Skip to main content

‘Hard’ data for matrix modelling of Laminaria digitata (Laminariales, Phaeophyta) populations

Abstract

The objective of the study was to produce a size-based matrix model of a Laminaria digitata (L.) Lamour. population. ‘Hard’ data for insertion in the matrix were collected in a 9 year cohort analysis of size and age specific survival and fertility for a stand in south west Nova Scotia, Canada. The product of the square matrix containing these values and a column vector containing the densities of size classes was used to project the size class structure one year later. The projected estimates were found to fit empirical estimates with some confidence. In contrast, an age-based fertility life table wrongly predicted a population declining in density by 45% per year. The study supports, in theory, the use of size-based matrix models for management of harvested stands. In reality, the amount of work required to obtain ‘hard’ data and the site specific nature of the projections may preclude the use of such an approach to broad scale management.

This is a preview of subscription content, access via your institution.

References

  • Åberg, P., 1990. Population ecology of Ascophyllum nodosum: Demography and reproductive effort in stochastic environments. Ph. D. Dissertation, University of Göteborg. pag. var.

  • Ang, P., 1987. Use of projection matrix models in the assessment of harvesting strategies for Sargassum. Hydrobiologia 151/152: 335–339.

    Google Scholar 

  • Ang, P. O. 1991. Natural dynamics of a Fucus distichus (Phaeophyceae, Fucales) population: reproduction and recruitment. Mar. Ecol. Prog. Ser. 78: 71–85.

    Google Scholar 

  • Ang, P. O. & R. E. De Wreede, 1990. Matrix models for algal life history stages. Mar. Ecol. Prog. Ser. 59: 171–181.

    Google Scholar 

  • Ang, P., R. E. De Wreede, F. Shaughnessy & L. Dyck, 1990. A simulation model for an Iridaea splendens (Gigartinales, Rhodophyta) in Vancouver, Canada. Proc. int. Seaweed Symp. 13: 191–196.

    Google Scholar 

  • Caswell, H., 1989. Matrix Population Models: Construction, Analysis and Interpretation. Sinauer, Sunderland, 328 pp.

    Google Scholar 

  • Chapman, A. R. O., 1984. Reproduction, recruitment and mortality in two species of Laminaria in southwest Nova Scotia. J. exp. mar. Biol. Ecol. 78: 99–109.

    Google Scholar 

  • Chapman, A. R. O. 1986. Age versus size: an analysis of age- and size-specific mortality and reproduction in a population of Laminaria longicruris Pyl. J. exp. mar. Biol. Ecol. 97: 113–122.

    Google Scholar 

  • Ford, H., F. G. Hardy & R. G. J. Edyvean, 1983. Population biology of the crustose red alga Lithophyllum incrustans Phil.: Three populations on the east coast of Britain. Biol. J. linn. Soc. 19: 211–220.

    Google Scholar 

  • Gunnarsson, K., 1991. Populations de Laminaria hyperborea et Laminaria digitata (Phéophycées) dans la Baie de Breidifjördur, Islande. Rit Fiskideildar 12: 1–148.

    Google Scholar 

  • Pérez, R. 1970. Longévité du sporophyte de Laminaria digitata (L.) Lamouroux. Revue Trav. Inst. Marit. 34: 363–374.

    Google Scholar 

  • Printz, H., 1926. Die Algenvegetationen des Tronhjemsfjordes. Skr. Norske Vidensk. Akad. Mat. — Nat. Kl. 5: 1–273.

    Google Scholar 

  • Southwood, T. R. E., 1978. Ecological Methods. Chapman & Hall, New York, 524 pp.

    Google Scholar 

  • Werner, P. A. & H. Caswell, 1977. Population growth rates and age versus size-distribution models for teasel (Dipsacus sylvestris Huds.). Ecology 58: 1103–1111.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Chapman, A.R.O. ‘Hard’ data for matrix modelling of Laminaria digitata (Laminariales, Phaeophyta) populations. Hydrobiologia 260, 263–267 (1993). https://doi.org/10.1007/BF00049027

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF00049027

Key words

  • Laminaria digitata
  • matrix modelling
  • demography
  • population biology