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Estimating the horizontal and temporal overlap of pelagic fish distribution in the Norwegian Sea using individual-based modelling
Utne, K.; Huse, G. (2012). Estimating the horizontal and temporal overlap of pelagic fish distribution in the Norwegian Sea using individual-based modelling. Mar. Biol. Res. Spec. Issue 8(5-6): 548-567. dx.doi.org/10.1080/17451000.2011.639781
In: Marine Biology Research. Taylor & Francis: Oslo; Basingstoke. ISSN 1745-1000, more
Peer reviewed article  

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Keywords
    Ecology; Genetic algorithms; Interactions; Spawning; Spring (season); Clupea harengus Linnaeus, 1758 [WoRMS]; Micromesistius poutassou (Risso, 1827) [WoRMS]; Scomber scombrus Linnaeus, 1758 [WoRMS]; ANE, North East Atlantic [Marine Regions]; Marine

Authors  Top 
  • Utne, K.
  • Huse, G., more

Abstract
    The most abundant pelagic fish species in the Norwegian Sea, Norwegian spring-spawning herring, Northeast Atlantic mackerel and Northeast Atlantic blue whiting have inter-annual variation in their summer feeding migrations. Knowledge about the spatial distribution and overlap is essential for understanding the species’ interactions and their impact on the ecosystem. Here we attempt to recreate the annual feeding migrations with individual-based modelling and use the results to estimate the daily horizontal overlap between the three species. Species-specific swimming velocities and direction, and the degree of random walk for each year 1995–2003 are found by using a genetic algorithm through calibration with survey observations. From the results it can be concluded that herring and mackerel have a very low horizontal overlap during the feeding season, while herring and blue whiting have a high horizontal overlap. Blue whiting and mackerel have some horizontal overlap in late summer, but a very limited vertical overlap. There is generally a high variability in the horizontal overlap between the species both seasonally and inter-annually. The species utilize many of the same feeding areas in the Norwegian Sea, but often at different times. The modelling approach developed can be useful for implementation of dynamic fish distribution in end to end ecosystem models.

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