Allometric equations for biomass estimation of Enset (Ensete ventricosum) grown in indigenous agroforestry systems in the Rift Valley escarpment of southern-eastern Ethiopia

Enset (Ensete ventricosum), commonly known as false banana, is a large thick, single-stemmed, perennial herbaceous banana-like plant growing in the wild of sub-Sahara Africa, Madagascar and parts of Asia. In Ethiopia it has been domesticated and serves as a food plant. While the productivity and management of enset for food (pseudostem and corm) has been studied, little attention has been given to total biomass production and associated carbon sequestration. The objective of this study was to develop and evaluate allometric models for estimating above and belowground biomass and organic matter contents of enset grown in indigenous agroforestry systems in Rift Valley escarpment of south-eastern Ethiopia. Biomass harvesting of 40 plants was carried out at altitudes from 1900 to 2400 m.a.s.l. The mean plant dry weight was 9.4 ± 0.84 kg and organic matter content 94 %. Pseudostem biomass accounted for highest (64 %) of total biomass, followed by corm (24 %) and foliage (12 %). Basal diameter (d ₁₀) was the best predictor variable for total and all biomass components (Spearman r = 0.775–0.980, p < 0.01). The power model using d ₁₀ and height (H) (Y = 0.0007d ₁₀ ^2.571 H ^0.101; R ² = 0.91) was found to be the best performing model (highest ranking over six good-of-fit statistics) for predicting total biomass. Model performance decreased in the order pseudostem > corm > foliage biomass. The models presented can be used to accurately predict biomass and organic matter of enset in the agroforestry systems of Rift Valley escarpments Ethiopia.     

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.     

Allometric equations for estimating the foliage biomass of Scots pine

The research described in this paper was performed in the Niepolomice Forest (Southern Poland) in 2001 as part of the Forest Environmental Monitoring and Management System (FOREMMS; 5FP IST) project. The material for the present study consisted of the measurement results of the biomass of Scots pine shoots with needles and needles alone carried out on 113 felled sample trees. The purpose of this study was to construct empirical equations for estimating the foliage biomass of Scots pine from easy to measure parameters. To achieve this aim, the dependence of the foliage biomass of Scots pine on stem diameter, height, age, crown length, basal area increment of the trees was analyzed. Using the biometric characteristics such as: tree diameter at breast height (dbh), basal area increment, age, height, and crown length empirical equations for estimating the foliage biomass of Scots pine reasonably precisely have been established. The created empirical equation gives accurate foliage biomass estimates. The explained variability varies between 65 and 85%, it depends on the number of variables applied in the equation. The equations presented in this paper were created with a view to their possible use in ecological studies where biomass quantity may be used, for example, in modeling carbon circulation in the forest ecosystem. From the point of view of forestry practice, these equations may help to assess biomass production in Scots pine stands.     

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.     

Potential of indigenous multistrata agroforests for maintaining native floristic diversity in the south-eastern Rift Valley escarpment, Ethiopia

Most studies undertaken in the field of agroforestry have focussed on system design, soil fertility management, and system interactions. Less emphasis has been placed on biodiversity aspects. The aim of this study is to investigate the potential of indigenous, multistrata agroforests for maintaining native woody species diversity in the south-eastern Rift Valley escarpment, Ethiopia. A total of 60 farms, representing three agroforest types (enset-AF, enset-coffee-AF and fruit-coffee-AF), were randomly selected along altitudinal gradients. Enset (Ensete ventricosum) is a perennial, herbaceous monocarpic banana-like plant which serves as a food plant in Ethiopia. The three agroforests are results of the domestication of natural forests and intensification of the landuse systems centuries ago. Sample-based assessment protocols were employed to place sample quadrats and to measure all individuals in the quadrats. A total of 58 woody species, belonging to 49 genera and 30 families, was recorded. Of all woody species identified, 86% were native. The highest proportion of native woody species was recorded in enset-AF (92%), followed by enset-coffee-AF (89%) and fruit-coffee-AF (82%). Among native tree species, Millettia ferruginea and Cordia africana were the most widespread. In all, 22 native woody species were recorded as of interest for conservation, acccording to IUCN Red lists and local criteria. Among them, Pygeum africanum and Rhus glutinosa were categorised as vulnerable in the wild, and in need of conservation priority. The introduction of non-native fruit trees in agroforests can be a threat to maintenance of native woody species. Management strategies favoring enset and coffee will also put other native tree species at risk. A smaller number of native woody species was recorded in fruit-coffee-AF, but a higher mean basal area and stem number. The mean basal area and stem number ranged from 5.4?±?0.5 to 11.7?±?1.0?m^2?ha^?1 and 625?±?84 to 1,505?±?142 stems?ha^?1, respectively. Altitude explained 68 and 71% of the variation in species richness and abundance, respectively. Finally, it is concluded that recognition of the indigenous agroforestry system as an option for maintaining native woody species should be given more attention, to counteract the local threat of these species from the wild.     

