References

Aldrin, M., Aanes, F. L., Tvete, I. F., Aanes, S., & Subbey, S. (2021). Caveats with estimating natural mortality rates in stock assessment models using age aggregated catch data and abundance indices. Fisheries Research, 243, 106071. https://doi.org/10.1016/j.fishres.2021.106071

Alonzo, S.H., and Mangel, M. 2004. The effects of size-selective fisheries on the stock dynamics of and sperm limitation in sex-changing fish. Fishery Bulletin 102(1): 1–14. National Marine Fisheries Service.

Alonzo, S.H., and Mangel, M. 2005. Sex-change rules, stock dynamics, and the performance of spawning-per-recruit measures in protogynous stocks. Fishery Bulletin 103(2): 229–246. National Marine Fisheries Service.

Alonzo, S.H., Ish, T., Key, M., MacCall, A.D., and Mangel, M. 2008. The Importance of Incorporating Protogynous Sex Change Into Stock Assessments. BULLETIN OF MARINE SCIENCE 83(1).

Amoroso, R., Lomonico, S., Snouffer, B., and Gutierrez, N.L. 2024. Data preparation to inform assessment and management approaches in data-limited fisheries – A practical manual. FAO, Rome. doi:10.4060/cd0366en.

Anderson, R.O., and Neumann, R.M. 1996. Length, weight, and associated structural indices. In Fisheries Techniques, 2nd edition. Edited by B.R. Murphy and D.W. Willis. American Fisheries Society, Bethesda, Maryland. pp. 447–482.

Arkhipkin, A.I., and Roa-Ureta, R. 2005. Identification of ontogenetic growth models for squid. Mar. Freshwater Res. 56(4): 371. doi:10.1071/MF04274.

Arkhipkin, A.I., Hendrickson, L.C., Payá, I., Pierce, G.J., Roa-Ureta, R.H., Robin, J.-P., and Winter, A. 2021. Stock assessment and management of cephalopods: advances and challenges for short-lived fishery resources. ICES Journal of Marine Science 78(2): 714–730. doi:10.1093/icesjms/fsaa038.

Arkhipkin, A.I., Rodhouse, P.G., Pierce, G.J., Sauer, W., Sakai, M., Allcock, L., Arguelles, J., Bower, J.R., Castillo, G., Ceriola, L., and others. 2015. World squid fisheries. Reviews in Fisheries Science & Aquaculture 23(2): 92–252. Taylor & Francis.

Armsworth, P.R. 2001. Effects of fishing on a protogynous hermaphrodite. Can. J. Fish. Aquat. Sci. 58(3): 568–578. doi:10.1139/f01-015.

Arnason, A. N., & Mills, K. H. (1981). Bias and Loss of Precision Due to Tag Loss in Jolly–Seber Estimates for Mark–Recapture Experiments. Canadian Journal of Fisheries and Aquatic Sciences, 38(9), 1077–1095. https://doi.org/10.1139/f81-148

Arreguín-Sánchez, F., Solís-Ramírez, M.J., and González De La Rosa, M.E. 2000. Population dynamics and stock assessment for Octopus maya (Cephalopoda: Octopodidae) fishery in the Campeche Bank, Gulf of Mexico. Revista de Biología Tropical 48(2–3): 323–331. http://creativecommons. org/licenses/by/3.0.

Ault, J.S., Smith, S.G., and Tilmant, J.T. 2009. Are the coral reef finfish fisheries of South Florida sustainable? Proceedings International Coral Reef Symposium. pp. 989–993. [accessed 27 October 2012].

Barange, M., Bernal, M., Cergole, M.C., Cubillos, L.A., Daskalov, G.M., de Moor, C.L., De Oliveira, J.A., Dickey-Collas, M., Gaughan, D.J., Hill, K., and others. 2009. Current trends in the assessment and management of stocks. Climate change and small pelagic fish: 191–255. Cambridge University Press: Cambridge, UK.

Barceló, C., White, J. W., Botsford, L. W., & Hastings, A. (2021). Projecting the timescale of initial increase in fishery yield after implementation of marine protected areas. ICES Journal of Marine Science, 78(5), 1860–1871. https://doi.org/10.1093/icesjms/fsaa233

Barnett, L. A. K., Branch, T. A., Ranasinghe, R. A., & Essington, T. E. (2017). Old-Growth Fishes Become Scarce under Fishing. Current Biology, 27(18), 2843-2848.e2. https://doi.org/10.1016/j.cub.2017.07.069

Batts, L., Minto, C., Gerritsen, H., & Brophy, D. (2019). Estimating growth parameters and growth variability from length frequency data using hierarchical mixture models. ICES Journal of Marine Science, 76(7), 2150–2163. https://doi.org/10.1093/icesjms/fsz103

Berger, A. M. (2019). Character of temporal variability in stock productivity influences the utility of dynamic reference points. Fisheries Research, 217, 185–197. https://doi.org/10.1016/j.fishres.2018.11.028

Bettross, E.A., and Willis, D.W. 1988. Seasonal patterns in sampling data for largemouth bass and bluegills in a northern Great Plains impoundment. Prairie Naturalist 20(4): 193–202.

Beverton, R.J.H. 1963. Maturation, growth and mortality of Clupeid and Engraulid stocks in relation to fishing. report, Rapports et procès-verbaux des réunions (1903–1991). doi:10.17895/ices.pub.19274888.v1.

Beverton, R.J.H. 1990. Small marine pelagic fish and the threat of fishing; are they endangered? Journal of Fish Biology 37(sA): 5–16. doi:10.1111/j.1095-8649.1990.tb05015.x.

Beverton, R.J.H. 1992. Patterns of reproductive strategy parameters in some marine teleost fishes. Journal of Fish Biology 41(sB): 137–160. doi:10.1111/j.1095-8649.1992.tb03875.x.

Beverton, R.J.H., and Holt, S.J. 1957. On the dynamics of exploited fish populations. Chapman and Hall, London UK.

