Environmental and climatic gradients as modulators of forest structure and biomass stocks in Amazonia
climate; environmental filters; remote sensing; soils; topography
The Amazon rainforest is the largest tropical forest in the world and is vital for maintaining
biodiversity and the global climate. It plays a crucial role in carbon storage and water cycling
and has great structural heterogeneity. The structure of the forest directly impacts factors such
as the rate of photosynthesis and the response to variations in precipitation and is modulated by
environmental factors and extreme climatic phenomena such as intense winds and lightning.
This thesis investigates how climatic, topographic and edaphic factors, as well as the frequency
of strong winds and lightning, influence height and above-ground biomass in the Pan-Amazon,
with a focus on large trees, which are the biggest contributors to biomass and the most exposed
to natural disturbances. The work is divided into two chapters. In the first, we analyze how
these factors determine the height and biomass of the Pan-Amazon, using remote sensing data
and reanalyses, with machine learning algorithms. In the second chapter, we use inventory data
of large trees to test the interactions of the predictors with height, density and biomass of this
forest component. We found clear patterns of negative influence of climatic seasonality and the
incidence of natural disturbances on the vertical structure of the forest and on above-ground
biomass stocks in the Pan-Amazon and discussed the results in the light of current climate
change and future scenarios