ss3sim: An R package for fisheries stock assessment simulation with stock synthesis

PLoS ONE

Volumn 9, Issue 4, 2014, Pages

  Anderson, Sean C ^a   Monnahan, Cole C ^b   Johnson, Kelli F ^b   Ono, Kotaro ^b   Valero, Juan L ^c  

^a SIMON FRASER UNIVERSITY   (Canada)

^b UNIVERSITY OF WASHINGTON   (United States)

^c Center for the Advancement of Population Assessment Methodology (CAPAM)   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AGRICULTURAL PROCEDURES; ARTICLE; COMPUTER PROGRAM; CONTROLLED STUDY; FISH STOCK; FISHERY; POPULATION DYNAMICS; REPRODUCIBILITY; SAMPLING; SIMULATION; STOCK ASSESSMENT; STOCK SYNTHESIS; VALIDATION PROCESS; ANIMAL; COMPUTER SIMULATION; FISH; THEORETICAL MODEL;

ANIMALS; COMPUTER SIMULATION; FISHERIES; FISHES; MODELS, THEORETICAL; SOFTWARE;

EID: 84899051327     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0092725     Document Type: Article

References (44)

1. Gulland JA (1983) Fish Stock Assessment: A Manual of Basic Methods. New York: Wiley. 223 p.
2. Hilborn RW, Walters C (1992) Quantitative Fisheries Stock Assessment: Choice, Dynamics, and Uncertainty. New York: Chapman and Hall. 570 p.
3. Hilborn R, Walters CJ (1987) A general model for simulation of stock and fleet dynamics in spatially heterogeneous fisheries. Can J Fish Aquat Sci 44: 1366-1369.
4. Rosenberg AA, Restrepo VR (1994) Uncertainty and risk evaluation in stock assessment advice for U.S. marine fisheries. Can J Fish Aquat Sci 51: 2715-2720. (Pubitemid 26447532)
5. Peterman RM (2004) Possible solutions to some challenges facing fisheries scientists and managers. ICES J Mar Sci 61: 1331-1343.
6. Deroba JJ, Butterworth DS, Methot RD, De Oliveira JAA, Fernandez C, et al. (2014) Simulation testing the robustness of stock assessment models to error: some results from the ICES strategic initiative on stock assessment methods. ICES J Mar Sci. In press. doi:10.1093/icesjms/fst237
7. Lee HH, Maunder MN, Piner KR, Methot RD (2011) Estimating natural mortality within a fisheries stock assessment model: An evaluation using simulation analysis based on twelve stock assessments. Fish Res 109: 89-94.
8. Jiao Y, Smith EP, O'Reilly R, Orth DJ (2012) Modelling non-stationary natural mortality in catch-at-age models. ICES J Mar Sci 69: 105-118.
9. Deroba JJ, Schueller AM (2013) Performance of stock assessments with misspecified age- and time-varying natural mortality. Fish Res 146: 27-40.
10. Johnson KF, Monnahan CC, McGilliard CR, Vert-pre KA, Anderson SC, et al. (2014) Time-varying natural mortality in fisheries stock assessment models: Identifying a default approach. ICES J Mar Sci. In press. doi:10.1093/icesjms/ fsu055
11. Lee HH, Maunder MN, Piner KR, Methot RD (2012) Can steepness of the stock-recruitment relationship be estimated in fishery stock assessment models? Fish Res 125-126: 254-261.
12. Schirripa MJ, Goodyear CP, Methot RM (2009) Testing different methods of incorporating climate data into the assessment of US West Coast sablefish. ICES J Mar Sci 66: 1605-1613.
13. Magnusson A, Hilborn R (2007) What makes fisheries data informative? Fish Fish 8: 337-358. (Pubitemid 350125488)
14. Wetzel CR, Punt AE (2011) Performance of a fisheries catch-at-age model (Stock Synthesis) in data-limited situations. Mar Freshwater Res 62: 927-936.
15. Ono K, Licandeo R, Muradian ML, Cunningham CJ, Anderson SC, et al. (2014) The importance of length and age composition data in statistical age-structured models for marine species. ICES J Mar Sci. In press. doi: 10.1093/icesjms/ fsu007
16. Yin Y, Sampson DB (2004) Bias and precision of estimates from an age-structured stock assessment program in relation to stock and data characteristics. N Am J Fish Manage 24: 865-879. (Pubitemid 39116005)
17. Methot RD Jr, Wetzel CR (2013) Stock Synthesis: A biological and statistical framework for fish stock assessment and fishery management. Fish Res 142: 86-99.
18. Maunder MN, Punt AE (2013) A review of integrated analysis in fisheries stock assessment. Fish Res 142: 61-74.
19. Cope JM (2013) Implementing a statistical catch-at-age model (Stock Synthesis) as a tool for deriving overfishing limits in data-limited situations. Fish Res 142: 3-14.
