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The Use and Usefulness of Artificial Herbivory in Plant-Herbivore Studies

  • K. Lehtilä
  • E. Boalt
Chapter
Part of the Ecological Studies book series (ECOLSTUD, volume 173)

Summary

Artificial damage is a popular method in plant-herbivore studies, because the use of real herbivores is often laborious and because it may be virtually impossible to use herbivores in many experimental setups. We made a literature search of studies that tested whether natural and artificial damage have similar effects on plants. Of 46 studies found, 33 (72%) reported a significant difference between responses to artificial and natural herbivore damage in at least one of the statistical tests included. The studies contained 280 statistical tests, of which 99 (35%) showed a significant difference between artificial and natural damage. Phytochemical responses to artificial and natural damage were different in 41% of the statistical tests and 75% of the studies found at least one significant difference. Plant resistance, measured as secondary damage, herbivore performance, fungal growth in damaged tissue or plant attractivity to parasitoids of herbivores, differed in 60% of the statistical tests and 85% of the studies had significant differences. Growth, reproduction and physiological responses to artificial and natural damage differed in 20–30% of statistical tests and 50–83% of studies had significant differences. Thus, studies on plant tolerance (growth and reproduction after damage) more often showed similar effects for artificial and natural damage than studies on plant resistance to herbivory, but even in tolerance studies artificial and natural damage often have different effects. Some studies indicated that application of herbivore saliva and careful imitation of timing and spatial pattern of damage helped in reaching the same effect with simulations and natural damage.

Keywords

Flea Beetle Artificial Damage Response Trait Natural Damage Damage Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • K. Lehtilä
  • E. Boalt

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