Using information-based methods to model age and growth of the silver scabbardfish, Lepidopus caudatus, from the mid-Atlantic Ocean

Abstract

The traditional species targeted by the Azorean demersal mixed hook-and-line commercial fisheries are presently facing a decline in captures, and the demand for new demersal resources is growing. The silver scabbardfish, Lepidopus caudatus, is a potential new resource to be exploited in the region; however, reports on its vulnerability and stock status are contradictory, which highlights the importance of arriving at accurate age and growth parameter estimates for this species. The 808 individuals used in the present study were acquired from commercial landings in the Azorean islands of São Miguel and Faial, collected monthly between 2004 and 2010. Ages were determined by counting growth increments in whole sagittal otoliths. Four different growth models were fitted to the data: von Bertalanffy growth function, the Gompertz model, the logistic model and the power function. Akaike's Information Criterion was used to evaluate the models and finally a multi-model inference was employed to arrive at model-averaged estimates of L_∞. The von Bertalanffy function performed as well as the other candidates, although the parameter estimates for this model were usually higher than for the Gompertz and logistic models. The analysis suggests that L. caudatus is a relatively fast-growing species that could constitute a sustainable resource for commercial fisheries in the region, pending further research into the unbalanced sex ratios observed here.

Key words:

• AIC weights
• Azores
• bottom longline fishery
• multi-model inference
• Trichiuridae

Acknowledgements

We would like to thank Ângela Canha, Dália Reis, Fátima Mendes and Rui Rosa for sampling advice and technical assistance. We are grateful for the contributions and comments made by anonymous reviewers.

Funding

This research was funded in part by the Direcção Regional de Ciência e Tecnologia of the Azores Regional Government (M2.1.2/I/014/2008) in collaboration with the European Social Fund program PRO-EMPREGO.

Editorial responsibility: Geir Ottersen

Additional information

Funding

Funding: This research was funded in part by the Direcção Regional de Ciência e Tecnologia of the Azores Regional Government (M2.1.2/I/014/2008) in collaboration with the European Social Fund program PRO-EMPREGO.