河南省杨树人工林生物量研究

利用河南省第7次森林资源连续清查资料,分别采用生物量转换因子法、生物量回归模型法、生物量转换因子连续函数法对河南省杨树人工林生物量进行了估算。经比较模型的适用范围,最终采用生物量转换因子法估算值作为河南省杨树人工林生物量;中、幼林生物量占整个杨树人工林生物量总量的80.47%,表明杨树人工林生物量在各龄组中分布不均衡;河南省杨树人工林生物量总体质量不高,但具有较大发展空间,通过加强杨树人工林的抚育管理措施,对提升整个区域的杨树生物量水平具有重要意义。     

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.     

Variations in the biomass of Eucalyptus plantations at a regional scale in Southern China

We quantified deviations in regional forest biomass from simple extrapolation of plot data by the biomass expansion factor method(BEF) versus estimates obtained from a local biomass model,based on large-scale empirical field inventory sampling data.The sources and relative contributions of deviations between the two models were analyzed by the boosted regression trees method.Relative to the local model,BEF overestimated accumulative biomass by 22.12%.The predominant sources of the total deviation (70.94%) were stand-structure variables.Stand age and diameter at breast height are the major factors.Compared with biotic variables,abiotic variables had a smaller overall contribution (29.06%),with elevation and soil depth being the most important among the examined abiotic factors.Large deviations in regional forest biomass and carbon stock estimates are likely to be obtained with BEF relative to estimates based on local data.To minimize deviations,stand age and elevation should be included in regional forest-biomass estimation.     

Variations in the biomass of <Emphasis Type="Italic">Eucalyptus</Emphasis> plantations at a regional scale in Southern China

We quantified deviations in regional forest biomass from simple extrapolation of plot data by the biomass expansion factor method (BEF) versus estimates obtained from a local biomass model, based on large-scale empirical field inventory sampling data. The sources and relative contributions of deviations between the two models were analyzed by the boosted regression trees method. Relative to the local model, BEF overestimated accumulative biomass by 22.12%. The predominant sources of the total deviation (70.94%) were stand-structure variables. Stand age and diameter at breast height are the major factors. Compared with biotic variables, abiotic variables had a smaller overall contribution (29.06%), with elevation and soil depth being the most important among the examined abiotic factors. Large deviations in regional forest biomass and carbon stock estimates are likely to be obtained with BEF relative to estimates based on local data. To minimize deviations, stand age and elevation should be included in regional forest-biomass estimation.     

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。     

基于国家森林资源清查数据的不同生物量和碳储量估计方法的对比分析

[目的]通过对不同生物量和碳储量的估计方法进行对比分析,为确定在国家森林资源清查中生物量和碳储量的具体估计方法提供依据。[方法]以广东省2012年森林资源清查的100个杉木林和80个马尾松林的实测样地资料为基础,利用近年来我国建立的主要树种立木生物量模型,对改进IPCC法、生物量模型法和转换因子连续函数法(即方精云法)3种方法按一元和二元模型共6种方案进行了对比;同时,基于改进IPCC法一元和二元模型的生物量估计值,用平均含碳系数法、组分含碳系数法和固定含碳系数(0.5或0.47)法分别对碳储量进行估计。[结果]用二元生物量模型法得到的杉木林和马尾松林样地的总生物量分别为320 Mg和331 Mg,一元生物量模型法的结果分别相差0.9%和6.2%;改进IPCC法的估计结果,采用二元和一元模型时杉木林分别相差-3.6%和-11.9%,马尾松林分别相差-8.5%和-19.6%;而方精云法的估计结果,采用二元和一元模型时杉木林分别相差6.65倍和6.60倍,马尾松林分别相差-14.3%和-18.0%。平均含碳系数法和组分含碳系数法的碳储量估计结果,杉木林仅相差0.2%,马尾松林相差约0.4%;固定含碳系数法的估计结果因树种而异,对杉木林要低估0.6%5.4%,对马尾松林要低估3.3%9.1%。[结论]对生物量的估计,采用生物量模型法准确性最高,而林木水平的生物量模型其预估精度要高于林分水平的模型;IPCC法是基于材积源的通用方法,将其中的缺省参数改进为可变参数模型,可大大提高方法的适应性;方精云法只是基于IPCC法所建立的林分水平模型在大尺度上的一种具体应用方法,其精度要低于林木水平的生物量模型法,不适于中小尺度应用。对碳储量的估计,采用平均含碳系数法与组分含碳系数法差异很小,但采用固定含碳系数法则误差较大。     

