Multi-Model Approach on Growth Estimation and Association With Life History Trait for Elasmobranchs
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...
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doaj-4836c72063004958bef174f8940325ee2021-02-23T05:57:29ZengFrontiers Media S.A.Frontiers in Marine Science2296-77452021-02-01810.3389/fmars.2021.591692591692Multi-Model Approach on Growth Estimation and Association With Life History Trait for ElasmobranchsKwang-Ming Liu0Kwang-Ming Liu1Kwang-Ming Liu2Chiao-Bin Wu3Shoou-Jeng Joung4Shoou-Jeng Joung5Wen-Pei Tsai6Kuan-Yu Su7Kuan-Yu Su8Institute of Marine Affairs and Resource Management, National Taiwan Ocean University, Keelung, TaiwanGeorge Chen Shark Research Center, National Taiwan Ocean University, Keelung, TaiwanCenter of Excellence for the Oceans, National Taiwan Ocean University, Keelung, TaiwanInstitute of Marine Affairs and Resource Management, National Taiwan Ocean University, Keelung, TaiwanGeorge Chen Shark Research Center, National Taiwan Ocean University, Keelung, TaiwanDepartment of Environmental Biology and Fisheries Science, National Taiwan Ocean University, Keelung, TaiwanDepartment of Fishery Production and Management, National Kaohsiung University of Science and Technology, Kaohsiung, TaiwanInstitute of Marine Affairs and Resource Management, National Taiwan Ocean University, Keelung, TaiwanGeorge Chen Shark Research Center, National Taiwan Ocean University, Keelung, TaiwanAge 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.https://www.frontiersin.org/articles/10.3389/fmars.2021.591692/fullsharksskates and raysvon Bertalanffy growth modelRobertson growth modelGompertz growth model |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
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 |
spellingShingle |
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 Multi-Model Approach on Growth Estimation and Association With Life History Trait for Elasmobranchs Frontiers in Marine Science sharks skates and rays von Bertalanffy growth model Robertson growth model Gompertz growth model |
author_facet |
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 |
author_sort |
Kwang-Ming Liu |
title |
Multi-Model Approach on Growth Estimation and Association With Life History Trait for Elasmobranchs |
title_short |
Multi-Model Approach on Growth Estimation and Association With Life History Trait for Elasmobranchs |
title_full |
Multi-Model Approach on Growth Estimation and Association With Life History Trait for Elasmobranchs |
title_fullStr |
Multi-Model Approach on Growth Estimation and Association With Life History Trait for Elasmobranchs |
title_full_unstemmed |
Multi-Model Approach on Growth Estimation and Association With Life History Trait for Elasmobranchs |
title_sort |
multi-model approach on growth estimation and association with life history trait for elasmobranchs |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Marine Science |
issn |
2296-7745 |
publishDate |
2021-02-01 |
description |
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. |
topic |
sharks skates and rays von Bertalanffy growth model Robertson growth model Gompertz growth model |
url |
https://www.frontiersin.org/articles/10.3389/fmars.2021.591692/full |
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