甘肃省森林碳储量现状与固碳速率北大核心CSCD

针对森林碳平衡再评估的重要性和区域尺度森林生态系统碳库量化分配的不确定性,该研究依据全国森林资源连续清查结果中甘肃省各森林类型分布的面积与蓄积比重以及林龄和起源等要素,在甘肃省布设212个样地,经野外调查与采样、室内分析,并对典型样地信息按照面积权重进行尺度扩展,估算了甘肃省森林生态系统碳储量及其分布特征。结果表明:甘肃省森林生态系统总碳储量为612.43 TgC,其中植被生物量碳为179.04 TgC,土壤碳为433.39 TgC。天然林是甘肃省碳储量的主要贡献者,其值为501.42 TgC,是人工林的4.52倍。天然林和人工林的植被碳密度均表现为随林龄的增加而增加的趋势,同一龄组天然林植被碳密度高于人工林。天然林土壤碳密度从幼龄林到过熟林逐渐增加,但人工林土壤碳密度最大值主要为近熟林。全省森林植被碳密度均值为72.43 Mg C·hm–2,天然林和人工林分别为90.52和33.79 Mg C·hm–2。基于森林清查资料和标准样地实测数据,估算出全省天然林和人工林在1996年的植被碳储量为132.47和12.81 TgC,2011年分别为152.41和26.63 TgC,平均固碳速率分别为1.33和0.92 TgC·a–1。甘肃省幼、中龄林面积比重较大,占全省的62.28%,根据碳密度随林龄的动态变化特征,预测这些低龄林将发挥巨大的碳汇潜力。     

浙江省森林生态系统碳储量及其分布特征

利用2011-2012年野外标准地实测资料, 结合第八次全国森林资源清查资料, 研究了浙江省森林生态系统碳储量及其分布特征。结果表明: 浙江省森林生态系统碳储量为602.73 Tg, 其中乔木层、灌草层、凋落物层和土壤层碳储量分别为122.88 Tg、16.73 Tg、11.36 Tg和451.76 Tg, 分别占生态系统碳储量的20.39%、2.78%、1.88%和74.95%; 在各森林类型中, 阔叶混交林碳储量为138.03 Tg, 所占比例最大(22.90%); 在森林各龄组中, 幼、中龄林约占浙江省森林生态系统碳储量的70.66%, 是碳储量的主要贡献者。浙江省森林生态系统平均碳密度为120.80 t·hm^-2, 乔木层、灌草层、凋落物层和土壤层碳密度分别为24.65 t·hm^-2、3.36 t·hm^-2、2.28 t·hm^-2和90.51 t·hm^-2。浙江省森林生态系统土壤层碳储量和生态系统碳储量呈极显著相关关系, 说明土壤层碳储量对浙江省森林生态系统碳储量贡献较大。浙江省天然林乔木层碳密度整体表现为过熟林>成熟林>近熟林>中龄林>幼龄林, 而人工林乔木层碳密度表现为过熟林>近熟林>成熟林>中龄林>幼龄林。浙江省幼、中龄林林分面积占比重较大, 占全省森林面积的76.76%, 若对现有森林进行更好的经营和管理, 可以增加浙江省森林的碳固存能力。     

宁夏回族自治区森林生态系统固碳现状

根据宁夏回族自治区森林资源清查资料以及野外调查和室内分析的结果,研究了宁夏地区森林生态系统固碳现状,估算了该区森林生态系统的碳密度、碳储量,并分析了其空间分布特征.结果表明: 宁夏森林各植被层生物量大小顺序为: 乔木层(46.64 Mg·hm^-2)>凋落物层(7.34 Mg·hm^-2)>细根层(6.67 Mg·hm^-2)>灌草层(0.73 Mg·hm^-2).云杉类(115.43 Mg·hm^-2)和油松(94.55 Mg·hm^-2)的单位面积植被生物量高于其他树种.不同林龄乔木层碳密度中,过熟林最高,但由于幼龄林面积所占比例最大,其乔木层碳储量(1.90 Tg C)最大.宁夏地区森林生态系统平均碳密度为265.74 Mg C·hm^-2,碳储量为43.54 Tg C,其中,植被层平均碳密度为27.24 Mg C·hm^-2、碳储量为4.46 Tg C,土壤层碳储量是植被层的8.76倍.宁夏地区的森林碳储量整体呈南高北低分布,总量较低.这与其森林面积小和林龄结构低龄化有很大关系.随着林龄结构的改善和林业生态工程的进一步实施,宁夏森林生态系统将发挥巨大的固碳潜力.     

