Temporal dynamics and spatial variations of forest vegetation carbon stock in Liaoning Province,China

There are many uncertainties in the estimation of forest car- bon sequestration in China, especially in Liaoning Province where vari- ous forest inventory data have not been fully utilized. By using forest inventory data, we estimated forest vegetation carbon stock of Liaoning Province between 1993 and 2005. Results showed that forest biomass carbon stock increased from 68.91 Tg C in 1993 to 97.51 Tg C in 2005, whereas mean carbon density increased from 18.48 Mg·ha -1 C to 22.33 Mg·ha -1 C. The carbon stora...     

Analysis of spatio-temporal changes in forest biomass in China

Forests play a central role in the global carbon cycle.China's forests have a high carbon sequestration potential owing to their wide distribution,young age and relatively low carbon density.Forest biomass is an essential variable for assessing carbon sequestration capacity,thus determining the spatio-temporal changes of forest biomass is critical to the national carbon budget and to contribute to sustainable forest management.Based on Chinese for-est inventory data (1999-2013),this study explored spatial patterns of forest biomass at a grid resolution of 1 km by applying a downscaling method and further analyzed spatio-temporal changes of biomass at different spatial scales.The main findings are:(1) the regression relationship between forest biomass and the associated influencing factors at a provincial scale can be applied to estimate biomass at a pixel scale by employing a downscaling method;(2) for-est biomass had a distinct spatial pattern with the greatest biomass occurring in the major mountain ranges;(3) forest biomass changes had a notable spatial distribution pattern;increase (i.e.,carbon sinks) occurred in east and southeast China,decreases (i.e.,carbon sources) were observed in the northeast to southwest,with the largest biomass losses in the Hengduan Mountains,Southern Hainan and Northern Da Hinggan Mountains;and,(4) forest vegetation functioned as a carbon sink during 1999-2013 with a net increase in biomass of 3.71 Pg.     

山西省森林植被碳储量及其动态变化研究

以山西省1995年、2000年和2005年的3期森林资源清查数据为基础,采用生物量换算因子法,研究了山西省森林植被碳储量及其动态变化。结果表明:10年间山西森林的碳储量总体呈上升的趋势。全省森林的总碳储量由1995年的3514.22万Mg增加到2005年的4505.61万Mg。在14个(类)森林优势树种中,栎类、油松和杨树这三者的碳储量占主导地位,合计占山西省森林总碳储量的60%以上。在全部森林中,幼、中龄林及近熟林的碳储量合计约占总量的90%。2005年,人工林碳储量占森林总碳储量的百分比提高了5.28%,全省森林平均碳密度为23.8933~26.3717Mg/hm2。     

Estimating net primary productivity of Chinese pine forests based on forest inventory data

Forest inventory data (FID) include forest resources informationat large spatial scale and long temporal scale. They are importantdata sources for estimating forest net primary productivity(NPP) and carbon budget at landscape and regional scales. Inthis study, more than 100 datasets of biomass, volume, NPP andstand age for Chinese pine forests (Pinus tabulaeformis) fromthe literature were synthesized to develop regression equationsbetween biomass and volume, and between NPP and biomass as wellas stand age. Using these regression equations and the fourthFID surveyed by the Forestry Ministry China from 1989 to 1993,NPP values of Chinese pine forests were estimated. The meanNPP of Chinese pine forests was 4.35 Mg ha^–1 yr^–1.NPP varied widely among provinces, ranging from 1.5 (Neimenggu)to 13.73 Mg ha^–1 yr^–1 (Guizhou). Total NPP of Chinesepine was 10.87 Tg yr^–1 (1 Tg = 10¹² g). NPP values ofChinese pine forests were not distributed evenly across differentprovinces in China. This study may be useful not only for estimatingforest carbon of other forest types but also for evaluatingterrestrial carbon balance at regional and global levels.     

