechanism of Reducing Emissions from Deforestation and Degradation (REDD) at the national level is to assess the amount of forest carbon. This is important for REDD inspections and subsequent funding from public funds or carbon markets. The objective is to find the carbon stock in soil, aboveground and belowground biomass for estimated carbon price in the community forest. The study site was carried out at Ban Phrao community forest, Sa Kaeo Province, East of Thailand. Field data were collected from temporary 16 plots the diversity of plant species, to assess forest biomass carbon storage based on the allometric equation, and to estimate the proportion of carbon contents in plant and soil by using CHN analyzer.

Mapping aboveground biomass and carbon in Shanghai's urban forest using Landsat ETM+ and inventory data

Quantifying the spatiotemporal distribution of forest biomass carbon (FBC) is vital for the management of urban forests in accordance with the rapid urbanization. This paper presents a method for quantifying and estimating the urban FBC in Shanghai, China, between 2005 and 2015, using data from 93 sampling forest plots and Landsat ETM + data. Our study included an analysis of the choice of predicted factors to estimate FBC and the method of carbon density estimation employed in the estimation. The results showed that combining regression analysis and spatial analysis to map forest carbon stocks at city level make available FBC estimates for the urban forests of Shanghai, China. Based on the proposal method, there was a decreasing trend of carbon density from downtown areas to outer suburban areas. About 92 % of the overall FBC storage in Shanghai distributed in the suburban areas whereas the urban areas shared a fraction amounting to only 8 % in 2015. From 2011–2015, the total urban forest carbon storage gradually increased by 32.3 %, whereas the average carbon density gradually decreased by 8.21 % in the urban areas. The associated values both increased continuously from 2005–2011, from 2005 to 2011, but the average carbon storage density decreased in the suburban districts. The total carbon stocks in the estimated forest biomass across Shanghai were about 1.5 Tg in 2005 and 2008, and 1.7 Tg in 2011 and 2015, while the associated average FBC density remained at about 17.5 t/ha from 2005 to 2015. This study provides important information required to manage the urban forest stand for optimal carbon sequestration.

Re-estimating the changes and ranges of forest biomass carbon in China during the past 40\u2009years

BackgroundIn recent decades the future of global forests has been a matter of increasing concern, particularly in relation to the threat of forest ecosystem responses under potential climate change. To the future predictions of these responses, the current forest biomass carbon storage (FCS) should first be clarified as much as possible, especially at national scales. However, few studies have introduced how to verify an FCS estimate by delimiting the reasonable ranges. This paper addresses an estimation of national FCS and its verification using two-step process to narrow the uncertainty. Our study focuses on a methodology for reducing the uncertainty resulted by converting from growing stock volume to above- and below-ground biomass (AB biomass), so as to eliminate the significant bias in national scale estimations.MethodsWe recommend splitting the estimation into two parts, one part for stem and the other part for AB biomass to preclude possible significant bias. Our method estimates the stem biomass from volume and wood density (WD), and converts the AB biomass from stem biomass by using allometric relationships.ResultsBased on the presented two-step process, the estimation of China’s FCS is performed as an example to explicate how to infer the ranges of national FCS. The experimental results demonstrate a national FCS estimation within the reasonable ranges (relative errors: + 4.46% and − 4.44%), e.g., 5.6–6.1 PgC for China’s forest ecosystem at the beginning of the 2010s. These ranges are less than 0.52 PgC for confirming each FCS estimate of different periods during the last 40 years. In addition, our results suggest the upper-limits by specifying a highly impractical value of WD (0.7 t∙m− 3) on the national scale. As a control reference, this value decides what estimate is impossible to achieve for the FCS estimates.ConclusionsPresented methodological analysis highlights the possibility to determine a range that the true value could be located in. The two-step process will help to verify national FCS and also to reduce uncertainty in related studies. While the true value of national FCS is immeasurable, our work should motivate future studies that explore new estimations to approach the true value by narrowing the uncertainty in FCS estimations on national and global scales.

