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ArticleAllometric equation for estimating tree above ground biomass modified by ecological environmental factors in tropical dipterocarp forests
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.Tropical Dipterocarp Forest (DF) plays an important role in mitigating climate change thanks to its carbon sequestration capacity. In order to estimate the CO2 absorption capacity of DF as a basis for the development of forest ecological services, a system of biomass equations is needed; while very few models for estimating biomass in DF have been published and have not yet reflected the impact of ecological environmental factors. The purpose of the study was to validate and select the best model for estimating tree above ground biomass (AGB, kg) in DF under the influence of ecological environmental factors, thereby improving the reliability. Twenty-eight 0.25 ha plots in the Central Highlands and one 1 ha plot in the Southeast ecoregion in Viet Nam were measured. A total of 329 trees were destructively sampled to obtain a dataset of AGB; Methods for developing equations were weighted nonlinear fixed/mixed models with/without random effects fit by Maximum Likelihood; Using K-fold cross validation with K = 10, we compared and selected the best model with and without ecological environmental factors. As a result, separate ecological environmental factors did not affect AGB, while the combination of the factors influences the AGB model through the form: AGB = AVERAGE × MODIFIER, AGB = a × Db ×WDd × exp (e2 × (P - 1502) + e3 × (BA - 12.62)) that was significantly more reliable than a model without these factors involved; where D (cm), WD (g / cm3), P (mm year-1) and BA (m2 ha-1) are the diameter at breast height, wood density, averaged annual rainfall and total basal area of forest stand, respectively. Keywords: above ground biomass, dipterocarp forest, ecological factor ID: 3473259 -
ArticleTree-biomass-carbon estimation in the coastal afforestation sites of Chittagong, Bangladesh
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.Global climate is changing relentlessly due to anthropogenic greenhouse gas emissions into the atmosphere. Its impacts are globally visible now. Bangladesh is the worst-affected country in the world due to this climate change. Coastal afforestation, among several forestry options, is critical to climate change mitigation and adaptation. This study estimated the tree biomass growth and its carbon in the Kattoli and Parki beach under the Chittagong coastal forest division. The study estimated that the total biomass density of Acacia auriculiformis, Acacia nilotica, Avicennia officinalis, Casuarina equisetifolia, Samanea saman, Sonneratia apetala and Terminalia arjuna were 131.57±6.77, 116.96±6.41, 350.64±7.99, 296.47±9.46, 119.27±7.45, 154.86±4.78 and 117.11±9.68 tha-1, respectively, with the mean annual increment of 65.79±3.38, 58.48±3.20, 15.25±0.35, 33.15±1.60, 59.63±3.73, 6.45±0.11 and 58.55±4.84 tha-1 yr-1, respectively. Furthermore, the total biomass-carbon of each species was also estimated, which were 65.79±3.38, 58.48±3.2, 175.32±3.10, 148.23±4.73, 59.63±3.73, 77.43±2.39 and 58.55±4.84 tCha-1 for the respective species, respectively, with the mean annual increment of 32.89±1.69, 29.24±1.60, 7.62±0.17, 16.57±0.80, 29.82±1.86, 3.23±0.10, 29.28±2.42 tCha-1 yr-1, respectively. All the findings of the study indicate that afforestation with both mangrove and non-mangrove species along with the coastal belts in Chittagong has the potential to mitigate climate change. The results can be useful for climate change mitigation practitioners, researchers, and policymakers on a native and broad scale. Keywords: Tree species; Coastal plantation; Carbon sequestration; Aboveground biomass; Belowground biomass ID: 3474035 -
ArticleDeveloping simultaneously modeling systems for improving the reliability of tree aboveground biomass- carbon and its components estimates for Machilus odoratissimus nees in the central highlands, Viet Nam
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.Machilus odoratissimus Nees is a multi-purpose species with, high economic value and environmental protection, so this tree species is commonly used in agroforestry models. In plantation management, it demands modeling systems that predict accurately aboveground biomass- carbon and its components. At the same time, the developed models support computing carbon accumulation of forest trees in agroforestry models for the program of reducing emissions from deforestation and forest degradation (REDD). Twenty-two 300 m2 plots were measured within the full range of 1 to 7 ages in the Central Highlands of VietNam. A total of 22 quadratic mean diameter trees were destructively sampled to obtain a dataset of the dry iomass/carbon of the stem (Bst/Cst), bark (Bba/Cba), branches (Bbr/Cbr), leaves (Ble/Cle), and total tree aboveground biomass/carbon (AGB/AGC). We examined the performance of weighted nonlinear models fit by maximum likelihood and weighted nonlinear seemingly unrelated regression (SUR) fit by generalized least squares for predicting tree aboveground biomass- carbon and its components. The simultaneous estimation of AGB/AGC and its components produced a higher reliability than that of the models of tree components and the total developed separately. The selected forms of modeling systems were AGB = Bst + Bba + Bbr + Ble = a1×(D2H)b1 + a2×(D2H)b2 + a3×Db3 + a4×(D2H)b4 and AGC = Cst + Cba+ Cbr + Cle = a1×(D2H)b1 ++2×(D2H)b2 + a3×Db3 + a4×(D2H)b4 (where D is the diameter at breast height and H is the height of the tree). Keywords: Agroforestry, Machilus odoratissimus, seemingly unrelated regression (SUR), tree biomass- carbon ID: 3472953
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