Predictive models for biomass and carbon stocks estimation in Grewia optiva on degraded lands in western Himalaya

Grewia optiva Drummond is one of important agroforestry tree species grown by the farmers in the lower and mid-hills of western Himalaya. Different models viz., monomolicular, logistic, gompetz, allometric, rechards, chapman and linear were fitted to the relationship between total biomass and diameter at breast height (DBH) as independent variable. The adjusted R² values were more than 0.924 for all the seven models implying that all models are apparently equally efficient. Out of the six non-linear models, allometric model (Y = a × DBH ^b ) fulfils the validation criterion to the best possible extent and is thus considered as best performing. Biomass in different tree components was fitted to allometric models using DBH as explanatory variable, the adjusted R² for fitted functions varied from 0.872 to 0.965 for different biomass components. The t values for all the components were found non-significant (p > 0.05), thereby indicating that model is valid. Using the developed model, the estimated total biomass varied from 6.62 Mg ha^?1 in 4 year to 46.64 Mg ha^?1 in 23 year old plantation. MAI in biomass varied from 1.66–2.05 Mg ha^?1 yr^?1. The total biomass carbon stocks varied from 1.99 Mg ha^?1 in 4 year to 15.27 Mg ha^?1 in 23 year old plantation. Rate of carbon sequestration varied from 0.63–0.81 Mg ha^?1 yr^?1. Carbon storage in the soil up to 30 cm soil depth varied from 25.4 to 33.6 Mg ha^?1.     

Allometric model of the height–diameter curve for even-aged pure stands of Japanese cedar (<Emphasis Type="Italic">Cryptomeria japonica</Emphasis>)

We derived an allometric model of the height–diameter curve for even-aged pure stands, which was a modification of the earlier model proposed by Inoue (2000a). An individual-dependent allometric equation was used as the height–diameter curve. Using the discriminant analysis method, all trees composed of a stand were stratified into upper and lower trees. It was assumed that both relationships between mean tree height H _m and upper tree height H _u and between mean DBH D _m and mean DBH of upper trees D _u could be described by the time-dependent allometric power equations. The height–diameter curve showed an average relationship between tree height and DBH of a given stand at a given time, and hence it could be assumed that the height–diameter curve contained two points (D _m , H _m ) and (D _u , H _u ). With these assumptions, we derived an allometirc model of height–diameter curve, which allowed the coefficients of the curve to be estimated from mean tree height and mean DBH. The proposed model was fitted to Japanese cedar (Cryptomeria japonica D. Don) data. The error ratio of the allometric model ranged from 2.254% to 13.412% (mean = 6.785%), which was significantly smaller than that of the earlier model. When the error of mean tree height was ±1.0 m or less, the effect of the error of mean tree height on the error ratio was comparatively small. This suggested that the error of ±1.0 m in mean tree height could be accepted in the estimation of height–diameter curve using the allometric model. These features enable us to combine the allometric model with Hirata’s vertical angle-count sampling or growth models. In conclusion, the allometric model would be one of the most practical and convenient approaches for estimating the height–diameter relationship of even-aged pure stands.     

Aboveground biomass quantification and tree-level prediction models for the Brazilian subtropical Atlantic Forest

