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.
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 (Actinopterygii: 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 garfish 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.,
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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.
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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.