Hook selectivity models assessment for black spot seabream. Classic and heuristic approaches.

Identificadores
URI: http://hdl.handle.net/10498/14804
DOI: :10.1016/j.fishres.2009.10.005
ISSN: 0165-7836
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2009-10-13Department
BiologíaSource
Fisheries Research 102 (2010) 41–49Abstract
Size selectivity of the deep water longline used in the black spot seabream (Pagellus bogaraveo) fishery in
the Strait of Gibraltar was studied with data of four sizes of hooks. Logistic (classic) and Artificial Neural
Networks (heuristic) selectivity models were fitted for two experimental fishing trials. Logistic selectivity
model was adequate for only one of the two periods analysed and the inferior results obtained with the
classical approach were significantly improved by ANNs. These results indicate that in the event that the
classic models do not fit well, perhaps due to poor quality of the data (such as a smaller sample size or
highly overlapped distributions), the simpler ANNs models, with capacity to combine linear relationships
and highly non-linear, are most appropriate to establish the functional relation between variables.
Subjects
Hook; Longline; Selectivity; Pagellus bogaraveo; Artificial Neural Networks; Strait of GibraltarCollections
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