黄土丘陵区沙棘地上部生物量估测量估测模型

根据沙棘生长因子与其地上部生物量间的关关系，以生长因子为自变量，沙棘地上部生物量为因变量，应用主成分分析和多元回归分析方法，依据最优子集和平均残差平方和的优选原则，从单生长因子，双生长因子、多生长因子估测模型中，筛选出具有最优性质的沙棘地上部生物量估测量模型，     

沙棘林木生长与地上部生物量动态

依据１９９８年在半干旱黄土丘陵区安塞、吴旗的调查资料,对沙棘年生长及单株地上部生物量进行了分析。结果表明：（１）时间的三次系基式与生长的关系能较好地反映生长期内生长与时间的关系;（２）沙棘单株地上部各器官生物量占地上部生物量的分配比率顺序为：枝〉茎〉叶〉桔枝;且枝、叶、枯枝生物量与树彰有十分显著的相关关系,茎与树龄间有的相关关系;（３）可用树高、地径、树个械模型与地径、冠幅、多年生枝长结合模型估测     

浙江舟山地区马尾松地上生物量模型研究

基于浙江舟山地区马尾松标准地的调查和几种常用的树木单株生物量估测模型,选择单个因子和多因子组合,分别对马尾松地上总生物量、树干生物量、树枝生物量和树叶生物量进行建模,并对各种模型进行误差分析,从中挑选最优的估测模型,可以在一定精度保证下,用于该地区马尾松生物量估测。     

思茅松树干生物量、树皮率与基本密度研究

建立思茅松树干生物量估测最优模型,分析思茅松木材基本密度、树皮率及其与胸径、树高、树龄等的关系.结果表明,在3种常用的生物量模型中,幂函数效果最好,且引入材积因子后,模型的估测精度有较明显提高;思茅松底部与中部木材基本密度无显著性差异,上部明显低于中部和底部;思茅松木材基本密度与树龄呈显著正相关,与胸径、树高等无显著相关;树干各部分树皮率底部最大,中部次之,上部最小.     

马尾松成熟林单木生物量模型研究

基于福建省漳平市马尾松人工成熟林标准地调查和生物量测定,应用几种常用的单木生物量估测方程,建立马尾松各组份生物量模型,并对模型进行拟合优度与误差分析,从中选用最优估测模型。为科学经营马尾松人工林,最大限度提高经济效益提供理论依据。     

基于无人机遥感的胡杨地上生物量估测模型构建

为了构建胡杨冠幅及地上生物量估测模型,在胡杨分布区设置的样地中选取328株样木,以无人机遥感数据提取的胡杨冠幅为自变量,以胡杨生物量模型获取的地上鲜生物量为因变量,通过相关及回归分析方法,构建不同函数形式的估测模型并进行精度分析。结果显示,墨玉县、巴楚县、轮台县,以无人机遥感估测胡杨生物量的最优模型均为三次曲线函数形式,精度分别为94.93%,95.63%,92.24%。研究确定了处于不同林龄胡杨样地的地上生物量的最优估测模型。可见,运用无人机遥感估测生物量是可行的,可为胡杨林的经营管理和生态价值评估提供技术支撑。     

海岸带复合农林业水杉林带生物量估测模型的研究

根据海岸带复合农林业不同立地类型（旱作田和水旱轮作田）水杉林带生物量的测定资料，建立了水杉林带树干、树枝、树叶、地上部分、地下部分及全株生物量模型。经择优分析，确认数学模型ｌｎｙ＝ａ＋ｂ．ｌｎｘ为水杉林中器官生物量的最优估测模型；以树冠体积（ｃ＾２ｈ）估测枝、叶量的效果好于对树干体积（Ｄ＾２Ｈ）的估测效果；其余器官生物量的估测则以Ｄ＾２Ｈ为佳。     

