, Volume 142, Issue 1, pp 46–56

Perfect is best: low leaf fluctuating asymmetry reduces herbivory by leaf miners

Plant Animal Interactions

DOI: 10.1007/s00442-004-1724-y

Cite this article as:
Cornelissen, T. & Stiling, P. Oecologia (2005) 142: 46. doi:10.1007/s00442-004-1724-y


Fluctuating asymmetry (FA) represents small, random variation from symmetry and can be used as an indicator of plant susceptibility to herbivory. We investigated the effects of FA of two oak species, Quercus laevis and Q. geminata, and the responses of three herbivore guilds: leaf miners, gallers, and chewers. To examine differences in FA and herbivory between individuals, 40 leaves from each tree were collected, and FA indices were calculated. To examine differences in FA and herbivory within-individuals, we sampled pairs of mined and unmined leaves for asymmetry measurements. Differences in growth of leaf miners between leaf types were determined by tracing 50 mines of each species on symmetric leaves and asymmetric leaves. Asymmetric leaves contained significantly lower concentrations of tannins and higher concentrations of nitrogen than symmetric leaves for both plant species. Both frequency of asymmetric leaves on plants and levels of asymmetry positively influenced the abundance of Brachys, Stilbosis and other leaf miners, but no significant relationship between asymmetry and herbivory was observed for Acrocercops. Brachys and Stilbosis mines were smaller on asymmetric leaves, but differences in mine survivorship between symmetric and asymmetric leaves were observed only for Stilbosis mines. This study indicated that leaf miners might use leaf FA as a cue to plant quality, although differential survivorship among leaf types was not observed for all species studied. Reasons for the different results between guilds are discussed.


Quercus Fluctuating asymmetry Plant quality Leaf miners 

Copyright information

© Springer-Verlag 2004

Authors and Affiliations

  1. 1.Department of Biology SCA 110University of South FloridaTampaUSA

Personalised recommendations