基于蓄积的森林生物量估算方法的对比分析

正森林生物量是指一个森林群落在一定时间内积累的有机质总量,是森林生态系统重要的特征数据,因此世界各国越来越重视对森林生物量的监测与研究[1-3],建立的生物量模型众多[4-6]。大尺度森林生物量监测,是以省、流域、国家乃至全球为对象,在估算方法一致的前提下,对多个时间点的森林生物     

非线性模型对数回归的偏差校正及与加权回归的对比分析

本文结合大样本的立木生物量实测数据,对非线性模型对数回归的偏差校正问题进行了探讨,并与加权回归结果进行了对比分析。首先,分析了对数回归产生偏差的内在原因,并提出了一个新的校正因子,同时对另外3个偏差校正因子一并进行了检验,结果表明本文和Baskerville(1972)提出的校正因子,能保证与加权回归估计结果趋于一致;然后,对非线性加权回归中基于普通回归残差推导的权函数与通用权函数(W＝1/f(x)²)的拟合效果进行了对比分析,结果表明二者基本相当,而通用权函数更具有广泛的适应性。建议对带有异方差的非线性模型,最好直接采用加权回归进行估计;当按照通用权函数进行估计其总相对误差超出一定范围时,应该根据普通回归估计的残差推导效果最佳的权函数后再进行加权回归。     

岷江上游亚高山暗针叶林的生物量碳密度

利用森林资源连续清查的样地数据,基于生物量与蓄积量之间的关系模型,估测岷江上游亚高山暗针叶林地上部分生物量碳密度、碳密度年增长率及其随林龄、海拔和坡向变化的分布规律.结果表明:岷江上游暗针叶林的成熟林、过熟林生物量碳密度较高,中龄林、幼龄林生物量碳密度较低,成熟林、过熟林生物量碳密度高于全国平均水平,而中龄林和近熟林低于全国平均水平,幼龄林与全国平均水平相近;中龄林生物量碳密度年增长率最大,为1.3%,其次为过熟林,生物量碳密度年增长率为0.8%,幼龄林生物量碳密度年增长率最小,为0.7%;海拔3600～3800m处生物量碳密度最大,明显高于其他海拔区段;海拔3000～3400m处生物量碳密度年增长率最高,为1.03%;半阴坡和半阳坡的生物量碳密度高且年增长率最大,其次是阴坡,阳坡生物量碳密度低,年增长率最小;过去20多年,岷江上游暗针叶林生物量碳密度呈现逐年增加的趋势,1997-2002年,生物量碳密度年平均增长率为1.15%,高于其他调查期间碳密度年增长率.     

Inventory-based estimates of forest biomass carbon stocks in China: A comparison of three methods

Several studies have reported different estimates for forest biomass carbon (C) stocks in China. The discrepancy among these estimates may be largely attributed to the methods used. In this study, we used three methods [mean biomass density method (MBM), mean ratio method (MRM), and continuous biomass expansion factor (BEF) method (abbreviated as CBM)] applied to forest inventory data to estimate China's forest biomass C stocks and their changes from 1984 to 2003. The three methods generated various estimates of the biomass C stocks: the lowest (4.0–5.9 Pg C) from CBM and the highest (5.7–7.7 Pg C) from MBM, with an intermediate estimate (4.2–6.2 Pg C) from MRM. Forest age class is a major factor responsible for these method-induced differences. MBM overestimates biomass for young-aged forests, but underestimates biomass for old-aged forests; while the reverse is true for MRM. Further, the three methods resulted in different estimates of biomass C stocks for different forest types. For temperate/subtropical mixed forests, MBM generated a 92% higher estimate than CBM and MRM generated a 14% lower than CBM. The degree of the overestimates is closely related with the proportion of young-aged forest within total area of each forest type.     