Beverton, R.J.H., and Holt, S.J. 1959. A review of the lifespans and mortality rates of fish in nature and their relation to growth and other physiological characteristics. Edited by G.E.W. Wolstenholme and M. O’Conner. J. & A. Churchill Ltd., London.

Boettiger, C., Lang, D.T., and Wainwright, P.C. 2012. rfishbase: exploring, manipulating and visualizing FishBase data from R. Journal of Fish Biology 81(6): 2030–2039. doi:10.1111/j.1095-8649.2012.03464.x.

Brodziak, J. 2002. In Search of Optimal Harvest Rates for West Coast Groundfish. N. Am. J. Fish. Man. 22(1): 258–271. doi:10.1577/1548-8675(2002)022<0258:ISOOHR>2.0.CO;2.

Brooks, E.N., Powers, J.E., and Cortés, E. 2010. Analytical reference points for age-structured models: application to data-poor fisheries. ICES J. Mar. Sci. 67(1): 165–175. doi:10.1093/icesjms/fsp225.

Buckmeier, D. L., Sakaris, P. C., & Schill, D. J. (2017). Validation of annual and daily increments in calcified structures and verification of age estimates. In M. C. Quist & D. A. Isermann (Eds.), Age adn Growth of Fishes: Principles and Techiques (pp. 33–79). American Fisheries Society.

Cadima, E.L. 2005. Sampling methods applied to fisheries science: a manual. Food & Agriculture Org.

Cadrin, S. X., Goethel, D. R., Berger, A., & Jardim, E. (2023). Best practices for defining spatial boundaries and spatial structure in stock assessment. Fisheries Research, 262, 106650. https://doi.org/10.1016/j.fishres.2023.106650

Cadrin, S. X., Goethel, D. R., Berger, A., & Jardim, E. (2023). Best practices for defining spatial boundaries and spatial structure in stock assessment. Fisheries Research, 262, 106650. https://doi.org/10.1016/j.fishres.2023.106650

Cadrin, S. X., Kerr, L. A., & Mariani, S. (Eds.). (2013). Stock Identification Methods. Elsevier. https://shop.elsevier.com/books/stock-identification-methods/cadrin/978-0-12-397003-9

Cadrin, S.X. 2012. Unintended consequences of MSY proxies for defining overfishing. International Council for the Exploration of the Sea, C.M. 2012/L:23, Copenhagen.

Cailliet, G. M., Andrews, A. H., Burton, E. J., Watters, D. L., Kline, D. E., & Ferry-Graham, L. A. (2001). Age determination and validation studies of marine fishes: Do deep-dwellers live longer? Experimental Gerontology, 36(4), 739–764. https://doi.org/10.1016/S0531-5565(00)00239-4

Campana, S. E. (2001). Accuracy, precision and quality control in age determination, including a review of the use and abuse of age validation methods. Journal of Fish Biology, 59(2), 197–242. https://doi.org/10.1111/j.1095-8649.2001.tb00127.x

Carline, R.F., Johnson, B.L., and Hall, T.J. 1984. Estimation and interpretation of proportional stock density for fish populations in Ohio impoundments. North American Journal of Fisheries Management 4(2): 139–154. Wiley Online Library.

Carr, B.H.C. 2018. Analysis of the Western and Central Pacific tuna and billfish fisheries through examination of historical catch records. PhD Thesis, Boston University.

Chan, N.C.S., Connolly, S.R., and Mapstone, B.D. 2012. Effects of sex change on the implications of marine reserves for fisheries. Ecological Applications 22(3): 778–791. doi:10.1890/11-0036.1.

Chapman, D. G. (1961). Statistical Problems in Dynamics of Exploited Fisheries Populations. https://www.semanticscholar.org/paper/Statistical-Problems-in-Dynamics-of-Exploited-Chapman/93e140411fa632d22fe0e0c1328619bcf898e7ec

Chapman, D. G., & Robson, D. S. (1960). The Analysis of a Catch Curve. Biometrics, 16(3), 354–368. https://doi.org/10.2307/2527687

Cheng, J., Edwards, L. J., Maldonado-Molina, M. M., Komro, K. A., & Muller, K. E. (2010). Real longitudinal data analysis for real people: Building a good enough mixed model. Statistics in Medicine, 29(4), 504–520. https://doi.org/10.1002/sim.3775

Chih, C.-P. 2011. The design effects of cluster sampling on the estimation of mean lengths and total mortality of reef fish. Fisheries Research 109(2–3): 295–302. doi:10.1016/j.fishres.2011.02.016.

Chilton, D., & Beamish, R. J. (1982). Age determination for fishes studied by the Groundfish Program at the Pacific Biological Station. Can. Spec. Publ. Fish. Aquat. Sci., 60.

Choat, J. H., Kritzer, J. P., & Ackerman, J. L. (2009). Ageing in Coral Reef Fishes: Do we Need to Validate the Periodicity of Increment Formation for every species of Fish for which we collect age-based Demographic Data? In B. S. Green, B. D. Mapstone, G. Carlos, & G. A. Begg (Eds.), Tropical Fish Otoliths: Information for Assessment, Management and Ecology (pp. 23–54). Springer Netherlands. https://doi.org/10.1007/978-1-4020-5775-5_2

Clark, W.G. 1991. Groundfish Exploitation Rates Based on Life History Parameters. Can. J. Fish. Aquat. Sci. 48(5): 734–750. doi:10.1139/f91-088.

Clark, W.G. 2002. F35% Revisited Ten Years Later. N. Am. J. Fish. Man. 22(1): 251–257. doi:10.1577/1548-8675(2002)022<0251:FRTYL>2.0.CO;2.

Cochran, W.G. 1953. Sampling Techniques. Wiley, New York.

Conquest, L., Burr, R., Donnelly, J., Chavarria, J., and Gallucci, V. 1996. Sampling methods for stock assessment for small-scale fisheries in developing countries. In Stock Assessment: Quantitative Methods and Applications for Small Scale Fisheries. Edited by V.F. Gallucci, S.B. Salia, D.J. Gustafson, and B.J. Rothschild. CRC Press, New York, NY. pp. 179–225.

