Asset Details
Do you wish to reserve the book?
Bayesian state-space models with multiple CPUE data: the case of a mullet fishery
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Bayesian state-space models with multiple CPUE data: the case of a mullet fishery
Do you wish to request the book?
Bayesian state-space models with multiple CPUE data: the case of a mullet fishery
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Bayesian state-space models with multiple CPUE data: the case of a mullet fishery
2017
Overview
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
