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, 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

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 (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.

Ider, D., Ramdane, Z., Mahé, K., Duffour, J., Bacha, M., and Amara, R. 40 DA 2017. Use of otolith-shape analysis for stock discrimination of Boops boops along the Algerian coast (southwestern Mediterranean Sea).

African Journal of Marine Science, 39: 251–258.

Jemaa, S., Bacha, M., Khalaf, G., Dessailly, D., Rabhi, K., and Amara,

R. 2015. What can otolith shape analysis tell us about population 41 DA structure of the European sardine, Sardina pilchardus, from Atlantic and

Mediterranean waters? Journal of Sea Research, 96: 11–17.

Jones, W. A., and Checkley, D. M. 2017. Classification of otoliths of

fishes common in the Santa Barbara Basin based on morphology and 42 DA, RF chemical composition. Canadian Journal of Fisheries and Aquatic

Sciences, 74: 1195–1207.

Jónsdóttir, I. G., Campana, S. E., and Marteinsdottir, G. 2006. Otolith

43 shape and temporal stability of spawning groups of Icelandic cod (Gadus DA

morhua L.). ICES Journal of Marine Science, 63: 1501–1512.

Karahan, A., Borsa, P., Gucu, A. C., Kandemir, I., Ozkan, E., Orek, Y.

A., Acan, S. C., et al. 2014. Geometric morphometrics, Fourier analysis

44 of otolith shape, and nuclear-DNA markers distinguish two anchovy DA

species (Engraulis spp.) in the Eastern Mediterranean Sea. Fisheries

Research, 159: 45–55.

Keating, J. P., Brophy, D., Officer, R. A., and Mullins, E. 2014. Otolith

shape analysis of blue whiting suggests a complex stock structure at 45 DA their spawning grounds in the Northeast Atlantic. Fisheries Research,

157: 1–6.

Kemp, J., Swearer, S. E., Jenkins, G. P., and Robertson, S. 2011. Otolith

46 chemistry is more accurate than otolith shape in identifying cod species DA

(genus Pseudophycis) in the diet of Australian fur seals (Arctocephalus pusillus doriferus). Canadian Journal of Fisheries and Aquatic Science,

68: 1732–1743.

Khemiri, S., Gaamour, A., Ben Abdallah, L., and Fezzani, S. 2018. The

47 use of otolith shape to determine stock structure of Engraulis DA

encrasicolus along the Tunisian coast. Hydrobiologia, 821: 73–82.

Lattuca, M. E., Lozano, I. E., Brown, D. R., Renzi, M., and Luizon, C.

A. 2015. Natural growth, otolith shape and diet analyses of Odontesthes 48 DA nigricans Richardson (Atherinopsidae) from southern Patagonia.

Estuarine, Coastal and Shelf Science, 166: 105–114.

Lee, B., Brewin, P. E., Brickle, P., and Randhawa, H. 2018. Use of

otolith shape to inform stock structure in Patagonian toothfish 49 DA (Dissostichus eleginoides) in the south-western Atlantic. Marine and

Freshwater Research, 69: 1238.

Leguá, J., Plaza, G., Pérez, D., and Arkhipkin, A. 2013. Otolith shape

analysis as a tool for stock identification of the southern blue whiting, 50 DA Micromesistius australis. Latin American Journal of Aquatic Research,

41: 479–489.

Libungan, L. A., and Pálsson, S. 2015. ShapeR: An R Package to study

51 otolith shape variation among fish populations. PLoS ONE, 10: DA

e012110.

Longmore, C., Fogarty, K., Neat, F., Brophy, D., Trueman, C., Milton,

A., and Mariani, S. 2010. A comparison of otolith microchemistry and

52 otolith shape analysis for the study of spatial variation in a deep-sea DA

teleost, Coryphaenoides rupestris. Environmental Biology of Fishes, 89:

591–605. Lord, C., Morat, F., Lecomte-Finiger, R., and Keith, P. 2012. Otolith

shape analysis for three Sicyopterus (Teleostei: Gobioidei: Sicydiinae) 53 DA species from New Caledonia and Vanuatu. Environmental Biology of

Fishes, 93: 209–222.

