Allometric models for estimation of aboveground biomass of Gmelina arborea Roxb. in pulpwood plantations of Bangladesh

Gmelina arborea Roxb. is a fast-growing, deciduous tree species native to Bangladesh. It has been widely planted since 1992 for commercial production of pulpwood in hilly areas of Bangladesh. The purpose of this study was to derive well-fitting allometric models for estimation of aboveground biomass, and carbon and nutrient (nitrogen, phosphorus and potassium) stocks in G. arborea to ensure sustainable production and management of this species. Eight linear models with 64 regression equations were tested for estimation of aboveground biomass, carbon and nutrient stocks in different parts (leaves, branches, bark and stem) of the plant. The best-fitting allometric models were selected in accordance with various relevant statistical criteria.     

异速模型评估森林植被生物量有机碳储量

在孟加拉的吉大港南部森林地区,利用异速模型评估森林植被的有机碳的储量.异速模型被分别应用测试树木(被划分两个胸高直径级)、灌木和草本植物.采用基部面积估算胸高直径级为从> 5 cm 到 ≤ 15 cm 和> 15 cm树木的生物量有机碳储量模型最好,分别有很高的决定系数(胸高直径级> 5 cm 到 ≤ 15 cm 的r2 为0.73697,胸高直径级> 15 cm 的r2为0.87703),且回归系数(P = 0.000)显著.其它模型(包括采用树高,胸高直径,树高和胸高直径,以及综合树高、胸高直径和木材密度)的线性和对数关系都表现出很低的决定系数.分别建立了20种优势树种的异速模型,采用树木基部面积的模型都得到很高的决定系数值.单独采用灌木和草本植物总生物量的异速模型有较高的决定系数(灌木的r2 为0.87948,草本植物的r2 为0.87325),且回归(系数)性显著(P = 0.000).生物量有机碳的评估是复杂的和耗时的研究,本研究所建立的异速模型可以应用于孟加拉和其它热带(地区)国家的森林植被的有机碳储量的测算.     

Mapping tree aboveground biomass and carbon in Omo Forest Reserve Nigeria using Landsat 8 OLI data

Protected areas in Nigeria are important ecosystems for carbon storage. The aim of this study was to estimate and map tree aboveground biomass (TAGB) and carbon (TAGC) within a tropical forest in Nigeria. Stepwise regression analysis was implemented to develop models for predicting TAGB in the forest stand, by integrating field TAGB data with Landsat 8 OLI data. Spectral variables used in the analysis include spectral bands, vegetation indices, tasseled cap indices and principal components. Model validation was performed using independent sample plots. The results showed that incorporating more than one category of spectral variables improved the prediction of TAGB. The best-fit model was applied to map the spatial distribution of TAGB and TAGC. The TAGC was estimated as 52.3% of TAGB, based on the average carbon content of tree species derived in this study. Average TAGB and TAGC estimates for the forest stand were 373.1 ± 165.4 t ha^?1 and 194 ± 82.7 t ha^?1, respectively. Reliable estimates of TAGB and TAGC for the forest reserve were obtained. This study provides important information required to manage the forest stand for optimal carbon sequestration.     

Species-specific biomass allometric models and expansion factors for indigenous and planted forests of the Mozambique highlands

Secondary Miombo woodlands and forest plantations occupy increasing areas in Mozambique, the former due to anthropogenic activities. Plantations, mainly species of Eucalyptus and Pinus, are being established on sites previously covered by secondary Miombo woodlands. This affects the evolution, cycle and spatiotemporal patterns of carbon(C) storage and stocks in forest ecosystems. The estimation of C storage, which is indispensable for formulating climate change policies on sequestrating CO_2, requires tools such as biomass models and biomass conversion and expansion factors(BCEF). In Mozambique, these tools are needed for both indigenous forests and plantations. The objective of this study is to fit species-specific allometric biomass models and BCEF for exotic and indigenous tree species. To incorporate efficient inter-species variability, biomass equations were fitted using nonlinear mixed-effects models. All tree component biomass models had good predictability; however, better predictive accuracy and ability was observed for the 2-predictors biomass model with tree height as a second predictor. The majority of the variability in BCEF was explained by the variation in tree species. Miombo species had larger crown biomass per unit of stem diameter and stored larger amounts of biomass per stem volume. However, due to relatively rapid growth, larger stem diameters, heights, and stand density, the plantations stored more biomass per tree and per unit area.     

