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      Allometric equations for estimating aboveground biomass of khat ( Catha edulis)-stimulate grown in agroforestry of Raya Valley, Northern Ethiopia

      research-article
      a , b ,
      Heliyon
      Elsevier
      Biomass, Carbon removal, East africa, Ethiopia, Khat plant

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          Abstract

          Khat plant ( Catha edulis Forsk) is an evergreen perennial cash crop cultivated in east Africa, southwest Arabia, and Madagascar. The plant is known for its production of stimulant fresh leaves, and expanding as expense of other land uses for its short-term financial returns. We, therefore, developed allometric equations for estimating aboveground biomass and carbon (C) removal of khat grown in farmlands of Raya Valley, Northern Ethiopia. A total of 31 plant individuals were harvested destructively on the basis of their diameters and age ranges. The equations were parametrized using biometric variables such as basal diameter ( d 10 ), diameter at breast height ( d), dominate height ( doh) and mean height ( h). Results of the analysis showed that, stem accounted for 58%, branch 32% and foliage 10% of the aboveground biomass (AGB). Commercial foliage biomass C removal ranged from 2.3 to 2.7 Mg ha −1. The power equation, AGB = b 1 ×d 10 b2 ×doh b3 , was the best (highest ranked using goodness-of-fit statistics), explaining 96% of the variation in aboveground biomass ( p < 0.01). Models comparisons showed that our best ranked equation (M6) improved the aboveground biomass estimate by 44% and 48 % that of generic and other species-site specific equations developed in the tropics, respectively. Thus, our best species-site specific equation developed in this study can accurately estimate aboveground of khat plant biomass in the study region.

          Abstract

          Biomass, carbon removal, East Africa, Ethiopia, Khat plant.

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          Improved allometric models to estimate the aboveground biomass of tropical trees.

          Terrestrial carbon stock mapping is important for the successful implementation of climate change mitigation policies. Its accuracy depends on the availability of reliable allometric models to infer oven-dry aboveground biomass of trees from census data. The degree of uncertainty associated with previously published pantropical aboveground biomass allometries is large. We analyzed a global database of directly harvested trees at 58 sites, spanning a wide range of climatic conditions and vegetation types (4004 trees ≥ 5 cm trunk diameter). When trunk diameter, total tree height, and wood specific gravity were included in the aboveground biomass model as covariates, a single model was found to hold across tropical vegetation types, with no detectable effect of region or environmental factors. The mean percent bias and variance of this model was only slightly higher than that of locally fitted models. Wood specific gravity was an important predictor of aboveground biomass, especially when including a much broader range of vegetation types than previous studies. The generic tree diameter-height relationship depended linearly on a bioclimatic stress variable E, which compounds indices of temperature variability, precipitation variability, and drought intensity. For cases in which total tree height is unavailable for aboveground biomass estimation, a pantropical model incorporating wood density, trunk diameter, and the variable E outperformed previously published models without height. However, to minimize bias, the development of locally derived diameter-height relationships is advised whenever possible. Both new allometric models should contribute to improve the accuracy of biomass assessment protocols in tropical vegetation types, and to advancing our understanding of architectural and evolutionary constraints on woody plant development. © 2014 John Wiley & Sons Ltd.
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            Tree allometry and improved estimation of carbon stocks and balance in tropical forests.

            Tropical forests hold large stores of carbon, yet uncertainty remains regarding their quantitative contribution to the global carbon cycle. One approach to quantifying carbon biomass stores consists in inferring changes from long-term forest inventory plots. Regression models are used to convert inventory data into an estimate of aboveground biomass (AGB). We provide a critical reassessment of the quality and the robustness of these models across tropical forest types, using a large dataset of 2,410 trees >or= 5 cm diameter, directly harvested in 27 study sites across the tropics. Proportional relationships between aboveground biomass and the product of wood density, trunk cross-sectional area, and total height are constructed. We also develop a regression model involving wood density and stem diameter only. Our models were tested for secondary and old-growth forests, for dry, moist and wet forests, for lowland and montane forests, and for mangrove forests. The most important predictors of AGB of a tree were, in decreasing order of importance, its trunk diameter, wood specific gravity, total height, and forest type (dry, moist, or wet). Overestimates prevailed, giving a bias of 0.5-6.5% when errors were averaged across all stands. Our regression models can be used reliably to predict aboveground tree biomass across a broad range of tropical forests. Because they are based on an unprecedented dataset, these models should improve the quality of tropical biomass estimates, and bring consensus about the contribution of the tropical forest biome and tropical deforestation to the global carbon cycle.
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              Estimating tree biomass of sub-Saharan African forests: a review of available allometric equations

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                Author and article information

                Contributors
                Journal
                Heliyon
                Heliyon
                Heliyon
                Elsevier
                2405-8440
                05 January 2021
                January 2021
                05 January 2021
                : 7
                : 1
                : e05839
                Affiliations
                [a ]Ethiopian Environment and Forest Research Institute, P.O. Box 24536, Adiss Abeba, Ethiopia
                [b ]Wondogenet Collage of Forestry and Natural Resources, Hawassa University, P.O. Box 128, Shashemene, Ethiopia
                Author notes
                []Corresponding author. meselenegash72@ 123456gmail.com
                Article
                S2405-8440(20)32681-5 e05839
                10.1016/j.heliyon.2020.e05839
                7803641
                157052f6-d64f-4a4c-961d-68ef81202683
                © 2020 The Author(s)

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 7 April 2020
                : 11 August 2020
                : 21 December 2020
                Categories
                Research Article

                biomass,carbon removal,east africa,ethiopia,khat plant
                biomass, carbon removal, east africa, ethiopia, khat plant

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