Allometric equations for predicting aboveground biomass of beech-hornbeam standsin the Hyrcanian forests of Iran

Vahedi, A. A.; Mataji, A A; Babayi-Kafaki, S.; Eshaghirad, J; Hodjati, Seyed Mohammad; Djomo, Adrien N.

doi:10.17221/39/2014-jfs

Cited by 38 publications

(24 citation statements)

References 38 publications

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“…These results were similar to those of Mamadou Laminou [16] who has shown that the best model for predicting leaves biomass of eight (8) plant species of the wet Ngaoundere savannah was the equation 4 model with RSE = 0.53, AIC = 43.3 and R 2 adj = 0.640. Contrary, these results differed from those of Djomo et al [12] and Vahedi et al [51].…”

Section: Discussioncontrasting

confidence: 93%

Allometric Equations for Predicting Biomass of <i>Daniellia oliveri</i> (Rolfe) Hutch. & Dalz. Stands in the Sudano-Guinea Savannahs of Ngaoundere, Cameroon

Alexandre¹,

Adamou²,

Tchobsala³

et al. 2019

EEB

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Allometric relationships for estimating biomass of Daniellia oliveri (Rolfe) Hutch & Dalz. stand were investigated in the sudano-guinea savannah of Ngaoundere, Cameroon. A total of 17 individual trees from Daniellia oliveri were harvested in Bini-Dang savannah across a range of diameter classes, from 5 to 40 cm. Diameter at breast height (D) and total height (H) were determined and considered as predictor variables, while total above-ground biomass, stem, branch, leaf and root biomass were the output variables of the allometric models. Among many models tested, the best ones were chosen according to the coefficient of determination adjusted (R 2 adj), the residual standard error (RSE) and the Akaike Information Criteria. The main results showed that the multiplication of tree H with D in the allometric equation did not improve in the degree of fitness of the allometric equations, except for leaf biomass. The fit allometric biomass of Daniellia oliveri model for leaf, branch, stem and root biomass and above ground biomass were the follow: Ln(Bl)= 3.0303 + 0.744*Ln(D 2 H); Ln(Bb) = 3.772 + 2.701*Ln(D); Ln(Bs) = 2.663 + 2.218*Ln(D), Ln(Br) = 2.072 + 1.920*Ln(D) and Ln(Bt) = -2.089 + 2.374*Ln(D) respectively. The root biomass represented on average 28% of the total aboveground biomass and these two biomasses were positively and significantly correlated (r = 0.93, p ˂ 0.05 and n = 11). For the Daniellia oliveri stands studied, the diameter at breast height (D) alone showed a very strong accuracy of estimation. It is concluded that the use of tree height in the allometric equation can be neglected for the species, as far as the present study area is concerned. Therefore, for estimating the biomass of Daniellia oliveri, the use of D as an independent variable in the allometric equation with a power equation would be recommended. The paper describes details of tree biomass allometry, which is important in carbon stock, sylviculture and savannah management.

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Section: Discussioncontrasting

confidence: 93%

Allometric Equations for Predicting Biomass of <i>Daniellia oliveri</i> (Rolfe) Hutch. & Dalz. Stands in the Sudano-Guinea Savannahs of Ngaoundere, Cameroon

Alexandre¹,

Adamou²,

Tchobsala³

et al. 2019

EEB

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“…The present study suggests that if diameter at breast height is available, a relative simple equation could be used to predict tree age. Trunk diameter is often the best predictor for age in allometric models, because both variables are strongly correlated [74], it is a relatively easy and inexpensive measurement to obtain, and is often available in forest inventory data [75]. In fact, growth estimates of forest trees are typically made by using measurements of diameter at breast height and of total height, which are scaled to the whole tree via allometric equations derived from destructive sampling [4,76].…”

Section: Dendrometry and Dendrochronologymentioning

confidence: 99%

Linking Dendrometry and Dendrochronology in the Dominant Azorean Tree Laurus azorica (Seub.) Franco

Matos

Silva

Camarinho

et al. 2019

Forests

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As in many archipelagos, the Azorean primary forest was largely cleared and replaced by secondary forest and grassland, the Azorean tree Laurus azorica (Seub.) Franco being one of the dominant trees in the remaining natural forests. Dendrochronological and dendrometric studies in the Azores mainly focused on non-indigenous trees, either used for timber (e.g., Cryptomeria japonica D. Don) or considered as invasive (Pittosporum undulatum Vent.). Therefore, this study aims to describe the growth ring anatomy of L. azorica, and to understand the relationship between dendrometric traits (e.g., trunk diameter at breast height; tree height), and the number of growth rings. Growth ring anatomy was accessed by wood anatomical preparation of microcore samples while tree age estimation was based on growth ring counts in wood cores taken at breast height and at base. A total of 145 trees were sampled, resulting in 262 increment cores, at six representative stands of laurel forest in São Miguel Island (Azores). The wood anatomical analysis confirmed the presence of clear annual ring boundaries, and a high structural similarity towards Laurus novocanariensis Rivas Mart., Lousã, Fern.Prieto, E.Días, J.C.Costa & C.Aguiar. Age at tree base averaged 33 years, with 60% of the trees between 25 and 50 years old, and only about 15% above 50 years old. This suggests the existence of a secondary forest that is more recent than expected, probably due to human disturbance. The allometric models showed best fit when calculated by stand, suggesting the effect of local environmental conditions on growth rate. Radial growth rate was estimated at 0.68 cm.year−1. Given the known dominance of this species and the threats affecting natural forests, this baseline study will allow a better understanding of forest distribution and dynamics, and support a more effective forest management approach.