内蒙古森林生态系统碳储量及其空间分布

内蒙古森林面积居全国第一位, 林木蓄积量居第五位, 准确地估算该区域森林碳储量对于评估中国森林碳储量以及制定森林资源管理措施均具有重要意义。该研究基于内蒙古森林资源野外样方调查和室内分析, 评估了内蒙古森林生态系统的固碳现状, 估算了内蒙古森林生态系统不同林型和不同碳库(乔木、灌木、草本、凋落物和土壤碳库)的碳密度大小, 揭示了其空间分布特征。在此基础上估算了内蒙古森林碳储量大小及空间格局。结果表明: 1)内蒙古森林植被层碳储量为787.8 Tg C, 乔木层、凋落物层、草本层和灌木层分别占植被层总碳储量的93.5%、3.0%、2.7%和0.8%。内蒙古森林植被层平均碳密度为40.4 t·hm^-2, 其中, 乔木层、凋落物层、草本层和灌木层的碳密度分别为35.6 t·hm^-2、2.9 t·hm^-2、1.2 t·hm^-2和0.6 t·hm^-2。2)内蒙古森林土壤层(0-100 cm)碳储量为2449.6 Tg C, 其中0-30 cm的土壤碳储量最高, 占总碳储量的79.8%。0-10 cm、10-20 cm和20-30 cm的土壤碳储量分别占0-30 cm土壤碳储量的38.8%、34.1%和27.1%。内蒙古森林土壤平均碳密度为144.4 t·hm^-2。黑桦(Betula davurica)林土壤碳密度最高, 云杉(Picea asperata)林最小。土壤碳密度随土壤深度的增加而降低。3)内蒙古森林生态系统碳储量为3237.4 Tg C, 植被层和土壤层碳储量分别占森林生态系统碳储量的24.3%和75.7%。落叶松(Larix gmelinii)林总碳储量最高, 其次为白桦(Betula platyphylla)林、夏栎(Quercus robur)林、黑桦林、榆树(Ulmus pumila)疏林和山杨(Populus davidiana)林。内蒙古森林生态系统平均碳密度为184.5 t·hm^-2。土壤碳密度与植被碳密度呈显著正相关关系。4)内蒙古森林生态系统碳储量和碳密度的空间分布总体上为东部地区高、西部地区低的趋势。在降水量充沛的东部地区和降水偏少的中西部地区, 有针对性地开展森林保护区建设和人工造林, 可显著提升区域的碳汇能力。     

安徽省森林碳储量现状及固碳潜力

为阐明安徽省不同林龄的森林生态系统的碳储量现状, 以及现有自然环境条件下顶极森林生态系统的固碳潜力, 采用野外样地调查和BIOME4模型方法对此进行研究。安徽省森林生态系统的现状总碳储量为714.5 Tg C, 其中植被碳402.1 Tg C、土壤碳312.4 Tg C。从幼龄林至过熟林的生长过程中, 森林生态系统的总碳密度和植被碳密度都呈现增长趋势。但土壤碳密度从幼龄林至近熟林阶段呈增加趋势, 近熟林以后出现减少趋势。安徽省幼龄林和中龄林占森林总面积的75%, 若幼、中龄林发展到近熟林阶段, 将增加125.4 Tg C。BIOME4模拟显示: 当森林发展到气候顶极森林时, 安徽省森林生态系统将增加245.7 Tg C, 即总固碳潜力包括植被固碳153.7 Tg C, 土壤固碳92.0 Tg C。     

天山森林生态系统碳储量格局及其影响因素

科学地估算亚洲中部天山雪岭杉(Picea schrenkiana)生态系统碳密度与碳储量是评价新疆森林碳汇潜力、评估森林在减缓大气CO₂浓度上升、应对气候变化等方面功能的关键, 对干旱区森林生态系统的保育和可持续发展具有重要意义。该文基于在天山雪岭杉林区布设的70个野外样地调查数据, 结合新疆森林资源连续清查数据, 全面估算了天山雪岭杉生态系统的碳密度和碳储量, 分析了其分布格局与影响因素。结果表明: 天山雪岭杉不同龄组叶、枝、干和根的含碳率变化不显著, 其乔木层平均含碳率为49%, 而林下植被(凋落物、草本等)平均含碳率仅为42%。雪岭杉森林生态系统单位面积生物量为187.98 Mg·hm^-2, 其中乔木层生物量占生态系统总生物量的98.93%。乔木层各组分生物量大小为: 干>根>枝>叶, 而各龄组生物量排序为: 成熟林>中龄林>近熟林>过熟林>幼龄林。雪岭杉生态系统碳密度为544.57 Mg·hm^-2, 碳储量为290.84 Tg C, 其中植被碳密度为92.57 Mg·hm^-2, 植被碳储量为53.14 Tg C, 土壤碳密度为452.00 Mg·hm^-2, 土壤碳储量为237.70 Tg C。天山雪岭杉生态系统碳密度分异与不同林区林带垂直宽度变化具有很高的相关性, 其生态系统碳密度西高东低的分布格局和它所处的环境因子西优东劣的变异是相一致的, 即不同的环境因素组合是造成天山雪岭杉生态系统碳密度差异的主要原因。     