Coscino, C.L., Bellquist, L., Harford, W.J., and Semmens, B.X. 2024. Influence of life history characteristics on data-limited stock status assertions and minimum size limit evaluations using Length-Based Spawning Potential Ratio (LBSPR). Fisheries Research 276: 107036. doi:10.1016/j.fishres.2024.107036.

De Moor, C.L., Butterworth, D.S., and De Oliveira, J.A.A. 2011. Is the management procedure approach equipped to handle short-lived pelagic species with their boom and bust dynamics? The case of the South African fishery for sardine and anchovy. ICES Journal of Marine Science 68(10): 2075–2085. doi:10.1093/icesjms/fsr165.

DeMartini, E. E., & Howard, K. G. (2016). Comparisons of body sizes at sexual maturity and at sex change in the parrotfishes of Hawaii: Input needed for management regulations and stock assessments. Journal of Fish Biology, 88(2), 523–541. https://doi.org/10.1111/jfb.12831

Demidenko, E., & Stukel, T. A. (2005). Influence analysis for linear mixed-effects models. Statistics in Medicine, 24(6), 893–909. https://doi.org/10.1002/sim.1974

Dorn, M. W. (2002). Advice on West Coast Rockfish Harvest Rates from Bayesian Meta-Analysis of Stock−Recruit Relationships. N. Am. J. Fish. Man., 22(1), 280–300. https://doi.org/10.1577/1548-8675(2002)022<0280:AOWCRH>2.0.CO;2

Dorn, M.W. 2002. Advice on West Coast Rockfish Harvest Rates from Bayesian Meta-Analysis of Stock−Recruit Relationships. North American Journal of Fisheries Management 22(1): 280–300. doi:10.1577/1548-8675(2002)022<0280:AOWCRH>2.0.CO;2.

Dowling, N.A., Smith, A.D.M., Smith, D.C., Parma, A.M., Dichmont, C.M., Sainsbury, K., Wilson, J.R., Dougherty, D.T., and Cope, J.M. 2019. Generic solutions for datalimited fishery assessments are not so simple. Fish and Fisheries 20(1): 174–188. doi:10.1111/faf.12329.

Dureuil, M., Aeberhard, W. H., Dowd, M., Pardo, S. A., Whoriskey, F. G., & Worm, B. (2022). Reliable growth estimation from mark–recapture tagging data in elasmobranchs. Fisheries Research, 256, 106488. https://doi.org/10.1016/j.fishres.2022.106488

Easter, E., and White, J. 2016. Spatial management for protogynous sex-changing fishes: a general framework for coastal systems. Mar. Ecol. Prog. Ser. 543: 223–240. doi:10.3354/meps11574.

Essington, T.E., Moriarty, P.E., Froehlich, H.E., Hodgson, E.E., Koehn, L.E., Oken, K.L., Siple, M.C., and Stawitz, C.C. 2015. Fishing amplifies forage fish population collapses. Proc. Natl. Acad. Sci. U.S.A. 112(21): 6648–6652. doi:10.1073/pnas.1422020112.

Eveson, J. P., Polacheck, T., & Laslett, G. M. (2007). Consequences of assuming an incorrect error structure in von Bertalanffy growth models: A simulation study. Canadian Journal of Fisheries and Aquatic Sciences, 64(4), 602–617. https://doi.org/10.1139/f07-036

Fabens, A. J. (1965). Properties and fitting of the Von Bertalanffy growth curve. Growth, 29(3), 265–289.

Ferreri, R., Basilone, G., D’Elia, M., Traina, A., Saborido-Rey, F., & Mazzola, S. (2009). Validation of macroscopic maturity stages according to microscopic histological examination for European anchovy. Marine Ecology, 30(s1), 181–187. https://doi.org/10.1111/j.1439-0485.2009.00312.x

Flores, A., Wiff, R., Ganias, K., & Marshall, C. T. (2019). Accuracy of gonadosomatic index in maturity classification and estimation of maturity ogive. Fisheries Research, 210, 50–62. https://doi.org/10.1016/j.fishres.2018.10.009

Fontoura, N. F., Jesus, A. S., Larre, G. G., & Porto, J. R. (2010). Can weight/length relationship predict size at first maturity? A case study with two species of Characidae. Neotropical Ichthyology, 8, 835–840. https://doi.org/10.1590/S1679-62252010005000013

Fournier, D., & Archibald, C. P. (1982). A General Theory for Analyzing Catch at Age Data. Canadian Journal of Fisheries and Aquatic Sciences, 39(8), 1195–1207. https://doi.org/10.1139/f82-157

Froese, R. 2004. Keep it simple: three indicators to deal with overfishing. Fish and Fisheries 5(1): 86–91. doi:10.1111/j.1467-2979.2004.00144.x.

Froese, R., and Pauly, D. 2011. FishBase. World Wide Web electronic publication. www.fishbase.org, version (06/2011).

Fromentin, J.-M., and Fonteneau, A. 2001. Fishing effects and life history traits: a case study comparing tropical versus temperate tunas. Fisheries Research 53(2): 133–150. doi:10.1016/S0165-7836(00)00299-X.

Gallucci, V.F., Amjoun, B., Hedgepeth, J., and Lai, H.L. 1996. Size-based methods of stock assessment of small-scale fisheries. In Stock Assessment: Quantitative Methods and Applications for Small-Scale Fisheries. Edited by V.F. Gallucci, S.B. Saila, D.J. Gustafson, and B.J. Rothschild. CRC Press, Boca Raton, FL. p. 515.

Garcia, S., and Josse, E. 1988. Notes on the assessment of the stocks of small pelagic species on the basis of length frequency analysis and converted catch curves. ICLARM.

Gelman, A., & Hill, J. (2007). Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge University Press.