Changes in forest cover and carbon stocks of the coastal scarp forests of the Wild Coast,South Africa

Land-use intensification and declines in vegetative cover are considered pervasive threats to forests and biodiversity globally. The small extent and high biodiversity of indigenous forests in South Africa make them particularly important. Yet, relatively little is known about their rates of use and change. From analysis of past aerial photos we quantified rates of forest cover change in the Matiwane forests of the Wild Coast, South Africa, between 1942 and 2007, as well as quantified above and belowground (to 0.5?m depth) carbon stocks based on a composite allometric equation derived for the area. Rates of forest conversion were spatially variable, with some areas showing no change and others more noticeable changes. Overall, the net reduction was 5.2% (0.08% p.a.) over the 65-year period. However, the rate of reduction has accelerated with time. Some of the reduction was balanced by natural reforestation into formerly cleared areas, but basal area, biomass and carbon stocks are still low in the reforested areas. The total carbon stock was highest in intact forests (311.7 ± 23.7 Mg C ha^?1), followed by degraded forests (73.5 ± 12.3 Mg C ha^?1) and least in regrowth forests (51.2 ± 6.2 Mg C ha^?1). The greatest contribution to total carbon stocks was soil carbon, contributing 54% in intact forests, and 78% and 68% in degraded and regrowth forests, respectively. The Matiwane forests store 4.78 Tg C, with 4.7 Tg C in intact forests, 0.06 Tg C in degraded forests and 0.02 Tg C in regrowth forests. The decrease in carbon stocks within the forests as a result of the conversion of the forest area to agricultural fields was 0.19 Tg C and approximately 0.0003 Tg C was released through harvesting of firewood and building timber.     

A review of the challenges and opportunities in estimating above ground forest biomass using tree-level models

Accurate biomass measurements and analyses are critical components in quantifying carbon stocks and sequestration rates, assessing potential impacts due to climate change, locating bio-energy processing plants, and mapping and planning fuel treatments. To this end, biomass equations will remain a key component of future carbon measurements and estimation. As researchers in biomass and carbon estimation, we review the present scenario of aboveground biomass estimation, focusing particularly on estimation using tree-level models and identify some cautionary points that we believe will improve the accuracy of biomass and carbon estimates to meet societal needs. In addition, we discuss the critical challenges in developing or calibrating tree biomass models and opportunities for improved biomass. Some of the opportunities to improve biomass estimate include integration of taper and other attributes and combining different data sources. Biomass estimation is a complex process, when possible, we should make use of already available resources such as wood density and forest inventory databases. Combining different data-sets for model development and using independent data-sets for model verification will offer opportunities to improve biomass estimation. Focus should also be made on belowground biomass estimation to accurately estimate the full forest contribution to carbon sequestration. In addition, we suggest developing comprehensive biomass estimation methods that account for differences in site and stand density and improve forest biomass modeling and validation at a range of spatial scales.     

国有北岭山林场生态公益林碳储量和碳密度研究

研究以小班为基本研究单元,按起源分林龄对广东省肇庆市国有北岭山林场生态公益林碳储 量进行了研究。国有北岭山林场乔木林总碳储量为 278.0×106kg,其中生态公益林碳储量为 244.9×106kg。生态公益林中天然林在不同林龄间的林分间平均碳密度不存在显著差异,范围（25.24±1.02）~ （28.01±1.69）×103 kg/hm2;而人工林则存在显著的差异,以 20~40 a 林龄的林分最大,为（34.22±2.77） ×103 kg/hm2,其次为大于 40 a 林龄的林分,为（23.34±0.72×103kg/hm2。在 20~40 a 林龄的生态公益林中,人工林平均碳密度显著大于天然林,但在大于 40 a 林龄的林分中,则显著小于天然林。     

西藏自治区森林碳密度及分布规律研究

利用森林资源连续清查实测样地及样木数据,结合相对树高曲线,构建生物量-蓄积量模型,解决了模型与各类森林资源调查数据的衔接问题,可应用于西藏自治区森林资源连续清查的目测与遥感样地生物量估算及森林资源规划设计调查小班生物量估算等。根据计算的森林资源连续清查各样地生物量密度,结合树种面积数据及含碳率,估算全区森林碳密度,并初步探讨了森林碳库地带性分布规律。     