吉林省森林植被固碳现状与速率

通过对吉林省森林植被的普遍调查、典型调查以及植被样品含碳率测定, 结合吉林省2009年和2014年森林清查数据, 估算了区域森林植被的碳储量、碳密度及固碳速率。研究结果表明: 林下植被的生物量在不同林分和同类林分中存在较大的差异, 整体不足乔木层生物量的3%, 灌木植物的生物量略高于草本植物和幼树。不同林分类型的乔木含碳率介于45.80%-52.97%之间, 整体表现为针叶林高于阔叶林; 灌木和草本植物分别为39.79%-47.25%和40%左右。吉林省森林植被碳转换系数以0.47或0.48更为准确, 若以0.50或0.45作为植被的碳转换系数计算碳储量, 会造成±5.26%的偏差。吉林省森林植被不仅维持着较高的碳库水平, 而且极具碳汇能力; 2009年和2014年碳储量分别为471.29 Tg C和505.76 Tg C, 累计碳增量34.47 Tg C, 平均每年碳增量6.89 Tg C·a^-1; 碳密度由64.58 t·hm^-2增至66.68 t·hm^-2, 平均增加2.10 t·hm^-2, 固碳速率0.92 t·hm^-2·a^-1。森林植被碳储量的增长主体是蒙古栎(Quercus mongolica)林和阔叶混交林, 合计碳增量占总体的90.34%。受植被发育引起的生物量增长、林分龄组晋级以及森林经营所引起的面积变化影响, 各龄组植被碳增量为幼龄林>过熟林>近熟林>中龄林, 成熟林表现为负增长; 固碳速率为过熟林>幼龄林>近熟林>中龄林>成熟林。森林植被碳储量和碳密度的市/区分布整体表现为自东向西明显的降低变化; 碳增量以东北和中东部地区较高, 西部地区较低; 固碳速率整体以南部的通化地区和白山地区相对较高, 中部的吉林地区和东部的延边地区次之, 西部的白城地区、松原地区等地呈负增长。     

浑善达克沙地榆树疏林和小叶杨人工林碳密度特征及其与林龄的关系

榆树(Ulmus pumila)疏林是浑善达克沙地的地带性隐域植被, 小叶杨(Populus simonii)是该区域主要的防风固沙造林树种。该文通过测定两种森林生态系统乔木层(叶、枝、干、根)、草本层(地上植被和地下根系)和土壤层(0-100 cm)的碳含量, 比较了两种森林生态系统的碳密度及其分配特征, 并运用空间代替时间的方法, 阐明了乔木层、土壤层和总碳密度随林龄增加的变化特征, 估算了两种森林生态系统的固碳速率。结果表明, 榆树疏林乔木层和土壤层平均碳含量都低于小叶杨人工林, 榆树疏林生态系统总碳密度是小叶杨人工林的1/2。两种森林生态系统的总碳密度中, 乔木层碳密度和土壤层碳密度总占比98%以上; 土壤层与植被层碳密度的比值随林龄的增加而降低, 过熟林时该比值分别为1.66 (榆树疏林)和1.87 (小叶杨人工林); 榆树疏林和小叶杨人工林的乔木层、土壤层和生态系统的总碳密度随林龄的增加而增加, 其中乔木层碳密度及榆树疏林总碳密度与林龄均呈现出显著的线性正相关关系。小叶杨人工林乔木层的固碳速率约为榆树疏林的5倍, 榆树疏林生态系统和小叶杨人工林生态系统的总固碳速率分别为0.81 Mg C·hm^-2·a^-1和5.35 Mg C·hm^-2·a^-1。这一研究结果有利于估算沙地森林生态系统的碳储量, 为区域生态环境恢复和增加碳汇的政策制定提供依据。     

