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Comprehensive discard reconstruction and abundance estimation using flexible selectivity functions
Aarts, G.; Poos, J.-J. (2010). Comprehensive discard reconstruction and abundance estimation using flexible selectivity functions, in: Poos, J.-J. (2010). Effort allocation of the Dutch beam trawl fleet. pp. 127-147
In: Poos, J.-J. (2010). Effort allocation of the Dutch beam trawl fleet. PhD Thesis. Rijksuniversiteit Groningen: Groningen. ISBN 978-90-367-4412-6. 173 pp., more

Also published as
  • Aarts, G.; Poos, J.-J. (2009). Comprehensive discard reconstruction and abundance estimation using flexible selectivity functions. ICES J. Mar. Sci./J. Cons. int. Explor. Mer 66(4): 763-771, more

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Keywords
    Flatfish fisheries; Population dynamics; Splines; Statistical models; ANE, North Sea [gazetteer]; Marine

Authors  Top 
  • Aarts, G.
  • Poos, J.-J., more

Abstract
    The additional mortality caused by discarding may hamper the sustainable use of marine resources, especially if it is not accounted for in stock assessment and fisheries management. Generally, long and precise time-series on age-structured landings exist, but historical discard estimates are often lacking or imprecise. The flatfish fishery in the North Sea is a mixed fishery targeting mainly sole and plaice. Owing to the gear characteristics and a minimum landing size for these species, considerable discarding occurs, especially for juvenile plaice. Discard samples collected by on-board observers are available since 1999 from a limited number of commercial fishing trips. Here, we develop a statistical catch-at-age model with flexible selectivity functions to reconstruct historical discards and estimate stock abundance. We do not rely on simple predefined selectivity ogives, but use spline smoothers to capture the unknown non-linear selectivity and discard patterns, and allow these to vary in time. The model is fitted to the age-structured landings, discards, and survey data, the most appropriate model is selected, and estimates of uncertainty are obtained

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