Gelman, A., Carlin, J. B., Stern, H. S., & Rubin, D. B. (2004). Bayesian data analysis, Second Edition. Chapman and Hall/CRC.

Goodyear, C.P. 1993. Spawning stock biomass per recruit in fisheries management: foundations and current use. In Risk evaluation and biological reference points for fisheries management. Edited by S.J. Smith and J.J. Hunt. Special Publication in Fisheries and Aquatic Sciences, 120, Canada.

Gudmundsson, G., & Gunnlaugsson, T. (2012). Selection and estimation of sequential catch-at-age models. Canadian Journal of Fisheries and Aquatic Sciences, 69(11), 1760–1772. https://doi.org/10.1139/f2012-095

Gulland, J.A. 1966. Manual of Sampling and Statistical Methods for Fisheries Biology: Part 1, Sampling Methods. FAO (Food and Agriculture Organization of the United Nations), Rome, Italy.

Gulland, J.A., and Rosenberg, A.A. 1992. A review of length-based approaches to assessing fish stocks. Food & Agriculture Org.

Gunderson, D. R., & Dygert, P. H. (1988). Reproductive effort as a predictor of natural mortality rate 1. ICES Journal of Marine Science, 44(2), 200–209. https://doi.org/10.1093/icesjms/44.2.200

Hamel, O. S., & Cope, J. M. (2022). Development and considerations for application of a longevity-based prior for the natural mortality rate. Fisheries Research, 256, 106477. https://doi.org/10.1016/j.fishres.2022.106477

Hamley, J. M., & Regier, H. A. (1973). Direct Estimates of Gillnet Selectivity to Walleye (Stizostedion vitreum vitreum). Journal of the Fisheries Research Board of Canada, 30(6), 817–830. https://doi.org/10.1139/f73-137

Hanson, K.C., Gravel, M.A., Graham, A., Shoji, A., and Cooke, S.J. 2008. Sexual Variation in Fisheries Research and Management: When Does Sex Matter? Reviews in Fisheries Science 16(4): 421–436. doi:10.1080/10641260802013866.

Harford, W., and Rios, A. 2018. SEDAR57-AP-01.

Harford, W.J. 2024. FishSimGTG: an {{R}} package for simulation of fish population dynamics and evaluation of management strategies. https://github.com/natureanalytics-ca/fishSimGTG.

Harford, W.J., Sagarese, S.R., and Karnauskas, M. 2019. Coping with information gaps in stock productivity for rebuilding and achieving maximum sustainable yield for grouper–snapper fisheries. Fish Fish 20(2): 303–321. doi:10.1111/faf.12344.

Hashiguti, D. T., Soares, B. E., Wilson, K. L., Oliveira-Raiol, R. D., & Montag, L. F. de A. (2019). Comparing three methods to estimate the average size at first maturity: A case study on a Curimatid exhibiting polyphasic growth. Ecology of Freshwater Fish, 28(2), 266–273. https://doi.org/10.1111/eff.12451

He, X., Mangel, M., & MacCall, A. (2006). A prior for steepness in stock-recruitment relationships, based on an evolutionary persistence principle. Fish Bull., 104, 428–433.

Heppell, S.S., Heppell, S.A., Coleman, F.C., and Koenig, C.C. 2006. Models to compare management options for a protogynous fish. Ecological Applications 16(1): 238–249. Wiley Online Library.

Hewitt, D. A., Lambert, D. M., Hoenig, J. M., Lipcius, R. N., Bunnell, D. B., & Miller, T. J. (2007). Direct and Indirect Estimates of Natural Mortality for Chesapeake Bay Blue Crab. Transactions of the American Fisheries Society, 136(4), 1030–1040. https://doi.org/10.1577/T06-078.1

Hilborn, R. 2010. Pretty good yield and exploited fisheries. Mar. Policy 34: 193–196.

Hoenig, J. M., Barrowman, N. J., Hearn, W. S., & Pollock, K. H. (1998). Multiyear tagging studies incorporating fishing effort data. Canadian Journal of Fisheries and Aquatic Sciences, 55(6), 1466–1476.

Hordyk, A., Ono, K., Sainsbury, K., Loneragan, N., and Prince, J. 2015a. Some explorations of the life history ratios to describe length composition, spawning-per-recruit, and the spawning potential ratio. ICES Journal of Marine Science 72(1): 204–216. doi:10.1093/icesjms/fst235.

Hordyk, A., Ono, K., Valencia, S., Loneragan, N., and Prince, J. 2015b. A novel length-based empirical estimation method of spawning potential ratio (SPR), and tests of its performance, for small-scale, data-poor fisheries. ICES Journal of Marine Science 72(1): 217–231. doi:10.1093/icesjms/fsu004.

Hordyk, A.R., Loneragan, N.R., and Prince, J.D. 2015c. An evaluation of an iterative harvest strategy for data-poor fisheries using the length-based spawning potential ratio assessment methodology. Fisheries Research 171: 20–32. doi:10.1016/j.fishres.2014.12.018.

Hordyk, A.R., Ono, K., Prince, J.D., and Walters, C.J. 2016. A simple length-structured model based on life history ratios and incorporating size-dependent selectivity: application to spawning potential ratios for data-poor stocks. Can. J. Fish. Aquat. Sci. 73(12): 1787–1799. doi:10.1139/cjfas-2015-0422.

Hordyk, A.R., Ono, K., Valencia, S., Loneragan, N., and Prince, J.D. 2015d. A novel length-based empirical estimation method of spawning potential ratio (SPR), and tests of its performance, for small-scale, data-poor fisheries. ICES J. Mar. Sci. 72: 217–231. doi:10.1093/icesjms/fsu004.

Hubert, W.A. 1996. Passive capture techniques. In Fisheries Techniques, 2nd edition. Edited by B.R. Murphy and D.W. Willis. American Fisheries Society, Bethesda, Maryland. pp. 157–192.

