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Growth zones and back-calculation for the sea urchin, Sphaerechinus granularis, from the Bay of Brest, France

Published online by Cambridge University Press:  11 May 2009

L.J.L. Lumingas
Affiliation:
URA CNRS D1513, Laboratoire d'Océanographie Biologique, Institut d'Etudes Marines, Université de Bretagne Occidentals 6 Avenue Le Gorgeu, BP 809, 29285 Brest Cedex, France.
M. Guillou
Affiliation:
URA CNRS D1513, Laboratoire d'Océanographie Biologique, Institut d'Etudes Marines, Université de Bretagne Occidentals 6 Avenue Le Gorgeu, BP 809, 29285 Brest Cedex, France.

Abstract

A procedure for accurately determining age and growth of the sea urchin Sphaerechinus granularis (Lamarck) (Echinodermata: Echinoidea) in the Bay of Brest (France) is described. Readings of growth lines were made from the longitudinal cross-section of interambulacral oral plates of sea urchins collected in February 1993. These results agree with age estimates calculated using the ELEFAN I programme based on diameter-frequency distributions of sea urchins collected from February 1992 to March 1993. A non-linear regression (monomolecular equation) best describes the relationship between test diameter and plate thickness. The diameter-at-age data can be increased by back-calculation, assuming a constant proportional deviation from the mean size of the test. Although von Bertalanffy growth curves fitted to actual observations were similar to those fitted to back-calculated diameter-at-age data, the latter produced a more adequate curve and increased the quality of the growth parameter estimators. The von Bertalanffy growth curve estimated by ELEFAN I shows a pattern similar to the back-calculated von Bertalanffy growth curve.

Type
Research Article
Copyright
Copyright © Marine Biological Association of the United Kingdom 1994

