Fraser River Sockeye Fisheries and Fisheries Management - Cohen ...

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the general ups and downs of the observed return values; thus reliability can beindependent of accuracy and precision as long as, on average, large forecasts are met bylarge returns and relatively small forecasts are met by relatively small returns. Unreliableforecasts for the period 1980 to 2009 are those where there is no significant relationshipbetween the size of the forecast and the size of the return. If the forecast is deemedreliable we can move forward with regression analysis and MAPE to describe forecastingprecision and accuracy.Precision: Regression estimates precision by the dispersion of data points around theregression line; in other words, the amount of variation in returns correlated by forecasts(R 2 ). For example, an R 2 value of 90% tells us that 90% of the year-to-year difference inreturns is correlated with forecasts. Importantly, R 2 values are independent of locationshifts. For example, forecasts may consistently over-estimate returns by 1 million fish,giving the forecaster high precision even if accuracy is low. Note: changes in R 2 can alsosignal changes in accuracy, when the regression slope departs from 1.Accuracy: Regression estimates accuracy by the combination of intercept and slope ofthe regression line. A perfect forecast to return regression will have high accuracy (i.e., aslope of 1, intercept of zero) and high precision (i.e., all points would cluster closely tothe regression line making R 2 close to 100%). A management group with highly accurateforecasts will therefore have a slope close to 1 (i.e., each 1000-fish increase in forecast ismatched by a 1000-fish increase in return) and an elevation close to zero (i.e., interceptnot statistically different from 0). If the regression slope is statistically significant butdeparts from 1, then accuracy will change as a function of forecast size (e.g., whenobserved returns are 50% different from forecasts across all levels of forecast, theregression slope will depart from 1). Accuracy also diminishes as regression elevationsdepart from 0; positive elevations reflect forecasts that have under-estimated the returnwhereas negative elevations reflect forecasts having over-estimated returns. If twomanagement groups have similar regression slopes and elevations, that with the highestR 2 value or lowest MAPE will be the one with the most accurate forecasts.Is statistical, biological, and social significance the same?Not always. Statistical significance is an inference based on the magnitude of thedifference in question relative to the noise in the data; biological significance refers to thefunctional relationship between organisms and their environment; social significanceincorporates economic and cultural ramifications. We often calculate statisticalsignificance by comparing the variance in data for a sub-group to total variance in theentire group. For example, a loss of a million fish may not be statistically significantF-4
elative to annual variations on the order of millions, or biologically significant in that itwill substantially alter future recruits per spawner, yet losing one million fish will likelycreate economic and cultural issues. For the purpose of this section, the term“significant” refers only to a statistical significance.F-5
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Fraser River Sockeye Fisheriesand F
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EXECUTIVE SUMMARY1. Catch Monitorin
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implement harvest rate ceilings to
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Table of ContentsEXECUTIVE SUMMARY
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List of TablesTable 1 Annual estima
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List of FiguresFigure 1 Fraser sock
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Figure 21 Estimates of total catch,
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List of AppendicesAppendix A Statem
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used to (1) estimate catch for each
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FISHERIES HARVESTINGOverview of Fis
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Figure 1 Fraser sockeye marine migr
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Table 2 Summary of available inform
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Table 3 provides the annual estimat
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Table 4 Summary of available inform
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season update teleconference meetin
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Catch Estimation MethodsThe procedu
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catch estimates was detected using
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of precision. The overall rating fo
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1998-00 - No agreements with Sto:lo
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initiation of the AFS Agreements in
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Table 12 Comparison of annual socke
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Table 13 Annual estimates of the ha
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Canadian Commercial FisheriesThe pr
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logbook systems. In addition to the
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Table 15 Fraser River sockeye salmo
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Available catch estimates for the r
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Table 17 Summary of available infor
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anged from less than 100 to over 30
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Washington State Recreational Fishe
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equirements have been applied to se
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salmon were biopsied or tagged with
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Stellako-Late Stuart and 531 Adams)
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FISHERIES MANAGEMENTOverview of Pre
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parents of the recruits). Effective
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within the confidence limits. For e
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Ratio of Return to Forecast5.04.03.
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Ratio of Return to Forecast5.04.03.
