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How reliable are the Powell–Wetherall plot method and the maximum-length approach? Implications for length-based studies of growth and mortality

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Abstract

Length-based methods are the cornerstone of many population studies and stock assessments. This study tested two widely used methods: the Powell–Wetherall (P–W) plot and the Lmax approach (i.e., estimating L directly from Lmax). In most simulations, P–W estimates of the ratio total mortality/growth (Z/K ratio) were biased beyond acceptable limits (bias > 30%). Bias in Z/K showed a complex behavior, without possible corrections. Estimates of asymptotic length (L) were less biased than Z/K, but were very sensitive to intra-cohort variability in growth and to changes in the occurrence of large individuals in the sample. Exclusion of the largest size classes during the regression procedure or weighing by abundance does not solve these issues. Perfect linearization of the data and extremely narrow confidence intervals for Z/K will lead users to erroneous overconfidence in outputs. Clearly, the P–W method is not suitable for the assessment of Z/K ratios of natural populations. Estimation of L may be tentatively possible under very specific conditions, with necessary external verifications. Also, this study demonstrates that there is no way to estimate L directly from Lmax, since there is no particular relationship to expect a priori between L and Lmax. Errors in estimating L directly affect the estimate of the growth constant K and all other subsequent calculations in population studies, stock assessments and ecosystem models. New approaches are urgently needed for length-based studies of body growth (e.g., unconstrained curve fit with subsequent bootstrapping), that consider the inherent uncertainty regarding the underlying data and processes.

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References

  • Anbalagan T, Murugan A, Jawahar P, Vijayanand P, Saravanan R, Veerappan N (2016) Age and growth of squirrel fish, Sargocentron rubrum, (Forsskal, 1775) from Cuddalore waters, Southeast coast of India. Indian J Geo-Mar Sci 45(12):1742–1748

    Google Scholar 

  • Arellano RV (1989) Estimation of growth parameters in Panulirus penicillatus using a Wetherall plot and comparisons with other lobsters. Fishbyte 7(2):13–15

    Google Scholar 

  • Auerswald K, Wittmer MHOM, Zazzo A, Schaufele R, Schnyder H (2010) Biases in the analysis of stable isotope discrimination in food webs. J Appl Ecol 47:936–941

    Article  Google Scholar 

  • Bensen MA (1965) Spurious correlations in hydraulics and hydrology. J Hydraul Div Proc Am Soc Civ Eng 91:35–42

    Google Scholar 

  • Beverton RJH, Holt SJ (1956) A review of methods for estimating rates in exploited fish populations, with special reference to sources of bias in catch sampling. Rapports et Procès-verbaux des Réunions du Conseil International de l’Exploration de la Mer 140:67–83

    Google Scholar 

  • Beverton RJH, Holt SJ (1957) On the dynamics of exploited fish populations. In: Fishery investigations series II, vol XIX. Ministry of Agriculture, Fisheries and Food

  • Boettiger C (2017) Package ‘rfishbase' - R Interface to FishBase. https://cran.r-project.org/web/packages/rfishbase/rfishbase.pdf

  • Brett MT (2004) When is a correlation between non-independent variables “spurious”? Oikos 105:647–656. https://doi.org/10.1111/j.0030-1299.2004.12777.x

    Article  Google Scholar 

  • Brey T, Pauly D (1986) A user’s guide to ELEFAN 0, 1 and 2 (revised and expanded version). Ber Inst Meeresk Kiel 149:77

    Google Scholar 

  • Brey T, Soriano M, Pauly D (1987) Electronic length frequency analysis: a revised and expanded user’s guide to ELEFAN 0, 1 and 2. In: Berichte aus dem Institut fur Meereskunde an der Chritian-Albrechts-Universitat Kiel 2nd edn. vol 177. p 31

  • Caut S, Angulo E, Courchamp F (2009) Variation in discrimination factors (D15N and D13C): the effect of diet isotopic values and applications for diet reconstruction. J Appl Ecol 46:443–453

    Article  CAS  Google Scholar 

  • Chayes F (1949) On ratio correlation in petrography. J Geol 57:239–254

    Article  Google Scholar 

  • Ehrhardt NM, Ault JS (1992) Analysis of two length-based mortality models applied to bounded catch length frequencies. Trans Am Fish Soc 121:115–122

    Article  Google Scholar 

  • Ford E (1933) An account of the herring investigations conducted at Plymouth from the years 1924 to 1933. J Mar Biol Assoc UK 19:305–384