黄土丘陵区柠条生物量调查研究

通过对２９块柠条林的调查，分析了柠条生物量的分配规律及环境因子对地上部生物量的影响，分别建立了用环境因子和生长因子预测地上部生物量的回归模型。     

欧美杨人工幼林地上生物量估测方法的探讨

用欧美杨密度试验林中所选择的标准木和侧枝作材料，以侧枝和树干的长度及直径为观测指标，分别采用不同的数学模型和估侧方法拟合侧枝的叶片、枝条和枝叶总生物量及树干生物量回归估侧模型，并对不同的估测方法进行分析比较和检验。经筛选，叶片、枝条及枝叶总生物量的枝长指数模型和基径的幂函数模型拟合最好，树干生物量则以树干长度与直径相乘积的指数模型最优。不论侧枝分龄与否和树干分段与否，所建模型均能获得较精确的估测结果。以５株活立木１９９２～１９９４年生长量观测数据为资料进行实测检验，估测值与伐倒实测值之间，树冠生物量相对误差平均为４．３１％，各株树干的相对误差都小于５％，地上部分总生物量平均只差２．５２％。     

梭梭人工林地上生物量预测研究

梭梭是荒漠地区分布面积较大、生态效益显著、经济价值较高的植物种。本文选用梭梭的地径Ｄ、株高Ｈ、冠幅面积Ｇ，采用回归分析的方法建立起梭梭地上鲜重生物量的预测模型，用平均拟合率，Ｆ检验等方法，从三个预测模型中选出最优的一个预测模型作为梭梭人工林地上鲜重生物量预测模型：Ｗ＝０．００３２４Ｄ＾１．５１７Ｈ＾０．８３６Ｇ＾１．１１８该预测模型的拟合率达到８０．１２％，可用于预测梭梭人工林的地上部生物量，为梭     

Modeling compatible single-tree aboveground biomass equations for masson pine (Pinus massoniana) in southern China

Because of global climate change,it is necessary to add forest biomass estimation to national forest resource monitoring.The biomass equations developed for forest biomass estimation should be compatible with volume equations.Based on the tree volume and aboveground biomass data of Masson pine(Pinus massoniana Lamb.) in southern China,we constructed one-,two-and three-variable aboveground biomass equations and biomass conversion functions compatible with tree volume equations by using error-in-variable simultaneous equations.The prediction precision of aboveground biomass estimates from one variable equation exceeded 95%.The regressions of aboveground biomass equations were improved slightly when tree height and crown width were used together with diameter on breast height,although the contributions to regressions were statistically insignificant.For the biomass conversion function on one variable,the conversion factor decreased with increasing diameter,but for the conversion function on two variables,the conversion factor increased with increasing diameter but decreased with increasing tree height.     

自然生草桃园表层土壤水分和草地地上生物量的空间分布及其关系

【目的】阐明桃树果园短期自然生草条件下土壤水分空间分布特征及其与草地地上生物量的关系。【方法】以信阳沙壤土五月鲜桃园为研究对象,在冬春季短期自然生草条件下,采用1 m×1 m网格采样法,以经典统计学和地统计学半方差函数为工具,研究表层(0~5 cm)土壤水分和草地地上生物量空间分布特征。【结果】表层(0~5 cm)土壤含水量和地上草地生物量符合正态分布,平均体积含水量为10.08%,95%置信区间为9.84%~10.32%,变异系数为16.36%,0.2 m×0.2 m草地地上生物量均值为9.17 g,变异系数为56.71%。区域田块尺度上,自然生草桃园草地地上生物量和表层(0~5 cm)土壤水分空间分布均符合指数函数模型,模型块金值/基台值分别为0.477 3和0.499 8,变程分别为7.20和2.51。即二者均具有中等程度的空间依赖性,草地地上生物量较表层(0~5 cm)土壤含水量具有更强的空间依赖性。克里格插值结果表明,表层(0~5 cm)土壤含水量和草地地上生物量空间上呈斑块状分布,且表现为距离树体越远值越大的分布特征。相关分析结果表明,地上生物量与表层(0~5 cm)土壤含水量之间极显著正相关(P<0.001)。【结论】果园短期自然生草有利于保蓄表层土壤水分,改善土壤水分条件,草地地上生物量是影响果园表层土壤水分空间分布的重要因素。     

Integrated individual tree biomass simultaneous equations for two larch species in northeastern and northern China

