University of Oxford

Iain's homepage
Main Current Research Publications Links CV

IC Biovision

Play

  Abstract

 

Submitted

Modelling density-dependent fish shoal distributions in the laboratory and field

Hensor, E.M.A. (1*), Couzin, I.D. (2), James, J (3) & Krause, J (1)

 

1 School of Biology, University of Leeds, Leeds, LS2 9JT, UK

2 Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA

3 Department of Physics, University of Bath, Bath BA2 7AY, UK.


*Author for correspondence.

Density-dependent variables have long been established as an important area of ecological research, but the effects of the local density of conspecifics on behaviour are less well-studied. We compared the influence of the density of conspecifics on the shoal size distribution of killifish, Fundulus diaphanus, in the laboratory and the field. In both environments we observed an increase in shoal size and shoal number with the density of individuals present. The increase in shoal size was markedly more steep in the field than in the laboratory, but direct comparison of the two was complicated by the fact that the absolute numbers of fish present at the field site were considerably higher than those used in the laboratory trials. We developed an individual-based model that was first used as a null model of shoal formation (defined by proximity to others) in fish with no shoaling tendency over the same range of densities used in the laboratory. Group size increased much more rapidly with increasing density in the laboratory than predicted by the null model. When we incorporated shoaling behaviour into our model, the laboratory results could be reproduced with high accuracy. However, when extrapolated to match conditions in the field, the model predicted smaller, more numerous shoals than were actually observed. We suggest this is due to heterogeneity of the field environment because fish were found to be highly aggregated in certain areas of our field site. The predictive power of laboratory studies for the field is discussed with regards to using individual-based modelling as tool for deriving such predictions.


©2002 Princeton UniversityE-mail me MainCurrent ResearchPublications • Links • CV • IC Biovision • Play