Forests are the largest biological reservoir of biomass and carbon on the planet. This fact turns them into the main tool to neutralise the CO₂ emitted by human activities. Despite such importance, the uncertainties associated with biomass estimates in forests, especially in (sub)tropical forests, are enormous. Facing this scenario, the objectives of this study were (1) to quantify through destructive sampling the aboveground biomass (AGB) of 105 trees of 47 species occurring in a secondary subtropical evergreen rainforest in Brazil; (2) to investigate the AGB distribution in different tree compartments; and (3) to fit tree-level models to improve biomass estimates for the referred forest type. The results revealed that most of the AGB was stored in the compartments stem and large branches (diameter ≥ 5 cm). There was an increase in the proportion of biomass – in relation to the total tree AGB (kg) – allocated in the large branches as tree diameter at breast height (DBH) increased; this pattern was not observed for the compartments stem, thin branches (diameter < 5 cm), and leaves. The compartments thin branches and leaves represented between 5.4% and 17.0%, and 1.3% and 2.9% of the total tree AGB, respectively. From the 10 fitted biomass models, the linearised power models yielded the smallest errors. The best performance model, which returned a mean bias of 1.7%, may be written as AGB = exp(?8.9807 + 2.1642·ln[DBH] + 0.5072·ln[h] + 0.9999·ln[ρ_bas]); Baskerville’s factor = 1.0175. If there are no (reliable) data on tree total height (h; m), the following model, which embedded the DBH and wood basic specific gravity (ρ_bas; kg m^?3), may be employed: AGB = exp(?9.0086 + 2.4606·ln[DBH] + 1.0895·ln[ρ_bas]); Baskerville’s factor = 1.0206.     

Carbon stocks and productivity of mangrove forests in Tanzania

Mangroves offer a number of ecosystem goods and services, including carbon (C) storage. As a carbon pool, mangroves could be a source of CO₂ emissions as a result of human activities such as deforestation and forest degradation. Conversely, mangroves may act as a CO₂ sink through biomass accumulation. This study aimed to determine carbon stocks, harvest removals and productivity of mangrove forests of mainland Tanzania. Nine species were recorded in mainland Tanzania, among them Avicennia marina (Forssk.) Vierh., Rhizophora mucronata Lam. (31%) and Ceriops tagal (Perr.) C.B.Rob. (20%) were dominant. The aboveground, dead wood, belowground and total carbon were 33.5 ± 5.8 Mg C ha^?1, 1.2 ± 1.1 (2% of total carbon), 30.0 ± 4.5 Mg C ha^?1 (46% of total carbon) and 64.7 ± 8.4 Mg C ha^?1 at 95% confidence level, respectively. Carbon harvest removals accounted for loss of about 4% of standing total carbon stocks annually. Results on the productivity of mangrove forests (using data from permanent sample plots monitored for four years [1995-1998]) showed an overall carbon increment of 5.6 Mg C ha^?1 y^?1 (aboveground carbon), 4.1 C ha^?1 y^?1 (belowground carbon) and 9.7 C ha^?1 y^?1 (total carbon) at 23%, 32% and 27% levels of uncertainty, respectively. Both natural death and tree cutting/harvest removals resulted in significant decline of annual carbon productivity. Findings from this study demonstrate that mangroves store large quantities of carbon and are more productive than other dominant forest formations in southern Africa. Both their deforestation and forest degradation, therefore, is likely to contribute to large quantities of emission and loss of carbon sink functionality. Therefore, mangroves need to be managed sustainably.     

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.     

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.     

Mangrove expansion and population structure at a planted site,East London,South Africa

Avicennia marina (Forrsk.) Vierh. was planted in 1969 at Nahoon Estuary, East London, followed a few years later by the planting of Bruguiera gymnorrhiza (L.) Lam. and Rhizophora mucronata (L.) among the larger A. marina trees. This study tested the hypothesis that mangroves have expanded and replaced salt marsh over a 33-year period (1978–2011). It provides important information on mangroves growing at higher latitudes, where they were thought to not occur naturally due to lower annual average temperatures. It further provides insights on future scenarios of possible shifts in vegetation types due to climate change at one of the most southerly distribution sites worldwide. The expansion of mangroves was measured using past aerial photographs and Esri ArcGIS Desktop 10 software. In addition, field surveys were completed in 2011 to determine the population structure of the present mangrove forest and relate this to environmental conditions. The study showed that mangrove area cover increased linearly at a rate of 0.06 ha y^?1, while the salt marsh area cover also increased (0.09 ha y^?1) but was found to be variable over time. The mangrove area is still relatively small (<2 ha) and expanded mostly over a bare sandflat area. Avicennia marina was the dominant species and had high recruitment (seedling density was 33 822 ± 16 364 ha^?1). Only a few Bruguiera gymnorrhiza and Rhizophora mucronata individuals were found (<10 adult trees), although observations indicate that some young plants are becoming established away from the parent plants. The site provides opportunities for studies on mangrove/salt marsh interactions in response to a changing climate. Mangroves should not be planted in non-native areas as they may become invasive outside their natural range. However, future increases in temperature will certainly lead to a southerly expansion of mangoves in South African estuaries.     

