Meta-analysis (inverse-variance, random-effects model) involving 46 studies was used to estimate the effect size of postrelease mortality (Fr) in six istiophorid billfish species (black marlin (Istiompax indica), blue marlin (Makaira nigricans), longbill spearfish (Tetrapturus pfluegeri), sailfish (Istiophorus platypterus), striped marlin (Kajikia audax), and white marlin (Kajikia albida)) following release from recreational, longline, and harpoon fishing gears. The studies involved 400 reporting pop-up satellite archival tags and 64 reporting acoustic (ultrasonic) tags. Despite fish being captured, tagged, and released under widely disparate conditions, locations, and gear types, Fr was homogeneous among species. Variability in Fr was principally due to random sampling error within studies with no evident patterns. Fifteen studies (33% of tags) indicated no mortality, and the overall summary effect size for Fr was 13.5% (95% CI: 10.3%–17.6%). Since the random-effects model decomposed to a fixed-effect model when the between-studies variance T2 = 0.00, results were confirmed using exact nonparametric inferential tests and sensitivity analyses. Our results support earlier findings in the Atlantic and substantiate the majority of istiophorid billfish survive when released from recreational and longline fishing gear, clearly implying catch-and-release as a viable management option that permits fishing activity while protecting parental biomass and the fishery.

Carvalho, F. C., Murie, D. J., Hazin, F. H. V., Hazin, H. G., Leite-Mourato, B., and Burgess, G. H. 2011. Spatial predictions of blue shark (Prionace glauca) catch rate and catch probability of juveniles in the Southwest Atlantic. – ICES Journal of Marine Science, 68: 890–900. Generalized regression analysis and spatial prediction was applied to catch per unit effort (cpue) data for blue shark (Prionace glauca) caught by the Brazilian tuna longline fleet between 1997 and 2008 (43 546 longline sets) to predict the effect of environmental, spatial, and temporal factors on catch distribution. In addition, the size distribution of blue sharks measured by on-board observers during the years 2006–2008 was used to model the proportion of juvenile blue sharks in the catches from a spatial perspective. Latitude was the most important factor influencing blue shark cpue in the Southwest Atlantic, with cpue spatial predictions suggesting two areas of higher catch probabilities. Latitude was also the most important factor influencing the proportion of juveniles in the catches. The spatial prediction map showed that juveniles were more frequently caught south of 35°S (∼38°S). This information can assist in the design of management strategies either to exploit this predictable spatial distribution of the catch or to manage the fisheries in a spatially explicit manner if one component (i.e. juveniles) requires protective measures.

-Distribution and relative abundance of blue sharks (Prionace glauca) in the southwestern Atlantic Ocean was modeled based on catch-per-unit-effort (CPUE) per 1000 hooks and length frequencies of blue sharks caught by the Brazilian pelagic tuna longline fleet. As a measure of relative abundance, CPUE of blue sharks caught in 58 238 fishing sets by the Brazilian pelagic tuna longline fleet (national and chartered), from 1978 to 2009, was standardized by a Generalized Linear Model (GLM) using three different approaches: i) a negative binomial error structure (log link); ii) the traditional delta lognormal model; and iii) the Tweedie distribution, recently proposed to adjust models with a high proportion of zeros. A cluster analysis using the K-means method was used to identify target species and incorporate it as a factor into the GLM. Cluster analysis grouped the data into six different fishing clusters according to the percentage of target species. Target factor (cluster) was the most important factor explaining the variance in all three CPUE models. The Tweedie model showed a relatively better fit compared to the other models. Blue shark nominal and standardized CPUE showed a relatively stable trend from 1978 to 1995. From 1995 onwards, however, there was an increasing trend in the standardized CPUE, up to a maximum value in 2008. In general, nominal CPUE and standardized CPUE tracked well up until 2000, after which standardized CPUE's values were at a noticeably lower level than nominal CPUE. Length frequency data were analyzed for 11 932 blue sharks measured as part of the Brazilian onboard observer program operating on the pelagic tuna longline fleet between 2006 and 2008, with sizes ranging from 91 to 224 cm fork length. Overall, blue shark size data showed clear spatial and seasonal distributions for males and females in the southwestern Atlantic Ocean, with juveniles predominantly concentrated in the most southerly latitudes.