河南省森林碳储量及动态变化研究

利用河南省1949—2003年间8次森林资源清查资料,建立不同优势树种生物量与蓄积量之间的回归方程,对河南省54a来森林的碳储量进行了推算。结果表明:河南省54a间森林的总碳储量虽然存在一定的波动现象,但总体呈上升的趋势。全省森林的总碳储量由1949年的2 863.91万t C增加到2003年的4 673.43万t C,共增加1 809.52万t C,年均增加33.51万t C。阔叶林占全省各时期森林总碳储量的80%以上,栎类和杨树两个树种占主导地位。河南森林幼、中龄林占的比重较大。全省森林平均碳密度为22.86~23.64t C/hm2,远低于全国、世界的平均水平。     

Estimating and mapping forest biomass in northeast China using joint forest resources inventory and remote sensing data

Being able to accurately estimate and map forest biomass at large scales is important for a better understanding of the terrestrial carbon cycle and for improving the effectiveness of forest management. In this study, forest plot sample data, forest resources inventory(FRI) data, and SPOT Vegetation(SPOT-VGT) normalized difference vegetation index(NDVI) data were used to estimate total forest biomass and spatial distribution of forest biomass in northeast China(with 1 km resolution). Total forest biomass at both county and provincial scales was estimated using FRI data of 11 different forest types obtained by sampling 1156 forest plots, and newly-created volume to biomass conversion models. The biomass density at the county scale and SPOT-VGT NDVI data were used to estimate the spatial distribution of forest biomass. The results suggest that the total forest biomass was 2.4 Pg(1 Pg = 10~(15) g), with an average of 77.2 Mg ha~(-1), during the study period. Forests having greater biomass density were located in the middle mountain ranges in the study area. Human activities affected forest biomass at different elevations, slopes and aspects. The results suggest that the volume to biomass conversion models that could be developed using more plot samples and more detailed forest type classifications would be better suited for the study area and would provide more accurate biomass estimates. Use of both FRI and remote sensing data allowed the down-scaling of regional forest biomass statistics to forest cover pixels to produce a relatively fineresolution biomass map.     

Description of a new procedure to estimate the carbon stocks of all forest pools and impact assessment of methodological choices on the estimates

Forest ecosystems play a major role in atmospheric carbon sequestration and emission. Comparable organic carbon stock estimates at temporal and spatial scales for all forest pools are needed for scientific investigations and political purposes. Therefore, we developed a new carbon stock (CS) estimation procedure that combines forest inventory and soil and litter geodatabases at a regional scale (southern Belgium). This procedure can be implemented in other regions and countries on condition that available external carbon soil and litter data can be linked to forest inventory plots. The presented procedure includes a specific CS estimation method for each of the following forest pools and subpools (in brackets): living biomass (aboveground and belowground), deadwood (dead trees and snags, coarse woody debris and stumps), litter, and soil. The total CS of the forest was estimated at 86 Tg (185 Mg ha^?1). Soil up to 0.2 m depth, living biomass, litter, and deadwood CSs account, respectively, for 48, 47, 4, and 1 % of the total CS. The analysis of the CS variation within the pools across ecoregions and forest types revealed in particular that: (1) the living biomass CS of broadleaved forests exceeds that of coniferous forests, (2) the soil and litter CSs of coniferous forest exceed those of broadleaved forests, and (3) beech stands come at the top in carbon stocking capacity. Because our estimates differ sometimes significantly from the previous studies, we compared different methods and their impacts on the estimates. We demonstrated that estimates may vary highly, from ?16 to +12 %, depending on the selected methods. Methodological choices are thus essential especially for estimating CO₂ fluxes by the stock change approach. The sources of error and the accuracy of the estimates were discussed extensively.     