ICES. (2008). Report of the Workshop on Maturity Ogive Estimation for Stock Assessment (WKMOG), 36 June 2008, Lisbon, Portugal. ICES CM2008/ACOM:33. 72 pp.

Jacobsen, N.S., and Essington, T.E. 2018. Natural mortality augments population fluctuations of forage fish. Fish and Fisheries 19(5): 791–797. doi:10.1111/faf.12290.

Jensen, A. L. (1997). Origin of the relation between K and Linf and synthesis of relations among life history parameters. Canadian Journal of Fisheries and Aquatic Sciences, 54, 987–989.

Jiao, Y., Smith, E. P., O’Reilly, R., & Orth, D. J. (2012). Modelling non-stationary natural mortality in catch-at-age models. ICES Journal of Marine Science, 69(1), 105–118. https://doi.org/10.1093/icesjms/fsr184

Johnston, A., Fink, D., Reynolds, M. D., Hochachka, W. M., Sullivan, B. L., Bruns, N. E., Hallstein, E., Merrifield, M. S., Matsumoto, S., & Kelling, S. (2015). Abundance models improve spatial and temporal prioritization of conservation resources. Ecological Applications, 25(7), 1749–1756. https://doi.org/10.1890/14-1826.1

Kadagi, N.I., Wambiji, N., Mann, B., Parker, D., Daly, R., Thoya, P., Rato, D.A.M., Halafo, J., Gaspare, L., Sweke, E.A., Ahmed, S., Raseta, S.B., Osore, M., Maina, J., Glaser, S., Ahrens, R., and Sumaila, U.R. 2022. Status and challenges for sustainable billfish fisheries in the Western Indian Ocean. Rev Fish Biol Fisheries 32(4): 1035–1061. doi:10.1007/s11160-022-09725-8.

Kindsvater, H.K., Reynolds, J.D., Sadovy de Mitcheson, Y., and Mangel, M. 2017. Selectivity matters: Rules of thumb for management of plate-sized, sex-changing fish in the live reef food fish trade. Fish and Fisheries 18(5): 821–836. Wiley Online Library.

Kinney, M.J., Chang, Y.-J., Ijima, H., Kanaiwa, M., Schemmel, E., and O’Malley, J. 2020. Length-Based Proportional Sampling for Life History Research: Establishing Uniform Sampling for North Pacific Billfish Species. Pacific Islands Fisheries Science Center, National Marine Fisheries Service, Honolulu, HI. Available from https://isc.fra.go.jp/reports/bill/bill_2020_2.html.

Klibansky, N., & Scharf, F. S. (2015). Success and failure assessing gonad maturity in sequentially hermaphroditic fishes: Comparisons between macroscopic and microscopic methods. Journal of Fish Biology, 87(4), 930–957. https://doi.org/10.1111/jfb.12765

Kritzer, J. P., Davies, C. R., & Mapstone, B. D. (2001). Characterizing fish populations: Effects of sample size and population structure on the precision of demographic parameter estimates. Canadian Journal of Fisheries and Aquatic Sciences. https://doi.org/10.1139/f01-098

Kritzer, J.P., Davies, C.R., and Mapstone, B.D. 2001. Characterizing fish populations: effects of sample size and population structure on the precision of demographic parameter estimates. Can. J. Fish. Aquat. Sci. 58(8): 1557–1568. doi:10.1139/f01-098.

Lai, H., Gallucci, V.F., Gunderson, D.R., and Donnelly, R.F. 1996. Age determination in fisheries: methods and applications to stock assessment. In Stock Assessment: Quantitative Methods and Applications for Small-Scale Fisheries. Edited by V.F. Gallucci, S.B. Saila, D.J. Gustafson, and B.J. Rothschild. CRC Press Inc., Boca Raton. pp. 82–178.

Lascelles, B., Notarbartolo Di Sciara, G., Agardy, T., Cuttelod, A., Eckert, S., Glowka, L., Hoyt, E., Llewellyn, F., Louzao, M., Ridoux, V., and Tetley, M.J. 2014. Migratory marine species: their status, threats and conservation management needs. Aquatic Conservation 24(S2): 111–127. doi:10.1002/aqc.2512.

Laslett, G. M., Eveson, J. P., & Polacheck, T. (2004). Fitting growth models to length frequency data. ICES Journal of Marine Science, 61(2), 218–230. https://doi.org/10.1016/j.icesjms.2003.12.006

LEE, R.M. 1912. AN INVESTIGATION INTO THE METHODS OF GROWTH DETERMINATION IN FISHES BY MEANS OF SCALES. ICES Journal of Marine Science s1(63): 3–34. doi:10.1093/icesjms/s1.63.3.

Liu, X., & Heino, M. (2014). Overlooked biological and economic implications of within-season fishery dynamics. Canadian Journal of Fisheries and Aquatic Sciences, 71(2), 181–188. https://doi.org/10.1139/cjfas-2013-0029

Lott, J., and Willis, D.W. 1991. Gill net mesh size efficiency for yellow perch. Prairie Naturalist 23: 139–144.

Loy, A., & Hofmann, H. (2013). Diagnostic tools for hierarchical linear models. WIREs Computational Statistics, 5(1), 48–61. https://doi.org/10.1002/wics.1238

MacCall, A.D. 2009. Mechanisms of low-frequency fluctuations in sardine and anchovy populations. In Climate Change and Small Pelagic Fish. p. 285.

Mace, P. M., & Sissenwine, M. P. (2002). Coping with uncertainty: Evolution of the relationship between science and management. American Fisheries Society Symposium, 27, 9–28.

Mace, P.M. 1994. Relationships between common biological reference points used as thresholds and targets of fisheries management strategies. Can J Fish Aquat Sci. 51(1): 110–122. doi:10.1139/f94-013.