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References

Bartlett, J.R., Randerson, P.F., Williams, R. & Ellis, D.M., 1984. The use of analysis of covariance in the back-calculation of growth in fish. Journal of Fish Biology, 24, 201213.CrossRefGoogle Scholar
Bertalanffy, L. Von, 1938. A quantitative theory of organic growth (inquiries on growth laws II). Human Biology, 10, 181213.Google Scholar
Cabioch, L., 1968. Contribution à la connaissance des peuplements benthiques de la Manche occidentale. Cahiers de Biologie Marine, 9, supplement, 493720.Google Scholar
Campana, S.E., 1990. How reliable are growth back-calculations based on otoliths? Canadian Journal of Fisheries and Aquatic Sciences, 47, 22192227.CrossRefGoogle Scholar
Casselman, J.M., 1987. Determination of age and growth. In The biology of fish growth (ed. A.H., Weatherley and H.S., Gill), pp. 209242. London: Academic Press.Google Scholar
Comely, C.A. & Ansell, A.D., 1988. Population density and growth of Echinus esculentus L. on the Scottish west coast. Estuarine, Coastal and Shelf Science, 27, 311334.CrossRefGoogle Scholar
Dahl, K., 1909. The assessment of age and growth in fish. Internationale Revue der Gesamten Hydrobiologie und Hydrographie, 2, 758769.CrossRefGoogle Scholar
Dix, T.G., 1972. Biology of Evechinus chloroticus (Echinoidia: Echinometridae) from different localities. 4. Age, growth, and size. New Zealand Journal of Marine and Freshwater Research, 6, 4868.CrossRefGoogle Scholar
Draper, N.R. & Smith, H., 1981. Applied regression analysis. New York: John Wiley and Sons.Google Scholar
Dubois, P. & Chen, C.-P., 1989. Calcification in echinoderms. In Echinoderm studies, vol. 3 (ed. M., Jangoux and J.M., Lawrence), pp. 109178. Rotterdam: A.A. Balkema.Google Scholar
Ebert, T. A., 1988. Calibration of natural growth lines in ossicles of two sea urchins, Strongylocentrotus purpuratus and Echinometra mathaei, using tetracycline. In Echinoderm biology (ed. R.D., Burkeet al.), pp. 435443. Rotterdam: A.A. Balkema.Google Scholar
Francis, R.I.C.C., 1990. Back-calculation of fish length: a critical review. Journal of Fish Biology, 36, 883902.CrossRefGoogle Scholar
Fraser, C.McL., 1916. Growth of the spring salmon. Transactions of the Pacific Fisheries Society, 1915, 2935.Google Scholar
Gage, J.D., 1991. Skeletal growth zones as age-markers in the sea urchin Psammechinus miliaris, Marine Biology, 110, 217228.CrossRefGoogle Scholar
Gage, J.D., 1992. Natural growth bands and growth variability in the sea urchin Echinus esculentus: results from tetracycline tagging. Marine Biology, 114, 607616.CrossRefGoogle Scholar
Gayanilo, F.C. Jr, Soriano, M. & Pauly, D., 1988. A draft guide to the Compleat ELEFAN. ICLARM Software 2. Manila: International Center for Living Aquatic Resources.Google Scholar
Goodwin, T.W., 1969. Pigments in Echinodermata. In Chemical zoology, vol. III. Echinodermata, Nematoda, and Acanthocephala (ed. M., Florkin and B.T., Scheer), pp. 135147. New York: Academic Press.Google Scholar
Guillou, M. & Michel, C., 1993. Reproduction and growth of Sphaerechinus granularis (Echinodermata: Echinoidea) in southern Brittany. Journal of the Marine Biological Association of the United Kingdom, 73, 179192.CrossRefGoogle Scholar
Hile, R., 1941. Age and growth of the rock bass, Ambloplites rupestris (Rafinesque) in Nebish Lake, Wisconsin. Transactions of Wisconsin Academy of Science, Arts and Letters, 33, 189337.Google Scholar
Hile, R., 1970. Body-scale relation and calculation of growth in fishes. Transactions of the American Fisheries Society, 99, 468474.2.0.CO;2>CrossRefGoogle Scholar
Huet, S., Jolivet, E. & Messéan, A., 1992. La régression non-linéaire: methodes et applications en biologie. Paris: INRA.Google Scholar
Jensen, M., 1969. Age determination of echinoids. Sarsia, 37, 4144.CrossRefGoogle Scholar
Kawamura, K., 1966. On the age determining character and growth of a sea urchin, Strongylocentrotus nudus. Scientific Reports of the Hokkaido Fisheries Experimental Station, 6, 5661.Google Scholar
Koehler, R., 1921. Faune de France. I. Échinodertnes. Paris: Paul Lechevalier.CrossRefGoogle Scholar
Lea, E., 1910. On the methods used in herring-investigations. Publications de Circonstance. Conseil Permanent International pour 1’ Exploration de la Mer. Copenhague, 53, 725.CrossRefGoogle Scholar
Le Cren, E.D., 1947. The determination of the age and growth of perch (Perca fluviatilis) from the opercular bone. Journal of Animal Ecology, 16, 188204.CrossRefGoogle Scholar
Lee, R.M., 1912. An investigation into the methods of growth determination in fishes by means of scales. Publications de Circonstance. Conseil Permanent International pour V Exploration de la Mer. Copenhague, 63, 335.CrossRefGoogle Scholar
Lee, R.M., 1920. A review of the methods of age and growth determination in fishes by means of scales. Fishery Investigations, Series 2. MAFF. London, 4(2), 133.Google Scholar
Longhurst, A.R. & Pauly, D., 1987. Ecology of tropical oceans. San Diego: Academic Press.Google Scholar
Marquardt, D.W., 1963. An algorithm for least-squares estimation of the nonlinear parameters. Journal of the Society for Industrial and Applied Mathematics, 11, 431441.CrossRefGoogle Scholar
Millier, C., 1982. Courbes de reponse. In Modeles dynamiques deterministes en biologie (ed. J.D., Lebreton and C., Millier), pp. 151170. Paris: Masson.Google Scholar
Moore, H.B., 1935. A comparison of the biology of Echinus esculentus in different habitats. Part II. Journal of the Marine Biological Association of the United Kingdom, 20, 109128.CrossRefGoogle Scholar
Nichols, D., Sime, A.A.T. & Bishop, G.M., 1985. Growth in populations of the sea-urchin Echinus esculentus L. (Echinodermata: Echinoidea) from the English Channel, and Firth of Clyde. Journal of Experimental Marine Biology and Ecology, 86, 219228.CrossRefGoogle Scholar
Pauly, D. & David, N., 1981. ELEFAN I, a BASIC program for the objective extraction of growth parameters from length-frequency data. Meeresforschung, 28, 205211.Google Scholar
Pearse, J.S. & Pearse, V.B., 1975. Growth zones in the echinoid skeleton. American Zoologist, 15, 731753.CrossRefGoogle Scholar
Rhoads, D.C. & Lutz, R.A., 1980. Introduction: skeletal records of environmental change. In Skeletal growth of aquatic organisms: biological records of environmental change (ed. D.C., Rhoads and R.A., Lutz), pp. 119. New York: Plenum Press.CrossRefGoogle Scholar
Richards, F.J., 1959. A flexible growth function for empirical use. Journal of Experimental Botany, 10, 290300.CrossRefGoogle Scholar
Ricker, W.E., 1992. Back-calculation of fish lengths based on proportionality between scale and length increments. Canadian Journal of Fisheries and Aquatic Sciences, 49, 10181026.CrossRefGoogle Scholar
Scherrer, B., 1984. Biostatistique. Boucherville, Canada: Gaetan Morin.Google Scholar
Sime, A.A.T., 1982. Growth ring analysis in regular echinoids. Progress in Underwater Science, 7, 714.Google Scholar
Smith, A.B., 1980. Stereom microstructure of the echinoid test. Special Papers of Palaeontology, 25, 181.Google Scholar
Sokal, R.R. & Rohlf, F.J., 1981. Biometry, 2nd ed. San Francisco: W.H. Freeman.Google Scholar
Statistical Graphics Corporation, 1993. Statistical graphics system, reference manual. STATGRAPHICS Version 7. Rockville, USA: Manugistics Inc.Google Scholar
Taki, J., 1972. A tetracycline labelling observation on growth zones in jaw apparatus of Strongylocentrotus intermedius. Bulletin of the Japanese Society of Scientific Fisheries, 38, 181188.CrossRefGoogle Scholar
Tortonese, E., 1965. Fauna d'ltalia, vol. VI. Echinodermata. (ed. Calderine, ). Bologna: Italia.Google Scholar
Whitney, R.R. & Carlander, K.D., 1956. Interpretation of body-scale regression for computing body length of fish. Journal of Wildlife Management, 20, 2127.CrossRefGoogle Scholar