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

Schymanski, S. J., Roderick, M. L., Sivapalan, M., Hutley, L. B., & Beringer, J. (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. doi:10.1111/j.1365-3040.2007.01728.x.

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BGC1039.pdf (Publisher version), 553KB
 
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Schymanski, S. J.1, Author           
Roderick, M. L., Author
Sivapalan, M., Author
Hutley, L. B., Author
Beringer, J., Author
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1Terrestrial Biosphere, Research Group Biospheric Theory and Modelling, Dr. A. Kleidon, Max Planck Institute for Biogeochemistry, Max Planck Society, ou_1497792              

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Free keywords: Adaptation Assimilation Costs and benefits Gas exchange Optimization Photosynthesis Australian tropical savanna Whole-plant photosynthesis Northern australia Stomatal conductance Electron-transport Global radiation Nitrogen-content Group selection Use efficiency Carbon
 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 (N-CP), the difference between carbon acquired by photosynthesis and carbon spent on maintenance of the organs involved in its uptake. We modelled N-CP 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. [References: 53]

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 Dates: 2007
 Publication Status: Issued
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 Identifiers: DOI: 10.1111/j.1365-3040.2007.01728.x
Other: BGC1039
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Title: Plant, Cell and Environment
Source Genre: Journal
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Publ. Info: Oxford, England : Blackwell Science
Pages: - Volume / Issue: 30 (12) Sequence Number: - Start / End Page: 1586 - 1598 Identifier: CoNE: https://pure.mpg.de/cone/journals/resource/954925471334
ISSN: 0140-7791