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1 Deepak George Pazhayamadom a, Emer Rogan a, Ciaran Kelly b and Edward Codling c a School of Biological, Earth and Environmental Sciences (BEES), University.

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Presentation on theme: "1 Deepak George Pazhayamadom a, Emer Rogan a, Ciaran Kelly b and Edward Codling c a School of Biological, Earth and Environmental Sciences (BEES), University."— Presentation transcript:

1 1 Deepak George Pazhayamadom a, Emer Rogan a, Ciaran Kelly b and Edward Codling c a School of Biological, Earth and Environmental Sciences (BEES), University College Cork, Ireland; b Fisheries Science Services, Marine Institute, Ireland; c Department of Mathematical Sciences, University of Essex, United Kingdom Can we manage a fishery if no previous data are available? A PPLICATION OF QUALITY CONTROL CHARTS IN MANAGEMENT OF DATA LIMITED FISHERIES Historical data Yes Qualitative risk assessments Quantitative stock assessments No Self Starting Cumulative Sum SS-CUSUM YES No historical data at 0 th year

2 2 SS-CUSUM Self starting CUSUM (Hawkins, 1998) Running mean (Calibrated using real time data) Three parameters 1. Allowance (k) 2. Control limit (h) 3. Winsorizing constant (w) SS-CUSUM is an indicator monitoring tool. SS-CUSUM do not need a reference point. SS-CUSUM calculate the cumulative deviations of indicator from running mean Parameters Allowance ( k ) accommodate the inherent variability in observations Control limit ( h ) produce signal if the indicator is in an out-of-control (OC) situation Winsorizing constant ( w ) make self starting CUSUM robust to outliers E VALUATION OF SS-CUSUM USING A STOCHASTIC SIMULATION TEST A stable fish stock was overfished and indicators were monitored using SS-CUSUM Signals obtained from SS-CUSUM were used to calculate sensitivity and specificity Sensitivity is the probability of getting a true signal when overfishing was applied Specificity is the probability of getting a true signal when there was no overfishing Indicator observations corresponding to out- of-control situations are omitted while calibrating the running mean P ERFORMANCE MEASURES USED Receiver Operator Characteristic ( ROC ) curves

3 3 SS-CUSUM was successful in detecting the fishing impact. An indicator is best when the apex of ROC curve is closer to upper left corner. The method performed best with Large Fish Indicators (LF catch numbers, LF catch weight and LF CPUE). R ESULTS (ROC CURVES ) C ONCLUSION All stock indicators in the study were useful in detecting fishing impact and hence SS-CUSUM can be potentially used for monitoring data poor fisheries R EFERENCE : Hawkins, D.,Olwell, D., 1998. Cumulative sum charts and charting for quality improvement: Springer Verlag, pp:162-168. B EST G OOD W ORST


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