不同林分起源的相容性生物量模型构建

目前为止已有不同方法构建生物量相容性模型,但不同林分起源的生物量相容性模型很少报道。针对此问题,以150株南方马尾松(Pinus masson iana)地上生物量数据为例,利用比例平差法和非线性联立方程组法建立不同起源地上生物量以及干材、干皮、树枝和树叶各分项生物量相容的通用性模型。根据分配层次不同,两种方法又各自考虑总量直接控制和分级联合控制两种方案。从直径、树高、地径、枝下高和冠幅5个林分变量中选取不同的变量构建一元、二元和三元生物量模型,并利用加权最小二乘回归法消除生物量模型中存在的异方差性。结果为:比例平差法和非线性联立方程组法都能有效保证各分项生物量总和等于总生物量,模型预测精度满足要求。总体而言,非线性联立方程组方法比比例平差方法精度高,同时两种方法中总量直接控制法比分级联合控制法预测效果好;各分项生物量模型本身作为权函数能有效消除异方差;各分项对应的三元生物量模型预测精度最高,其次是二元生物量模型,最低是一元生物量模型,但这些差异不是很大。总之,为权衡考虑模型预测精度和调查成本,建议把直径和树高作为协变量利用总量直接控制非线性联立方程组法对不同起源生物量建模。     

两种相容性生物量模型的比较——以广东省3个阔叶树种为例

基于广东省樟树、木荷和枫香3个阔叶树种共270株样木的生物量实测数据,采用多元非线性联合估计,按分量相加和总量控制两种方法,分别构建了一元(胸径)和二元(胸径、树高和胸径、冠幅)的相容性生物量模型,比较分析了这两种相容性生物量模型的拟合效果和预估精度。结果表明:(1)分量相加和总量控制构建相容性模型对3个树种拟合效果均较好,预估精度均较高,二者之间差别不大,但总体上分量相加模型拟合效果较优。(2)二元模型拟合效果和预估精度普遍优于一元模型,但加入第二个变量的异同,在各个分量中的表现不一。加入树高因子,显著改进树干和树皮的拟合效果;加入冠幅因子,显著改进树枝、树叶和地上部分的拟合效果。选择胸径和冠幅因子建立二元生物量模型可以获得较高的拟合精度。(3)基于最优独立模型构建的相容性模型拟合和预估效果最优,地上部分总量甚至优于最优独立模型。因此,各分量相加构建的相容性模型略优于总量控制。对于阔叶树种自变量的选取,二元模型加入冠幅因子的精度高于加入树高因子。     

天然云杉相容性生物量估算模型

基于150株天然云杉实测材积和生物量数据,利用非线性度量误差方法,建立相容性立木材积与生物量方程,并采用总量直接控制方案和分级联合控制方案研建了地上总生物量与4个分项(干材、干皮、树枝、树叶)的相容性方程系统,其中又采取了独立估计和联合估计两种处理方法进行地上生物量的估计.结果表明: 所建一元、二元相容性立木材积和地上生物量模型的材积和生物量决定系数均在0.85以上,最高达0.99,在胸径基础上增加树高变量能显著提高材积的预估效果,但对生物量的预估效果改进不大.就总量与分量相容性模型而言,分级联合控制方案所建的一元模型好于总量直接控制所建的一元模型,两种方案所建的二元模型效果相当.对一元、二元相容性生物量模型的拟合效果进行对比,结果显示,解释变量的增加明显提高了树枝和树叶生物量的拟合效果,对其他几个分量的拟合效果改善不大.对独立估计和联合估计的对比分析显示,两种估计方法几乎没有差异.     

基于森林调查数据的长白山天然林森林生物量相容性模型

森林生物量估算是进行陆地生态系统碳循环和碳动态分析的基础,但现有估测模型存在着总量与分量不相容的问题.本文以吉林省汪清天然林区为例,提出了基于森林调查的相容性森林生物量模型设计思想,并采用联立方程组为不同森林群落构造了一系列引入林分蓄积因子的相容性生物量模型,得到的预估精度较高.其中,针叶林、阔叶林和针阔混交林群落的森林生物量模型预估精度均在95%以上,基本上解决了森林生物量模型的相容性问题.     

