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Adaptation of fisheries sonar for monitoring schools of large pelagic fish: dependence of schooling behaviour on fish finding efficiency

Published online by Cambridge University Press:  26 February 2008

Patrice Brehmer ,
Stratis Georgakarakos ,
Erwan Josse ,
Vasilis Trygonis  and
John Dalen
Patrice Brehmer
Affiliation:
University of the Aegean/Co IRD-UR109, Centre de Recherche Halieutique Méditerranéenne et Tropicale, 1 avenue Jean Monnet, BP 171, 34203 Sète, France
Stratis Georgakarakos
Affiliation:
University of the Aegean, Fisheries and Sonar Laboratory, University Hill, 81100 Mytilini, Greece
Erwan Josse
Affiliation:
Institut de Recherche pour le Développement, US004, Centre de Bretagne, BP 70, 29280 Plouzané, France
Vasilis Trygonis
Affiliation:
University of the Aegean, Fisheries and Sonar Laboratory, University Hill, 81100 Mytilini, Greece
John Dalen
Affiliation:
Institute of Marine Research, P.O. Box 1870, Nordnes 5817, Bergen, Norway
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Abstract

Multibeam omnidirectional sonars are tools currently used by fishers, but also allow the monitoring of pelagic fish schools surrounding a platform. Multibeam processing methods now offer improved capacities for raw data storage. The Simrad SP90 sonar was used for the detection of fish schools associated with drifting fish aggregating devices (FADs), and digital systems developed for the acquisition and processing of volume backscattering echoes and position data. Data sampling methods were defined based on two modes: one for periods searching for FADs and associated schools, and one for school monitoring in drifting mode. Validation of the detection of several FAD-associated schooling species was made by simultaneous visual observations or/and cross-checking with echosounder recordings. The characteristics of schooling behaviour in the targeted fish species are fundamental for the correct interpretation of acoustic data. Sonar detection threshold is the result of a compromise between fish number, size, species and the nearest neighbour distance (NND) of individuals per dynamic structure (school or shoal). Tuna schooling dynamics mean that NND can sometimes be too large to allow the presence of these fish to be detected, despite their number. Sonar data should be analysed and interpreted in a holistic manner, in combination with behaviour pattern and dynamics of all species around the drifting FADs. An autonomous sonar buoy prototype equipped with 360° scanning sonar coupled to video cameras will increase our understanding of tuna behaviour around drifting or anchored objects. A similar methodology can be applied to different kinds of platforms, either anchored or in permanent positions. This would improve the monitoring of fish schools around artificial reefs, open sea aquaculture farms, and across estuaries, channels or straits; applications which are undoubtedly essential for progressive fisheries management.

Keywords

Autonomous systemBehaviourBuoyFADSchoolSonarTuna
Type
Research Article
Information
Aquatic Living Resources , Volume 20 , Issue 4: Fish Aggregating Devices as Instrumented Observatories of Pelagic Ecosystems , October 2007 , pp. 377 - 384
Copyright
© EDP Sciences, IFREMER, IRD, 2008

