Fishing logbook-based onboard monitoring: an effective and reliable alternative for tracking the common eel fishery (Ophichthus remiger) in northern Peru
DOI:
https://doi.org/10.47193/mafis.3932026010706Keywords:
Participatory monitoring, monitoring methods, comparative analysis, fishers, small scaleAbstract
Since 2022, the Asociación Peruana de Productores de Anguila (APPA) has implemented two private monitoring systems in the common eel (Ophichthus remiger) fishery in northern Peru: the Onboard Observer System (SOB-anguila), operated by a technical observer, and the Fishing Logbook System (SBP-anguila), carried out by the crew of 19 commercial vessels. Between September 2022 and August 2023, both systems achieved coverage levels of 4.6% (SOB) and 88.5% (SBP) of the 2,414 trips reported by APPA. The reliability of the SBP-anguila was evaluated using indicators of completeness, temporal continuity, spatial and trip-level coverage, in addition to a statistical validation analysis at the haul level. This included the Wilcoxon signed-rank test to compare operational variables such as catch volume, CPUE, fishing effort, bycatch, and discards, as well as Fisher’s exact test to assess the occurrence of juveniles. The results show that the SBP-anguila is a robust and efficient system, with consistent records, broad spatial coverage, and strong representativity. No statistically significant differences were found for six of the eight variables analyzed in comparison with the SOB-anguila. Likewise, the SBP-anguila demonstrated a high capacity to accurately estimate critical variables that require greater coverage, such as bycatch and discards. Its proper implementation, based on timely training, standardized protocols, and the commitment of the harvesting sector, strengthens its potential as an effective, sustainable, and low-cost tool, and its integration into conventional fishery monitoring systems is recommended.
Downloads
References
Agnese F, Othman Z, Mitin A, Wan Yahaya WAJ. 2024. Participatory monitoring in farmer field school program through Whatsapp among indigenous farmers in rural Sarawak, Malaysia. Interac Learn Environ. 32 (9): 5699-5710. DOI: https://doi.org/10.1080/10494820.2023.2223241 DOI: https://doi.org/10.1080/10494820.2023.2223241
Anderson JL, Anderson CM, Chu J, Meredith J, Asche F, Sylvia G, Smith MD, Anggraeni D, Arthur R, Guttormsen A, et al. 2015. The fishery performance indicators: a management tool for triple bottom line outcomes. PLoS ONE. 10 (5): e0122809. DOI: https://doi.org/10.1371/journal.pone.0122809 DOI: https://doi.org/10.1371/journal.pone.0122809
[APPA y REDES-SP] Asociación Peruana de Productores de Anguila y REDES-Sostenibilidad Pesquera. 2022a. Guía de identificación de las especies que interactúan en la pesquería de anguila del norte del Perú: material de soporte para la tripulación a bordo de la flota de la APPA. Lima: APPA y REDES-SP. https://www.anguilaperuana.com/recursos/#flipbook-df_1522/3/.
[APPA y REDES-SP] Asociación Peruana de Productores de Anguila y REDES-Sostenibilidad Pesquera. 2022b. Manual de muestreo y registro a bordo de la pesquería de anguila del norte del Perú: material de soporte para la tripulación a bordo de la flota de la APPA. Lima: APPA y REDES-SP. https://www.anguilaperuana.com/recursos/#flipbook-df_1316/2/.
[APPA y REDES-SP] Asociación Peruana de Productores de Anguila y REDES-Sostenibilidad Pesquera. 2022c. Protocolo de registro, muestreo biométrico y de la composición de captura realizado por el observador a bordo de la flota de la APPA. Versión 1, junio 2022. Proyecto de mejoramiento pesquero de anguila peruana. Lima: APPA y REDES-SP. https://fisheryprogress.org/sites/default/files/documents_actions/I02-I-22-Protocolo%20de%20registro%20de%20la%20bit%C3%A1cora%20de%20pesca%20y%20muestreo%20realizado%20por%20EL%20OBSERVADOR%20a%20bordo%20de%20la%20flota%20de%20la%20APPA.pdf.
