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Supplementary Materials Assessing the Performance of Statistical Supplementary materials Assessing the performance of statistical classifiers to discriminate fish stocks using Fourier analysis of otolith shape Szymon Smoliński 1,2,5, Franziska Maria Schade3, Florian Berg1,4 1 Institute of Marine Research, P.O. Box 1870 Nordnes, 5817 Bergen, Norway 2 Department of Fisheries Resources, National Marine Fisheries Research Institute, Kołłątaja 1, 81-332 Gdynia, Poland 3 Thuenen Institute of Baltic Sea Fisheries, Alter Hafen Süd 2, 18069 Rostock, Germany 4 University of Bergen, Department of Biological Sciences, P.O. Box 7803, 5020 Bergen, Norway 5 E-mail: [email protected] Table S1. List of scientific papers selected for the review with indicated method for otolith shape classification. DA – Discriminant Analysis, KNN – K Nearest Neighbor, SVM – Support Vector Machines, RF – Random Forest, NB – Naive Bayes, BN – Bayesian Networks, Log – Logistic Regression, HP – HyperPipes, J48 – J48/C4.5, IBk – k-Nearest Neighbours, RoF – Rotation Forest, between-class COA – between-class Correspondence Analysis, NN – Neural Network. Type of classify- No Reference cation method Afanasyev, P. K., Orlov, A. M., and Rolsky, A. Y. 2017. Otolith shape 1 analysis as a tool for species identification and studying the population DA structure of different fish species. Biology Bulletin, 44: 952–959. Aguera, A., and Brophy, D. 2011. Use of saggital otolith shape analysis to discriminate Northeast Atlantic and Western Mediterranean stocks of 2 DA Atlantic saury, Scomberesox saurus saurus (Walbaum). Fisheries Research, 110: 465–471. Arechavala-Lopez, P., Sanchez-Jerez, P., Bayle-Sempere, J. T., Sfakianakis, D. G., and Somarakis, S. 2012. Discriminating farmed 3 gilthead sea bream Sparus aurata and European sea bass Dicentrarchus DA labrax from wild stocks through scales and otoliths. Journal of Fish Biology, 80: 2159–2175. Avigliano, E., Rolón, M. E., Rosso, J. J., Mabragaña, E., and Volpedo, A. V. 2018. Using otolith morphometry for the identification of three 4 sympatric and morphologically similar species of Astyanax from the DA Atlantic Rain Forest (Argentina). Environmental Biology of Fishes, 101: 1319–1328. Bacha, M., Jemaa, S., Hamitouche, A., Rabhi, K., and Amara, R. 2014. Population structure of the European anchovy, Engraulis encrasicolus, 5 DA in the SW Mediterranean Sea, and the Atlantic Ocean: evidence from otolith shape analysis. ICES Journal of Marine Science, 71: 2429–2435. Bacha, M., Jeyid, A. M., Jaafour, S., Yahyaoui, A., Diop, M., and Amara, R. 2016. Insights on stock structure of round sardinella 6 DA Sardinella aurita off north-west Africa based on otolith shape analysis. Journal of Fish Biology, 89: 2153–2166. Bani, A., Poursaeid, S., and Tuset, V. M. 2013. Comparative 7 morphology of the sagittal otolith in three species of south Caspian DA gobies. Journal of Fish Biology, 82: 1321–1332. Bardarson, H., Mcadam, B. J., Thorsteinsson, V., and Hjorleifsson, E. 2017. Otolith shape differences between ecotypes of Icelandic cod 8 (Gadus morhua) with known migratory behaviour inferred from data DA storage tags. Canadian Journal of Fisheries and Aquatic Science, 74: 2122–2130. Begg, G. and Brown, R. W. 2000. Stock identification of haddock 9 Melanogrammus aeglefinus on Georges Bank based on otolith shape DA analysis. Transactions of the American Fisheries Society, 129: 