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 (AIC_c), the AIC_c difference, the AIC_c 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, k_r or k_g > 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.

年龄和生长信息对于鱼类种群评估至关重要，生长模型的选择可能会影响种群评估和后续渔业管理决策的准确性。以前关于弹性支的年龄和生长的描述主要依靠冯·贝塔兰菲增长模型（VBGM）。然而，已经注意到，鲨鱼，溜冰鞋和rays鱼在大小，形状和生活史特征方面表现出显着变化。鉴于这种变化，VBGM不一定会为所有的弹性分支提供最佳的拟合。本研究试图通过使用多模型方法来测试四个增长模型（VBGM，两参数VBGM，Robertson（Logistic）和Gompertz模型）来改善增长估计，以适合观察或模拟的年龄长度数据。弹性分支38种（44例）。_c），AIC _c差，AIC _c权重，贝叶斯信息准则（BIC）和留一法交叉验证（LOOCV）。VBGM和两参数VBGM最适合生长缓慢和寿命延长（_L∞ > 100 cm TL，0.02 <k <0.25 yr ^–1）的物种，例如远洋鲨。对于快速生长的小鲨鱼（_L∞ <100 cm TL，k _r或k _g > 0.2 yr ^–1）在深水区和小型深潜式溜冰鞋/射线中，Robertson和Gompertz型号最适合。浅水区小鲨鱼最适合的生长模型是两参数VBGM和Robertson模型。尽管发现弹性支的最合适生长模型与它们的生活史特征有关，但也有例外。因此，在本研究中，建议将多模型方法与本研究中为每个组选择的最佳拟合模型相结合，以估计弹力支。