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The Effect of Sex and Early Environment on the Lateralization of the Rainbowfish Melanotaenia duboulayi

  • Anne-Laurence Bibost
  • Erin Kydd
  • Culum Brown
Chapter

Abstract

The influence of environmental complexity on the development of brain lateralization during ontogeny was investigated using the rainbowfish, Melanotaenia duboulayi. Male and female fish reared in enriched and impoverished environments were swum in a flume where they schooled with their mirror image on the left- or right-hand side. Interestingly, rearing conditions influenced the development of laterality in each sex differently. Males were more strongly lateralized when reared in enriched conditions compared with those reared in impoverished conditions. In contrast, females tended to show the opposite pattern. This difference in response to enrichment was likely due to variation in life-history priorities between sexes that can provide alterative fitness benefits. Males and females respond to stimuli differently as male are motivated by agonistic interactions with one another and courting females, whereas females are motivated by foraging. These varying motivating factors likely interact with habitat complexity in different ways during development resulting in different developmental trajectories with respect to laterality. When we examined turning preferences of females in a radial maze, we found no differences between fish reared in different habitats with respect to the turn biases. However, we did find that the activity rates of enriched females tended to be higher across all time periods, whereas impoverished fish increased activity levels as they became familiar with the apparatus. In general, our results suggest that male fish laterality may be more responsive to changes in rearing conditions than females.

Keywords

Enrich Environment Habitat Complexity Female Fish Schooling Behavior Cerebral Lateralization 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Department of Biological SciencesMacquarie UniversitySydneyAustralia

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