Mangel, M., MacCall, A. D., Brodziak, J., Dick, E. J., Forrest, R. E., Pourzand, R., & Ralston, S. (2013). A perspective on steepness, reference points, and stock assessment. Can J Fish Aquat Sci., 70(6), 930–940. https://doi.org/10.1139/cjfas-2012-0372

Maunder, M. N., & Punt, A. E. (2013). A review of integrated analysis in fisheries stock assessment. Fisheries Research, 142, 61–74. https://doi.org/10.1016/j.fishres.2012.07.025

Maunder, M. N., Hamel, O. S., Lee, H.-H., Piner, K. R., Cope, J. M., Punt, A. E., Ianelli, J. N., Castillo-Jordán, C., Kapur, M. S., & Methot, R. D. (2023). A review of estimation methods for natural mortality and their performance in the context of fishery stock assessment. Fisheries Research, 257, 106489. https://doi.org/10.1016/j.fishres.2022.106489

Mazloumi, N., & Nicol, S. (2023). Preparing for climate related impacts: Knowledge assessment of the life history of key exploited fish species managed in a climate hotspot. Marine Policy, 148, 105381. https://doi.org/10.1016/j.marpol.2022.10538

McCluskey, S. M., & Lewison, R. L. (2008). Quantifying fishing effort: A synthesis of current methods and their applications. Fish and Fisheries, 9(2), 188–200. https://doi.org/10.1111/j.1467-2979.2008.00283.x

Mero, S., and Willis, D. 1992. Seasonal variation in sampling data for walleye and sauger collected with gill nets from Lake Sakakawea, North Dakota. Prairie Naturalist 24: 231–231. NORTH DAKOTA NATURAL SCIENCE SOCIETY.

Miethe, T., and Dobby, H. 2022. Testing length-based reference points in a management strategy evaluation for cuckoo ray ( Leucoraja naevus ) and thornback ray ( Raja clavata ). ICES Journal of Marine Science 79(1): 129–146. doi:10.1093/icesjms/fsab248.

Min, M. A., Head, M. A., Cope, J. M., Hastie, J. D., & Flores, S. M. (2022). Limitations and applications of macroscopic maturity analyses: A comparison of histological and visual maturity for three west coast groundfish species. Environmental Biology of Fishes, 105(2), 193–211. https://doi.org/10.1007/s10641-021-01208-2

Miranda, L. E., & Colvin, M. E. (2017). Sampling for age and growth estimation. In M. C. Quist & D. A. Isermann (Eds.), Age and Growth of Fishes: Principles and Techniques (pp. 107–126). American Fisheries Society.

Miranda, L.E. 2007. Approximate Sample Sizes Required to Estimate Length Distributions. Trans Am Fish Soc 136(2): 409–415. doi:10.1577/T06-151.1.

Motulsky, H. J., & Christopoulos, A. (2003). Fitting models to biological data using linear and nonlinear regression: A practical guide to curve fitting. GraphPad Software, San Diego, California.

Myers, R. A., Barrowman, N. J., Hilborn, R., & Kehler, D. G. (2002). Inferring Bayesian Priors with Limited Direct Data: Applications to Risk Analysis. North American Journal of Fisheries Management, 22(1), 351–364. https://doi.org/10.1577/1548-8675(2002)022<0351:IBPWLD>2.0.CO;2

Myers, R. A., Bowen, K. G., & Barrowman, N. J. (1999). Maximum reproductive rate of fish at low population sizes. Canadian Journal of Fisheries and Aquatic Sciences, 56, 2404–2419.

NEFSC. 2008. Assessment of 19 Northeast Groundfish Stocks through 2007: Report of the 3rd Groundfish Assessment Review Meeting (GARM III), Northeast Fisheries Science Center (NEFSC), Woods Hole, Massachusetts, August 4–8, 2008, 2008pg. 884  US Department of Commerce, NOAA Fisheries, Northeast Fisheries Science Center Reference Document 08-15.

Nesslage, G., Schueller, A. M., Rezek, A. R., & Mroch, R. M. (2022). Influence of sample size and number of age classes on characterization of ageing error in paired-age comparisons. Fisheries Research, 249, 106255. https://doi.org/10.1016/j.fishres.2022.106255

Neumann, R., and Allen, M. 2007. Size structure. In Analysis and Interpretation of Freshwater Fisheries Data. Edited by C.S. Guy and M.L. Brown. American Fisheries Society, Bethesda, Maryland. pp. 375–421.

Ogle, Brenden, T. O., & McCormick, J. L. (2017). Growth estimation: Growth models and statistical inference. In M. C. Quist & D. A. Isermann (Eds.), Age and Growth of Fishes: Priciples and Techniques (pp. 265–359). American Fisheries Society.

Pardo, S. A., Cooper, A. B., & Dulvy, N. K. (2013). Avoiding fishy growth curves. Methods in Ecology and Evolution, 4(4), 353–360. https://doi.org/10.1111/2041-210x.12020

Parker, G.A. 1992. The evolution of sexual size dimorphism in fish*. Journal of Fish Biology 41(sB): 1–20. doi:10.1111/j.1095-8649.1992.tb03864.x.

Pauly, D. (1980). On the interrelationships between natural mortality, growth parameters, and mean environmental temperature in 175 fish stocks. Cons. Intl. Explor. Mer., 39, 175–192.

Pauly, D. (1984). Fish population dynamics in tropical waters: A manual for use with programmable calculators. ICLARM Stud. Rev. (8): 325p.

Pauly, D. (1987). A review of the ELEFAN system for analysis of length-frequency data in fish and aquatic invertebrates. https://digitalarchive.worldfishcenter.org/handle/20.500.12348/3366

Pennington, M., Burmeister, L.-M., and Hjellvik, V. 2002. Assessing the precision of frequency distributions estimated from trawl-survey samples. Fishery Bulletin 100(1): 74–81. National Marine Fisheries Service.

Peterman, R. M. (2004). Possible solutions to some challenges facing fisheries scientists and managers. ICES J. Mar. Sci., 61, 1331–1343.

