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Credit: 3ws

Quantifying the impact of environmental variables upon catch-per-unit-effort of the blue shark ( Prionace glauca ) in the w estern English Channel. J. D. Mitchell* † , K. J. Collins † , P. I. Miller ‡ , L.A. Suberg † † University of Southampton, ‡ Plymouth Marine Laboratory. Credit: 3ws.

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Credit: 3ws

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  1. Quantifying the impact of environmental variables upon catch-per-unit-effort of the blue shark (Prionaceglauca) in the western English Channel J. D.Mitchell*†, K. J. Collins†, P. I. Miller‡, L.A. Suberg†† University of Southampton, ‡ Plymouth Marine Laboratory Credit: 3ws Credit: James R.D. Scott * Corresponding author. Email: jonathanmitchell023@gmail.com

  2. Contents • Introduction • Aims and Objectives • Research Importance • Methods • Results • Research Limitations • Wider Implications for Fisheries Management • Summary • References Source: Compagno, (1984)

  3. Introduction • Migratory pelagic species • Single North Atlantic population1, segregated by age and sex2,3 • Mostly juvenile females in W. English Channel between June-October4,5 • Migrations driven by temperature, productivity and prey availability5,6 • Blue sharks targeted by Shark Angling Club of GB (SACGB) recreational rod and reel fishery, based in Looe, Cornwall Source: Kohler et al. (1998) (1) Kohler et al., 1998; (2) Stevens, 1990; (3) Nakano and Stevens, 2009; (4) Stevens, 1976; (5) Vas, 1990; (6) Nakano and Seki, 2003

  4. Credit: Baz Richardson

  5. Credit: The Portbyhan Hotel

  6. Aims and Objectives • To quantify how environmental variables affected CPUE of blue sharkin the western English Channel fishery between June-September 1998-2011 • Sea Surface Temperature (SST), surface chlorophyll a concentration (CHL), and tidal mixing front density • Generalised Additive Models (GAM) utilized • First study to analyse these relationships for blue sharks in shelf waters, and in North Atlantic Credit: J Pierson Source: Simpson et al. (1981)

  7. Why does this research matter? • High bycatchin North Atlantic Tuna and Swordfish longline fisheries7 • Export of shark fins to Asia highly lucrative • Recent growth in landings – 3,028 tonnes in 1990 to 37,178 tonnes in 20108 • Declines of 5-60% recorded in parts of North Atlantic in the last 30years9,10,11 • This study aimed to improve knowledge of environmental preferences and fisheries interactions of this species Credit: Shawn Heinrichs Credit: Alex Hofford (7) Buencuerpoet al., 1998; (8) ICCAT, 2012; (9) Campanaet al., 2006; (10) Baum et al., 2003; (11) Aires-da-Silva et al., 2008

  8. Study Location • SACGB fishing area in western English Channel • 16-40 km south of Looe, ~500 km-2 area UK FRANCE

  9. Method • GAM quantified the effect of SST, CHL, and front density (predictor variables) upon CPUE (response variable) • Monthly CPUE from SACGB fishing log • Spatio-temporally averaged environmental data – remote sensing • Second GAM analysed time-lagged effect of front density upon CPUE LOOE

  10. Credit: Total Fishing Credit: SACGB Credit: Fishing Cornwall

  11. Results - Model Variance

  12. Sea Surface Temperature • Maximum CPUE at 16.7⁰C • Peak CPUE between 16-17⁰C also recorded in North Pacific12,13 and South Atlantic14 commercial fisheries, using GAMs • Approximately central in 13-18⁰C optimum thermal range proposed for this species15 (12) Bigelow et al., 1999; (13) Walsh and Kleiber, 2001; (14) Carvalhoet al., 2011; (15) Casey, 1982

  13. Surface Chlorophyll a Concentration • Positive effect on CPUE – peak at 1.77mg m-3 • Similar peak CPUE at 2.10mg m-3observed in South Atlantic longline fishery14 • However, unexpected decline in CPUE at higher CHL - larger error levels and bloom datapoints? (14) Carvalho et al., 2011

  14. Front Density • Negative linear relationship opposite to that expected • Frontal strength positively affected CPUE in North Pacific fisheries12, and distribution and residence time of blue shark in Celtic Sea & Bay of Biscay16 • Widespread high productivity of English Channel potential cause of unexpected trend?? • Time-lagged effects… (12) Bigelow et al., 1999; (16) Queirozet al., 2012

  15. Time-lagged Front Density • Explained12.6% of model deviance and significant • Overall positive (but variable) effect on CPUE • Time-lag between evolution of front and accumulation of productivity, and attraction of planktivorous fish, then predators? • Increasing frontal energy at time-lags of 1 week and 1 month previously observed to increase blue shark CPUE12 (12) Bigelow et al., 1999

  16. Research Limitations • Fisheries bias – misrepresenting true environmental preferences • Effort not fully standardised – no. of anglers and trip length • Coarse resolution of spatio-temporally averaged data unable to represent effects of fine-scale features • GAM ‘n’ and confidence intervals Credit: Andy Jones