935–945. Benzinou, A., Carbini, S., Nasreddine, K., Elleboode, R., and Mahé, K. 2013. Discriminating stocks of striped red mullet (Mullus surmuletus) in KNN, 10 the Northwest European seas using three automatic shape classification SVM methods. Fisheries Research, 143: 153–160. Bergenius, M. A. J., Begg, G. A., and Mapstone, B. D. 2006. The use of otolith morphology to indicate the stock structure of common coral trout 11 DA (Plectropomus leopardus) on the Great Barrier Reef, Australia. Fishery Bulletin, 104: 498–511. Boudinar, A. S., Chaoui, L., Mahe, K., Cachera, M., and Kara, M. H. 2015. Habitat discrimination of big-scale sand smelt Atherina boyeri 12 Risso, 1810 (Atheriniformes: Atherinidae) in eastern Algeria using DA somatic morphology and otolith shape. Italian Journal of Zoology, 82: 446–453. Boudinar, A. S., Chaoui, L., Quignard, J. P., Aurelle, D., and Kara, M. H. 2016. Otolith shape analysis and mitochondrial DNA markers 13 distinguish three sand smelt species in the Atherina boyeri species DA complex in western Mediterranean. Estuarine, Coastal and Shelf Science, 182: 202–210. Bourehail, N., Morat, F., Lecomte-Finiger, R., and Kara, M. 2015. Using otolith shape analysis to distinguish barracudas Sphyraena sphyraena 14 DA and Sphyraena viridensis from the Algerian coast. Cybium, 39: 271– 278. Brophy, D., Haynes, P., Arrizabalaga, H., Fraile, I., Fromentin, J. M., Garibaldi, F., Katavic, I., et al. 2016. Otolith shape variation provides a 15 DA marker of stock origin for north Atlantic bluefin tuna (Thunnus thynnus). Marine and Freshwater Research, 67: 1023–1036. Burke, N., Brophy, D., and King, P. a. 2008a. Otolith shape analysis: its application for discriminating between stocks of Irish Sea and Celtic Sea 16 DA herring (Clupea harengus) in the. ICES Journal of Marine Science, 65: 1670–1675. Burke, N., Brophy, D., and King, P. A. 2008b. Shape analysis of otolith 17 annuli in Atlantic herring (Clupea harengus); a new method for tracking DA fish populations. Campana, S. E., and Casselman, J. M. 1993. Stock discrimination using 18 otolith shape analysis. Canadian Journal of Fisheries and Aquatic DA Sciences, 50: 1062–1083. Cañás, L., Stransky, C., Schlickeisen, J., Sampedro, M. P., and Fariña, 19 DA A. C. 2012. Use of the otolith shape analysis in stock identification of anglerfish (Lophius piscatorius) in the Northeast Atlantic. ICES Journal of Marine Science. Capoccioni, F., Costa, C., Aguzzi, J., Menesatti, P., Lombarte, A., and Ciccotti, E. 2011. Ontogenetic and environmental effects on otolith 20 shape variability in three Mediterranean European eel (Anguilla DA anguilla, L.) local stocks. Journal of Experimental Marine Biology and Ecology. Cardinale, M., Doering-Arjes, P., Kastowsky, M., and Mosegaard, H. 2004. Effects of sex, stock, and environment on the shape of known-age 21 DA Atlantic cod (Gadus morhua) otoliths. Canadian Journal of Fisheries and Aquatic Science, 61: 158–167. Castonguay, M., Simard, P., and Gagnon, P. 1991. Usefulness of Fourier Analysis of otolith shape for Atlantic mackerel (Scomber scombrus) 22 DA stock discrimination. Canadian Journal of Fisheries and Aquatic Sciences, 48: 296–302. Clardy, T. R. 2008. Spatial and temporal variability in the relative 23 contribution of king mackerel (Scomberomorus cavalla) stocks to winter DA mixed fisheries off South Florida. Fishery Bulletin, 106: 152–160. Curin-Osorio, S., Cubillos, L. A., and Chong, J. 2012. On the intraspecific variation in morphometry and shape of sagittal otoliths of 24 DA common sardine, Strangomera bentincki, off central-southern Chile. Scientia Marina, 76: 659–666. DeVries, D. A., Grimes, C. B., and Prager, M. H. 2002. Using otolith 25 shape analysis to distinguish eastern Gulf of Mexico and Atlantic Ocean DA stocks of king mackerel. Fisheries Research. Doering, P., and Lufwig, J. 1990. Shape analysis of otoliths-a tool for 26 indirect ageing of eel, Anguilla anguilla (L.)