Functional composition of tall-statured trees underpins aboveground biomass in tropical forests

The influences of trait diversity(i.e.,the niche complementarity effect) and functional composition(i.e.,the mass ratio effect) on aboveground biomass(AGB) is a highly debated topic in forest ecology.Therefore,further studies are needed to explore these mechanisms in unstudied forest ecosystems to enhance our understanding,and to provide guidelines for specific forest management.Here,we hypothesized that functional composition would drive AGB better than trait diversity and stem size inequality ...     

Allometric equations for estimating the above-ground biomass in tropical lowland Dipterocarp forests

Allometric equations can be used to estimate the biomass and carbon stock of forests. However, so far the equations for Dipterocarp forests have not been developed in sufficient detail. In this research, allometric equations are presented based on the genera of commercial species and mixed species. Separate equations are developed for the Dipterocarpus, Hopea, Palaquium and Shorea genera, and an equation of a mix of these genera represents commercial species. The mixed species is constructed from commercial and non-commercial species. The data were collected in lowland mixed Dipterocarp forests in East Kalimantan, Indonesia. The number of trees sampled in this research was 122, with diameters (1.30 m or above buttresses) ranging from 6 to 200 cm. Destructive sampling was used to collect the samples where diameter at breast height (DBH), commercial bole height (CBH), and wood density were used as predictors for dry weight of total above-ground biomass (TAGB). Model comparison and selection were based on Akaike Information Criterion (AIC), slope coefficient of the regression, average deviation, confidence interval (CI) of the mean, paired t-test. Based on these statistical indicators, the most suitable model is ln(TAGB) = c + αln(DBH). This model uses only a single predictor of DBH and produces a range of prediction values closer to the upper and lower limits of the observed mean. Model 1 is reliable for forest managers to estimate above-ground biomass, so the research findings can be extrapolated for managing forests related to carbon balance. Additional explanatory variables such as CBH do not really increase the indicators’ goodness of fit for the equation. An alternative model to incorporate wood density must be considered for estimating the above-ground biomass for mixed species. Comparing the presented equations to previously published data shows that these local species-specific and generic equations differ substantially from previously published equations and that site specific equations must be considered to get a better estimation of biomass. Based on the average deviation and the range of CI, the generalized equations are not sufficient to estimate the biomass for a certain type of forests, such as lowland Dipterocarp forests. The research findings are new for Dipterocarp forests, so they complement the previous research as well as the methodology of the Good Practice Guidance for Land Use and Land Use Change and Forestry (GPG-LULUCF).     

黄土丘陵区沙棘地上部生物量估测模型

根据沙棘生长因子与其地上部生物量间的相关关系,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模型,复相关系数为０．９４２１～０．９９５９,经检验均达十分显著水平。这一研究结果改进了非破坏性调查沙棘地上部生物量的方法。     

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).     

Ecoregional variations of aboveground biomass and stand structure in evergreen broadleaved forests

Biotic and abiotic factors control aboveground biomass(AGB) and the structure of forest ecosystems. This study analyses the variation of AGB and stand structure of evergreen broadleaved forests among six ecoregions of Vietnam. A data set of 173 1-ha plots from 52 locations in undisturbed old-growth forests was developed. The results indicate that basal area and AGB are closely correlatedwith annual precipitation, but not with annual temperature,evaporation or hours of sunshine. Basal area and AGB are positively correlated with trees [ 30 cm DBH. Most areas surveyed(52.6%) in these old-growth forests had AGB of100–200 Mg ha~(-1); 5.2% had AGB of 400–500 Mg ha~(-1),and 0.6% had AGB of [ 800 Mg ha~(-1). Seventy percent of the areas surveyed had stand densities of 300–600 ind.ha~(-1), and 64% had basal areas of 20–40 m~2 ha~(-1). Precipitation is an important factor influencing the AGB of old-growth, evergreen broadleaved forests in Vietnam.Disturbances causing the loss of large-diameter trees(e.g.,[ 100 cm DBH) affects AGB but may not seriously affect stand density.     

