Prista, Nuno and Diawara, Norou and Costa, Maria José and Jones, Cynthia (2011) Use of SARIMA models to assess data-poor fisheries: a case study with a sciaenid fishery off Portugal. Fishery Bulletin, 109(2), pp. 170-185.
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Research on assessment and monitoring methods has primarily focused on fisheries with long multivariate data sets. Less research exists on methods applicable to data-poor fisheries with univariate data sets with a small sample size. In this study, we examine the capabilities of seasonal autoregressive integrated moving average (SARIMA) models to fit, forecast, and monitor the landings of such data-poor fisheries. We use a European fishery on meagre (Sciaenidae: Argyrosomus regius), where only a short time series of landings was available to model (n=60 months), as our case-study. We show that despite the limited sample size, a SARIMA model could be found that adequately fitted and forecasted the time series of meagre landings (12-month forecasts; mean error: 3.5 tons (t); annual absolute percentage error: 15.4%). We derive model-based prediction intervals and show how they can be used to detect problematic situations in the fishery. Our results indicate that over the course of one year the meagre landings remained within the prediction limits of the model and therefore indicated no need for urgent management intervention. We discuss the information that SARIMA model structure conveys on the meagre lifecycle and fishery, the methodological requirements of SARIMA forecasting of data-poor fisheries landings, and the capabilities SARIMA models present within current efforts to monitor the world’s data-poorest resources.
|Title:||Use of SARIMA models to assess data-poor fisheries: a case study with a sciaenid fishery off Portugal|
|Journal or Publication Title:||Fishery Bulletin|
|Page Range:||pp. 170-185|
|Issuing Agency:||United States National Marine Fisheries Service|
|Depositing User:||Patti M. Marraro|
|Date Deposited:||07 Jun 2012 14:53|
|Last Modified:||07 Jun 2012 14:53|
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