1. Monitoring data poor fisheries using a self starting scheme Deepak George Pazhayamadom University College Cork, Ireland

2. Indicator based management using traffic light approach Limit- 18cm Precautionary- 25cm Acceptable- 28cm Empirical indicators e.g. Mean length or Mean weight Reference directionse.g. Increased or decreased? Reference limite.g. Whether management required or not?

3. Statistical Process Control (SPC)- Shewhart control chart (A Statistical framework for traffic light approach) True Positive True Negative False Positive False Negative

4. Statistical Process Control (SPC)- CUSUM control chart [z t =(D-µ)/σ] D = Indicator(Time Series) µ = Control Mean (Target) σ = Standard Deviation

5. Self starting CUSUM control chart (SS-CUSUM) Is it useful to monitor data poor fisheries?

6. Methods - Fisheries Simulation SS-CUSUM

7. Methods - Stock Indicators 1.Mean Age 2. Mean Length 3. Mean Weight 4. Large Fish Catch Numbers (LFCN) 5. Large Fish Catch Weight (LFCW) Age 1Age 2Age 3Age 4Age 5Age 6Age 7 n=5 n=10 n=20 n=35 n=25 n=4 n=1 e.g. LFCN = 30/100

8. Methods - An example scenario 1.Monitored 20 years 2.Fixed parameters (k=0.5, h=0) 3.Collected data on TP, TN, FP, FN 4.Repeated 1000 times Repeated for control limit (h) ranging from 0 to 6 with 0.1 interval

9. Results - Performance Measures Sensitivity – Probability of True Positive signals Specificity – Probability of True Negatives 1.Receiver Operator Characteristic (ROC) Curve (Sensitivity Vs 1-Specificity) 2. Optimal Performance (Sensitivity=Specificity)

11. Thank You Any questions? deepakgeorgep@student.ucc.ie Acknowledgements Emer Rogan University College Cork, Ireland Ciaran Kelly Marine Institute, Ireland Edward A. Codling University of Essex, UK