长江三角洲地区森林碳汇的初步估算与分析

利用森林资源清查数据,采用回归模型和含碳系数换算方法,估算了长三角区域的森林生物量和碳储量,分析了该区域森林碳汇的结构、分布及其增长潜力,提出了构建区域协作机制和发展区域碳汇林业的相关建议。     

基于异速生长和理论生长方程的广东省木荷生物量动态预测

【目的】将异速生长方程与理论生长方程相结合,预测广东省木荷生物量动态,为广东省木荷林碳汇计量提供模型和方法,为其他树种碳汇计量提供可借鉴的方法学支持。【方法】基于实测样木生物量调查数据,包括40株树干解析资料,构建由胸径和年龄的理论生长方程以及地上生物量和胸径的异速生长方程组成的模型系,利用非线性度量误差联立方程组,在胸径生长速度分级情况下拟合模型参数;基于3期森林资源连续清查固定样地样木数据,对广东省木荷生物量动态进行预测。采用决定系数( R 2)和均方根误差(RMSE)评价模型拟合效果,通过生物量存量估计误差和增量估计误差判断模型预测效果。【结果】在胸径生长速度分级情况下,理论生长方程中年龄对胸径的解释率达0.95以上,比不分级提高0.166 3,均方根误差下降到1.97 cm,降低2.16 cm以上,预测胸径对地上生物量的解释率提高到近0.82;接近独立异速生物量模型中实测胸径对地上生物量的解释率达0.88以上,比不分级提高近0.30,均方根误差下降到51 kg左右,下降30 kg以上。在胸径生长速度不分级情况下,各期生物量存量估计误差变动幅度在-46.31%~77.45%之间,而分级情况下下降到-16.13%~7.06%;在尺度上,分级与不分级均呈相同规律,即单木误差小于林分误差、林分误差小于区域误差。不分级时,单木水平和区域尺度间的误差不大于10%,而分级时小于8%。不同间隔期生物量增量估计误差,不分级时估计值普遍偏大,在32.57%~115.45%之间,而分级时下降到-6.57%~15.77%之间,在单木尺度上不超过±10%;随着尺度增大,增量估计误差不断增加,不分级时单木水平和区域尺度间的误差介于10%~15%之间,分级时稳定在8%左右。【结论】对于理论生长方程和异速生长方程组成的模型系,分级可极大提高模型精度,减小预测估计误差;生长速度不分级时,仅利用胸径或年龄数据,分级时,则可利用2期胸径数据或1期胸径和年龄数据,就可预测未来生物量动态,简单方便,在森林资源连续清查和碳汇造林的碳汇量计量中具有极大应用价值,区域尺度上的估计误差也可基本满足精度要求。     

中国林木生物质能源潜力测算及变化趋势

基于各省份林业统计数据,文中利用自下而上分析方法测算了中国林木生物质能源的资源潜力,并对变化趋势进行分析。结果表明:1993—2013年中国林木生物质能源资源潜力由0.78亿t标准煤增长到1.05亿t标准煤,20年间增长了34.62%;从资源构成来看,灌木平茬剩余物和采伐剩余物是林木生物质能源的主要供给来源;从区域变化来看,不同省份资源潜力呈现明显差异,但全国平均水平的逐步提高并非个别省份资源潜力大幅度提高使然,而是绝大部分省份资源潜力的共同增长促成了平均水平的连年提高。     

华北落叶松人工林的生物量估算参数

分析华北落叶松人工林4个典型区域(关帝山、五台山中山区、五台山盆地区和塞罕坝)的生物量估算参数(生物量转扩因子、生物量扩展因子和根茎比)及其区域分异。结果表明:关帝山林区和五台山林区(中山区和盆地区)的生物量转扩因子平均值间无显著差异(P>0.05)且都大于塞罕坝林区(P<0.05);关帝山林区、五台山盆地区和塞罕坝林区的生物量扩展因子平均值间无显著差异(P>0.05)且都小于五台山中山区(P<0.05);生物量转扩因子和生物量扩展因子随林龄、平均胸径和蓄积量的增加而减小并趋于稳定;4个区域的根茎比平均值间无显著差异(P>0.05);根茎比随林龄和平均胸径的增加而增加(P<0.01),但与林分密度和蓄积量无显著相关性(P>0.05)。由于不同区域的生物量转扩因子和生物量扩展因子平均值间存在显著差异,故而建议按区域选择它们的值,并尽可能利用它们与林分测量指标的函数关系来确定。     

