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Reconciling the optimal and empirical approaches to modelling stomatal conductance

dc.contributor.authorMedlyn, Belinda E.en
dc.contributor.authorDuursma, Remko A.en
dc.contributor.authorEamus, Dereken
dc.contributor.authorEllsworth, David S.en
dc.contributor.authorPrentice, I. Colinen
dc.contributor.authorBarton, Craig V.M.en
dc.contributor.authorCrous, Kristine Y.en
dc.contributor.authorDe Angelis, Paoloen
dc.contributor.authorFreeman, Michaelen
dc.contributor.authorWingate, Lisaen
dc.date.accessioned2025-02-12T10:18:47Z
dc.date.available2025-02-12T10:18:47Z
dc.date.issued2011en
dc.description.abstractModels of vegetation function are widely used to predict the effects of climate change on carbon, water and nutrient cycles of terrestrial ecosystems, and their feedbacks to climate. Stomatal conductance, the process that governs plant water use and carbon uptake, is fundamental to such models. In this paper, we reconcile two long-standing theories of stomatal conductance. The empirical approach, which is most commonly used in vegetation models, is phenomenological, based on experimental observations of stomatal behaviour in response to environmental conditions. The optimal approach is based on the theoretical argument that stomata should act to minimize the amount of water used per unit carbon gained. We reconcile these two approaches by showing that the theory of optimal stomatal conductance can be used to derive a model of stomatal conductance that is closely analogous to the empirical models. Consequently, we obtain a unified stomatal model which has a similar form to existing empirical models, but which now provides a theoretical interpretation for model parameter values. The key model parameter, g1, is predicted to increase with growth temperature and with the marginal water cost of carbon gain. The new model is fitted to a range of datasets ranging from tropical to boreal trees. The parameter g1 is shown to vary with growth temperature, as predicted, and also with plant functional type. The model is shown to correctly capture responses of stomatal conductance to changing atmospheric CO2, and thus can be used to test for stomatal acclimation to elevated CO2. The reconciliation of the optimal and empirical approaches to modelling stomatal conductance is important for global change biology because it provides a simple theoretical framework for analyzing, and simulating, the coupling between carbon and water cycles under environmental change.en
dc.description.statustrueen
dc.format.extent11en
dc.identifier.otherresearchoutputwizard:f2965xPUB1790en
dc.identifier.otherScopus:79955035036en
dc.identifier.otherWOS:289641400010en
dc.identifier.urihttps://dspace-test.anu.edu.au/handle/1885/733713845
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=79955035036&partnerID=8YFLogxKen
dc.language.isoEnglishen
dc.sourceGlobal Change Biologyen
dc.subjectCoupled conductance and photosynthesis modelsen
dc.subjectMarginal water cost of carbonen
dc.subjectStomatal conductanceen
dc.subjectStomatal optimizationen
dc.titleReconciling the optimal and empirical approaches to modelling stomatal conductanceen
dc.typeArticleen
local.bibliographicCitation.lastpage2144en
local.bibliographicCitation.startpage2134en
local.contributor.affiliationMedlyn, Belinda E.; Macquarie Universityen
local.contributor.affiliationDuursma, Remko A.; Western Sydney Universityen
local.contributor.affiliationEamus, Derek; University of Technology Sydneyen
local.contributor.affiliationEllsworth, David S.; Western Sydney Universityen
local.contributor.affiliationPrentice, I. Colin; Macquarie Universityen
local.contributor.affiliationBarton, Craig V.M.; Forest Science Centreen
local.contributor.affiliationCrous, Kristine Y.; Plant Sciences, Division of Plant Sciences, Research School of Biology, ANU College of Science and Medicine, The Australian National Universityen
local.contributor.affiliationDe Angelis, Paolo; Tuscia Universityen
local.contributor.affiliationFreeman, Michael; Swedish University of Agricultural Sciencesen
local.contributor.affiliationWingate, Lisa; University of Cambridgeen
local.identifier.citationvolume17en
local.identifier.doi10.1111/j.1365-2486.2010.02375.xen
local.identifier.pure65a9343c-c829-4c3f-9e2d-791cc55a454ben
local.type.statusPublisheden

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