Hydraulic properties of Amazonian trees: spatial variation and consequences for vulnerability to drought

The Amazon rainforest is the largest and most diverse tropical forest on the planet and it plays a fundamental role in global biogeochemical cycles and carbon sequestration from atmosphere. Changes on temperature and precipitation regime due climate change are likely to cause permanent disturbance in Amazon rainforest, a biome highly dependent of water availability. Studies carried in Amazonia have documented increased rates of tree mortality, reduction in forest carbon sink, and shifts on species and functional composition likely caused by on-going changes in climate. As temperature and the frequency of droughts are predicted to continue increasing in future is fundamental to understand how the water stress caused by these impacts will affect tree species in the Amazon. In this thesis I aimed to enhance the understanding of the sensitivity and vulnerability of Amazonian trees to drought by combining an extensive long-term tree monitoring database with in-situ experiments carried along a wide precipitation gradient. Firstly, I showed how tree hydraulic traits, therefore drought vulnerability vary across Amazonian forests, with site water availability, soil texture and biogeographic regions being the main contributors of this variation. Secondly, I showed that hydraulic traits are related with changes in aboveground biomass changes at community level (Chapter 2). In Chapter 3 I found that there is phylogenetic signal for embolism resistance, being Fabaceae an especially resistant clade. I further used this information to create a map of embolism resistance across 582 Amazonian tree communities distributed in the whole domain. Finally, I showed how embolism resistance and hydraulic safety margins are related to species biogeographical distribution, life history characteristics and drought induced mortality. Overall, this thesis assessed the variation of the hydraulic traits across Amazonian forests and among tree taxa, as well as validated the predictive power of Amazonian hydraulic traits over forest dynamics.