Hostname: page-component-7bb8b95d7b-5mhkq Total loading time: 0 Render date: 2024-09-16T20:39:36.601Z Has data issue: false hasContentIssue false
  • English
  • Français

Spatial analysis and abundance estimation of the southernmost population of purple clam, Amiantis purpurata in Patagonia (Argentina)

Published online by Cambridge University Press:  19 September 2003

Enrique Mario Morsan
Get access Rights & Permissions [Opens in a new window]

Abstract

Spatial distribution of the southernmost population of the purple clam, Amiantis purpurata (Bivalvia: Veneridae), was described from systematic survey data (density and local biomass), and was related to environmental variables (depth and sediment). Geostatistical techniques were used to model and map density, and to estimate absolute biomass.

Spatial distribution was highly contagious: half of the population lives at densities up to 240 clams m−2. Higher clam abundance occur only at sites with finer and well sorted sediment and intermediate depth. Even when the demographic structure of the population was composed of three year-classes recruited between 1978 and 1980, local biomass and density exhibited a non-linear relationship between them, and discrepancies between their distributions of frequency, their relationship with depth, and variographic analysis.

The spherical model was fitted to the experimental variograms. Anisotropy was explored and introduced into the model. The resulting map shows the location and extension of the patches in the study area; they conform a fringe where the highest concentrations are oriented parallel to the coast line, interrupted by small shoals. No anisotropism was evident in the variographic analysis of local biomass. The kriged mean was 3369 g m−2; and estimated total biomass was 53,290 tn.

Such differences between density and local biomass seem to be linked to compensatory processes involving biomass, growth and mortality, originated at the scale of individual overlapping neighbourhoods.

Type
Research Article
Information
Journal of the Marine Biological Association of the United Kingdom , Volume 83 , Issue 5 , October 2003 , pp. 1073 - 1082
Copyright
Copyright © Marine Biological Association of the United Kingdom 2003