Peterson, L. K., Jones, M. L., Brenden, T. O., Vandergoot, C. S., & Krueger, C. C. (2021). Evaluating methods for estimating mortality from acoustic telemetry data. Canadian Journal of Fisheries and Aquatic Sciences, 78(10), 1444–1454. https://doi.org/10.1139/cjfas-2020-0417

Pine Iii, W.E., Martell, S.J.D., Jensen, O.P., Walters, C.J., and Kitchell, J.F. 2008. Catch-and-release and size limit regulations for blue, white, and striped marlin: the role of postrelease survival in effective policy design. Can. J. Fish. Aquat. Sci. 65(5): 975–988. doi:10.1139/f08-020.

Pons, M., Branch, T.A., Melnychuk, M.C., Jensen, O.P., Brodziak, J., Fromentin, J.M., Harley, S.J., Haynie, A.C., Kell, L.T., Maunder, M.N., Parma, A.M., Restrepo, V.R., Sharma, R., Ahrens, R., and Hilborn, R. 2017. Effects of biological, economic and management factors on tuna and billfish stock status. Fish and Fisheries 18(1): 1–21. doi:10.1111/faf.12163.

Pope, K.L., and Willis, D.W. 1996. Seasonal influences on freshwater fisheries sampling data. Reviews in Fisheries Science 4(1): 57–73. doi:10.1080/10641269609388578.

Prince, J. D., Hordyk, A., Valencia, S. R., Loneragan, N., & Sainsbury, K. (2015). Revisiting the concept of Beverton­­–Holt life-history invariants with the aim of informing data-poor fisheries assessment. ICES J. Mar. Sci., 72(1), 194–203. https://doi.org/10.1093/icesjms/fsu011

Prince, J. D., Wilcox, C., & Hall, N. (2023). How to estimate life history ratios to simplify data-poor fisheries assessment. ICES Journal of Marine Science, 80(10), 2619–2629. https://doi.org/10.1093/icesjms/fsad026

Prince, J., and Hordyk, A. 2019. What to do when you have almost nothing: A simple quantitative prescription for managing extremely datapoor fisheries. Fish Fish 20(2): 224–238. doi:10.1111/faf.12335.

Prince, J., Harford, W. J., Taylor, B. M., & Lindfield, S. J. (2022). Standard histological techniques systematically under-estimate the size fish start spawning. Fish and Fisheries, 23(6), 1507–1516. https://doi.org/10.1111/faf.12702

Prince, J.D., Hordyk, A., Valencia, S.R., Loneragan, N., and Sainsbury, K. 2015. Revisiting the concept of Beverton­­–Holt life-history invariants with the aim of informing data-poor fisheries assessment. ICES J Mar Sci 72(1): 194–203. doi:10.1093/icesjms/fsu011.

Prince, J.D., Wilcox, C., and Hall, N. 2023. How to estimate life history ratios to simplify data-poor fisheries assessment. ICES Journal of Marine Science 80(10): 2619–2629. doi:10.1093/icesjms/fsad026.

Punt, A. E., & Dorn, M. (2014). Comparisons of meta-analytic methods for deriving a probability distribution for the steepness of the stock–recruitment relationship. Fisheries Research, 149, 43–54. https://doi.org/10.1016/j.fishres.2013.09.015

Quinn, T.J.I., and Deriso, R.B. 1999. Quantitative Fish Dynamics. Oxford University Press, New York, USA.

Reis, E. G., & Pawson, M. G. (1992). Determination of gill-net selectivity for bass (Dicentrarchus labrax L.) using commercial catch data. Fisheries Research, 13(2), 173–187. https://doi.org/10.1016/0165-7836(92)90025-O

Restrepo, V.R., Thompson, G.G., Mace, P.M., Gabriel, W.L., Low, L.L., MacCall, A.D., Methot, R.D., Powers, J.E., Taylor, B.L., Wade, P.R., and Witzig, J.F. 1998. Technical guidance on the use of precautionary approaches to implementing National Standard 1 of the Magnuson–Stevens Fishery Conservation and Management Act. NOAA Tech. Memo. NMFS-F/SPO-31, 54 p.

Ricker, W. E. (1975). Computation and interpretation biological statistics of fish populations (Vol. 191). Bulletin of the Fisheries Research Board of Canada.

Rubin, D. B. (1984). Bayesianly Justifiable and Relevant Frequency Calculations for the Applied Statistician. The Annals of Statistics, 12(4), 1151–1172.

Santos Nobre, J., & da Motta Singer, J. (2007). Residual Analysis for Linear Mixed Models. Biometrical Journal, 49(6), 863–875. https://doi.org/10.1002/bimj.200610341

Schnute, J. (1981). A Versatile Growth Model with Statistically Stable Parameters. Canadian Journal of Fisheries and Aquatic Sciences, 38(9), 1128–1140. https://doi.org/10.1139/f81-153

Shuter, J.L., Broderick, A.C., Agnew, D.J., Jonzén, N., Godley, B.J., MilnerGulland, E.J., and Thirgood, S. 2011. Conservation and management of migratory species. In Animal Migration. Edited by E.J. Milner-Gulland, J.M. Fryxell, and A.R.E. Sinclair. Oxford University Press. pp. 172–206. doi:10.1093/acprof:oso/9780199568994.003.0011.

Smith, M. W., Then, A. Y., Wor, C., Ralph, G., Pollock, K. H., & Hoenig, J. M. (2012). Recommendations for Catch-Curve Analysis. North American Journal of Fisheries Management, 32(5), 956–967. https://doi.org/10.1080/02755947.2012.711270

Snijders, T. A. B., & Bosker, R. (2011). Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling. 1–368.

Soares, B. E., Barros, T. F., Hashiguti, D. T., Pereira, D. C., Ferreira, K. C. F., & Caramaschi, É. P. (2020). Traditional approaches to estimate length at first maturity (L50) retrieve better results than alternative ones in a Neotropical heptapterid. Journal of Fish Biology, 97(5), 1393–1400. https://doi.org/10.1111/jfb.14505

Spirk, P.J. 2012. Effects of length limits on sexually size dimorphic fishes.

