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Self-starting CUSUM approach for monitoring data poor fisheries

  • Deepak George Pazhayamadom
  • , Ciarán J. Kelly
  • , Emer Rogan
  • , Edward A. Codling
  • University College Cork
  • Marine Institute
  • University of Essex

Research output: Contribution to journalArticlepeer-review

Abstract

This study attempts to determine whether a fish stock can be monitored and assessed if no historical fisheries data are available. Many existing methods require a time series of population and fishing pressure observations to estimate reference points to trigger decision rules. We demonstrate here the self-starting cumulative sum control chart (SS-CUSUM) where reference points are calibrated from indicator observations sequentially in real time as they are monitored. We used SS-CUSUM to monitor catch-based indicators from a simulated fishery where no previous scientific data are available. In the scenarios considered, the SS-CUSUM was successful in producing responses to fishing impacts with all indicators. A qualitative assessment on performance measures showed that the method worked best with indicators that represented the large fish component in landed catches (large fish indicators). Our study implies that neither a reference point nor a formal fish stock assessment is necessarily required to detect the impact of fishing on stock biomass. We discuss how SS-CUSUM could be incorporated into the assessment process for data poor fisheries.

Original languageEnglish
Pages (from-to)114-127
Number of pages14
JournalFisheries Research
Volume145
DOIs
Publication statusPublished - Aug 2013

Keywords

  • Data poor
  • Fisheries monitoring
  • Indicators
  • Self-starting CUSUM

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