Characterization of sound scattering layers in the Bay of Biscay using broadband acoustics, nets and video
Autoři:
Arthur Blanluet aff001; Mathieu Doray aff001; Laurent Berger aff002; Jean-Baptiste Romagnan aff001; Naig Le Bouffant aff002; Sigrid Lehuta aff001; Pierre Petitgas aff001
Působiště autorů:
Unité Écologie et Modèles pour l’Halieutique, Ifremer, Nantes, France
aff001; Service Acoustique Sous-marine et Traitement de l’Information, Ifremer, Brest, France
aff002
Vyšlo v časopise:
PLoS ONE 14(10)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0223618
Souhrn
Sound scattering layers (SSLs) are observed over a broad range of spatio-temporal scales and geographical areas. SSLs represent a large biomass, likely involved in the biological carbon pump and the structure of marine trophic webs. Yet, the taxonomic composition remains largely unknown for many SSLs. To investigate the challenges of SSL sampling, we performed a survey in a small study area in the Northern Bay of Biscay (France) by combining broadband and narrowband acoustics, net sampling, imagery and video recordings. In order to identify organisms contributing to the observed SSLs, we compared measured frequency spectra to forward predicted spectra derived from biological data. Furthermore, to assess the confidence in SSL characterization, we evaluated uncertainties in modeling, acoustical and biological samplings. Here, we demonstrate for the first time that SSL backscattering intensity in the Bay of Biscay can be dominated in springtime by resonant gas bearing organisms below 100 kHz, namely siphonophores and juvenile fishes and by pteropods at higher frequencies. Thus, we demonstrate the importance of broadband acoustics combined to nets, imagery and video to characterize resonant backscatterers and mixed mesozooplankton assemblages.
Klíčová slova:
Acoustics – Bioacoustics – Copepods – Fish – Resonance frequency – Statistical distributions – Swimming – Acoustic scattering
Zdroje
1. Mair AM, Fernandes PG, Lebourges-Dhaussy A, Brierley AS. An investigation into the zooplankton composition of a prominent 38-kHz scattering layer in the North Sea. Journal of Plankton Research. 2005;27(7):623–633. doi: 10.1093/plankt/fbi035
2. Lavery AC, Wiebe PH, Stanton TK, Lawson GL, Benfield MC, Copley N. Determining dominant scatterers of sound in mixed zooplankton populations. The Journal of the Acoustical Society of America. 2007;122(6):3304. doi: 10.1121/1.2793613 18247742
3. Peña M, Olivar MP, Balbín R, López-Jurado JL, Iglesias M, Miquel J, et al. Acoustic detection of mesopelagic fishes in scattering layers of the Balearic Sea (western Mediterranean). Canadian Journal of Fisheries and Aquatic Sciences. 2014;71(8):1186–1197. doi: 10.1139/cjfas-2013-0331
4. Proud R, Handegard NO, Kloser RJ, Cox MJ, Brierley AS, Handling editor: Demer David. From siphonophores to deep scattering layers: uncertainty ranges for the estimation of global mesopelagic fish biomass. ICES Journal of Marine Science. 2018.
5. Tont SA. Deep scattering layers: patterns in the Pacific. Calif Coop Ocean Fish Investig Rep. 1976;18:112–117.
6. Dietz R. Deep scattering layer in the Pacific and Antarctic Oceans. J mar Res. 1948;7(3):430–442.
7. Irigoien X, Klevjer TA, Røstad A, Martinez U, Boyra G, Acuña JL, et al. Large mesopelagic fishes biomass and trophic efficiency in the open ocean. Nature Communications. 2014;5(1). doi: 10.1038/ncomms4271 24509953
8. Davison PC, Checkley DM, Koslow JA, Barlow J. Carbon export mediated by mesopelagic fishes in the northeast Pacific Ocean. Progress in Oceanography. 2013;116:14–30. doi: 10.1016/j.pocean.2013.05.013
9. Banse K. Zooplankton: Pivotal role in the control of ocean production. ICES Journal of Marine Science. 1995;52(3-4):265–277. doi: 10.1016/1054-3139(95)80043-3
10. Beaugrand G, Brander KM, Lindley JA, Souissi S, Reid PC. Plankton effect on cod recruitment in the North Sea. Nature. 2003;426(6967):661–664. doi: 10.1038/nature02164 14668864
11. Sieburth JM, Smetacek V, Lenz J. Pelagic ecosystem structure: Heterotrophic compartments of the plankton and their relationship to plankton size fractions 1. Limnology and Oceanography. 1978;23(6):1256–1263. doi: 10.4319/lo.1978.23.6.1256
12. Brodeur RD, Seki MP, Pakhomov EA, Suntsov AV. Micronekton—What are they and why are they important? PICES Press. 2005;13:7–11.
