Modeling the relationship between leaf phenology and hydraulics of plants in the Amazon rainforest: a trait-based approach to the effects of reduced precipitation

Author(s)

Gabriela Martins Sophia

• Document type: Master's Dissertation
• Press: Rio Claro. 2021-05-20.
• Institution: Universidade Estadual Paulista (Unesp). Instituto de Biociências. Rio Claro
• Defense date: 2021-04-23
• Advisor: David Montenegro Lapola; Leonor Patrícia Cerdeira Morellato

Abstract

Dynamic global vegetation models (DGVMs) have been developed to better understand the vegetation's response to climate changes. However, DGVMs generate variable responses since it is represented by a small set of plant functional types. Models based on the variability of functional traits appear as an alternative to better represent the plant life strategies. Including leaf phenology in these models is of paramount importance because it plays a role in controlling the seasonality of carbon, water, and energy fluxes. In tropical ecosystems, such as in the Amazon, phenology is mainly driven by soil water availability, so simulating the impacts of a predicted drier climate requires the representation of the connection between phenology and the hydraulic strategies of plants. This work contributed to the development of the CAETÊ trait-based model through the implementation of a leaf phenology module linked to plant hydraulic system. The development was applied to the entire Amazon biome and its main objective was to improve the representation of the seasonality of the leaf area index (LAI) with consequent improvement in the carbon and water cycle, and therefore to assess the impacts of climate changes on it. For this, two functional traits are being used as variants: WD (wood density - determining the hydraulic system) and τleaves (leaf carbon residence time - determining the leaf age). Equations already existing in other vegetation models were used and adapted to the CAETÊ model. The model was applied under a 30% reduction of precipitation. As a result, the inclusion of the phenology module improved the model's performance in relation to LAI seasonality in regions where soil water is a limiting factor; as well as improving the representation of the gross primary productivity of the ecosystem (GPP) and providing a more demarcated spatial variability of the Amazon region. At the level of biogeochemical cycling, a 30% reduction in precipitation led to a reduction in soil water availability, in GPP, LAI and evapotranspiration (ET) for less humid regions of the Amazon; while for more humid areas there were no evident impacts, consistent with the observations that in these regions a reduction in the rainfall regime is not sufficient to determine the biogeochemical and LAI processes. Finally, it is generally concluded that the inclusion of leaf phenology improves the performance of the model, but that adjustments to the new module are necessary so that it also represents seasonality in regions that are not determined by water in the soil. (AU)

• FAPESP's process: 19/06487-5 - Trait-based modeling of the impacts of climate change on plant phenology-related functionality
• Grantee: Gabriela Martins Sophia
• Support Opportunities: Scholarships in Brazil - Master