Skip to main content
Log in

Qualitative Assessment of the Stock Status of Freshwater Bream Abramis brama (Cyprinidae) from the Ural Stock Based on the LB-SPR Method

  • Published:
Journal of Ichthyology Aims and scope Submit manuscript

Abstract

Based on the size composition of freshwater bream Abramis brama in commercial catches from the Ural River, we have assessed the stock status of the Ural stock of the North Caspian population using the LB-SPR method. Values of the parameters of the Bertalanffy equation have been calculated for the bream from the Ural stock for the first time: the asymptotic length of an individual is 47.0 cm, the growth constant is 0.13, the hypothetical age at which the fish length would be 0 is 2.17; 50% of individuals mature at a length of 23.2 cm and 95% at a length of 28.7 cm. The estimated spawning potential ratio (0.26) is lower than the biological target (0.40) and formally indicates the state of stock overfishing.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.
Fig. 6.
Fig. 7.
Fig. 8.

Similar content being viewed by others

REFERENCES

  1. Babayan, V.K., Bobyrev, A.E., Bulgakova, T.I., et al., Metodicheskie rekomendatsii po otsenke zapasov prioritetnykh vidov vodnykh biologicheskikh resursov (Methodological Recommendations for Assessment of Resources of Priority Species of Aquatic Biological Resources), Moscow: VNIRO, 2018.

  2. Bertalanffy, L., Basic concepts in quantitative biology of metabolism, Helgol. Wiss. Meeresunters., 1964, vol. 9, pp. 5–37. https://doi.org/10.1007/BF01610024

    Article  CAS  Google Scholar 

  3. Brooks, E.N., Powers, J.E., and Cortés, E., Analytical reference points for age-structured models: application to data-poor fisheries, ICES J. Mar. Sci., 2010, vol. 67, no. 1, pp. 165–175. https://doi.org/10.1093/icesjms/fsp225

    Article  Google Scholar 

  4. Choat, J.H. and Robertson, D.R., Age-based studies on coral reef fishes, in Coral Reef Fishes: Dynamics and Diversity in a Complex Ecosystem, Sale, P.F., Ed., San Diego: Academic, 2002, pp. 57–80.

    Google Scholar 

  5. Choat, J., Axe, L., and Lou, D., Growth and longevity in fishes of the family Scaridae, Mar. Ecol.: Progr. Ser., 1996, vol. 145, pp. 33–41. https://doi.org/10.3354/meps145033

    Article  Google Scholar 

  6. Chugunova, N.I., Rukovodstvo po izucheniyu vozrasta i rosta ryb (Guide for the Study of Age and Growth of Fishes), Moscow: Akad. Nauk SSSR, 1959.

  7. Clark, W.G.W., F 35% revisited ten years later, N. Am. J. Fish. Manage., 2002, vol. 22, pp. 251–257. https://doi.org/10.1577/1548-8675(2002)022<0251:FRTYL>2.0.CO;2

    Article  Google Scholar 

  8. Coulson, P.G., Potter, I.C., and Hall, N.G., The biological characteristics of Scorpis aequipinnis (Kyphosidae) including relevant comparisons with those of other species and particularly of a heavily exploited congener, Fish. Res., 2012, vols. 125–126, pp. 272–282. https://doi.org/10.1016/j.fishres.2012.02.031

    Article  Google Scholar 

  9. FishBase, Version 12/2019, Froese R. and Pauly D., Eds., 2019. https://www.fishbase.org.

  10. Gerritsen, H.D. and McGrath, D., Precision estimates and suggested sample sizes for length-frequency data, Fish. Bull., 2007, vol. 106, pp. 116–120.

    Google Scholar 

  11. Goodyear, C.P. Spawning stock biomass per recruit in fisheries management: foundation and current use, Can. Spec. Publ. Fish. Aquat. Sci., 1993, vol. 120, pp. 67–81.

    Google Scholar 

  12. Haddon, M.J., Modelling and Quantitative Methods in Fisheries, New York: Chapman and Hall, 2011. https://doi.org/10.1201/9781439894170

  13. Hewitt, D.A. and Hoenig, J.M., Comparison of two approaches for estimating natural mortality based on longevity, Fish. Bull., 2005, vol. 103, pp. 433–437.

    Google Scholar 

  14. Hordyk, A.R., LBSPR: length-based spawning potential ratio, R package version 0.1.5. https://CRAN.R-project.org/ package=LBSPR. 2019.