人工神经网络与相容性生物量模型预测单木地上生物量的比较

森林生物量是林业生产经营和森林资源监测的重要指标,为探索高效低偏的单木生物量估测方法,引入人工神经网络.本研究采用黑龙江省东折棱河林场的101株长白落叶松地上生物量数据,基于不同变量(胸径、树高、冠幅)组合建立了4个聚合模型体系(AMS),采用加权回归消除模型的异方差.然后,基于最优的变量组合建立人工神经网络(ANN)...     

广西主要树种(组)异速生长模型及森林生物量特征

基于广西11类主要树种(组)5个龄组(245株样木、345块样地)的生物量实测调查,建立了各树种(组)的生物量优化异速生长模型,探讨广西森林生态系统总生物量及不同森林类型、不同龄组、不同层次的生物量组成与分配。结果表明:(1)广西11类树种(组)叶、枝、干、根、全株生物量(除了杉树叶、桉树叶生物量)、地上-地下、胸径-树高的优化回归模型均为幂函数,经t检验均达到显著水平(P0.05),其中11类树种(组)以全株生物量的模拟效果最好;(2)广西森林总生物量为1425.37 Tg,平均生物量为105.36 Mg/hm2,各森林类型总生物量为松树林(366.14 Tg)硬阔(291.08 Tg)软阔(239.75 Tg)石山林(165.51 Tg)杉木林(164.01 Tg)桉树林(99.55 Tg)栎类(46.34 Tg)八角林(20.21 Tg)油茶林(19.59 Tg)竹林(13.19 Tg),均随年龄的增加而增加,各层次生物量均以乔木层占绝对优势,所占比例为78.30%—97.47%,各龄组地上生物量均大于地下生物量;(3)考虑统计学与实际应用之间的平衡及异速生长模型的可解释量、回归系数的显著性,以胸径为变量的生物量模型能有效估算广西主要树种(组)各器官及总生物量;(4)优化筛选的广西各树种(组)的地上-地下优化异速生长模型及推算的地上-地下生物量比,对于估计广西森林地下生物量具有重要参考价值。     

上海两种常绿阔叶树种生物量分配及异速生长模型

选取香樟(Cinnamomum camphora)和广玉兰(Magnolia grandiflora)两种上海代表性树种作为研究对象,采用整株收获法获取两种树种主要测树因子和地上各组分生物量,分析生物量分配格局,采用非线性方程,探讨最佳生物量异速生长模型和预测变量。结果表明:(1)香樟和广玉兰树种地上生物量分配表现为干枝叶。树叶、树枝、树干生物量分别占地上整株生物量的17.88%和27.31%、30.48%和27.93%、51.64%和44.76%,广玉兰叶和枝的生物量相对比例差异不显著。(2)基于胸径、高度、冠幅3个变量,建立了9种异速生物量模型,通过方程拟合优度进行评价,香樟叶、枝、干和地上整株生物量分别以模型8、模型3、模型4和模型7拟合效果最好;广玉兰则分别以模型4、模型9、模型2和模型4拟合为好。鉴于树木高度和冠幅的不易获得性,在综合考虑模型拟合优度和适应性的基础上,实际应用中需选择既实用又符合精度要求的模型。     