? Internationale Revue der DA gesamten Hydrobiologie und Hydrographie, 75: 737–743. Duarte-Neto, P., Lessa, R., Stosic, B., and Morize, E. 2008. The use of sagittal otoliths in discriminating stocks of common dolphinfish 27 DA (Coryphaena hippurus) off northeastern Brazil using multishape descriptors. ICES Journal of Marine Science, 65: 1144–1152. Duncan, R., Brophy, D., and Arrizabalaga, H. 2018. Otolith shape 28 analysis as a tool for stock separation of albacore tuna feeding in the DA Northeast Atlantic. Fisheries Research, 200: 68–74. Farias, I., Vieira, A. R., Gordo, L. S., and Figueiredo, I. 2009. Otolith shape analysis as a tool for stock discrimination of the black 29 DA scabbardfish, Aphanopus carbo Lowe, 1839 (Pisces: Trichiuridae), in Portuguese waters. Scientia Marina, 73: 47–53. Ferguson, G. J., Ward, T. M., and Gillanders, B. M. 2011. Otolith shape and elemental composition: Complementary tools for stock 30 DA discrimination of mulloway (Argyrosomus japonicus) in southern Australia. Fisheries Research, 110: 75–83. Fernandez-Jover, D., and Sanchez-Jerez, P. 2015. Comparison of diet 31 and otolith growth of juvenile wild fish communities at fish farms and DA natural habitats. ICES Journal of Marine Science, 72: 916–929. Finn, J. E., Burger, C. V., and Holland-Bartels, L. 1997. Discrimination among populations of sockeye salmon fry with Fourier Analysis of 32 DA otolith banding patterns formed during incubation. Transactions of the American Fisheries Society, 126: 559–578. Fowler, A. M., Macreadie, P. I., Bishop, D. P., and Booth, D. J. 2015. 33 Using otolith microchemistry and shape to assess the habitat value of oil DA structures for reef fish. Marine Environmental Research, 106: 103–113. Friedland, K., and Reddin, D. 1994. Use of otolith morphology in stock 34 discriminations of Atlantic salmon (Salmo salar). Canadian Journal of DA Fisheries and Aquatic Sciences, 51: 91–98. Galley, E. A., Wright, P. J., and Gibb, F. M. 2006. Combined methods 35 of otolith shape analysis improve identification of spawning areas of DA Atlantic cod. ICES Journal of Marine Science, 63: 1710–1717. Gonzalez-Salas, C., and Lenfant, P. 2007. Interannual variability and intraannual stability of the otolith shape in European anchovy Engraulis 36 DA encrasicolus (L.) in the Bay of Biscay. Journal of Fish Biology, 70: 35– 49. Harbitz, A., and Albert, O. T. 2015. Pitfalls in stock discrimination by 37 shape analysis of otolith contours. ICES Journal of Marine Science, 72: DA 2090–2097. He, T., Cheng, J., Qin, J., Li, Y., and Gao, T. 2018. Comparative 38 analysis of otolith morphology in three species of Scomber. DA Ichthyological Research, 65: 192–201. Hüssy, K., Mosegaard, H., Albertsen, C. M., Nielsen, E. E., Hemmer- Hansen, J., and Eero, M. 2016. Evaluation of otolith shape as a tool for 39 DA stock discrimination in marine fishes using Baltic Sea cod as a case study. Fisheries Research, 174: 210–218.
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