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Basford, D.J., Elephteriou, A. & Raffaelli, D., 1989. The epifauna of the northern North Sea (56°-61°N). Journal of the Marine Biological Association of the United Kingdom, 69, 387–407.CrossRefGoogle Scholar
Buestel, D., Dao, J.C. & Gohin, F., 1985. Estimation d'un stock naturel de coquilles Saint-Jacques par une methode combinant les dragages et la plongee. Traitment des resultants par une methode geostatistique. International Councilfor the Exploration of the Sea (CMPapers and Reports), CM 1985/K: 18, 12 pp.Google Scholar
Clark, C.W., 1982. Concentration profiles and the production and managements of marine fisheries. In Economic theory of natural resources (ed W. Eichhorn), pp. 97–112. Germany: PhysicaVerlag, Wu«rzburg-Wien.Google Scholar
Conan, G.Y., 1985. Assessment of shellfish stocks by geostatistical techniques. International Council for the Exploration of the Sea (CM Papers and Reports), CM 1985/K:30, 19 pp.Google Scholar
Cressie, N., 1991. Stastisticsfor spatial data. New York: John Wiley & Sons. Deutsch, C.V. & Journel, A.G., 1992. GSLIB. Geostatistical software library and user's guide. New York: Oxford University Press.Google Scholar
Elliot, J.M., 1977. Some methods for the statistical analysis of samples of benthic invertebrates. Freshwater Biological Association Scientific Publication, no. 25, 149 p.Google Scholar
Folk, R.L. & Ward, W.C., 1957. Brazos river bar: a study in the significance of grain size parameters. Journal of Sedimentary Petrology, 27, 3–26.Google Scholar
Freire, J., Fernandez, L. & Gonzalez Gurriaran, E., 1991. Spatial distribution of decapods crustaceans in the Galician continental shelf (NW Spain) using geostatistical analysis. International Council for the Exploration of the Sea (CM Papers and Reports), CM 1991/K:4, 12 pp.Google Scholar
Gonzalez Gurriaran, E., Freire, J. & Fernandez, L., 1993. Geostatistical analysis of spatial distribution of Liocarcinus depurator, Macropipus tuberculatus and Polybius henslowii (Crustacea: Branchyura) over the Galician continental shelf (NW Spain). Marine Biology, 115, 453–461.Google Scholar
Griffiths, J.C., 1967. Scientific methods in analysis of sediments. New York: McGraw-Hill Book Company.Google Scholar
Hall, M., 1983. A spatial approach of the population dynamics ofmanila clam, Tapes phillipinarum. PhD thesis, University of Washington, USA.Google Scholar
Hilborn, R. & Walters, C., 1992. Quantitative fisheries stock assessment: choice, dynamics and uncertainty. New York: Chapman & Hall.CrossRefGoogle Scholar
Journel, A.G., 1986. Geostatistics: models and tools for the earth sciences. Mathematical Geology, 18, 199–140.Google Scholar
Journel, A.G. & Huilbregts, C.J., 1978. Mining geostatistics. London: Oxford University Press.Google Scholar
Maravelias, C.D., Reid, D.G., Simmonds, E.J. & Haralabous, J., 1996. Spatial analysis and mapping of acoustic survey data in the presence of high local variability: geostatistical application to North Sea herring (Clupea harengus). Canadian Journal of Fisheries and Aquatic Sciences, 53, 1497–1505.Google Scholar
Matheron, G., 1971. The theory of regionalized variables and its applications. Les Cahiers du Centre de Morphologie Mathematique, no. 5. Fontainbleau, France: Ecole Nationale Superieure des Mines de Paris.Google Scholar
Morsan, E.M., 2000. Dinamicapoblacwnaly explotacwnpesquera dela almeja pürpura, Aminatis purpurata Lam. 1856. Tesis doctoral, Universidad Nacional del Sur, Bahia Blanc, Argentina.Google Scholar
Nicolajsen, A. & Conan, G., 1987. Assessment by geostatistical techniques of populations of Iceland scallop (Chalmys islandica) in the Barent Sea. International Council for the Exploration of the Sea (CMPapers and Reports), CM 1987/K: 14, 6 pp.Google Scholar
Orensanz, J.M. & Jamieson, G., 1998. The assessment and management of spatially structured stocks: an overview of the North Pacific Symposium on invertebrate stock assessment and management. In Proceedings of the North Pacific Symposium on invertebrate stock assessment and management (ed. G.S. Jamieson and A. Campbell), pp. 441–459. Canadian Special Publication of Fisheries and Aquatic Sciences, no. 125.Google Scholar
Orensanz, J.M., Parma, A.M. & Iribarne, O.O., 1991. Population dynamics and management of natural stocks. In Scallops: biology, ecology and aquaculture (ed. S. Shumway), pp. 625–713. Amsterdam: Elsevier.Google Scholar
Pelletier, D. & Parma, A.M., 1994. Spatial distribution of Pacific Halibut (Hippoglossus stenolepis). An application of geostatistics to longline survey data. Canadian Journal of Fisheries and Aquatic Sciences, 51, 1506–1518.Google Scholar
Petitgas, P., 1993. Geostatistics for fish stock assessment: a review and an acoustic application. ICES Journal of Marine Science, 50, 285–298.CrossRefGoogle Scholar
Petitgas, P. & Prampart, A., 1993. EVA (EstimationVAriance): a geostatistical software on IBM-PC for structure characteriza-tion and variance computation. International Council for the Exploration of the Sea (CM Papers and Reports), CM 1993/D: 65, 32 pp.Google Scholar
Rossi, R.E., Mulla, D., Journel, A.G. & Franz, E.H., 1992. Geostatistical tools for modeling and interpreting ecological spatial dependence. Ecological Monographs, 62, 277–314.Google Scholar
Sauriau, P.G. & Bacher C., 1991. Cartographie krigee des mollus-ques suspensivores competiteurs trophiques des huîtres du bassin de Marennes-Oleron: implications pour la planification de l'enchantillonnage. Journal de Recherche Oceanographie, 16, 1–4.Google Scholar
Thrush, S., 1991. Spatial pattern in soft bottom communities. Trends in Ecology and Evolution, 6, 75–79.Google Scholar
Warren, W.G., 1998. Spatial analysis for marine populations: factors to be considered. In Proceedings of the North Pacific Symposium on invertebrate stock assessment and management (ed. G.S. Jamieson and A. Campbell), pp. 21–28. Canadian Special Publication of Fisheries and Aquatic Sciences, no. 125.Google Scholar
Williamson, N.J. & Traynor, J.J., 1996. Application of a one-dimensional geostatistical procedure to fisheries acoustic surveys of Alaskan pollock. ICES Journal of Marine Science, 53, 423–428.Google Scholar