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Modelling the growth of crustacean species

  • Yi Jay Chang
  • , Chi Lu Sun
  • , Yong Chen
  • , Su Zan Yeh
  • National Taiwan University

Research output: Contribution to journalReview articlepeer-review

100 Scopus citations

Abstract

Crustaceans play an important role in marine ecosystem and worldwide fisheries. Accurate and quantitative description of growth is crucial in modelling the demographics and fisheries stock assessment. The stepwise growth as a result of the moulting process and the lack of permanent calcified structures make the traditional approaches developed for finfish inappropriate for crustaceans. This study reviews the data collection, quantitative methods and various sources of uncertainty for modelling the growth of crustacean. The methods were reviewed based on their data requirement and mathematical/statistical complexity ranging from simple growth rate, continuous growth curve to stepwise growth curve and size transition matrix. A comparative example of different growth models was illustrated with four selected crustaceans: American lobster (Homarus americanus, Nephropidae), Dungeness crab (Metacarcinus magister, Cancridae), blue crab (Callinectes sapidus, Portunidae) and pronghorn spiny lobster (Panulirus penicillatus, Palinuridae). Model selection and multi-model inference based on the information theory was discussed for modelling the growth components of moutling increment and intermoult period. Various drivers in determination of the growth pattern of crustaceans were evaluated, including life history strategy and environmental stress. The incorporation of environmental factors into the development of growth models and the recent progress in age-determination were highlighted. We discussed possible research needs for better quantification of crustaceans growth.

Original languageEnglish
Pages (from-to)157-187
Number of pages31
JournalReviews in Fish Biology and Fisheries
Volume22
Issue number1
DOIs
StatePublished - Mar 2012

Keywords

  • Age and growth
  • Crustaceans
  • Environmental factor
  • Growth model
  • Moult
  • Uncertainty

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