[APPA y REDES-SP] Asociación Peruana de Productores de Anguila y REDES-Sostenibilidad Pesquera. 2022d. Protocolo de registro de la bitácora de pesca y muestreo de la composición de la captura realizada por pescadores a bordo de la flota de la APPA. Versión 1, junio 2022. Proyecto de mejoramiento pesquero de anguila peruana. Lima: APPA y REDES-SP. https://fisheryprogress.org/sites/default/files/documents_actions/I01-I-22-Protocolo%20de%20registro%20de%20la%20bit%C3%A1cora%20de%20pesca%20realizada%20por%0PESCADORES%20a%20bordo%20de%20la%20flota%20de%20la%20APPA.pdf.
Babcock EA, Pikitch EK. 2003. How much observer coverage is enough to adequately estimate bycatch? Pew Institute for Ocean Science and Oceana. 36 p. https://oceana.org/wp-content/uploads/sites/18/BabcockPikitchGray2003FinalReport1.pdf.
Benoît HP y Allard J. 2009. Can the data from at-sea observer surveys be used to make general inferences about catch composition and discards? Can J Fish Aquatic Sci. 66 (12): 2025-2039. DOI: https://doi.org/10.1139/F09-116 DOI: https://doi.org/10.1139/F09-116
Boenish R, Willard D, Kritzer JP y Reardon K. 2020. Fisheries monitoring: perspectives from the United States. Aquacult Fish. 5 (3): 131-138. DOI: https://doi.org/10.1016/j.aaf.2019.10.002 DOI: https://doi.org/10.1016/j.aaf.2019.10.002
Casal G, Sánchez-Carnero N, Domínguez-Gómez JA, Kutser T, Freire J. 2012. Assessment of AHS (Airborne Hyperspectral Scanner) sensor to map macroalgal communities on the Ria de Vigo and Ria de Aldan coast (NW Spain). Mar Biol. 159: 1997-2013. DOI: https://doi.org/10.1007/s00227-012-1987-5 DOI: https://doi.org/10.1007/s00227-012-1987-5
Castillo R, Gómez E, Paredes F. 2000. Pesquería y biología de la anguila común Ophichthus pacifici (Gunther) en el Perú. Inf Prog Inst Mar Perú. 134. 19 p. https://hdl.handle.net/20.500.12958/1168.
Cepeda-Cuervo E, Aguilar W, Cervantes V, Corrales M, Díaz I, Rodríguez D. 2008. Intervalos de confianza e intervalos de credibilidad para una proporción. Rev Colomb Estad. 31 (2): 211-228. https://www.redalyc.org/pdf/899/89912222006.pdf.
Cochran WG. 1977. Sampling techniques. 3ra ed. Nueva York: John Wiley y Sons.
Cohen J. 1960. A coefficient of agreement for nominal scales. Educ Psychol Meas. 20 (1): 37-46. DOI: https://doi.org/10.1177/001316446002000104
Cohen J. 1988. Statistical power analysis for the behavioral sciences. 2da ed. Hillsdale: Lawrence Erlbaum Associates. https://utstat.utoronto.ca/brunner/oldclass/378f16/readings/CohenPower.pdf.
Cotter AJR, Course G, Buckland ST, Garrod C. 2002. A PPS sample survey of English fishing vessels to estimate discarding and retention of North Sea cod, haddock, and whiting. Fish Res. 55: 25-35. DOI: https://doi.org/10.1016/S0165-7836(01)00306-X DOI: https://doi.org/10.1016/S0165-7836(01)00306-X
Duarte D, Cadrin S. 2024. Review of methodologies for detecting an observer effect in commercial fisheries data. Fish Res. 274: 107000. DOI: https://doi.org/10.1016/j.fishres.2024.107000 DOI: https://doi.org/10.1016/j.fishres.2024.107000
Elliott VL, Chheng P, Sophorn UY, Holtgrieve GW. 2019. Monitoring of tropical freshwater fish resources for sustainable use. J Fish Biol. 94 (6): 1019-1025. DOI: https://doi.org/10.1111/jfb.13974 DOI: https://doi.org/10.1111/jfb.13974
[FAO] Food and Agriculture Organization of the United Nations. 1997. Fisheries management. FAO Technical Guidelines for Responsible Fisheries. 4. 82 p. https://www.fao.org/4/i2708e/i2708e00.pdf.