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Table 20 Pre-season forecast models
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different from the straight line),
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Prediction ability of ForecastsProp
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Stock MAPEReturn Explainedby Foreca
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test fisheries are analyzed in-seas
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Inputs to the cumulative-normal mod
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eginning of the runs, but by mid-ru
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Median Absolute Percent Error (1997
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variety of hydroacoustic techniques
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enefited from improved technologies
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Post-season estimates of Escapement
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precision achieved was considerably
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m 3 /sec during the sockeye run. Fi
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Escapement TargetsOur evaluations r
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20% of the average of the 4-year se
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Table 24 Low escapement benchmarks
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Table 25 Comparison of post-season
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fisheries have been permitted to ta
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sub-dominant cycle years (e.g., 200
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SummaryLow Escapement Benchmarks (L
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Extent of OverharvestingThe estimat
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2,000,0001,800,000Early StuartCatch
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Cultus Lake Sockeye Recovery Effort
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Figure 23 Number of adult sockeye e
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Recovery ObjectivesIn anticipation
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2008 the escapement estimate was 34
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BRISTOL BAY, ALASKA SOCKEYE FISHERY
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accurate, precise, and timely, (2)
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The Bay is subjected to large tidal
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activity (Bocking and Peterman 1988
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% of total run45%40%35%30%25%20%15%
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Harvest estimation methodsTotal har
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Millions of sockeyeYearFigure 27 Hi
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management structure complements th
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1.5Togiak4.03.5NushagakMillions of
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Millions of sockeye7.06.05.04.03.02
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logical given the dynamics of the r
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1.61.4Number of fish (millions)1.21
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Pre-season forecastsAs noted above,
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8.0y = 0.79x + 1.59R² = 0.417.8Log
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12010080MAPE60402001971-1980 1981-1
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Median percent error (MPE)3020100-1
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Table 28 Average age composition of
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dampeners to reduce surface turbule
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current year’s run is accounted f
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and 1999 Revised Annexes. This inte
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Bristol Bay was in 1997 when there
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upon by managers to determine when
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STATE OF THE SCIENCECatch Monitorin
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2006) due to concerns regarding the
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RECOMMENDATIONS1. DFO needs to ensu
Page 178 and 179: LITERATURE CITEDAdkison, M.D. and R
Page 180 and 181: Beacham, T.D., M. Lapointe, J.R. Ca
Page 182 and 183: CSAS. 2007 Pre-season run size fore
Page 184 and 185: Evans, D.G., J.B. Browning and B.G.
Page 186 and 187: Hardie, D.C., D.A. Nagtegaal, K. He
Page 188 and 189: Pacific Salmon Commission. 1998. Re
Page 190 and 191: Robichaud, D., J.J. Smith, K. K. En
Page 192 and 193: Valderrama, D. and J.L. Anderson. 2
Page 194 and 195: Appendix A Statement of Work.Cohen
Page 196 and 197: All sectors3.7 The Contractor will
Page 198 and 199: “State of the Science”. Comment
Page 200 and 201: 3.3 The Contractor will review and
Page 202 and 203: Appendix BList of requests to DFO b
Page 204 and 205: DFO Request 15: Recent CSAS documen
Page 206 and 207: Item Description DateRequestedReque
Page 208 and 209: Appendix CFirst Nation catch monito
Page 210 and 211: Table C-1 Summary of information re
Page 212 and 213: Table C-2 Weekly catch monitoring e
Page 214 and 215: Table D-1 Summary of information re
Page 216 and 217: community of Port Renfrew. The area
Page 218 and 219: IPrecision ( + % of the estimate)10
Page 220 and 221: Table E-2 Annual Strait of Georgia
Page 222 and 223: Table E-4 Annual Johnstone Strait e
Page 224 and 225: Table E-6 Lower Fraser River recrea
Page 226 and 227: 0 would mean that the forecast does
Page 230 and 231: Appendix G Graphical representation
Page 232 and 233: Early Stuart Timing GroupEarly Stua
Page 234 and 235: Summer-run Timing GroupSummer run7.
Page 236 and 237: Fraser River Indicator Stocks (list
Page 254 and 255: Appendix H Pre-season forecast: sum
Page 256 and 257: ManagementGroup(IndicatorStock)MAPE
Page 258 and 259: ManagementGroup(IndicatorStock)MAPE
Page 260 and 261: Appendix I Methods of In-season Sto
Page 262 and 263: Marine Gillnet Test FisheriesThe gi
Page 264 and 265: Expansion line (x1000)9080706050403
Page 266 and 267: Table I-2 Mean values for purse sei
Page 268 and 269: Figure I-5 Map of test fishing loca
Page 270 and 271: Appendix J The Hydroacoustics progr
Page 272 and 273: An SEF project was secured in 2007
Page 274 and 275: Conservation action Comments Partne
Page 276 and 277: Table K-2 Summary of actions to rec
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Table L-1 Catch and escapement of s
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Table L-3 Performance criteria of p
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Ratio of annual return to the avera
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Appendix M Reviewer comments on the
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Request #5: Sockeye allocations by
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utility of pre-season forecasts. Pr
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3. Are there additional quantitativ
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made via tagging and experimentatio
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Page 60: The authors make extensive
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ensure the reader does not assume t
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The reported excerpts from Bradford
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(budgets, legal issues, pseudo-cons
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REVIEW 3/3Reviewer Name: Dr Sean Co
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season forecasts that eventually co
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allocation shows "No agreement", an
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size.Figures showing errors for pre
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Goals can easily generate confusion
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Total rows from all these tables be
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Exploitation Rate100%90%80%70%60%50
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Exploitation RateEarly Stuart90%80%
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