西非Sudanian热带林地11个树种地上生物量异速生长预测

Allometric models are necessary for estimating biomass in terrestrial ecosystems. Generalized allometric relationship exists for many tropical trees, but species- and region-specific models are often lacking. We developed species-specific allometric models to predict aboveground biomass for 11 native tree species of the Sudanian savanna-woodlands. Diameters at the base and at breast height, with species means ranging respectively from 11 to 28 cm and 9 to 19 cm, and the height of the trees were used as predictor variables. Sampled trees spanned a wide range of sizes including the largest sizes these species can reach. As a response variable, the biomass of the trees was obtained through destructive sampling of 4 754 trees during wood harvesting. We used a stepwise multiple regression analysis with backward elimination procedure to develop models separately predicting, total biomass of the trees, stem biomass, and biomass of branches and twigs. All species-specific regression models relating biomass with measured tree dimensions were highly significant (p < 0.001). The biomass of branches and twigs was less predictable compared to stem biomass and total biomass, although their models required fewer predictors and predictor interactions. The best-fit equations for total above-ground biomass and stem biomass had R ² > 0.70, except for the Acacia species; for branches including twig biomass, R²-values varied from 0.749 for Anogeissus leiocarpa to 0.183 for Acacia macrostachya. The use of these equations in estimating available biomass will avoid destructive sampling, and aid in planning for sustainable use of these species.     

Allometric models for estimating aboveground biomass of shade trees and coffee bushes grown together

Allometric models for dominant shade tree species and coffee plants (Coffea arabica) were developed for coffee agroforestry systems in Matagalpa, Nicaragua. The studied shade tree species were Cordia alliodora, Juglans olanchana, Inga tonduzzi and I. punctata. The models predict aboveground biomass based on diameter at breast height (for trees), and the stem diameter at a height of 15 cm and plant height (for coffee plants). In addition, the specific gravity of the studied species was determined.The total aboveground biomass of the shade trees varied between 3.5 and 386 kg per tree, and between 0.005 and 2.8 kg per plant for coffee. The aboveground biomass components (foliage, branch, and stem) are closely related with diameter at breast height (r > 0.75). The best-fit models for aboveground biomass of the shade trees were logarithmic, with adjusted R ² between 0.71 and 0.97. In coffee plants, a high correlation was found (r = 0.84) with the stem diameter at 15 cm height, and the best-fit model was logarithmic, as well. The mean specific gravity was 0.52 (± 0.11) for trees and 0.82 (± 0.06) for coffee plants.     

Coarse root biomass and architecture of hybrid aspen ‘Crandon’ (Populus alba L. × P. grandidenta Michx.) grown in an agroforestry system in central Iowa,USA

In this study, we evaluated ‘Crandon’ coarse root biomass and architecture grown at different topographic positions and fertilizer rates. Complete excavations were conducted on a subset of trees after the first growing season and showed that root biomass was strongly related to stem biomass (R² = 0.93), but not topographic position or fertilizer rate. After the third growing season, subsamples of roots were collected from another subset of trees and showed coarse root architecture variables to be strongly related to several metrics of the tree and root size (R² = 0.61 to 0.82), while also differing by topographic position. Equations relating root biomass to stem biomass were derived from both methodologies (complete excavation v. subsampling for architecture measurements), and comparison of the equations indicated no difference in slopes (p = 0.59) or intercepts (p = 0.90), although the subsampling approach had a weaker model fit. Our results suggest ‘Crandon’ roots (i) adhere to strong allometric relationships with stem biomass, (ii) alter their architecture within the constraints of this allometric relationship according to site conditions, and (iii) can be subsampled to estimate root biomass from root architecture parameters with similar accuracy (but less precision) compared to complete excavations.     

