Plant Behavioural Ecology

Plant behaviour is different to animal behaviour using plasticity in growth and development rather than movement. Plants actively forage their environment for light and soil resources placing roots and branches in environmentally beneficial positions so as to enhance survival and thus eventual fitness. But decisions about placement are (1) often made on future predictions of energy return, (2) optimized to minimize resource outlay using self-recognition while maximizing energy return, (3) made to guard territory (4) used to ensure plants linger longer in resource-rich patches. Complexity in plant sexual systems and life cycle has arisen from genetic assimilation of behavioural changes as the balance of trade-offs in resource availability has altered. Plant behaviour can thus be regarded as intelligent.

Keywords: foraging; self-recognition; territoriality; plasticity; optimal energy return; decision making; intelligence

Figure 1. (a) The Charnov model of optimal foraging. The curves indicate the trajectories of net energy uptake from three hosts ‘a’ ‘b’ and ‘c’. Optimal foraging, that is optimizing the energy gained to the energy invested, is indicated by the dotted asymptotes to each curve. The very thick straight line joins together the points of asymptote contact for each host to indicate how optimal foraging works for different hosts. Failure to go through the zero point indicates biological error in foraging. Based on the Charnov (1976) model for optimal foraging for animals. and (b) The parasite Dodder forages according to the Charnov (1976) animal optimal foraging model. Six different hosts were used to estimate energy invested versus energy gain during parasitical exploitation by Dodder. Energy gained was measured after 28 days as net increase in weight. Energy invested was calculated from the coil length used to parasitize the host. Note the identity with Charnov theory (Figure 1a) indicating that Dodder optimally forages and that Dodder determines energy investment well before any net energy gain. Data redrawn from Kelly (1990).
Figure 2. The genetic assimilation of a behavioural character varying quantitatively between two different environments E1 and E2. The figure charts the trajectories of behaviour of three individuals, a, b, c during an environmental shift from E1 to E2 and then perhaps back to E1. ‘a’ shows limited plasticity and dies in the initial environmental shift. ‘b’ and ‘c’ are sufficiently plastic in behaviour to quantitatively change the character and survive the environmental shift. For example, the environmental shift might result from higher volcanic activity increasing areas of bare soil. Individual plants who respond behaviourally to bare soil by producing larger numbers of smaller seeds, more rapidly colonize this new environment. With time gene combinations arise that enables this behaviour to develop with greater rapidity, higher probability or lower cost thus honing the genotype but by epigenetic means. On return to E1 (if this happens) or to a different E (such as temporary bare soil in forest regeneration), the character expression is now shifted to the different, in this case, higher value. The mechanism emphasizes the survival of the adaptable. Modified from Waddington (1957).
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 References
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 Further Reading
    book Ballare CL (1994) "Light gaps: sensing the light opportunities in highly dynamic canopy environments". In: Caldwell MM and Pearcy RW (eds) Exploitation of Environmental Heterogeneity by Plants, pp. 73–111. New York: Academic Press.
    book Bazzaz FA (1996) Plants in Changing Environments. Cambridge, UK: Cambridge University Press.
    book Bell G and Lechowicz MJ (1994) "Spatial heterogeneity at small scales and how plants respond to it". In: Caldwell MM and Pearcy RW (eds) Exploitation of Environmental Heterogeneity by Plants, pp. 391–411. New York: Academic Press.
    Gersani M, Brown JS, O'Brien EE, Maina GM and Abramsky Z (2001) Tragedy of the commons as a result of root competition. Ecology 89: 660–669.
    Givnish TJ (1982) On the adaptive significance of leaf height in forest herbs. American Naturalist 120: 353–381.
    book Grime JP, Crick JC and Rincon JE (1986) "The ecological significance of plasticity". In: Jennings DH and Trewavas AJ (eds) Plasticity in Plants. Symposium of the Society of Experimental Biology and Medicine. XL, pp. 5–29. London: Cambridge University Press.
    Jones M and Harper JL (1987) The influence of neighbours on the growth of trees. I. The demography of buds in Betula pendula. Proceedings of the Royal Society of London, Series B. Biological Sciences 232: 1–18.
    book Kuppers M (1994) "Canopy gaps: competitive light interception and economic space filling". In: Caldwell MM and Pearcy RW (eds) Exploitation of Environmental Heterogeneity by Plants, pp. 111–144. New York: Academic Press.
    Novoplansky A (2003) Ecological implications of the determination of branch hierarchies. New Phytologist 160: 111–118.
    Sachs T, Novoplansky A and Cohen D (1993) Plants as competing populations of redundant organs. Plant Cell and Environment 16: 765–770.
    book Schlichting CD and Pigliucci M (1998) Phenotypic Evolution: a Reaction Norm Perspective. Sunderland, MA: Sinauer Associates Inc.
    Silvertown J and Gordon GM (1989) A framework for plant behaviour. Annual Review of Ecology and Systematics 20: 349–366.
    Yamada T, Okuda T, Abdullah M, Awang M and Furukawa A (2000) The leaf development process and its significance for reducing self-shading of a tropical pioneer tree species. Oecologia 125: 476–482.
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Trewavas, Anthony J(Sep 2007) Plant Behavioural Ecology. In: eLS. John Wiley & Sons Ltd, Chichester. http://www.els.net [doi: 10.1002/9780470015902.a0003672]