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Modelling the direct impact of bottom trawling on the North Sea fish community to derive estimates of fishing mortality for non-target fish species
Piet, G.J.; Van Hal, R.; Greenstreet, S.P. R. (2009). Modelling the direct impact of bottom trawling on the North Sea fish community to derive estimates of fishing mortality for non-target fish species. ICES J. Mar. Sci./J. Cons. int. Explor. Mer 66(9): 1985-1998. https://dx.doi.org/10.1093/icesjms/fsp162
In: ICES Journal of Marine Science. Academic Press: London. ISSN 1054-3139; e-ISSN 1095-9289, more
Peer reviewed article  
Available in  Authors 
Keywords
    Data > Fishery data > Catch/effort
    Distribution > Geographical distribution
    Fishing
    Impacts
    Spatial distribution
    Marine/Coastal
Author keywords
    catch efficiency; elasmobranchs; fishing effort; fishing impact;non-target species; spatial distribution
Authors  Top 
  • Piet, G.J., more
  • Van Hal, R.
  • Greenstreet, S.P. R.
Abstract
    This study introduces a spatially explicit model that combines abundance data for all the main fish species in the demersal North Sea fish community with international effort data and estimates of gear-, species-, and size-dependent catch efficiency to determine the mortality of non-target fish species caused by bottom trawl fisheries and its spatial variation. Where necessary information was lacking, assumptions were made, and a sensitivity analysis performed to examine the impact of these issues on model results. Model outcomes were validated using international landings and discard data for five target species: cod, haddock, whiting, sole, and plaice. This showed that depending on its configuration, the model could reproduce recorded landings and discards of these species reasonably well. This suggests that the model could be used to simulate rates of fishing mortality for non-target fish species, for which few data are currently available. Sensitivity analyses revealed that model outcomes were most strongly influenced by the estimates of gear catch efficiency and the extent to which the distributions of fishing effort and each species overlapped. Better data for these processes would enhance the contribution that this type of model could make in supporting an ecosystem approach to fisheries management.
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