臭冷杉生物量分配格局及异速生长模型

摘 要：臭冷杉是长白山阔叶红松林中重要针叶树种,采用整株收获法分析21株臭冷杉地上地下生物量分配格局。在枝条水平上采用样枝直径（BD）、样枝长度（BL）、样枝所在轮生枝位置（WP）建立活枝、针叶生物量异速生长模型,在植株水平上采用胸径（DBH）、树高（H）、年龄（Age）、树冠长度（CL）、树冠比率（CR）、南北向冠幅（CW1）、东西向冠幅（CW2）等变量建立树干木质、树皮、活枝、针叶、粗根及整株生物量模型。并利用逐步线性回归法获得不同器官生物量最优模型。结果表明：（1）活枝生物量主要集中在树冠中下层,针叶生物量集中在树冠中层。树冠中层和下层枝叶生物量无显著差异（p>0.05）;（2）21株臭冷杉地上生物量和地下生物量变动范围分别为1.026–506.047 kg/株和0.241–112.000 kg/株。粗根、活枝、针叶、树干木质、树皮及枯枝生物量占整株生物量的相对比例分别为18.68%、18.39%、12.02%、39.29%、8.70%和2.92%;（3）地上生物量与地下生物量呈显著线性相关（p<0.001）,拟合线性方程斜率为0.23;（4）枝条水平上,活枝生物量模型解释量超过95%,平均预测误差小于30%。与单变量（BD）活枝生物量模型相比,2变量（BD、BL）和3变量（BD、BL、WP）模型解释量分别提高1.2%和2.0%,平均预测误差分别下降6.26%和9.27%。针叶生物量相对较难预测,模型解释量仅为82.7%,平均预测误差接近50%,模型中增加BL 和WP变量并未提高针叶生物量的预测精度。活枝生物量与BD、BL、WP正相关,针叶生物量与BD正相关,与BL、WP负相关;（5）植株水平上,基于胸径的单变量模型可解释量大于90%,增加树高变量未能显著提高生物量模型的预测精度。年龄决定了臭冷杉的树干生物量,忽视年龄变量将会产生生物量预测误差。树冠特征是影响枝叶生物量预测精度的重要变量。综合考虑模型的可解释量及回归系数显著性可知,胸径是预测臭冷杉不同器官生物量的可靠变量。     

基于不同预测变量的天然椴树可加性地上生物量模型构建

森林生物量是森林生态系统的最基本数量特征,生物量数据是研究许多林业问题和生态问题的基础,因此,准确测定生物量对于计算碳储量以及研究气候变化、森林健康、森林生产力、养分循环等十分重要.目前,测算森林生物量常用的方法为生物量模型估算法.本研究基于小兴安岭地区和张广才岭地区97株实测生物量数据,建立了3个天然椴树立木可加性生物量模型系统(基于胸径的一元可加性生物量模型系统、基于胸径和树高的二元可加性生物量模型系统、基于最优变量的最优可加性生物量模型系统),采用非线性似乎不相关回归法进行参数估计,用加权方法解决模型的异方差问题,并采用“刀切法”进行模型检验.结果表明: 3种可加性生物量模型系统均能较好地对椴树各部分生物量进行拟合和预测(调整后确定系数R_a²>0.84,平均预测误差百分比MPE<8.5%,平均绝对误差MAE<16.3 kg,平均百分标准误差MPSE<28.5%),其中,树干和地上生物量的拟合效果优于树叶、树枝和树冠;在引入树高和树冠因子后,提高了模型的拟合效果和预测能力(R_a²提高0.01～0.04,MAE降低0.01～4.55 kg),缩小了预测值置信区间的范围,树干、树叶和地上生物量提高较多,树枝和树冠提高较少.总体来看,最优生物量模型系统效果最好,其次为二元生物量模型系统,再次是一元生物量模型系统,添加树高和树冠因子进行生物量模型的构建十分必要.     

基于森林调查数据的长白山天然林森林生物量相容性模型

森林生物量估算是进行陆地生态系统碳循环和碳动态分析的基础,但现有估测模型存在着总量与分量不相容的问题.本文以吉林省汪清天然林区为例,提出了基于森林调查的相容性森林生物量模型设计思想,并采用联立方程组为不同森林群落构造了一系列引入林分蓄积因子的相容性生物量模型,得到的预估精度较高.其中,针叶林、阔叶林和针阔混交林群落的森林生物量模型预估精度均在95%以上,基本上解决了森林生物量模型的相容性问题.     