Height-diameter models with random coefficients and site variables for tree species of Central Maine

Height-diameter models were developed for nine tree species common to the northeastern United States: Abies balsamea, Acer rubrum, Betula papyrifera, B. populifolia, Picea rubens, P. mariana, Pinus strobus, Populus tremuloides, and Tsuga canadensis. Stem heights and diameters were collected from 6 146 trees (between 136 and 2615 trees per species) on 50 plots within 10 structurally diverse stands that are part of a long-term silvicultural experiment in central Maine. The models were developed using both generalized nonlinear least squares (GNLS) and multi-level, mixed-effects approaches. Mixed-effects approaches were superior to GNLS, with inclusion of site covariates (tree density and basal area) accounting for some of the variability explained by the random coefficients in the full mixed-effect models. Analysis of plot-level parameter estimates suggested that differences in stand structure (even-aged vs. uneven-aged silvicultural practices) had a significant influence on the height-diameter relationships.     

Stem biomass and volume models of selected tropical tree species in West Africa

Estimating tree volume and biomass constitutes an essential part of the forest resources assessment and the evaluation of the climate change mitigation potential of forests through biomass accumulation and carbon sequestration. This research article provides stem volume and biomass equations applicable to five tree species, namely Afzelia africana Sm. (Caesalpiniaceae), Anogeissus leiocarpa (DC.) Guill. and Perr. (Combretaceae), Ceiba pentandra (L.) Gaertn. (Bombacaceae), Dialium guineense Willd. (Caesalpiniaceae), Diospyros mespiliformis Hochst. ex A.DC. (Ebenaceae) in natural protected tropical forests and, in addition, Tectona grandis L.f. (Verbenaceae) in plantations. In addition to the tree species specific equations, basic wood density, as well as carbon, nitrogen, organic matter and ash content were determined for these tree species in tropical conditions in West Africa. One hundred and sixty-two sample trees were measured through non-destructive sampling and analysed for volume and biomass. Stem biomass and stem volume were modelled as a function of diameter (at breast height; Dbh) and stem height (height to the crown base). Logarithmic models are presented that utilise Dbh and height data to predict tree component biomass and stem volumes. Alternative models are given that afford prediction based on Dbh data alone, assuming height data to be unavailable. Models that include height are preferred, having better predictive capabilities. Ranges in carbon, nitrogen and ash contents are given as well. The successful development of predictive models through the use of non-destructive methods in this study provide valuable data and tools for use in determining the contribution of these major African rainforest tree species to global carbon stocks, while ensuring the preservation of this valued African resource. This study needs to be expanded to further regions and tree species to complete a full inventory of all tree species, emphasising the relevance of African trees to carbon stocks at a global scale.     

Fine-scale habitat differentiation shapes the composition,structure and aboveground biomass but not species richness of a tropical Atlantic forest

Evaluating the influences of fine-scale habitat heterogeneity on the composition, diversity, structure and functioning of forests is critical to understand how tropical forests will respond to climate change and devise forest management strategies that will enhance biodiversity conservation and aboveground biomass stock. Here, we hypothesized that topographic and soil factors determine fine-scale habitat differentiation, which in turn shape community composition, species richness, structure and aboveground biomass at the local scale in tropical forests.To test this hypothesis, we selected two areas(each100 × 100 m) with contrasting fine-scale topographic conditions where all trees, palms and lianas with a diameter at breast height ≥ 10 cm were tagged and identified to species. In each selected area, 100 subplots of 10 × 10 m were established. We mainly found that higher topographic variability caused higher habitat differentiation with changes in species composition and community structure,but did not change species richness. Our habitat-scale analyses indicated that, in the less heterogeneous area, the distribution of species was more uniform along a fine-scale topographical gradient with no variation in convexity,which induced changes in structure and aboveground biomass, but not in species richness. The nonsignificant relationship between species richness and aboveground biomass may be attributable to species redundancy or functional dominance. This study suggests that environmental filtering is a fundamental process for shaping community assembly and forest functioning along a local topographical gradient in tropical forests.     