基于树高和树冠因子的立木材积模型研究

[目的]由于激光雷达技术已经能准确测定立木树高及相关树冠因子,应用该技术建立基于树高和树冠因子的立木材积模型,为激光技术在森林蓄积估计中提供技术支撑.[方法]利用云杉、冷杉、栎树、桦树4个树种组的3 010株实测样木数据,分析了立木材积与胸径、树高、树冠因子之间的相关关系;并通过对数回归方法构建了基于树高和树冠因子的立木材积模型,用确定系数R²和平均预估误差MPE等6项指标对模型进行评价.[结果]表明,立木材积与单一因子之间的相关,以胸径最为紧密,其次是树高,再次是冠长和冠幅.基于树高和树冠因子的立木材积模型中,以树高和冠幅作为解释变量的二元模型效果较好,再增加冠长因子的三元模型改进不大.云杉、冷杉、栎树、桦树4个树种组基于树高冠幅的立木材积模型,其R²分别为0.81、0.80、0.76和0.77,MPE分别为4.7%、5.3%、5.4%和5.3%,模型预估精度均能达到95%左右.[结论]本文对材积与林木因子之间相关关系的定量分析,建立了云杉、冷杉、栎树、桦树4个树种的立木材积模型,模型预估精度高.为激光雷达技术定量估测森林参数提供了依据.     

Models for estimation of carbon sequestered by Cupressus lusitanica plantation stands at Wondo Genet,Ethiopia

This study compared models for estimating carbon sequestered aboveground in Cupressus lusitanica plantation stands at Wondo Genet College of Forestry and Natural Resources, Ethiopia. Relationships of carbon storage with tree component and stand age were also investigated. Thirty trees of three different ages (5, 12 and 24 years), comprising 10 trees from each stand, were sampled in order to generate dry biomass and carbon data from tree components. Five linear and non-linear biomass and carbon models were compared and evaluated for estimation of overall aboveground carbon, carbon by age groups, and carbon by diameter at breast height (DBH) classes using performance indicator statistics. Among the models compared, a carbon model described by Y = b ₀ D ² H + ? (p-value < 0.001), where D = DBH (in cm), H = total height of the tree (in m), ? = error, and b ₀ is a parameter, was found to be the best model for estimation of carbon sequestered aboveground in C. lusitanica plantation stands of the study area. The study also indicated the overall superiority of carbon models over biomass models in estimation of aboveground carbon of C. lusitanica. It was concluded that, for the range of DBH utilised in the current study, the carbon model described can be a useful tool in estimation of carbon storage of C. lusitanica plantations in the study area and other related sites.     

Allometric equations from a non-destructive approach for biomass prediction in natural forest and plantation in West Africa

Allometric equations are required for a rapid estimation of commercial timber volume and forest biomass stocks. In order to preserve the forest ecosystem, this study applied a non-destructive sampling approach to measure biophysical properties of living trees. From these measurements, volume and biomass models were developed for 11 dominant tree species in a semi-deciduous natural forest and for Acacia auriculiformis in a plantation located in southern Benin. The observations were combined to develop also generic models applicable to non-dominant tree species. Wood samples of the tree species were collected with an increment borer and analysed in the laboratory to determine species-specific wood densities. The sample size was composed of 243 trees in natural forest and 21 trees in plantation. The measurements were conducted in 30 plots of 50 m × 50 m. The graphical assessment of correlation between model outputs (biomass and volume) and variables (diameter and height) and the statistical analysis confirmed that the logarithmic model with two variables had the best predictions. The assessment also confirmed that the model using diameter only as a variable had good predictions when observations on height were unavailable. The comparative analysis of model predictions showed that the generic model in this study over-estimated biomass by up to 74.80% for certain species and under-estimated biomass by 21.18% for other species. The study shows that there are no statistically significant differences between the wood densities in this research and that published in previous studies.     

Allometric relationship for estimating above-ground biomass of Aegialitis rotundifolia Roxb. of Sundarbans mangrove forest, in Bangladesh

