Optimal choice of species and size class for transplanting coral community

Soyoka Muko, Yoh Iwasa

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

Transplantation of sessile organisms living in a planned destruction site to a safe site is an important means of restoration to mitigate biodiversity loss following anthropogenic developments. In particular, corals, which play fundamental roles in the coral reef ecosystem and contribute to biodiversity, are good candidates for transplantation. In this study, we investigate the optimal choice of species and size class to be used for coral transplantation. We first studied a case in which the objective function to evaluate the success of transplantation is the maximum total coverage. The optimal strategy is to choose the species and size class with higher net coverage gain per unit handling effort. It is often recommended to transplant only one or a few species and neglect others, even if the original community consists of many species. This may achieve high coverage in the restored coral community but cause loss of species diversity. To overcome this problem, we next study a case in which the objective of the transplantation operation is to maximize the "prosperity index", defined as the product of total coverage and species diversity. In this case, the optimal strategy depends on the species property, population size, and the limitation of total cost allowed for transplantation, but it tends to recommend more species to be transplanted than what is recommended by the coverage maximization criterion. We conclude that maximization of the prosperity index is a better criterion for transplantation than simple coverage maximization.

Original languageEnglish
Pages (from-to)130-137
Number of pages8
JournalJournal of Theoretical Biology
Volume273
Issue number1
DOIs
Publication statusPublished - Mar 21 2011

All Science Journal Classification (ASJC) codes

  • Medicine(all)
  • Immunology and Microbiology(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • Modelling and Simulation
  • Statistics and Probability
  • Applied Mathematics

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