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.     

Aboveground biomass increment and stand dynamics in tropical evergreen broadleaved forest

Forest ecosystems can modify the atmospheric CO₂ through biomass accumulation mostly in tree stems with diameter at breast height (DBH) ≥ 10 cm. Aboveground biomass increment (ΔAGB), and changes in stand AGB, no. stems and basal area (BA) were calculated from mortality, recruitment, and growth data of tree stems in tropical evergreen broadleaved forest, Central Highland Vietnam. Data were derived from ten 1-ha permanent plots established in 2004, where all stems with DBH ≥ 10 cm were tagged, identified to species, and measured for DBH in 2004 and 2012. In an 8-year duration, the increment was 53 ± 10 stems ha^–1, 7.8 ± 0.3 m² ha^–1 for BA and 86.0 ± 4.6 Mg ha^–1 for AGB. The stem mortality rate was 0.9% year^–1 and the stem recruitment rate was 2.2% year^–1. Annual ΔAGB was 10.8 Mg ha^–1 year^–1, equaling to 5.4 Mg C ha^–1 year^–1. Of which, tree stems of 35–80 cm DBH classes accounted for 65%. The results indicated that the forest is in stage of carbon sequestration. Any disturbances causing death of 35–80 cm DBH tree stems will much reduce carbon sequestration capacity and it will take a long time for AGB to return to pre-disturbance stage.     

Species-specific allometric equations for improving aboveground biomass estimates of dry deciduous woodland ecosystems

Allometric equations are important for quantifying biomass and carbon storage in terrestrial forest ecosystems.However,equations for dry deciduous woodland ecosystems,an important carbon sink in the lowland areas of Ethiopia have not as yet been developed.This study attempts to develop and evaluate species-specific allometric equations for predicting aboveground biomass(AGB)of dominant woody species based on data from destructive sampling for Combretum collinum,Combretum molle,Combretum harotomannianum,Terminalia laxiflora and mixed-species.Diameter at breast height ranged from 5 to 30 cm.Two empirical equations were developed using DBH(Eq.1)and height(Eq.2).Equation 2 gave better AGB estimations than Eq.1.The inclusion of both DBH and H were the best estimate biometric variables for AGB.Further,the equations were evaluated and compared with common generic allometric equations.The result showed that our allometric equations are appropriate for estimating AGB.The development and application of empirical species-specific allometric equations is crucial to improve biomass and carbon stock estimation for dry woodland ecosystems.     

Mortality and growth of cut pieces of viviparous mangrove (Rhizophora apiculata and R. mucronata) seedlings in the field condition

Viviparous seedlings of the mangrove species Rhizophora apiculata and R. mucronata were divided into even lengths of the top, middle, and bottom parts, and these cut pieces were planted in the field. The mortality and growth were monitored for 38 months after transplantation, and compared with intact seedlings planted in the same place. Both mean diameter and stem height of R. mucronata cut pieces were largest for the bottom parts, intermediate for the middle parts, and the smallest for the top parts. Among cut pieces of R. apiculata, the pattern for diameter was the same, but the mean stem height showed no differences among treatments. For both species, the mortality was associated with the initial volume of individual cut pieces. The bottom cut pieces with large volumes showed lowest mortality. Almost all cut pieces of R. apiculata formed prop roots above ground, but only 30% of R. mucronata cut pieces formed them. In the 38-month-old plantation, the mean diameters of the various cut-piece treatments of R. apiculata and R. mucronata were, respectively, 0.78–1.37 and 0.56–0.89 times as large as those for the intact seedlings; corresponding values for mean stem heights were 0.81–0.85 and 0.50–1.00. These results suggest a possibility that cut pieces can be a useful plantation material.     