[FAO] Food and Agriculture Organization of the United Nations. 1999. Guidelines for the routine collection of capture fishery data. FAO Fish Tech Pap. 382. https://www.fao.org/4/X2465E/x2465e00.htm.
[FAO] Food and Agriculture Organization of the United Nations. 2005. Guidelines for designing data collection and sharing systems for co-managed fisheries. Part 1. Technical guidelines. FAO Fish Tech Pap. 494/2. https://openknowledge.fao.org/server/api/core/bitstreams/ec559698-6e4e-4255-ba96-9ed5024faf64/content.
[FAO] Food and Agriculture Organization of the United Nations. 2019. Participatory monitoring and evaluation in marine protected areas: experiences from North and West Africa/Suivi et évaluation participatifs dans les aires marines protégées: expériences en Afrique du Nord et de l’Ouest. FAO Fisheries and Aquaculture Circular/Circulaire sur les pêches et l’aquaculture. 1173. 96 p. https://openknowledge.fao.org/items/506ecfc2-cf0c-4965-8e4a-b1821d427329.
Fernández-Cásseres MA, Russi-Pulgar D. 2023. Categorical variable analyses: chi-square, Fisher exact, Mantel-Haenszel. Handbook for designing and conducting clinical and translational research. Translational sports medicine. p. 151-156. DOI: https://doi.org/10.1016/B978-0-323-91259-4.00043-6 DOI: https://doi.org/10.1016/B978-0-323-91259-4.00043-6
Fritz CO, Morris PE, Richler JJ. 2012. Effect size estimates: current use, calculations, and interpretation. J Exp Psychol Gen. 141 (1): 2-18. DOI: https://doi.org/10.1037/a0024338 DOI: https://doi.org/10.1037/a0024338
Fulton S, Hernández-Velasco A, Suarez-Castillo A, Fernández-Rivera Melo F, Rojo M, Sáenz-Arroyo A, Hudson Weaver A, Cudney-Bueno R, Micheli F, Torre J. 2019. From fishing fish to fishing data: the role of artisanal fishers in conservation and resource management in Mexico. En: Salas S, Barragán-Paladines M, Chuenpagdee R, editores. Viability and sustainability of small-scale fisheries in Latin America and The Caribbean. MARE Publication Series. 19: 151-175. DOI: https://doi.org/10.1007/978-3-319-76078-0_7 DOI: https://doi.org/10.1007/978-3-319-76078-0_7
Galán J, Carbajal W, Castañeda J. 2007. La anguila Ophichthus remiger en aguas de las islas lobos de afuera, Lambayeque, durante el 2005. Inf Prog Inst Mar Perú. 34 (4): 281-294. https://hdl.handle.net/20.500.12958/1839
Gilman E, Perez Roda A, Huntington T, Kennelly SJ, Suuronen P, Chaloupka M, Medley PAH. 2020. Benchmarking global fisheries discards. Sci Rep. 10: 14017. DOI: https://doi.org/10.1038/s41598-020-71021-x DOI: https://doi.org/10.1038/s41598-020-71021-x
Gutiérrez Torero M, Ñiquen Carranza M, Peraltilla Neyra S, Herrera Almirón N. 2000. Las Operaciones Eureka: una aproximación a la abundancia de anchoveta en el período 1966-1982. Bol Inst Mar Perú. 19 (1-2): 83-102. https://revistas.imarpe.gob.pe/index.php/boletin/article/view/161/150.
Henriques NS, Russo T, Erzini K, Gonçalves JM. 2025. On the accuracy of self-reported data for fishing effort estimates-a case study from a polyvalent coastal fishery. Fish Res. 288: 107483. DOI: https://doi.org/10.1016/j.fishres.2025.107483. DOI: https://doi.org/10.1016/j.fishres.2025.107483
Hoare D, Graham N, Schön P-J. 2011. The Irish Sea data enhancement project: comparison of self-sampling and national data-collection programmes-results and experiences. ICES J Mar Sci. 68: 1778-1784. DOI: https://doi.org/10.1093/icesjms/fsr100
House J, Kleiber D, Steenbergen DJ, Stacey N. 2022. Participatory monitoring in community-based fisheries management through a gender lens. Ambio. 52 (2): 300-318. DOI: https://doi.org/10.1007/s13280-022-01783-3
[IMARPE] Instituto del Mar del Perú. 2019. Aprobar la directiva observación técnica científica de Investigación a bordo de embarcaciones pesqueras. Resolución de Dirección Ejecutiva Científica-2019-IMARPE/DEC. http://www.imarpe.pe/imarpe/archivos/res_DEC_075_2019.pdf.