Estimation of Forest Biomass and Carbon Storage in China Based on Forest Resources Inventory Data

Forests are important in the global carbon cycle and it is necessary to quickly and accurately measure forest volume to estimate forest aboveground biomass (AGB) and aboveground carbon storage (AGC). In this paper, we used data from the eighth forest resources inventory of China to establish two stand volume models based on stand density and forest basal area for 37 arbor forest types (dominant species); and performed a comparative analysis to obtain the best model. Then the AGB, AGB density, AGC, and AGC density of the different forest types and regions were estimated by conversion function methods. The results showed that: (1) The volume model of tree height and forest basal area could better fit the natural growth process of forests, and 36 of the 37 forest types had R2 greater than 0.8; (2) The average AGB density of arbor forest in China was 95.03 Mg ha−1 and the average AGC density was 48.15 Mg ha−1 (3) Among forest types, Picea asperata Mast., Quercus spp., and Populus spp. had the highest AGB and AGC, while Cinnamomum camphora (L.) Presl, Pinus taiwanensis Hayata, and Pinus densiflora Sieb. et Zucc. had the lowest. The AGB density and AGC density of Phoebe zhennan S. Lee et F. N. Wei and Pinus densata Mast. were the highest, while those of Pinus densiflora Sieb. et Zucc., Pinus elliottii Engelmann, and Eucalyptus robusta Smith were the lowest. (4) Among regions, AGB and AGC ranging from high to low, were as follows: northwest, southwest, northeast, central south, east, and north. The northwest and southwest regions accounted for more than 70% of the country’s AGB and AGC. The average AGB density and AGC density among the regions were 91.34 Mg ha−1 and 46.4 Mg ha−1, respectively. Ranging from high to low as follows: southwest, northwest, northeast, east, central south, and north. The methods used in this paper provide a basis for fast and accurate estimation of stand volume, and the estimates of AGB and AGC have important reference value for explaining the role of ecosystems in coping with global climate change in China.

Difference analysis in estimating biomass conversion and expansion factors of masson pine in Fujian Province, China based on national forest inventory data: A comparison of three decision tree models of ensemble learning.

Biomass conversion and expansion factors (BCEFs) are important parameters for estimating carbon storage in forest biomass. Clarifying the source of differences in estimating BCEFs could reduce uncertainties in forest biomass carbon estimation. The decision tree models of ensemble learning can be used to properly figure out the source of differences in estimating BCEFs. However, the comparison of different decision tree models for analyzing differences in estimating BCEFs has never been reported. In this study, three models [the boosted regression trees (BRT), random forest(RF), and Cubist] and data of 331 masson pine plots from the 8th Chinese National Forest Inventory for Fujian Province were used to analyze the differences in estimating BCEFs (including above- and below-ground). The results showed that BCEFs were following right-skewed distribution, with the mean, minimum and maximum value being 0.69 t·m-3, 0.67 t·m-3 and 0.71 t·m-3, respectively. All three models performed well in BCEFs prediction and fitting, and could explain more than 92.8% variations of BCEFs. All three models showed that average DBH and volume were the top two highest relative importance predictors. BCEFs decreased with the increases of average DBH and volume. Stand characteristics factors, such as average DBH, volume, average age and average height, had great influence on BCEFs. Both soil factors and topographic factors had little influence on BCEFs. Using a few variables (such as average DBH, volume, average age and avera-ge height) which contained more BCEFs prediction information could have preferable forecasting precision when building BCEFs models. Moreover, widely representative samples with different average tree ages, average DBH and volume should be chosen to calculate BCEFs when applying constant BCEFs.

Shifts in tree functional composition amplify the response of forest biomass to climate.

