How reliable are the abundance indices derived from commercial catch-effort standardization?

Canadian Journal of Fisheries and Aquatic Sciences

Volumn 66, Issue 7, 2009, Pages 1169-1178

  Ye, Yimin ^a,b   Dennis, Darren ^b  

^a FOOD AND AGRICULTURE ORGANIZATION OF THE UNITED NATIONS   (Italy)

^b CSIRO   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

ABUNDANCE ESTIMATION; CATCH PER UNIT EFFORT; COMMERCIAL ACTIVITY; DATA SET; ERROR ANALYSIS; FOOD ORGANISM; LOBSTER; STANDARDIZATION; STOCK ASSESSMENT;

AUSTRALASIA; AUSTRALIA;

PANULIRUS ORNATUS;

EID: 70349490446     PISSN: 0706652X     EISSN: None     Source Type: Journal    
DOI: 10.1139/F09-070     Document Type: Article

References (33)

1. Anderson, O.F. 2003. CPUE analysis and stock assessment of the Eats Cape Hills (ORD2A) orange roughy fishery for 2003. N.Z. Fish. Assoc. Rep. No. 2003/34.
2. Bannerot, S.P., and Austin, C.B. 1983. Using frequency distributions of catch per unit effort to measure fish-stock abundance. Trans. Am. Fish. Soc. 112(5): 608-617. doi:10.1577/1548-8659(1983)112<608:UFDOCP>2.0.CO;2.
3. Baranov, F.I. 1918. On the equation of the biological basis of fisheries. Nauchn. Issled. Ikhtiologicheskii Ist. Izv. 1: 81-128.
4. Battaile, B.C., and Quinn, T.J., II. 2004. Catch per unit effort standardization of the eastern Bering Sea walleye pollock (Theragra chalcogramma) fleet. Fish. Res. 70: 161-177. doi:10.1016/j.fishres.2004.08.029.
5. Beverton, R.J.H., and Holt, S.J. 1957. On the dynamics of exploited fish populations. Fishery Investigations Series II. No. XIX. Ministry of Agriculture, Fisheries and Food, London, UK.
6. Bishop, J., Venables, W.N., and Wang, Y. 2004. Analysing commercial catch and effort data from a Penaeid trawl fishery: a comparison of linear models, mixed models and generalized estimating equations approaches. Fish. Res. 70(2-3): 179-193. doi:10.1016/j.fishres.2004.08.003.
7. Bishop, J., Venables, W.N., Dichmont, C.M., and Sterling, D.J. 2008. Standardizing catch rates: is logbook information by itself enough? ICES J. Mar. Sci. 65(2): 255-266. doi:10.1093/icesjms/ fsm179.
8. Campbell, R.A. 2004. CPUE standardization and the construction of indices of stock abundance in a spatially varying fishery using general linear models. Fish. Res. 70(2-3): 209-227. doi:10.1016/j.fishres.2004.08.026.
9. Chen, C., Chock, D.P., and Winkler, S.L. 1999. A simulation study of confounding in generalized linear models for air pollution epidemiology. Environ. Health Perspect. 107(3): 217-222. doi:10.2307/3434512. PMID:10064552.
10. Cochran, W.G. 1977. Sampling techniques. 3rd ed. Wiley, New York.
11. Cooke, J.G., and Beddington, J.R. 1984. The relationship between catch rates and abundance in fisheries. IMA J. Math. Appl. Med. Biol. 1(4): 391-405. doi:10.1093/imammb/1.4.391.
12. Davison, A.C., and Hinkley, D.V. 1997. Bootstrap methods and their application. Cambridge University Press, Cambridge, UK.
13. Fox, J. 2002. An R and S-PLUS companion to applied regression. Sage Publications, New York.
14. Ghosh, S., Pahwa, P., and Rennie, D.C. 2008. A comparison between the design-based and model-based approaches using longitudinal survey data. Model Assist. Stat. Appl. 3: 177-185.
15. Gulland, J.A. 1956. On the fishing effort in English demersal trawl fisheries. Fishery Investigations Series II. Vol. XX. Ministry of Agriculture, Fisheries and Food, London, UK.
16. Harley, S.J., Myers, R.A., and Dunn, A. 2001. Is catch-per-unit-effort proportional to abundance? Can. J. Fish. Aquat. Sci. 58(9): 1760-1772. doi:10.1139/cjfas-58-9-1760.
