The pelagic thresher shark, Alopias pelagicus, like most large sharks produces a low number of offspring (two embryos per litter). However, there is no accurate information on its population status. To improve the accuracy of population simulations, a stochastic stage-based birth-flow model was constructed to assess the stock status of the pelagic thresher in the north-western Pacific. Based on the best biological information available, its life history was represented as four stages: neonates, juveniles, subadults, and adults. Results indicated that, without mortality from fishing, the stock would clearly increase (mean annual population growth rate (?) = 1.058 year–1, 95% CI = 1.014–1.102 year–1). When current fishing mortality was taken into account, a decrease in population was indicated (? = 0.979 year–1, 95% CI = 0.921–1.030 year–1) with a projected reduction of 34.3% over 20 years. These results suggest that the stock is overexploited. Simulations using various management measures showed that the population will remain steady under these protection options. However, this species is extremely vulnerable to overexploitation and is especially sensitive at the juvenile and adult stages, implying that nursery closures or size limit management measures are urgently needed to ensure the sustainable utilisation of the stock.

The Yellowfin Tuna Thunnus albacares is one of the major fish species caught around subsurface fish aggregation devices (FADs) in the waters southwest of Taiwan. However, how it interacts with other organisms around FADs is poorly known. In this study, the diet and feeding habits of juvenile Yellowfin Tuna were estimated from the analysis of stomach contents from 1,477 specimens with FLs ranging from 24 to 108 cm and stable isotope analysis (202 specimens) collected around FADs in the waters southwest of Taiwan. The analysis of stomach contents indicated that juvenile Yellowfin Tuna with FL < 50 cm mainly feed on larval purpleback flying squid Sthenoteuthis oualaniensis, larval shrimps, and zooplanktonic organisms such as amphipods. Yellowfin Tuna with FL of ∼50 cm switch their diet to teleost fishes such as Japanese Barracudina Lestrolepis japonica, Skinnycheek Lanternfish Benthosema pterotum, and fishes in the families Exocoetidae and Scombridae. Stable isotope analysis indicated that the δ¹⁵N values ranged between 6.2‰ and 12.6‰, and the estimated trophic position varied from 3.18 ± 0.24 for tuna with FL < 30 cm, while it reached 4.59 ± 0.50 for those with FL > 50 cm and 4.75 ± 0.06 for those with FL > 90 cm. Based on the distinct diet shift of the juvenile Yellowfin Tuna, demonstrated by both stomach contents and stable isotope analyses, this study concluded that the tuna shift their diet at approximately 50 cm FL. Received March 31, 2015; accepted September 9, 2015

The vital parameter data for 62 stocks, covering 38 species, collected from the literature, including parameters of age, growth, and reproduction, were log-transformed and analyzed using multivariate analyses. Three groups were identified and empirical equations were developed for each to describe the relationships between the predicted finite rates of population increase (λ’) and the vital parameters, maximum age (T_max), age at maturity (T_m), annual fecundity (f/R_c)), size at birth (L_b), size at maturity (L_m), and asymptotic length (L_∞). Group (1) included species with slow growth rates (0.034 yr^-1 < k < 0.103 yr^-1) and extended longevity (26 yr < T_max < 81 yr), e.g., shortfin mako Isurus oxyrinchus, dusky shark Carcharhinus obscurus, etc.; Group (2) included species with fast growth rates (0.103 yr^-1 < k < 0.358 yr^-1) and short longevity (9 yr < T_max < 26 yr), e.g., starspotted smoothhound Mustelus manazo, gray smoothhound M. californicus, etc.; Group (3) included late maturing species (L_m/L_∞ ≧ 0.75) with moderate longevity (T_max < 29 yr), e.g., pelagic thresher Alopias pelagicus, sevengill shark Notorynchus cepedianus. The empirical equation for all data pooled was also developed. The λ’ values estimated by these empirical equations showed good agreement with those calculated using conventional demographic analysis. The predictability was further validated by an independent data set of three species. The empirical equations developed in this study not only reduce the uncertainties in estimation but also account for the difference in life history among groups. This method therefore provides an efficient and effective approach to the implementation of precautionary shark management measures.

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_cdifference, the AIC_cweight, 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_ror 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.

An increase in yellowfin tuna (Thunnus albacares) catch by danish seine fisheries around the subsurface fish aggregating devices (FADs) in southern Taiwan waters has been a concern of local government and environmental groups. However, the attraction mechanism of aggregating tunas at the subsurface FADs is still poorly understood. The objective of this study is to examine the fine‐scale vertical and horizontal movements of juvenile yellowfin tunas around a subsurface FAD. In total, 53 tunas (35–81 cm fork length) were tagged with ultrasonic telemetry tags and released at a subsurface FAD in the waters off Shiao‐Liu‐Chiu Island, southwestern Taiwan from October 2008 to December 2009. These tunas stayed at the subsurface FAD for up to 31 days, with daytime vertical movement depths averaging 60–80 m at a maximum depth of 250 m. At night, the tuna gathered at a shallow depth of 40 m. The mean depth of vertical movement in the daytime is significantly different from that of the nighttime (P < 0.05). The maximum detectable distance of horizontal movement was 1.6 km, with 80% of the long horizontal movements occurring in the daytime. It is likely that the purpose of these vertical and horizontal movements was for feeding or avoiding predators. Moreover, the tagged tunas did not depart from the subsurface FAD simultaneously, suggesting distinct behaviors in their movements.