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).     

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Functions for estimating aboveground biomass of birch in Norway

A suite of regional allometric aboveground biomass functions were derived for Betula pubescens and Betula pendula for Norwegian conditions. The data consisted of 67 trees sampled throughout Norway. A total of 14 component functions were developed for total aboveground, total stem, stemwood, stem bark, live crown, live branch, leaf, and dead branch biomass using combinations of diameter at breast height and height as predictor variables. Application of the derived functions to existing local southern Norwegian mountain birch and regional Swedish biomass datasets indicated an overall good predictive ability of the developed functions. However, the functions produced slight underestimates, suggesting that the respective birch populations had differing biomass allocation patterns. When the developed functions were applied to Norwegian National Forest Inventory data, they produced slightly higher biomass stock and stock change estimates than what is obtained using existing Swedish functions. The higher estimates were evident in the north, central, and western part of Norway, while estimates were similar in southeastern Norway where growing conditions are most similar to Swedish conditions. The analysis indicates that the derived functions are the best available for regional birch biomass stock and stock change estimation in Norway.     

Integrating regional climate change into allometric equations for estimating tree aboveground biomass of Masson pine in China

Key message

A climate-sensitive aboveground biomass (AGB) equation, in combination with nonlinear mixed-effects modeling and dummy variable approach, was developed to examine how climate change may affect the allometric relationships between tree diameter and biomass. We showed that such changes in allometry need to be taken into account for estimating tree AGB in Masson pine.

Context

As a native species and being widely distributed in subtropical China, Masson pine (Pinus massoniana Lamb.) forests play a pivotal role in maintaining forest ecosystem functions and mitigation of carbon concentration increase at the atmosphere. Traditional biomass allometric equations do not account for a potential effect of climate on the diameter–biomass relationships. The amplitude of such an effect remains poorly documented.

Aims

We presented a novel method for detecting the long-term (2041–2080) effects of climate change on the diameter–biomass relationships and the potential consequences for long-term changes of biomass accumulation for Masson pine.

Methods

Our approach was based on a climate-sensitive AGB model developed using a combined nonlinear mixed-effects model and dummy variable approach. Various climate-related variables were evaluated for their contributions to model improvement. Heteroscedasticity was accounted for by three residual variance functions: exponential function, power function, and constant plus function.

Results

The results showed that diameter at breast height, together with the long-term average of growing season temperature, total growing season precipitation, mean temperature of wettest quarter, and precipitation of wettest quarter, had significant effects on values of AGB. Excessive rain during the growing season and high mean temperature in the wettest quarter reduced the AGB, while a warm growing season and abundant precipitation in the wettest quarter increased the AGB.

Conclusion

Climate change significantly affected the allometric scale of biomass equation. The new climate-sensitive allometric model developed in this study may improve biomass predictions compared with the traditional model without climate effects. Our findings suggested that the AGB of Masson pine trees with the same diameter at breast height under three climate scenarios including representative concentration pathway (RCP) 2.6, RCP 4.5, and RCP 8.5 in the future period 2041–2080 would increase by 24.8 ± 32.7% (mean ± standard deviation), 27.0 ± 33.4%, and 27.7 ± 33.8% compared with the constant climate (1950–2000), respectively. As a consequence, we may expect a significant regional variability and uncertainty in biomass estimates under climate change.

     

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 for aboveground biomass estimation by size class for Pinus brutia Ten. trees growing in North and South Aegean Islands, Greece

Empirical allometric equations relating biomass of aboveground components to dendrometric variables for Pinus brutia Ten. trees are derived in this paper. They are based on data collected from Lesvos (North Aegean Sea) and Crete (South Aegean Sea) Islands. Comparisons to published equations for the same species growing in northwestern and southeastern Turkey, for Pinus nigra A. growing in Turkey and Pinus halepensis Mill. found in Western Aegean (island of Evia), are also presented. The biomass of branches from destructively sampled trees (twelve in Crete and six in Lesvos) was divided into four size classes (0?C0.63 cm, 0.64?C2.5 cm, 2.51?C7.61 cm, and 7.62?C22.8 cm). Tree crown biomass was calculated as the sum of the biomass in the four classes plus the fraction of stem above crown base. Over bark stem biomass was estimated through bole volume conversion based on wood density. The results showed clearly that, for a given diameter, the Cretan trees had more crown biomass and a higher share of small branches than trees on Lesvos, probably due to differences in environment and stand structure. Comparisons to published diameter versus crown biomass equations reveal a lower crown biomass for Turkish sites of Calabrian pine and Aleppo pine on Evia Island, while only Turkish Black pine seems to be comparable to the Calabrian pine on Crete. The derived allometries can be used for landscape fire behavior modeling, for ecophysiological studies and for the Kyoto protocol requirements of carbon changes in Pinus brutia Ten. forests located in northern and southern Greek sites.     

