과제정보
The National Institute of Fisheries Science provided the CPUE data, and Statistics Korea offered fishery yield data. Handling editor, Dr. Yong-Woo Lee's advice improved our manuscript.
참고문헌
- Aeberhard WH, Flemming JM, Nielsen A. Review of statespace models for fisheries science. Annu Rev Stat Appl. 2018;5:215-35. https://doi.org/10.1146/annurev-statistics-031017-100427
- Carruthers TR, McAllister MK, Taylor NG. Spatial surplus production modeling of Atlantic tunas and billfish. Ecol Appl. 2011;21:2734-55. https://doi.org/10.1890/10-2026.1
- Castro Hernandez JJ, Ortega Santana AT. Synopsis of biological data on the chub marckerel (Scomber japonicus Houttuyn, 1782).Rome: Food and Agriculture Organization of the United Nations; 2000.
- Chaloupka M, Balazs G. Using Bayesian state-space modelling to assess the recovery and harvest potential of the Hawaiian green sea turtle stock. Ecol Model. 2007;205:93-109. https://doi.org/10.1016/j.ecolmodel.2007.02.010
- Cho J, Lee JS, Nam J. A study on estimating the fishery optimal production by using a bio-economic model. Busan: Korea Maritime Institute; 2009.
- Choi YM, Zhang CI, Kim YS, Baik CI, Park YC. Ecological characteristics and biomass of chub mackerel, Scomber japonicus Houttuyn in Korean waters. Korean Soc Fish Resour. 2004a ;7:79-89.
- Choi YM, Zhang CI, Lee JB, Kim JY, Cha HK. Stock assessment and management implications of chub mackerel, Scomber japonicus in Korean waters. Korean Soc Fish Resour. 2004b;6:90-100.
- Clarke RP, Yoshimoto SS, Pooley SG. A bioeconomic analysis of the northwestern Hawaiian Islands lobster fishery. Mar Resour Econ. 1992;7:115-40. https://doi.org/10.1086/mre.7.3.42629029
- de Valpine P. Frequentist analysis of hierarchical models for population dynamics and demographic data. J Ornithol. 2012;152:393-408. https://doi.org/10.1007/s10336-010-0642-5
- Fournier DA, Skaug HJ, Ancheta J, Ianelli J, Magnusson A, Maunder MN, et al. AD model builder: using automatic differentiation for statistical inference of highly parameterized complex nonlinear models. Optim Methods Softw. 2012;27:233-49. https://doi.org/10.1080/10556788.2011.597854
- Fox WW. An exponential surplus-yield model for optimizing exploited fish populations. Trans Am Fish Soc. 1970;99:80-8. https://doi.org/10.1577/1548-8659(1970)99<80:AESMFO>2.0.CO;2
- Haddon M. Modelling and quantitative methods in fisheries. 2nd ed. Boca Raton, FL: CRC Press; 2011.
- Hilborn R. Pretty good yield and exploited fishes. Mar Policy. 2010;34:193-6. https://doi.org/10.1016/j.marpol.2009.04.013
- Hilborn R, Walters CJ. Quantitative fisheries stock assessment. Boston, MA: Springer; 1992.
- Hiyama Y, Yoda M, Ohshimo S. Stock size fluctuations in chub mackerel (Scomber japonicus) in the East China sea and the Japan/East sea. Fish Oceanogr. 2002;11:347-53. https://doi.org/10.1046/j.1365-2419.2002.00217.x
- Jeong M, Nam J. Estimation of fishery resource rebuilding and economic effects on coastal gill-net fishery as a result of Korean vessel buy-back program. Ocean Polar Res. 2017;39:221-32. https://doi.org/10.4217/OPR.2017.39.3.221
- Kim HA, Seo YI, Cha HK, Kang HJ, Zhang CI. A study on the estimation of potential yield for Korean west coast fisheries using the holistic production method (HPM). J Korean Soc Fish Technol. 2018;54:38-53. https://doi.org/10.3796/KSFOT.2018.54.1.038
- Korean Ministry of Ocean and Fisheries. Management plan for total allowable catch for 11 species in 2017 [Internet]. 2017 [cited 2019 Mar 28]. URL http://www.mof.go.kr/article/view.do?menuKey=376&boardKey=10&articleKey=14439
- Kristensen K, Nielsen A, Berg CW, Skaug H, Bell BM. TMB: automatic differentiation and Laplace approximation. J Stat Softw. 2016;70:1-21.