Tree biomass plays a key role in sustainable management by providing different aspects of ecosystem. Estimation of above ground biomass by non-destructive means requires the development of allometric equations. Most researchers used DBH (diameter at breast height) and TH (total height) to develop allometric equation for a tree. Very few species-specific allometric equations are currently available for shrubs to estimate of biomass from measured plant attributes. Therefore, we used some of readily measurable variables to develop allometric equations such as girth at collar-height (GCH) and height of girth measuring point (GMH) with total height (TH) for A. rotundifolia, a mangrove species of Sundarbans of Bangladesh, as it is too dwarf to take DBH and too irregular in base to take Girth at a fixed height. Linear, non-linear and logarithmic regression techniques were tried to determine the best regression model to estimate the above-ground biomass of stem, branch and leaf. A total of 186 regression equations were generated from the combination of independent variables. Best fit regression equations were determined by examining co-efficient of determination (R2), co-efficient of variation (CV), mean-square of the error (MSerror), residual mean error (Rsme), and F-value. Multiple linear regression models showed more efficient over other types of regression equation. The performance of regression equations was increased by inclusion of GMH as an independent variable along with total height and GCH.     

Equations for estimating the above-ground biomass of Larix sibirica in the forest-steppe of Mongolia

Biomass functions were established to estimate above-ground biomass of Siberian larch (Larix sibirica) in the Altai Mountains of Mongolia. The functions are based on biomass sampling of trees from 18 different sites, which represent the driest locations within the natural range of L. sibirica. The best performing regression model was found for the equations y = (D ² H)/(a+bD) for stem biomass, y = aD ^b for branch biomass, and y=aD ^b H ^c for needle biomass, where D is the stem diameter at breast height and H is the tree height. The robustness of the biomass functions is assessed by comparison with equations which had been previously published from a plantation in Iceland. There, y=aD ^b H ^c was found to be the most significant model for stem and total above-ground biomasses. Applying the equations from Iceland for estimating the above-ground biomass of trees from Mongolia resulted in the underestimation of the biomass in large-diameter trees and the overestimation of the biomass in thin trees. The underestimation of thick-stemmed trees is probably attributable to the higher wood density, which has to be expected under the ultracontinental climate of Mongolia compared to the euoceanic climate of Iceland. The overestimation of the biomass in trees with low stem diameter is probably due to the high density of young growth in the not systematically managed forests of the Mongolian Altai Mountains, which inhibits branching, whereas the plantations in Iceland are likely to have been planted in lower densities.     

Allometric models for predicting above- and belowground biomass of <Emphasis Type="Italic">Leucaena</Emphasis>-KX2 in a shaded coffee agroecosystem in Hawaii

We developed site-specific allometric models for Leucaena leucocephala × pallida var. KX2 trees in a shaded coffee agroecosystem in Hawaii to predict above- and belowground biomass and the regrowth potential of pollarded trees. Models were used to compare tree growth rates in an experimental agroforestry system with different pollarding frequencies and additions of tree pruning residues as mulch. For all allometric equations, a simple power model (Y = aX^b) provided the optimal prediction of biomass or regrowth after pollarding. For aboveground biomass components (stem, branches, leaves, and seed and pods), stem diameter alone was the best predictor variable. Stump diameter provided the best prediction of coarse root biomass and aboveground regrowth after pollarding. Predictions of biomass from generalized allometric models often fell outside the 95% confidence intervals of our site-specific models, especially as biomass increased. The combination of pollarding trees once per year plus the addition of tree mulch resulted in the greatest aboveground regrowth rates as well as accumulation of biomass and C in the stump plus coarse roots. Although optimal prediction required the development of site-specific allometric relationships, a simple power model using stem or stump diameter alone can provide an accurate assessment of above- and belowground tree biomass, as well as regrowth potential under specific management scenarios.     

Functions for Biomass Estimation of Young Pinus sylvestris,Picea abies and Betula spp. from Stands in Northern Sweden with High Stand Densities

New silvicultural regimes with high within-stand competition require new functions for estimation of standing stock and growth of biomass components, since the allometry of trees is changed by light competition. This paper presents functions for estimation of the aboveground biomass dry weights for stem wood, stem bark, branches and leaves of young (diameter at breast height <10 cm) Scots pine (Pinus sylvestris L.), Norway spruce [Picea abies (L.) Karst.] and birch (Betula pendula Roth. and Betula pubescens Ehrh.) trees growing in dense mixed stands. The functions were derived from a sample consisting of 84 Scots pine, 43 Norway spruce and 66 birch trees from six stands in northern Sweden with high stand densities (>10000 st ha^-1). The logarithmically transformed power function displayed a good ability to stabilize the variance of dry weights and showed a good fit to the material (0.37< R ² <0.99). A comparison with the most commonly used biomass functions in Sweden today showed that they overestimated the weight of stem wood and branches, while the weight of foliage was underestimated. The nature of these discrepancies suggested that the precision of biomass estimations might also be improved for young trees at wider spacing.     

