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Modeling functional diversity and resilience of Amazon Forest to climate change beyond carbon stocks

Grant number: 19/04223-0
Support Opportunities:Scholarships in Brazil - Doctorate
Effective date (Start): June 01, 2019
Effective date (End): July 31, 2022
Field of knowledge:Biological Sciences - Ecology - Ecosystems Ecology
Principal Investigator:David Montenegro Lapola
Grantee:Bianca Fazio Rius
Host Institution: Centro de Pesquisas Meteorológicas e Climáticas Aplicadas à Agricultura (CEPAGRI). Universidade Estadual de Campinas (UNICAMP). Campinas , 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


The uncertainties regarding the resilience of Amazon Basin forests to climate change isof primary importance in a rapidly changing world considering that these ecosystems provide a considerable amount of goods and services to humanity. In that sense, this proposal intends to investigate the resilience of Amazon forest to climate change taking into account the ecosystem's multifunctionality and the role of functional diversity in promoting it (or not). For this, we will further develop and apply the Dynamic Global Vegetation Model (DGVM) named CAETÊ (Carbon and Ecosystem Functional Trait Evaluation model), a trait-based model that seeks to represent plant functional diversity more reliably through the usage of empirical values (that are variants in space and time) for functional traits. This approach allows us to investigate issues related to functional diversity that were previously impossible to make due to the Plant Functional Type (PFT) scheme used in most DGVMs; an approach in which functional traits are fixed in space and time and which, in addition to making it impossible to study functional diversity, may lead to an under estimation of ecosystem resilience. Six functional traits compose the focus of the present proposal: specific leaf area, wood density, adult plant height, nitrogen and phosphorous contents on leaves and g1 (stomatal condunctance sensitivity to CO2 assimilation rate). As specific objectives we intend to answer: i) How consistently is the approach used by CAETÊ in represent the different facets of functional diversity (functional identity, richness, divergence, evenness and redundancy) when compared to empirical measurements?; ii) How the different facets of functional diversity are related to ecosystem functioning considering the following processes: net primary productivity, vegetation carbon stock and evapotranspiration?; iii) What are the impacts of climate change on the different facets of functional diversity? and iv) How resilient in terms of the resistance and recovery of its ecosystem processes (cited in question ii) are Amazon forest to climate change and what is the role of functional diversity? To understand the impacts of climate change we will use three levels (from low to high severity) of disturbance on three climatic variables (temperature, precipitation and CO2 concentration). We hope that our approach improve the representation of functional diversity in vegetation models allowing an advance on the compreehension of the functional diversity role in determining ecosystem funcioning and resilience. This is of primary importance in the face of the expected climate changes that together with land use change will certanly lead to a loss on biodiversity (including functional diversity loss). In that sense, fill these knowledge gaps could, ultimately, lead to a better management and conservation strategies for biodiversity. (AU)

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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., . (15/02537-7, 19/04223-0, 17/00005-3)

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