Alometria de Árvores e Biomassa Florestal na Amazônia Sul-Ocidental
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 r...
| Autor principal: | Melo, Antonio Willian Flores de |
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| Grau: | Tese |
| Idioma: | por |
| Publicado em: |
Instituto Nacional de Pesquisas da Amazônia – INPA
2020
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| Assuntos: | |
| Acesso em linha: |
https://repositorio.inpa.gov.br/handle/1/4997 http://lattes.cnpq.br/9339997282776018 |
| Resumo: |
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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. |