PS 8-107 - Assessing and characterizing plant functional types of tropical trees across a hydrological gradient in the central and eastern Amazon

Abstract: Tropical forests boast immense species diversity. As major contributors to the terrestrial carbon and water cycles, the fate of these ecosystems is crucial. Yet, due to climate change, they are experiencing more frequent droughts. Quantifying the diversity of both tree species and physiological function can help us understand not only current capacities for water and carbon cycling but also how forest function will likely be impacted in the future. The goal of our study was to characterize and assess the functional variation of tropical trees across water availability gradients (i.e. plateau of the eastern Amazon and valley of the central Amazon), representing differences in water table depth. We aim to 1) determine the functional types and quantify functional diversity within each site and 2) compare the functional types found and the relative functional diversity between them. To this end, we first collected leaf-level physiological and anatomical traits from 12 tree species in the plateau, representing ≥ 25% of the tree biomass in this region. Our data include CO2 response curves, light response curves, stomatal conductance (gsw) as a function of vapor pressure deficit (VPD), sap flow, and stomatal and xylem anatomy. By applying a principal component analysis (PCA) to these trait data, we are identifying unique clusters of species, grouping those species into empirically-based functional types, and then using those types to evaluate functional diversity at the plot level.

Preliminary analysis of our data shows high variability in the maximum rate of Rubisco carboxylation (Vcmax), maximum rate of electron transport (Jmax), stomatal anatomy, gsw, and VPD sensitivity, indicating a wide variation in plant functional types. Our next steps are to refine our divisions of functional types by incorporating metrics of plant hydraulics including leaf water potential and P50, the water potential resulting in a 50% loss of hydraulic conductivity. We will extend our collections to the valley site, allowing us to compare functional types and diversity between deep (plateau) and shallow (valley) water tables. Data collected so far in the valley indicate less variation in hydraulic traits and comparatively higher gsw of trees than those in the plateau. By quantifying large-scale functional diversity and by further linking these to remote sensing products, we can improve our predictions of tropical forest responses to climate change and use these data to improve the conservation of these ecologically important ecosystems.