An alternative surplus production model

Rankin, Peter Sheldon and Lemos, Ricardo T. (2015) An alternative surplus production model. Ecological Modelling, 313 109-126. doi:10.1016/j.ecolmodel.2015.06.024


Author Rankin, Peter Sheldon
Lemos, Ricardo T.
Title An alternative surplus production model
Journal name Ecological Modelling   Check publisher's open access policy
ISSN 0304-3800
1872-7026
Publication date 2015-10-10
Sub-type Article (original research)
DOI 10.1016/j.ecolmodel.2015.06.024
Volume 313
Start page 109
End page 126
Total pages 18
Place of publication Amsterdam, Netherlands
Publisher Elsevier
Collection year 2016
Language eng
Formatted abstract
In this work we present a novel surplus production model for fisheries stock assessment. Our goal is to enhance parameter estimation and fitting speed. The model employs a production function that differs from the canonical logistic (Schaefer) and Gompertz (Fox) functions, but is still connected to the Pella–Tomlinson formulation. We embed this function in a state-space model, using observed catch-per-unit-effort indices and measures of fishing effort as input. From the literature we derive Bayesian prior densities for all model hyperparameters (carrying capacity, catchability, growth rate and error variance), as well as the state (annual stock biomass). We use the well-studied Namibian hake fishery as a case study, via which we compare the Schaefer, Fox and Pella–Tomlinson models with the new model. We also develop a package for the software R, which employs a Shiny application for data exploration, model specification, and output analyses. Posterior densities of hyperparameters and reference points agree across models. Identifiability issues emerge in the more cumbersome Pella–Tomlinson model. The new model yields small but consistent improvements in precision. It also renders implementation faster and easier, with no hidden truncation of negative biomasses. We conclude by discussing theoretical and practical extensions to this new model.
Keyword Surplus production model
Stock assessment
Bayesian inference
Fisheries models
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Mathematics and Physics
Official 2016 Collection
School of Biological Sciences Publications
 
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