Advertisement

Environmental Science and Pollution Research

, Volume 25, Issue 12, pp 11295–11302 | Cite as

MOSAIC: a web-interface for statistical analyses in ecotoxicology

  • Sandrine CharlesEmail author
  • Philippe Veber
  • Marie Laure Delignette-Muller
Aquatic organisms and biological responses to assess water contamination and ecotoxicity

Abstract

In ecotoxicology, bioassays are standardly conducted in order to measure acute or chronic effects of potentially toxic substances on reproduction, growth, and/or survival of living animals. MOSAIC, standing for MOdeling and StAtistical tools for ecotoxICology, is a user-friendly web interface dedicated to the mathematical and statistical modelling of such standard bioassay data. Its simple use makes MOSAIC a turnkey decision-making tool for ecotoxicologists and regulators. Without wasting time on extensive mathematical and statistical technicalities, users are provided with advanced and innovative methods for a valuable quantitative environmental risk assessment. MOSAIC is available at http://pbil.univ-lyon1.fr/software/mosaic/.

Keywords

Standard bioassay data Survival statistical analysis Reprotoxicity statistical analysis SSD analysis R software 

Notes

Acknowledgements

The authors thank the French National Agency for Water and Aquatic Environments (ONEMA, now denominate French Agency for Biodiversity) for its financial support in the development of the MOSAIC web-interface.

References

  1. Aldenberg T, Slob W (1993) Confidence limits for hazardous concentrations based on logistically distributed NOEC toxicity data. Ecotoxicol Environ Saf 25:48–63CrossRefGoogle Scholar
  2. Charles S, Ducrot V, Azam D, Benstead R, Brettschneider D, De Schamphelaere K, Filipe Goncalves S, Green JW, Holbech H, Hutchinson TH, Faber D, Laranjeiro F, Matthiessen P, Norrgren L, Oehlmann J, Reategui-Zirena E, Seeland-Fremer A, Teigeler M, Thome JP, Tobor Kaplon M, Weltje L, Lagadic L (2016) Optimizing the design of a reproduction toxicity test with the pond snail Lymnaea stagnalis. Regul Toxicol Pharmacol 81:47–56CrossRefGoogle Scholar
  3. Delignette-Muller ML, Dutang C (2015) fitdistrplus: an R package for fitting distributions. J Stat Softw 64(4):1–34. http://www.jstatsoft.org/v64/i04/. [Online; accessed 23-June-2017]CrossRefGoogle Scholar
  4. Delignette-Muller ML, Lopes C, Veber P, Charles S (2014) Statistical handling of reproduction data for exposure-response modeling. Environ Sci Technol 48(13):7544–7551CrossRefGoogle Scholar
  5. Delignette-Muller ML, Ruiz P, Charles S, Duchemin W, Lopes C, Kon-Kam-king G, Veber P (2016) morse: modelling tools for reproduction and survival data in ecotoxicology. https://CRAN.R-project.org/package=morse. R package version 2.2.0 [Online; accessed 23-June-2017]
  6. Ducrot V, Askem C, Azam D, Brettschneider D, Brown R, Charles S, Coke M, Collinet M, Delignette-Muller ML, Forfait-Dubuc C, Holbech H, Hutchinson T, Jach A, Kinnberg KL, Lacoste C, Le Page G, Matthiessen P, Oehlmann J, Rice L, Roberts E, Ruppert K, Davis JE, Veauvy C, Weltje L, Wortham R, Lagadic L (2014) Development and validation of an OECD reproductive toxicity test guideline with the pond snail Lymnaea stagnalis (Mollusca, Gastropoda). Regul Toxicol Pharmacol 70:605–614CrossRefGoogle Scholar
  7. Forfait-Dubuc C, Charles S, Billoir E, Delignette-Muller M (2012) Survival data analyses in ecotoxicology: critical effect concentrations, methods and models. What should we use? Ecotoxicology 12:1072–1083CrossRefGoogle Scholar
  8. Green JW, Springer TA, Staveley JP (2013) The drive to ban the NOEC/LOEC in favor of ECx is misguided and misinformed. Integr Environ Assess Manag 9:12–16CrossRefGoogle Scholar
  9. Kefford B, Nugegoda D (2006) Validating species sensitivity distributions using salinity tolerance of riverine macroinvertebrates in the southern Murray-Darling Basin (Victoria, Australia). Can J Fish Aquat Sci 63:1865–1877CrossRefGoogle Scholar
  10. Kon Kam King G, Veber P, Charles S, Delignette-Muller ML (2014) MOSAIC_SSD: a new web tool for species sensitivity distribution to include censored data by maximum likelihood. Environ Toxicol Chem/SETAC 33(9):2133–2139CrossRefGoogle Scholar
  11. OCaml (2016) http://ocaml.org/. [Online; accessed 23-June-2017]
  12. Ocsigen (2016) http://ocsigen.org/ocsigenserver/. [Online; accessed 23-June-2017]
  13. OECD (2016) Test No. 243: Lymnaea stagnalis reproduction test. OECD Guideline (July), 1–31Google Scholar
  14. PRABI (2016) http://www.prabi.fr/. [Online; accessed 23-June-2017]
  15. R Core Team (2016) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. https://www.R-project.org. [Online; accessed 23-June-2017]Google Scholar

Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Université de Lyon, Université Lyon 1, UMR CNRS 5558, Laboratoire de Biométrie et Biologie ÉvolutiveVilleurbanneFrance
  2. 2.Université de Lyon, VetAgro Sup Campus Vetérinaire de LyonMarcy l’ÉtoilesFrance

Personalised recommendations