Validating Community-Led Forest Biomass Assessments

The lack of capacity to monitor forest carbon stocks in developing countries is undermining global efforts to reduce carbon emissions. Involving local people in monitoring forest carbon stocks could potentially address this capacity gap. This study conducts a complete expert remeasurement of community-led biomass inventories in remote tropical forests of Papua New Guinea. By fully remeasuring and isolating the effects of 4,481 field measurements, we demonstrate that programmes employing local people (non-experts) can produce forest monitoring data as reliable as those produced by scientists (experts). Overall, non-experts reported lower biomass estimates by an average of 9.1%, equivalent to 55.2 fewer tonnes of biomass ha^-1, which could have important financial implications for communities. However, there were no significant differences between forest biomass estimates of expert and non-expert, nor were there significant differences in some of the components used to calculate these estimates, such as tree diameter at breast height (DBH), tree counts and plot surface area, but were significant differences between tree heights. At the landscape level, the greatest biomass discrepancies resulted from height measurements (41%) and, unexpectedly, a few large missing trees contributing to a third of the overall discrepancies. We show that 85% of the biomass discrepancies at the tree level were caused by measurement taken on large trees (DBH ≥50cm), even though they consisted of only 14% of the stems. We demonstrate that programmes that engage local people can provide high-quality forest carbon data that could help overcome barriers to reducing forest carbon emissions in developing countries. Nonetheless, community-based monitoring programmes should prioritise reducing errors in the field that lead to the most important discrepancies, notably; overcoming challenges to accurately measure large trees.     

Allometric equations for integrating remote sensing imagery into forest monitoring programmes

Remote sensing is revolutionizing the way we study forests, and recent technological advances mean we are now able – for the first time – to identify and measure the crown dimensions of individual trees from airborne imagery. Yet to make full use of these data for quantifying forest carbon stocks and dynamics, a new generation of allometric tools which have tree height and crown size at their centre are needed. Here, we compile a global database of 108753 trees for which stem diameter, height and crown diameter have all been measured, including 2395 trees harvested to measure aboveground biomass. Using this database, we develop general allometric models for estimating both the diameter and aboveground biomass of trees from attributes which can be remotely sensed – specifically height and crown diameter. We show that tree height and crown diameter jointly quantify the aboveground biomass of individual trees and find that a single equation predicts stem diameter from these two variables across the world's forests. These new allometric models provide an intuitive way of integrating remote sensing imagery into large‐scale forest monitoring programmes and will be of key importance for parameterizing the next generation of dynamic vegetation models.     

岷江上游亚高山林区老龄林地上生物量动态变化

中国川西亚高山森林中的天然林大部分为成过熟的老龄林,对其生物量动态研究有助于了解其碳储量的动态变化规律.利用全国森林资源连续清查的27个固定样地数据,基于地上各器官生物量与树干胸径(D)和树高(h)的异速生长方程,估算了岷江上游亚高林山老龄林地上生物量密度的动态变化特征及其时空变化规律.结果表明,(1)从1988～2002年期间,老龄林地上生物量密度净增量为(27.311±15.580)Mg·hm-2,平均每年增长率为(1.930±1.091 )Mg·hm-2·a-1,平均每年枯损率为(2 271±1.424)Mg·hm-2·a-1;(2)地上生物量变化受各径级保留木生长量、枯损量及进界生长量影响,其中20～40cm径级保留木生长量与生物量净增量最大,>80cm径级生物量增量最小,40～60cm和60～80cm径级生物量在调查期间净增量出现负增长.(3)岷江上游老龄林地上生物量动态变化具有时空异质性,同一样地在不同调查间隔期或同一调查期间不同样地间生物量变化不同,不仅有增量数值大小差异,还表现为生物量增量的正负差异.     

