Open Access
Issue
Aquat. Living Resour.
Volume 39, 2026
Article Number 14
Number of page(s) 14
DOI https://doi.org/10.1051/alr/2026008
Published online 29 May 2026
  • Alhoniemi E, Himberg J, Parviainen J, Vesanto J. 1999. SOM-Toolbox 2.0. https://github.com/ilarinieminen/SOM-Toolbox. (accessed 05 December 2025). [Google Scholar]
  • Amandè MJ, Ariz J, Chassot E, et al. 2008. Bycatch and discards of the European purse seine tuna fishery in the Indian Ocean: Characteristics and estimation for the 2003–2007 period. Indian Ocean Tuna Commission document, IOTC-2008-WPEB-12, 23 p. [Google Scholar]
  • Ariyarathna MM, Amarasinghe US. 2012. A fishery associated with floating objects in the Indian ocean off southern Sri Lanka. Asian Fish Sci. 25: 278–289. [Google Scholar]
  • Chathurika KBE, Dissanayake DCT. 2016. Initial study on catch, species composition and reproductive biology of fishes off the south-west coast of Sri Lanka, targeted by ring nets while utilizing natural floating objects. J. Appl. Ichthyol. 32: 464–470. [Google Scholar]
  • Cheilari A, Guillen J, Damalas D, Barbas T. 2013. Effects of the fuel price crisis on the energy efficiency and the economic performance of the European Union fishing fleets. Mar. Policy 40: 18–24. [Google Scholar]
  • Coulter A, Cashion T, Cisneros-Montemayor AM, Popov S, Tsui G, Le Manach F, Schiller L, Palomares MLD, Zeller D, Pauly D. 2020. Using harmonized historical catch data to infer the expansion of global tuna fisheries. Fish Res. 221: 105379. [Google Scholar]
  • Dagorn L, Holland KN, Restrepo V, Moreno G. 2013. Is it good or bad to fish with FADs? What are the real impacts of the use of drifting FADs on pelagic marine ecosystems? Fish Fish. 14: 391–415. [Google Scholar]
  • Davies TK, Mees CC, Milner-Gulland EJ. 2014. The past, present and future use of drifting fish aggregating devices (FADs) in the Indian Ocean. Mar. Policy 45: 163–170. [Google Scholar]
  • 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. [Google Scholar]
  • DFAR. 2025. Fishing boat operation licenses and online departure data base of the Department of Fisheries and Aquatic Resources, 2024. https://www.msdfar.com (accessed 19 April 2025). [Google Scholar]
  • Dunn OJ. 1964. Multiple comparisons using rank sums. Technometrics 6: 241–252. [Google Scholar]
  • Dupaix A, Ménard F, Filmalter JD, Baidai Y, Bodin N, Capello M, et al. 2024. The challenge of assessing the effects of drifting fish aggregating devices on the behaviour and biology of tropical tuna. Fish Fish. 25: 381–400. [Google Scholar]
  • FAO. 1995. Code of Conduct for Responsible Fisheries. Rome, FAO. 41p. [Google Scholar]
  • Fréon P, Dagorn L. 2000. Review FAO. 1995. Code of Conduct for Responsible Fisheries. Food and Agriculture Organization of the United Nations, Rome, p. 41. [Google Scholar]
  • Gulland JA. 1983. Fish stock assessment: A Manual of Basic Methods, FAO/Wiley Series on Food and Agriculture, Vol. 1, Wiley, Manchester, p. 223. [Google Scholar]
  • Gunawardane NDP, de Croos MDST, Amarasinghe US. 2023. Spatio-temporal patterns of the multi-day fishing in the Indian Ocean off Sri Lanka, and their importance for fisheries monitoring, control and surveillance. Reg. Stud. Mar. Sci. 66: 103168. [Google Scholar]
  • Hewapathirana HPK, Maldeniya R, Perera ULK. 2015. Sri Lanka: National Report to the Scientific Committee of the Indian Ocean Tuna Commission, 2015. IOTC-2015-SC18-NR26. Indian Ocean Tuna Commission, Victoria, Mahé, Seychelles. [Google Scholar]
  • Hilborn R, Branch TA, Ernst B, Magnusson A, Minte-Vera CV, Scheuerell MD, Valero JL. 2003. State of the world’s fisheries. Annu. Rev. Environ. Resour. 28: 359–399. [Google Scholar]
  • Kivilnoto K. 1996. Topology preservation in self-organizing maps, Proceedings of ICNN’96, IEE International Conference on Neural Networks, IEEF, Service Center. [Google Scholar]
  • Kohonen T. 2001. Self-Organizing Maps, 3rd edn, Springer, Berlin. https://doi.org/10.1007/978-3-642-56927-2. [Google Scholar]
  • Kohonen T. 2014. MATLAB Implementations and Applications of the Self-Organizing Map, Unigrafia Oy, Helsinki, Finland, ISBN: 9789526036786 [Google Scholar]