Carbon storage dynamics of subtropical forests estimated with multi-period forest inventories at a regional scale:the case of Jiangxi forests

Temperate and high-latitude forests are carbon sinks and play pivotal roles in offsetting greenhouse gas emissions of CO_2.However,uncertainty still exists for subtropical forests,especially in monsoon-prevalent eastern Asia.Earlier studies have depended on remote sensing,ecosystem modeling,carbon fluxes,or single period forest surveys to estimate carbon sequestration capacities,and the results vary significantly.This study was designed to utilize multi-period forest survey data to explore spatial-dynamics of biomass storage in subtropical forests of China.Jiangxi province,a region with over 60% subtropical forest cover,was selected as the case study site and is located in central east China.Based on forest inventory data 1984-2013,and the stock-difference and biomass expansion factor methods,the carbon storage and density,of arboreal forests,economic forests,bamboo forests,woodlands and shrubberies were estimated.The results show that carbon storage increased from 159.1 Tg C in 1988 to 276.1 TgC in 2013,making up 3.1-3.8% of carbon stored throughout China.Among the four types of forests,the amount of carbon stored was as follows:arboreal forest economic forest bamboo forest woodland and shrubbery.Arboreal forests accounted for 64.0-79.4% of the total.Forest carbon density increased from 21.2 Mg C ha~(-1) in 1984 to26.2 Mg C ha~(-1) in 2013,equal to 61.2-70.2% of the average carbon density of China's forests in the same period.Forest carbon storage in Jiangxi will reach 355.5 Tg C and 535.8 Tg C in 2020 and 2030,respectively,and forest carbon density is predicted to be 31.9 Mg C ha~(~-1)and 46.4 Mg C ha~(-1),respectively.As one of the few studies using multi-period data tracking biomass dynamics in Jiangxi province,the findings of this study may be used as a reference for other research.Using Jiangxi as a case study underlies the fact that subtropical forests in China have great carbon sequestration potential and have fundamental significance to offset global environmental change effects.     

森林植被碳贮量估算及分析

文章基于岳阳市2009年森林资源统计数据,对全市森林植被类型的生物量、碳贮量和碳密度进行初步估算。结果表明:岳阳市森林植被碳贮量为9.238Tg,其中,平江县的森林植被C贮量最大,为3.606Tg,占总C贮量的39.03%。各森林类型的C贮量来看,松木林的C贮量最大,为2.754Tg,占总C贮量的29.81%。岳阳市森林植被平均C密度为16.02t.hm-2,各县市区森林植被的C密度为13.39~27.10t.hm-2,森林植被平均C密度最大是云溪区,为29.02t.hm-2,各森林类型中阔叶树的C密度最大,为27.24t.hm-2,是全市森林植被平均C密度的近2倍。       

岷江上游亚高山暗针叶林的生物量碳密度

利用森林资源连续清查的样地数据,基于生物量与蓄积量之间的关系模型,估测岷江上游亚高山暗针叶林地上部分生物量碳密度、碳密度年增长率及其随林龄、海拔和坡向变化的分布规律.结果表明:岷江上游暗针叶林的成熟林、过熟林生物量碳密度较高,中龄林、幼龄林生物量碳密度较低,成熟林、过熟林生物量碳密度高于全国平均水平,而中龄林和近熟林低于全国平均水平,幼龄林与全国平均水平相近;中龄林生物量碳密度年增长率最大,为1.3%,其次为过熟林,生物量碳密度年增长率为0.8%,幼龄林生物量碳密度年增长率最小,为0.7%;海拔3600～3800m处生物量碳密度最大,明显高于其他海拔区段;海拔3000～3400m处生物量碳密度年增长率最高,为1.03%;半阴坡和半阳坡的生物量碳密度高且年增长率最大,其次是阴坡,阳坡生物量碳密度低,年增长率最小;过去20多年,岷江上游暗针叶林生物量碳密度呈现逐年增加的趋势,1997-2002年,生物量碳密度年平均增长率为1.15%,高于其他调查期间碳密度年增长率.     

