Fitting a non-parametric stock-recruitment model in R that is useful for deriving MSY reference points and accounting for model uncertainty

ICES Journal of Marine Science

Volumn 70, Issue 1, 2013, Pages 56-67

  Cadigan, Noel G ^a  

^a MEMORIAL UNIVERSITY OF NEWFOUNDLAND   (Canada)

Author keywords

Beverton Holt model; confidence intervals; hockey stick model; monotone spline; Ricker model

Indexed keywords

BOOTSTRAPPING; CONFIDENCE INTERVAL; DATA SET; FISHERY MODELING; MAXIMUM SUSTAINABLE YIELD; RECRUITMENT (POPULATION DYNAMICS); STOCK ASSESSMENT; UNCERTAINTY ANALYSIS;

EID: 84871206222     PISSN: 10543139     EISSN: 10959289     Source Type: Journal    
DOI: 10.1093/icesjms/fss183     Document Type: Article

References (34)

1. Beverton, R. J. H., and Holt, S. J. 1957. On the Dynamics of Exploited Fish Populations. Chapman and Hall, London. 533
2. Barrowman, N., and Myers, R. A. 2000. Still more spawner-recruit curves: The hockey stick and its generalizations. Canadian Journal of Fisheries and Aquatic Sciences, 57: 665-676
3. Bousquet, N., Duchesne, T., and Rivest, L.-P. 2008. Redefining the maximum sustainable yield for the Schaefer population model including multiplicative environmental noise. Journal of Theoretical Biology, 254: 65-75
4. Bravington, M. V., Stokes, T. K., and O'Brien, C. M. 2000. Sustainable fishing: The bottom line. Marine and Freshwater Research, 51: 465-475
5. Brodziak, J., and Legault, C. M. 2005. Model averaging to estimate rebuilding targets for overfished stocks. Canadian Journal of Fisheries and Aquatic Sciences, 62: 544-562
6. Cadigan, N. G. 2011. Impact of stock-recruit and natural mortality process errors on MSY reference points. DFO Canadian Science Advisary Secretariat Research Document 2012/075. iii+20
7. Cook, R. M. 1998. A sustainability criterion for the exploitation of North Sea cod. ICES Journal of Marine Science, 55: 1061-1070
8. Cleveland,W. S. 1981. LOWESS: A program for smoothing scatterplots by robust locally weighted regression. The American Statistician, 35: 54
9. Duplisea, D., and Fréchet, A. 2010. Precautionary reference point estimates for northern Gulf of St. Lawrence (3Pn4RS) cod (Gadus morhua) and methods for their calculation. DFO Canadian Science Advisary Secretariat Research Document 2009/097 iv+24
10. Duplisea, D., and Fre'chet, A. 2011. Updated reference point estimates for northern Gulf of St. Lawrence (3Pn4RS) cod (Gadus morhua) based on revised beginning of year weights at age. DFO Canadian Science Advisary Secretariat Research Document 2011/ 003 iv+8
11. Efron, B., and Tibshirani, R. J. 1993. An Introduction to the Bootstrap. Chapman-Hall, New York. 456
12. Evans, G. T., and Rice, J. C. 1988. Predicting recruitment from stock size without the mediation of a functional relation. Journal du Conseil International pour l'Exploration de la Mer, 44: 111-122
13. Fronczyk, K., Kottas, A., and Munch, S. 2011. Flexible modeling for stock-recruitment relationships using Bayesian nonparametric mixtures. Environmental and Ecological Statistics, 19: 183-204
14. Hilborn, R., and Stokes, K. 2010. Defining overfished stocks: Have we lost the plot? Fisheries, 35: 113-120
15. Hutchings, J. A., and Rangeley, R. W. 2011. Correlates of recovery for Canadian Atlantic cod (Gadus morhua). Canadian Journal of Zoology, 89: 386-400
16. ICES. 2011. Report of the ICES Advisory Committee, 2011. ICES Advice, 2011. Book 1, 226
17. Jiao, Y., Schneider, D., Chen, Y., and Wroblewski, J. 2004. An analysis of error structure in modeling the stock-recruitment data of gadoid stocks using generalized linear models. Canadian Journal of Fisheries and Aquatic Sciences, 61: 134-146
18. Legović, T., Klanjčšek, J., and Geček, S. 2010. Maximum sustainable yield and species extinction in ecosystems. Ecological Modeling, 221: 1569-1574
19. Mesnil, B., and Rochet, M.-J. 2010. A continuous hockey stick stock- recruit model for estimating MSY reference points. ICES Journal of Marine Science, 67: 1780-1784
20. Michielsens, C. G. J., and McAllister, M. K. 2004. A Bayesian hierarchical analysis of stock-recruitment data: Quantifying structural and parameter uncertainties. Canadian Journal of Fisheries and Aquatic Sciences, 61: 1032-1047
21. Munch, S. B., Kottas, A., and Mangel, M. 2005. Bayesian nonparametric analysis of stock-recruitment relationships. Canadian Journal of Fisheries and Aquatic Sciences, 62: 1808-1821
22. Myers, R., Rosenberg, A., Mace, P., Barrowman, N., and Restrepo, V. 1994. In search of thresholds for recruitment overfishing. ICES Journal of Marine Science, 51: 191-205
23. Needle, C. L. 2002. Recruitment models: Diagnosis and prognosis. Reviews in Fish Biology and Fisheries, 11: 95-111
24. Overholtz,W. J. 1999. Precision and uses of biological reference points calculated from stock recruitment data. North American Journal of Fisheries Management, 19: 643-657
25. Pya, N. 2010. Additive models with shape constraints. PhD thesis. University of Bath, Department of Mathematical Sciences. 195
26. Pya, N. 2012. scam: Shape constrained additivemodels.Rpackage version 1.1-1. http://CRAN.R-project.org/package=scam
27. Quinn, T. J., and Deriso, R. B., 1999. Quantitative Fish Dynamics. Oxford University Press, New York. 560
28. R Development Core Team. 2011. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL http://www.Rproject. org/.
29. Ricker, W. E. 1954. Stock and recruitment. Journal of the Fisheries Research Board of Canada, 11: 559-623
30. Simmonds, E. J., Campbell, A., Skagen, D., Roel, B. A., and Kelly, C. 2011. Development of a stock-recruit model for simulating stock dynamics for uncertain situations: The example of Northeast Atlantic mackerel (Scomber scombrus). ICES Journal of Marine Science, 68: 848-859
31. Sissenwine, M. P., and Shepherd, J. G. 1987. An alternative perspective on recruitment overfishing and biological reference points. Canadian Journal of Fisheries and Aquatic Sciences, 44: 913-918
32. Walters, C. J. 1990. A partial bias correction factor for stock-recruitment parameter estimation in the presence of auto-correlated environmental effects. Canadian Journal of Fisheries and Aquatic Sciences, 47: 516-519
33. Wood, S. N. 2006. Generalized AdditiveModels. An Introduction with R. CRC Press, New York, 416
34. Wood, S. N. 2011. Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models. Journal of the Royal Statistical Society B 73: 3-36