Determinants and correlates of above-ground biomass in a secondary hillside rainforest in Central Vietnam

Despite inception of carbon-conservation forestry programs, information about total above-ground woody biomass (TAGB) in Vietnamese secondary lowland rainforests is still scarce. We elucidated major factors influencing local variation of TAGB within an anthropogenically modified hillside forest in Th?a Thiên-Hu? Province. On forty 400 m² sized plots all tree species were recorded, and their biomass was calculated using allometric equations. In addition, bio-physical parameters relating to terrain and soils were measured. Effects of bio-physical variables on forest TAGB were assessed using multivariate regression methods. Forest TAGB (average 117 Mg ha^?1) was primarily explained by forest structural variables, i.e. tree densities and average heights, in particular presence of large trees. TAGB was largely determined by the biomass of a few species which dominated different forest parts (ridges or hill base); TAGB was hardly influenced by species diversity. Many dominant trees were light-demanding species; these were characterised by scarce rejuvenation and high tree mortality. Bio-physical patterns indicated that previous logging impacts persisted and continued to influence seedling establishment, sapling growth/survival, and—ultimately—species composition. Nutrient patterns were mostly explained by interactions with certain tree species and tree foliage cover, as modulated by terrain and logging impacts. Development trajectories of TAGB over the next 10–20 years could not be predicted easily since (1) many functionally important late-succession species (e.g. dipterocarps) were very scarce; (2) the sizes of initially established light-demanding species appeared to meet limits, including increasing tree mortality; and (3) rejuvenation and species succession differed locally and proceeded along largely unpredictable pathways. Some suggestions for further research are made.     

Allometric equations for accurate estimation of above-ground biomass in logged-over tropical rainforests in Sarawak, Malaysia

Although allometric equations can be used to accurately estimate biomass and/or carbon stock in forest ecosystems, few have been developed for logged-over tropical rainforests in Southeast Asia. We developed allometric relationships between tree size variables (stem diameter at breast height (dbh) and tree height) and leaf, branch, stem and total above-ground biomass in two logged-over tropical rainforests with different soil conditions in Sarawak, Malaysia. The study sites were originally classified as mainly lowland dipterocarp forest and have been selectively logged in the past 20 years. In total, 30 individuals from 27 species were harvested to measure above-ground parts. The correlation coefficients for the allometric relationships obtained for total above-ground biomass as a function of dbh had high values (0.99), although the relationships for leaf biomass had a relatively low coefficient (0.83). We also found relatively high coefficients for allometric relationships between tree height and plant-part biomass, ranging from 0.82 to 0.97. Moreover, there were no differences for allometric equations of total above-ground biomass between study sites. A comparison of equations of above-ground biomass in various previously reported tropical rainforests and pan-tropic general equations imply that our allometric equations differ largely from the equations for tropical primary forests, early successional secondary forest, and even for the general models. Therefore, choosing the biomass estimation models for above-ground biomass in the logged-over forests of Southeast Asia requires careful consideration of their suitability.     

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.     