陕西省森林生态系统碳储量分布格局分析

为明晰陕西省森林生态系统碳储量分布格局, 基于2009年森林资源清查资料和2011年调查所得样地实测数据, 对陕西省森林生态系统碳储量、碳密度及其空间分布特征进行了研究分析。结果表明: 陕西省森林生态系统总碳储量为790.75 Tg, 土壤层、植被层和枯落物层碳储量分别占总碳储量的72.14%、26.52%和1.34%; 其中, 栎类碳储量在各森林类型中所占比重最大(44.17%), 中、幼龄林是陕西省森林生态系统碳储量的主要贡献者, 约占总碳储量的49%。陕西省森林生态系统平均碳密度为123.70 t·hm^-2, 土壤层最大, 枯落物层最小, 植被层居中; 碳密度均随龄级增加而升高, 同一龄级表现为天然林高于人工林生态系统。此外, 陕西省森林生态系统碳储量、碳密度分布格局不尽一致, 反映了森林覆盖面积及森林质量对碳储量的影响。未来应加强林地抚育管理水平, 增加造林再造林面积以增加碳储存, 应对全球气候变化。     

甘肃省5种典型人工林生态系统固碳现状与潜力

基于野外调查与室内实测数据,结合第八次全国森林资源清查资料,分析了甘肃省5种典型人工林生态系统(刺槐、杨树、油松/华山松、落叶松及云杉林)森林生态系统碳密度、碳储量,并估算了乔木层固碳潜力.结果表明: 5种典型人工林生态系统平均碳密度和总碳储量分别为139.65 t·hm^-2和85.78 Tg,不同人工林类型之间差异较大.不同龄组间碳密度表现为近熟林(250.70 t·hm^-2)最大,其次是成熟林(175.97 t·hm^-2)和中龄林(156.92 t·hm^-2),幼龄林(117.56 t·hm^-2)最低.碳储量表现为幼龄林(45.47 Tg)>中龄林(19.54 Tg)>成熟林(11.84 Tg)>近熟林(8.93 Tg),幼中龄林碳储量占总碳储量的75.9%.5种典型人工林乔木层现实固碳潜力合计为7.27 Tg,刺槐林(2.49 Tg)和杨树林(2.10 Tg)最大;各龄组中,幼龄林现实固碳潜力最大(3.78 Tg),其次是中龄林(2.04 Tg),近熟林最小(0.45 Tg).5种典型人工林乔木层最大固碳潜力达27.55 Tg,表现为刺槐林(9.42 Tg)>落叶松林(6.22 Tg)≈云杉林(6.36 Tg)>杨树林(3.18 Tg)>油松/华山松林(2.37 Tg);其中,幼、中龄林最大固碳潜力分别为18.48和6.89 Tg,占总最大固碳潜力的92%.     

Current stocks and rate of sequestration of forest carbon in Gansu Province,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.     

Carbon density characteristics of sparse Ulmus pumila forest and Populus simonii plantation in Onqin Daga Sandy Land and their relationships with stand age

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.     

Carbon storage and its distribution of forest ecosystems in Zhejiang Province,China

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.     

Present status and rate of carbon sequestration of forest vegetation in Jilin Province,Northeast China

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.     

Carbon storage and potentials of the broad-leaved forest in alpine region of the Qinghai- Xizang Plateau,China

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.     

青藏高原高寒区阔叶林植被固碳现状、速率和潜力

为明晰青藏高原高寒区阔叶林植被碳储量现状及其动态变化特征, 利用森林资源清查数据和标准样地实测数据, 估算了青藏高原高寒区(青海和西藏两省区)阔叶林植被的碳储量、固碳速率和固碳潜力。结果表明: 2011年青藏高原高寒区阔叶林植被碳储量为310.70 Tg, 碳密度为89.04 Mg·hm^-2。六类阔叶林型(栎(Quercus)林、桦木(Betula)林、杨树(Populus)林、其他硬阔林、其他软阔林和阔叶混交林)中, 阔叶混交林的碳储量最大, 杨树林碳储量最小; 其他硬阔林碳密度最大, 其他软阔林碳密度最小。空间分配上碳储量和碳密度表现为: 乔木层>灌木层>凋落物层>草本层>枯死木层。不同龄级碳储量和碳密度总体表现为随林龄增加逐渐增大的趋势。阔叶林碳储量从2001年的304.26 Tg增加到2011年的310.70 Tg, 平均年固碳量为0.64 Tg·a^-1, 固碳速率为0.19 Mg·hm^-2·a^-1。不同林型固碳速率表现为其他软阔林最大, 其他硬阔林最小; 不同龄级表现为成熟林最大, 幼龄林最小。阔叶林乔木层固碳潜力为19.09 Mg·hm^-2, 且不同林型固碳潜力表现为栎林最大, 桦树林最小。三次调查期间阔叶林碳储量逐渐增加, 主要原因是近年来森林保护工程的开展使阔叶林生长健康良好。     

Carbon storage of the forests and its spatial pattern in Nei Mongol,China

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.