[IMARPE] Instituto del Mar del Perú. 2020. La pesquería de anguila Ophichthus remiger en el norte del Perú y procecuines de pesca para el año 2021. Informe correspondiente al Oficio Nº 1268-2020-IMARPE/DEC. Callao: IMARPE. https://www.gob.pe/institucion/imarpe/informes-publicaciones/5355454-informe-correspondiente-al-oficio-n-1268-2020-imarpe-pcd.
[IMARPE] Instituto del Mar del Perú. 2021a. La pesquería de anguila Ophichthus remiger en el norte del Perú y proyecciones de pesca para el año 2022. Informe correspondiente al Oficio Nº 1050-2021-IMARPE-PCD. Callao: IMARPE. https://www.gob.pe/institucion/imarpe/informes-publicaciones/3166056-informe-correspondiente-al-oficio-n-1050-2021-imarpe-pcd.
[IMARPE] Instituto del Mar del Perú. 2021b. Programa de observadores a bordo de la flota industrial de cerco “Programa bitácoras de pesca” (PBP), pesquería del stock norte-centro de la anchoveta, reporte de la segunda temporada de pesca 2019. Callao: IMARPE. 23 p. https://www.imarpe.pe/imarpe/archivos/reportes/imarpe_rtp_segunda_temporada_pesca_2019.pdf.
[IMARPE] Instituto del Mar del Perú. 2022a. Informe de la prospección biológica pesquera del recurso anguila Ophichthus remiger, entre los 03° 24′ y 07° 00′ S, del 17 al 22 de agosto del 2022-Operación anguila I. R. M. Nº 266-2022-PRODUCE. Callao: IMARPE. https://cdn.www.gob.pe/uploads/document/file/4576543/PRODUCE-DGPARPA%20Informe%20prospecci%C3%B3n%20recurso%20anguila%20-%2021.09.2022.pdf?v=1684438937.
[IMARPE] Instituto del Mar del Perú. 2022b. Informe de la pesquería de anguila (Ophichthus remiger) en el norte del Perú durante el 2022 y proyecciones de pesca para el año 2023. Informe correspondiente al Oficio Nº 1301-2022-IMARPE-PCD. Callao: IMARPE. https://cdn.www.gob.pe/uploads/document/file/4069828/Informe%20de%20la%20pesquer%C3%ADa%20de%20anguila%20en%20el%20norte%20del%20Per%C3%BA.pdf?v=1674740147.
[IMARPE] Instituto del Mar del Perú. 2023a. Informe de la operación anguila II, extremo norte del dominio marítimo peruano y los 06° 30′ S, 6 al 13 de junio de 2023. R. M. Nº 184-2023-PRODUCE. Informe correspondiente al Oficio Nº 888-2023-IMARPE/PCD. Callao: IMARPE. https://cdn.www.gob.pe/uploads/document/file/4925166/Informe%20Operaci%C3%B3n%20Anguila%20II.pdf.
[IMARPE] Instituto del Mar del Perú. 2023b. Informe de la pesquería de anguila (Ophichthus remiger) en el norte del Perú durante el 2023 y proyecciones de pesca para el año 2024. Informe correspondiente al Oficio Nº 1555-2023-IMARPE/PCD. Callao: IMARPE. https://cdn.www.gob.pe/uploads/document/file/5828533/5171087-informe-de-la-pesqueria-de-anguila-y-proyecciones-de-pesca-2024.pdf?v=1707340845.
