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Calibrating virtual population analysis for fisheries stock assessment

Published online by Cambridge University Press:  11 June 2008

Yong Chen ,
Yan Jiao ,
Chi-Lu Sun  and
Xinjun Chen
Yong Chen
Affiliation:
School of Marine Sciences, University of Maine, Orono, Maine 04469, USA The Key Laboratory of Shanghai Education Commission for Oceanic Fisheries Resources Exploitation, Shanghai Fisheries University, Shanghai 200090, China
Yan Jiao
Affiliation:
Department of Fisheries and Wildlife Sciences, Virginia Tech Blacksburg, VA 24061, USA
Chi-Lu Sun
Affiliation:
Institute of Oceanography, National Taiwan University, 1 Section 4 Roosevelt Road, Taipei, Taiwan 10617, China
Xinjun Chen
Affiliation:
The Key Laboratory of Shanghai Education Commission for Oceanic Fisheries Resources Exploitation, Shanghai Fisheries University, Shanghai 200090, China
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Abstract

Virtual population analysis (VPA) is often used for assessing freshwater and marine fisheries resources. One important component in VPA is to calibrate abundance estimates with a time series of abundance indices. One of the commonly used calibration processes usually includes simultaneous estimation of cohort sizes across all ages and years. This reduces the flexibility of the model in accounting for age- and year-effects, in particular in the presence of an age-specific curvilinear relationship between abundance index and stock abundance. In this study, we compared this simultaneous method tuning approach with a stepwise approach which calibrates abundance age by age in tuning VPA. The simulation study suggests that the stepwise procedure tends to perform better with no obvious retrospective errors in the estimated stock biomass compared with the simultaneous method which tends to have large positive retrospective errors. In applying the stepwise procedure and simultaneous method to a cod fishery data set, we found large differences in the stock sizes estimated for the most recent year using these two methods, with the current stock size estimated using the stepwise method being substantially smaller than that estimated with the simultaneous method. Considering the likelihood of the presence of curvilinear relationship between abundance index and stock abundance, we conclude that the stepwise method yields more reliable results, and is less risk-prone in using VPA for fisheries stock assessment.

Keywords

Virtual population analysis (VPA)CalibrationStepwise procedureRetrospective problemStock assessment, and simulation
Type
Research Article
Information
Aquatic Living Resources , Volume 21 , Issue 2 , April 2008 , pp. 89 - 97
Copyright
© EDP Sciences, IFREMER, IRD, 2008