Forests have a key role in global ecosystems, hosting much of the world's terrestrial biodiversity and acting as a net sink for atmospheric carbon. These and other ecosystem services that are provided by forests may be sensitive to climate change as well as climate variability on shorter time scales (for example, annual to decadal). Previous studies have documented responses of forest ecosystems to climate change and climate variability, including drought-induced increases in tree mortality rates. However, relationships between forest biomass, tree species composition and climate variability have not been quantified across a large region using systematically sampled data. Here we use systematic forest inventories from the 1980s and 2000s across the eastern USA to show that forest biomass responds to decadal-scale changes in water deficit, and that this biomass response is amplified by concurrent changes in community-mean drought tolerance, a functionally important aspect of tree species composition. The amplification of the direct effects of water stress on biomass occurs because water stress tends to induce a shift in tree species composition towards species that are more tolerant to drought but are slower growing. These results demonstrate concurrent changes in forest species composition and biomass carbon storage across a large, systematically sampled region, and highlight the potential for climate-induced changes in forest ecosystems across the world, resulting from both direct effects of climate on forest biomass and indirect effects mediated by shifts in species composition.

An assessment of forest biomass carbon storage and ecological compensation based on surface area: A case study of Hubei Province, China

Area is a basic indicator used in ecological investigations; conventional ellipsoid area describes the earth as a standard ellipsoid without considering undulation of the surface. However, using conventional ellipsoid area in ecological investigations introduces errors in the estimation of forest biomass carbon storage (BCS) in mountainous and hilly areas. In this study, BCS and ecological compensation of the 103 counties in Hubei Province, China, were measured using surface area. Results show that: (1) the surface area of Hubei Province is about 1.97×105km2, approximately 1.34×104km2 greater than the calculated ellipsoid area. In terms of forest area, the surface and ellipsoid areas are 6.52×104 and 5.92×104km2, respectively; forest area calculated using surface area is 10.13% greater than that using ellipsoid area. (2) There is a significant difference between the BCS measured in the two areas for mountain landforms, the average difference being 9.13×104 t. Plain landforms and hilly landforms have lower average differences, 2.63×103 t and 2.95×104 t, respectively. (3) The ecological compensation for forest ecosystems in Hubei Province is 33.47 billion Yuan and counties that should be assigned the highest ecological compensation are mainly located in western Hubei. (4) The differences in BCS calculated by the two area methods indicate a typical state of agglomeration in the region, where the western mountainous area belongs to the High–High cluster and the central–southern plain region to the Low–Low cluster. Findings from our investigation show an applied prospective for quantitatively estimating BCS and other resources in a much larger scale. Furthermore, ecological compensation transfer provides a reference for government decision makers to balance the interests of different regions for sustainable development and eco-environmental protection.

The Effects of Land Cover Changes on Forest Carbon Storage in 40 Years: A Case Study in Turkey

In this study, forest biomass carbon storage changes were estimated for a case study area of Caykara planning unit based on forest inventory for the years 1971 and 2010 using tree species dependent biomass expansion factors. The outputs were handled in the context of forest dynamics represented by temporal and spatial changes of land cover. Quantitative evidence showed that there were drastic changes of carbon storage in above and below ground forest ecosystems from 2.34 Tg carbon to 3.91 Tg carbon between two periods. Carbon sequestration rate was 1.37 Mg carbon yr–1 ha–1 for living biomass due mainly to the increase of forest area and growing stock and its quality. On the other hand, such a rate of increase in carbon storage was not influenced negatively by an almost tripling in the total number of patches from 406 to 1,445 in the same period.

Spatiotemporal Distribution and Driving Factors of Forest Biomass Carbon Storage in China: 1977–2013

Increasing forest vegetation is important for carbon dynamics and to maintain the ecological and environmental balance in China. However, there is little understanding of how socioeconomic factors affect forest biomass carbon storage (FBCS). Here, we used continuous functions for biomass expansion factors and China’s seven completed forest inventories to estimate the changes in FBCS for 31 provinces in mainland China between 1977 and 2013. We developed a model that decomposes the contribution of the different socioeconomic factors driving FBCS. We found China’s FBCS increased from 4972 TgC (1 Tg = 1012g) in 1977–1981 to 7435 TgC in 2009–2013, with a mean growth of 77 TgC/a, and the average forest carbon density increased from 36.0 to 38.9Mg/ha (1 Mg = 106g), mainly due to the arbor forest contribution. Among the seven regions in China, the southwestern region currently accounts for the highest proportion (37.3%) of national FBCS, followed by northeastern (19.7%), northern (12.5%) and eastern region (10.8%). The main socio-economic factors affecting FBCS were forest land dependence, industrial structure and economic development level. Optimizing forest type and age structure, improving forest productivity, and strengthening forest management are feasible options to further increase China’s FBCS.