Jennings S. 2005. Indicators to support an ecosystem approach to fisheries. Fish Fish. 6 (3): 212-232. DOI: https://doi.org/10.1111/j.1467-2979.2005.00189.x
Jentoft S. 2005. Fisheries co-management as empowerment. Mar Policy. 29 (1): 1-7. DOI: https://doi.org/10.1016/j.marpol.2004.01.003 DOI: https://doi.org/10.1016/j.marpol.2004.01.003
Joo R, Grados D, Bouchon M, Díaz E. 2016. Tamaño óptimo de muestra del programa de observadores a bordo de la flota dirigida a la explotación de la anchoveta peruana (Engraulis ringens). Rev Peru Biol. 23 (2): 169-182. DOI: https://doi.org/10.15381/rpb.v23i2.12429
Kasten P, Jenkins SR, Christofoletti RA. 2021. Participatory monitoring-a citizen science approach for coastal environments. Front Mar Sci. 8: 681969. DOI: https://doi.org/10.3389/fmars.2021.681969 DOI: https://doi.org/10.3389/fmars.2021.681969
Landis JR, Koch GG. 1977. The measurement of observer agreement for categorical data. Biometrics. 33: 159-174. DOI: https://doi.org/10.2307/2529310
Liggins GW, Bradley MJ, Kennelly SJ. 1997. Detection of bias in observer-based estimates of retained and discarded catches from a multi species trawl fishery. Fish Res. 32 (2): 133-147. DOI: https://doi.org/10.1016/S0165-7836(97)00053-2
Lin KK, Arya N, Anderson ST. 2024. Categorical variable analyses. En: Bakal JA, Haglin JM, Abboud J, Crisco JJ, Eltorai AEM, editores. Translational Orthopedics. 1ra ed. Academic Press. p. 147-149. DOI: https://doi.org/10.1016/B978-0-323-85663-8.00069-6
Little LR, Wayte SE, Tuck GN, Smith ADM, Klaer N, Haddon M, Punt AE, Thomson R, Day J, Fuller M. 2011. Development and evaluation of a CPUE-based harvest control rule for the southern and eastern scalefish and shark fishery of Australia. ICES J Mar Sci. 68 (8): 1699-1705. DOI: https://doi.org/10.1093/icesjms/fsr019 DOI: https://doi.org/10.1093/icesjms/fsr019
Løkkeborg S, Pina T. 1997. Effects of setting time, setting direction and soak time on longline catch rates. Fish Res. 32 (3): 213-222. DOI: https://doi.org/10.1016/S0165-7836(97)00070-2
Macaya VJ. 2023. Caracterización de la composición de la captura asociada a la pesquería de peces obtenida mediante el uso de espinel vertical en el archipiélago Juan Fernández (AJF), Chile [tesis de licenciatura]. Concepción: Facultad de Ciencias Naturales y Oceanográficas, Universidad de Concepción. 48 p.
Macdonald P, Angus CH, Cleasby IR, Marshall CT. 2014. Fishers’ knowledge as an indicator of spatial and temporal trends in abundance of commercial fish species: megrim (Lepidorhombus whiffiagonis) in the northern North Sea. Mar Policy. 45: 228-239. DOI: https://doi.org/10.1016/j.marpol.2013.11.001
Maldonado R. 2025. Propuesta de un plan técnico para mitigar la pesca fantasma en la captura de anguila Ophichthus remiger (Valenciennes, 1842) en la zona norte del litoral peruano, 2023-2024. [tesis de licenciatura]. Piura: Facultad de Ingeniería Pesquera, Universidad Nacional de Piura. https://hdl.handle.net/20.500.12676/6474.
