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

We present a model that simulates the foraging behaviour of tunas in the vicinity of ocean fronts. Stochastic dynamic programming is used to determine optimal habitat choice and swimming speed in relation to environmental variables (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 sensory 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 landscapes for all combinations of states, and makes explicit, testable predictions about time- and statedependent behaviour. Enhanced levels of searching activity when hungry and towards the end of the day are an important feature of the optimal behaviour predicted. We consider the model to be particularly representative of the behaviour of the warm-water tunas or Neothunnus (e.g. skipjack, Katsuwonus pelamis, and yellowfin, Thunnus albacares) and for surfacedwelling 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 Thunnus maccoyii), for which extended vertical migrations are a significant and 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 differences exist between and within the different tuna species, but it does show how differences in susceptibility to thermal stress will permit different behaviour.

[1]  Pierre Fréon,et al.  Dynamics of pelagic fish distribution and behaviour : effects on fisheries and stock assessment , 1999 .

[2]  R. Laurs,et al.  Metabolic rate of the albacore tuna Thunnus alalunga , 1982 .

[3]  P. Fiedler,et al.  Tuna aggregation and feeding near fronts observed in satellite imagery , 1987 .

[4]  P. Howey,et al.  Results of pop-up satellite tagging of spawning size class fish in the Gulf of Maine: do North Atlantic bluefin tuna spawn in the mid-Atlantic? , 1999 .

[5]  David A. Fournier,et al.  Physiological and behavioural thermoregulation in bigeye tuna (Thunnus obesus) , 1992, Nature.

[6]  Richard W. Brill,et al.  A review of temperature and oxygen tolerance studies of tunas pertinent to fisheries oceanography, movement models and stock assessments , 1994 .

[7]  J. Power,et al.  Satellite observed sea-surface temperatures and yellowfin tuna catch and effort in the Gulf of Mexico. , 1991 .

[8]  Bart Nooteboom,et al.  A theoretical model , 2018 .

[9]  D. J. Mcfarland.  Decision making in animals , 1977, Nature.

[10]  R. D. Hill.  Microcomputer monitor and blood sampler for free-diving Weddell seals. , 1986, Journal of applied physiology.

[11]  Graham,et al.  STUDIES OF TROPICAL TUNA SWIMMING PERFORMANCE IN A LARGE WATER TUNNEL - ENERGETICS , 1994, The Journal of experimental biology.

[12]  B. Collette,et al.  Scombrids of the world : an annotated and illustrated catalogue of tunas, mackerels, bonitos, and related species known to date. v. 2 , 1983 .

[13]  P. Webb.  Hydrodynamics and Energetics of Fish Propulsion , 1975 .

[14]  Richard W. Brill,et al.  Selective advantages conferred by the high performance physiology of tunas, billfishes, and dolphin fish , 1996 .

[15]  Graham,et al.  STUDIES OF TROPICAL TUNA SWIMMING PERFORMANCE IN A LARGE WATER TUNNEL - THERMOREGULATION , 1994, The Journal of experimental biology.

[16]  Paul C. Fiedler,et al.  Albacore tuna catch distributions relative to environmental features observed from satellites , 1984 .

[17]  J. Magnuson.  COMPARATIVE STUDY OF ADAPTATIONS FOR CONTINUOUS SWIMMING AND HYDROSTATIC EQUILIBRIUM OF SCOMBROID AND XIPHOID FISHES , 1973 .

[18]  J. Emlen.  The Role of Time and Energy in Food Preference , 1966, The American Naturalist.

[19]  Bruce Hannon,et al.  Dynamic Modeling , 1994, Springer US.

[20]  D. L. Aksnes,et al.  A revised model of visual range in fish , 1997 .

[21]  Graham,et al.  STUDIES OF TROPICAL TUNA SWIMMING PERFORMANCE IN A LARGE WATER TUNNEL - KINEMATICS , 1994, The Journal of experimental biology.

