“APPLICATION OF SIGNAL DETECTION METHODS TO

THE FISHERIES MANAGEMENT SYSTEM”

By, Deepak George Pazhayamadom

Emer Rogan(Department of ZEPS, University College Cork)

Ciaran Kelly(Fisheries Science Services, Marine Institute)

Edward Codling(Lecturer in Mathematical Biology, University of

Essex)

Supervisors

Department of Zoology, Ecology and Plant Science (ZEPS)

University College Cork (UCC), Cork, Ireland

Fisheries Management(Traditional approach)

Fishery Dependent Data:Catch (BIAS,

NOISE)Fishery Independent Data:

Survey (BIAS, NOISE)

Fisheries Management(Alternative approach)

SSB, F [Estimated Indicators] (Stock abundance and Exploitation)

Population models with assumptions

Monitor with Reference Limits(Acceptable, Precautionary, Limit)

Regulate with output controls

HCR (Eg: TAC)Other measures (Eg: Effort)

Next Year

Limit 1000 1.5

Precautionary 1500 0.8

Acceptable 2000 0.5

F

SSB

Statistical Process Control

Statistical Signals [Stock Indicators]

EXISTING APPROACH

Maximize Yield Stabilize Yield

Scandol, J., 2003. Use of cumulative sum (CUSUM) control charts of landed catch in the management of fisheries. Fish. Res. 64, 19-36.

Scandol, J., 2005. Use of Quality Control Methods to Monitor the Status of Fish Stocks. In: Kruse, G.H., Galluci, V.F., Hay, D.EPetitgas, P. (2009). "The CUSUM out-of-control table to monitor changes in fish stock status using many indicators." Aquat. Living Resour. 22(2): 201-206., Perry, R.I., Peterman, R.M., Shirley, T.C., Spencer, P.D., Wilson, B., Woodby, D.(Eds.), Fisheries Assessment in Data Limited Situations. Alaska Sea Grant AK-SG-05-02. ISBN:156612-093-4,pp.213-234.

FISBOAT Project (Fishery Independent Survey Based Operational Assessment Tools)

Petitgas, P. (2009). "The CUSUM out-of-control table to monitor changes in fish stock status using many indicators." Aquat. Living Resour. 22(2): 201-206.

Mesnil, B. and P. Petitgas (2009). "Detection of changes in time-series of indicators using CUSUM control charts." Aquat. Living Resour. 22(2): 187-192.

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REFERENCE:

SPC(Statistical Process Control)

SPC is a statistical technique concerned with stabilizing processes to fixed targets and improvements for

Making inferences about process behaviour Decision making

Time Series Data (On Process)

Monitor Indicator

Out of

Control

?

YESNO Correct Cause

Product

N =N+1N =N+1

N = ‘1’ year

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Monitor a process using indicator/s and stabilize the system using corrective action if the control chart signals an “Out of Control” situation.

UPPER CONTROL LIMIT (UCL)

CONTROL MEAN (Cµ)

LOWER CONTROL LIMIT (LCL)

UPPER CONTROL LIMIT (UCL)

Allowance Parameter (‘K’)

CUSUM Control Chart

• Standardize each indicator

[zt=(D-µ)/σ]

D = Indicator(Time Series), µ = Control Mean, σ = Control S.D.

• Standardized values (zt) are converted to Lower and Upper CUSUMs

Lower CUSUM : Ф-n = min (0, Ф -

n-1 + zn + k), Ф-0 = 0

Upper CUSUM : Ф+n = max (0, Ф +

n-1 + zn - k), Ф+0 = 0

k = Allowance parameter

7

UCL

LCL

Cµ

K= 1

Fisheries Management

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Recommendations:1. Empirical Indicators2. Catch Data

- Age Based Numbers

- Age Based Weight- Proportions

Recommendations:1. Relationship with SSB2. Best Matches (Correlations)3. Use of Combined IndicatorsPHASE I: (Reference Period)1. From all available data2. Moving Average3. SSB levels

PHASE II: (Tune CUSUMs)IC-ARL, OC-ARL

STEPS & GUIDELINES

ICES Stocks1. Scenarios of past events2. Life histories

Phase III: Action ?Best Strategy or HCRs

• Data ?

• Define Indicators ?

• Best Indicators ?

• Control Mean (‘µ’) ?

• Control Limits (‘h’) ?

• Inherent variability (‘k’) ?

• HCR ?

Data : Greenland Halibut in Subareas I and II (1964-2006)Simulation : Age Structured Population Numbers for 100 years (1995 onwards)

Exponential Decay and Catch Equations were used. Average Fishing Mortalities (1964-2006) with variation (C.V.=0.2)

Iterations : 1000

CUSUM

Reference Period : 1980-1989Indicators : CN6,CN11Allowance (k) : 1Reference Limit (h) : 1Action : Triggered with Lower CUSUM LimitHCR : 20% to 50% reduction in Fishing Mortality (Random)

Reference:James, L. J., (2008). M.Sc. Thesis, ‘Use of cumulative sum (CUSUM) control charts of empirical indicators to monitor the status of fisheries in the North-east Atlantic’

Potential Indicator: CN11

IllustrationCUSUM with HCR

CN6r= 0.09310228

CN11r= 0.90395651

IllustrationCUSUM with HCR

CN6r= 0.09310228

CN11r= 0.90395651

Project Outline

TASK 1Define

IndicatorsTASK 2

Find Best Indicators

TASK 3Control Mean

TASK 4Control Limits

TASK 4Allowance

TASK 5Performance Evaluation

TASK 6Evaluate

model HCRs

Single SpeciesSimulation Framework

TASK 7Multiple

Stocks and/orEcosystem

Interactions

To develop a theoretical management framework based on HCR that use SPC methods with indicators from number of stocks to successfully manage model fisheries at the ecosystem level.