北京地区栓皮栎地上部分生物量的研究

以北京地区栓皮栎人工林为研究对象,应用典型样地调查法和相对生长法对乔木生物量展开研究,结果显示：各器官中生物量大小顺序为树干〉枝条〉叶片,其中树干约占65%,树冠约占35%。通过回归分析探讨了各变量的相关性,并对其各器官的生物量与胸径和树高进行模型拟合。其中树干和树冠的生物量与胸径、树高的拟合方程分别是：W=0.018（D2H）1.09、W=0.9（D）2.128。     

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.     

Comparison between TanDEM-X- and ALS-based estimation of aboveground biomass and tree height in boreal forests

Interferometric Synthetic Aperture Radar (InSAR) data from TerraSAR-X add-on for Digital Elevation Measurement (TanDEM-X) were used to estimate aboveground biomass (AGB) and tree height with linear regression models. These were compared to models based on airborne laser scanning (ALS) data at two Swedish boreal forest test sites, Krycklan (64°N19°E) and Remningstorp (58°N13°E). The predictions were validated using field data at the stand-level (0.5–26.1 ha) and at the plot-level (10 m radius). Additionally, the ALS metrics percentile 99 (p99) and vegetation ratio, commonly used to estimate AGB and tree height, were estimated in order to investigate the feasibility of replacing ALS data with TanDEM-X InSAR data. Both AGB and tree height could be estimated with about the same accuracy at the stand-level from both TanDEM-X- and ALS-based data. The AGB was estimated with 17.2% and 14.6% root mean square error (RMSE) and the tree height with 7.6% and 4.1% RMSE from TanDEM-X data at the stand-level at the two test sites Krycklan and Remningstorp. The Pearson correlation coefficients between the TanDEM-X height and the ALS height p99 were r?=?.98 and r?=?.95 at the two test sites. The TanDEM-X height contains information related to both tree height and forest density, which was validated from several estimation models.     

The estimation of aboveground biomass and nutrient pools of understorey plants in closed Norway spruce forests and on clearcuts

The estimation model PhytoCalc allows a non-destructive quantification of dry weight and nutrient pools of understorey plants in forests by using the relationship between species biomass, cover and mean shoot length. The model has been validated with independent samples in several German forest types and can be a useful tool in forest monitoring. However, in open areas within forests (e.g. clearcuts), the current model version underestimates biomass and produces unreliable nutrient pool estimations. Thus, tissue density, as approximated by leaf dry matter content (LDMC), is systematically higher under high light compared to low light conditions. We demonstrate that the ratio of LDMC under clearcut conditions to LDMC under forest conditions can be used to adjust the PhytoCalc model to clearcut conditions. We investigated the LDMC ratio of five exemplary species commonly occurring on clearcuts. Integrating the square of the ratio as a correction factor improved estimates of biomass to more than 70% fit between observations and predictions. Results also suggest this ratio can be used to correct nutrient concentrations modelled in PhytoCalc, which tend to be overestimated in clearcuts. As morphological groups of plant species exhibit significantly different ratios, we advise using group-specific correction factors for clearcut adjustments in the future.     

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.     

Height–diameter models for tropical forests on Hainan Island in southern China

Measurements on 8352 felled trees from 31 plots in tropical forests on Hainan Island provided information to investigate the relationship between total tree height and diameter at 1.3 m (DBH). Out of 33 model forms either published or derivable from published forms, a modification of the exponential model published by Meyer (Meyer, H.A. A mathematical expression for height curves. J. For. 38 (1940) 415–420) was selected based on low bias and relatively good precision of its predictions on individual plots. Variations from plot-to-plot were significant. Therefore, a parameter prediction method based on predictor variables derived from all DBH values on a plot was developed in order to provide a method to localize the model. In a test with independent data from an additional 36 plots, the localized height-prediction model produced predictions with a pooled mean-squared error of 3.8 m², a pooled R² of 0.72, and an average bias of −0.2 m. Even though tremendous variability exists in tropical forests and modeling height–DBH relationships never provides high levels of precision, this model will provide a useful and economical alternative to attempting height measurements during inventories of these forests.     