思茅松天然林单木生物量地理加权回归模型构建

通过调查云南省思茅区思茅松天然林63株思茅松单木的地上部分干、枝、叶生物量数据,并测定其中30株的根系生物量数据。基于普通最小二乘模型选型,采用地理加权回归的方法构建思茅松单木树干生物量、树枝生物量、树叶生物量和地上部分生物量,以及根系生物量和整株生物量模型。结果表明:(1)地理加权回归模型(GWR)的决定系数(R2)大于普通最小二乘(OLS)模型,且GWR模型拟合的R2值除树叶生物量模型外,其余生物量维量模型均大于0.950;Akaike信息指数(AIC)值小于普通最小二乘(OLS)模型,平均相对误差(EE)和平均相对误差绝对值(RMA)的绝对值除树枝生物量外均小于OLS模型,说明GWR模型拟合效果优于OLS模型;(2)地理加权回归模型拟合在一定程度上克服了OLS在拟合生物量模型中存在的异方差问题。     

A forest biomass yield table based on an empirical model

We report an empirical model for estimating unutilized wood biomass, and its application to Cryptomeria japonica D. Don and Larix kaempferi in Tohno City, Iwate Prefecture, northeast Japan. Outputs from the model are the quantity of unutilized wood biomass and merchantable volume produced by timber harvest. The unutilized wood biomass is divided into stumps, tops, branches, foliages, small trees, and unutilized stems due to their defects. Inputs to the model are mean diameter at breast height (DBH), mean tree height, trees per unit area, and timber utilization standards. DBH distribution, DBH–height curve, stem form, bark thickness, and relationship of stem biomass to foliage and branch biomass could be described by the proposed model, indicating its validity. The proposed model enables us to develop the forest biomass yield tables modified from the existing stem volume yield tables. The developed forest biomass yield tables indicated that the unutilized wood biomass due to defects accounted for the largest part of the whole unutilized wood biomass, and that the ratio of unutilized parts in stem volume to total stem volume could vary with stand age and site productivity class. Based on a comparison of the developed forest biomass yield tables with those reported previously, we concluded that the proposed model-based forest biomass yield table would be useful for estimating the quantity of unutilized wood biomass.     

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.     

Trends in allometric models and aboveground biomass of family Rhizophoraceae mangroves in the Coral Triangle ecoregion,Southeast Sulawesi,Indonesia

This study aims to establish allometric models and estimate aboveground biomass (AGB) of mangroves Rhizophoraceae in the Southeast Sulawesi, Indonesia. Allometric models of the AGB of mangroves Rhizophora apiculata, R. mucronata, and Ceriops tagal were established using independent variables consisting stem diameter at 30 cm from the ground (D₃₀), diameter at breast height (DBH), D₃₀²H and DBH²H. The AGB of mangroves was estimated by applying allometric model and tree census. The results showed that the best fitting allometric models of AGB for R. apiculata is based on variable DBH, while DBH²H is the best variable for R. mucronata trees. Conversely, the D₃₀ is the best variable for estimating AGB of C. tagal trees. Thus, there is some variation of independent variables on allometric models for the estimation of AGB for Rhizophoraceae mangroves. The AGB (ton ha^?1) of R. apiculata, R. mucronata, and C. tagal was estimated respective 651.60, 232.11 and 154.56 in the protected area, and respective 137.59, 189.35 and 39.06 ton ha^?1 in the unprotected area. Higher AGB of mangroves growing in the protected area indicated the suitable condition and undisturbed by human activities. The conservation of mangroves is necessary for the sustainability of mangroves and coastal ecosystems in the Coral Triangle ecoregion.     