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.     

滇西南巨尾桉人工林木根径、胸径与树高模型研究

为研究巨尾桉人工林林木根径、胸径与树高数学模型,在滇西南的双江县选取138株（其中建模样本103株,检验样本35株）树干健全、通直圆满、无分杈的巨尾桉人工林样木,采集其根径与树高、胸径与树高成对数据。利用SPSS 21.0回归分析,分别建立线性方程、对数曲线、指数曲线和Logistic曲线等11个数学模型,以决定系数（R²）、估计值的标准误（SEE）、均方差（RMSE）、平均绝对偏差(MAD)、相对误差（RS）、模型预估精度（P）、显著性(Sig)P值作为模型评价指标,对比11个模型的拟合效果。结果表明,11个根径—树高模型显著性（Sig）P<0.001,其中有9个模型的预估精度大于97%,回归方程达到极显著水平,拟合效果较好;11个胸径—树高模型显著性（Sig）P<0.001,其中9个模型的预估精度大于97%,回归方程达到极显著水平,拟合效果也较好。通过对各项评价指标进行比较分析,确定三次项曲线H=a₀+a₁DR+a₂DR²+a₃DR³是拟合效果最好的根径—树高数学模型,代入拟合参数后的根径—树高数学模型表达式为H=11.069901-0.729389DR+0.096782DR²-0.001984DR³;线性方程H=a₀+a₁D是拟合效果最好的胸径—树高数学模型,代入拟合参数的胸径—树高数学模型表达式为H=4.818702+0.891217D。     

Effect of species grouping and site variables on aboveground biomass models for lowland tropical forests of the Indo-Malay region

Key message

This study assessed the effect of ecological variables on tree allometry and provides more accurate aboveground biomass (AGB) models through the involvement of large samples representing major islands, biogeographical zones and various succession and degradation levels of natural lowland forests in the Indo-Malay region. The only additional variable that significantly and largely contributed to explaining AGB variation is grouping based on wood-density classes.

Context

There is a need for an AGB equation at tree level for the lowland tropical forests of the Indo-Malay region. In this respect, the influence of geographical, climatic and ecological gradients needs to be assessed.

Aims

The overall aim of this research is to provide a regional-scale analysis of allometric models for tree AGB of lowland tropical forests in the Indo-Malay region.

Methods

A dataset of 1300 harvested trees (5 cm ≤ trunk diameter ≤ 172 cm) was collected from a wide range of succession and degradation levels of natural lowland forests through direct measurement and an intensive literature search of principally grey publications. We performed ANCOVA to assess possible irregular datasets from the 43 study sites. After ANCOVA, a 1201-tree dataset was selected for the development of allometric equations. We tested whether the variables related to climate, geographical region and species grouping affected tree allometry in the lowland forest of the Indo-Malay region.

Results

Climatic and major taxon-based variables were not significant in explaining AGB variations. Biogeographical zone was a significant variable explaining AGB variation, but it made only a minor contribution on the accuracy of AGB models. The biogeographical effect on AGB variation is more indirect than its effect on species and stand characteristics. In contrast, the integration of wood-density classes improved the models significantly.

Conclusion

Our AGB models outperformed existing local models and will be useful for improving the accuracy on the estimation of greenhouse gas emissions from deforestation and forest degradation in tropical forests. However, more samples of large trees are required to improve our understanding of biomass distribution across various forest types and along geographical and elevation gradients.