20. Haltuch MA, Ono K, Valero JL (2013) Status of the U.S. petrale sole resource in 2012. Technical report, Pacific Fishery Management Council.
21. Helu SL, Sampson DB, Yin Y (2000) Application of statistical model selection criteria to the Stock Synthesis assessment program. Can J Fish Aquat Sci 57: 1784-1793.
22. Crone PR, Valero JL (In review) Evaluation of length vs. age selectivity in stock assessments based on management criteria: It matters when fitting to length-composition data.
23. Hurtado-Ferro F, Punt AE, Hill KT (2013) Use of multiple selectivity patterns as a proxy for spatial structure. Fish Res. In press. doi:10.1016/j.fishres.2013.10.001
24. Wilberg MJ, Bence JR (2006) Performance of time-varying catchability estimators in statistical catch-at-age analysis. Can J Fish Aquat Sci 63: 2275-2285. (Pubitemid 44812808)
25. R Core Team (2013) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.
26. Taylor I, Stewart I, Hicks A, Garrison T, Punt A, et al. (2013) r4ss: R code for Stock Synthesis. R package version 1.20.
27. Fournier DA, Skaug HJ, Ancheta J, Ianelli J, Magnusson A, et al. (2012) AD Model Builder: Using automatic differentiation for statistical inference of highly parameterized complex nonlinear models. Optim Methods & Soft 27: 233-249.
28. Bolker BM, Gardner B, Maunder M, Berg CW, Brooks M, et al. (2013) Strategies for fitting nonlinear ecological models in R, AD Model Builder, and BUGS. Methods Ecol Evol 4: 501-512.
29. Hill KT, Crone PR, Lo NCH, Demer DA, Zwolinski JP, et al. (2012) Assessment of the Pacific sardine resource in 2012 for U.S. management in 2013. Technical report, Pacific Fishery Management Council, Portland, Oregon, United States of America.
30. Wilson G, Aruliah DA, Brown CT, Chue Hong NP, Davis M, et al. (2014) Best practices for scientific computing. PLOS Biol 12: e1001745.
31. Methot RD, Taylor IG (2011) Adjusting for bias due to variability of estimated recruitments in fishery assessment models. Can J Fish Aquat Sci 68: 1744-1760.
32. Wickham H (2009) ggplot2 : Elegant Graphics for Data Analysis. New York: Springer. 213 p.
33. Kell LT, Mosqueira I, Grosjean P, Fromentin JM, Garcia D, et al. (2007) FLR: An open-source framework for the evaluation and development of management strategies. ICES J Mar Sci 64: 640-646. (Pubitemid 350067293)
34. Hillary R (2009) An introduction to FLR fisheries simulation tools. Aquat Living Resour 22: 225-232.
35. Piner KR, Lee HH, Maunder MN, Methot RD (2011) A simulation-based method to determine model misspecification: Examples using natural mortality and population dynamics models. Mar Coast Fish 3: 336-343.
36. Vert-pre KA, Amoroso RO, Jensen OP, Hilborn R (2013) Frequency and intensity of productivity regime shifts in marine fish stocks. Proc Natl Acad Sci USA 110: 1779-1784.
37. Walther GR, Post E, Convey P, Menzel A, Parmesan C, et al. (2002) Ecological responses to recent climate change. Nature 416: 389-395. (Pubitemid 34272866)
38. Royama T (1992) Analytical Population Dynamics. London: Chapman and Hall. 371 p.
39. Fu C, Mohn R, Fanning LP (2001) Why the Atlantic cod (Gadus morhua) stock off eastern Nova Scotia has not recovered. Can J Fish Aquat Sci 58: 1613-1623. (Pubitemid 32752587)
40. Beamish RJ (1995) Climatic change and northern fish populations. Can. Spec. Publ. Fish. Aquat. Sci. No.121.
41. Pyper BJ, Peterman RM (1998) Comparison of methods to account for autocorrelation in correlation analyses of fish data. Can J Fish Aquat Sci 55: 2127-2140. (Pubitemid 28560395)
42. 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.
43. Legault CM (2008) Report of the retrospective working group. NOAA NMFS Northeast Fisheries Science Center Reference Document 09-01. Northeast Fisheries Science Center Reference Document 09-01, NOAA NMFS, Woods Hole, Massachusetts, United States of America.
44. Crone PR, Maunder MN, Valero JL, D MJ, Semmens BX (2013) Selectivity: Theory, estimation, and application in fishery stock assessment models. Workshop series report 1. Center for the Advancement of Population Assessment Methodology, La Jolla, California, United States of America.