3种异速生长方程对生物量建模的对比分析

利用5个树种的1 055株样木的生物量实测数据,对3种常用的异速生长方程的建模效果进行比较分析。结果表明,二元生物量模型M=aDbHc的拟合效果通常要好于一元生物量模型M=aDb;基于组合变量的常用二元模型M=a(D2H)b并不适合于各类生物量的估计,仅对树干生物量和干材生物量的估计是有效的,对其它生物量的估计其效果还不如一元模型;建立树冠、树枝和树叶生物量模型时,采用组合变量D3/H可能是合适的。     

Carbon and biomass partitioning in balsam fir (Abies balsamea)

Balsam fir (Abies balsamea (L.) Mill) was extensively sampled to investigate the effects of forest management practices, site location, within-crown position, tree component (i.e., stem, foliage, branches and roots), and tree social classes on biomass and carbon (C) partitioning at the individual tree level and across ecological regions. The sites were located in three ecologically distinct forest regions of west-central New Brunswick, Canada. There were no significant differences in %C content of trees across ecological regions or across tree social classes. However, at the individual tree level, significant differences were evident in biomass and C allocation between different parts of the tree, between treatment types (i.e., unmanaged and pre-commercially thinned stands) and between within-crown positions, indicating the need for separate estimates of biomass and C content of tree components to obtain more precise estimates of quantities at the stand level. Calculating stand C content based on constant allocation values, as is commonly done, produced errors of up to 15% compared with the values calculated in this study. Three allometric equations of biomass and C that account for partitioning among different parts of the tree were developed and compared: (1) a third-order polynomial, (2) a modified inverse polynomial and (3) a modified Weibull equation. Diameter at breast height (DBH) was used as the only explanatory variable to describe fresh biomass, dry biomass and C content. All regressions derived showed a high correlation with DBH, with most r2 values > 0.95. A comparison of the equation results showed that the modified Weibull equation gave consistent results with the best overall fit and was the simplest of the three equations investigated. The regressions can be used to estimate forest biomass and tree C content at the stand level, given specific information on DBH.     

Aboveground biomass estimation of small diameter woody species of tropical dry forest

Estimation of accurate biomass of different forest components is important to estimate their contribution to total carbon stock. There is lack of allometric equations for biomass estimation of woody species at sapling stage in tropical dry forest (TDF), and therefore, the carbon stored in this forest component is ignored. We harvested 46 woody species at sapling stage in a TDF and developed regression models for the biomass estimation of foliage, branch, bole and the total aboveground part. For foliage and branch biomass, the models with only stem diameter as estimator showed greater R ². For bole and aboveground biomass, the models including wood specific gravity or wood density exhibited higher R ² than those without wood density. Also, the model consisting of wood density, stem diameter and height had the lowest standard error of estimate for bole and aboveground biomass. Moreover, the R ² values are very similar among models for each component. The measurement error of height and the use of a standard value of wood density together may introduce more than 2 % error into the models. Therefore, we suggest using diameter-only model, which may be more practical and equally accurate when applied to stands outside our study area.     

An allometric equation for estimating stem biomass of Acacia auriculiformis in the north-eastern region of Bangladesh

Tree biomass plays an important role in sustainable management and in estimating forest carbon stocks. The objective of this study was to select the best model for measuring stem biomass of Acacia auriculiformis in the study area. Data from five hillocks and 120 individual trees from each hillock were used in this study. Twelve different forms of linear, power and exponential equations were compared in this study to select the best model. Two models (VI and XI) were selected based on R ², adjusted R ², the Akaike information criterion, F-statistics and the five assumptions of linear regression. Model VI was discarded based on the Durbin-Watson value of autocorrelation of the residuals, then the ARIMA (2, 0, 1) model was used to remove the autocorrelation from the model and the final bias-corrected model XI was derived. The model was validated with a test data set having the same range of DBH and stem height of the training data set on the basis of linear regression, Morisita's similarity index, and t-test for mean difference between predicted and expected biomass. A comparison between the best logarithmic and non-linear allometric model shows that the non-linear model produces systematic biases and overestimates stem biomass for larger trees. The overall results showed that the bias-corrected logarithmic model XI can be used efficiently for estimating stem biomass of A. auriculiformis in the northeastern region of Bangladesh.     

