Pazhayamadom, Deepak George and Kelly, Ciarán J and Rogan, Emer and Codling, Edward A (2015) Decision Interval Cumulative Sum Harvest Control Rules (DI-CUSUM-HCR) for managing fisheries with limited historical information. Fisheries Research, 171. pp. 154-169. DOI https://doi.org/10.1016/j.fishres.2014.09.009
Pazhayamadom, Deepak George and Kelly, Ciarán J and Rogan, Emer and Codling, Edward A (2015) Decision Interval Cumulative Sum Harvest Control Rules (DI-CUSUM-HCR) for managing fisheries with limited historical information. Fisheries Research, 171. pp. 154-169. DOI https://doi.org/10.1016/j.fishres.2014.09.009
Pazhayamadom, Deepak George and Kelly, Ciarán J and Rogan, Emer and Codling, Edward A (2015) Decision Interval Cumulative Sum Harvest Control Rules (DI-CUSUM-HCR) for managing fisheries with limited historical information. Fisheries Research, 171. pp. 154-169. DOI https://doi.org/10.1016/j.fishres.2014.09.009
Abstract
This study examines whether a fish stock can be managed using cumulative sum (CUSUM) control charts if limited historical information is available for the fish stock. We use the term 'limited' in the sense of having a minimal number of historical observations of relevant stock indicators and their respective control means (or reference points) that are aligned with the objectives of fisheries management. In the present study, a Decision Interval Cumulative Sum (DI-CUSUM) control chart was used to monitor two indices from a simulated fishery; the recruitment indicator and the large fish indicator (LFI). The fishery was subsequently managed using a harvest control rule (HCR) that triggered only when a significant deviation in the indicator trend was detected by the DI-CUSUM. The HCR was constructed using methods adopted from engineering process control theory where the adjustment in total allowable catch was determined by estimating the size of the shift in the indicator time series. We found that monitoring a combined indicator of both recruitment and LFI was more successful in controlling the fishery irrespective of the initial state of the fish stock. We discuss how DI-CUSUM could be incorporated into the management process for data poor fisheries.
Item Type: | Article |
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Uncontrolled Keywords: | Decision interval CUSUM; Indicator; Data poor; Fisheries management |
Subjects: | Q Science > QA Mathematics 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: | 18 Nov 2014 10:23 |
Last Modified: | 04 Dec 2024 07:07 |
URI: | http://repository.essex.ac.uk/id/eprint/11672 |