Functional diversity analysis along a precipitation gradient in the Amazon basin using vegetation modeling.

• Grant number: 23/06975-5
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: September 01, 2023
• End date: March 31, 2024
• Field of knowledge: Biological Sciences - Ecology - Ecosystems Ecology
• Principal Investigator: David Montenegro Lapola
• Grantee: Marcela Gutierrez Pereira
• Host Institution: Centro de Pesquisas Meteorológicas e Climáticas Aplicadas à Agricultura (CEPAGRI). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil

Abstract

The decreasing west-east precipitation gradient in the Amazon basin is one of the determining factors for the spatial distribution of different vegetation types observed in the region. The survival and abundance of plants in different environments are determined, at least in part, by their functional traits, which can define how they affect and respond to the environment. The combination of all attributes within an ecological unit determines functional diversity, which is specific to each region and highly relevant to the effects of climate change on ecosystem functioning and their ability to maintain their processes and properties. However, studies on how functional diversity is distributed across different Amazonian regions are still scarce. Therefore, the present study aims to evaluate how functional diversity is distributed along the west-east precipitation gradient in three specific regions (northwest, central, and southeast) across the Amazon basin. To do so, we will utilize simulations based on the trait-based vegetation model called CAETÊ (CArbon and Ecosystem functional Trait Evaluation model). This model seeks to represent the functional diversity of the Amazon forest by combining functional traits that form distinct plant life strategies, which exhibit different survival and abundance depending on environmental conditions. In addition to serving as an introduction to the scientific field for the beneficiary, this project will represent an advancement in the analysis of functional diversity within emerging vegetation models based on varying functional traits.