Forest biomass estimation at large scale has become an important topic in the background of facing global climate change, and it is fundamental to develop individual tree biomass equations suitable for large-scale estimation. Based on the measured data of biomass components and stem volume from 100 sample trees of two larch species (Larix gmelinii and L. principis-rupprechtii) in northeastern and northern China, an integrated equation system including individual tree biomass equations, stem volume equation and height–diameter regression model were constructed using the dummy variable model and error-in-variable simultaneous equations. In the system, all the parameters of equations were estimated simultaneously, so that the aboveground biomass equation was compatible to stem volume equation and biomass conversion factor (B_CF) function; the belowground biomass equation was compatible to root-to-shoot ratio (R_SR) function; and stem wood, stem bark, branch and foliage biomass equations were additive to aboveground biomass equation. In addition, the system also ensured the compatibility between one- and two-variable models. The results showed that: (1) whether aboveground biomass equations or belowground biomass equations and stem volume equations, the estimates for larch in northeastern China were greater than those in northern China; (2) B_CF of a larch tree decreased with the growing diameter while R_SR increased with the growing diameter; (3) the proportion of stem wood biomass to aboveground biomass increased with the growing diameter while those of stem bark, branch, and foliage biomass decreased.     

多伦县退耕还林地林下植被地上生物量年变化及影响因子研究

根据内蒙古多伦县2005-2010年6年退耕还林地林下植被地上生物量与气候观测资料,对不同年际林下植被地上生物量变化以及与植被盖度、密度、高度、全年降水量等因子相关分析,建立了影响因子对林下植被地上生物量回归模型并进行预测分析.结果表明:不同年际退耕还林地林下植被地上生物量差异显著,生物量的变化随着退耕还林工程期的延长...     

岷江干旱河谷区峨眉蔷薇地上生物量及模型研究

岷江干旱河谷区是植被恢复困难地带,研究峨眉蔷薇生物量及模型,可对岷江干旱河谷区植被保护与恢复工作提供科学理论依据.研究结果表明:①不同径级的峨眉蔷薇各器官生物量分配大小,在阴阳坡均表现为干生物量>枝生物量>皮生物量>叶生物量,占比最大的主干部分对地上生物量总量贡献较大;②峨眉蔷薇对海拔梯度的响应,在阴阳坡均表现为中坡位...     

筇竹与黄皮树人工混交林中筇竹地上部分生物量模型构建

本研究以筇竹与黄皮树人工混交林中筇竹地上部分为研究对象,测定分析了1~4年生分株地上部分各构件生物量及含水率,建立人工筇竹分株地上部分各构件的生物量及总生物量模型,以期为人工筇竹林的经营管理及其碳汇项目的开发提供科学依据。结果表明：随着筇竹分株年龄的增加,各构件含水率和生物量均逐渐减少,筇竹1~4年生分株地上部分平均含水率分别为57.62%、53.40%、50.01%、42.66%,平均生物量分别为133.99、123.31、109.76、85.39 g/m²;各年龄分株地上部分生物量的分配均呈现出秆＞枝＞叶的变化规律。不同年龄分株的胸径与秆、枝、叶生物量及地上部分总生物量均有极显著相关性(P＜0.01)。以胸径为自变量建立的各年龄筇竹分株地上部分总生物量模型的决定系数(R²)均在0.93以上,具有较高的可信度,也有着较强的适用性,可用于类似立地条件下的筇竹分株生物量估测。     

Comparison on Estimation of Wood Biomass Using Forest Inventory Data

Based on sixth and seventh national forestry inventory data of the six provinces,including Guangdong,Jiangxi,Guizhou,Shaanxi,Jilin and Beijing,the three methods(IPCC,continuous function for biomass expansion factor and weighted biomass regression model) were selected to estimate wood biomass in this paper.The estimation of the three methods were compared and analyzed from calculating process,method characters,repeatability and verifiability to stability of growth rate of biomass between two periods.The results showed the total biomass estimated by IPCC method with variable BEF2 was large,the total biomass estimated by IPCC method with constant BEF2 was small and the total biomasses estimated by continuous function for biomass expansion factor and weighted biomass regression model were middle.The biomass expansion factor derived from weighted regression model was most stable in the different provinces. Based on the seventh national forestry inventory data, the biomass expansion factors of various kinds of tree species derived from IPCC and the weighted regression model were more stable than the biomass expansion factors derived from continuous function method.The growth rate of biomass between two periods was the same regular pattern as the biomass expansion factors.     