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“…Perennial grasses can be grown by ratooning, a form of zero-tillage harvest that leaves roots and soil undisturbed, and can rapidly increase soil organic C while providing high biomass yields (Matsuoka and Stolf, 2012; Sumiyoshi et al, 2016). Many generalized models predict biomass and C stock in forestry and agroforestry systems (Nair et al, 2009; Chave et al, 2014; Vahedi et al, 2014; Ali et al, 2015; Kuyah and Rosenstock, 2015; Kuyah et al, 2016; Mganga, 2016), but only a few equations have been developed for non-forest crops (Navar et al, 2004; Nafus et al, 2009; Martin et al, 2013; Fard and Heshmati, 2014; Oliveras et al, 2014). However, Martin et al (2013) used stalk base D, stalk H (the length from the base stalk to the base of the forth internode) to predict stalk biomass and soluble sugar concentration of Sweet Sorghum ∗ ( Sorghum bicolor ) in Australia.…”

Section: Introductionmentioning

confidence: 99%

Allometric Models for Predicting Aboveground Biomass and Carbon Stock of Tropical Perennial C4 Grasses in Hawaii

et al. 2017

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Biomass is a promising renewable energy option that provides a more environmentally sustainable alternative to fossil resources by reducing the net flux of greenhouse gasses to the atmosphere. Yet, allometric models that allow the prediction of aboveground biomass (AGB), biomass carbon (C) stock non-destructively have not yet been developed for tropical perennial C4 grasses currently under consideration as potential bioenergy feedstock in Hawaii and other subtropical and tropical locations. The objectives of this study were to develop optimal allometric relationships and site-specific models to predict AGB, biomass C stock of napiergrass, energycane, and sugarcane under cultivation practices for renewable energy and validate these site-specific models against independent data sets generated from sites with widely different environments. Several allometric models were developed for each species from data at a low elevation field on the island of Maui, Hawaii. A simple power model with stalk diameter (D) was best related to AGB and biomass C stock for napiergrass, energycane, and sugarcane, (R2 = 0.98, 0.96, and 0.97, respectively). The models were then tested against data collected from independent fields across an environmental gradient. For all crops, the models over-predicted AGB in plants with lower stalk D, but AGB was under-predicted in plants with higher stalk D. The models using stalk D were better for biomass prediction compared to dewlap H (Height from the base cut to most recently exposed leaf dewlap) models, which showed weak validation performance. Although stalk D model performed better, however, the mean square error (MSE)-systematic was ranged from 23 to 43 % of MSE for all crops. A strong relationship between model coefficient and rainfall was existed, although these were irrigated systems; suggesting a simple site-specific coefficient modulator for rainfall to reduce systematic errors in water-limited areas. These allometric equations provide a tool for farmers in the tropics to estimate perennial C4 grass biomass and C stock during decision-making for land management and as an environmental sustainability indicator within a renewable energy system.

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Allometric equations for predicting aboveground biomass of beech-hornbeam standsin the Hyrcanian forests of Iran

Cited by 38 publications

References 38 publications

Allometric Equations for Predicting Biomass of <i>Daniellia oliveri</i> (Rolfe) Hutch. & Dalz. Stands in the Sudano-Guinea Savannahs of Ngaoundere, Cameroon

Allometric Equations for Predicting Biomass of <i>Daniellia oliveri</i> (Rolfe) Hutch. & Dalz. Stands in the Sudano-Guinea Savannahs of Ngaoundere, Cameroon

Linking Dendrometry and Dendrochronology in the Dominant Azorean Tree Laurus azorica (Seub.) Franco

Allometric Models for Predicting Aboveground Biomass and Carbon Stock of Tropical Perennial C4 Grasses in Hawaii

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Allometric equations for predicting aboveground biomass of beech-hornbeam standsin the Hyrcanian forests of Iran

Cited by 38 publications

References 38 publications

Allometric Equations for Predicting Biomass of &lt;i&gt;Daniellia oliveri&lt;/i&gt; (Rolfe) Hutch. & Dalz. Stands in the Sudano-Guinea Savannahs of Ngaoundere, Cameroon

Allometric Equations for Predicting Biomass of &lt;i&gt;Daniellia oliveri&lt;/i&gt; (Rolfe) Hutch. & Dalz. Stands in the Sudano-Guinea Savannahs of Ngaoundere, Cameroon

Linking Dendrometry and Dendrochronology in the Dominant Azorean Tree Laurus azorica (Seub.) Franco

Allometric Models for Predicting Aboveground Biomass and Carbon Stock of Tropical Perennial C4 Grasses in Hawaii

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Product

Resources

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Allometric Equations for Predicting Biomass of <i>Daniellia oliveri</i> (Rolfe) Hutch. & Dalz. Stands in the Sudano-Guinea Savannahs of Ngaoundere, Cameroon

Allometric Equations for Predicting Biomass of <i>Daniellia oliveri</i> (Rolfe) Hutch. & Dalz. Stands in the Sudano-Guinea Savannahs of Ngaoundere, Cameroon