Abstract
Growth in fishes is usually modelled by a function encapsulating a common growth mechanism across ages. However, several theoretical works suggest growth may comprise two distinct mechanistic phases arising from changes in reproductive investment, diet, or habitat. These models are termed two-state or biphasic, where acceleration in growth typically changes around some transition age. Such biphasic models have already been successfully applied in elasmobranch species, where such transitions are detectable from length-at-age data alone, but where estimation has assumed normally distributed errors, which is inappropriate for such slow-growing and long-lived fishes. Using recent advances in growth parameter estimation, we implement a biphasic growth model with asymmetric and heavy-tailed errors. We use data from six datasets, encompassing four species of elasmobranchs, to compare the performance of the von Bertalanffy and biphasic models under normal, skew-normal, and Student-t error distributions. Conditional expectation maximization estimation proves both effective and efficient in this context. Most datasets analysed here supported asymmetric and heavy-tailed errors and biphasic growth, producing parameter estimates different from previous studies.
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Acknowledgements
The authors thank the advisory editor and two anonymous referees for their helpful comments and suggestions which greatly improved and early version of this manuscript.
Funding
J.E. Contreras-Reyes’ research was fully supported by FONDECYT (Chile) grant No. 11190116. R. Wiff was funded by CAPES Project Conicyt FB 0002 (2014) and by ANID - Programa Iniciativa Científica Milenio - Código ICN2019_015.
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The authors have adhered to general guidelines for ethical use of animals in research and to the legal requirements and any other institutional guidelines promulgated in Chile. In addition, we would like to thank the authors who facilitated their information (Section 2.1) to us to conduct the analyses.
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Contreras-Reyes, J.E., Wiff, R., Soto, J. et al. Biphasic growth modelling in elasmobranchs based on asymmetric and heavy-tailed errors. Environ Biol Fish 104, 615–628 (2021). https://doi.org/10.1007/s10641-021-01100-z
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DOI: https://doi.org/10.1007/s10641-021-01100-z