Abstract
Black scabbardfish (Aphanopus carbo Lowe, 1839) is a widely distributed species across the Atlantic ocean. In Portuguese mainland waters the existing specimens are immature (not able to reproduce). It is admitted that they have migrated from the West of the British Isles and that they remain in the area for some years, until they attain an adequate size or physiological conditions which allow them to migrate and reproduce elsewhere.The present study aims to model the dynamics of the population of black scabbardfish living in the International Council for the Exploration of the Seas Division IXa, for which disaggregated data are available, although within the context of a larger population. With this purpose, a state-space model is used, which enables the estimation of the unknown abundance (latent process) by exploring its dependency relationship with the observational data on the species fishing landings in that area. The population is partitioned into length groups and the population evolution process is subdivided into biological related subprocesses.The estimation is achieved within a Bayesian paradigm, where all the available biological information is incorporated in the prior distributions of the parameters of the subprocesses. Later, short-term trajectories of the population living in IXa are studied, via simulations that are constructed based on different management scenarios.
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Acknowledgements
This work is financed by National Funds through FCT—Fundação para a Ciência e a Tecnologia—in the scope of projects UID/MAT/00297/2013 and PEst-OE/MAT/UI0006/2014 and by EU Funds in the scope FP7-DEEPFISHMAN project, management and monitoring of deep-sea fisheries and stocks, Grant agreement no.: 227390.
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Natário, I., Figueiredo, I., Lucília Carvalho, M. (2015). A State Space Model Approach for Modelling the Population Dynamics of Black Scabbardfish in Portuguese Mainland Waters. In: Bourguignon, JP., Jeltsch, R., Pinto, A., Viana, M. (eds) Dynamics, Games and Science. CIM Series in Mathematical Sciences, vol 1. Springer, Cham. https://doi.org/10.1007/978-3-319-16118-1_26
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