Mahé, K., Evano, H., Mille, T., Muths, D., and Bourjea, J. 2016. Otolith

shape as a valuable tool to evaluate the stock structure of swordfish 54 DA Xiphias gladius in the Indian Ocean. African Journal of Marine Science,

38: 457–464.

NB, BN,

Log, HP, Mapp, J., Hunter, E., Van Der Kooij, J., Songer, S., and Fisher, M. 2017. J48, RF, 55 Otolith shape and size: The importance of age when determining indices KNN, for fish-stock separation. Fisheries Research, 190: 43–52. SVM,

RoF

Mejri, M., Trojette, M., Allaya, H., Ben Faleh, A., Jmil, I., Chalh, A.,

Quignard, J. P., et al. 2018. Use of otolith shape to differentiate two

56 lagoon populations of Pagellus erythrinus (: Perciformes: DA

Sparidae) in Tunisian waters. Acta Ichthyologica et Piscatoria, 48: 153–

161.

Mérigot, B., Letourneur, Y., and Lecomte-Finiger, R. 2007.

Characterization of local populations of the common sole Solea solea 57 DA (Pisces, Soleidae) in the NW Mediterranean through otolith

morphometrics and shape analysis. Marine Biology, 151: 997–1008. Midway, S. R., Cadrin, S. X., and Scharf, F. S. 2014. Southern flounder

58 (Paralichthys lethostigma) stock structure inferred from otolith shape DA

analysis. Fisheries Bulletin, 112: 326–338.

Mirasole, A., Gillanders, B. M., Reis-Santos, P., Grassa, F., Capasso, G.,

Scopelliti, G., Mazzola, A., et al. 2017. The influence of high pCO2 on

59 otolith shape, chemical and carbon isotope composition of six coastal DA

fish species in a Mediterranean shallow CO2 vent. Marine Biology, 164:

191.

Morat, F., Letourneur, Y., Nerini, D., Banaru, D., and Batjakas, I. E.

2012. Discrimination of red mullet populations (Teleostean, Mullidae)

60 along multi-spatial and ontogenetic scales within the Mediterranean DA

basin on the basis of otolith shape analysis. Aquatic Living Resources,

25: 27–39.

Boundary- Nasreddine, K., Benzinou, A., and Fablet, R. 2009. Shape geodesics for based 61 the classification of calcified structures: Beyond Fourier shape classify- descriptors. Fisheries Research, 98: 8–15. cation

Neves, A., Sequeira, V., Farias, I., Vieira, A. R., Paiva, R., and Gordo,

L. S. 2010. Discriminating bluemouth, Helicolenus dactylopterus

62 (Pisces: Sebastidae), stocks in Portuguese waters by means of otolith DA

shape analysis. Journal of the Marine Biological Association of the

United Kingdom, 91: 1237–1242.

Paul, K., Oeberst, R., and Hammer, C. 2013. Evaluation of otolith shape

63 analysis as a tool for discriminating adults of Baltic cod stocks. Journal DA

of Applied Ichthyology, 29: 743–750. Petursdottir, G., Begg, G. A., and Marteinsdottir, G. 2006.

Discrimination between Icelandic cod (Gadus morhua L.) populations 64 DA from adjacent spawning areas based on otolith growth and shape.

Fisheries Research, 80: 182–189.

Ponton, D. 2006. Is geometric morphometrics efficient for comparing between-

65 otolith shape of different fish species? Journal of Morphology, 267: class

750–757. COA

Pothin, K., Gonzalez-Salas, C., Chabanet, P., and Lecomte-Finiger, R.

2006. Distinction between Mulloidichthys flavolineatus juveniles from 66 DA Reunion Island and Mauritius Island (south-west Indian Ocean) based on

otolith morphometrics. Journal of Fish Biology, 69: 38–53.

Radhakrishnan, K. V., Li, Y., Jayalakshmy, K. V., Liu, M., Murphy, B.

R., and Xie, S. 2012. Application of otolith shape analysis in identifying 67 DA different ecotypes of Coilia ectenes in the Yangtze Basin, China.

Fisheries Research, 125–126: 156–160.

Radhakrishnan, K. V, Liu, M., He, W., Murphy, B. R., and Xie, S. 2010.

