Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 509912
Title Optimization and Game Theory in Canopy Models
Author(s) Anten, N.P.R.
Source In: Canopy Photosynthesis: From Basics to Applications / Hikosaka, Kouki, Niinemets, Ülo, Antan, Niels P.R., Dordrecht : Springer (Advances in Photosynthesis and Respiration ) - ISBN 9789401772907 - p. 355 - 377.
DOI https://doi.org/10.1007/978-94-017-7291-4_13
Department(s) Crop and Weed Ecology
PE&RC
Publication type Peer reviewed book chapter
Publication year 2016
Abstract Ecological optimization theory in combination with canopy modeling is increasingly being accepted as a powerful tool in various scientific fields including ecology, crop science and global change biology. However, the success of this approach critically depends on the adequate choice of optimization criteria and on the structure and assumptions of the canopy models towhich it is
linked. This chapter starts with the conventional optimization criterion, that of static plant simple optimization, whereby traits are assumed optimal when whole-canopy carbon gain is maximized. It shows how this approach has been widely and often successfully used but also howit often fails to capture key features of vegetation stands. It then lays out a number innovative steps by which optimization could be made more amenable to our understanding of real plant systems. These include: the introduction of evolutionary game theory that takes plant competition into account, the shift from static photosynthesis to dynamic growth models and expanding from simple fitness proxies such as photosynthesis to local population growth. Overall it is argued that future optimization models should employ combinations of these elements.
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