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ArticleYield prediction model for falcata (paraserianthes falcataria (L.) Nielsen) in falcata-based agroforestry systems in Misamis Oriental, Philippines
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.Sustainable adaption of Falcata-based agroforestry systems and improve tree component productivity in Misamis Oriental necessitates derivation of quantitative information on yield. The project was conducted to determine the yield of Falcata planted in agroforestry systems considering various stand characteristics, physiographic characteristics, cultural practice, and pest incidence. A total of 360 rectangular temporary sample plots (1000 m2 or 20 m x 50 m) across 3 cities and 15 municipalities were established. Diagnostic tests, correlation analysis, and multiple regression analysis were used to develop the Falcata yield, prediction model. The result showed that the yield of Falcata under woodlot, boundary planting, alley cropping, multistorey, intercropping, and taungya agroforestry systems can be explained by age, merchantable height, site index, and spacing. The final yield model for Falcata is sqrtVolume (m3) = 0.1841444 - 10.42376*1/SI + 0.0029367*SP + 0.0842593*A + 0.0473169*MH. The newly developed model will serve as a guide in decision-making as to the right time to harvest, appropriate density, a suitable site for the establishment, and the right merchantable height for greater productivity. Keywords: Falcata, agroforestry, yield, volume, model ID: 3623089 -
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 -
ArticleAllometric models for estimating above ground biomass of Bambusa tulda Roxb. and Melocanna baccifera (Roxb.) Kurz
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.Allometric equations are used to estimate the biomass and carbon stock of forests. There is a dearth of species- specific allometric equations for bamboos growing in Bangladesh. Bambusa tulda and Melocanna baccifera are the two most common bamboo species of commercial importance in Bangladesh. This study reports allometric equations for estimating biomass of bamboo compartments (leaf, branches, and stem) and total above-ground biomass. Data was collected from natural bamboo forests of different locations of Khagrachhari district. A total of 50 bamboos (25 B. tulda and 25 M. baccifera) were sampled following the destructive method. Bamboo leaf, branch, and stem were measured for fresh weight in the field. Sub-samples were collected in sufficient amounts and processed in the laboratory for density and oven-dry weight to derive fresh to oven-dry weight ratio. Commonly used 10 candidate equations were tested using Diameter at Breast Height (DBH), diameter at base (D5), and height (H) as explanatory variables to find the best fitted allometric equation. In total, the study developed 60 models with 10 for each component of the two species. Applying the goodness-of-fit statistics, 4 best-fitted models were selected for estimating stem and total above-ground biomass (TAGB) of the two bamboo species. The best fit allometric biomass models for M. baccifera were, Ys = 0.398*DBH1.542 and Yt = 0.627*DBH1.382, where, Ys = stem biomass and Yt = total above-ground biomass. On the other hand, best fit allometric biomass models for B. tulda were, Ys = 0.041*DBH1.0658*H1.2311, and Yt = 0.235*D5 1.867, where, D5 is diameter at the base (5 cm above the ground). The relationship between the biomass and dendrometric variables in the form of best-fitted models was statistically significant at p < 0.05 levels. The allometric models developed by this study will be useful for better estimation of biomass and sequestered carbon in the plain land homestead forests of Bangladesh. Keywords: Khagrachhari, Bamboo, Carbon sequestration, Bambusa tulda and Melocanna baccifera ID: 3623846
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