Dynamics of forest biomass carbon stocks from 1949 to 2008 in Henan Province, east-central China

We estimated forest biomass carbon storage and carbon density from 1949 to 2008 based on nine consecutive forest inventories in Henan Province, China. According to the definitions of the forest inventory, Henan forests were categorized into five groups: forest stands, economic forests, bamboo forests, open forests, and shrub forests. We estimated biomass carbon in forest stands for each inventory period by using the continuous biomass expansion factor method. We used the mean biomass density method to estimate carbon stocks in economic, bamboo, open and shrub forests. Over the 60-year period, total forest vegetation carbon storage increased from 34.6 Tg (1 Tg = 1 × 1012 g) in 1949 to 80.4 Tg in 2008, a net vegetation carbon increase of 45.8 Tg. By stand type, increases were 39.8 Tg in forest stands, 5.5 Tg in economic forests, 0.6 Tg in bamboo forests, and −0.1 Tg in open forests combine shrub forests. Carbon storage increased at an average annual rate of 0.8 Tg carbon over the study period. Carbon was mainly stored in young and middle-aged forests, which together accounted for 70–88% of the total forest carbon storage in different inventory periods. Broad-leaved forest was the main contributor to forest carbon sequestration. From 1998 to 2008, during implementation of national afforestation and reforestation programs, the carbon storage of planted forest increased sharply from 3.9 to 37. 9 Tg. Our results show that with the growth of young planted forest, Henan Province forests realized large gains in carbon sequestration over a 60-year period that was characterized in part by a nation-wide tree planting program.

Improving the estimate of forest biomass carbon storage by combining two forest inventory systems

ABSTRACTQuantifying forest carbon storage and its spatial distribution at regional scales is critical for the creation of greenhouse gases inventories, the evaluation of forest services and carbon-oriented forest management. The plot-based forest inventory (PBFI) and stand-based forest inventory (SBFI) collect extensive information on trees and stands respectively, and together, provide an opportunity to improve the regional estimates of forest carbon. In this study, we applied the SBFI to overcome the spatial extent limits of the PBFI in neighboring plots and improve the regional carbon estimation. We found that the forests in Sichuan Province reserved a total of 624.2 Tg C in biomass and featured a large spatial heterogeneity, with high values in natural forests and low values in plantations. We found that the solo use of PBFI derived a slightly higher (46.63 Mg C/ha) estimation on average compared with the integrated method (43.6 Mg C/ha). However, when considering the spatial distribution, the PBFI generated an overestimation of young forests located between 3000and 4000 m in elevation, and an underestimation in mature forests. The spatially explicit biomass carbon estimation could be helpful in guiding regional forest management and biodiversity conservation.

Forest biomass carbon storage from multiple inventories over the past 30 years in Gansu Province, China: implications from the age structure of major forest types

We used the forest inventory data of Gansu Province, China to quantify carbon storage and carbon density changes by regional forest cover and by typical forest types in 1979–2006. Total forest area increased from 1.77 × 106 ha in 1979 to 2.32 × 106 ha in 2006, and the forest carbon storage, estimated by the continuous biomass expansion factor method, increased from 83.14 to 100.66 Tg, equivalent to a carbon accumulation rate of 0.0071 Tg per year during the period. Mean carbon densities were 44.83–48.50 t ha−1 and the values decreased slightly over the time period. Natural forests generated greater carbon storage and density than did plantations. By regression analysis, forest stand age was an important parameter in carbon density studies. We developed various regression equations between carbon density and stand age for major types of natural forests and plantations in the region. Our results can be used for proper selection of re-forestation species and efficient management of young and middle-aged forests, offering great potential for future carbon sequestration, especially in arid and semi-arid regions.