Biomass,stem basic density and expansion factor functions for five exotic conifers grown in Denmark

Adequate allometric equations are needed for estimating carbon pools of fast growing tree species in relation to international reporting of CO₂ emissions and for assessing their possible contribution to increasing forest biomass resources. We developed models for predicting biomass, stem basic density and expansion factors of stem to above-ground biomass for five fast growing conifers. Data included destructive measurements of 236 trees from 14 sites, covering a wide range of growth conditions. To ensure model efficiency, models for predicting stem, crown and total above-ground biomass for the five species were estimated simultaneously using a linear, mixed effects model that allowed contemporaneous correlations between the different tree components. Models differed among species and included dbh and tree height. The models explained more than 98% of the variation in above-ground biomass and reflected differences in the allometry between tree species. Stem density differed among species but generally declined with increasing site index and dbh. The overall model for predicting stem basic density included dbh, H₁₀₀ and site index and explained 66% of the total variation. Expansion factors decreased from 1.8–2.0 in small trees (dbh < 10 cm) to 1.1–1.2 for large trees (dbh > 25 cm), but differed among species. The overall model explained 86% of the variation and included quadratic mean diameter and dbh.     

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.     

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.     

Estimating biomass of white spruce seedlings with vertical photo imagery

Estimation of individual tree seedling biomass isrequired in a variety of forest management andresearch applications such as assessment of netprimary productivity and carbon sequestrationpotential of forest stands, understory forest fuelinventories, and development of silviculturalguidelines to promote the growth of desired treespecies. Photo imagery is a promising non-destructivemethod for estimating the aboveground biomass of treeseedlings. This method was tested using naturallyregenerated white spruce (Picea glauca (Moench)Voss) seedlings growing in the understory of a mixedconifer shelterwood in central Ontario. In the fall of1997, 45 seedlings were sampled from plots exposed toone of three mechanical release treatments (earlyspring release, mid summer release, and no release(control)) in 1994. Each seedling was photographed inthe field to measure the vertical projected area(silhouette area) of the aboveground portion of theseedling. Seedlings were harvested, basal diameter andtotal height measured, and biomass (dry mass) offoliage, branches, main stem and total abovegroundplant tissue determined. Regression analysis revealeda strong relationship between both silhouette area andbasal diameter, and seedling biomass. Coefficients ofdetermination for regression equations usingsilhouette area were equal to 0.892, 0.918, 0.926, and0.937 for the main stem, branches, foliage, and totalaboveground biomass, respectively. Respectivecoefficients of determination for regression equationsusing basal diameter were 0.960, 0.945, 0.953, and0.977. Silhouette area-based equations for totalaboveground and foliar biomass differed significantly(P < 0.005) among release treatments. Nosignificant differences among treatments were observedbetween silhouette area-based equations for biomass ofbranches and main stem (P > 0.05), or betweenbasal diameter-biomass (allometric) equations for allcomponents (P > 0.1). The method was thentested by validating the biomass equations using anindependent data set from 35 white spruce seedlingsfrom the same site and cohort, but exposed todifferent treatments and microenvironmentalconditions. For each seedling, biomass components werepredicted using silhouette area-based and allometricequations, and a relative error of predictioncalculated. The mean relative error for silhouettearea-based predictions varied among biomass componentsfrom –20.25% to –3.21%, with standard deviation ofthe error ranging from 23.04% to 33.44%. The meanrelative error for allometric equations ranged from–2.46% to –21.75%, with standard deviations of23.34% to 32.61%. These results suggest that: (1)photo imagery can be used as an alternative to moretraditional allometric methods of biomass estimation,and (2) general (developed for a broad range ofgrowing conditions) equations derived by either methodare preferable to those specifically calibrated for agiven growing environment.     