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References

Chatfield C., 2003, The analysis of time series, an introduction. 6th edn. London, Chapman & Hall/ CRC Press.
Crecco, V.A., Savoks, T.F., 1985, Density-dependent catchability and its potential causes and consequences on Connecticut River American shad, Alosa sapidissima. Can. J. Fish. Aquat. Sci. 42, 1649–1657. CrossRef
Darby C.D., Flatman S., 1994, Virtual population analysis: version 3.1 (Windows/DOS) user guide. MAFF Inform. Technol., 85 p.
De Valpine, P., 2002, Review of methods for fitting time-series models with process and observation errors and likelihood calculations for nonlinear, non-Gaussian state-space models. Bull. Mar. Sci. 70, 455–471.
Gascon D., 1988, Catch projections. In: Rivard D. (Ed.), Collected papers on stock assessment methods. CAFSAC Res. Doc 88/61.
Gavaris, S., 1988, An adaptive frame work for the estimation of population size. CAFSAC Res. Doc. 88/29
Gavaris, S., 1993, Analytical estimates of reliability for the projected yield from commercial fisheries. In: Smith S.J., Hunt J.J., Rivard D. (Eds.) Risk evaluation and biological reference points for fisheries management. Can. Spec. Publ. Fish. Aquat. Sci. 120, 185–192.
Harley, S.J., Myers, R.A., Dunn, A., 2001, Is catch-per-unit-effort proportional to abundance? Can. J. Fish. Aquat. Sci. 58, 1760–1772. CrossRef
Hilborn, R., 1985, Simplified calculation of optimum spawning stock size from Ricker's stock recruitment curve. Can. J. Fish. Aquat. Sci. 42, 1833–1834. CrossRef
Hilborn R., Walters C., 1992, Quantitative fisheries stock assessment: choice, dynamics and uncertainty. New York, Chapman and Hall.
Hilborn, R., Peterman, R.M., 1996, The development of scientific advice with incomplete information in the context of the precautionary approach. FAO Fish. Techn. Pap. 350, 2, pp. 77–101.
ICES, 1991, Report of the working group on methods of fish stock assessment. St.John's NF, ICES CM 1991/Assessment 25.
Megrey, B.A., 1989, Review and comparison of age-structured stock assessment models from theoretical and applied points of view. Am. Fish. Soc. Symp. 6, 8–48.
Mohn, R.K., 1993, Bootstrap estimates of ADAPT parameters, their projection in risk analysis and their retrospective patterns. In: Smith S.J., Hunt J.J., Rivard D. (Eds.) Risk evaluation and biological reference points for fisheries management. Can. Spec. Publ. Fish. Aquat. Sci. 120, 173–184.
Mohn, R., 1999, The retrospective problem in sequential population analysis: An investigation using cod fishery and simulated data. ICES J. Mar. Sci. 56, 473–488. CrossRef
Myers, R.A., Hutchings, J.A., Barrowman, N.J., 1997, Why do fish stocks collapse? The example of cod in Atlantic Canada. Ecol. Appl. 7, 91–106. CrossRef
National Research Council (NRC), 1998, Improving Fish Stock Assessment. The National Academy Press, Washington, DC.
Paloheimo, J.E., 1980, Estimating mortality rates in fish populations. Trans. Am. Fish. Soc. 109, 378–386. 2.0.CO;2>CrossRef
Paloheimo, J.E., Dickie, L.M., 1964, Abundance and fishing success. Rapp. P.-V. Réun. Cons. Int. Explor. Mer 155, 152–163.
Parma A.N., 1993, Retrospective catch-at-age analysis of pacific halibut: implications on assessment of harvesting policies. In: Kruse G., Eggers D.M., Pautzke C., Marasco R.J., Quinn II T.J. (Eds.). Proc. Int. Symp. Management Strategies for Exploited Fish Populations. Alaska Sea Grant College Program, pp. 287–265.
Parzen E., 1960, Modern probability theory and its application. John Wiley and Sons, New York.
Patterson, K.R., Kirkwood, G.P., 1995, Comparative performance of ADAPT and Laurec-Shepherd methods for estimating fish population parameters and in stock management. ICES J. Mar. Sci. 52, 183–196. CrossRef
Pope, J.G., 1972, An investigation of the accuracy of Virtual Population Analysis using cohort analysis. Res. Bull. ICNAF 9, 65–74.
Quinn T.J., Deriso R.B., 1999, Quantitative fish dynamics. Oxford University Press, Inc. New York.
Rajakauna, H., Chen, Y., Snelgrove, P., 2005, Is retrospective error a “true error”? Mathematical basis of adaptive framework for virtual population analysis. Math. Phys. Fish. Sci. 3, 36–64.
Rivard, D., Foy, M.G., 1987, An analysis of errors in catch projections for Canadian Atlantic fish stocks. Can. J. Fish. Aquat. Sci. 44, 967–981. CrossRef
Salthang, A., Anes, S., 2003, Catchability and the spatial distribution of fishing vessels. Can. J. Fish. Aquat. Sci. 60, 259–268. CrossRef
Secor, D.H., 2007, The year-class phenomenon and the storage effect in marine fishes. J. Sea Res. 57, 91–103. CrossRef
Shelton P.A., Stansbury D.E., Murphy G.R., Lilly G.R., Brattey J., 1996, An assessment of the cod stock in NAFO divisions 2J+3KL. NAFO SCR Doc. 90/96.
Shepherd, J.G., 1999, Extended survivors analysis: an improved method for the analysis of catch-at-age data and abundance indices. ICES J. Mar. Sci. 56, 584–591. CrossRef
Sinclair A., Gascon D., O'Boyle R., Rivard D., Gavaris S., 1990, Consistency of some northwest Atlantic ground fish stock assessments. NAFO SCR Doc. 90/96.
Smith, S.J., Gavaris, S., 1993, Evaluation the accuracy of projected catch estimates from sequential population analysis and trawl survey abundance estimates. In: Smith S.J., Hunt J.J., Rivard D. (Eds.) Risk evaluation and biological reference points for fisheries management, Can. Spec. Publ. Fish. Aquat. Sci. 120, 163–172.
Swain, D.P., Sinclair, A.F., 1994, Fish distribution and catchability: what is the appropriate measure of distribution? Can. J. Fish. Aquat. Sci. 51, 1046–1054. CrossRef
Walters, C., Maguire, J., 1996, Lessons for stock assessment from the northern cod collapse. Rev. Fish Biol. Fish. 6, 125–137.
Xiao Y. 2007, The fundamental equations of multi-species virtual population analysis and its variants. Ecol. Model. 201, 477–494.
Xiao, Y., Wang, Y.G., 2007, A revisit to Pope's cohort analysis. Fish. Res. 86, 153–158. CrossRef