Scientia Marina, Vol 81, No 3 (2017)

Bayesian state-space models with multiple CPUE data: the case of a mullet fishery


https://doi.org/10.3989/scimar.04461.11A

Rodrigo Sant’Ana
Universidade do Vale do Itajaí , Brazil
orcid http://orcid.org/0000-0003-2252-6014

Paul Gerhard Kinas
Universidade Federal de Rio Grande , Brazil
orcid http://orcid.org/0000-0002-1294-9518

Laura Villwock de Miranda
Instituto de Pesca de São Paulo , Brazil
orcid http://orcid.org/0000-0002-1750-8973

Paulo Ricardo Schwingel
Universidade do Vale do Itajaí , Brazil
orcid http://orcid.org/0000-0003-2524-9550

Jorge Pablo Castello
Universidade Federal de Rio Grande , Brazil
orcid http://orcid.org/0000-0002-1962-6471

João Paes Vieira
Universidade Federal de Rio Grande , Brazil
orcid http://orcid.org/0000-0002-0669-9444

Abstract


We propose a novel Bayesian hierarchical structure of state-space surplus production models that accommodate multiple catch per unit effort (CPUE) data of various fisheries exploiting the same stock. The advantage of this approach in data-limited stock assessment is the possibility of borrowing strength among different data sources to estimate reference points useful for management decisions. The model is applied to thirteen years of data from seven fisheries of the lebranche mullet (Mugil liza) southern population, distributed along the southern and southeastern shelf regions of Brazil. The results indicate that this modelling strategy is useful and has room for extensions. There are reasons for concern about the sustainability of the mullet stock, although the wide posterior credibility intervals for key reference points preclude conclusive statistical evidence at this time

Keywords


hierarchical models; MCMC; multiple fisheries; data-limited; stock assessment; Mugil liza

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