Boletín de Investigaciones Marinas y Costeras

Vol. 54 No. 2 (2025)
Research Articles

Length estimation of anchoveta (Engraulis ringens) using echosounder in difficult to access fishing areas in the Atacama Region, Chile

PDF (Español (España))
  • Luis La Cruz,
  • Cristián Henríquez-Pastene,
  • Adrian Ibieta,
  • Francisco Leiva-Dietz
Luis La Cruz
Instituto de Fomento Pesquero
Cristián Henríquez-Pastene
Instituto de Fomento Pesquero
Adrian Ibieta
Instituto de Fomento Pesquero
Francisco Leiva-Dietz
Instituto de Fomento Pesquero
DOI: https://doi.org/10.25268/bimc.invemar.2025.54.2.1321

Published 2025-07-01

Keywords

  • Pelagic,
  • Peruvian anchoveta,
  • fisheries,
  • monitoring,
  • echo sounder

How to Cite

1.
La Cruz L, Henríquez-Pastene C, Ibieta A, Leiva-Dietz F. Length estimation of anchoveta (Engraulis ringens) using echosounder in difficult to access fishing areas in the Atacama Region, Chile. Bol. Investig. Mar. Costeras [Internet]. 2025 Jul. 1 [cited 2025 Jul. 4];54(2):70-89. Available from: https://boletin.invemar.org.co/ojs/index.php/boletin/article/view/1321

Copyright (c) 2025 Luis Angel La Cruz Aparco, Cristián Henríquez-Pastene, Adrian Ibieta, Francisco Leiva-Dietz

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Abstract

This study explores the use of hydroacoustic methods to estimate the size distribution of Peruvian anchoveta, offering an alternative to traditional biological sampling methods. Acoustic data were collected using two algorithms: Single Target and Tracked Target, along with a
TS to length conversion model specific to Peruvian anchoveta. The results showed that the Single Target algorithm estimated sizes ranging from 8.5 to 16 cm, with a mode of 12.0 cm, while the Tracked Target algorithm identified a range of 9 to 14 cm, with a mode of 11.5
cm. Juvenile anchovies represented 45.8% and 51.2% of the population in each algorithm, respectively. Additionally, the depth of the echoes ranged from 3.92 to 43.95 m, suggesting that larger Peruvian anchoveta tend to inhabit deeper coastal zones, possibly as a physiological
adaptation to these environments. The study demonstrates the effectiveness of hydroacoustics for estimating fish sizes, especially in areas where traditional sampling is inaccessible or difficult to carry out. This approach contributes to understanding fish population dynamics
and opens the door to future studies.

PDF (Español (España))

Downloads

Download data is not yet available.