Developing individual tree-based models for estimating aboveground biomass of five key coniferous species in China

Estimating individual tree biomass is critical to forest carbon accounting and ecosystem service modeling. In this study, we developed one- (tree diameter only) and two-variable (tree diameter and height) biomass equations, biomass conversion factor (BCF) models, and an integrated simultaneous equation system (ISES) to estimate the aboveground biomass for five conifer species in China, i.e., Cunninghamia lanceolata (Lamb.) Hook., Pinus massoniana Lamb., P. yunnanensis Faranch, P. tabulaeformis Carr. and P. elliottii Engelm., based on the field measurement data of aboveground biomass and stem volumes from 1055 destructive sample trees across the country. We found that all three methods, including the one- and two-variable equations, could adequately estimate aboveground biomass with a mean prediction error less than 5%, except for Pinus yunnanensis which yielded an error of about 6%. The BCF method was slightly poorer than the biomass equation and the ISES methods. The average coefficients of determination (R ²) were 0.944, 0.938 and 0.943 and the mean prediction errors were 4.26, 4.49 and 4.29% for the biomass equation method, the BCF method and the ISES method, respectively. The ISES method was the best approach for estimating aboveground biomass, which not only had high accuracy but also could estimate stocking volumes simultaneously that was compatible with aboveground biomass. In addition, we found that it is possible to develop a species-invariant one-variable allometric model for estimating aboveground biomass of all the five coniferous species. The model had an exponent parameter of 7/3 and the intercept parameter a ₀ could be estimated indirectly from stem basic density (a ₀ = 0.294 ρ).     

湖南毛竹林生物量模型研究

为准确测算湖南省毛竹碳汇林的固碳能力,促进湖南省毛竹碳汇林业的均衡稳定发展,在湖南省毛竹主产区设置标准样地,并根据胸径、龄阶实测258株毛竹的生物量,用多元回归方法建立毛竹地上部分总生物量及其各器官生物量的一元(以胸径为自变量)、二元(以胸径和龄阶为自变量)模型。通过模型评价与检验,各模型均符合适用精度,具有适宜的预估水平。     

Estimating aboveground biomass of Pinus densata-dominated forests using Landsat time series and permanent sample plot data

Southwest China is one of three major forest regions in China and plays an important role in carbon sequestration.Accurate estimations of changes in aboveground biomass are critical for understanding forest carbon cycling and promoting climate change mitigation.Southwest China is characterized by complex topographic features and forest canopy structures,complicating methods for mapping aboveground biomass and its dynamics.The integration of continuous Landsat images and national forest inventory data provides an alternative approach to develop a long-term monitoring program of forest aboveground biomass dynamics.This study explores the development of a methodological framework using historical national forest inventory plot data and Landsat TM timeseries images.This method was formulated by comparing two parametric methods:Linear Regression for Multiple Independent Variables(MLR),and Partial Least Square Regression(PLSR);and two nonparametric methods:Random Forest(RF)and Gradient Boost Regression Tree(GBRT)based on the state of forest aboveground biomass and change models.The methodological framework mapped Pinus densata aboveground biomass and its changes over time in Shangri-la,Yunnan,China.Landsat images and national forest inventory data were acquired for 1987,1992,1997,2002 and 2007.The results show that:(1)correlation and homogeneity texture measures were able to characterize forest canopy structures,aboveground biomass and its dynamics;(2)GBRT and RF predicted Pinus densata aboveground biomass and its changes better than PLSR and MLR;(3)GBRT was the most reliable approach in the estimation of aboveground biomass and its changes;and,(4)the aboveground biomass change models showed a promising improvement of prediction accuracy.This study indicates that the combination of GBRT state and change models developed using temporal Landsat and national forest inventory data provides the potential for developing a methodological framework for the long-term mapping and monitoring program of forest aboveground biomass and its changes in Southwest China.