  15. Hordyk, A.R., Ono, K., Sainsbury, K.J., et al., Some explorations of the life history ratios to describe length composition, spawning-per-recruit, and the spawning potential ratio, ICES J. Mar. Sci., 2015a, vol. 72, no. 1, pp. 204–216. https://doi.org/10.1093/icesjms/fst235

    Article  Google Scholar 

  16. Hordyk, A.R., Ono, K., Valencia, S.R., et al., 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., 2015b, vol. 72, no. 1, pp. 217–231. https://doi.org/10.1093/icesjms/fsu004

    Article  Google Scholar 

  17. Jensen, A.L., Beverton and Holt life history invariants result from optimal trade-off of reproduction and survival, Can. J. Fish. Aquat. Sci., 1996, vol. 53, pp. 820–822. https://doi.org/10.1139/f95-233

    Article  Google Scholar 

  18. Kuz’menko, S.V., Fishery and qualitative characteristics of the bream from the Ural River, Materialy I Vserosssiiskoi konfrentsii “Sovremennoe sostoyanie bioresursov vnutrennikh vodoemov” (Proc. I All-Russ. Conf. “Modern State of Biological Resources of Inland Reservoirs”), Moscow: Akvaros, 2011, vol. 1, pp. 448–453.

  19. Levashina, N.V., Specific distribution of bream Abramis brama (Linnaeus, 1758) in the northern part of the Caspian Sea in the present, Estestv. Nauki, 2013, no. 3, pp. 33–51.

  20. Levashina, N.V., Population development of the bream Abramis brama (Linnaeus, 1758) and its commercial use in the Volga-Caspian basin, Extended Abstract of Cand. Sci. (Biol.) Dissertation, Astrakhan: Astrakhan State Tech. Univ., 2020.

  21. Levashina, N.V. and Popov, N.N., Modern commercial and biological characteristics of the bream Abramis brama in the Volga and Ural rivers, Vopr. Rybolov., 2012, vol. 13, no. 4 (52), pp. 805–819.

  22. Mace, P. and Sissenwine, M., How much spawning is enough? Risk evaluation and biological reference points for fisheries management, Can. Spec. Publ. Fish. Aquat. Sci., 1993, vol. 120, pp. 101–118.

    Google Scholar 

  23. Maceina, M.J. and Pereira, D.L., Recruitment, in Analysis and Interpretation of Freshwater Fisheries Data, Guy, C.S. and Brown, M.L., Eds., Bethesda, MD: Am. Fish. Soc., 2007, pp. 121–185. https://doi.org/10.47886/9781888569773.ch4

  24. Mitrofanov, V.P., Dukravets, G.M., Mel’nikov, V.A., et al., Ryby Kazakhstana. Tom 3. Karpovye (Fishes of Kazakhstan, Vol. 3: Cyprinidae Fishes), Alma-Ata: Nauka, 1988.

  25. Ogle, D.H., FishR vignette—maturity schedules. 2013. https://www.derekogle.com/fishR/examples/oldFishRVignettes/Maturity.pdf.

  26. Ogle, D.H., Introductory Fisheries Analyses with R, Boca Raton, FL: CRC Press, 2016. https://doi.org/10.1201/9781315371986.

  27. Ogle, D.H., Wheeler, P., and Dinno, A., FSA: fisheries stock analysis, R package version, 2021. https://github.com/ droglenc/FSA.

  28. Petukhova, N.G., Preliminary assessment of the stock status of Atlantic bonito (Sarda sarda) in the northeastern part of the Atlantic Ocean, J. Ichthyol., 2020, vol. 60, no. 5, pp. 732–741. https://doi.org/10.1134/S0032945220050069

    Article  Google Scholar 

  29. Pravdin, I.F., Rukovodstvo po izucheniyu ryb (Guide for Study of Fishes), Moscow: Pishchevaya Prom-st’, 1966.

  30. Prince, J.D., Hordyk, A.R., Valencia, S.R., et al., Revisiting the concept of Beverton–Holt life-history invariants with the aim of informing data-poor fisheries assessment, ICES J. Mar. Sci., 2015a, vol. 72, no. 1, pp. 194– 203. https://doi.org/10.1093/icesjms/fsu011

    Article  Google Scholar 

  31. Prince, J. D., Victor, S., Kloulchad, V., et al., Length based SPR assessment of eleven Indo-Pacific coral reef fish populations in Palau, Fish. Res., 2015b, vol. 171, pp. 42–58. https://doi.org/10.1016/j.fishres.2017.12.012

    Article  Google Scholar 

  32. Prince, J.D., Lalavanua, W., Tamanitoakula, J., et al., Spawning potential surveys reveal an urgent need for effective management, Fish. Newslett., 2019, vol. 158, pp. 28–36.