References

  1. Alheit, J. and Niquen, M. (2004). Regime shifts in the Humboldt Current ecosystem. Progress in Oceanography, 60(2-4), pp.201–222. https://doi.org/10.1016/j.pocean.2004.02.006
  2. Báez, J.C., Gimeno, L. and Real, R. (2021). North Atlantic Os- cillation and Fisheries Management during Global Climate Change. Reviews in Fish Biology and Fisheries, 31, pp. 319–336. https://doi.org/10.1007/s11160-021-09645-z
  3. Balk, H. and Lindem, T. (2000). Amélioration des détections de poissons à partir des données de sonar à double faisceau. Aquatic Living Resources, 13(5), pp. 297–303. https://doi. org/10.1016/s0990-7440(00)01079-2
  4. Bassett, C., De Robertis, A. and Wilson, C.D. (2018). Broad- band echosounder measurements of the frequency re- sponse of fishes and euphausiids in the Gulf of Alaska. ICES Journal of Marine Science, 75(3), pp. 1131–1142. https://doi.org/10.1093/icesjms/fsx204
  5. Benoit‐Bird, K.J. and Waluk, C.M. (2020). Exploring the prom- ise of broadband fisheries echosounders for species dis- crimination with quantitative assessment of data process- ing effects. Journal of the Acoustical Society of America, 147(1), pp. 411–427. https://doi.org/10.1121/10.0000594
  6. Bertrand, A., Gerlotto, F., Bertrand, S., Gutiérrez, M., Alza, L., Chipollini, A., Díaz, E., Espinoza, P., Ledesma, J., Ques- quén, R., Peraltilla, S. and Chavez, F. (2008). Schooling behaviour and environmental forcing in relation to an- choveta distribution: An analysis across multiple spatial scales. Progress in Oceanography, 79(2), pp. 264–277. https://doi.org/10.1016/j.pocean.2008.10.018
  7. Bertrand, A., Segura, M., Gutierrez, M. and Vasquez, L. (2004). From small-scale habitat loopholes to decadal cycles: a habitat-based hypothesis explaining fluctua- tion in pelagic fish populations off Peru. Fish and Fisher- ies, 5(4), pp. 296–316. https://doi.org/10.1111/j.1467- 2679.2004.00165.x
  8. Boswell, K.M., Wilson, M.P. and Wilson, C.A. (2007). Hy- droacoustics as a tool for assessing fish biomass and size distribution associated with discrete shallow water estua- rine habitats in Louisiana. Estuaries and Coasts, 30(4), pp. 607–617. https://doi.org/10.1007/BF02841958
  9. Canales, C.M., Adasme, N.A., Cubillos, L.A., Cuevas, M.J. and Nazareth Sánchez (2018). Long-time spatio-temporal vari- ations in anchovy (Engraulis ringens) biological traits off northern Chile: an adaptive response to long-term environ- mental change? ICES Journal of Marine Science, 75(6), pp.1908–1923. https://doi.org/10.1093/icesjms/fsy082
  10. Castillo, J., Saavedra, A., Leiva, F., Legua, J., La Cruz, L., Alegría, N., Núñez, S., Silva, J. and Sepulveda, A. (2022). Estimación de la fuerza de blanco (TS) para las unidades demográficas de anchoveta a nivel nacional 2020-2019. Chile: Instituto de Fomento Pesquero, p.170.
  11. Castillo, P.R., Ñiquen, M., Cruz, L.L., Guevara-Carrasco, R. and Cuadros, G. (2021). Migration behavior of anchoveta (Engraulis ringens) in the Northern Humboldt Current Sys- tem between September 2019 and September 2020. Latin American Journal of Aquatic Research, 49(5), pp.702–716. http://dx.doi.org/10.3856/vol49-issue5-fulltext-2669
  12. Chavez, F.P. and Messié, M. (2009). A comparison of Eastern Boundary Upwelling Ecosystems. Progress in Ocean- ography, 83(1-4), pp.80–96. https://doi.org/10.1016/j. pocean.2009.07.032
  13. Chu, D. (2011). Technology evolution and advances in fisher- ies acoustics. Journal of Marine Science and Technology, 19(3). https://doi.org/10.51400/2709-6998.2188
  14. De Robertis, A. and Higginbottom, I. (2007). A post-processing technique to estimate the signal-to-noise ratio and remove echosounder background noise. ICES Journal of Marine Science, 64(6), pp.1282–1291. https://doi.org/10.1093/ icesjms/fsm112
  15. Demer, D.A., Berger, L., Bernasconi, M., Bethke, E., Bo- swell, K., Chu, D., Domokos, R., Dunford, A., Fassler, S., Gauthier, S., Hufnagle, L.T., Jech, J.M., Bouffant, N., Lebourges-Dhaussy, A., Lurton, X., Macaulay, G.J., Perrot, Y., Ryan, T., Parker-Stetter, S. and Stienessen, S. (2015). Calibration of acoustic instruments. International Council for the Exploration of the Sea (ICES) Copenhagen, Denmar, Copenhagen, Denmar: International Council for the Exploration of the Sea (ICES) C, p.133. http://dx.doi. org/10.25607/OBP-185
