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Using Catch Statistics to Investigate Effects of Seismic Activity on Fish Catch Rates

Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 730)

Abstract

Norway has been a petroleum nation for several decades, with most of its offshore activities originally concentrated in the North Sea. As these reserves diminish, focus is shifting to areas further north, some of which, particularly the Lofoten/Vesterålen area, are crucial for the reproduction of major fish stocks such as Gadus morhua (northeastern arctic cod), Melanogrammus aeglefinus (haddock), and Clupea harengus (herring) in the Barents Sea. Cod stocks are the basis for enormous seasonal fisheries during the spawning season in late winter, but other species such as Pollachius virens (saithe), Melanogrammus aeglefinus, Brosme brosme (tusk), Molva molva (ling), Sebastes marinus (golden redfish), and Lophius piscatorius (angler) provide a living for local fishermen the whole year-round. Although the area has not yet been opened for exploitation, seismic surveys for petroleum reserves have been carried out by the Norwegian authorities during the summers of 2008 and 2009 (Fig. 1). Seismic air gun investigations are major sources of low-frequency noise in areas of petroleum industry activity. The sound from the guns has its peak energy in the most sensitive hearing range of fish. It has already been documented that air gun activity can have a negative impact on fish catch rates (Engås et al. 1996; Skalski et al. 1992). Fishermen in the area are, quite naturally, anxious about the effect of seismic activity on their livelihoods. To determine whether the seismic exploration carried out in the Lofoten/Vesterålen area has had an effect on the local fisheries, data from official databases of landed catches have been analyzed.

Keywords

Fishing Gear Seismic Survey Catch Rate Melanogrammus Aeglefinus Offshore Activity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Aud Vold
    • 1
  • Sven Løkkeborg
    • 1
  • Maria M. Tenningen
    • 1
  1. 1.Institute of Marine ResearchBergenNorway

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