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Performance evaluation and application of the phenology model in CAETÊ, a trait-based dynamic vegetation model

Grant number: 19/26239-6
Support type:Scholarships abroad - Research Internship - Master's degree
Effective date (Start): May 28, 2020
Effective date (End): August 27, 2020
Field of knowledge:Biological Sciences - Ecology - Applied Ecology
Principal Investigator:David Montenegro Lapola
Grantee:Gabriela Martins Sophia
Supervisor abroad: Anja Rammig
Home Institution: Centro de Pesquisas Meteorológicas e Climáticas Aplicadas à Agricultura (CEPAGRI). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
Local de pesquisa : Technische Universität München, Weihenstephan (TUM), Germany  
Associated to the scholarship:19/06487-5 - Trait-based modeling of the impacts of climate change on plant phenology-related functionality, BP.MS

Abstract

Phenology changes are a key biological response of forests to climate change and influence biogeochemical cycles. However, current vegetation models are unable to represent seasonal cycles, and thus phenological behaviour of the Amazon rainforest, misrepresenting predictions of future climate scenarios. This scientific proposal has two objectives: (i) validate the phenology module currently implemented in the CAETÊ model and (ii) apply the phenology module with a range of different input data. For this, the variables related to the biogeochemical cycles used to evaluate the performance of the CAETÊ will be gross primary productivity (GPP), net primary productivity (NPP), biomass, evapotranspiration and leaf area index (LAI). This validation will be performed using the International Land Model Benchmarking (ILAMB) protocol to compare the CAETE simulation results with observed data and with output from other dynamic vegetation models. Then, the phenology module will be applied with a CO2 concentration of 600 ppmv along with a reduction of precipitation to assess the model behaviour, and in particular the simulated response of phenology. With the results, it is planned the development of a phenology module that represents the current conditions of the Amazon Basin, and through this, it is expected that its application will be effective and sensitive in phenology compared to other equally efficient DGVMs. For this, the proposal involves a scientific knowledge exchange between the beneficiary, and the Brazilian and foreign scientists that are leading researchers on ecosystem modeling, ecosystem ecology and biogeochemistry through a four months research stay at the Professorship for Land Surface-Atmosphere Interactions (LSAI) at Technical University of Munich (TUM), Germany, which has a strong expertise in the development and application of dynamic vegetation models.