Stamatopoulos, C. 2002. Sample-based fishery surveys: a technical handbook. Food and Agriculture Organization of the United Nations, Rome.

Stamps, J. 1993. Sexual size dimorphism in species with asymptotic growth after maturity. Biological Journal of the Linnean Society 50(2): 123–145. Oxford University Press.

Stearns, S.C., and Koella, J.C. 1986. THE EVOLUTION OF PHENOTYPIC PLASTICITY IN LIFEHISTORY TRAITS: PREDICTIONS OF REACTION NORMS FOR AGE AND SIZE AT MATURITY. Evolution 40(5): 893–913. doi:10.1111/j.1558-5646.1986.tb00560.x.

Stewart, I.J., and Hamel, O.S. 2014. Bootstrapping of sample sizes for length- or age-composition data used in stock assessments. Can. J. Fish. Aquat. Sci. 71(4): 581–588. doi:10.1139/cjfas-2013-0289.

Stewart, J. (2011). Evidence of age-class truncation in some exploited marine fish populations in New South Wales, Australia. Fisheries Research, 108(1), 209–213. https://doi.org/10.1016/j.fishres.2010.11.017

Taylor, M. H., & Mildenberger, T. K. (2017). Extending electronic length frequency analysis in R. Fisheries Management and Ecology, 24(4), 330–338. https://doi.org/10.1111/fme.12232

Tsai, W.-P., and Huang, C.-H. 2022. Data-limited approach to the management and conservation of the pelagic thresher shark in the Northwest Pacific. Conservation Science and Practice 4(6): e12682. Wiley Online Library.

Vigliola, L., & Meekan, M. G. (2009). The Back-Calculation of Fish Growth From Otoliths. In B. S. Green, B. D. Mapstone, G. Carlos, & G. A. Begg (Eds.), Tropical Fish Otoliths: Information for Assessment, Management and Ecology (pp. 174–211). Springer Netherlands. https://doi.org/10.1007/978-1-4020-5775-5_6

Walters, C.J., and Martell, S.J.D. 2004. Fisheries Ecology and Management. Princeton University Press, USA.

Wang, J., Xu, L., Li, B., Tian, S., and Chen, Y. 2020. An evaluation of the effects of sample size on estimating length composition of catches from tuna longline fisheries using computer simulations. Aquaculture and Fisheries 5(3): 122–130. doi:10.1016/j.aaf.2019.09.001.

Wang, K., Zhang, C., Xu, B., Xue, Y., & Ren, Y. (2020). Selecting optimal bin size to account for growth variability in Electronic LEngth Frequency ANalysis (ELEFAN). Fisheries Research, 225, 105474. https://doi.org/10.1016/j.fishres.2019.105474

Wiff, R., Quiroz, J. C., Neira, S., Gacitúa, S., & Barrientos, M. A. (2016). Chilean fishing law, maximum sustainable yield and the stock-recruitment relationship. Latin American Journal of Aquatic Research, 44(2), Article 2. https://doi.org/10.3856/vol44-issue2-fulltext-19

Windsland, K. (2015). Total and natural mortality of red king crab (Paralithodes camtschaticus) in Norwegian waters: Catch–curve analysis and indirect estimation methods. ICES Journal of Marine Science, 72(2), 642–650. https://doi.org/10.1093/icesjms/fsu138

Wszola, L.S., Feiner, Z.S., Chizinski, C.J., Poletto, J.B., and DeLong, J.P. 2022. Fishing regulations, sexual dimorphism, and the life history of harvest. Can. J. Fish. Aquat. Sci. 79(9): 1435–1446. doi:10.1139/cjfas-2021-0248.

Zare, K., & Rasekh, A. (2011). Diagnostic measures for linear mixed measurement error models. SORT-Statistics and Operations Research Transactions, 35(2), Article 2.

Zhang, F., Reid, K. B., & Nudds, T. D. (2021). The longer the better? Trade-offs in fisheries stock assessment in dynamic ecosystems. Fish and Fisheries, 22(4), 789–797. https://doi.org/10.1111/faf.12550

Zhang, Z., Campbell, A., & Lessard, J. (2007). Modeling northern abalone, haliotis kamtschatkana, population stock and recruitment in British Columbia. J. Shellfish Res., 26(4), 1099–1107. https://doi.org/10.2983/0730-8000(2007)26[1099:MNAHKP]2.0.CO;2

Zhou, S., Hutton, T., Lei, Y., Miller, M., van Der Velde, T., & Deng, R. A. (2022). Estimating growth from length frequency distribution: Comparison of ELEFAN and Bayesian approaches for red endeavour prawns (Metapenaeus ensis). ICES Journal of Marine Science, 79(6), 1942–1953. https://doi.org/10.1093/icesjms/fsac131

Glossary

Fishery
A unit determined by an authority or other entity that is engaged in raising and/or harvesting fish. Typically, the unit is defined in terms of some or all of the following: people involved, species or type of fish, area of water or seabed, method of fishing, class of boats and purpose of the activities.

Fletcher, W.J., Chesson, J. Fisher, M., Sainsbury K.J., Hundloe, T. Smith A.D.M., and B. Whitworth (2002): National ESD reporting framework for Australian fisheries: The “How To” guide for wild capture fisheries. FRDC Project 2000/145. Canberra, Australia

Population
A self-sustaining group of individuals, from a single species, whose dynamics are primarily determined by birth and death processes.

Cadrin, S.X., Kerr, L.A., and Mariani, S. (Editors). 2013. Stock Identification Methods. Elsevier.

Stock
An exploited fishery unit. A stock may be a single spawning component, a population, a metapopulation, or comprise portions of these units. For management purposes stocks are considered discrete units, and each stock can be exploited independently or catches can be assigned to the stock of origin.

Cadrin, S.X., Kerr, L.A., and Mariani, S. (Editors). 2013. Stock Identification Methods. Elsevier.