How many feeding data be integrated into a model for a Norwegian fjord population of cod (Gadus morhua L.)?
In: Scientia Marina (Barcelona). Consejo Superior de Investigaciones Científicas. Institut de Ciènces del Mar: Barcelona. ISSN 0214-8358; e-ISSN 1886-8134, more
Also appears in:Ulltang, Ø.; Blom, G. (2003). Fish stock assessments and predictions: integrating relevant knowledge. SAP Symposium held in Bergen, Norway 4-6 December 2000. Scientia Marina (Barcelona), 67(S1). Institut de Ciències de Mar: Barcelona. 374 pp. https://dx.doi.org/10.3989/scimar.2003.67s1, more
|   |
| Keywords |
Aquatic organisms > Marine organisms > Fish > Marine fish
Behaviour > Feeding behaviour > Cannibalism
Feeding
Models > Mathematical models
Organisms > Aquatic organisms > Animals > Aquatic animals > Marine animals > Fishes > Aquatic animals > Marine fishes > Osteichthyes > Cod
Population characteristics > Population number
Population functions > Mortality
Gadus morhua Linnaeus, 1758 [WoRMS]
ANE, Norway [Marine Regions]
Marine/Coastal |
| Abstract |
We investigate how cod feeding data may be included into a recently developed age-structured model for a coastal cod population in a small fjord in northern Norway. The model integrates data from mark-recapture experiments, trawl-surveys and commercial catches. The fjord population has high biomass density (2-3 tonnes km-2) and low fishing mortality rates (F <0.30 year-1). The model output parameters (cannibalism mortality rate, other natural mortality rate, fishing mortality rate, recruitment numbers, gear selection functions for commercial and research trawls and trawl catchability coefficient) are estimated using a weighted least-square minimisation routine. We evaluate different strategies for, and effects of, inclusion of feeding data in the model, and evaluate the effects of uncertainty in the different data sets. Representation of the feeding data as an Ursin lognormal distributed size (predator weight/prey weight) food preference function yielded realistic cannibalism mortalities. The sensitivity of the results to data input are discussed. |
|