17. Kimura, D.K. 1981. Standardized measures of relative abundance based on modelling log(c.p.u.e), and their application to Pacific ocean perch (Sebastes alutus). J. Cons. Int. Explor. Mer. 39: 211-218.
18. Large, P.A. 1992. Use of a multiplicative model to estimate relative abundance from commercial CPUE data. ICES J. Mar. Sci. 49(3): 253-261. doi:10.1093/icesjms/49.3.253.
19. Maunder, M.N., and Punt, A.E. 2004. Standardizing catch and effort data: a review of recent approaches. Fish. Res. 70(2-3): 141-159. doi:10.1016/j.fishres.2004.08.002.
20. National Research Council. 2000. Improving the collection, management and use of marine fisheries data. National Academy Press, Washington, D.C.
21. Price, J.D., and Hilborn, R. 1998. Concentration profiles and invertebrate fisheries management. In Proceedings of the North Pacific Symposium on Invertebrate Stock Assessment and Management, 6-10 March 1995, Nanaimo, British Columbia. Edited by G.S. Jamieson and A. Campbell. Can. Spec. Publ. Fish. Aquat. Sci. pp. 187-196.
22. Punt, A.E., Walker, T.I., Taylor, B.L., and Pribac, F. 2000. Standardization of catch and effort data in a spatially-structured shark fishery. Fish. Res. 45(2): 129-145. doi:10.1016/S0165-7836(99)00106-X.
23. Quinn, T.J., II, and Deriso, R.B. 1999. Quantitative fish dynamics. Oxford University Press, Oxford, UK.
24. Quinn, G.P., and Keough, M.J. 2002. Experimental design and data analysis for biologists. Cambridge University Press, Cambridge, UK.
25. Richards, L.J., and Schnute, J.T. 1986. An experimental and statistical approach to the question: is CPUE an index of abundance? Can. J. Fish. Aquat. Sci. 43(6): 1214-1227. doi:10.1139/f86-151.
26. Rose, G.A., and Kulka, D.W. 1999. Hyperaggregation of fish and fisheries: how catch-per-unit-effort increased as the northern cod (Gadus morhua) declined. Can. J. Fish. Aquat. Sci. 56(Suppl. 1): 118-127. doi:10.1139/cjfas-56-S1-118.
27. Spiegelhalter, D., Thomas, A., Best, N., and Lunn, D. 2003. Win-BUGS user manual. MRC Biostatistics Unit, Cambridge, UK.
28. Stevens, D.L., Jr. 2006. Spatial properties of design-based versus model-based approaches to environmental sampling. In Proceedings of the 7th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, 5-7 July 2006, Lisbon, Portugal. Edited by M. Caetano and M. Painho. Instituto Geográfico Português, Lisbon, Portugal. pp. 119-125.
29. Van der Meer, J. 1997. Sampling design of monitoring programmes for marine benthos: a comparison between the use of fixed versus randomly selected stations. J. Sea Res. 37(1-2): 167-179. doi:10.1016/S1385-1101(97)00007-5.
30. Xiao, Y., Punt, A.E., Millar, R.B., and Quinn, T.J., II. (Editors). 2004. Models in fisheries research: GLMs, GAMS and GLMMs. Fish. Res. 70(2-3): 137-139. doi:10.1016/j.fishres.2004.08.001.
31. Yamada, H., Takagi, N., and Nishimura, D. 2006. Recruitment abundance index of Pacific bluefin tuna using fisheries data on juveniles. Fish. Sci. 72(2): 333-341. doi:10.1111/j.1444-2906.2006.01154.x.
32. Ye, Y., Pitcher, R., Dennis, D., and Skewes, T. 2005. Constructing abundance indices from scientific surveys of different designs for the Torres Strait ornate rock lobster (Panulirus ornatus) fishery, Australia. Fish. Res. 73: 187-200. doi:10.1016/j.fishres. 2004.12.010.
33. Ye, Y., Dennis, D., Skewes, T., Polon, P., Pantus, F., Brewer, D., Haywood, M., McLeod, I., Wassenberg, T., Pillans, P., Chetwynd, D., and Sheils, J. 2007. 2006 relative abundance and preseason surveys, assessment of the Torres Strait lobster fishery and TAC estimation. CSIRO, Brisbane, Australia. Final Rep. Proj. No. AFMA 2006/817, 2006/827.