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Title: Aboveground biomass allometric models for large trees in southwestern Amazonia
Keywords: Brazil
Amazon forest
Tropical forest
Forest management
Carbon stock
Global warming
Climate change
Issue Date: Sep-2022
Publisher: Elsevier
Citation: ROMERO, F. M. B. et al. Aboveground biomass allometric models for large trees in southwestern Amazonia. Trees, Forests and People, [S.l.], v. 9, p. 1-13, Sept. 2022. DOI: 10.1016/j.tfp.2022.100317.
Abstract: Most of the basal area in Amazon forest is in large trees, many of which are species of interest for forest management. In forest management these trees are divided into the commercial bole that is harvested for wood production and the stump and crown that are left in the forest where they decompose and emit CO2 over a period of years. Part of the commercial bole is converted to wood products that store carbon according to their durability. The quantification of these components is difficult due to their size, especially in the case of the crown, which causes uncertainties in the estimates of biomass and carbon. Our study estimated the aboveground biomass and carbon of 223 trees and subsequently fit allometric equations to these estimates. Aboveground biomass was calculated from stem volume, wood density and a biomass expansion factor, while total carbon stock estimates used carbon content determined in the laboratory. Linear models (log-transformed) were tested to derive the best-fit allometric model for total aboveground biomass and carbon. The best-fit allometric models used squared tree diameter, tree height, and wood density for biomass, whereas the best carbon model also used carbon content. Our models were more efficient in estimating biomass than were frequently used regional and pan-tropical models. Our equations allow reducing the errors in estimates of forest biomass and carbon stocks, in addition to allowing estimation of the amount of carbon emitted after harvest, although the other models also had good fits and can be used according to the criteria of each researcher and the availability of data.
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