Advertisement

Limnology

, Volume 19, Issue 1, pp 1–5 | Cite as

Lower sensitivity of cyprinid fishes to three acetylcholinesterase inhibitor pesticides: an evaluation based on no-effect concentrations

  • Yuichi Iwasaki
  • Marko Jusup
  • Kenichi Shibata
  • Takashi Nagai
  • Shosaku Kashiwada
Rapid communication Note on important and novel findings

Abstract

Researchers have suggested that cyprinid fishes are less sensitive to chemical stress than comparable fish families, yet few empirically based evaluations of this hypothesis have been conducted. In this study, we developed a generalized linear mixed model in which the no-effect concentrations (NECs; threshold concentration below which no effect on survival is predicted during prolonged exposure) of 29 fish species from 13 families exposed to an acetylcholinesterase inhibitor pesticide (carbaryl, chlorpyrifos, or malathion) were used as the response variable. The corresponding specific somatic maintenance (SSM) rates, as a size-independent proxy for fish metabolism and a categorical variable regarding whether the species is a cyprinid, were used as the predictor variables. We included SSM rates in the analysis because previous work demonstrated that they are negatively correlated with NECs. Our results indicate that the NECs for cyprinid fishes were significantly higher than those for other fishes, suggesting that cyprinids are indeed less sensitive to the three studied pesticides. Although the SSM rates were negatively related with the NECs, the actual relationship between the two was not clear, implying that the importance of SSM rates may depend on the taxonomic group tested.

Keywords

Species sensitivity Trait Tolerance Resistance Freshwater fish 

Notes

Acknowledgements

This study was supported by a Grant-in-Aid for Strategic Research Base Project for Private Universities funded by the Ministry of Education, Culture, Sport, Science, and Technology, Japan (2014–2018, No. S14111016), the Japan Science and Technology Agency's program to disseminate the Tenure Tracking System, and the Research Grant Program of Inamori Foundation. We thank multiple anonymous reviewers for providing helpful comments on previous versions of the manuscript.

References

  1. Baas J, Kooijman SALM (2015) Sensitivity of animals to chemical compounds links to metabolic rate. Ecotoxicology 24:657–663. doi: 10.1007/s10646-014-1413-5 CrossRefPubMedGoogle Scholar
  2. Bolker BM, Brooks ME, Clark CJ, Geange SW, Poulsen JR, Stevens MHH, White JSS (2009) Generalized linear mixed models: a practical guide for ecology and evolution. Trends Ecol Evol 24:127–135CrossRefPubMedGoogle Scholar
  3. Brix KV, DeForest DK, Adams WJ (2001) Assessing acute and chronic copper risks to freshwater aquatic life using species sensitivity distributions for different taxonomic groups. Environ Toxicol Chem 20:1846–1856CrossRefPubMedGoogle Scholar
  4. Development Core Team R (2014) R: a language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
  5. Faraway JJ (2006) Extending the linear model with R: generalized linear mixed effects and nonparametric regression models. Chapman & Hall/CRC, Boca RatonGoogle Scholar
  6. Hanson N, Stark JD (2012) Comparison of population level and individual level endpoints to evaluate ecological risk of chemicals. Environ Sci Technol 46:5590–5598CrossRefPubMedGoogle Scholar
  7. Hayashi TI, Kamo M, Tanaka Y (2009) Population-level ecological effect assessment: estimating the effect of toxic chemicals on density-dependent populations. Ecol Res 24:945–954CrossRefGoogle Scholar
  8. Heath AG (1995) Water pollution and fish physiology, 2nd edn. CRC Press, Boca RatonGoogle Scholar
  9. Ippolito A, Todeschini R, Vighi M (2012) Sensitivity assessment of freshwater macroinvertebrates to pesticides using biological traits. Ecotoxicology 21:336–352. doi: 10.1007/s10646-011-0795-x CrossRefPubMedGoogle Scholar
  10. Iwasaki Y, Hayashi TI, Kamo M (2010) Comparison of population-level effects of heavy metals on fathead minnow (Pimephales promelas). Ecotoxicol Environ Saf 73:465–471CrossRefPubMedGoogle Scholar
  11. Iwasaki Y, Hayashi TI, Kamo M (2013) Estimating population-level HC5 for copper using a species sensitivity distribution approach. Environ Toxicol Chem 32:1396–1402. doi: 10.1002/etc.2181 CrossRefPubMedGoogle Scholar
  12. Jager T, Albert C, Preuss TG, Ashauer R (2011) General unified threshold model of survival: a toxicokinetic-toxicodynamic framework for ecotoxicology. Environ Sci Technol 45:2529–2540CrossRefPubMedGoogle Scholar
  13. Jusup M, Sousa T, Domingos T, Labinac V, Marn N, Wang Z, Klanjšček T (2017) Physics of metabolic organization. Phys Life Rev 20:1–39. doi: 10.1016/j.plrev.2016.09.001 CrossRefPubMedGoogle Scholar
  14. Kaneko T, Hasegawa S, Uchida K, Ogasawara T, Oyagi A, Hirano T (1999) Acid tolerance of Japanese dace (a cyprinid teleost) in Lake Osorezan, a remarkable acid lake. Zool Sci 16:871–877. doi: 10.2108/zsj.16.871 CrossRefGoogle Scholar
  15. Kooijman SALM, Bedaux JJM (1996) Some statistical properties of estimates of no-effect concentrations. Water Res 30:1724–1728. doi: 10.1016/0043-1354(96)00055-3 CrossRefGoogle Scholar
  16. Nisbet RM, Muller EB, Lika K, Kooijman S (2000) From molecules to ecosystems through dynamic energy budget models. J Anim Ecol 69:913–926. doi: 10.1046/j.1365-2656.2000.00448.x CrossRefGoogle Scholar
  17. Stark JD, Banks JE, Vargas R (2004) How risky is risk assessment: the role that life history strategies play in susceptibility of species to stress. Proc Nat Acad Sci USA 101:732–736CrossRefPubMedPubMedCentralGoogle Scholar
  18. Teather K, Parrott J (2006) Assessing the chemical sensitivity of freshwater fish commonly used in toxicological studies. Water Qual Res J Can 41:100–105Google Scholar
  19. Winfield IJ, Townsend CR (1991) The role of cyprinids in ecosystems. In: Winfield IJ, Nelson JS (eds) Cyprinid fishes: systematics, biology and exploitation. Springer, Netherlands, pp 552–571CrossRefGoogle Scholar
  20. Woltering DM (1984) The growth response in fish chronic and early life stage toxicity tests: a critical review. Aquat Toxicol 5:1–21. doi: 10.1016/0166-445x(84)90028-6 CrossRefGoogle Scholar

Copyright information

© The Japanese Society of Limnology 2017

Authors and Affiliations

  1. 1.Research Center for Life and Environmental SciencesToyo UniversityOuraJapan
  2. 2.Center of Mathematics for Social CreativityHokkaido UniversitySapporoJapan
  3. 3.Institute for Agro-Environmental SciencesNational Agriculture and Food Research OrganizationTsukubaJapan
  4. 4.Research Institute of Science for Safety and SustainabilityNational Institute of Advanced Industrial Science and TechnologyTsukubaJapan

Personalised recommendations