    Article  Google Scholar 

  • Fournier DA, Sibert JR, Majkowski J, Hampton J (1990) MULTIFAN a likelihood-based method for estimating growth parameters and age composition from multiple length frequency data sets illustrated using data for southern Bluefin Tuna (Thunnus maccoyii). Can J Fish Aquat Sci 47(2):301–317. https://doi.org/10.1139/f90-032

    Article  Google Scholar 

  • Fournier DA, Hampton J, Sibert JR (1998) MULTIFAN-CL: a length-based, age-structured model for fisheries stock assessment, with application to south pacific albacore, Thunnus alalunga. Can J Fish Aquat Sci 55:2105–2116

    Article  Google Scholar 

  • Francis RICC (1990) Back-calculation of fish length: a critical review. J Fish Biol 36:883–902

    Article  Google Scholar 

  • Froese R, Pauly D (2000) Fishbase 2000: concepts, design and data sources. ICLARM, Los Baños, p 344

    Google Scholar 

  • Froese R, Pauly D (eds) (2017) FishBase. www.fishbase.org, version (06/2017)

  • García-Carreras B, Jennings S, Le Quesne WJF (2016) Predicting reference points and associated uncertainty from life histories for risk and status assessment. ICES J Mar Sci 73:483–493. https://doi.org/10.1093/icesjms/fsv195

    Article  Google Scholar 

  • Garrido S, Ben-Hamadou R, Santos AMP, Ferreira S, Teodósio MA, Cotano U, Irigoien X, Peck MA, Saiz E, Ré P (2015) Born small, die young: intrinsic, size-selective mortality in marine larval fish. Sci Rep 5:17065

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Gayanilo FC Jr, Sparre P, Pauly D (2005) FAO-ICLARM stock assessment tools II (FiSAT II) revised version user’s guide. In: FAO computerized information series (Fisheries) No 8, FAO, Revised version Rome

  • Gayanilo JF, Sparre P, Pauly D (1995) FAO/ICLARM stock assessment tools (FiSAT) user’s guide. In: FAO Report No 8, Rome, p 126

  • Grønkjær P, Skov C, Berg S (2004) Otolith-based analysis of survival and size-selective mortality of stocked 0 + year pike related to time of stocking. J Fish Biol 64:1625–1637. https://doi.org/10.1111/j.0022-1112.2004.00421.x

    Article  Google Scholar 

  • Gulland JA (1965) Manual of methods for fish stock assessment part I fish population analysis. In: FAO fish technical paper, 2nd edn. vol 40

  • Gulland JA, Holt SJ (1959) Estimation of growth parameters for data at unequal time intervals. J du Cons 25:47–49

    Article  Google Scholar 

  • Hilborn R, Ovando D (2014) Reflections on the success of traditional fisheries management. ICES J Mar Sci 71:1040–1046. https://doi.org/10.1093/icesjms/fsu034

    Article  Google Scholar 

  • Hordyk A, Ono K, Valencia S, Loneragan N, Prince J (2015) 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. https://doi.org/10.1093/icesjms/fsu004

    Article  Google Scholar 

  • Hufnagl M, Temming A, Siegel V, Tulp I, Bolle L (2010) Estimating total mortality and asymptotic length of Crangon crangon (Linnaeus, 1758) between 1955 and 2006. ICES J Mar Sci 67:875–884

    Article  Google Scholar 

  • Hufnagl M, Huebert KB, Temming A (2013) How does seasonal variability in growth, recruitment, and mortality affect the performance of length-based mortality and asymptotic length estimates in aquatic resources? ICES J Mar Sci 70:329–341

    Article  Google Scholar 

  • Isaac VJ (1990) The accuracy of some length-based methods for fish population studies. ICLARM Tech Rep 27:81

    Google Scholar 

  • Kanaroglou PS (1996) On spurious correlation in geographical problems. Can Geogr 40:194–202

    Article  Google Scholar 

  • Kendall BW, Gray CA, Bucher D (2009) Age validation and variation in growth, mortality and population structure of Liza argentea and Myxus elongatus (Mugilidae) in two temperate Australian estuaries. J Fish Biol 75:2788–2804

    Article  PubMed  CAS  Google Scholar 

  • Kenney BC (1982) Beware of spurious self-correlations! Water Resour Res 18:1041–1048