13. Kaartvedt S, Staby A, Aksnes D. Efficient trawl avoidance by mesopelagic fishes causes large underestimation of their biomass. Marine Ecology Progress Series. 2012;456:1–6.
14. Kloser RJ, Ryan TE, Keith G, Gershwin L. Deep-scattering layer, gas-bladder density, and size estimates using a two-frequency acoustic and optical probe. ICES Journal of Marine Science: Journal du Conseil. 2016;73(8):2037–2048. doi: 10.1093/icesjms/fsv257
15. Benoit-Bird KJ, Lawson GL. Ecological Insights from Pelagic Habitats Acquired Using Active Acoustic Techniques. Annual Review of Marine Science. 2016;8(1):463–490. doi: 10.1146/annurev-marine-122414-034001 26515810
16. Stanton T, Wiebe PH, Chu D, Benfield MC, Scalon L, Martin LV, et al. On acoustic estimates of zooplankton biomass. ICES Journal of Marine Science. 1994;51(4):505–512. doi: 10.1006/jmsc.1994.1051
17. Davison PC, Koslow JA, Kloser RJ. Acoustic biomass estimation of mesopelagic fish: backscattering from individuals, populations, and communities. ICES Journal of Marine Science. 2015;72(5):1413–1424. doi: 10.1093/icesjms/fsv023
18. Demer DA, Andersen LN, Bassett C, Berger L, Chu D, Condiotty J, et al. USA–Norway EK80 Workshop Report: Evaluation of a wideband echosounder for fisheries and marine ecosystem science. NOAA’s Southwest Fisheries Science Center in San Diego, California, USA: ICES; 2017. 336.
19. Stanton TK, Sellers CJ, Jech JM. Resonance classification of mixed assemblages of fish with swimbladders using a modified commercial broadband acoustic echosounder at 1–6 kHz. Canadian Journal of Fisheries and Aquatic Sciences. 2012;69(5):854–868. doi: 10.1139/f2012-013
20. Jech JM, Lawson GL, Lavery AC. Wideband (15–260 kHz) acoustic volume backscattering spectra of Northern krill (Meganyctiphanes norvegica) and butterfish (Peprilus triacanthus). ICES Journal of Marine Science. 2017;74(8):2249–2261. doi: 10.1093/icesjms/fsx050
21. Bassett C, De Robertis A, Wilson CD, Ratilal HeP. Broadband echosounder measurements of the frequency response of fishes and euphausiids in the Gulf of Alaska. ICES Journal of Marine Science. 2018;75(3):1131–1142. doi: 10.1093/icesjms/fsx204
22. Doray M, Petitgas P, Romagnan JB, Huret M, Duhamel E, Dupuy C, et al. The PELGAS survey: Ship-based integrated monitoring of the Bay of Biscay pelagic ecosystem. Progress in Oceanography. 2018;166:15–29. doi: 10.1016/j.pocean.2017.09.015
23. Lezama-Ochoa A, Ballón M, Woillez M, Grados D, Irigoien X, Bertrand A. Spatial patterns and scale-dependent relationships between macrozooplankton and fish in the Bay of Biscay: an acoustic study. Marine Ecology Progress Series. 2011;439:151–168. doi: 10.3354/meps09318
24. Remond B. Les couches diffusantes du golfe de Gascogne: caractérisation acoustique, composition spécifique et distribution spatiale [PhD Thesis]. Université Pierre et Marie Curie. Institut Français pour l’Exploitation de la MER (IFREMER), Unité Ecologie et Modèles pour l’Halieutiques (EMH); 2015. Available from: http://archimer.ifremer.fr/doc/00267/37784/.