     

森林景观模拟与构景因素控制试验

[目的]通过构景因素控制试验,揭示林木胸径与密度对森林景观的影响规律,为林分密度调控提供参考。[方法]以枫香林为例,综合应用PhotoShop、AutoCAD、SpeedTree等软件,开展森林景观模拟;借助林业试验设计方法开展胸径、密度与景观美景度关系的两因素、单因素控制性试验。[结果](1)在设定的10个密度水平下,胸径变化对美景度(SBE)的影响总体不显著,景观优劣次序为20 cm30 cm10 cm;但若取各胸径级前3个高分SBE比较,则优先次序为30 cm20 cm10 cm;(2)密度对美景度的影响总体上为极显著,不同胸径级的美景度随密度变化均为先升后降趋势,以适中密度为最优,但随着树体的增大,峰值密度向左偏移,10 cm、20 cm、30 cm的最佳密度分别为1 389、833、389株·hm-2。密度-美景度曲线拟合结果为二次曲线,函数形式分别为SBE10=3.435+0.005X1-1.639E(-6)X12(R2=0.719)、SBE_(20)=4.013+0.004X2-1.677E(-6)X_2~2(R~2=0.713)、SBE_(30)=6.355+0.001X3-8.128E(-7)X32(R2=0.728);(3)胸径与密度的交互效应对美景度有极显著影响,但同一密度、同属随机分布的不同模拟场景对美景度的影响不显著。[结论]组合应用多种软件进行森林景观模拟与评价取得了良好结果,方法可行;林分美学质量受胸径、密度两个因素的综合影响,随着胸径增大而提高,但不同胸径有不同的最佳配密匹配度。     

Predicting seedling biomass of radiata pine from allometric variables

Allometric equations predict tree seedling biomass from non-destructively measured variables such as stem diameter (D), height (H) and seedling silhouette area (A), measured by digital imaging. This study investigates whether one general allometric equation can predict biomass of radiata pine (Pinus radiata D.Don) seedlings grown under three levels of photosynthetic photon flux density (PPFD). It also identifies which commonly used variables (A, D ² H or D ²) were the best for predicting seedling biomass under these conditions. Radiata pine seedlings were grown with constant daytime (12 h d⁻¹) PPFD = 500, 250 or 125 μmol m⁻² s⁻¹ for 11 weeks. Seedlings were randomly selected every 10 d for measurement. Analysis of covariance tested whether the relationship between seedling biomass and A, D ² H or D ² varied for each PPFD level. PPFD levels influenced the relationship between biomass and A, D ² H or D ². As a result, “full” allometric models which varied with PPFD levels were more accurate and precise at predicting biomass than “reduced” models which did not vary with PPFD level, although a “reduced” model using D ² also performed well.     

基于线性混合模型的落叶松枝条基径模型

以黑龙江省五营林业局丽林林场30株人工落叶松2 190个枝条基径数据为例,利用逐步回归技术建立了落叶松枝条基径模型:BD=b1+b2DINC+b3DINC2+b4DBH.DINC2。然后,利用S-PLUS软件中的LME过程,拟合线性枝基径模型。采用AIC、BIC、对数似然值和似然比检验等模型评价统计指标对不同模型的拟合效果进行比较分析。结果表明:当拟合枝条基径模型时,b1、b2、b3同时作为混合参数时模型拟合最好。为了矫正混合模型构建过程中产生的异方差现象,把幂函数和指数函数加入到枝条基径混合模型中。指数函数显著提高了枝条基径混合模型的拟合效果,并且消除了异方差现象。模型模拟表明:对于大小相同树木,枝条基径随着着枝深度(DINC)的增加而增大,对于大小不同的树木,枝条基径随着胸径(DBH)的增加而增大。林木的胸径变量很好地反映了不同大小树木的枝条基径的变化。在不知道详细林分信息的前提下,可以利用树木变量合理地预测兴安落叶松人工林的枝条基径的变化规律。     

Comparison of allometric equations and biomass expansion factors for six evergreen broad-leaved trees in subtropical forests in southern Korea