Otolith retrieval from faeces and reconstruction of prey-fish size for visual 68 Great Cormorant (Phalacrocorax carbo) wintering at the East Dongting judgment Lake National Nature Reserve, China. Environmental Biology of Fishes,

89: 505–512.

Rodgveller, C. J., Hutchinson, C. E., Harris, J. P., Vulstek, S. C., and

Guthrie, C. M. 2017. Otolith shape variability and associated body 69 DA growth differences in giant grenadier, Albatrossia pectoralis. PLOS

ONE, 12: e0180020. Sadighzadeh, Z., Tuset, V. M., Valinassab, T., Dadpour, M. R., and

Lombarte, A. 2012. Comparison of different otolith shape descriptors

70 and morphometrics for the identification of closely related species of DA

Lutjanus spp. from the Persian Gulf. Marine Biology Research, 8: 802–

814.

Sahyoun, R., Claudet, J., Fazio, G., Da Silva, C., and Lecomte-Finiger,

71 R. 2007. The otolith as stress indicator of parasitism on European eel. DA

Vie et milieu - life and environment, 57: 193–200.

Salimi, N., Loh, K. H., Dhillon, S. K., and Chong, V. C. 2016. Fully-

automated identification of fish species based on otolith contour: using 72 DA short-time Fourier transform and discriminant analysis (STFT-DA).

PeerJ, 4:e1664.

Schulz-Mirbach, T., and Reichenbacher, B. 2008. Fossil Aphanius

(Teleostei, Cyprinodontiformes) from southwestern Anatolia (Turkey): 73 DA A contribution to the evolutionary history of a hotspot of freshwater

biodiversity. Geodiversitas, 30: 577–592.

Schulz-Mirbach, T., Stransky, C., Schlickeisen, J., and Reichenbacher,

B. 2008a. Differences in otolith morphologies between surface- and

74 cave-dwelling populations of Poecilia mexicana (Teleostei, Poeciliidae) DA

reflect adaptations to life in an extreme habitat. Evolutionary Ecology

Research, 10: 537–558.

Schulz-Mirbach, T., Scherb, H., and Reichenbacher, B. 2008b. Are

75 hybridization and polyploidization phenomena detectable in the fossil DA

record? - A case study on otoliths of a natural hybrid, Poecilia formosa (Teleostei: Poeciliidae). Neues Jahrbuch Fur Geologie und

Palaontologie-Abhandlungen, 249: 223–238.

Schulz-Mirbach, T., and Plath, M. 2012. All good things come in threes

76 species delimitation through shape analysis of saccular, lagenar and DA

utricular otoliths. Marine and Freshwater Research, 63: 934–940.

Shepard, K. E., Patterson III, W. F., and DeVries, D. A. 2010. Trends in

Atlantic contribution to mixed-stock king mackerel landings in South 77 DA Florida inferred from otolith shape analysis. Marine and Coastal

Fisheries: Dynamics, Management, and Ecosystem Science, 2: 195–204.

Simoneau, M., Casselman, J. M., and Fortin, R. 2000. Determining the

effect of negative allometry (length/height relationship) on variation in 78 DA otolith shape in lake trout (Salvelinus namaycush), using Fourier-series

analysis. Canadian Journal of Zoology, 78: 1597–1603.

Smith, M. 1992. Regional Differences in Otolith Morphology of the

79 Deep Slope Red Snapper Etelis carbuncdus. Canadian Journal of DA

Fisheries and Aquatic Sciences, 49: 795–804.

Steer, M. A., and Fowler, A. J. 2015. Spatial variation in shape of

80 otoliths for southern Hyporhamphus melanochir - Contribution DA

to stock structure. Marine Biology Research, 11: 504–515.

Stransky, C. 2005. Geographic variation of golden redfish (Sebastes

marinus) and deep-sea redfish (S. mentella) in the North Atlantic based 81 DA on otolith shape analysis. ICES Journal of Marine Science, 62: 1691–

1698.

Stransky, C., and MacLellan, S. E. 2005. Species separation and 82 DA zoogeography of redfish and rockfish (genus Sebastes) by otolith shape analysis. Canadian Journal of Fisheries and Aquatic Sciences, 62: 2265–

2276.

