Aquat. Living Resour.
Volume 13, Number 4, July-August 2000Mechanisms and Effects of the Aggregation of Tuna by FADs
|Page(s)||203 - 211|
|Published online||15 July 2000|
Modeling tuna behaviour near floating objects: from individuals to aggregations
Centre IRD de Montpellier, BP 5045, 34032 Montpellier cedex 1, France
2 Centre IRD de Brest, BP 70, 29280 Plouzané cedex, France
Accepted: 26 July 2000
A fuzzy logic model of tuna behaviour near Fish Aggregating Devices (FADs) was developed to reproduce individual differences in horizontal movements observed from ultrasonic telemetry experiments. In this model, the behaviour of an individual is based on its surrounding environment (FADs and prey) and on its internal state (stomach fullness), which depends on its recent past actions. Internal sensors are used to determine the motivation of the fish, combined with external sensors, this determines its movements. Sensory information and motivation are modeled using fuzzy sets. A FAD attracts an individual when it is located within the FAD’s range of influence. The time spent near a FAD depends on the feeding motivation of the fish and on its surrounding environment. If the fish is not hungry, it stays near the FAD. Otherwise, the fish has to forage in order to eat, and might therefore leave the FAD if no prey is available in its vicinity. By varying the environmental conditions near FADs, the model reproduces the different horizontal movement patterns observed for tunas. The model is then extended to allow multiple individuals to co-exist, each individual modeled through the above behavioural model, without any direct or indirect interactions between them. This way, we study the effects of individual behaviour on tuna aggregation near FADs. We find that the model predicts the temporal dynamics of aggregation around FADs exhibited by tunas. By examining the effects of several FAD network models on the aggregation, we also estimate optimal spatial arrangements of FADs.
Key words: tuna / Fish Aggregating Devices / behaviour / model / fuzzy logic
© Elsevier, Inra, Ifremer, Cemagref, Ird, Cnrs, 2000
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