    Article  Google Scholar 

  • Lucena-Frédou F, Kell L, Frédou T, Gaertner D, Potier M, Bach P, Travassos P, Hazin F, Ménard F (2017) Vulnerability of teleosts caught by the pelagic tuna longline fleets in South Atlantic and Western Indian Oceans. Deep Sea Res II. https://doi.org/10.1016/j.dsr2.2016.10.008 (In press)

    Article  Google Scholar 

  • Marshall MD, Holley MP, Maceina MJ (2009) Assessment of the flathead catfish population in a lightly exploited fishery in Lake Wilson, Alabama. N Am J Fish Manag 29:869–875

    Article  Google Scholar 

  • Mathews CP, Samuel M (1990) The relationship between maximum and asymptotic length in fishes. Fishbyte 8(2):14–16

    Google Scholar 

  • Mildenberger TK (2017) Single-species fish stock assessment with TropFishR. https://cran.r-project.org/web/packages/TropFishR/vignettes/tutorial.html. Accessed 01 Jan 2018

  • Mildenberger TK, Taylor MH, Wolff M (2017) TropFishR: an R package for fisheries analysis with length–frequency data. Methods Ecol Evolut. https://doi.org/10.1111/2041-210X.12791

    Article  Google Scholar 

  • Miller TJ (1997) The use of field studies to investigate selective processes in fish early life history. In: Chambers RC, Trippel EA (eds) Early life history and recruitment in fish populations. Chapman and Hall, London, pp 197–223

    Chapter  Google Scholar 

  • Mohamed S, Rao GS (1997) Seasonal growth, stock-recruitment relationship and predictive yield of the Indian squid Loligo duvauceli (Orbigny) exploited off Karnataka coast. Indian J Fish 44:319–329

    Google Scholar 

  • Palomares MLD, Pauly D (2009a) The growth of jellyfishes. Hydrobiologia 616:11–21

    Article  Google Scholar 

  • Palomares MLD, Pauly D (2009b) SeaLifeBase World Wide Web electronic publication Version (07/2009). http://www.sealifebase.org. Accessed 01 Jan 2018

  • Pauly D (1983) Some simple methods for the assessment of tropical fish stocks. FAO Fish Tech Pap 234:52

    Google Scholar 

  • Pauly D (1986) On improving operations and use of the ELEFAN programs Part II improving the estimation of L(inf). Fishbyte 4(1):18–20

    Google Scholar 

  • Pauly D (1998) Beyond our original horizons: the tropicalization of Beverton and Holt. Rev Fish Bioland Fish 8:307–334

    Article  Google Scholar 

  • Pauly D, David N (1981) ELEFAN I, a basic program for the objective extraction of growth parameters from length–frequency data. Berichte der Deutschen Wissenschaftlichen Kommission für Meeresforschung 28(4):205–211

    Google Scholar 

  • Pauly D, Greenberg A (2013) ELEFAN in R: a new tool for length–frequency analysis. Univ B C Fish Centre Res Rep 21(3):52

    Google Scholar 

  • Pauly D, Palomares ML (2005) Fishing down marine food webs: it is far more pervasive than we thought. Bull Mar Sci 76(2):197–211

    Google Scholar 

  • Pearson K (1897) On a form of spurious correlation which may arise when indices are used in the measurement of organs. Proc R Soc Lond 60:489–498

    Article  Google Scholar 

  • Petersen CGJ (1891) Eine methode zur bestimmung des alters und des wuchses der fisches. Mitt Dtsch Seefisch Ver 11:226–235

    Google Scholar 

  • Powell DG (1979) Estimation of mortality and growth parameters from the length frequency of a catch. Rapports et Procès-verbaux des Réunions, Conseil international pour L’Exploration de la Mer 175:167–169

    Google Scholar 

  • Reed JL (1921) On the correlation between any two functions and its application to the general case of spurious correlation. J Wash Acad Sci 11:449–455

    Google Scholar 

  • Sampson DB, Scott RD (2011) A spatial model for fishery age-selection at the population level. Can J of Fish Aquat Sci 68:1077–1086

    Article  Google Scholar 

  • Sampson DB, Scott RD (2012) An exploration of the shapes and stability of population-selection curves. Fish Fish 13:89–104

    Article  Google Scholar 

  • Schwamborn SHL, Ferreira BP (2002) Age structure and growth of the dusky damselfish, Stegastes fuscus, from Tamandaré reefs, Pernambuco, Brazil. Environ Biol Fish 63:79–88

    Article  Google Scholar 

  • Shelton AO, Hutchings JA, Waples RS, Keith DM, Akçakaya HR, Dulvy NK (2015) Maternal age effects on Atlantic cod recruitment and implications for future population trajectories. ICES J Mar Sci 72:1769–1778. https://doi.org/10.1093/icesjms/fsv058