[22]  Robert J. Olson,et al.  Apex Predation by Yellowfïn Tuna (Thunnus albacares): Independent Estimates from Gastric Evacuation and Stomach Contents, Bioenergetics, and Cesium Concentrations , 1986 .

[23]  J. Hunter,et al.  The Dynamics of Tuna Movements: An Evaluation of Past and Future Research , 1987 .

[24]  J. Gerritsen.  Size Efficiency Reconsidered: A General Foraging Model for Free-Swimming Aquatic Animals , 1984, The American Naturalist.

[25]  A. Fiúza,et al.  Supporting the Portuguese fisheries with satellites , 1992 .

[26]  Jarl G Iske,et al.  Modelling spatial dynamics of fish , 1998 .

[27]  J. Keen,et al.  Environmental preferences of yellowfin tuna (Thunnus albacares) at the northern extent of its range , 1997 .

[28]  Effect of Water Clarity on Albacore Catches , 1959 .

[29]  I. Nakamura,et al.  Fao Species Catalogue , 1972 .

[30]  T. Schoener.  A Brief History of Optimal Foraging Ecology , 1987 .

[31]  C. Barnard.  Behavioural Ecology: An Evolutionary Approach, 2nd edition, J.R. Krebs, N.B. Davies (Eds.). Blackwell Scientific Publications, Oxford (1984), xi , 1985 .

[32]  Donald B. Olson,et al.  Life on the edge : marine life and fronts , 1994 .

[33]  R. Macarthur,et al.  On Optimal Use of a Patchy Environment , 1966, The American Naturalist.

[34]  Øyvind Fiksen,et al.  A spatially explicit fitness‐based model of capelin migrations the Barents Sea , 1995 .

[35]  L. Gustafsson.  Behavioural ecology: An evolutionary approach (3rd edn): edited by J.R. Krebs and N.B. Davies, Blackwell Scientific Publications, 1991. £19.95 pbk (xi + 482 pages) ISBN 0 632 02702 9 , 1992 .

[36]  Barbara A. Block,et al.  Horizontal movements and depth distribution of large adult yellowfin tuna (Thunnus albacares) near the Hawaiian Islands, recorded using ultrasonic telemetry: implications for the physiological ecology of pelagic fishes , 1999 .

[37]  J. Kitchell,et al.  Tuna Metabolic Rates Estimated from Energy Losses during Starvation , 1991, Physiological Zoology.

[38]  Toward a synthetic eco-ethology of tropical tunas , 1995 .

[39]  Heeny S. H. Yuen,et al.  Swimming Speeds of Yellowfin and Skipjack Tuna , 1966 .

[40]  G. D. Sharp,et al.  AN ENERGETICS MODEL FOR THE EXPLOITED YELLOWFIN TUNA, THUNNUSALBACARES,POPULATION IN THE EASTERN PACIFIC OCEAN , 1976 .

[41]  T. N. Stevenson,et al.  Fluid Mechanics , 2021, Nature.

[42]  G. Kawamura,et al.  Vision in Tunas and Marlins , 1981 .

[43]  J. Magnuson.  Digestion and Food Consumption by Skipjack Tuna (Katsuwonus pelamis) , 1969 .

[44]  J. Giske,et al.  Ecology in Mare Pentium: an individual-based spatio-temporal model for fish with adapted behaviour , 1998 .

[45]  J. Atema.  Chemical senses, chemical signals, and feeding behavior in fishes , 1980 .

[46]  J. Giske,et al.  A theoretical model of aquatic visual feeding , 1993 .

[47]  J. Magnuson,et al.  III. – BIOENERGETIC SPECTRA OF SKIPJACK AND YELLOWFIN TUNAS , 1978 .

[48]  B. Collette,et al.  FAO species catalogue. Volume 2. Scombrids of the world. An annotated and illustrated catalogue of tunas, mackerels, bonitos and related species known to date. , 1983 .

[49]  P W Hochachka,et al.  Microcomputer-assisted metabolic studies of voluntary diving of Weddell seals. , 1986, The American journal of physiology.