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References

Andersen L.N., Berg S., Gammelsæter O.B., Lunde E.B., 2006, New scientific multibeam systems for fisheries research applications. In: Rodriguez J.SM. (Eds), Proc. 8th Eur. Conf. Underwater Acoustics, pp. 385-386.
Brehmer P., Gerlotto F., Samb B., 2000, Measuring fish avoidance during surveys. ICES CM 2000/K:07.
Brehmer P., Gerlotto F., Rouault A., 2002, In situ inter-standardisation of acoustic data: an integrated database for fish school behavioural studies. Acta Acoust.88, 730-734.
Brehmer, P., Gerlotto, F., Guillard, J., Sanguinède, F., Guénnegan, Y., Buestel, D., 2003, New applications of hydroacoustic methods for monitoring shallow water aquatic ecosystems: the case of mussel culture grounds. Aquat. Living Resour. 16, 333-338. CrossRef
Brehmer, P., Lafont, T., Georgakarakos, S., Josse, E., Gerlotto, F., Collet, C., 2006, Omnidirectional multibeam sonar monitoring: Applications in fisheries science. Fish Fish. 7, 165-179. CrossRef
Brehmer, P., Gerlotto, F., Laurent, C., Cotel, P., Achury, A., Samb, B., 2007, Schooling behaviour of small pelagic fish: phenotypic expression of independent stimuli. Mar. Ecol. Prog. Ser. 334, 263-272. CrossRef
Castro, J.J., Santiago, J.A., Santana-Ortega, A.T., 2001, A general theory on fish aggregation to floating objects: an alternative to the meeting point hypothesis. Rev. Fish Biol. Fish. 11, 255-277. CrossRef
Dagorn, L., Holland, K.N., Itano, D.G., 2007, Behaviour of yellowfin (Thunnus albacares) and bigeye (T. obesus) tuna in a network of fish aggregating devices (FADs). Mar. Biol. 151, 595-606. CrossRef
Dempster, T., Taquet, M., 2004, Fish aggregation device (FAD) research: gaps in current knowledge and future directions for ecological studies. Rev. Fish Biol. Fish. 14, 21-42. CrossRef
Dempster, T., Sanchez-Jerez, P., Bayle-Sempere, J.T., Giménez-Casalduero, F., Valle, C., 2002, Attraction of wild fish to sea-cage fish farms in the south-western Mediterranean Sea: spatial and short-term temporal variability. Mar. Ecol. Prog. Ser. 242, 237-252. CrossRef
Diner N., Massé J., 1987, Fish school behaviour during echo survey observed by acoustic device. Internat. Symp. Fisheries Acoustics, 21-24 June, 1987, Seattle.
Diner, N, 2007, Evaluating uncertainty in measurements of fish shoal aggregate backscattering cross-section caused by small shoal size relative to beam width. Aquat. Living Resour. 20, 17-121. CrossRef
Doray, M., Josse, E., Gervain, P., Reynal, L., Chantrel, J., 2006, Acoustic characterisation of pelagic fish aggregations around moored fish aggregating devices in Martinique (Lesser Antilles). Fish. Res. 82, 162-175. CrossRef
Fedoryako, B.I., 1988, Fish accumulations in the open ocean near stationary buoys. J. Ichthyol. 28, 667–669.
Fonteneau, A., Ariz, J., Gaertner, D., Nordstrom, V., Pallares, P., 2000, Observed changes in the species composition of tuna schools in the Gulf of Guinea between 1981 and 1999, in relation with the Fish Aggregating Device fishery. Aquat. Living Res. 13, 253-257. CrossRef
Foote, K.G., Chu, D., Hammar, T.R., Baldwin, K.C., Mayer, L.A., Hufnagle, L.C., Jech, J.M., 2005, Protocols for calibrating multibeam sonar. J. Acoust. Soc. Am. 117, 2013-2027. CrossRef
Fréon, P., Dagorn, L., 2000, Review of fish associate behaviour: toward a generalisation of the meeting point hypothesis. Rev. Fish Biol. Fish. 10, 183-207. CrossRef
Gerlotto F., Hamitouche C., Simmonds E.J., Georgakarakos S., Fernandes P., 2001, Analyse et visualisation tri-dimensionnelle des images sonar. Final report, Fair CT 96 1717, CRHMT, Sète.
Gaertner, D., Pagavino, M., Marcano, J., 1996, Utilisation de modèles linéaires généralisés pour évaluer les stratégies de pêche thonière à la senne en présence d'espèces associées dans l'Atlantique ouest. Aquat. Living Resour. 9, 305-323. CrossRef
Gerlotto, F., 1993, Identification and spatial stratification of tropical fish concentrations using acoustic populations. Aquat. Living Resour. 6, 243-254. CrossRef
Goncharov, S.E., Borisenko, E.S., Pyanov, A., 1989, Jack mackerel schools defence reaction to a surveying vessel. Proc. Inst. Acoust. 11, 74-78.
Hafsteinsson, M.T., Misund, O.A., 1995, Recording the migration behaviour of fish schools by multi-beam sonar during conventional acoustic surveys. ICES J. Mar. Sci. 52, 915-924. CrossRef