An evaluation of the conical approximation as a generic model for estimating stem volume, biomass and nutrient content in young Eucalyptus plantations

Accurately and non-destructively quantifying the volume, mass or nutrient content of tree components is fundamental for assessing the impact of site, treatment, and climate on biomass, carbon sequestration, and nutrient uptake of a growing plantation. Typically, this has involved the application of allometric equations utilising diameter and height, but for accurate results, these equations are often specific to species, site, and silvicultural treatment. In this study, we assessed the value of incorporating a third piece of information: the height of diameter measurement. We derived a more general volume equation, based on the conical approximation, using a diameter projected to the base of the tree. Common equations were developed which allowed an accurate estimate of stem volume, dry weight and nutrient content across two key plantation grown eucalypt species, Eucalyptus grandis W. Hill ex Maiden and Eucalyptus globulus (Labill.). The conical model was developed with plantation-grown E. grandis trees ranging from 0.28 to 15.85 m in height (1.05 g to 80.3 kg stem wood dry weight), and E. globulus trees ranging from 0.10 to 34.4 m in height (stem wood dry weight from 0.48 g to 652 kg), grown under a range of contrasting cultural treatments, including spacing (E. grandis), site (E. globulus) and fertilization (nitrogen and phosphorus) for both species. With log transformed data the conical function (V_con) was closely related to stem sectional volume over bark and stem weight (R² = 0.996 and 0.990, respectively) for both E. grandis and E. globulus, and the same regressions can be applied to both species. Back transformed data compared with the original data yielded modelling efficiencies of 0.99 and 0.97, respectively. Relationships between V_con and bark dry weight differed for the two species, reflecting differing bark characteristics. Young trees with juvenile foliage had a different form of relationship to older trees with intermediate or adult foliage, the change of slope corresponding to heights about 1.5 m for E. grandis and age 1 year for E. globulus. The V_con model proved to be robust, and unlike conventional models, does not need additional parameters for estimating biomass under different cultural treatments. More than 99% of the statistical variance of the logarithm of biomass was accounted for in the model. V_con captures most of the change in stem taper associated with cultural treatments and some of the change in stem form that occurs after the crown base has lifted appreciably. Fertilization increased N and P concentrations in stem wood and bark, and regressions to estimate N and P contents (the products of biomass and concentration) were dependent on treatment. For instance, there was a large growth response to N fertilization in E. globulus corresponding with a change (P < 0.05) in the intercept of the regression to estimate N content.     

Combining harvest sample data with inventory data to estimate forest biomass

Forest biomass databases which go beyond stem volume are needed for carbon balance calculations and also for forest monitoring, forest damage inventories and the solution of other related problems. In this article, it is shown how recursive multiple regression analysis can combine forest inventory data with biomass harvest data. The stand‐level conversion factor derived for Pinus sylvestris L. branch biomass for the “Severka”; Forest Farm shows a reasonable goodness of fit, with a coefficient of determination of R² = 0.87. Statistically significant coefficients were achieved by including stand density and the quadratic mean diameter in the regression. Equations developed for Switzerland, using Burger's Picea abies (L.) Karst. branch and needle conversion factors for individual trees, show R² = 0.87 and R ² = 0.91, achieved by taking h _dom.50, elevation, diameter at breast height and age into account.     

Allometry and partitioning of individual tree biomass and carbon of Abies nephrolepis Maxim in northeast China

Abies nephrolepis Maxim is an important commercial conifer species in northeastern China. In this study, we compared the partitioning and variations of biomass and carbon concentration for four tree components (i.e. stem, root, branch, and foliage). The results indicated that foliage had the largest carbon concentration, which was significantly different from other tree components. Above-ground biomass or carbon accounted for about 78% of the total tree biomass or carbon, whereas below-ground biomass or carbon corresponded to about 22%. The root-to-shoot ratio averaged .28 for biomass and .27 for carbon. We applied likelihood analysis to investigate the error structure of allometric relationship W?=?a·D^b and found that the multiplicative error structure was favored. Thus, the additive systems of biomass and carbon equations in a log-transformed scale were constructed using nonlinear seemly unrelated regression. The model fitting results showed that all biomass and carbon equations fitted the data well. Further, five approaches for calculating carbon stock of individual trees were evaluated and compared. The carbon allometric equations and the estimated biomass multiplied by weighted mean carbon concentration were more advantageous, whereas using the generic carbon concentration constants produced significant biases in estimating the carbon stock of individual trees.     

