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Behavioral type and growth rate in a cichlid fish


  • Dik Heg
  • Roger Schürch
  • Susan Rothenberger


Behavioral syndromes or animal personalities may emerge due to covariation with different life-history strategies individual animals pursue, like risk-associated feeding rates translating in different growth trajectories. However, less clear is how this might affect individuals in cooperatively breeding species, where subordinates assist dominants in raising offspring, and growth has profound life-history and social consequences. Here, we examined the effects of behavioral type on growth rates and feeding in the cooperatively breeding cichlid fish Neolamprologus pulcher, comparing growth rates of individuals settled inside a group (dominant or subordinate) or unsettled fish (aggregation) of different behavioral types (bold-shy continuum) under a feeding regime where food could not be monopolized. Controlling for other factors, we found no effect of the behavioral type on the growth rates of dominants and subordinates in either sex. In contrast, bold female aggregation fish were significantly growing faster in length compared with shy female aggregation fish, whereas no such effect was detected in male aggregation fish. These growth rate differences were largely matched by differences in feeding rates, but locomotion appeared more important in determining growth than feeding rate. Our results show that differences in social status may need to be taken into account when testing for correlations between behavioral type and growth in vertebrates, and cautions that growth adjustments may get obscured due to correlated changes in other costly behaviors, like locomotion. Copyright 2011, Oxford University Press.

Suggested Citation

  • Dik Heg & Roger Schürch & Susan Rothenberger, 2011. "Behavioral type and growth rate in a cichlid fish," Behavioral Ecology, International Society for Behavioral Ecology, vol. 22(6), pages 1227-1233.
  • Handle: RePEc:oup:beheco:v:22:y:2011:i:6:p:1227-1233

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    References listed on IDEAS

    1. Bates, Douglas & Mächler, Martin & Bolker, Ben & Walker, Steve, 2015. "Fitting Linear Mixed-Effects Models Using lme4," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i01).
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