Mandeville CP, Nilsen EB, Herfindal I, Finstad AG. 2023. Participatory monitoring drives biodiversity knowledge in global protected areas. Commun Earth Environ. 4 (1): 240. DOI: https://doi.org/10.1038/s43247-023-00906-2
Martina Vásquez JJ. 2018. Estimación del coeficiente de capturabilidad (q) y de la biomasa de anguila común (Ophichthus remiger) del norte de Perú mediante análisis geoestadístico de las densidades de captura. An Cient. 79 (1): 168-177. DOI: http://dx.doi.org/10.21704/ac.v79i1.1159 DOI: https://doi.org/10.21704/ac.v79i1.1159
Mendo T, Mendo J, Ransijn J M, Gomez I, Gil-Kodaka P, Fernández J, Delgado R, Travezaño A, Arroyo R, Loza K, et al. 2022. Assessing discards in an illegal small-scale fishery using fisher-led reporting. Rev Fish Biol Fish. 32 (3): 963-974. DOI: https://doi.org/10.1007/s11160-022-09708-9 DOI: https://doi.org/10.1007/s11160-022-09708-9
Mion M, Piras C, Fortibuoni T, Celic I, Franceschini G, Giovanardi O, Belardinelli A, Martinelli M, Raicevich S. 2015. Collection and validation of selfsampled e-logbook data in a Mediterranean demersal trawl fishery. Reg Stud Mar Sci. 2: 76-86. DOI: https://doi.org/10.1016/j.rsma.2015.08.009 DOI: https://doi.org/10.1016/j.rsma.2015.08.009
Mitroi V, Ahi KC, Bulot PY, Tra F, Deroubaix JF, Ahoutou MK, Quiblier C, Kone´ M, Coulibaly JC, Humbert JF. 2020. Can participatory approaches strengthen the monitoring of cyanobacterial blooms in developing countries? Results from a pilot study conducted in the Lagoon Aghien (Ivory Coast). PLoS ONE. 15 (9): e0238832. DOI: https://doi.org/10.1371/journal.pone.0238832 DOI: https://doi.org/10.1371/journal.pone.0238832
Nardi D, Bozzini A, Morgante G, Gaccione A, Finozzi V, Battisti A. 2023. Participatory ground data are complementary to satellite bark beetle detection. Ann For Sci. 80 (1): 46. DOI: https://doi.org/10.1186/s13595-023-01216-5
NOAA [National Oceanic and Atmospheric Administration Fisheries]. 2020. NOAA fisheries issues emergency action to waive observer coverage on a case-by-case basis. Gobierno de los Estados Unidos. [consultado 15 septiembre 2025]. https://www.fisheries.noaa.gov/action/noaa-fisheries-issues-emergency-action-waive-observer-coverage-case-case-basis?utm_source=chatgpt.com.
Okoye K, Hosseini S. 2024. Wilcoxon statistics in R: signed-rank test and rank-sum test. R programming: statistical data analysis in research. Singapore: Springer Nature Singapore. p. 279-303. DOI: https://doi.org/10.1007/978-981-97-3385-9_13
O’Neill, MF, Campbell AB, Brown IW, Johnstone R. 2010. Using catch rate data for simple cost-effective quota setting in the Australian spanner crab (Ranina ranina) fishery. ICES J Mar Sci. 67: 1538-1552. DOI: https://doi.org/10.1093/icesjms/fsq095 DOI: https://doi.org/10.1093/icesjms/fsq095
Ouled-Cheikh J, Sanpera C, Bécares J, Arcos JM, Carrasco JL, Ramírez F. 2020. Spatiotemporal analyses of tracking data reveal fine-scale, daily cycles in seabird-fisheries interactions. ICES J Mar Sci. 77 (7-8): 2508-2517. DOI: https://doi.org/10.1093/icesjms/fsaa098
Posit PBC. 2024. RStudio (versión 2024.12.0+467) [entorno de desarrollo integrado]. https://posit.co/download/rstudio-desktop/.
Prescott J, Riwu J, Stacey N, Prasetyo A. 2016. An unlikely partnership: fishers’ participation in a small-scale fishery data collection program in the Timor Sea. Rev Fish Biol Fish. 26: 679-692 DOI: https://doi.org/10.1007/s11160-015-9417-7
[PRODUCE] Ministerio de la Producción. 2011. Decreto Supremo Nº 13-2011). Revista Peruana de Biología 13-2011-PRODUCE. Reglamento de Ordenamiento Pesquero del Recurso Anguila (Ophichthus remiger). Lima: PRODUCE. https://spij.minjus.gob.pe/spij-ext-web/#/detallenorma/H1040689.