Stransky, C., Baumann, H., Fevolden, S. E., Harbitz, A., Høie, H.,

Nedreaas, K. H., Salberg, A. B., et al. 2008a. Separation of Norwegian 83 DA coastal cod and Northeast Arctic cod by outer otolith shape analysis.

Fisheries Research, 90: 26–35.

Stransky, C., Murta, A. G., Schlickeisen, J., and Zimmermann, C.

2008b. Otolith shape analysis as a tool for stock separation of horse 84 DA mackerel (Trachurus trachurus) in the Northeast Atlantic and

Mediterranean. Fisheries Research, 89: 159–166.

Torres, G. J., Lombarte, A., and Morales-Nin, B. 2000a. Variability of

85 the sulcus acusticus in the sagittal otolith of the genus Merluccius DA

(Merlucciidae). Fisheries Research, 46: 5–13.

Torres, G. J., Lombarte, A., and Morales-Nin, B. 2000b. Sagittal otolith

size and shape variability to identify geographical intraspecific 86 DA differences in three species of the genus Merluccius. Journal of the

Marine Biological Association of the UK, 80: 333–342.

Tracey, S. R., Lyle, J. M., and Duhamel, G. 2006. Application of

87 elliptical Fourier analysis of otolith form as a tool for stock DA

identification. Fisheries Research, 77: 138–147.

Trojette, M., Ben Faleh, A., Fatnassi, M., Marsaoui, B., Mahouachi, N.

E. H., Chalh, A., Quignard, J.-P., et al. 2015. Stock discrimination of

88 two insular populations of Diplodus annularis (Actinopterygii: DA

Perciformes: Sparidae) along the coast of Tunisia by analysis of otolith

shape. Acta Ichthyologica et Piscatoria, 45: 363–372. Tuset, V. M., Parisi-Baradad, V., and Lombarte, A. 2013. Application of

otolith mass and shape for discriminating scabbardfishes Aphanopus 89 DA spp. in the north-eastern Atlantic Ocean. Journal of Fish Biology, 82:

1746–1752.

Vasconcelos, J., Vieira, A. R., Sequeira, V., González, J. A., Kaufmann,

M., and Gordo, L. S. 2018. Identifying populations of the blue jack

90 mackerel (Trachurus picturatus) in the Northeast Atlantic by using DA

geometric morphometrics and otolith shape analysis. Fishery Bulletin,

116: 81–92.

Vieira, A. R., Neves, A., Sequeira, V., Paiva, R. B., and Gordo, L. S.

2014. Otolith shape analysis as a tool for stock discrimination of 91 DA forkbeard (Phycis phycis) in the Northeast Atlantic. Hydrobiologia, 728:

103–110.

Vignon, M., Morat, F., Galzin, R., and Sasal, P. 2008. Evidence for

spatial limitation of the bluestripe snapper Lutjanus kasmira in French 92 DA Polynesia from parasite and otolith shape analysis. Journal of Fish

Biology, 73: 2305–2320.

Villegas-Hernández, H., González-Salas, C., Aguilar-Perera, A., and

López-Gómez, M. J. 2008. Settlement dynamics of the coral reef fish 93 DA Stegastes partitus, inferred from otolith shape and microstructure

analysis. Aquatic Biology, 1: 249–258.

Villegas-Hernández, H., Rodríguez-Canul, R., Guillén-Hernández, S.,

Zamora-Bustillos, R., and González-Salas, C. 2014. Population 94 DA differentiation in Haemulon plumieri juveniles across the northern coast

of the Yucatan Peninsula. Aquatic Biology, 20: 129–137. Villegas-Hernández, H., Lloret, J., Muñoz, M., Poot-López, G. R.,

Guillén-Hernández, S., and González-Salas, C. 2018. Age-specific

95 environmental differences on the otolith shape of the bastard grunt DA

(Pomadasys incisus) in the north-western Mediterranean. Environmental

Biology of Fishes, 101: 775–789.

Wang, Y., Ye, Z., Liu, Q., and Cao, L. 2011. Stock discrimination of

spottedtail goby (Synechogobius ommaturus) in the Yellow Sea by 96 DA analysis of otolith shape. Chinese Journal of Oceanology and

Limnology, 29: 192–198.