Effects of harvest management practices on forest biomass and soil carbon in eucalypt forests in New South Wales,Australia: Simulations with the forest succession model LINKAGES

Understanding long-term changes in forest ecosystem carbon stocks under forest management practices such as timber harvesting is important for assessing the contribution of forests to the global carbon cycle. Harvesting effects are complicated by the amount, type, and condition of residue left on-site, the decomposition rate of this residue, the incorporation of residue into soil organic matter and the rate of new detritus input to the forest floor from regrowing vegetation. In an attempt to address these complexities, the forest succession model LINKAGES was used to assess the production of aboveground biomass, detritus, and soil carbon stocks in native Eucalyptus forests as influenced by five harvest management practices in New South Wales, Australia. The original decomposition sub-routines of LINKAGES were modified by adding components of the Rothamsted (RothC) soil organic matter turnover model. Simulation results using the new model were compared to data from long-term forest inventory plots. Good agreement was observed between simulated and measured above-ground biomass, but mixed results were obtained for basal area. Harvesting operations examined included removing trees for quota sawlogs (QSL, DBH >80 cm), integrated sawlogs (ISL, DBH >20 cm) and whole-tree harvesting in integrated sawlogs (WTH). We also examined the impact of different cutting cycles (20, 50 or 80 years) and intensities (removing 20, 50 or 80 m³). Generally medium and high intensities of shorter cutting cycles in sawlog harvesting systems produced considerably higher soil carbon values compared to no harvesting. On average, soil carbon was 2–9% lower in whole-tree harvest simulations whereas in sawlog harvest simulations soil carbon was 5–17% higher than in no harvesting.     

Ecosystem carbon storage and partitioning in a tropical seasonal forest in Southwestern China

Tropical forests play an important role in the global carbon cycle. Despite an increasing number of studies have addressed carbon storage in tropical forests, the regional variation in such storage remains poorly understood. Uncertainty about how much carbon is stored in tropical forests is an important limitation for regional-scale estimates of carbon fluxes and improving these estimates requires extensive field studies of both above- and belowground stocks. In order to assess the carbon pools of a tropical seasonal forest in Asia, total ecosystem carbon storage was investigated in Xishuangbanna, SW China. Averaged across three 1 ha plots, the total carbon stock of the forest ecosystem was 303 t C ha⁻¹. Living tree carbon stocks (both above- and belowground) ranged from 163 to 258 t C ha⁻¹. The aboveground biomass C pool is comparable to the Dipterocarp forests in Sumatra but lower than those in Malaysia. The variation of C storage in the tree layer among different plots was mainly due to different densities of large trees (DBH > 70 cm). The contributions of the shrub layer, herb layer, woody lianas, and fine litter each accounted for 1–2 t C ha⁻¹ to the total carbon stock. The mineral soil C pools (top 100 cm) ranged from 84 to 102 t C ha⁻¹ and the C in woody debris from 5.6 to 12.5 t C ha⁻¹, representing the second and third largest C component in this ecosystem. Our results reveal that a high percentage (70%) of C is stored in biomass and less in soil in this tropical seasonal forest. This study provides an accurate estimate of the carbon pool and the partitioning of C among major components in tropical seasonal rain forest of northern tropical Asia. Results from this study will enhance our ability to evaluate the role of these forests in regional C cycles and have great implications for conservation planning.     

Spatially explicit assessment of carbon stocks of a managed forest area in eastern Germany

The Kyoto-protocol permits the accounting of changes in forest carbon stocks due to forestry. Therefore, forest owners are interested in a reproducible quantification of carbon stocks at the level of forest management units and the impact of management to these stocks or their changes. We calculated the carbon stocks in tree biomass and the organic layer including their uncertainties for several forest management units (Tharandt forest, Eastern Germany, 5,500 ha) spatially explicit at the scale of individual stands by using standard forest data sources. Additionally, soil carbon stocks along a catena were quantified. Finally, carbon stocks of spruce and beech dominated stands were compared and effects of thinning intensity and site conditions were assessed. We combined forest inventory and data of site conditions by using the spatial unions of the shapes (i.e., polygons) in the stand map and the site map. Area weighted means of carbon (C) stocks reached 10.0 kg/m2 in tree biomass, 3.0 kg/m2 in the organic layer and 7.3 kg/m2 in mineral soil. Spatially explicit error propagation yielded a precision of the relative error of carbon stocks at the total studied area of 1% for tree biomass, 45% for the organic layer, and 20% for mineral soil. Mature beech dominated stands at the Tharandt forest had higher tree biomass carbon stocks (13.4 kg/m2) and lower organic layer carbon stocks (1.8 kg/m2) compared to stands dominated by spruce (11.6, 3.0 kg/m2). The difference of tree biomass stocks was mainly due to differences in thinning intensity. The additional effect of site conditions on tree carbon stocks was very small. We conclude that the spatially explicit combination of stand scale inventory data with data on site conditions is suited to quantify carbon stocks in tree biomass and organic layer at operational scale.     

