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。     

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.     

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。     

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,spatial distribution and the influence factors in Tianshan forests

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.     

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.     

Carbon density and its spatial distribution in the Potentilla fruticosa dominated alpine shrub in Qinghai,China

Aims Shrub recovery is recognized as an important cause of the increase of carbon stocks in China, and yet there are great uncertainties in the carbon sink capacities of shrubs. Our objectives were to estimate carbon density and its spatial distribution in alpine shrubs.
Methods Eight sites in Potentilla fruticosa dominated shrublands across Qinghai, China were investigated. Plant biomass and carbon content in leaves, branches and stems, and roots were measured to analyze the biomass allocation and carbon density.
Important findings Mean carbon densities in biological carbon, litter, soil and whole ecosystem of P. fruticosa shrublands were 5088.54, 542.1, 35903.76 and 41534.4 kg·hm^-2, respectively. Carbon density in the shrub layer was more than 68% of the biological carbon density of the whole ecosystem and was mainly distributed in roots (49.5%-56.1%). Carbon density of the herbaceous layer was 22.5% of the biological carbon density of the whole ecosystem and was also mainly distributed in roots (59.6%-75.1%). The biological carbon density of P. fruticosa shrublands (5.08 t·hm^-2) was lower than the average carbon density of shrub communities in China (10. 88 t·hm^-2). Soil carbon density contributed the largest proportion (85.8%) of total carbon density in P. fruticosa shrublands.     

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.     

Storage of carbon,nitrogen and phosphorus in temperate shrubland ecosystems across Northern China

Aims Studying storage of carbon (C), nitrogen (N) and phosphorus (P) in ecosystems is of significance in understanding carbon and nutrient cycling. Previous researches in ecosystem C, N and P storage have biased towards forests and grasslands. Shrubland ecosystems encompass a wide gradient in precipitation and soil conditions, providing a unique opportunity to explore the patterns of ecosystem C, N and P storage in relation to climate and soil properties.
Methods We estimated densities and storage of organic C, N and P of shrubland ecosystems in Northern China based on data from 433 shrubland sites.
Important findings The main results are summarized as follows: the average organic C, N and P densities in temperate shrubland ecosystems across Northern China were 69.8 Mg·hm^-2, 7.3 Mg·hm^-2 and 4.2 Mg·hm^-2, respectively. The average plant C, N and P densities were 5.1 Mg·hm^-2, 11.5 × 10^-2 Mg·hm^-2 and 8.6 × 10^-3 Mg·hm^-2, respectively, and were significantly correlated with precipitation and soil nutrient concentrations. The average litter C, N and P densities were 1.4 Mg·hm^-2, 3.8 ×10^-2 Mg·hm^-2, 2.5 ×10^-3 Mg·hm^-2 and were significantly correlated with temperature and precipitation. The average soil organic C, N and P densities in the top 1 m were 64.0 Mg·hm^-2, 7.1 Mg·hm^-2 and 4.2 Mg·hm^-2, respectively and the former two were significantly correlated with temperature and precipitation. The total organic C, N and P storage of shrublands in Northern China were 1.7 Pg, 164.9 Tg and 124.8 Tg, respectively. The plant C, N and P storage were 128.4 Tg, 3.1 Tg and 0.2 Tg, respectively. The litter C, N and P storage were 8.4 Tg, 0.45 Tg, 0.027 Tg, respectively. Soil is the largest C, N and P pool in the studied area. The soil organic C, N and P storage in the top 1 meter were 1.6 Pg, 161.3 Tg and 124.6 Tg, respectively.     

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。     

Distribution of biomass in relation to environments in shrublands of temperate China

Aims Shrubland is one of the most widely distributed vegetation types in northern China. Previous studies on pattern and dynamics of plant biomass have been focused on forest and grassland ecosystems, while relevant knowledge on shrubland ecosystems is lacking. It is important to include shrublands in northern China to improve the accuracy in estimating the terrestrial ecosystem biomass in China.
Methods Based on investigations and samplings from 433 shrubland sites, we explored the distribution and allocation patterns of biomass in relation to climatic and soil nutrient factors of shrublands of temperate China.
Important findings The average shrubland biomass density in northern China is 12.5 t·hm^-2. It decreases significantly from temperate deciduous shrubland in northeast to desert shrubland in northwest. The average biomass density of temperate deciduous shrubland, alpine shrubland, and desert shrubland is 14.4, 28.8, and 5.0 t·hm^-2, respectively. Within temperate deciduous shrublands, plant biomass is lower in North China than in Northeast China. The average aboveground and belowground biomass density of shrub layer is 4.5 and 5.4 t·hm^-2, respectively; while that of grass layer is 0.8 and 1.8 t·hm^-2, respectively. Environmental factors affect biomass allocation across different plant organs. The belowground-aboveground biomass ratio of shrub exhibits no significant changes with environmental variables. The leaf-stem ratio increases with annual precipitation, and leaf biomass is low in arid region.     

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。     

甘肃省森林碳储量现状与固碳速率

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 Tg C, 其中植被生物量碳为179.04 Tg C, 土壤碳为433.39 Tg C。天然林是甘肃省碳储量的主要贡献者, 其值为501.42 Tg C, 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 Tg C, 2011年分别为152.41和26.63 Tg C, 平均固碳速率分别为1.33和0.92 Tg C·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。     

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 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.     

Soil carbon storage and its determinants in the forests of Shaanxi Province,China

Aims The bank of soil carbon of forests plays an important role in the global carbon cycle. Our aim is to understand the characteristics of soil carbon storage and its determinants in the forests in Shaanxi Province.Methods The data of forest inventory in 2009 and resampling in 2011 were used to analyze the characteristics of soil carbon storage and its determinants in the forest soil in Shaanxi Province.Important findings The soil carbon storage in the forests in Shaanxi Province was 579.68 Tg. Soil carbon storage of Softwood and Hardwood forests were the highest among all forest types, accounting for 36.35% of the whole province forest soil carbon storage. The forest soil carbon storage was 4.15 times greater in the natural forest (467.17 Tg) than that in the plantations. The young and middle-aged forests were the main contributors to the total carbon storage across all age groups, accounting for about 57.30% of the total forest soil carbon storage. The average soil carbon density of forests in Shaanxi Province was 90.68 t∙hm^-2, in which the soil carbon density of Betula forests was the highest (141.74 t∙hm^-2). Soil carbon density of different forest types were gradually decreased with soil depth. In addition, it was highest in middle-aged forest. Soil carbon density was higher in the natural forest ecosystems than that in the plantations within the each age group, indicating natural forest ecosystems have higher capacity of carbon sequestration. Differences in the spatial patterns between carbon storage and density indicated that carbon storage was related to forest coverage. The soil carbon density and storage of forests in Yulin were the lowest across the province. This suggests that, in order to enhance the regional carbon sequestration capacity in this region, we need to appropriately strengthen artificial afforestation activities and manage them scientifically and rationally. The soil carbon density of forests in Shaanxi Province decreased with the increase of longitude, latitude, and annual temperature, but increased with the increase of altitude and annual rainfall. This study provides data basis for provincial estimation of forest soil carbon bank in China.     

Carbon cycle of larch plantation based on CO2FIX model

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.     

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.     

Spatial pattern of soil organic carbon of the main forest soils and its influencing factors in Guangxi,China

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.     

Research on characteristics of biomass distribution in urban forests of Shanghai metropolis based on remote sensing and spatial analysis

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.