Blue shark conservation in the Indian Ocean: data-limited insights on population structure, distribution, and stock assessments

Abstract

Despite advances in ocean science, potential uncertainty continues to surround the stock dynamics of the blue shark (Prionace glauca) in the Indian Ocean. Fork-length (FL) data from 31,404 sharks, collected by observers between 2006 and 2022, were analyzed in this study. Population structure analysis revealed spatial, seasonal, and size variability, with FL declining more in females (-2.90 cm/year) than in males (-2.44 cm/year). Small juveniles concentrated in temperate waters (30 degrees S-40 degrees S) in summer/autumn, while juveniles had a broader range (10 degrees N-40 degrees S). Adults ranged widely (10 degrees N-40 degrees S) with higher densities in southern areas (30 degrees S-40 degrees S) in spring/summer. Males dominated the population (55 %), with spatial and seasonal sex ratio shifts, and the proportion of females increasing with size in most seasons. Several analytical approaches, including length-based mortality estimators (MLZ), and spawning potential ratio (SPR), were applied alongside empirical length-based indicators (LBIs) as auxiliary. A stochastic framework with bootstrap statistics was developed, to compare prior research with revisited growth parameters using ELEFAN_GA_Boot. Empirical surveillance LBIs revealed increases in male abundance in 2018 and 2022, and in female abundance in 2017 and 2022. SPR estimates were 50 % in one scenario and 37 % in another, suggesting ongoing overfishing to the reference range (SPR 30 %-60 %). Current exploitation rates are near the sustainability threshold of 0.5 year-1 , indicating fishing levels are likely sustainable but close to the threshold level. Findings indicate blue sharks are not overfished but require adaptive sex-specific management to mitigate overfishing risks. Collaboration among researchers, managers, and fleets is vital for sustainable practices. Continuous monitoring and adaptive management are essential for long-term sustainability, and size-based methods provide valuable insights for data-limited stocks.