Distribution patterns of tree,understorey, and detritus biomass in coniferous and broad-leaved forests of Western Himalaya,India

Forest biomass pools are the major reservoirs of atmospheric carbon in both coniferous and broad-leaved forest ecosystems and thus play an important role in regulating the regional and global carbon cycle. In this study, we measured the biomass of trees, understorey, and detritus in temperate (coniferous and broad-leaved) forests of Kashmir Himalaya. Total ecosystem dry biomass averaged 234.2 t/ha (ranging from 99.5 to 305.2 t/ha) across all the forest stands, of which 223 t/ha (91.9–283.2 t/ha) were stored in above- and below-ground biomass of trees, 1.3 t/ha (0.18–3.3 t/ha) in understorey vegetation (shrubs and herbaceous), and 9.9 t/ha (4.8–20.9 t/ha) in detritus (including standing and fallen dead trees, and forest floor litter). Among all the forests, the highest tree, understorey, and detritus biomass were observed in mid-altitude Abies pindrow and Pinus wallichiana coniferous forests, whereas the lowest were observed in high-altitude Betula utilis broad-leaved forests. Basal area has showed significant positive relationship with biomass (R² = 0.84–0.97, P < 0.001) and density (R² = 0.49–0.87). The present study will improve our understanding of distribution of biomass (trees, understorey, and detritus) in coniferous and broad-leaved forests and can be used in forest management activities to enhance C sequestration.     

湖南主要森林类型碳汇功能及其经济价值评价

利用湖南省森林资源主要数据汇编(1999—2003年),依据不同森林类型生物量与蓄积量之间的回归方程,对湖南省几种主要森林类型的生物量和碳贮量进行了推算,分析了不同林龄结构的碳密度以及天然林与人工林的碳贮量,并对整个湖南省的森林经济价值进行估算。结果表明:湖南省主要森林类型的总碳贮量为94.935 Tgc,碳汇总经济价值为70 723.26万元,固定CO2的经济效益达259 554.36万元。阔叶树的碳汇能力最强,其次是杉木和马尾松;湖南省的天然林和人工林的碳贮量相差不大,不同龄组碳密度高低排序的基本规律是:过熟林>成熟林>近熟林>中龄林>幼龄林;而中龄林的碳贮量最多,过熟林碳贮量最少。     

Inventory-based estimates of forest biomass carbon stocks in China: A comparison of three methods

Several studies have reported different estimates for forest biomass carbon (C) stocks in China. The discrepancy among these estimates may be largely attributed to the methods used. In this study, we used three methods [mean biomass density method (MBM), mean ratio method (MRM), and continuous biomass expansion factor (BEF) method (abbreviated as CBM)] applied to forest inventory data to estimate China's forest biomass C stocks and their changes from 1984 to 2003. The three methods generated various estimates of the biomass C stocks: the lowest (4.0–5.9 Pg C) from CBM and the highest (5.7–7.7 Pg C) from MBM, with an intermediate estimate (4.2–6.2 Pg C) from MRM. Forest age class is a major factor responsible for these method-induced differences. MBM overestimates biomass for young-aged forests, but underestimates biomass for old-aged forests; while the reverse is true for MRM. Further, the three methods resulted in different estimates of biomass C stocks for different forest types. For temperate/subtropical mixed forests, MBM generated a 92% higher estimate than CBM and MRM generated a 14% lower than CBM. The degree of the overestimates is closely related with the proportion of young-aged forest within total area of each forest type.