Allometric equations for biomass estimations in Cameroon and pan moist tropical equations including biomass data from Africa

Moist tropical forests in Africa and elsewhere store large amounts of carbon and need accurate allometric regressions for their estimation. In Africa the absence of species-specific or mixed-species allometric equations has lead to broad use of pan moist tropical equations to estimate tree biomass. This lack of information has raised many discussions on the accuracy of these data, since equations were derived from biomass collected outside Africa.     

Generalized biomass equations for the main aboveground biomass components of maritime pine across contrasting environments

• Introduction   

In order to predict the biomass of aerial components of maritime pine stands (Pinus pinaster Ait.), generalized allometric equations were developed using data collected from the southern and northern margins of its geographical area.     

Allometric biomass equations for tree species used in agroforestry systems in Uganda

Estimates of above-ground biomass are required for better planning, sustainable management and monitoring of changes in carbon stocks in agroforestry systems. The objective of this study was to develop and compare biomass equations for Markhamia lutea, Casuarina equisetifolia, Maesopsis eminii and Grevillea robusta grown in a linear simultaneous agroforestry system in Uganda. These species were established in single rows in the middle of fields in 1995 from four-month old seedlings. A total of 57 trees were sampled for this study, 13 for M. lutea, 12 for C. equisetifolia, 16 for M. eminii and 16 for G. robusta. Biomass values of the various tree components (stem, branches and foliage) as well as the total above-ground biomass were fitted to linear and non-linear allometric models using total height, diameter-at-breast height (DBH), crown width as predictor variables. Although both DBH and height are typically used as independent variables for predicting above-ground biomass, the addition of height in biomass equations did not significantly improve model performance for M. eminii, M. lutea and G. robusta. However, addition of height significantly increased the proportion of variation explained in above-ground biomass for C. equisetifolia, while DBH did not significantly improve the prediction of biomass. The study confirmed the need for developing species-specific biomass equations.     

Allometric tree biomass models of various species grown in short-rotation agroforestry systems

Biomass equations for tree species and the early stages of growth used in short-rotation coppices and agroforestry systems are still lacking. Further, discussion about the structure and parameters of biomass equations are still ongoing. Yield estimations should be precise, while keeping efforts low. To determine the influence of tree species, farming system, and tree position (inner and outer row) on allometric relationships, we derived biomass equations for various tree species from organic and conventional silvoarable agroforestry systems with an alley-cropping configuration. The allometric equations were based on the power relationship between aboveground dry biomass and stem base diameter (SBD) as a single variable or in combination with tree height (H) and were calculated by log-linear mixed-effect regression. Equations span the third and fourth growth year of the first rotation and were validated on the fourth year. Neither farming system nor row position influenced allometric relationship, although biometric variables varied between trees from inner and outer rows. A general model across species explained 95% (\(R_{\text{cond}}^{2}\)) of the variation for tree dry weight or 97% (\(R_{\text{cond}}^{2}\)) with H as covariate. Yet, for the sake of precision, species-specific equations were necessary. The best fitting equation with only SBD as predictor had species-specific allometric factors and a general exponent across species. However, predicted yields were biased by 8–31%. Thus, functions incorporating H are recommended, as compensation for variances in height-diameter relationships due to the ontogenetic stage, site differences, or social status of the tree reduced the bias of biomass estimation (<10%).     

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.     

Intra-specific differences in allometric equations for aboveground biomass of eastern Mediterranean Pinus brutia

? Context

Biomass prediction is important when dealing for instance with carbon sequestration, wildfire modeling, or bioenergy supply. Although allometric models based on destructive sampling provide accurate estimates, alternative species-specific equations often yield considerably different biomass predictions. An important source of intra-specific variability remains unexplained.

? Aims

The aims of the study were to inspect and assess intra-specific differences in aboveground biomass of Pinus brutia Ten. and to fill the gap in knowledge on biomass prediction for this species.

? Methods

Two hundred one trees between 2.3 and 55.8 cm in diameter at breast height were sampled throughout the eastern- and southernmost natural distribution area of P. brutia, in Middle East, where it forms different stand structures. Allometric equations were fitted separately for two countries. The differences in biomass prediction at tree, stand, and forest level were analyzed. The effect of stand structure and past forest management was discussed.

? Results

Between-country differences in total aboveground biomass were not large. However, differences in biomass stock were large when tree components were analyzed separately. Trees had higher stem biomass and lower crown biomass in dense even-aged stands than in more uneven-aged and sparse stands.

? Conclusion

Biomass and carbon predictions could be improved by taking into account stand structure in biomass models.