  • Lek S, Guégan JF. 2000. Artificial Neural Networks: Application To Ecology and Evolution, Springer Verlag, Berlin, https://doi.org/10.1007/978-3-642-57030-8. [Google Scholar]
  • Lek S, Scardi M, Verdonschot PEM, Descy J-P, Park Y-S. 2005. Modelling Community Structure in Freshwater Ecosystems, Springer-Verlag, Berlin, p. 518. https://doi.org/10.1007/b138251. [Google Scholar]
  • Ministry of Fisheries (MoF). 2022. Mid-term Plan 2023–2027. Ministry of Fisheries, Colombo, p. 39. [Google Scholar]
  • Mitsunaga Y, Endo C, Babaran RP. 2013. Schooling behavior of juvenile yellowfin tuna Thunnus albacares around a fish aggregating device (FAD) in the Philippines. Aquat. Living Resour. 26: 79–84. [Google Scholar]
  • Noranarttragoon P, Sinanan P, Boonjohn N, Khemakorn P, Yakupitiyage A. 2013. The FAD fishery in the Gulf of Thailand: time for management measures. Aquat. Living Resour. 26: 85–96. [Google Scholar]
  • Park Y-S, Céréghino R, Compin A, Lek S. 2003. Applications of artificial neural networks for patterning and predicting aquatic insect species richness in running waters. Ecol. Modell. 160: 265–280. [Google Scholar]
  • Park Y-S, Oberdoff T, Lek S. 2005. Patterning riverine fish assemblages using an unsupervised neural network, in: Lek S, Scardi M, Verdonschot PFM, Descy JP, Park Y-S (Eds.), Modelling Community Structure in Freshwater Ecosystems, Springer-Verlag, Heidelberg, pp. 43–53. https://doi.org/10.1007/3-540-26894-4_5. [Google Scholar]
  • Park Y-S, Grenouillet G, Esperance B, Lek S. 2006. Stream fish assemblages and basin land cover in a river network. Sci. Total Environ. 365: 140–153. [Google Scholar]
  • Punyadewa NBP, Deepananda KHMA, Gunawardane NDP, Digamadulla DS, Amarasinghe US. 2025. A flotsam-associated fishery in the Indian Ocean, and its potential impact on pelagic bycatch species. Sri Lanka J. Aquat. Sci. 30: 83–100. [Google Scholar]
  • R Core Team. 2022. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna. https://www.R-project.org [Google Scholar]
  • Ross RR, Savada AM. 1990. Sri Lanka: A Country Study, 2nd edn, Area Handbook Series, Library of Congress, Federal Research Division, Washington DC, p. 322. [Google Scholar]
  • Rousseau Y, Watson RA, Blanchard JL, Fulton EA. 2019. Evolution of global marine fishing fleets and the response of fished resources. Proc. Natl. Acad. Sci. U.S.A. 116: 12238–12243. [Google Scholar]
  • Sumaila UR, Teh L, Watson R, Tyedmers P, Pauly D. 2008. Fuel price increase, subsidies, overcapacity, and resource sustainability. ICES J. Mar. Sci. 65: 832–840. [Google Scholar]
  • Sumaila UR, Ebrahim N, Schuhbauer A, Skerritt D, Li Y, Kim HS, Mallory TG, Lam VWL, Pauly D. 2019. Updated estimates and analysis of global fisheries subsidies. Mar. Policy 109: 103695. [Google Scholar]
  • Sun C, Hobday AJ, Condie SA, Baird ME, Eveson JP, Hartog JR, et al. 2022. Ecological forecasting and operational information systems support sustainable ocean management. Forecasting 4: 1051–1079. [Google Scholar]
  • United Nations. 2025. United Nations Fish Stocks Agreement: A Guide for Raising Awareness, Furthering Understanding and Strengthening Implementation of its Provisions. United Nations, Office of Legal Affairs Division for Marine Affairs and the Law of the Sea, New York, p. 279. [Google Scholar]
  • Vatanen T, Osmala T, Raiko K, Lagus M, Sysi-Aho M, Orešič T, Honkela H, Lähdesmäki M. 2015. Self-organization and missing values in SOM and GTM. Neurocomputing 147: 60–70. [Google Scholar]
  • Vesanto J. 2005. SOM implementation in SOM toolbox. SOM toolbox online help. Available online: http://www.cis.hut.fi/projects/somtoolbox/documentation/somalg.shtml. (accessed 05 December 2025). [Google Scholar]
  • Vesanto J, Himberg J, Alhoniemi E, Parhankangas J. 2000. SOM Toolbox for Matlab 5. SOM Toolbox Team. Helsinki University of Technology, Helsinki, Finland, http://www.cis.hut.fi/projects/somtoolbox/. (Accessed on 05 December 2025). [Google Scholar]
  • Vierros M, Suttle CA, Harden-Davies H, Burton G. 2016. Who owns the ocean? Policy issues surrounding marine genetic resources. Limnol. Oceanogr. Bull. 25: 29–35. [Google Scholar]

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