[PRODUCE] Ministerio de la Producción. 2021a. Resolución Ministerial Nº 81-2021-PRODUCE: Autorizar al Instituto del Mar del Perú-IMARPE la ejecución de la pesca exploratoria del Recurso Anguila (Ophichthus remiger) con la participación de embarcaciones de menor escala por el período de vigencia del régimen provisional de extracción para el citado recurso, aprobado por Resolución Ministerial Nº 453-2020-PRODUCE, en el área marítima comprendida entre los 04° 30′ S y 06° 30′ S, a efectos de obtener información biológica-pesquera que contribuya al aprovechamiento óptimo del Recurso Anguila. Lima: PRODUCE. https://cdn.www.gob.pe/uploads/document/file/1720017/R.%20M.%20N%C2%BA%20081-2021-PRODUCE.pdf.pdf?v=1615292303.
[PRODUCE] Ministerio de la Producción. 2021b. Resolución Ministerial Nº 392-2021-PRODUCE: Modifican la R. M. Nº 81-2021-PRODUCE, que autorizó al IMARPE la ejecución de pesca exploratoria del recurso anguila con participación de embarcaciones de menor escala, por el período de vigencia del régimen provisional de extracción aprobado por R. M. Nº 453-2020-PRODUCE. Lima: PRODUCE. https://busquedas.elperuano.pe/dispositivo/NL/2013460-1.
[PRODUCE] Ministerio de la Producción. 2024a. Resolución Ministerial Nº 374-2024-PRODUCE: Exposición de motivos Decreto Supremo que aprueba el Reglamento de Ordenamiento Pesquero del Recurso Anguila (Ophichthus remiger). Lima: PRODUCE. https://www.gob.pe/institucion/produce/normas-legales/5989411-374-2024-produce.https://cdn.www.gob.pe/uploads/document/file/6941491/5989411-eposicion-de-motivos-rop-anguila.pdf?v=1726421444.
[PRODUCE] Ministerio de la Producción. 2024b. Resolución Ministerial Nº 3-2024-PRODUCE: Establecen el régimen provisional de extracción del recurso anguila para el año 2024. Lima: PRODUCE. https://busquedas.elperuano.pe/dispositivo/NL/2250392-1.
[PRODUCE] Ministerio de la Producción. 2024c. Decreto Supremo Nº 18-2024-PRODUCE: Reglamento de Ordenamiento Pesquero del Recurso Anguila (Ophichthus remiger). Lima: PRODUCE. https://cdn.www.gob.pe/uploads/document/file/7325562/6254554-d-s-n-018-2024-produce%282%29.pdf?v=1734119484.
[PRODUCE] Ministerio de la Producción. 2024d. Ficha técnica de anguila período 2024. Lima: PRODUCE, Oficina de Estudios Económicos (OEE), https://www.producempresarial.pe/wp-content/uploads/2025/02/246-Ficha-Recurso-Anguila_Ano-2024.pdf.
Punt AE, Butterworth DS, De Moor CL, De Oliveira JA, Haddon M. 2014. Management strategy evaluation: best practices. Fish Fish. 17 (2): 303-334. DOI: https://doi.org/10.1111/faf.12104
Radinger J, Britton JR, Carlson SM, Magurran AE, Alcaraz‐Hernández JD, Almodóvar A, Benejam L, Fernández‐Delgado C, Nicola G, Oliva‐Paterna F, et al. 2019. Effective monitoring of freshwater fish. Fish Fish. 20 (4): 729-747. DOI: https://doi.org/10.1111/faf DOI: https://doi.org/10.1111/faf.12373
Ramos CL. 2024. Programa de observadores de campo en la pesca artesanal del Instituto del Mar del Perú [tesis de licenciatura]. Pisco: Facultad de Ingeniería Pesquera y de Alimentos, Universidad Nacional de San Luis Gonzaga. 81 p.
R Core Team. 2024. R: A language and environment for statistical computing (versión 4.5.0) [software]. R Foundation for Statistical Computing. https://www.R-project.org/.