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).     

Assessment of crown woody biomass in <Emphasis Type="Italic">Eucalyptus grandis</Emphasis> and <Emphasis Type="Italic">E. globulus</Emphasis> plantations

Young trees were harvested to explore non-destructive methodologies to estimate live branch dry weights in young fast-growing Eucalyptus species under different spacing and fertilizer treatments. Branch growth can vary with silvicultural management such as spacing, fertilizing and thinning, and over relatively short periods in response to environmental conditions. Many published regressions based on standard measurements of height and diameter are site, age and treatment specific. The aim of this study was to improve our capacity to predict woody crown dry weight, based on stem measurements, and to minimize (or eliminate) treatment effects on the resulting model. In young trees, branches are temporary support structures for foliage and are often discarded as the base of the green crown rises. As temporary structures they represent an investment of biomass and nutrient elements, and are subject to selection pressures to maximize the return on investment by the tree. Trees were harvested from existing plantation experiments located in south-eastern Queensland for E. grandis W. Hill ex Maiden (ranging from 0.28 to 15.85 m in height, to 5 years old) and south-western Australia for E. globulus Labill. (0.10–34.4 m in height, to 10.2 years) in order to examine the impact of spacing, nitrogen and phosphorus fertilization on early growth. Relationships to estimate crown woody biomass from non-destructive measurements were developed, and these relationships tended to have different slopes and intercepts for trees with predominantly juvenile foliage and those with intermediate or adult foliage. Dry weight of whole-crown live branch wood (W_branch) was related to heights and/or diameter at breast height (D_BH), but the regressions parameters were different, depending on treatment. The relationships became more generic (i.e. less dependent on treatment effects) between W_branch and stem sectional area at the height of the base of the green crown (SA_CB), consistent with the pipe model theory (R² > 0.91 for the two species for trees with intermediate/adult leaves). However, W_branch was more closely related again to the stem volume above the base of the green crown and treatment effects were not significant (V_Con,gc, R² > 0.93). Branches exit the stem below the green crown, and for E. grandis the best relationship was on stem volume above the lowest live branch (V_Con,llb, R² 0.94). Limited sampling from four other species with similar or contrasting crown characteristics indicated that the relationship could be applied quite generally. Individual E. grandis branch woody dry weight was closely related to the conical volume of the main (first order) branch (V_con,br, R² 0.98₎. The whole crown equivalent, branch woody dry weight plus stem dry weight above the lowest live branch, was also closely related to the stem volume within the woody crown (V_Con,llb, R² 0.97–0.99). While the slope of this relationship was still significantly different between trees with juvenile and intermediate/adult foliage, it had a similar form, suggesting that trees with juvenile foliage allocated a different proportion of their woody biomass within the crown to branches than older trees.     

Aboveground biomass equations for individual trees of <Emphasis Type="Italic">Cryptomeria japonica</Emphasis>, <Emphasis Type="Italic">Chamaecyparis obtusa</Emphasis> and <Emphasis Type="Italic">Larix kaempferi</Emphasis> in Japan

Generic equations are proposed for stem, branch and foliage biomass of individual trees in even-aged pure stands of Cryptomeria japonica, Chamaecyparis obtusa and Larix kaempferi. Biomass data was collected from a total of 1,016 individual trees from 247 stands throughout Japan, and five regression models were assessed by root mean square error, mean bias, fit index (FI), and AIC. The results show that a power equation using diameter at breast height (dbh) and height is the most suitable for all species and components. This equation is more accurate than the familiar power equation that uses ‘dbh² height’, and it expresses the greater volume of branch and foliage mass of trees with a lower height/diameter ratio. A power equation using dbh is more reasonable for models with dbh as the only independent variable and more accurate than a power equation using ‘dbh² height’ for estimating branch and foliage mass. Estimating error for branch and foliage mass is larger than that for stem mass, but the entire aboveground biomass can be estimated with an error of less than 19%, except in the case of small trees with dbh less than 10 cm.