Modeling the role of nutrients for the stability of the Amazon Forest in light of climate change

• Grant number: 17/00005-3
• Support Opportunities: Scholarships in Brazil - Doctorate (Direct)
• Start date: February 01, 2017
• End date: March 31, 2021
• Field of knowledge: Physical Sciences and Mathematics - Geosciences - Meteorology
• Principal Investigator: David Montenegro Lapola
• Grantee: João Paulo Darela Filho
• Host Institution: Instituto de Biociências (IB). Universidade Estadual Paulista (UNESP). Campus de Rio Claro. Rio Claro , SP, Brazil
• Associated research grant: 15/02537-7 - AmazonFACE/ME: the Amazon-FACE Model-Experiment integration project - the role of biodiversity and climate feedbacks, AP.PFPMCG.JP
• Associated scholarship(s): 19/08194-5 - Incorporating soil nitrogen and phosphorus cycling in CAETÊ, a trait-based dynamic vegetation model, BE.EP.DD

Abstract

The Amazon forest dieback hypothesis was postulated in early 2000, and many studies suggested that a future climate induced dieback of the Amazon forest was a real possibility. More recently, it was considered less probable since the Carbon Dioxide (CD) fertilization effect would maintain forest productivity and biomass for decades to come. The response of the Amazon forest to elevated CD is however very uncertain in reality, and in particular two important features in regards to that have not been considered in vegetation model projections: 1) the potentially limiting role of nutrients on the CD fertilization effect (as observed in the Oak Ridge FACE experiment) and 2) the possibility of interspecific response variation, e.g. different plant growth/surviving strategies are likely to differ in their responses to climate change and elevated CD. The former would result in lowered forest productivity and carbon (C) accumulation, which could accelerate climate-induced biome shifts. The latter however would lead to changes in plant community composition but not necessarily to a change of biomes as predicted by the Amazon forest dieback hypothesis. These uncertainties keep the question of how the Amazon forest will respond to future global change, and whether a dieback of the Amazon could indeed occur, as an open question. The importance of biogeochemical cycles, mainly nitrogen and phosphorus, are increasingly recognized and nutrients have a demonstratively strong control on future global carbon cycle projections (Wieder et al. 2015). In addition, models based on traits and functional attributes rise as a promising alternative to better characterize survival and growth strategies, e.g. as demonstrated in the studies by Pavlick et al. [2013], Fyllas et al. [2014] and van Bodegom et al. [2014]. The role of nutrients and plant functional diversity is of particular relevance for tropical forests, due to the strong control of tropical forests on the global C cycle and the high plant diversity they harbor. This DD project will address the Amazon forest dieback hypothesis by employing a trait-based modelling approach, and consider fully coupled important biogeochemical cycles, a unique combination of characteristics in global ecosystem modeling. The DD project will comprise necessary developments in Carbon and Ecosystem functional Trait Evaluation (CAETÊ) by means of development and implementation of both nitrogen and phosphorus cycles dynamics, all within a trait-based approach. These developments will allow investigating the effects of N and P cycle dynamics on the CD fertilization effect, and the response of plant functional diversity to elevated CD and climate change which will ultimately constrain (or not) the likelihood and nature of the Amazon forest dieback. (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

RIUS, BIANCA FAZIO; DARELA FILHO, JOAO PAULO; FLEISCHER, KATRIN; HOFHANSL, FLORIAN; BLANCO, CAROLINA CASAGRANDE; RAMMIG, ANJA; DOMINGUES, TOMAS FERREIRA; LAPOLA, DAVID MONTENEGRO. Higher functional diversity improves modeling of Amazon forest carbon storage. ECOLOGICAL MODELLING, v. 481, p. 14-pg., 2023-03-13. (15/02537-7, 19/04223-0, 17/00005-3)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

DARELA FILHO, João Paulo. Modeling the impacts of increased concentration of CO2 and nutrients over the functional composition of the amazon forest. 2021. Doctoral Thesis - Universidade Estadual Paulista (Unesp). Instituto de Biociências. Rio Claro Rio Claro.