1. 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

2. 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.

3. 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.

4. Methodology – shark tracking

5. 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.

6. 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.

7. 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.

8. Results – fishing fleet

9. Results – fishing fleet
 Overall pattern showed a general decrease of fishing activity until late spring – early
summer, with a subsequent increase before the end of the year.

10. Results – blue sharks
 A total of 32 blue sharks (21 females and 11 males) ranging in size from 90 to 200 cm fork
length (FL) were satellite tagged; high space-use was observed in coastal areas.

11. Results – blue sharks

12. 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).

13. Results – shark/boat interactions

14. Results – shark/boat interactions
 Shark/boat interactions were observed at the northern approach of the Bay of Biscay
shelf edge and off the south-western and western Iberia coast.

15. Results – Shark/boat interactions

16. 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.

17. Preliminary results – full Atlantic

18. 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/