西藏自治区云杉林生物量密度模型研建

生物量密度模型是估算生物量和碳储量的依据。以西藏主要针叶树种云杉为研究对象,利用森林资源连续清查实测样地和样木数据,建立了云杉林生物量密度模型。结果表明:生物量密度随树高、郁闭度、胸径及林龄的增加而增加,随海拔的升高和经度的增加而减少。以海拔、郁闭度、平均胸径、经度作为解释变量构建的生物量密度非线性模型,其决定系数为0.716,总相对误差和平均系统误差控制在±1%以内,预估精度达到91.9%,可应用于实测或目测样地/小班生物量估算;以海拔、郁闭度、林龄、经度作为解释变量构建的生物量密度非线性模型,其决定系数为0.626,总相对误差和平均系统误差控制在±2%以内,预估精度达到90.6%,可应用于遥感样地/小班生物量估算;以海拔、郁闭度、胸径、林龄作为解释变量的生物量密度模型,其决定系数为0.717,总相对误差和平均系统误差控制在±2%以内,预估精度达到91.9%,可用于估算某个时间段内云杉林生物量变化或碳汇量。结合西藏森林资源连续清查或森林资源规划设计调查数据,可用于全区尺度上云杉林生物量的估算;利用林龄等因子建立的生物量模型,可掌握生物量、碳汇在空间上的分布规律及某一时期内的碳汇估算。     

基于森林清查资料的中国森林植被碳储量

利用第七次全国森林资源连续清查数据,以回归模型估计法作为乔木林生物量的主要计算方法,以树种含碳率作为生物量转换为碳储量的系数,从单木归并到样地,从样地加权平均至省级区域,估算乔木林碳储量;以加权平均转换系数估算疏林地、散生木和四旁树的碳储量,以模型法估算竹林、灌木林的碳储量。结果表明:中国森林植被碳储量主要集中在西南和东北两大区;乔木林是中国森林植被碳储量的主体;人工林碳储量在中国乔木林碳储量中比例超过15%;阔叶树的碳储量和碳密度均大于针叶树。     

湖南杉木林生物量密度的模拟与预测

杉木作为我国南方地区重要用材树种,在森林固碳增汇方面起着重要作用。本研究在利用森林资源连续清查样地数据对湖南省杉木林样地尺度进行碳储量估算的基础上,通过多因子非线性回归方法,量化环境因子和林分因子对生物量密度的影响,以期为提高杉木生产力提供参考。     

西藏自治区森林枯落物碳储量估算

利用典型样地采样,建立了枯落物碳密度与厚度关系方程,并结合森林资源连续清查的样地坡度与枯落物厚度因子,估算出西藏自治区森林枯落物碳储量.结果表明,西藏自治区丰富的森林植被生产了巨大的枯落物层碳库,有机碳分解和碳库消耗缓慢.研究该部分碳库状况,为估算和评价陆地生态系统碳储量并据此制定相应的对策提供了基础数据.     

西藏自治区冷杉林生物量分布格局及模型研建

基于第八次全国森林资源连续清查实测样地数据,研建了冷杉林生物量密度多元线性和非线性模型,探寻地理因子与林分因子对生物量的协同影响。结果表明:以胸径、郁闭度为自变量构建的模型,其决定系数为0.526,预估精度为93.63%;以林龄、海拔、郁闭度为自变量构建的模型,其决定系数为0.403,预估精度为92.28%。结合西藏森林资源连续清查或森林资源规划设计调查数据,可用于全区尺度上冷杉林生物量的估算;利用林龄、海拔为自变量构建的模型,可用于掌握生物量、碳汇在空间上的分布规律及某一时期内的碳汇量。     

基于GIS的森林清查固定样地生物量变化分析

以20世纪90年代和21世纪初两个时期的森林资源清查样地数据为基础,估算了小兴安岭地区森林生物量,采用了相对生长法和模型法构建样地森林生物量估算模型,在GIS技术的支持下,最终分别得出了小兴安岭森林生物量等级分布和森林生物量变化的结果.     

全国森林资源清查样地标准化和时间归一化数据库的建立

为实现森林生物量和碳储量的年度监测,准确把握森林资源的消长动态,研究探讨了全国森林资源清查样地数据标准化和归一化的技术方法和路线,对以省为单位的最新两期或多期(1999—2015年)森林资源清查地面样地数据进行标准化和时间归一化,获取目标年度的森林资源样地和样木数据,建立了全国范围的2005,2012和2014年3个年度样地和样木数据库,为我国森林资源数据分析、森林蓄积量和生物量估算等多项工作提供有效地面数据支撑。     

基于TM数据的森林植物碳储量估测方法研究

以广东省第六次森林资源连续清查样地数据为基础，根据TM数据及其非线性组合的光谱信息，结合地学信息及林分信息，建立了森林植物碳储量估测的多元线性回归方程及神经网络模型。分析结果表明，神经网络模型的估测精度高于回归模型估测精度，但用它们估测落实到样地的森林植物碳储量误差仍然较大，还不能满足样地调查精度的要求。     

云南省森林碳储量现状与动态分析

以第八次森林资源连续清查数据为基础,采用生物量换算因子连续函数法估算云南省森林碳储量。结果表明:云南省森林碳储量为7.76×108t,阔叶林在面积、蓄积、生物量和碳密度等方面都占有绝对优势,固碳方面发挥更大作用,天然林在各方面均优于人工林。森林资源动态分析结果,我国人工林面积得到大增长,森林面积和蓄积呈现增长态势。     

