Frontiers in Marine Science (Feb 2021)

Multi-Model Approach on Growth Estimation and Association With Life History Trait for Elasmobranchs

  • Kwang-Ming Liu,
  • Kwang-Ming Liu,
  • Kwang-Ming Liu,
  • Chiao-Bin Wu,
  • Shoou-Jeng Joung,
  • Shoou-Jeng Joung,
  • Wen-Pei Tsai,
  • Kuan-Yu Su,
  • Kuan-Yu Su

DOI
https://doi.org/10.3389/fmars.2021.591692
Journal volume & issue
Vol. 8

Abstract

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Age and growth information is essential for stock assessment of fish, and growth model selection may influence the accuracy of stock assessment and subsequent fishery management decision making. Previous descriptions of the age and growth of elasmobranchs relied mainly on the von Bertalanffy growth model (VBGM). However, it has been noted that sharks, skates and rays exhibit significant variety in size, shape, and life history traits. Given this variation, the VBGM may not necessarily provide the best fit for all elasmobranchs. This study attempts to improve the growth estimates by using multi-model approach to test four growth models—the VBGM, the two-parameter VBGM, the Robertson (Logistic) and the Gompertz models to fit observed or simulated length-at-age data for 38 species (44 cases) of elasmobranchs. The best-fit growth model was selected based on the bias corrected Akaike’s Information Criterion (AICc), the AICc difference, the AICc weight, the Bayesian Information Criterion (BIC), and the Leave-one-out cross-validation (LOOCV). The VBGM and two-parameter VBGM provide the best fit for species with slow growth and extended longevity (L∞ > 100 cm TL, 0.02 < k < 0.25 yr–1), such as pelagic sharks. For fast-growing small sharks (L∞ < 100 cm TL, kr or kg > 0.2 yr–1) in deep waters and for small-sized demersal skates/rays, the Robertson and the Gompertz models provide the best fit. The best-fit growth models for small sharks in shallow waters are the two-parameter VBGM and the Robertson model. Although it was found that the best-fit growth models for elasmobranchs were associated with their life history trait, exceptions were also noted. Therefore, a multi-model approach incorporating with the best-fit model selected for each group in this study was recommended in growth estimation for elasmobranchs.

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