    Article  Google Scholar 

  • Silva CC, Schwamborn R, Lins-Oliveira JE (2014) Population biology and color patterns of the blue land crab, Cardisoma guanhumi (Latreille 1828) (Crustacea: Gecarcinidae) in Northeastern. Braz Braz J Biol 74:949–958

    Article  PubMed  CAS  Google Scholar 

  • Sogard SM (1997) Size-selective mortality in the juvenile stage of teleost fishes: a review. Bull Mar Sci 60:1129–1157

    Google Scholar 

  • Soriano ML, Moreau, J, Hoenig JM, Pauly D (1990) New junctions for the analysis of two-phase growth of juvenile and adult fishes, with application to Nile perch ICES CM 1990/0:16 Statistics Cttee, p 13, (Mimeo)

  • Somerton DA, Kobayashi DR (1991) Robustness of the Wetherall length-based method to population disequilibrium. Fish Bull US 89:307–314

    Google Scholar 

  • Sparre P, Venema SC (1998) Introduction to tropical fish stock assessment Part 1. In: Manual FAO fisheries technical paper, (306 1, Rev 2), p 407

  • Then AY, Hoenig JM, Gedamke T, Ault J (2015) Comparison of two length-based estimators of total mortality: a simulation approach. Trans Am Fish Soc 144:1206–1219

    Article  Google Scholar 

  • Thorson JT, Munch SB, Cope JM, Gao J (2017) Predicting life history parameters for all fishes worldwide. Ecol Appl 27:2262–2276. https://doi.org/10.1002/eap.1606/full

    Article  PubMed  Google Scholar 

  • Uusi-Heikkilä S, Whiteley AR, Kuparinen A, Matsumura S, Venturelli PA, Wolter C, Slate J, Primmer CR, Meinelt T, Killen SS, Bierbach D, Polverino G, Ludwig A, Arlinghaus R (2015) The evolutionary legacy of size-selective harvesting extends from genes to populations. Evol Appl 8(6):597–620. https://doi.org/10.1111/eva.12268

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Vincenzi S, Mangel M, Crivelli AJ, Munch S, Skaug HJ (2014) Determining individual variation in growth and its Implication for life-history and population processes using the empirical bayes method. PLoS Comput Biol 10(9):e1003828. https://doi.org/10.1371/journal.pcbi.1003828

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • von Bertalanffy L (1934) Untersuchungen über die Gesetzlichkeit des Wachstums I Teil: allgemeine Grundlagen der Theorie; Mathematische und Physiologische Gesetzlichkeiten des Wachstums bei Wassertieren. Dev Genes Evol 131:613–651

    Google Scholar 

  • von Bertalanffy L (1938) A quantitative theory of organic growth (inquiries on growth laws II). Hum Biol 10:181–213

    Google Scholar 

  • Walford LA (1946) A new graphic method of describing the growth of animals. Biol Bull 90(2):141–147

    Article  PubMed  CAS  Google Scholar 

  • Wetherall A (1986) A new method for estimating growth and mortality parameters from length frequency data. Fishbyte (ICLARM/The WorldFish Center) 4(1):12–14

    Google Scholar 

  • Wetherall JA, Polovina JJ, Ralston S (1987) Estimating growth and mortality in steady-state fish stocks from length–frequency data. In: Pauly D, Morgan GR (eds) Length-based methods in fisheries research ICLARM Conference and Proceedings, vol 13, pp 53–74

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Acknowledgements

Many thanks to Daniel Pauly for initiating this work many years ago and for numerous inspiring comments. Thanks to M. L. ‘Deng’ Palomares for encouraging the formation of a new working group on this subject and for her enthusiasm regarding this new project. Many thanks to Marc Taylor and Tobias Mildenberger for their enthusiasm and competence in forming a working group to develop new bootstrap-based methods. Many thanks to the reviewers for their valuable suggestions, which helped to improve the earlier versions of this article. Many thanks to Eduardo T. Paes, Matthias Wolff, Tommaso Giarrizzo, Marc Taylor and Tobias Mildenberger for helpful comments regarding this controversial subject.

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Schwamborn, R. How reliable are the Powell–Wetherall plot method and the maximum-length approach? Implications for length-based studies of growth and mortality. Rev Fish Biol Fisheries 28, 587–605 (2018). https://doi.org/10.1007/s11160-018-9519-0

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