  16. Doray, M., Berger, L., Le Bouffant, N., Yves Coail, J., Vacherot, J.-P., De La Bernardie, X., Morinière, P., Lys, E., Schwab,R. and Petitgas, P. (2016). A method for controlled target strength measurements of pelagic fish, with application to European anchovy (Engraulis encrasicolus). Ices Journal of Marine Science, 73(8), pp.1987–1997. https://doi. org/10.1093/icesjms/fsw084
  17. Foote, K.G. (1987). Fish target strengths for use in echo integrator surveys. The Journal of the Acoustical So- ciety of America, 82(3), pp. 981–987. https://doi. org/10.1121/1.395298.
  18. Ganais, K. (2014). Biology and ecology of sardines and ancho- vies. CRC Press, p. 394.
  19. Garcés, C., Niklitschek, E.J., Plaza, G., Cerna, F., Leisen, M., Toledo, P. and Barra, F. (2019). Anchoveta Engraulis ringens along the Chilean coast: Management units, demographic units and water masses: Insights from multiple otolith‐based approaches. Fisheries Oceanography, 28(6), pp.735–750. https://doi.org/10.1111/fog.12455.
  20. Gibson, R.N., Atkinson, A. and Gordon (2016). Oceanog- raphy and Marine Biology. 1st ed. [online] CRC Press. Available at: https://www.taylorfrancis.com/chapters/ edit/10.1201/9781420094220-9/review-underwater-stereo- image-measurement-marine-biology-ecology-applications- mark-shortis-euan-harvey-dave-abdo .
  21. Gutiérrez, M., Swartzman, G., Bertrand, A. and Bertrand, S. (2007). Anchovy (Engraulis ringens) and sardine (Sardinops sagax) spatial dynamics and aggregation patterns in the Humboldt Current ecosystem, Peru, from 1983?2003. Fisheries Oceanography, 16(2), pp. 155–168. https://doi.org/10.1111/j.1365-2419.2006.00422.x
  22. Gutiérrez, T.M., Castillo, P.J., Naranjo, B.L. and Akester, M.J. (2017). Current state of goods, services and governance of the Humboldt Current Large Marine Ecosystem in the context of climate change. Environmental Develop- ment, 22, pp. 175–190. https://doi.org/10.1016/j.en- vdev.2017.02.006
  23. Harrison, D.E. and Chiodi, A.M. (2015). Multi-decadal vari- ability and trends in the El Niño-Southern Oscillation and tropical Pacific fisheries implications. Deep Sea Research Part II: Topical Studies in Oceanography, 113, pp. 9–21. https://doi.org/10.1016/j.dsr2.2013.12.020
  24. Hasegawa, K., Yan, N. and Mukai, T. (2021). In situ broadband acoustic measurements of age-0 walleye pollock and pointhead flounder in Funka Bay, Hokkaido, Japan. Jour- nal of marine science and technology, 29(2). https://doi. org/10.51400/2709-6998.1076
  25. Hazen, E.L. and Horne, J.K. (2003). A method for evaluating the effects of biological factors on fish target strength. ICES Journal of Marine Science, 60(3), pp. 555–562. https://doi.org/10.1016/S1054-3139(03)00053-5
  26. Hernández-Santoro, C., Landaeta, M.F. and Jorge Castillo Pizarro (2018). Effect of ENSO on the distribution and con- centration of catches and reproductive activity of anchovy Engraulis ringens in northern Chile. Fisheries Oceanogra- phy, 28(3), pp. 241–255. https://doi.org/10.1016/S1054-3139(03)00053-5
  27. Hesterberg, T. (2011). Bootstrap. Wiley Interdisciplinary Reviews: Computational Statistics, 3(6), pp. 497–526. https://doi.org/10.1002/wics.182
  28. Hilborn, R. and Walters, C.J. (2013). Quantitative Fisheries Stock Assessment. Springer eBooks, 3(6), p. 570. https:// doi.org/10.1007/978-1-4615-3598-0
  29. Hinchliffe, C., Kuriyama, P.T., Punt, A.E., Field, J.C., Thomp- son, A.R., Santora, J.A., Muhling, B.A., Koenigstein, S., Hernvann, P.-Y. and Tommasi, D. (2025). Long-term popu- lation trend of northern anchovy (Engraulis mordax) in the California Current system. ICES Journal of Marine Sci- ence, 82(1). https://doi.org/10.1093/icesjms/fsae177
  30. IFOP (2025). Programa de seguimiento de las principales pesquerías pelágicas de la zona norte de Chile, entre la Región Arica– Parinacota y Coquimbo, año 2024. Subsec- retaría de Economía y EMT / febrero 2025. IFOP, p. 15.
  31. Knudsen, H.P. (2006). Gauging the Reliability of Acoustic Instruments for Fisheries Surveys. Oceans, 69, pp. 1–6. https://doi.org/10.1109/OCEANS.2006.307044
  32. Korneliussen, R.K. (2018). Fifty years of marine tag recoveries from Atlantic salmon. ICES Cooperative Research Report, 343, p. 110. https://doi.org/10.17895/ices.pub.4542
  33. Kubilius, R., Bergès, B. and Macaulay, G.J. (2023). Remote acoustic sizing of tethered fish using broadband acous- tics. Fisheries Research, 260, p.106585. https://doi. org/10.1016/j.fishres.2022.106585
  34. Kubilius, R., Macaulay, G.J. and Ona, E. (2020). Remote siz- ing of fish-like targets using broadband acoustics. Fisher- ies Research, 228, p.105568. https://doi.org/10.1016/j.fishres.2020.105568