25. Stanton TK, Chu D, Jech JM, Irish JD. New broadband methods for resonance classification and high-resolution imagery of fish with swimbladders using a modified commercial broadband echosounder. ICES Journal of Marine Science. 2010;67(2):365–378. doi: 10.1093/icesjms/fsp262
26. Ainslie MA, Leighton TG. Review of scattering and extinction cross-sections, damping factors, and resonance frequencies of a spherical gas bubble. The Journal of the Acoustical Society of America. 2011;130(5):3184–3208. doi: 10.1121/1.3628321 22087992
27. Trenkel VM, Berger L. A fisheries acoustic multi-frequency indicator to inform on large scale spatial patterns of aquatic pelagic ecosystems. Ecological Indicators. 2013;30:72–79. doi: 10.1016/j.ecolind.2013.02.006
28. Love RH. Predictions of volume scattering strengths from biological trawl data. The Journal of the Acoustical Society of America. 1975;57(2):300. doi: 10.1121/1.380460
29. Doray M, Duhamel E, Huret M, Petitgas P. PELGAS 2016 cruise, Thalassa R/V; 2016.
30. Demer DA, Berger L, Bernasconi M, Eckhard B, Boswell K, Chu D, et al. Calibration of acoustic instruments. Denmark: ICES; 2015. 326. Available from: http://ices.dk/sites/pub/Publication%20Reports/Cooperative%20Research%20Report%20(CRR)/crr326/CRR326.pdf.
31. Maclennan ND, Fernandes PG, Dalen J. A consistent approach to definitions and symbols in fisheries acoustics. ICES Journal of Marine Science. 2002;59(2):365–369. doi: 10.1006/jmsc.2001.1158
32. Trenkel VM, Berger L, Bourguignon S, Doray M, Fablet R, Massé J, et al. Overview of recent progress in fisheries acoustics made by Ifremer with examples from the Bay of Biscay. Aquatic Living Resources. 2009;22(4):433–445. doi: 10.1051/alr/2009027
33. De Robertis A, McKelvey DR, Ressler PH. Development and application of an empirical multifrequency method for backscatter classification. Canadian Journal of Fisheries and Aquatic Sciences. 2010;67(9):1459–1474. doi: 10.1139/F10-075
34. Wiebe PH, Allison D, Kennedy M, Moncoiffe G. A vocabulary for the configuration of net tows for collecting plankton and micronekton. Journal of Plankton Research. 2015;37(1):21–27. doi: 10.1093/plankt/fbu101
35. Colas F, Tardivel M, Perchoc J, Lunven M, Forest B, Guyader G, et al. The ZooCAM, a new in-flow imaging system for fast onboard counting, sizing and classification of fish eggs and metazooplankton. Progress in Oceanography. 2018;166:54–65. doi: 10.1016/j.pocean.2017.10.014
36. Gorsky G, Ohman MD, Picheral M, Gasparini S, Stemmann L, Romagnan JB, et al. Digital zooplankton image analysis using the ZooScan integrated system. Journal of Plankton Research. 2010;32(3):285–303. doi: 10.1093/plankt/fbp124
37. Pilcheral M, Colin S, Irisson JO. EcoTaxa, a tool for the taxonomic classification of images; 2017. Available from: http://ecotaxa.obs-vlfr.fr.
38. Benoit-Bird KJ. The effects of scattering-layer composition, animal size, and numerical density on the frequency response of volume backscatter. ICES Journal of Marine Science. 2009;66(3):582–593. doi: 10.1093/icesjms/fsp013
39. Chu D, Foote KG, Stanton TK. Further analysis of target strength measurements of Antarctic krill at 38 and 120 kHz: Comparison with deformed cylinder model and inference of orientation distribution. The Journal of the Acoustical Society of America. 1993;93(5):2985. doi: 10.1121/1.405818
40. Chu D, Wiebe P. Measurements of sound-speed and density contrasts of zooplankton in Antarctic waters. ICES Journal of Marine Science. 2005;62(4):818–831. doi: 10.1016/j.icesjms.2004.12.020
41. Gorska N, Ona E, Korneliussen R. Acoustic backscattering by Atlantic mackerel as being representative of fish that lack a swimbladder. Backscattering by individual fish. ICES Journal of Marine Science. 2005;62(5):984–995. doi: 10.1016/j.icesjms.2005.03.010
42. Ye Z. Low-frequency acoustic scattering by gas-filled prolate spheroids in liquids. The Journal of the Acoustical Society of America. 1997;101(4):1945–1952. doi: 10.1121/1.418225
43. Scoulding B, Chu D, Ona E, Fernandes PG. Target strengths of two abundant mesopelagic fish species. The Journal of the Acoustical Society of America. 2015;137(2):989–1000. doi: 10.1121/1.4906177 25698030
44. Love RH. Resonant acoustic scattering by swimbladder-bearing fish. The Journal of the Acoustical Society of America. 1978;64(2):571. doi: 10.1121/1.382009
45. Alexander R. Physical aspects of swimbladder function. Biological Reviews. 1966;41(1):141–176. doi: 10.1111/j.1469-185X.1966.tb01542.x 5323464
46. Horn MH. Swimbladder state and structure in relation to behavior and mode of life in stromateoid fishes. Fishery bulletin. 1975;73:95–109.
