Alometria de Árvores e Biomassa Florestal na Amazônia Sul-Ocidental

Abstract

The world’s tropical forests, and the Amazonian Forest in particular, play an important role because they store between 193 ± 58 Pg and 228 ± 12 Pg of carbon and are facing intensive conversion to other land uses. There is a high level of uncertainty related to the quantification of this carbon reservoir and its emissions, in part due to the low density of field samples to characterize the natural variability. This research aimed to develop allometric equations for estimating total above and below-ground dry biomass for both trees and bamboo, apply these equations on forest inventory data, and test methods of extrapolation of the estimates to the landscape through remote sensing information. In order to adjust the allometric equations, we used the direct compartment method, roots (thin 2 mm < ∅ < 5 cm and thick ∅ ≥ 5 cm), trunks, branches (thin ∅ < 10 cm and thick ∅ ≥ 10 cm) and leaves of 190 trees with diameters varying between 5 and 92 cm; and 206 bamboo individuals (Guadua weberbaueri), subdivided in below- (roots) and above-ground (stems, branches and leaves) biomass. The basic wood density was determined in three trunk positions and in thick branches (∅ ≥ 10 cm) in 81 trees of different species with diameters varying between 11 and 90 cm. To determine forest biomass from remote sensing data, methods and density of LiDAR points were tested. The results showed that the allometrics patterns for estimating tree biomass in the Southwestern Amazon are different from other sampled regions in the Amazon. This fact may be related to lower tree height and wood density and higher water content in the fresh biomass. Were tested eight allometric models to estimate below-ground, above-ground and total biomass of individual trees in primary forest. Considering accuracy, practicality and costs, the use of the simple power equation involving only diameter (AGB tree = a × D b ) presented the best performance to estimate forest biomass. Bamboo biomass is an important component of the forest carbon cycle in a considerable part of the Southwestern Amazon. Were found a low allometric relation between bamboo dried biomass and its stalk diameter and height, a result distinct to those found by other authors, suggesting that there are different allometric patterns among the bamboo populations in this part of the Amazon. For the Amazon rainforest, an environment of low topographic variability, it is recommended the use of LiDAR point clouds with a density ≥ 2 m −2 to generate forest structure metrics and biomass estimation. To increase sample density is fundamental to improve the accuracy of forest biomass estimates. However, in order to contemplate spatial variability and access a large territorial extensions ecosystem such as the Amazonia, it is necessary to combine field data with remote sensing data as LiDAR. Open forests (+200,000 km 2 ) in the southwestern Amazonia are significantly different from forests in other regions of the Amazon. These differences can lead to disparities of up to 35 % in estimated forest biomass and consequently in carbon stocks and fluxes between forests and the atmosphere. To improve the accuracy of forest biomass estimates via LiDAR, consideration should be given to: (1) The quantity and size of the calibration plots; (2) the density of LiDAR points; and (3) the computation method.

Keywords: forest biomass. allometric equations. LiDAR. Acre.