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

  • Sant’Ana R
  • Gerhard Kinas P
  • Villwock de Miranda L
  • et al.
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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

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Sant’Ana, R., Gerhard Kinas, P., Villwock de Miranda, L., Schwingel, P. R., Castello, J. P., & Paes Vieira, J. (2017). Bayesian state-space models with multiple CPUE data: the case of a mullet fishery. Scientia Marina, 81(3), 361. https://doi.org/10.3989/scimar.04461.11a

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