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。     

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。     

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。     

小兴安岭7种典型林型林分生物量碳密度与固碳能力

森林生物碳储量作为森林生态系统碳库的重要组成部分, 在全球碳循环中发挥着重要作用。以小兴安岭7种典型林型为研究对象, 通过外业样地调查与室内实验分析相结合的方法, 从林分尺度对林分生物量与碳密度进行计量, 分析了林分生物碳储量的空间分配格局, 并对林分年固碳能力与碳汇潜力进行了探讨。结果表明: 小兴安岭不同林型从幼龄林到成熟林的乔木层碳密度增长速率为: 蒙古栎(Quercus mongolica)林>兴安落叶松(Larix gmelinii)林>云冷杉(Picea-Abies)林>樟子松(Pinus sylvestris var. mongolica)林>山杨(Populus davidiana)林>红松(Pinus koraiensis)林>白桦(Betula platyphylla)林。7种典型林型不同龄组(幼龄林、中龄林、近熟林和成熟林)林分生物量碳密度分别为: 红松林31.4、74.7、118.4和130.2 t·hm^-2; 兴安落叶松林28.9、44.3、74.2和113.3 t·hm^-2; 樟子松林22.8、52.0、71.1和92.6 t·hm^-2; 云冷杉林23.1、44.1、77.6和130.3 t·hm^-2; 白桦林18.8、35.3、66.6和88.5 t·hm^-2; 蒙古栎林25.0、20.0、47.5和68.9 t·hm^-2; 山杨林19.8、28.7、43.7和76.6 t·hm^-2。红松林、兴安落叶松林、樟子松林和蒙古栎林在幼龄林时林分年固碳量较高, 其他林型在成熟林时林分年固碳量较高。7种典型林型不同龄组的林分生物量碳密度均随林龄增长而增加, 但不同林型的碳汇功能存在差异, 同一林型不同林龄的生物量碳密度增幅差异也较大。林分年固碳量在0.4-2.8 t·hm^-2之间, 碳汇能力较强、碳汇潜力较大。尤其是小兴安岭目前林分质量较差, 幼龄林和中龄林所占的比重较大, 具有较大的碳汇潜力。研究结果可为森林经营管理及碳汇功能评价提供参考。     

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。     

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。     

广西主要森林土壤有机碳空间分布及其影响因素

为阐明广西森林土壤有机碳密度分布格局及其主要影响因素, 基于森林资源清查资料和345个调查样地的土壤数据, 估算了广西主要森林土壤有机碳储量, 采用地统计学方法描绘了土壤有机碳密度的空间分布, 并利用主成分分析和逐步回归分析方法分析了影响土壤有机碳密度的主要因子。结果表明: 广西主要森林土壤有机碳储量(0-100 cm)达到1686.88 Tg, 土壤有机碳密度为124.70 Mg·hm^-2, 低于全国森林土壤平均水平。广西主要森林土壤有机碳密度最佳拟合模型为指数模型, 呈中等强度空间相关, Kriging插值显示土壤碳密度高值区在东北区域, 低值区在西北区域, 表现为喀斯特区域低、非喀斯特区域高的特点。广西主要森林土壤碳密度在不同植被类型和土壤类型下表现出一定差异, 其中竹林>落叶阔叶林>暖性针叶林>常绿落叶阔叶林>常绿阔叶林, 黄壤>红壤>赤红壤>石灰土。主成分分析和逐步回归分析结果发现土层深度、经纬度、海拔是影响广西森林土壤有机碳的主要因子, 其中以土层深度影响最大, 主要受岩溶地貌的影响。     

1985—2030年江西泰和县森林植被碳储量的时空动态

根据第6次森林清查小班数据,运用生物量转换因子法和平均生物量法估算了2003年江西省泰和县森林植被的生物量和碳储量,采用空间替代时间的方法,利用Logistic方程拟合了泰和主要森林类型年龄与碳密度的曲线关系,并结合小班轮伐信息,估算了全县1985—2003年的植被生物量和碳储量,分析了期间的时空动态特征,并以2003年为基准年,假定到2020、2030年泰和县森林植被面积保持稳定、且不考虑轮伐期,推算了此情景下2020、2030年泰和县植被碳储量.结果表明：2003年,泰和县森林林分总面积15.74×10⁴ hm²,总生物量6.71 Tg,植被碳储量4.14 Tg C,平均碳密度26.31 t C·hm^{- 2}. 1985、1994、2003、2020、2030年泰和县森林植被碳储量分别为1.06、2.83、4.14、5.65和6.35Tg C,森林植被碳密度的空间分布由东西部向中部递减.人工造林使泰和县林分面积大幅增加,全县森林植被的固碳能力明显增强.     

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。     

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.     

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.     

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.     

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.     

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%.