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Indonesian Journal of Forestry Research
Vol 1, No 2 (2014): Indonesian Journal of Forestry Research
ALLOMETRIC EQUATIONS FOR ESTIMATING ABOVE GROUND BIOMASS IN PAPUA TROPICAL FOREST
Maulana, Sandhi Imam ( Forestry Research Institute at Manokwari-Forestry Research and Development Agency Jl. Inamberi, Susweni PO BOX 159, Manokwari 98313-Papua Barat)
Article Info   ABSTRACT
Published date:
31 Oct 2014
 
Allometric equations can be used to estimate the biomass and carbon stock of the forest. However, so far the allometric equations for commercial species in Papua tropical forests have not been appropriately developed. In this research, allometric equations are presented based on the genera of commercial species. Few equations have been developed for the commercial species of Intsia, Pometia, Palaquium and Vatica genera and an equation of a mix of these genera. The number of trees sampled in this research was 49, with diameters (1,30 m above ground or above buttresses) ranging from 5 to 40 cm. Destructive sampling was used to collect the samples where Diameter at Breast Height (DBH) and Wood Density (WD) were used as predictors for dry weight of Total Above-Ground Biomass (TAGB). Model comparison and selection were based on the values of F-statistics, R-sq, R-sq (adj), and average deviation. Based on these statistical indicators, the most suitable model for Intsia, Pometia, Palaquium and Vatica genera respectively are Log(TAGB) = -0,76 + 2,51Log(DBH), Log(TAGB) = -0,84 + 2,57Log(DBH), Log(TAGB) = -1,52 + 2,96Log(DBH), and Log(TAGB) = -0.09 + 2,08Log(DBH). Additional explanatory variables such as Commercial Bole Height (CBH) do not really increase the indicators’ goodness of fit for the equation. An alternative model to incorporate wood density should  be considered for estimating the above ground biomass for mixed genera.  Comparing the presented mixed-genera equation; Log(TAGB) = 0,205 + 2,08Log(DBH) + 1,75Log(WD), R-sq: 97,00%, R-sq (adj): 96,90%, F-statistics 750,67, average deviation: 3,50%; to previously published data shows that this local species-specific equation differs substantially from previously published equations and this site-specific equation is  considered to give a better estimation of biomass.
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