Maximum survival of eggs as the key parameter of stock-recruit meta-analysis: Accounting for parameter and structural uncertainty

Canadian Journal of Fisheries and Aquatic Sciences

Volumn 70, Issue 4, 2013, Pages 527-533

  Pulkkinen, Henni ^a,b   Mäntyniemi, Samu ^b  

^a UNIVERSITY OF OULU   (Finland)

^b UNIVERSITY OF HELSINKI   (Finland)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN ANALYSIS; DATA SET; HIERARCHICAL SYSTEM; LIFE CYCLE; META-ANALYSIS; PARAMETERIZATION; RECRUITMENT (POPULATION DYNAMICS); SALMONID; SURVIVAL; UNCERTAINTY ANALYSIS;

SALMO SALAR;

EID: 84876337454     PISSN: 0706652X     EISSN: 12057533     Source Type: Journal    
DOI: 10.1139/cjfas-2012-0268     Document Type: Article

References (34)

1. Aas, O., Einum, S., Klemetsen A., and Skurdal, J. 2011. Atlantic salmon ecology. Wiley-Blackwell, Oxford.
2. Ackefors, H., Johansson, N., and Wahlberg, B. 1991. The Swedish compensatory programme for salmon in Baltic: an action plan with biological and economic implications. ICES Mar. Sci. Symp. 192: 109-119.
3. Barrowman, N.J., and Myers, R.A. 2000. Still more spawner-recruitment curves: the hockey stick and its generalizations. Can. J. Fish. Aquat. Sci. 57(4): 665-676. doi:10.1139/f99-282.
4. Brännström, Å., and Sumpter, J.D.T. 2005. The role of competition and clustering in population dynamics. Proc. R. Soc. B Biol. Sci. 272: 2065-2072. doi:10. 1098/rspb.2005.3185.
5. Brodziak, J., and Legault, C.M. 2005. Model averaging to estimate rebuilding targets for overfished stocks. Can. J. Fish. Aquat. Sci. 62(3): 544-562. doi:10. 1139/f04-199.
6. Carlin, B.P., and Chib, S. 1995. Bayesian Model Choice via Markov chain Monte Carlo methods. J. Stat. Soc. Ser. B (Methodogical), 57(3): 473-484.
7. Dahlberg, M.D. 1979. A review of survival rates of fish eggs and larvae in relation to impact assessments. Mar. Fish. Rev. 41: 1-12.
8. Dorn, M. 2002. Advice on West Coast Rockfish harvest rates from Bayesian meta-analysis of stock-recruit relationships. N. Am. J. Fish. Manage. 22(1): 280-300. doi:10.1577/1548-8675(2002)022<0280:AOWCRH>2.0.CO;2.
9. Forrest, R.E., McAllister, M.K., Dorn, M.W., Martell, S.J.D., and Stanley, R.D. 2010. Hierarchical Bayesian estimation of recruitment parameters and reference points for Pacific rockfishes (Sebastes spp.) under alternative assumptions about the stock-recruit function. Can. J. Fish. Aquat. Sci. 67(10): 1611-1634. doi:10.1139/F10-077.
10. Gelman, A., Carling, J.B., Stern, H.S., and Rubin, D.B. 2004. Bayesian data analysis. 2nd ed. Chapman & Hall/CRC, Boca Raton.
11. He, X., Mangel, M., and MacCall, A. 2006. A prior for steepness in stock-recruitment relationships, based on an evolutionary persistence principle. Fish. Bull. 104(3): 428-433.
12. Hillary, R.M., Levontin, P., Kuikka, S., Mäntyniemi, S., Mosqueira, I., and Kell, L. 2012. Multi-level stock-recruit analysis: beyond steepness and into model uncertainty. Ecol. Modell. 242: 69-80. doi:10.1016/j.ecolmodel.2012.05.024.
13. Hoeting, J.A., Madigan, D., Raftery, A.E., and Volinsky, C.T. 1999. Bayesian model averaging: a tutorial. Stat. Sci. 14(4): 382-417. doi:10.1214/ss/1009212519.
14. Hyatt, K.D., Mathias, K.L., McQueen, D.J., Mercer, B., Milligan, P., and Rankin, D.P. 2005. Evaluation of hatchery versus wild sockeye salmon fry growth and survival in two British Columbia Lakes. N. Am. J. Fish. Manage. 25(3): 745-762. doi:10.1577/M03-230.1.
15. Kuparinen, A., Mäntyniemi, S., Hutchings, J.A., and Kuikka, S. 2012. Increasing biological realism of fisheries stock assessment: towards hierarchical Bayesian methods. Environ. Rev. 20(2): 135-151. doi:10.1139/a2012-006.
16. Lambert, Y. 2008. Why should we closely monitor fecundity in marine fish populations? J. Northw. Atl. Fish. Sci. 41: 93-106. doi:10.2960/J.v41.m628.
17. Mace, P.M., and Doonan, I.J. 1988. A generalized bioeconomic simulation model for fish population dynamics. N.Z. Fish. Assess. Res. Doc. No. 88/4.
