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Modelling tropical forest responses to drought and El Nino with a stomatal optimization model based on xylem hydraulics

Eller, Cleiton B.; Rowland, L.; Oliveira, Rafael; Bittencourt, Paulo L.; Barros, Fernanda V.; da Costa, Antonio Carlos Lola; Meir, Patrick; Friend, Andrew D.; Mencuccini, Maurizio; Sitch, Stephen; Cox, Peter M.

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The current generation of dynamic global vegetation models (DGVMs) lacks a mechanistic representation of vegetation responses to soil drought, impairing their ability to accurately predict Earth system responses to future climate scenarios and climatic anomalies, such as El Niño events. We propose a simple numerical approach to model plant responses to drought coupling stomatal optimality theory and plant hydraulics that can be used in dynamic global vegetation models (DGVMs). The model is...[Show more]

dc.contributor.authorEller, Cleiton B.
dc.contributor.authorRowland, L.
dc.contributor.authorOliveira, Rafael
dc.contributor.authorBittencourt, Paulo L.
dc.contributor.authorBarros, Fernanda V.
dc.contributor.authorda Costa, Antonio Carlos Lola
dc.contributor.authorMeir, Patrick
dc.contributor.authorFriend, Andrew D.
dc.contributor.authorMencuccini, Maurizio
dc.contributor.authorSitch, Stephen
dc.contributor.authorCox, Peter M.
dc.date.accessioned2019-04-15T11:52:48Z
dc.identifier.issn0962-8436
dc.identifier.urihttp://hdl.handle.net/1885/159677
dc.description.abstractThe current generation of dynamic global vegetation models (DGVMs) lacks a mechanistic representation of vegetation responses to soil drought, impairing their ability to accurately predict Earth system responses to future climate scenarios and climatic anomalies, such as El Niño events. We propose a simple numerical approach to model plant responses to drought coupling stomatal optimality theory and plant hydraulics that can be used in dynamic global vegetation models (DGVMs). The model is validated against stand-scale forest transpiration (E) observations from a long-term soil drought experiment and used to predict the response of three Amazonian forest sites to climatic anomalies during the twentieth century. We show that our stomatal optimization model produces realistic stomatal responses to environmental conditions and can accurately simulate how tropical forest E responds to seasonal, and even long-term soil drought. Our model predicts a stronger cumulative effect of climatic anomalies in Amazon forest sites exposed to soil drought during El Niño years than can be captured by alternative empirical drought representation schemes. The contrasting responses between our model and empirical drought factors highlight the utility of hydraulically-based stomatal optimization models to represent vegetation responses to drought and climatic anomalies in DGVMs. This article is part of a discussion meeting issue ‘The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications’.
dc.description.sponsorshipThis study was funded by the Newton Fund through the Met. Office Climate Science for Service Partnership Brazil (CSSP Brazil), UK NERC independent fellowship grant no. NE/N014022/1 to L.R., UK NERC grant no. NE/J010154/1 to S.S., UK NERC grant no. NE/J011002 to S.S., P.M. and M.M., ARC grant DP170104091 to P.M., and CNPQ grant no. 457914/2013-0/MCTI/CNPq/FNDCT/ LBA/ESECAFLOR to A.C.L.d.C.
dc.format.mimetypeapplication/pdf
dc.language.isoen_AU
dc.publisherRoyal Society of London
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourcePhilosophical Transactions of the Royal Society of London Series B
dc.titleModelling tropical forest responses to drought and El Nino with a stomatal optimization model based on xylem hydraulics
dc.typeJournal article
local.description.notesImported from ARIES
local.identifier.citationvolume373
dc.date.issued2018
local.identifier.absfor060799 - Plant Biology not elsewhere classified
local.identifier.ariespublicationu4485658xPUB1339
local.type.statusPublished Version
local.contributor.affiliationEller, Cleiton B, University of Exeter
local.contributor.affiliationRowland, L, University of Edinburgh
local.contributor.affiliationOliveira, Rafael, University of Campinas, Brazil
local.contributor.affiliationBittencourt, Paulo L., Instituto de Biologia
local.contributor.affiliationBarros, Fernanda V, University of Campinas
local.contributor.affiliationda Costa, Antonio Carlos Lola , Universidade Federal do Para
local.contributor.affiliationMeir, Patrick, College of Science, ANU
local.contributor.affiliationFriend, Andrew D, University of Cambridge
local.contributor.affiliationMencuccini, Maurizio, CREAF
local.contributor.affiliationSitch, Stephen, University of Exeter
local.contributor.affiliationCox, Peter M, University of Exeter
dc.relationhttp://purl.org/au-research/grants/arc/DP170104091
local.bibliographicCitation.issue1760
local.identifier.doi10.1098/rstb.2017.0315
local.identifier.absseo970106 - Expanding Knowledge in the Biological Sciences
dc.date.updated2019-03-12T07:28:44Z
local.identifier.scopusID2-s2.0-85054774553
dcterms.accessRightsOpen Access
dc.provenancePublished by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
dc.rights.licenseCreative Commons Attribution License
CollectionsANU Research Publications

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