This study was conducted to compare the allometric equations and biomass expansion factors (BEFs) of six dominant evergreen broad-leaved trees (Camellia japonica L, Castanopsis sieboldii Hatus, Quercus acuta Thunb, Q. glauca Thunb, Machilus thunbergii S. et Z., and Neolitsea sericea Koidz) in subtropical forests. A total of 86 trees were destructively sampled to quantify the aboveground biomass of each tree component (i.e., leaves, branches, and stem). Species-specific or generalized allometric equations and species-dependent BEFs were developed for each tree component of the six broad-leaved forest trees. Species-specific allometric equations were significant (P < 0.05), with the diameter at breast height (DBH) accounting for 68–99% of the variation, whereas generalized allometric equations explained 64–96% of the variation. The values of stem density ranged broadly from 0.49 g cm^?3 for C. sieboldii to 0.79 g cm^?3 for Q. glauca, with a mean value of 0.68 g cm^?3. The BEFs were significantly (P < 0.05) lower for C. sieboldii (1.25) than for M. thunbergii (2.02). Stem density and aboveground BEFs had a significant negative relationship with tree ages. The results indicate that species-specific allometric equations and species-dependent BEFs are applicable for obtaining accurate biomass estimates of subtropical evergreen broad-leaved forests.     

Fractal analysis of canopy architectures of Acacia angustissima, Gliricidia sepium, and Leucaena collinsii for estimation of aboveground biomass in a short rotation forest in eastern Zambia

A study was conducted at Msekera Regional Agricultural Research Station in eastern Zambia to (1) describe canopy branching properties of Acacia angustissima, Gliricidia sepium and Leucaena collinsii in short rotation forests, (2) test the existence of self similarity from repeated iteration of a structural unit in tree canopies, (3) examined intra-specific relationships between functional branching characteristics, and (4) determine whether allometric equations for relating aboveground tree biomass to fractal properties could accurately predict aboveground biomass. Measurements of basal diameter (D10) at 10cm aboveground and total height (H), and aboveground biomass of 27 trees were taken, but only nine trees representative of variability of the stand and the three species were processed for functional branching analyses (FBA) of the shoot systems. For each species, fractal properties of three trees, including fractal dimension (Dfract), bifurcation ratios (p) and proportionality ratios (q) of branching points were assessed. The slope of the linear regression of p on proximal diameter was not significantly different (P < 0.01) from zero and hence the assumption that p is independent of scale, a pre-requisite for use of fractal branching rules to describe a fractal tree canopy, was fulfilled at branching orders with link diameters >1.5 cm. The proportionality ration q for branching patterns of all tree species was constant at all scales. The proportion of q values >0.9 (fq) was 0.8 for all species. Mean fractal dimension (Dfract) values (1.5?1.7) for all species showed that branching patterns had an increasing magnitude of intricacy. Since Dfract values were ≥1.5, branching patterns within species were self similar. Basal diameter (D10), proximal diameter and Dfract described most of variations in aboveground biomass, suggesting that allometric equations for relating aboveground tree biomass to fractal properties could accurately predict aboveground biomass. Thus, assessed Acacia, Gliricidia and Leucaena trees were fractals and their branching properties could be used to describe variability in size and aboveground biomass.     

Allometric models for estimation of aboveground carbon stocks in improved fallows in eastern Zambia

This paper presents allometric functions for estimation of C stocks in aboveground tree biomass in 2-year-old improved fallows in eastern Zambia. A total of 222 individual trees representing 12 tree species were destructively harvested for C analysis by LECO CHN-1000 analyzer. Allometric models relating collar diameter (D₁₀) and total tree height (H) to stem and total aboveground C stocks were developed using data from tree fallows. Logarithmically transformed power functions displayed a good ability to stabilize variance of aboveground C stocks and showed a good fit (84 < R ² < 99) with a bias of 0.7–3.6%. D₁₀ alone and in combination with H explained most of the variability in total aboveground C stocks. Validation of the species-specific and generalized models with field data indicated that they accurately predicted aboveground tree C stocks. Generalized C estimation functions were also validated and described 73–97% of variability in aboveground C stocks with an average unsigned deviation of 1.5–4.9%. The C functions will serve as a vital tool for predicting and monitoring C pool sizes in long-term studies and agroforestry projects, especially where destructive sampling is not possible.