- Kwon Y, Zhang CI, Pyo HD, Seo YI. Comparison of models for estimating surplus productions and methods for estimating their parameters. J Korean Soc Fish Technol. 2013;49:18-28. https://doi.org/10.3796/KSFT.2013.49.1.018
- Lee HN, Kim HS. Variation of fisheries conditions of mackerel (Scomber japonicus) fishing ground for large purse seine fisheries. Bull Korean Soc Fish Technol. 2011;47:108-17. https://doi.org/10.3796/KSFT.2011.47.2.108
- McAllister MK, Pikitch EK, Babcock EA. Using demographic methods to construct Bayesian priors for the intrinsic rate of increase in the Schaefer model and implications for stock rebuilding. Can J Fish Aquat Sci. 2001;58:1871-90. https://doi.org/10.1139/f01-114
- McAllister MK, Pikitch EK, Punt AE, Hilborn R. A Bayesian approach to stock assessment and harvest decisions using the sampling/importance resampling algorithm. Can J Fish Aquat Sci. 1994;51:2673-87. https://doi.org/10.1139/f94-267
- Meyer R, Millar RB. BUGS in Bayesian stock assessments. Can J Fish Aquat Sci. 1999;56:1078-87. https://doi.org/10.1139/f99-043
- Millar RB, Meyer R. Bayesian state-space modeling of age-structured data: fitting a model is just the beginning. Can J Fish Aquat Sci. 2000a;57:43-50. https://doi.org/10.1139/f99-169
- Millar RB, Meyer R. Bayesian stock assessment using a nonlinear state-space model. Can J Fish Aquat Sci. 1999;56:37-52. https://doi.org/10.1139/f98-146
- Millar RB, Meyer R. Non-linear state space modelling of fisheries biomass dynamics by using Metropolis-Hastings within-Gibbs sampling. J R Stat Soc Ser C Appl Stat. 2000b;49:327-42. https://doi.org/10.1111/1467-9876.00195
- Musick JA, Bonfil R. Management techniques for elasmobranch fisheries. Rome: Food and Agriculture Organization of the United Nations; 2005.
- National Research Council. Improving fish stock assessments. Washington, DC: National Academies Press; 1998.
- Pedersen MW, Berg CW. A stochastic surplus production model in continuous time. Fish Fish. 2017;18:226-43. https://doi.org/10.1111/faf.12174
- Plummer M, Best N, Cowles K, Vines K. CODA: convergence diagnosis and output analysis for MCMC. R News. 2006;6:7-11.
- Prager MH. A suite of extensions to a nonequilibrium surplus-production model. Fish Bull. 1994;92:374-89.
- Prager MH. User's guide for ASPIC suite, version 7: a stock-production model incorporating covariates and auxiliary programs. Portland, OR: Prager Consulting; 2016.
- Punt A. Extending production models to include process error in the population dynamics. Can J Fish Aquat Sci. 2003;60:1217-28. https://doi.org/10.1139/f03-105
- Quinn TJ, Deriso RB. Quantitative fish dynamics. Oxford: Oxford University Press; 1999.
- Ricker WE. Computation and interpretation of biological statistics of fish populations. Bull Fish Res Board Can. 1975;1-382.
- Schaefer MB. Some aspects of the dynamics of populations important to the management of the commercial marine fisheries. Inter-Am Trop Tuna Comm. 1954;1:23-56.
- Schnute J. Improved estimates from the Schaefer production model: theoretical considerations. J Fish Res Board Can. 1977;34:583-603. https://doi.org/10.1139/f77-094
- Skaug H, Fournier D. Random effects in AD model builder, ADMB-RE user guide 11.2. admb-project.org; 2017.
- Walters CJ, Hilborn R. Adaptive control of fishing systems. J Fish Res Board Can. 1976;33:145-59. https://doi.org/10.1139/f76-017
- Walters CJ, Martell SJD. Fisheries ecology and management. Princeton, NJ: Princeton University Press; 2004.
- Wang Y, Zheng J, Yu C. Stock assessment of chub mackerel (Scomber japonicus) in the central East China Sea based on length data. J Mar Biol Assoc UK. 2014;94:211-17. https://doi.org/10.1017/S0025315413001434
- Winker H, Carvalho F, Kapur M. JABBA: just another Bayesian biomass assessment. Fish Res. 2018;204:275-88. https://doi.org/10.1016/j.fishres.2018.03.010
- Yoshimoto SS, Clarke RP. Comparing dynamic versions of the Schaefer and Fox production models and their application to lobster fisheries. Can J Fish Aquat Sci. 1993;50:181-89. https://doi.org/10.1139/f93-020