Banca de QUALIFICAÇÃO: LORRAYNE APARECIDA GONÇALVES

Uma banca de QUALIFICAÇÃO de DOUTORADO foi cadastrada pelo programa.
DISCENTE : LORRAYNE APARECIDA GONÇALVES
DATA : 30/09/2024
HORA: 10:00
LOCAL: Remoto
TÍTULO:

Environmental and climatic drivers of forest structure and biomass stocks in the Amazon

PALAVRAS-CHAVES:

environmental predictors; climate change; carbon stocks; basal area; large trees

PÁGINAS: 55
GRANDE ÁREA: Ciências Biológicas
ÁREA: Ecologia
RESUMO:

The Amazon rainforest is the largest tropical forest in the world, plays a crucial role in maintaining biodiversity and global climate stability, and has great biological and environmental heterogeneity. Several ecological and historical factors interact to determine the structure of the Amazon rainforests. The main objective of this thesis was to investigate how climatic, edaphic, and topographic factors interact with the structure and aboveground biomass of the vegetation. In the first chapter, we performed a broad analysis at the pan-Amazon level using remote sensing data to understand the influence of the 14 predictors on height and aboveground biomass. We extracted information for 4000 100 ha buffers, employed Random Forest to test two hypotheses related to climate and natural disturbances, and used the models to predict vegetation structure considering the effects found. In the second chapter we sought to understand how these environmental factors are related to the structure and biomass of large trees in the Amazon. For this purpose, we used data from 30 sampling sites distributed across seven municipalities in the western part of the state of Pará in Brazil, created grids between 40 and 50 ha, and applied linear models relating the predictors to stem height, individual density, basal area, and aboveground biomass. In both chapters, we found a complex interaction between climate, soil, and topography, modulating forest structure and aboveground biomass stocks. The maximum accumulated water deficit, slope, and elevation of the terrain were important predictors, both in the large-scale analysis and for large trees. Variables related to precipitation and temperature were also important for both scales of analysis as well as soil granulometry, nutrition, and acidity properties. The incidence of lightning and strong winds were important predictors of tree height and biomass on a regional scale. These results contribute to the understanding of the heterogeneity in forest structure and its main predictors, and contribute to studies on the resilience of forests to climate change.

MEMBROS DA BANCA:
Presidente - 996.005.011-49 - DIVINO VICENTE SILVÉRIO - UnB
Externa à Instituição - 080.407.636-73 - LUDMILA RATTIS - UNICAMP
Externa à Instituição - MARCIA NUNES MACEDO - IPAM