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Optimization and Game Theory in Canopy Models

  • Chapter
Canopy Photosynthesis: From Basics to Applications

Part of the book series: Advances in Photosynthesis and Respiration ((AIPH,volume 42))

Summary

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 to which 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 how it 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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Abbreviations

A D :

Daily leaf photosynthesis (mol CO2 d−1 m−2)

A max :

Light saturated leaf photosynthesis (μmol CO2 s−1 m−2)

A 0 :

Light saturated leaf photosynthesis of the top most leaf in the canopy (μmol CO2 s−1 m−2)

β :

Degree to which canopies of neighboring plants are mixed.

Cb :

Crown base of a plant (when r or m are added it refers to a resident or mutant).

f :

Cumulated amount of LAI above a given point (m2 m−2)

fr :

Frequency of a strategy in a population (dimensionless)

f st :

Fraction of NPP allocated to stem growth (dimensionless)

F :

General indicator of fitness (no units)

H max :

Maximum tree height

I(f):

Light intensity (photon flux density ) at depth f in the canopy (μmol s−1 m−2)

I 0 :

Light intensity (photon flux density ) above the canopy (μmol s−1 m−2)

k :

Extinction coefficient for light

λ :

A Lagrangian multiplier

LAI :

Leaf area index (m2 m−2)

LMA:

Leaf mass per unit area (g m−2)

M s :

Stem mass per unit length (g m−1)

NPP:

Net primary productivity (e.g. g plant−1 day−1 but definition per unit land area also possible)

N area :

Leaf nitrogen content per unit area (mmol m−2)

N o :

N area of the top most leaf in the canopy (mmol m−2)

p :

The fraction of the shading that plant experiences being caused by its own leaves

P :

General indicator of plant performance (no units) often used as fitness proxy (e.g. photosynthesis growth etc)

R :

General indicator for resources (no units)

r eff :

Fraction of nitrogen that plants resorb from senescing leaves

S d :

Solar beam

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Acknowledgments

I thank, Kouki Hikosaka, Marloes van Loon, Peter Vermeulen and an anonymous reviewer for valuable comments on the manuscript.

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  1. Crop and Weed Ecology, Centre for Crop Systems Analysis, Wageningen University, Wageningen, The Netherlands

    Niels P. R. Anten

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Editors and Affiliations

  1. Graduate School of Life Sciences, Tohoku University, Sendai, Japan

    Kouki Hikosaka

  2. Environmental Sciences, Estonian University of Life Sciences Institute of Agricultural and, Tartu, Estonia

    Ülo Niinemets

  3. Crop and Weed Ecology, Centre for Crop Systems Analysis, Wageningen University, Wageningen, Gelderland, The Netherlands

    Niels P.R. Anten

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Anten, N.P.R. (2016). Optimization and Game Theory in Canopy Models. In: Hikosaka, K., Niinemets, Ü., Anten, N. (eds) Canopy Photosynthesis: From Basics to Applications. Advances in Photosynthesis and Respiration, vol 42. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-7291-4_13

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