The role of functional diversity in modulating the functioning of a tropical forest in the central Amazon

• Grant number: 24/11029-4
• Support Opportunities: Scholarships in Brazil - Master
• Start date: December 01, 2024
• End date: February 28, 2026
• 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 Amazon Rainforest is the most biodiverse region in the world, playing a key role as a carbon sink, which is stored as biomass in plants and soil. Its functioning is linked to several processes, such as primary productivity and carbon storage, which depends on the physiological responses and conditions of plants, determined, in part, by their functional attributes. The set of all attributes in an ecological unit determines the functional diversity, which is specific to each region. Functional diversity is directly related to processes and properties that guide the functioning of ecosystems, such as primary productivity and biomass. However, there are few studies that seek to understand how functional diversity is related to the functioning of tropical forests. Thus, the present work aims to evaluate, through modeling, how changes in functional diversity modulate the functioning of a tropical forest in the central Amazon. To do so, we will use simulations made from 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 through the combination of functional attributes that form distinct plant life strategies, which have differentiated survival and abundance depending on environmental conditions. The project will represent an advance in the way of analyzing functional diversity in the new generation of vegetation models based on variant functional attributes, in addition to elucidating a better understanding of the factors that modulate the functioning of tropical forests and their responses to environmental and climate change.