A dynamic optimisation model for the behaviour of tunas at ocean fronts

Citation
Ds. Kirby et al., A dynamic optimisation model for the behaviour of tunas at ocean fronts, FISH OCEANO, 9(4), 2000, pp. 328-342
Citations number
60
Categorie Soggetti
Aquatic Sciences
Journal title
FISHERIES OCEANOGRAPHY
ISSN journal
10546006 → ACNP
Volume
9
Issue
4
Year of publication
2000
Pages
328 - 342
Database
ISI
SICI code
1054-6006(200012)9:4<328:ADOMFT>2.0.ZU;2-Z
Abstract
We present a model that simulates the foraging behaviour of tunas in the vi cinity of ocean fronts. Stochastic dynamic programming is used to determine optimal habitat choice and swimming speed in relation to environmental var iables (water temperature and clarity) and prey characteristics (abundance and energy density). By incorporating submodels for obligate physiological processes (gastric evacuation, standard and active metabolic costs) and sen sory systems (visual feeding efficiency), we have integrated into a single fitness-based model many of the factors that might explain the aggregation of tunas at ocean fronts. The modelling technique describes fitness landsca pes for all combinations of states, and makes explicit, testable prediction s about time- and state-dependent behaviour. Enhanced levels of searching a ctivity when hungry and towards the end of the day are an important feature of the optimal behaviour predicted. We consider the model to be particular ly representative of the behaviour of the warm-a ater tunas or Neothunnus ( e.g. skipjack, Katsuwonus pelamis, and yellowfin, Thunnus albacares) and fo r surface-dwelling temperate tunas (e.g. young albacore, Thunnus alalunga), which are often observed to aggregate near fronts. For the bluefin group ( i.e. older albacore; northern and southern bluefin, Thunnus thynnus and Thu nnus maccoyii), for which extended vertical migrations are a significant an d as yet unexplained component of behaviour, the model is able to reproduce observed behaviour by adopting the lower optimal temperature and standard metabolic rate of albacore. The model cannot explain why physiological diff erences exist between and within the different tuna species, but it does sh ow how differences in susceptibility to thermal stress will permit differen t behaviour.