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A test of the optimality approach to modelling canopy properties and CO2 uptake by natural vegetation

Schymanski, S., Roderick, M., Sivapalan, M., Hutley, Lindsay and Beringer, Jason (2007). A test of the optimality approach to modelling canopy properties and CO2 uptake by natural vegetation. Plant, Cell and Environment,30(12):1586-1598.

Document type: Journal Article
Citation counts: Scopus Citation Count Cited 28 times in Scopus Article | Citations

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IRMA ID 73195523xPUB26
Title A test of the optimality approach to modelling canopy properties and CO2 uptake by natural vegetation
Author Schymanski, S.
Roderick, M.
Sivapalan, M.
Hutley, Lindsay
Beringer, Jason
Journal Name Plant, Cell and Environment
Publication Date 2007
Volume Number 30
Issue Number 12
ISSN 0140-7791   (check CDU catalogue open catalogue search in new window)
Scopus ID 2-s2.0-35648962911
Start Page 1586
End Page 1598
Total Pages 13
Place of Publication Oxford
Publisher Blackwell
Field of Research 0607 - Plant Biology
HERDC Category C1 - Journal Article (DEST)
Abstract Photosynthesis provides plants with their main building material, carbohydrates, and with the energy necessary to thrive and prosper in their environment. We expect, therefore, that natural vegetation would evolve optimally to maximize its net carbon profit (Ncp), the difference between carbon acquired by photosynthesis and carbon spent on maintenance of the organs involved in its uptake. We modelled Ncp for an optimal vegetation for a site in the wet-dry tropics of north Australia based on this hypothesis and on an ecophysiological gas exchange and photosynthesis model, and compared the modelled CO2 fluxes and canopy properties with observations from the site. The comparison gives insights into theoretical and real controls on gas exchange and canopy structure, and supports the optimality approach for the modelling of gas exchange of natural vegetation. The main advantage of the optimality approach we adopt is that no assumptions about the particular vegetation of a site are required, making it a very powerful tool for predicting vegetation response to long-term climate or land use change.
DOI http://dx.doi.org/10.1111/j.1365-3040.2007.01728.x   (check subscription with CDU E-Gateway service for CDU Staff and Students  check subscription with CDU E-Gateway in new window)
 
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