Estimation of stem and tree level biomass models for Prosopis juliflora/pallida applicable to multi-stemmed tree species

The aim of this paper is to develop biomass models for commonly multi-stemmed Prosopis juliflora/pallida trees. The data were collected on three of the Cape Verde islands (Maio, Santiago and Santo Antao). The dataset covers 240 trees containing 1,882 stems with stem diameter at breast height over 2 cm; of that 255 individual tree stems were sampled destructively. These calibration data were used to construct stem and tree-level models for estimation of total aboveground biomass and its fine and course fractions with diameter threshold of 5 cm. A set of parameterized biomass models for multi-stemmed Prosopis spp. trees suited for biomass estimation at tree and stem levels using appropriate set of independent variables, commonly available in forest inventory programs, was created. The effect of site (island) on tree allometry was not detected. The two-phase construction of tree biomass models based on destructive sampling limited to individual stems combined with a routine field measurement of entire multi-stemmed tree specimen represents a practicable approach leading to biomass and carbon assessment that may be generally suited for tree species with complex multi-stemmed growth form similar to that of Prosopis spp.     

Estimating Canopy Structure in an Amazon Forest from Laser Range Finder and IKONOS Satellite Observations1

Canopy structural data can be used for biomass estimation and studies of carbon cycling, disturbance, energy balance, and hydrological processes in tropical forest ecosystems. Scarce information on canopy dimensions reflects the difficulties associated with measuring crown height, width, depth, and area in tall, humid tropical forests. New field and spaceborne observations provide an opportunity to acquire these measurements, but the accuracy and reliability of the methods are unknown. We used a handheld laser range finder to estimate tree crown height, diameter, and depth in a lowland tropical forest in the eastern Amazon, Brazil, for a sampling of 300 trees stratified by diameter at breast height (DBH). We found significant relationships between DBH and both tree height and crown diameter derived from the laser measurements. We also quantified changes in crown shape between tree height classes, finding a significant but weak positive trend between crown depth and width. We then compared the field‐based measurements of crown diameter and area to estimates derived manually from panchromatic 0.8 m spatial resolution IKONOS satellite imagery. Median crown diameter derived from satellite observations was 78 percent greater than that derived from field‐based laser measurements. The statistical distribution of crown diameters from IKONOS was biased toward larger trees, probably due to merging of smaller tree crowns, underestimation of understory trees, and overestimation of individual crown dimensions. The median crown area derived from IKONOS was 65 percent higher than the value modeled from field‐based measurements. We conclude that manual interpretation of IKONOS satellite data did not accurately estimate distributions of tree crown dimensions in a tall tropical forest of eastern Amazonia. Other methods will be needed to more accurately estimate crown dimensions from high spatial resolution satellite imagery.     

How to map forest structure from aircraft,one tree at a time

Forest structure is strongly related to forest ecology, and it is a key parameter to understand ecosystem processes and services. Airborne laser scanning (ALS) is becoming an important tool in environmental mapping. It is increasingly common to collect ALS data at high enough point density to recognize individual tree crowns (ITCs) allowing analyses to move beyond classical stand‐level approaches. In this study, an effective and simple method to map ITCs, and their stem diameter and aboveground biomass (AGB) is presented. ALS data were used to delineate ITCs and to extract ITCs’ height and crown diameter; then, using newly developed allometries, the ITCs’ diameter at breast height (DBH) and AGB were predicted. Gini coefficient of DBHs was also predicted and mapped aggregating ITCs predictions. Two datasets from spruce dominated temperate forests were considered: one was used to develop the allometric models, while the second was used to validate the methodology. The proposed approach provides accurate predictions of individual DBH and AGB (R² = .85 and .78, respectively) and of tree size distributions. The proposed method had a higher generalization ability compared to a standard area‐based method, in particular for the prediction of the Gini coefficient of DBHs. The delineation method used detected more than 50% of the trees with DBH >10 cm. The detection rate was particularly low for trees with DBH below 10 cm, but they represent a small amount of the total biomass. The Gini coefficient of the DBH distribution was predicted at plot level with R² = .46. The approach described in this work, easy applicable in different forested areas, is an important development of the traditional area‐based remote sensing tools and can be applied for more detailed analysis of forest ecology and dynamics.