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.     

Improvement in accuracy of aboveground biomass estimation in Eucalyptus nitens plantations: Effect of bole sampling intensity and explanatory variables

Two sets of aboveground biomass equations were fitted for stem only and stem plus crown predictive variables in Eucalyptus nitens plantations in Northern Spain. A sample of 40 trees was chosen after a complete study of variation in tree height and diameter in the region. The trees were felled and the biomass was divided into the following components: wood, bark, thick branches, thin branches, twigs, leaves and dead branches along the stem. Bole biomass was estimated by systematic subsampling of one 5 cm-thick disk every 0.5 m. Such intensive subsampling enabled determination of the effect of subsampling intensity on accuracy and bias of wood estimation, considering two ratio-type estimators: stem weight to dry matter, determined by the complete weighing (CW) method (i.e. of the fresh weight of the entire stem) and volume to dry matter, determined by the partial weighing (PW) method. The changes in moisture content and basic density along the stem explained the serious risk of dry mass or weight overestimation when a systematic subsample is considered. The average basic density was usually found at a relative height of 30-35% along the stem. The default choice of the bottom disk or log as the first section resulted in overestimations for the CW method and underestimations for the PW one. The biomass equations were fitted by seemingly unrelated regression, with corrections for heteroscedasticity carried out by weighted fitting. Diameter at breast height was the best explanatory variable, and the inclusion of height did not improve the accuracy, except for wood. The inclusion of crown variables improved the predictive ability for crown fractions, increasing the accuracy for estimating thick branches (by 10.8%), twigs (by 19.1%) and leaves (by 17.3%). The biomass of each fraction decreased in the following order: wood > bark > thick branches > dead branches along the stem > leaves > thin branches > twigs. The changes in these percentages with diameter class and the predictive ability of the fitted equations were also studied.     

Growth models and site index table of natural Korean pine forests

IntroductionKoreanpine(PinuskOraiensisSieb.etZucc.)isoneofthemostimportanttimberspeciesanditisnaturaIIydistributedinHeilongjiang,JiIinandLiaon-ingprovincesinChina.ManyforestryresearchersmadeextensiveandprofoundstudiesonthisspeciesJiangYiyin(1985)studiedthegroWthandgrowthmodelsforpIantationsofKoreanpine.However,veryfewpaperswerefoundonthegroWthmodeIsofnaturalKoreanpineforest.Koreanpinehasa1onggroWthperiod.ForextensivelymanagingKoreanpineforest,itneedstheJorestrytabIeswithhighac-Curacy…     

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.     

Allometric equations based on a fractal branching model for estimating aboveground biomass of four native tree species in the Philippines

Fractal branching models can provide a non-destructive and generic tool for estimating tree shoot and root length and biomass, but field validation is rarely described in the literature. We compared estimates of above ground tree biomass for four indigenous tree used on farm in the Philippines based on the WanFBA model tree architecture with data from destructive sampling. Allometric equations for the four species varied in the constant (biomass at virtual stem diameter 1) and power of the scaling rule (b in Y = aD ^b ), deviating from the value of 8/3 that is claimed to be universal. Allometric equations for aboveground biomass were 0.035 D ^2.87 for Shorea contorta, 0.133 D ^2.36 for Vitex parviflora, 0.063 D ^2.54 for Pterocarpus indicus and 0.065 D ^2.28 for Artocarpus heterophyllus, respectively. Allometric equations for branch biomass had a higher b factor than those for total biomass (except in Artocarpus); allometric equations for the leave + twig fraction a lower b. The performance of the WanFBA model was significantly improved by introduction of a tapering factor “τ“ for decrease of branch diameter within a single link. All statistical tests performed on measured biomass versus biomass predicted from the WanFBA results confirm the viability of the WanFBA model as a non-destructive tool for predicting above-ground biomass equations for total biomass, branch biomass and the leaf + twig fraction.