Reis-Filho JA. 2023. The participatory actions of artisanal fishers reveal spatial-temporal trends of seahorse catches as basis for future management. Fish Sci. 89 (3): 317-329. DOI: https://doi.org/10.1007/s12562-023-01677-7 DOI: https://doi.org/10.1007/s12562-023-01677-7
Reis-Filho JA, Ramos-Filho F, Castello L, Giarrizzo T. 2023. I fish, therefore I monitor: participatory monitoring to assess inland small-scale fisheries. Environ Manage. 72 (3): 540-557. DOI: https://doi.org/10.1007/s00267-023-01819-8 DOI: https://doi.org/10.1007/s00267-023-01819-8
Roberson LA, Kiszka JJ, Watson JE. 2019. Need to address gaps in global fisheries observation. Conserv Biol. 33 (4): 966-968. DOI: https://doi.org/10.1111/cobi.13265 DOI: https://doi.org/10.1111/cobi.13265
Robinson J, Graham NAJ, Cinner JE, Almany GR, Waldie P. 2014. Fish and fisher behaviour influence the vulnerability of groupers (Epinephelidae) to fishing at a multispecies spawning aggregation site. Coral Reefs. 34: 371-382. DOI: https://doi.org/10.1007/s00338-014-1243-1 DOI: https://doi.org/10.1007/s00338-014-1243-1
Roman S, Jacobson N, Cadrin SX. 2011. Assessing the reliability of fisher self‐sampling programs. N Am J Fish Manage. 31 (1): 165-175. DOI: https://doi.org/10.1080/02755947.2011.562798 DOI: https://doi.org/10.1080/02755947.2011.562798
Rosenthal R, Rubin DB. 1989. Effect size estimation for one-sample multiple-choice-type data: Design, analysis, and meta-analysis. Psychol Bull. 106 (2): 332-337. DOI: https://doi.org/10.1037/0033-2909.106.2.332. DOI: https://doi.org/10.1037//0033-2909.106.2.332
SAI GLOBAL. 2020. Pesca de anguila (Ophichthus remiger) en el norte del Perú entre las regiones de Tumbes a Piura. Informe de pre evaluación. https://fisheryprogress.org/system/files/documents_assessment/Preevaluacion%20%20Pesca%20Anguila%20Comun%20%20Norte%20de%20Peru_Spanish.pdf.
Silvano RAM, Hallwass G. 2020. Participatory research with fishers to improve knowledge on small-scale fisheries in tropical rivers. Sustainability. 12 (11): 4487. DOI: https://doi.org/10.3390/su12114487
Tomczak M, Tomczak E. 2014. The need to report effect size estimates revisited. An overview of some recommended measures of effect size. Trends Sport Sci. 1 (21): 19-25.
van Helmond ATM, Mortensen LO, Plet‐Hansen KS, Ulrich C, Needle CL, Oesterwind D, Kindt‐Larsen L, et al. 2019. Electronic monitoring in fisheries: lessons from global experiences and future opportunities. Fish Fish. 20 (3): 1-28. DOI: https://doi.org/10.1111/faf.12425 DOI: https://doi.org/10.1111/faf.12425
Villaseñor E, Porter-Bolland L, Escobar F, Guariguata MR, Moreno-Casasola P. 2016. Characteristics of participatory monitoring projects and their relationship to decision-making in biological resource management: a review. Biodivers Conserv. 25: 2001-2019. DOI: https://doi.org/10.1007/s10531-016-1184-9 DOI: https://doi.org/10.1007/s10531-016-1184-9
Wilson EB. 1927. Probable inference, the law of succession, and statistical inference. J Am Statist Assoc. 22 (158): 209-212. DOI: https://doi.org/10.1080/01621459.1927.10502953 DOI: https://doi.org/10.1080/01621459.1927.10502953
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Rosa Vinatea-Chávez, Andrea Pasara-Polack, Jorge Grillo-Núñez, Karla Loza-Choque, Nathaly Vargas
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Authors of articles published in Marine and Fishery Sciences retain copyright on their articles, except for any third-party images and other materials added by Marine and Fishery Sciences, which are subject to copyright of their respective owners. Authors are therefore free to disseminate and re-publish their articles, subject to any requirements of third-party copyright owners and subject to the original publication being fully cited. Visitors may also download and forward articles subject to the citation requirements. The ability to copy, download, forward or otherwise distribute any materials is always subject to any copyright notices displayed. Copyright notices must be displayed prominently and may not be obliterated, deleted or hidden, totally or partially.
This journal offers authors an Open Access policy. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles, or use them for any other legal purpose within the Creative Commons 4.0 license (BY-NC-SA), without asking prior permission from the publisher or the author. This is in accordance with the BOAI definition of Open Access.
