Interactions and space-use overlap between satellite- tracked blue sharks and longline fishing vessels NUNO QUEIROZ, NICK E. HUMPHRIES, GONZALO MUCIENTES, LARA L. SOUSA & DAVID W. SIMS CIBIO – UNIVERSITY OF PORTO | MARINE BIOLOGICAL ASSOCIATION OF THE UK | IMM – CSIC
Background Pelagic longlines are probably the most widespread fishing gear in the world’s oceans; Longlines are known to interact with several marine predators, being linked with declines in targeted and bycatch species, including seabirds, turtles, tunas and sharks; The blue shark is the most commonly caught shark in longlines targeting swordfish and tuna species, with an estimated 10.7 million sharks killed as bycatch each year.
Novel approach to assess bycatch mortality Blue sharks exhibit an extensive distribution and migratory movements which hint at the possibility that sharks are vulnerable to longline gear throughout a large part of their lives; Understand where and when interactions between sharks and longliners happen; Mapping regions higher bycatch/higher mortality could lead to the implementation of fishing restrictions.
Methodology – boat tracking Vessel monitoring system (VMS) data from Spanish and Portuguese longliners greater than 15 m operating in the north-east Atlantic were obtained; Boat GPS positions spanned from January 2006 to December 2008 and movements between fishing locations were ignored, retaining only data relative to fishing activity; To quantify the shared space use between longliners and tracked sharks over time, the number of days with shared occupancy (i.e. presence of both boats and sharks in a grid cell) was recorded.
Results – fishing fleet Data belonging to a total of 103 longliners targeting large pelagics were analysed; longlines were deployed over a large area for a cumulative number of 17,853 days.
Results – fishing fleet Highly unbalanced fishing effort concentrated in three main regions: southwest of Ireland, west of the Iberian Peninsula and southwest of the Canary Islands.
Results – shark/boat interactions Of the 17 blue sharks successfully tracked five (29.4%) spent at least 1 day-at-risk from longliners; One shark (#6 – tracked for 13 days) reached a maximum of 3 days-at-risk; The percentage of time-at-risk ranged from 0.9% (#17) to 23.1% (#6) of tracking time; 2 sharks (#7 and 10) were captured by surface longliners in the single day fish were at-risk; Overall, confirmed fishing mortality was around ~9.4%, with 3 sharks being caught by longliners during the relatively short tracking period (< 120 d).
Conclusions Swordfish are pelagic, highly migratory/broad distribution species; this seems to have influenced the distribution of the fishing fleet, namely the vast geographic extent occupied and unevenly distributed effort; Results suggest there is a large shark/boat spatial overlap namely in productive regions; High percentage of the tracked blue sharks at-risk during short tracking periods; Population structuring in blue sharks, coupled with our results of highly unbalanced fishing effort, suggests different segments of the population face differential risk from longlining effort; Extensive space-use of restricted core areas is another factor known to increase interactions with fisheries and exacerbate catch rates; Mapping/quantification of interactions can be a general utility tool applicable to management of pelagic species.
Acknowledgments I would like to thank Professor D.W. Sims and all the co-authors of the presented study; MBA (Marine Biological Association of the U. K.) Behavioural Ecology Laboratory; CIBIO (Centro de Investigação em Biodiversidade e Recursos Genéticos); This work was supported by FCT (Fundação para a Ciência e a Tecnologia) and the Save our Seas Foundation. www.mba.ac.uk/simslab/