空间误差模型在黑龙江省森林碳储量空间分布的应用

基于黑龙江省2010年一类调查数据和重点公益林检测样地（5075块）数据以及同期黑龙江省、吉林省和内蒙古自治区59个气象站的气象数据,以森林碳储量为因变量,以胸径、每公顷株数、海拔、坡度及降雨与温度的乘积因子作为自变量,利用GeoDA软件构建空间误差模型,用全局Moran I 来描述不同空间尺度下模型残差的空间自相关性,计算最佳带宽（25 km）下的局域Moran I来表现模型残差的空间分布,计算组内方差来解释模型残差的空间异质性,最后将模型的预估结果生成黑龙江省森林碳储量的空间分布图.结果表明： 黑龙江省森林碳储量的分布具有空间效应;本文所选林分因子、地形因子及气象因子都显著影响森林碳储量的空间分布,胸径是最主要的因子.空间误差模型可以很好地解决模型残差的空间自相关性及空间异质性.由模型的预估结果可以看出,森林碳储量的空间分布存在很大差异,张广才岭、小兴安岭及大兴安岭地区是森林分布较密集的区域,松嫩平原地区的森林碳储量分布较少,完达山地区处于中等水平.
     

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。     

海南岛森林生态系统碳储量及其空间分布特征

利用最新的森林资源二类调查分布数据和野外样地调查资料,采用InVEST模型和空间统计分析等方法,研究了海南岛森林生态系统碳储量及其空间分布特征。结果表明：海南岛森林生态系统总碳储量为338.15 TgC,其中地上生物、地下生物、凋落物和土壤的碳储量分别为85.12、18.73、2.90 TgC和231.40 TgC,所占比重依次为25.17%、5.54%、0.86%和68.43%。海南岛森林生态系统平均碳密度为147.66 MgC/hm²,其中地上生物、地下生物、凋落物和土壤碳密度分别为37.17、8.18、1.27 MgC/hm²和101.04 MgC/hm²。不同市县森林生态系统碳储量分布在8.55—35.40 TgC的范围内,最高的是琼中县。不同植被类型中,橡胶林的碳储量最高,占全岛森林生态系统总碳储量的27.72%;热带山地雨林的碳密度最高,达到249.64 MgC/hm²。在海拔梯度上,森林生态系统碳密度呈现先增加后减少的变化特征,在海拔600—1300 m范围内的碳密度最高,碳密度为20...     

西藏昌都地区森林植被碳储量及空间分布格局

基于昌都地区第6次二类森林资源清查数据资料,运用生物量转换因子法进行生物量估算,以藏东南实测含碳率与国内含碳率的相关研究相结合,确定不同树种的含碳率,在此基础上,估算了昌都地区的森林碳储量和碳密度,并探讨其空间分布格局。结果表明:昌都地区的森林总碳储量约为1.058×10~8t,平均碳密度为67.31 t·hm~(-2),均低于林芝地区;各森林类型碳储量在4.5×10~2~8.21×10~7t,以云杉林的碳储量占绝对优势,为昌都地区的77.82%,碳密度则在19.88~81.16 t·hm~(-2);从龄组来看,以成、过熟林碳储量为主,占总森林碳储量的77.91%,各龄组碳密度随年龄增加呈近直线增加趋势;从森林碳储量和碳密度的分布格局来看,森林碳储量呈以左贡县最高,丁青县最低,"三江"南部区为高森林碳储量区,"三江"中游区为低森林碳储量区,"三江"上游区为中等森林碳储量区的总体分布格局;总体上,森林碳密度则呈以东北部江达县为最高,东南部的芒康县为最低,"三江"上游区平均碳密度最高,"三江"南部区次之,"三江"中游区最低,但空间分布差异相对较小(60.55~74.41 t·hm~(-2))。     