  35. Ladroit, Y., Escobar-Flores, P.C., Schimel, A.C.G. and O’Driscoll, R.L. (2020). ESP3: An open-source software for the quantitative processing of hydro-acoustic data. SoftwareX, 12, p. 100581. https://doi.org/10.1016/j. softx.2020.100581
  36. Letessier, T.B., Proud, R., Meeuwig, J.J., Cox, M.J., Hosegood, P.J. and Brierley, A.S. (2021). Estimating Pelagic Fish Biomass in a Tropical Seascape Using Echosounding and Baited Stereo-Videography. Ecosystems, 25(6), pp. 1400–1417. https://doi.org/10.1007/s10021-021-00723-8
  37. Loranger, S., Jech, M.J. and Lavery, A.C. (2022). Broadband acoustic quantification of mixed biological aggregations at the New England shelf break. The Journal of the Acousti- cal Society of America, 152(4), pp. 2319–2335. https://doi. org/10.1121/10.0014910
  38. Love, R.H. (1971). Measurements of fish target strength: a review. Fishery Bulletin, 69(4), pp. 703–715.
  39. Love, R.H., Fialkowski, J.M. and Jagielo, T.H. (2016). Target strength distributions of Pacific sardine schools: Model results at 500 Hz to 10 kHz. The Journal of the Acoustical Society of America, 140(6), pp. 4456–4471. https://doi. org/10.1121/1.4966553
  40. Maclennan, D., Fernandes, P. and Dalen, J. (2002). A con- sistent approach to definitions and symbols in fisheries acoustics. ICES Journal of Marine Science, 59(2), pp. 365–369. https://doi.org/10.1006/jmsc.2001.1158
  41. Nielsen, J. and Lundgren, B. (1999). Hydroacoustic ex situ target strength measurements on juvenile cod (Gadus morhua L.). ICES Journal of Marine Science, 56(5), pp. 627–639. https://doi.org/10.1006/jmsc.1999.0515
  42. Ñiquen, M. and Bouchon, M. (2004). Impact of El Niño events on pelagic fisheries in Peruvian waters. Deep Sea Re- search Part II: Topical Studies in Oceanography, 51(6-9), pp. 563–574. https://doi.org/10.1016/j.dsr2.2004.03.001
  43. Ona, E. (1999). Methodology for Target Strength measure- ments (With special reference to in situ techniques for fish and mikro-nekton). ICES Cooperative Research Report, 235(65), p. 35. https://doi.org/10.17895/ices.pub.5367
  44. Ortiz, M. (2020). Pre-image population indices for anchovy and sardine species in the Humboldt Current System off Peru and Chile: Years decaying productivity. Ecologi- cal Indicators, 119, p. 106844. https://doi.org/10.1016/j. ecolind.2020.106844
  45. Øvredal, J.T. and Totland, B. (2002). The scantrol FishMe- ter for recording fish length, weight and biological data. Fisheries Research, 55(1-3), pp. 325–328. https://doi. org/10.1016/S0165-7836(01)00274-0.
  46. Palermino, A., De Felice, A., Canduci, G., Biagiotti, I., Costan- tini, I., Centurelli, M. and Leonori, I. (2023). Application of an analytical approach to characterize the target strength of ancillary pelagic fish species. Scientific Reports, 13(1). https://doi.org/10.1038/s41598-023-42326-4
  47. Reid, R.G. (2000). Report on echo trace classification. ICES Cooperative Research Report, 238, p. 155.
  48. Robotham, H., Bosch, P., Gutiérrez-Estrada, J.C., Castillo, J. and Inmaculada Pulido-Calvo (2009). Acoustic identifica- tion of small pelagic fish species in Chile using support vector machines and neural networks. Fisheries Re- search, 102(1-2), pp. 115–122. https://doi.org/10.1016/j. fishres.2009.10.015
  49. RStudio, T. (2020). Rstudio: integrated development for r. Rstudio Team. [online] rstudio.com. Available at: http:// www.rstudio.com
  50. Ryan, T.E., Downie, R.A., Kloser, R.J. and Keith, G. (2015). Reducing bias due to noise and attenuation in open-ocean echo integration data. ICES Journal of Marine Science, 72(8), pp. 2482–2493. https://doi.org/10.1093/icesjms/ fsv121
  51. Sawada, K., Furusawa, M. and Williamson, N.J. (1993). Condi- tions for the precise measurement of fish target strength in situ. The Journal of The Marine Acoustics Society of Ja- pan, 20(2), pp. 73–79. https://doi.org/10.3135/jmasj.20.73
  52. Simmonds, J. and MacLennan , D. (2025). Fisheries acoustics: Theory and practice. Fish and Aquatic Resources. [online] https://books.google.cl/books?id=1w5LiIr3NdoC. Available at: https://books.google.cl/books?id=1w5LiIr3NdoC
  53. Soule, M., Barange, M., Haakon Solli and Hampton, I. (1997). Performance of a new phase algorithm for discriminating between single and overlapping echoes in a split-beam echosounder. ICES Journal of Marine Science, 54(5), pp. 934–938. https://doi.org/10.1006/jmsc.1997.0270

Similar Articles

1 2 3 4 5 6 7 8 9 > >> 

You may also start an advanced similarity search for this article.