Pazhayamadom, Deepak George and Kelly, Ciarán J and Rogan, Emer and Codling, Edward A (2013) Self-starting CUSUM approach for monitoring data poor fisheries. Fisheries Research, 145. pp. 114-127. DOI https://doi.org/10.1016/j.fishres.2013.02.002
Pazhayamadom, Deepak George and Kelly, Ciarán J and Rogan, Emer and Codling, Edward A (2013) Self-starting CUSUM approach for monitoring data poor fisheries. Fisheries Research, 145. pp. 114-127. DOI https://doi.org/10.1016/j.fishres.2013.02.002
Pazhayamadom, Deepak George and Kelly, Ciarán J and Rogan, Emer and Codling, Edward A (2013) Self-starting CUSUM approach for monitoring data poor fisheries. Fisheries Research, 145. pp. 114-127. DOI https://doi.org/10.1016/j.fishres.2013.02.002
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. © 2013 Elsevier B.V.
Item Type: | Article |
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Uncontrolled Keywords: | Self-starting CUSUM; Indicators; Data poor; Fisheries monitoring |
Subjects: | Q Science > QA Mathematics Q Science > QH Natural history > QH301 Biology S Agriculture > SH Aquaculture. Fisheries. Angling |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Mathematics, Statistics and Actuarial Science, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 05 Aug 2013 10:50 |
Last Modified: | 16 May 2024 17:05 |
URI: | http://repository.essex.ac.uk/id/eprint/7237 |