A novel statistical method for validating the periodicity of vertebral growth band formation in elasmobranch fishes

Abstract

A simple age verification method is presented for centrum edge analysis (CEA) of elasmobranch species. In this method, a binomial model is linked with a von Mises distribution for circular data, taking the characteristics of the CEA data into account. The periodicity of growth band pairs is categorized as no cycle, an annual cycle, or a biannual cycle. Three models are then constructed according to different periodicities. We use the Akaike information criterion (AIC) to determine which model is the best. The models were applied to the shortfin mako shark ( Isurus oxyrinchus ) data collected in the North Pacific to identify the best periodicity model. The AIC best-fitting model was one involving an annual cycle. The general performance of the method was evaluated using simulated data of various sample sizes, formation times, and durations of growth band pairs. The simulation trials showed that the performance of the method was satisfactory with moderate sample sizes. This method should improve the accuracy of age determination and could be applied to all species that have periodic growth band pairs.

Age, growth and genetic status of the white shark (Carcharodon carcharias) from Kashima-nada, Japan

“…The periodicity of growth band formation is essential information in age determinations . Recently, Okamura and Semba (2009) reported a statistical method for validating the periodicity in elasmobranchs. However, like in the MIR method, monthly samples are needed.…”

Improving age, growth, and maturity estimates for aseasonally reproducing chondrichthyans

“…The seasonal distribution of RMI values was typical of many tropical Carcharhiniformes (Piercy et al, 2007;Romine et al, 2006;Santana and Lessa, 2004) lacking the distinctive pattern more frequently seen in temperate species (Goldman and Musick, 2006). Okamura and Semba (2009) demonstrated to what extent variation in timing and duration of band formation can obscure patterns in verification. These factors probably contributed to the slightly ambiguous pattern observed in RMI values in this study.…”

Selection of Models to PredictPanopea globosaGrowth: Application of a Mixture Probability Distribution Function

“…Nonetheless, age validation defined as the determination of growth band periodicity deposition is problematic, and solutions have been difficult (Kilada et al 2007). Methods reported for age validation typically use the marginal increment ratio (Campana 2001) or the dendrochronology approach (Calderon-Aguilera et al 2010, Cortez-Lucero et al 2011); however, both techniques have been criticized because the methodologies do not have robust statistical analyses, and cannot identify annual or biannual cycles quantitatively (Okamura & Semba 2009, Okamura et al 2013.…”