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。     

深圳市森林植被碳储量特征及其空间分布

基于2005年深圳市森林资源二类调查资料数据,采用材积源生物量法,计测深圳市森林植被碳储量和碳密度,分析了深圳市森林植被碳储量空间分布格局.结果表明,2005年深圳市森林植被总碳储量为225.04×10⁴Mg,平均碳密度为25.63MgC·hm^-2.深圳市各区的森林植被碳储量空间分布上有显著差异.表现为龙岗区(123.13×10⁴Mg)>宝安区(46.70×10⁴Mg)>盐田区(20.49×10⁴Mg)>罗湖区(14.75×10⁴Mg)>南山区(12.79×10⁴Mg)>福田区(5.63×10⁴Mg)>保护区(1.57×10⁴Mg).各区碳密度分布为盐田区(46.18MgC·hm^-2)>福田区(37.63 MgC·hm^-2)>罗湖区(36.78MgC·hm^-2)>龙岗区(26.60MgC·hm^-2)>保护区>(24.19 MgC·hm^-2)>宝安区(19.53MgC·hm^-2),与碳储量大小分布无明显相关.深圳市乔木林碳储量为146.11×10⁴Mg,以中幼龄林为主,占73.2%,平均碳密度为30.76MgC·hm^-2.根据森林植被碳储量与碳密度的空间差异性对深圳市森林进行了区划,并分区提出了提高深圳市森林碳吸存能力的有效措施.     

黑龙江省森林植被碳储量及其动态变化

黑龙江省的森林资源在全国森林资源中占有较为重要的位置.利用我国第一次(1973～1976年)至第六次(1999～2003年)森林资源清查资料,以及不同树种生物量和蓄积量之间的线性关系,对黑龙江省近30年来森林碳储量进行了求和推算.结果表明,黑龙江省6次森林资源清查中森林的总碳储量分别是7.916×10⁸ t、.413×10⁸ t、.661×10⁸ t、.880×10⁸ t、6.216×10⁸ t和6.011×10⁸ t,总体呈先下降后上升的趋势,说明30年间黑龙江省的森林是CO₂的"汇";特别是1977～1981年后,黑龙江省森林碳储量呈逐渐上升趋势,说明近20年来黑龙江省森林CO₂"汇"的作用在增强.如果对现有森林进行更好地抚育和管理,黑龙江省森林作为CO₂"汇"的潜力很大.     

四川省森林植被碳储量的空间分异特征

森林植被碳储量的空间分异特征研究可为以减排增汇为目标的森林生态系统碳库管理提供重要的基础数据.根据实测的林分含碳量和区域生物量-蓄积量回归模型计算了四川省森林植被碳储量,使用ArcGIS软件绘制和分析了四川森林植被碳储量的空间分异特征.结果表明,四川省森林植被的平均碳密度为38.04 MgC·hm-2(12.15～59.51 MgC·hm-2).受青藏高原隆升和人类活动干扰及其叠加效应的影响,四川森林植被碳密度空间分异明显,总体上表现出随纬度、海拔高度和坡度的增加而增加,随经度的增加而减小,高海拔地区和陡坡地带具有较高的碳密度.减少人类活动对森林的破坏及采取森林分区经营管理是稳定和增强四川森林碳汇功能的有效途径.     

西藏林芝地区森林碳储量、碳密度及其分布

利用林芝地区第六次二类森林资源清查数据,运用材积源生物量法和平均生物量法,结合不同树种的分子式含碳率,估算了林芝地区森林及其组分的碳储量、碳密度,并分析其分布特征.结果表明: 2004年,林芝地区森林碳储量为2.43×10⁸ t,森林平均碳密度为76.01 t·hm^-2,其中,林分碳储量>灌木林碳储量>疏林碳储量>散生木碳储量>竹林碳储量>四旁树碳储量,各林分类型碳储量在2.51×10⁵～1.27×10⁸ t,共计占总森林碳储量的92.0%,各林分类型的平均碳密度为103.16 t·hm^-2,其中冷杉林的碳储量和碳密度均最高.在区域分布上,森林碳储量由西北向东南递增,森林平均碳密度由西南向东北递增.林分碳储量以成、过熟林碳储量为主,而过熟林的碳密度在各龄级中最高.随着过熟林的增加,林芝地区森林碳储量将增加;但随着过熟林的死亡和分解,林芝地区森林碳储量将有减小趋势.     