Wong, J. Y., Chu, C., Chong, V. C., Dhillon, S. K., and Loh, K. H. 2016.

97 Automated otolith image classification with multiple views: an DA

evaluation on Sciaenidae. Journal of Fish Biology, 89: 1324–1344.

Youssef, E. H., Youssef, E., Mostafa, E. Y., Driss, M., Fathallah, N.,

Alain, C., and Khalid, M. 2016. Otolith recognition system using a 98 NN normal angles contour. In International Conference on Image and Signal

Processing, pp. 30–39.

Yu, X., Cao, L., Liu, J., and Zhao, B. 2014. Application of otolith shape

analysis for stock discrimination and species identification of five goby 99 DA species (Perciformes: Gobiidae) in the northern Chinese coastal waters.

Chinese Journal of Oceanology and Limnology, 32: 1060–1073.

Zhang, C., Ye, Z., Panhwar, S. K., and Shen, W. 2013. Stock

discrimination of the Japanese Spanish mackerel (Scomberomorus 100 DA niphonius) based on the otolith shape analysis in the Yellow Sea and

Bohai Sea. Journal of Applied Ichthyology, 29: 368–373. Zhang, C., Ye, Z., Wan, R., Ma, Q., and Li, Z. 2014. Investigating the

population structure of small yellow croaker (Larimichthys polyactis) 101 DA using internal and external features of otoliths. Fisheries Research, 153:

41–47.

Zhang, C., Ye, Z., Li, Z., Wan, R., Ren, Y., and Dou, S. 2016.

Population structure of Japanese Spanish mackerel Scomberomorus

102 niphonius in the Bohai Sea, the Yellow Sea and the East China Sea: RF

evidence from random forests based on otolith features. Fisheries

Science, 82: 251–256.

Zhang, C., Fan, Y., Ye, Z., Li, Z., and Yu, H. 2017. Identification of five

103 Pampus species from the coast of China based on sagittal otolith DA

morphology analysis. Acta Oceanologica Sinica, 36: 51–56.

Zhao, B., Liu, J., Song, J., Cao, L., and Dou, S. 2017. Evaluation of

removal of the size effect using data scaling and elliptic Fourier

104 descriptors in otolith shape analysis, exemplified by the discrimination DA

of two yellow croaker stocks along the Chinese coast. Chinese Journal of

Oceanology and Limnology, 35: 1482–1492.

Zhao, B., Liu, J., Song, J., Cao, L., and Dou, S. 2018. Otolith shape

analysis for stock discrimination of two Collichthys genus croaker 105 DA (Pieces: Sciaenidae,) from the northern Chinese coast. Journal of

Oceanology and Limnology, 36: 981–989. Science Press.

Zhuang, L., Ye, Z., and Zhang, C. 2014. Application of otolith shape

analysis to species separation in Sebastes spp. from the Bohai Sea and 106 DA the Yellow Sea, northwest Pacific. Environmental Biology of Fishes, 98:

547–558.

1 Fig S1. Results of hyperparameter tuning for classification of fish based on cod otolith shape

2 descriptors for a) KNN, b) CART, c) RF, d) SVM. Number of neighbors and number of

3 randomly selected predictors are indicated with # in a) and c).

4 Fig S2. Results of hyperparameter tuning for classification of fish based on herring otolith

5 shape descriptors for a) KNN, b) CART, c) RF, d) SVM. Number of neighbors and number of

6 randomly selected predictors are indicated with # in a) and c).

7 Fig. S3. Mean shapes of otoliths reconstructed for different stocks and stock components of

8 cod (a) and herring (b) based on Fourier descriptors. 9

10 Fig. S4. Classification accuracy of different statistical models based on herring data split into

11 2-class subsets. The names of selected stock components are indicated in the titles of the

12 plots. The box represents the interquartile range (IQR) with the median (midline) accuracy

13 obtained during cross-validation, and the first and third quantiles at the bottom and top of the 14 box, respectively. Lower and upper whiskers are restricted to 1.5 x IQR and black dots

15 represent outliers.