Do we have enough information to apply the ecosystem approach to management of deep-sea fisheries? An example from the West of Scotland

Sheila Heymans, Kerry Howell, Morag Ayers, Michael Burrows, John D M Gordon, Emma G. Jones, Francis Neat

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22 Citations (Scopus)

Abstract

There is currently a global call for more use of an ecosystem approach to fisheries management (EAFM), and ecosystem models such as Ecopath with Ecosim (EwE) are being used to provide a holistic view of ecosystem-fisheries interactions. Although these can be useful for an EAFM, the relative paucity of data available for deep-sea ecosystems raises concerns whether we can effectively apply an EAFM to the deep sea. The deep-sea ecosystem off the west coast of Scotland has been studied for longer and in more detail than most. This study assimilates the significant published and unpublished information available on this ecosystem into an EwE model. The results suggest that there are sufficient data available to construct an ecosystem model, but the quality of the data varies and serious potential sources of error are present in biomass and discard estimates. The assumptions needed to produce a model are varied and must be considered when interpreting the outputs of the model. Ecosystem modelling provides a unique view of the deep-water ecosystem and facilitates hypothesis development concerning predator-prey and inter-fishery interactions. Sharks are used to illustrate the benefits of using an ecosystem model to describe changes in their biomass and their prey species. The results show that both fishing for sharks and fishing for their prey affect the biomass of sharks.
Original languageEnglish
Pages (from-to)265-280
Number of pages16
JournalICES J MAR SCI
Issue number8
DOIs
Publication statusPublished - 2011

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Keywords

  • DIFFERENT TRAWLS
  • SHARKS
  • Marine & Freshwater Biology
  • FRONTIER
  • Oceanography
  • ROCKALL TROUGH
  • MORTALITY
  • WATER FISHERY
  • Fisheries
  • NORTHEAST ATLANTIC-OCEAN
  • DISCARDS
  • DEMERSAL FISH
  • TEMPERATURE

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