西藏林芝地区森林碳储量、碳密度及其分布

利用林芝地区第六次二类森林资源清查数据,运用材积源生物量法和平均生物量法,结合不同树种的分子式含碳率,估算了林芝地区森林及其组分的碳储量、碳密度,并分析其分布特征.结果表明:2004年,林芝地区森林碳储量为2.43×1O8 t,森林平均碳密度为76.01 t·hm-2,其中,林分碳储量＞灌木林碳储量＞疏林碳储量＞散生木碳储量＞竹林碳储量＞四旁树碳储量,各林分类型碳储量在2.51×105～1.27×108 t,共计占总森林碳储量的92.0％,各林分类型的平均碳密度为103.16 t·hm-2,其中冷杉林的碳储量和碳密度均最高.在区域分布上,森林碳储量由西北向东南递增,森林平均碳密度由西南向东北递增.林分碳储量以成、过熟林碳储量为主,而过熟林的碳密度在各龄级中最高.随着过熟林的增加,林芝地区森林碳储量将增加;但随着过熟林的死亡和分解,林芝地区森林碳储量将有减小趋势.     

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.     

基于地理加权回归拓展模型的天然次生林碳储量空间分布

为精准获取区域尺度天然次生林的碳储量及其空间分布格局,以吉林省汪清林业局浪溪林场的天然次生林为研究对象,基于165块局级固定样地,以林分因子、地形因子和土壤因子为影响因子,将普通地理加权回归模型(GWR)作为基础,从空间维度、参数异质性特征和残差空间自相关性3个方面进行改进,构建7类拓展模型,即地理海拔加权回归模型(G...     

基于地统计学和CFI样地的浙江省森林碳空间分布研究

基于浙江省2009年CFI固定样地数据、森林资源规划设计调查林相图,利用地统计学方法对浙江省森林碳空间分布进行了模拟分析。结果表明,CFI固定样地数据用于省域范围的森林碳汇空间特征研究是合适的。数据显示,浙江森林植被平均碳密度为22.07Mg/hm2;与四川、福建、海南等地相比,平均碳密度较低。受人类活动、自然环境等因素影响,浙江省森林碳分布主要表现为:总体上森林碳密度空间变化趋势自西向东逐渐降低,与自然空间(海拔、地势等)趋势一致。基于地统计学和CFI固定样地,对省域范围的森林资源空间分布的研究,可以为省域森林碳汇管理提供依据,为我国特别是亚热带南方集体林区利用国家CFI数据进行大区域同类研究提供借鉴。     

胶州湾滨海湿地土壤有机碳时空分布及储量

在胶州湾选取芦苇、碱蓬、光滩及大米草4种典型滨海湿地类型,分季节和层次采集土壤样品,测定土壤有机碳含量,分析滨海湿地土壤有机碳的时空分布及储量.结果表明: 垂直方向上,除光滩湿地沿剖面呈先减小后稍有上升的趋势外,其他湿地均随土壤深度的增加而减小;水平方向上,湿地土壤有机碳含量表现为大米草湿地>光滩湿地>碱蓬湿地>芦苇湿地;季节上,湿地土壤有机碳含量表现为春季>夏季>秋季>冬季.土壤有机碳含量与土壤含盐量、含水率、TN及C/N呈正相关,与土壤容重、pH值呈负相关.不同类型湿地土壤剖面有机碳密度表现为光滩湿地>芦苇湿地>碱蓬湿地,湿地类型对土壤有机碳含量和有机碳密度分布的影响存在一定差异.因储碳层厚度及储碳层内有机碳密度的差异,光滩湿地单位面积有机碳储量明显高于碱蓬和芦苇湿地,具有较大的储碳潜能,对研究区滨海湿地起到一定的碳汇作用.     

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.     

吉林省森林生态系统的碳储量、碳密度及其分布

利用森林资源二类调查汇总数据和标准地实测数据,研究吉林省森林生态系统的碳密度、碳储量及其组分和分布特征.结果表明:吉林省森林生态系统碳储量为1827.293TgC,其中乔木层、灌草层、枯落物层和土壤层的碳储量分别为439.152、5.195、45.600和1330.466TgC,分别占总碳量的24.1%、0.3%、2.5%和73.1%.吉林省森林生态系统碳密度为225.304MgC.hm-2,各层碳密度的大小顺序为土壤层(164.666MgC.hm-2)>乔木层(54.352MgC.hm-2)>枯落物层(5.644MgC.hm-2)>灌草层(0.643MgC.hm-2).不同类型森林生态系统碳储量在9.357～959.716TgC,碳密度在180.648～254.627MgC.hm-2之间,各林型分配特征表现为土壤层最大、灌草层最小.全省森林生态系统碳储量和碳密度的空间分布总体上为东部山区高、中西部平原地区低.吉林省森林中中龄林分比重大,若对现有森林加以更好的管理,可以增加其碳吸存潜力.     

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.