MEPS 657:191-207 (2021)  -  DOI: https://doi.org/10.3354/meps13544

ABSTRACT: Knowledge of sea turtle demographic rates is central to modeling their population dynamics, but few studies have quantitatively synthesized existing data globally. Here, we used a Bayesian hierarchical model to conduct a meta-analysis of published von Bertalanffy growth curve parameters (growth coefficient, K; asymptotic length, L_∞) for chelonid sea turtles. We identified 34 studies for 5 of 6 extant chelonids that met minimum selection criteria. We implemented a suite of models that included a multivariate normal likelihood on the log-transformed values of the 2 parameters to evaluate the influence of species, population (regional management unit, RMU), parameter estimation method (mark-recapture, skeletochronology, length-frequency analysis), latitude, and sampled body size range (all sizes, no large, no small, no large or small) on growth parameter estimates. According to information criteria, the best model included a random effect of species. The second best model also included latitude as a fixed effect, but RMU, parameter estimation method, latitude, and sampled body size ultimately did not strongly influence the means or variances of K and L_∞ among studies. The apparent lack of RMU effect on parameter estimates within species may be an artifact of the small number of RMUs with published growth parameter estimates. The species-specific, and in some cases RMU-specific, posterior means and standard deviations of K and L_∞ from this study would be appropriate priors for future studies of growth in chelonid sea turtles or for models of population dynamics. We highlight the need for expanded study and synthesis of sea turtle somatic growth rates.

KEY WORDS: Bayesian hierarchical model · von Bertalanffy growth · Meta-analysis · Chelonia mydas · Caretta caretta · Lepidochelys kempii · Eretmochelys imbricata · Lepidochelys olivacea

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Cite this article as: Ramirez MD, Popovska T, Babcock EA (2021) Global synthesis of sea turtle von Bertalanffy growth parameters through Bayesian hierarchical modeling. Mar Ecol Prog Ser 657:191-207. https://doi.org/10.3354/meps13544 Export citation Share:    Facebook - - linkedIn