18. Mäntyniemi, S., Kuikka, S., Rahikainen, M., Kell, L.T., and Kaitala, V. 2009. The value of Information in fisheries management: North Sea herring as an example. ICES J. Mar. Sci. 66(10): 2278-2283. doi:10.1093/icesjms/fsp206.
19. Marshall, C.T., O'Brien, L., Tomkiewicz, J., Köster, F.W., Kraus, G., Marteinsdottir, G., Morgan, M.J., Saborido-Rey, F., Blanchard, J.L., Secor, D.H., Wright, P.J., Mukhina, N.V., and Björnsson, H. 2003. Developing alternative indices of reproductive potential for use in fisheries management: case studies for stocks spanning an information gradient. J. Northw. Atl. Fish. Sci. 33: 161-190. doi: 10.2960/J.v33.a8.
20. Michielsens, C.G.J., and McAllister, M.K. 2004. A Bayesian hierarchical analysis of stock-recruit data: quantifying structural and parameter uncertainties. Can. J. Fish. Aquat. Sci. 61(6): 1032-1047. doi:10.1139/f04-048.
21. Michielsens, C.G.J., Mäntyniemi, S., and Vuorinen, P.J. 2006. Estimation of annual mortality rates caused by early mortality syndromes (EMS) and their impact on salmonid stock recruit relationships. Can. J. Fish. Aquat. Sci. 63(9): 1968-1981. doi:10.1139/f06-095.
22. Minto, C., Myers, R.A., and Blanchard, W. 2008. Survival variability and population density in fish populations. Nature, 452(20): 344-348. doi:10.1038/ nature06605. PMID:18354480.
23. Mueter, F.J., Peterman, R.M., and Pyper, B.J. 2002. Opposite effects of ocean temperature on survival rates of 120 stocks of Pacific salmon (Oncorhynchus spp.) in northern and southern areas. Can. J. Fish. Aquat. Sci. 59(3): 456-463. doi:10.1139/f02-020.
24. Munch, S.B., Kottas, A., and Mangel, M. 2005. Bayesian nonparametric analysis of stock-recruitment relationships. Can. J. Fish. Aquat. Sci. 62(8): 1808-1821. doi:10.1139/f05-073.
25. Myers, R.A., Bowen, K.G., and Barrowman, N.J. 1999. Maximum reproductive rate of fish at low population sizes. Can. J. Fish. Aquat. Sci. 56(12): 2404-2419. doi:10.1139/f99-201.
26. Nash, R.D.M., and Geffen, A.J. 2012. Mortality through the early life-history of fish: What can we learn from European plaice (Pleuronectes platessa L.)? J. Mar. Syst. 93: 58-68. doi:10.1016/j.jmarsys.2011.09.009.
27. Plummer, M. 2003. JAGS: a program for analysis of Bayesian graphical models using Gibbs sampling. In Proceedings of the 3rd International Workshop on Distributed Statistical Computing (DSC 2003), 20-22 March, Vienna, Austria. ISSN 1609-395X.
28. Prevost, E., Parent, E., Crozier, W., Davison, I., Dumas, J., Gudbergsson, G., Hindar, K., McGinnity, P., MacLean, J., and Saettem, L.A. 2003. Setting biological reference points for Atlantic salmon stocks: transfer of information from data-rich to sparse-data situations by Bayesian hierarchical modelling. ICES J. Mar. Sci. 60(6): 1177-1193. doi:10.1016/j.icesjms.2003.08.001.
29. Pulkkinen, H., Mäntyniemi, S., Kuikka, S., and Levontin, P. 2011. More knowledge with the same amount of data: advantage of accounting for parameter correlations in hierarchical meta-analyses. Mar. Ecol. Prog. Ser. 433: 29-37.
30. Quinn, T.J., and Deriso, R. 1999. Quantitative fish dynamics. Oxford University Press, New York.
31. Raftery, A.E., Newton, M.A., Satagopan, J.M., and Krivitsky, P.V. 2007. Estimating the integrated likelihood via posterior simulation using the harmonic mean identity. Bayesian Statistics, 8: 1-45.
32. Romakkaniemi, A. 2008. Conservation of Atlantic salmon by supplementary stocking of juvenile fish. Academic dissertation, Department of Biological and Environmental Sciences, University of Helsinki and Finnish Game and Fisheries Research Institute.
33. Su, Z., Peterman, R.M., and Haeseker, S.L. 2004. Spatial hierarchical Bayesian models for stock-recruitment analysis of pink salmon (Oncorhynchus gorbuscha). Can. J. Fish. Aquat. Sci. 61(12): 2471-2486. doi:10.1139/f04-168.
34. Uusitalo, L., Kuikka, S., and Romakkaniemi, A. 2005. Estimation of Atlantic salmon smolt carrying capacity of rivers using expert knowledge. ICES J. Mar. Sci. 62: 708-722. doi:10.1016/j.icesjms.2005.02.005.zzz.