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Growth of tropical Dasyatid rays estimated using a multi-analytical approach. | LitMetric

Growth of tropical Dasyatid rays estimated using a multi-analytical approach.

PLoS One

Australian Institute of Marine Science, Crawley, Western Australia, Commonwealth of Australia ; School of Veterinary and Life sciences, Murdoch University, Perth, Western Australia, Commonwealth of Australia.

Published: August 2014

AI Article Synopsis

  • Researchers studied the age and growth of four types of stingrays at Ningaloo Reef, with sample sizes ranging from 19 to 40 individuals for each species.
  • Age estimates from vertebrae band counts were between 1 and 27 years across all species.
  • The study combined several methods to determine growth parameters, finding that the two-parameter von Bertalanffy growth model best fit the data, allowing for the estimation of median sizes and growth rates for each stingray species.

Article Abstract

We studied the age and growth of four sympatric stingrays: reticulate whipray, Himanutra uarnak (n=19); blue mask, Neotrygon kuhlii (n=34); cowtail, Pastinachus atrus (n=32) and blue-spotted fantail, Taeniura lymma (n=40) rays at Ningaloo Reef, a fringing coral reef on the north-western coast of western Australia. Age estimates derived from band counts within sectioned vertebrae ranged between 1 and 27 years (H. uarnak, 1 - 25 yrs.; N. kuhlii, 1.5 - 13 yrs.; P. atrus, 1 - 27 yrs. and T. lymma, 1 -11 yrs.). Due to limitations of sample sizes, we combined several analytical methods for estimating growth parameters. First, we used nonlinear least squares (NLS) to identify the growth model that best fitted the data. We then used this model, prior information and the data within a Bayesian framework to approximate the posterior distribution of the growth parameters. For all species the two-parameter von Bertalanffy growth model provided the best fit to size-at-age datasets. Based on this model, the Bayesian approach allowed the estimation of median values of W(D∞) (cm) and k (yr(-1)) for the four species (H. uarnak: 149 and 0.12; N. kuhlii: 42 and 0.38; P. atrus 156 and 0.16, and T. lymma 33 and 0.24, respectively). Our approach highlights the value of combining different analytical methods and prior knowledge for estimating growth parameters when data quality and quantity are limited.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3795619PMC
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0077194PLOS

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