47. Blaxter J, Batty R. Swimbladder “behaviour” and target strength. Rapports et Proces-verbaux des Réunions du Conseil International pour l’Exploration de la Mer. 1990;189:233–244.
48. Faivre R, Iooss B, Mahévas S, Makowski D, Monod H. Analyse de sensibilité et exploration de modèles: application aux sciences de la nature et de l’environnement. Editions Quae; 2013.
49. McLachlan G, Krishnan T. The EM algorithm and extensions. vol. 382. John Wiley & Sons; 2007.
50. Peña M. Robust clustering methodology for multi-frequency acoustic data: A review of standardization, initialization and cluster geometry. Fisheries Research. 2018;200:49–60.
51. Schmidt J. On the larval and post-larval development of the Argentines (Argentina silus (Ascan.) and Argentina sphyraena (Linné)) with some notes on Mallotus villosus (O. F. Müller). In: MEDDLELSER FRA KOMMISSIONEN FOR HAVUNDERSOGELSER. vol. 2 of FISKERI; 1906. p. 20.
52. Gorska N. Evaluation of sound extinction and echo interference in densely aggregated zooplankton. OCEANOLOGICA. 2000;42(3):315–334.
53. Stranne C, Mayer L, Weber TC, Ruddick BR, Jakobsson M, Jerram K, et al. Acoustic Mapping of Thermohaline Staircases in the Arctic Ocean. Scientific Reports. 2017;7(1). doi: 10.1038/s41598-017-15486-3 29123176
54. Fromant G. Mesure de Matières En Suspension (MES) dans la colonne d’eau par combinaison de méthodes acoustiques et optiques. Université de Bretagne Occidentale. Institut Universitaire Européen de la Mer (IUM), au Laboratoire Domaines Océaniques (LDO—UMR 6538); 2015.
55. Marshall NB. Swimbladder Structure of Deep-sea Fishes in Relation to Their Systematics and Biology. vol. 31 of Discovery reports. National institute of oceanography ed. University Press, 1960; 1960.
56. Doray M, Berger L, Le Bouffant N, Coail JY, Vacherot JP, de La Bernardie X, et al. A method for controlled target strength measurements of pelagic fish, with application to European anchovy (Engraulis encrasicolus). ICES Journal of Marine Science. 2016;73(8):1987–1997. doi: 10.1093/icesjms/fsw084
57. Knutsen T, Hosia A, Falkenhaug T, Skern-Mauritzen R, Wiebe PH, Larsen RB, et al. Coincident Mass Occurrence of Gelatinous Zooplankton in Northern Norway. Frontiers in Marine Science. 2018;5(158).
58. Benfield MC, Lavery AC, Wiebe PH, Greene CH, Stanton TK, Copley NJ. Distributions of physonect siphonulae in the Gulf of Maine and their potential as important sources of acoustic scattering. Canadian Journal of Fisheries and Aquatic Sciences. 2003;60(7):759–772. doi: 10.1139/f03-065
59. Barham EG. Deep Scattering layer migration and composition: observations from a diving saucer. Science. 1966;151(3716):1399–1403. doi: 10.1126/science.151.3716.1399 17817303
60. Pugh PR. The distribution of siphonophores in a transect across the North Atlantic Ocean at 32 N. Journal of Experimental Marine Biology and Ecology. 1975;20(1):77–97. doi: 10.1016/0022-0981(75)90103-3
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