云南省森林生态系统植被碳储量及碳密度估算

基于2009-2013年第8次全国森林资源连续清查数据,利用生物量扩展因子法,采用改良的计算参数,从不同龄组、林型等方面进行考虑,对云南省森林资源的生物量、碳储量及碳密度进行了估算。结果表明,我国第8次森林资源清查中,云南省森林林分生物量为1 640.92×106t,平均生物量为101.71 t/hm2,林分碳储量为775.30×106t C,林分平均碳密度为50.77 t C/hm2,森林植被碳储量总量为818.29×106t C。人工林碳储量只占林分碳储量的5.90%,幼龄林只占林分碳储量的17.09%;天然林与成熟林在云南省森林资源碳储量中所占比重较大,在扩大云南省森林植被碳储量方面,可以通过选择林龄结构及森林林分类型来加以实现。人工林将会在森林植被碳储量中占有越来越重要的地位。     

基于森林资源二类调查数据的大冶市森林植被碳储量和碳密度测算

森林通过吸收大气中的二氧化碳固定到碳库中，在“双碳”目标中起着碳中和的重要作用。本研究基于大冶市2019年林业资源二类调查小班数据，采用材积源生物量法对大冶市森林资源的植被碳储量和碳密度进行测算，结果表明：大冶市现有森林植被碳储量114.36×10⁴ t,平均植被碳密度为23.66 t·hm^-2;碳储量较高的区域主要集中分布在大冶南部山区，灌木林碳储量占比最高，其次为马尾松林；马尾松林的平均植被碳密度最高，达到35.64 t·hm^-2。该测算结果可为大冶市实现“双碳”目标以及森林资源的科学管理提供数据基础和决策依据。     

河口县森林碳储量估算分析

以森林资源规划设计调查数据为基础,采用生物量扩展因子法和平均生物量法,从不同森林类型、不同起源、不同龄组、不同优势树种组等方面,估算了河口县森林碳储量及碳密度.结果从碳储量来说:河口县总碳储量为2840396 t,以乔木林碳储量为主,以天然林的碳储量为主,以阔叶林碳储量为主,以近熟林、成熟林、过熟林碳储量为主,以其他阔...     

云南松林碳储量的初步估算

以云南省第五次森林资源连续清查数据及云南省林业调查规划院专业调查的林木、林下灌木、林下草本植物生物量、林下土壤有机碳含量等资料成果为依据,对云南省的云南松林碳储量进行估算.估算结果,云南松林储碳总量为4.649亿t.文章还以"连清"推算的生长率及消耗率数据为依据预测了云南松林碳储增长量.     

云南省森林生物量与生产力研究

森林是陆地生态系统的主体,生物量是反映森林生态系统功能的重要指标.通过利用最新的(2002年)森林资源清查数据,以生物量与蓄积量之间的关系模型为基础,对云南省的森林生物量及生产力进行了估计,为碳汇研究及森林生态系统评价提供重要依据.     

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.     

Dynamics of forest biomass carbon stocks from 1949 to 2008 in Henan Province,east-central China

We estimated forest biomass carbon storage and carbon density from 1949 to 2008 based on nine consecutive forest inventories in Henan Province,China.According to the definitions of the forest inventory,Henan forests were categorized into five groups: forest stands,economic forests,bamboo forests,open forests,and shrub forests.We estimated biomass carbon in forest stands for each inventory period by using the continuous biomass expansion factor method.We used the mean biomass density method to estimate carbon stocks in economic,bamboo,open and shrub forests.Over the 60-year period,total forest vegetation carbon storage increased from34.6 Tg(1 Tg = 1×10~(12)g) in 1949 to 80.4 Tg in 2008,a net vegetation carbon increase of 45.8 Tg.By stand type,increases were 39.8 Tg in forest stands,5.5 Tg in economic forests,0.6 Tg in bamboo forests,and-0.1 Tg in open forests combine shrub forests.Carbon storageincreased at an average annual rate of 0.8 Tg carbon over the study period.Carbon was mainly stored in young and middle-aged forests,which together accounted for 70–88%of the total forest carbon storage in different inventory periods.Broad-leaved forest was the main contributor to forest carbon sequestration.From 1998 to 2008,during implementation of national afforestation and reforestation programs,the carbon storage of planted forest increased sharply from 3.9 to 37.9 Tg.Our results show that with the growth of young planted forest,Henan Province forests realized large gains in carbon sequestration over a 60-year period that was characterized in part by a nation-wide tree planting program.     

我国21世纪森林资源发展趋势灰色预测

应用邓聚龙教授创立的灰色理论与方法,以我国森林资源连续清查统计数据为基础,建立灰色预测的GM(1 1)模型,对全国森林资源主要指标(1)森林覆盖率;2)有林地面积;3)活立木总蓄积量)的发展趋势进行预测。由于连续清查数据具有连续性、可比性特征,因此,预测结果经检验,精度较高,可以作为宏观决策的科学依据。     

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.     

基于森林生物量相容性模型长白山天然林生物量估测

利用中国第四次(1997年)二类森林调查数据,借助长白山天然林森林生物量相容性模型,以汪清天然林区为例,对阔叶林、针叶林及针阔混交林等不同森林群落进行森林生物量及其分量的估测,研究区森林生物量密度及碳密度估测值分别为110.06 t/hm2和51.73 t/hm2,碳库估测值为0.0119 Gt C.阔叶林生物量占总森林生物量的59%,在该研究区占主导地位。