    Google Scholar 

  33. Restrepo, V. and Powers, J., Precautionary control rules in US fisheries management: specification and performance, ICES J. Mar. Sci., 1999, vol. 56, pp. 846–852.

    Article  Google Scholar 

  34. Rikhter, V.A. and Efanov, V.N., An approach to evaluation of natural mortality of fish populations, Tr. Atl. Nauchno-Issled. Inst. Rybn. Khoz. Okeanogr., 1977, no. 73, pp. 75–77.

  35. Roff, D.A., The evolution of life history parameters in teleosts, Can. J. Fish. Aquat. Sci., 1984, vol. 41, pp. 989–1000.

    Article  Google Scholar 

  36. Shibaev, S.V., Golubkova, T.A., and Ryabchun, V.A., Cohort analysis of population dynamics of the common bream (Abramis brama L.) in the Vistula (Kaliningrad) Bay of the Baltic Sea, Izv. Kaliningrad. Gos. Tekh. Univ., 2012, no. 24, pp. 95–102.

  37. Sudakov, G.A., Vlasenko, A.D., Khodorevskaya R.P., et al., Instruktsii po sboru i pervichnoi obrabotke materialov vodnykh bioresursov Kaspiiskogo basseina i sredy ikh obitaniya (Instructions for Sampling and Primary Processing of Materials of Aquatic Bioresources from the Caspian Basin and Their Environment), Astrakhan: Kasp. Nauchno-Issled. Inst. Rybn. Khoz., 2011.

  38. Tanasiichuk, N.P., The bream of the North Caspian Sea: distribution, change in age composition, and impact of fishing on the population composition, Tr. Kasp. Nauchno-Issled. Inst. Rybn. Khoz. Okeanogr., 1959, vol. 15, pp. 3–37.

    Google Scholar 

  39. Then, A.Y., Honeig, J.M., Hall, N.G., and Hewitt, D.A., Evaluating the predictive performance of empirical estimators of natural mortality rate using information on over 200 fish species, ICES J. Mar. Sci., 2015, vol. 72, no. 1, pp. 82–92. https://doi.org/10.1093/icesjms/fsu136

    Article  Google Scholar 

  40. Thorson, J., FishLife: predict life history parameters for any fish, R package version 2.0.0, 2019. http://github.com/ James-Thorson/FishLife.

  41. Thorson, J.T., Munch, S.B., Cope, J.M., and Gao, J., Predicting life history parameters for all fishes worldwide, Ecol. Appl., 2017, vol. 27, no. 8, pp. 2262–2276. http://onlinelibrary. wiley.com/doi/10.1002/eap.1606/full.

    Article  Google Scholar 

  42. Walters, C.J. and Martell, S.J.D., Fisheries Ecology and Management, Princeton: Princeton Univ. Press, 2004.

    Google Scholar 

  43. Zhang, C.I. and Megrey, B.A., A revised Alverson and Carney model for estimating the instantaneous rate of natural mortality, Trans. Am. Fish. Soc., 2006, vol. 135, no. 3, pp. 620–633. https://doi.org/10.1577/T04-173.1

    Article  Google Scholar 

  44. Zykov, L.A., Bioekologicheskie aspekty teorii estestvennoi smertnosti ryb (Bioecological Aspects of the Theory of Natural Mortality of Fishes), Astrakhan: Astrakhan. Gos. Univ., 2005.

Download references

ACKNOWLEDGMENTS

The authors are grateful to the developer of the LB-SPR method and LB-SPR software package A. Hordyk (Centre for Fish, Fisheries and Aquatic Ecosystems Research), as well as to N.G. Petukhova (Russian Federal Research Institute of Fishery and Oceanography) for advice on the application of the method and interpretation of the results.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to I. A. Safaraliev.

Ethics declarations

The authors declare that they have no conflict of interests.

Additional information

Translated by D. Zabolotny

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Safaraliev, I.A., Popov, N.N. Qualitative Assessment of the Stock Status of Freshwater Bream Abramis brama (Cyprinidae) from the Ural Stock Based on the LB-SPR Method. J. Ichthyol. 62, 476–486 (2022). https://doi.org/10.1134/S0032945222030134

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S0032945222030134

Keywords:

Navigation