Haugland, E.K., Misund, O.A., 2004, Evidence for a clustered spatial distribution of clupeid fish schools in the Norwegian Sea and off the coast of southwest Africa. ICES J. Mar. Sci. 61, 1088-1092. CrossRef
Josse, E., Bertrand, A., 2000, In situ acoustic target strength measurements of tuna associated with a fish aggregating device. ICES J. Mar. Sci. 57, 911-918. CrossRef
Josse, E., Dagorn, L., Bertrand, A., 2000, Typology and behaviour of tuna aggregations around fish aggregating devices from acoustic surveys in French Polynesia. Aquat. Living Resour. 13, 183-192. CrossRef
Mackinson, S., Nøttestad, L., Guénette, S., Pitcher, T.J., Misund, O.A., Fernö, A., 1999, Cross-scale observations on distribution and behavioural dynamics of ocean feeding Norwegian spring spawning herring (Clupea harengus L.). ICES J. Mar. Sci. 56, 613-626. CrossRef
Marsac F., Fonteneau A., Ménard F., 2000, Drifting FADs used in tuna fisheries: an ecological trap? In: Le Gall J.Y., Cayré P., Taquet M. (Eds.), Pêche thonière et dispositifs de concentration de poissons. Ed. Ifremer, Actes Colloq. 28, 537-552.
Miquel J., Delgado de Molina A., Ariz J., Delgado de Molina R., Déniz S., Díaz N., Iglesias M., Santana J.C., Brehmer P., 2006, Acoustic Selectivity in Tropical Tuna (Experimental Purse-seine Campaign in the Indian Ocean). Western and Central Pacific Fisheries Commission, `WCPFC-SC2', FT WP-8; IOTC-2006-WPTT-06, Manila.
Misund, O.A., 1990, Observation of schooling herring: school dimensions, swimming behaviour and avoidance of vessel and purse seine. Rapp. P.-v. Réun. Cons. Int. Explor. Mer 189, 135–146.
Misund, O.A., Aglen, A., Beltestad, A.K., Dalen, J., 1992, Relationship between the geometric dimensions and biomass of schools. ICES J. Mar. Sci. 49, 305-315. CrossRef
Misund, O.A., Coetzee, J., 2000, Recording fish schools by multi-beam sonar: potential for validating and supplementing echo integration recordings of schooling fish. Fish. Res. 47, 149-159. CrossRef
Palud P., Brehmer P., 2004, Montage du sonar multifaisceaux omnidirectionnel de longue portée SIMRAD SP91–160; Navire: Indian ocean explorer (Belize) EU project: FADIO, 5th Framework Programme, Research Directorate General; Contract #QLRI-CT-2002-02773. Rapp. Techn. CRHMT, Sète.
Parin N.V., Fedoryako B.I., 1999, Pelagic fish communities around floating objects in the open ocean. In: Scott M.D., Bayliff W.H., Lennert-Cody C.E., Schaefer K.M. (Eds.), Proc. Int. Workshop on the Ecology and Fisheries for Tuna Associated with Floating Objects. Inter-Am. Trop. Tuna Comm. Spec. Rep. 11, La Jolla, CA, pp. 447-458.
Pedersen, B., Trevorrow, M.V., 1999, Continuous monitoring of fish in a shallow channel using a fixed horizontal sonar. J. Acoust. Soc. Am. 105, 3126-3135. CrossRef
Petitgas P., Monimeau L., Brehmer P., Gerlotto F., 1996, Characterizing the spatial distribution of fish schools with a point process approach: a first application on sonar recordings. ICES CM 1996/B:31.
Pitcher T. J., 1986, The behavior of teleost fishes. John Hopkins University Press, Baltimore.
Relini, G., Relini, M., Montanari, M., 2000, An offshore buoy as a small artificial island and a fish-aggregating device (FAD) in the Mediterranean. Hydrobiologia 440, 65-80. CrossRef
Rose, G.A., Legget, W.C., 1988, Hydroacoustic signal classification of fish schools by species. Can. J. Fish. Aquat. Sci. 45, 597-604. CrossRef
Simrad 1992, Operator Manual Simrad SR240, Fishery sonar. P2291E Software Version 5.0X.Mar, Simrad AS, Horten, Norway.
Simrad 2003, New Sonar Scientific Data Logger. News Bulletin, Fishery 11, Horten, Norway.
Simrad 2004, Simrad SP90 Low frequency long range fishery sonar; Operator manual. 850-164511 / Rev. E, Simrad AS, Horten, Norway.
Simrad 2007, Operator Manual SX90, Fish finder sonar, Simrad AS, 307672 / Rev. A, Horten, Norway. Taquet M., 2004, Le comportement agrégatif des dorades coryphènes (Coryphaena hippurus) autour des objets flottants. Thèse Doct. Univ. Paris 6.
Tang, Y., Iida, K., Mukai, T., Nishimori, Y., 2006, Estimation of fish school volume using omnidirectional multibeam sonar: scanning modes and algorithms. J. Acoust. Soc. Am. 45, 4868-4974.
Trygonis V., Georgakarakos S., 2007, Investigation of school speed measurement errors by simulation. In: Report, the Working Group on Fisheries Acoustics Science and Technology (WGFAST), ICES Fish. Technol. Comm. ICES CM 2007/FTC:09.