西藏自治区森林碳密度及分布规律研究

利用森林资源连续清查实测样地及样木数据,结合相对树高曲线,构建生物量-蓄积量模型,解决了模型与各类森林资源调查数据的衔接问题,可应用于西藏自治区森林资源连续清查的目测与遥感样地生物量估算及森林资源规划设计调查小班生物量估算等。根据计算的森林资源连续清查各样地生物量密度,结合树种面积数据及含碳率,估算全区森林碳密度,并初步探讨了森林碳库地带性分布规律。     

川西米亚罗林区林场水平森林生物量研究

利用川西米亚罗林区森林资源清查数据,以森林蓄积量和森林生物量之间的关系模型为基础,对川西林业局301林场的森林生物量进行了估算,并对研究地区不同林龄及森林类型的森林生物量进行了分析。研究结果表明:1)研究区域林分总生物量为3 041 229t,林分单位面积平均生物量为87.13 t/hm2,低于全国生物量及四川省生物量的平均值,主要由于占绝对优势的云、冷杉林所处立地条件差,生物量较低造成;2)林分年龄结构不合理,成、过熟林面积较大(占69%);3)水土保持林的生物量在所有森林类型中所占比例最高(占80%)。     

Additive prediction of aboveground biomass for Pinus radiata (D. Don) plantations

A general and two country-specific systems of additive equations were developed to predict aboveground biomass of Pinus radiata plantations from stand variables that are routinely measured in inventory plots and predicted by conventional growth and yield models. The data for this work consisted of 319 plot-based biomass estimates that were derived from individual tree biomass equations developed in situ. These plot-based biomass estimates were compiled from studies reported in the forestry and ecological literature since 1960 and also from personal communications. They represent more than 60 sites worldwide with a majority in Australia and New Zealand. The systems of additive biomass equations developed from these data provide an alternative and addition to the current methods of estimating the aboveground biomass of P. radiata plantations. They also provide a direct linkage between forest inventory measures, outputs from conventional growth and yield models and biomass and carbon stock estimates at the same spatial scale. This direct linkage provides a new basis for scaling to a remote sensing image from which biomass and carbon stocks across the landscape can be mapped. Comparisons of prediction accuracies between this approach and other methods such as scaling up from individual tree biomass estimates and biomass expansion factors highlighted considerable methodological differences in the estimates of aboveground biomass and associated uncertainties over a range of stand age and conditions. These differences should be carefully evaluated before adopting a particular method to estimate aboveground biomass and carbon stocks of P. radiata plantations at a local, regional or national scale.     

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.     

利用MODIS数据反演森林生物量的方法研究

以东北三省为试验区,利用MOD IS时间序列上的植被指数NDVI,结合森林资源清查样地数据测算的林分生物量,以及年均降水量、年均蒸散量、年均湿润度、年均积温、经度、纬度等地理环境因子,采用多元线性回归的方法构建森林生物量遥感估测模型。通过样本检验,该模型对东北三省的森林生物量密度估测精度较高,与检验样本的平均每公顷生物量平均相差1.30%;通过样本定位检验,平均相差21.87%。该模型适宜在宏观尺度上估测森林生物量。     

Applicability of Fitted and Published Biomass Equations for Larix Species in Northeastern China

ABSTRACT

This study reviewed published biomass equations for Larix species in the literature and developed additive biomass equations (by nonlinear seemingly unrelated regression known as NSUR) and independent equations, respectively, based on DBH-only and DBH-H variables with the biomass data of 150 trees sampled in northeastern China. The applicability of fitted and published equations was comprehensively assessed with respect to Larix species, their provinces and origins when applied in northeastern China. The results showed that equations derived from the local study area did not always perform better than the published biomass equations in the literature. Tree-level equations performed slightly broader than stand-level equations. Nonlinear regression could provide higher applicability due to correction factors in the linear regression. Adding tree height as the second variable improved the applicability of stem and aboveground published equations. The applicability of original published equations was better for northeastern China for sites of similar latitude. When using published biomass equations, care should be taken to assess the uncertainty and applicability of biomass equations, which is important for the sustainable management of forested resources. Published information on biomass equations is especially necessary for forestry organizations that do not have the opportunity to develop their own equations.