  17. Wider Implications for Fisheries Management • Improved knowledge of blue shark biology and ecology – environmental preferences • In combination with population dynamics and migration data offers potential for effective fisheries management • Remote sensing based management effective for reducing loggerhead turtle bycatch17 and managing Atlantic bluefintuna18 • Can similar strategies be applied to blue sharks? Source: TurtleWatch (NOAA) (17) Howell et al., 2008; (18) Druon, 2010

  18. Summary • Aim – To quantify the impact of SST, CHL and front density upon blue shark CPUE in a recreational fishery • Outcome – Environmental variables had a substantial and variable impact upon CPUE – reflecting environmental preferences • Importance – Provided insights into blue shark biology and ecology – vital for future development of fisheries management models • Take-home message– Integrated remote sensing based management models could be a powerful tool for halting declines in North Atlantic population

  19. Acknowledgments • The staff and fishermen of the SACGB for providing CPUE data, and to charter vessel skippers M. Collings, D. Bond, and P. Curtis, for allowing observation of the angling process • The Natural Environment Research Council Earth Observation Data Acquisition and Analysis Service (NEODAAS) for supplying satellite data for this study

  20. References • Kohler, N. E., Casey, J. G. & Turner, P. A. (1998). NMFS cooperative shark tagging program, 1962-93: an atlas of shark tag and recapture data. Marine Fisheries Review 60, 1-87. • Stevens, J. D. (1990). Further results from a tagging study of pelagic sharks in the north-east Atlantic. Journal of the Marine Biological Association of the United Kingdom70, 707-720. • Nakano, H. & Stevens, J. D. (2009). The biology and ecology of the blue shark, Prionaceglauca. In Sharks of the Open Ocean: Biology, Fisheries and Conservation (Camhi, M. D., Pikitch, E. K. & Babcock, E. A., eds), pp. 140-151. Oxford, UK: Blackwell Publishing Ltd. • Stevens, J. D. (1976). First results of shark tagging in the north-east Atlantic 1972-75. Journal of the Marine Biological Association of the United Kingdom 56, 929-937. • Vas, P. (1990). The abundance of the blue shark, Prionaceglauca, in the western English Channel. Environmental Biology of Fishes 29, 209-225. • Nakano, H. & Seki, M. P. (2003). Synopsis of biological data on the blue shark, (PrionaceglaucaLinnaeus). Bulletin of the Fisheries Research Agency of Japan 6, 18-55. • Buencuerpo, V., Rios, S. & Moron, J. (1998). Pelagic sharks associated with the swordfish, Xiphiasgladius, fishery in the eastern North Atlantic Ocean and the Strait of Gibraltar. Fishery Bulletin96, 667–685. • ICCAT (2012). ICCAT Report 2010-2011: Executive Summary: Sharks.Available at http://www.iccat.es/Documents/SCRS/ExecSum/SHK_EN.pdf (last accessed 12 April 2013). • Campana, S. E., Marks, L., Joyce, W. & Kohler, N. E. (2006). Effects of recreational and commercial fishing on blue sharks (Prionaceglauca) in Atlantic Canada, with inferences on the North Atlantic population. Canadian Journal of Fisheries and Aquatic Sciences 63, 670-682.

  21. References cont… • Baum, J. K., Myers, R. A., Kehler, D. G., Worm, B., Harley, S. J. & Doherty, P. A. (2003). Collapse and conservation of shark populations in the north-west Atlantic. Science. 299, 389-392. • Aires-da-Silva, A. M., Hoey, J. J. & Gallucci, V. F. (2008). A historical index of abundance for the blue shark (Prionaceglauca) in the western North Atlantic. Fisheries Research 92, 41-52. • Bigelow, K. A., Boggs, C. H. & He, X. (1999). Environmental effects on swordfish and blue shark catch rates in the US North Pacific longline fishery. Fisheries Oceanography 8, 178-198. • Walsh, W. A. & Kleiber, P. (2001). Generalized additive model and regression tree analyses of blue shark (Prionaceglauca) catch rates in the Hawaii-based commercial longline fishery. Fisheries Research 53, 115-131. • Carvalho, F. C., Murie, D. J., Hazin, F. H. V., Hazin, H. G., Leite-Mourato, B. & Burgess, G. H. (2011). Spatial predictions of blue shark (Prionaceglauca) catch rate and catch probability of juveniles in the south-west Atlantic. ICES Journal of Marine Science 68, 890-900. • Casey, J. G. (1982). The blue shark, Prionaceglauca. In Fish Distribution (Grosslein, M. D. & Azarovitz, T. R., eds), pp. 45-48. New York, NY: New York Sea Grant Institute. • Queiroz, N., Humphries, N. E., Noble, L. R., Santos, A. M. & Sims, D. W. (2012). Spatial dynamics and expanded vertical niche of blue sharks in oceanographic fronts reveal habitat targets for conservation. PLoS One 7. • Howell, E. A., Kobayashi, D. R., Parker, D. M., Balazs, G. H. & Polovina, J. J. (2008). TurtleWatch: a tool to aid in the by-catch reduction of loggerhead turtles Carettacaretta in the Hawaii-based pelagic longline fishery. Endangered Species Research5, 267–278. • Druon, J-N. (2010). Habitat mapping of the Atlantic bluefin tuna derived from satellite data: its potential as a tool for the sustainable management of pelagic fisheries. Marine Policy 34, 293-297.

  22. Credit: Chris Fallows

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