What drives foraging behaviour of the intertidal limpet Cellana grata? A quantitative test of a dynamic optimization model



  1. State-dependent models (SDMs) of behaviour, based on dynamic fitness-maximizing optimality routines, offer a powerful approach to understanding the plasticity and complexity in the timing of behaviour of foraging animals; yet, they are rarely developed for individual species. Such models permit evaluation of the sensitivity of predicted behavioural patterns to parameters that describe the main elements of environmental risk and the dynamics of internal states, such as energy stores, that determine motivational state.

  2. Here, we develop a state-dependent dynamic model for the temporal organization of foraging in a cyclic environment, using the intertidal grazing limpet Cellana grata as a test species. Estimates of relevant parameter values were obtained wherever possible and a sensitivity analysis performed to estimate the relative importance of these parameters.

  3. The results demonstrated the value of constructing an optimality model of the combined effects of gut processing and food supply, alongside the costs and risks of foraging. The dynamic model was able to satisfactorily reproduce the foraging behaviour of the limpet and highlighted several emergent details of behaviour that were not immediately apparent or predicted using a more simple, static model.

  4. Ranking the importance of the different parameters in the foraging behaviour of the limpet helped to identify research priorities for further studies on these grazers. Among the investigated parameters, standing crop and gut volume appeared to be of greatest importance, while energy costs and ingestion rates were of relatively lower importance. Risks of mortality during the different phases also played a fundamental role, dictating the main temporal limits within which activity occurred.

  5. Even with the great number of parameters required with respect to simpler static models, the benefits of following such a dynamic approach were evident and outweighed the additional effort needed for their estimation, supporting the use of dynamic modelling approaches in future research into the behaviour of mobile consumers.