Estimating carbon stock in secondary forests: Decisions and uncertainties associated with allometric biomass models

Secondary forests are a major terrestrial carbon sink and reliable estimates of their carbon stocks are pivotal for understanding the global carbon balance and initiatives to mitigate CO₂ emissions through forest management and reforestation. A common method to quantify carbon stocks in forests is the use of allometric regression models to convert forest inventory data to estimates of aboveground biomass (AGB). The use of allometric models implies decisions on the selection of extant models or the development of a local model, the predictor variables included in the selected model, and the number of trees and species for destructive biomass measurements. We assess uncertainties associated with these decisions using data from 94 secondary forest plots in central Panama and 244 harvested trees belonging to 26 locally abundant species. AGB estimates from species-specific models were used to assess relative errors of estimates from multispecies models. To reduce uncertainty in the estimation of plot AGB, including wood specific gravity (WSG) in the model was more important than the number of trees used for model fitting. However, decreasing the number of trees increased uncertainty of landscape-level AGB estimates substantially, while including WSG had limited effects on the accuracy of the landscape-level estimates. Predictions of stand and landscape AGB varied strongly among models, making model choice an important source of uncertainty. Local models provided more accurate AGB estimates than foreign models, but high variability in carbon stocks across the landscape implies that developing local models is only justified when landscape sampling is sufficiently intensive.     

Predicting growth and sequestration of carbon by plantations growing in regions of low-rainfall in southern Australia

In regions of Australia of low–medium rainfall (500–800 mm/year), there is growing community and land-owner support for re-planting trees to achieve multiple environmental objectives, particularly amelioration of soil salinity. Sequestration of carbon by newly established trees is not only another important environmental benefit, but also a potential commercial benefit. To obtain estimates of carbon sequestered by species of commercial potential in such regions, we calibrated the carbon (C) accounting model FullCAM to Eucalyptus cladocalyx and Corymbia maculata plantations. This was achieved by harvesting trees of a range in sizes to determine the allometric relationships that most accurately predict biomass and stem density from measures of stem diameter. Predictions of stem diameter were obtained from a forest growth model (3-PG) previously calibrated for these two species. By applying these predictions of changes in stem diameter as the stand matures in our allometric relationships, we estimated changes in partitioning of biomass (between stem, branches, bark, foliage and roots) and stem wood density as the stand matures under scenarios of 500, 600 and 750 mm mean annual rainfall. We found that for both species, regardless of annual rainfall, throughout the rotation 37–50% of carbon sequestered in the total tree biomass was in the stem, 18–27% in both branches and roots, and the remainder in foliage or bark. However, rate of accumulation of carbon was dependent on annual rainfall, with average annual rate of sequestration of carbon in tree biomass and litter during the first rotation of E. cladocalyx (or C. maculata) increasing from 3.68 (or 4.17) to 4.72 (or 4.86) Mg C ha⁻¹ yr⁻¹ as annual rainfall increased from about 500 to 750 mm. Although it was predicted that decomposition negated any accumulation of debris between successive rotations, carbon was predicted to accumulate in sawlog products, given that assumed rates of product decomposition were slightly less than their rate of accumulation. This resulted in a slight increase (<8 Mg C ha⁻¹) in predicted total sequestration of carbon between successive rotations.     

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.     

林木生物量模型研究概述

林木生物量模型回归估计法是林分生物量测定的常用方法之一,林木生物量模型的研究对森林生物量的研究及其估测有重要价值。随着森林碳储量的研究,森林生物量再次被重视,其精度要求也随之提高。介绍了林木生物量模型历史和现状,对生物量模型类型、参数估计方法、模型评介指标,模型中的异方差、不兼容等问题及其解决方法作了简介,概括了当前国内的一些新进展,并对未来的发展趋势作了预测。     

一个新的通用性相对生长生物量模型

针对West等(1997;1999)提出的理论生物量模型与经验模型存在显著差异的问题,对应用最广的一元生物量模型M=aDb的2个参数进行专题研究。首先,基于几何学的观点推导出参数b的理论值为7/3(≈2.33),与大量已有研究结果的对比表明,该理论参数值能够很好地描述地上生物量与胸径之间的平均相对生长关系;然后,利用包含1441株样木的5组立木生物量数据对新提出的通用性理论模型进行验证;最后,分析参数a与木材密度ρ之间的相关性,并建立二者之间的线性回归模型。新的模型既简单明了,又能反映不同树种之间的生物量差异,可为建立用于区域性和国家级森林生物量估计的通用性生物量模型提供可行途径。