AmazonFACE∫ME

The AmazonFACE model-experiment integration project

The role of biodiversity and climate feedbacks

Despite being suggested, for more than 20 years now, as a process of utter importance for the resilience of tropical forests and maintenance of the global carbon cycle, the existence, magnitude and duration of a supposed “CO₂ fertilization” effect in tropical forests remains largely undetermined. The AmazonFACE∫ME project – funded by FAPESP in Brazil and by DFG in Germany – initiates the long-term ecosystem modeling activities within the AmazonFACE (Free-Air CO₂ Enrichment) experiment under execution in central Amazonia aiming to investigate the effects of increased atmospheric CO₂ on the ecology and resilience of the forest – which is also the major objective of this proposal.

The project investigates a set of scientific questions related to carbon metabolism and cycling, water use, nutrient cycling and functional diversity of tropical forest plants. These questions are tackled in the context of three project tasks:

• An assumption-based intercomparison of results from 14 dynamic global vegetation models (DGVM) run with LBA input data from the AmazonFACE experimental site under current and +200ppmv [CO₂]. Three of these models simulate only the carbon cycle, other five consider carbon and nitrogen cycles, and other six consider the cycles of carbon, nitrogen and phosphorus. Such a model intercomparison provides the first set of hypothesis to be verified in the AmazonFACE field experiment.
• Development of the Carbon and Ecosystem functional Trait Evaluation – CAETÊ model, a new DGVM based on functional traits and trade-offs (instead of the standard plant functional types logic) that provides better ways to tackle the enormous plant funcational diversity found in tropical forests and how it responds to environmental changes (more information about the CAETÊ model);
• A modeling exercise to investigate potential feedbacks that elevated [CO₂] can cause between the Amazonian biosphere and atmosphere using a DGVM dynamically coupled to a general circulation model of the atmosphere.

The approach of integrating ecosystem modeling and observational experimentation employed here is key to efficiently enhance our predictive understanding of climate change’s impact on the Amazon and other tropical ecosystems.

Research team

• Anja Rammig – Technical University of Munich – TUM, Freising, Alemanha, pesquisadora
• Bart Kruijt – Univ. Wageningen, Holanda, pesquisador
• Tomas Domingues – Universidade de São Paulo (USP), pesquisador
• Alexandro J. Baldassin – Universidade Estadual Paulista (UNESP), pesquisador
• Carolina Blanco – Universidade Estadual de Campinas (UNICAMP), pós-doutoranda
• Maíra Padgurschi – Universidade Estadual de Campinas (UNICAMP), pós-doutoranda
• Anthony P. Walker – Oak Ridge National Laboratory (ORNL), USA, pesquisador
• Richard Norby – Oak Ridge National Laboratory (ORNL), USA, pesquisador
• Celso von Randow – Instituto Nacional de Pesquisas Espaciais (INPE), pesquisador
• Gilvan Sampaio – Instituto Nacional de Pesquisas Espaciais (INPE), pesquisador
• Manoel Cardoso – Instituto Nacional de Pesquisas Espaciais (INPE), pesquisador
• Alessandro Araújo – Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA), pesquisador
• Carlos A. Quesada – Instituto Nacional de Pesquisas da Amazônia (INPA), pesquisador
• João P. Darela Filho – Universidade Estadual de Campinas (UNICAMP), doutorando
• Bianca Fazio Rius – Universidade Estadual de Campinas (UNICAMP), doutoranda
• Moara C. Teixeira – Universidade Estadual de Campinas (UNICAMP), doutoranda
• Gabriela Sophia – Universidade Estadual Paulista (UNESP), mestranda
• Bárbara Cardeli – Universidade Estadual Paulista (UNESP), mestranda
• Gabriel Marandola – Universidade Estadual de Campinas (UNICAMP), iniciação científica
• Thalia Andreuccetti – Universidade Estadual de Campinas (UNICAMP), iniciação científica
• Tainá Almeida – Universidade Estadual de Campinas (UNICAMP), iniciação científica
• Caio Fascina – Universidade Estadual de Campinas (UNICAMP), treinamento técnico
• Isabelle Ferreira – Universidade Estadual de Campinas (UNICAMP), treinamento técnico

Funding

FAPESP (Brazil) and GDF (Germany)

Results

• Sampaio, G. et al., 2021. CO₂ physiological effect can cause rainfall decrease as strong as large-scale deforestation in the Amazon. Biogeosciences, 18 (8): 2511–2525.
• Cordeiro, A. L. et al., 2020. Fine‐root dynamics vary with soil depth and precipitation in a low‐nutrient tropical forest in the Central Amazonia. Journal of Plant-Environment Interactions, 1:3–16.
• Fleischer, K. et al., 2019. Amazon forest response to CO₂ fertilization dependent on plant phosphorus acquisition. Nature Geoscience, 12:736–741.
• Lapola, D. M. et al., 2018. Limiting the high impacts of Amazon forest dieback with no-regrets science and policy action. PNAS, 115:46:11671-11679.
• Lapola, D. M., 2018. Bytes and boots to understand the future of the Amazon forest. New Phytologist, 219:845-847.

Data & Codes

All data and codes resulting from this project are deposited at UNICAMP’s Data Repository under the tag “AmazonFACE/ME”