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Ecotoxicology

, Volume 28, Issue 7, pp 732–743 | Cite as

Realistic low-doses of two emerging contaminants change size distribution of an annual flowering plant population

  • Marjo Patama
  • Regina G. BelzEmail author
  • Aki Sinkkonen
Article

Abstract

HHCB [1,3,4,6,7,8-hexahydro-4,6,6,7,8,8-hexamethylcyclopenta(g)-2-benzopyran] and 4-tert-octylphenol [4-(1,1,3,3-tetramethylbutyl)phenol] are widely used emerging contaminants that have the potential to cause adverse effects in the environment. The purpose of this study was to observe if and how environmentally realistic concentrations of these contaminants alter growth in plant populations. It was hypothesized that within an exposed Gypsophila elegans Bieb (annual baby’s breath) population especially fast-growing seedlings are impaired even when the population mean is unaffected, and small doses can cause hormesis and, thus, an increase in shoot or root length. In a dose-response experiment, an experimental population of G. elegans was established (total 15.600 seeds, 50 seeds per replicate, 24 replicates per concentration, 5.2 seedlings/cm2) and exposed to 12 doses of HHCB or 4-tert-octylphenol. After five days, shoot and root length values were measured and population averages, as well as slow- and fast-growing subpopulations, were compared with unexposed controls. Growth responses were predominantly monophasic. HHCB seemed to selectively inhibit both root and shoot elongation among slow- and fast-growing individuals, while 4-tert-octylphenol selectively inhibited both root and shoot elongation of mainly fast-growing seedlings. The ED50 values (dose causing 50% inhibition) revealed that the slow-growing seedlings were more sensitive and fast-growing seedlings less sensitive than the average of all individuals. Although there was toxicant specific variation between the effects, selective toxicity was consistently found among both slow- and fast-growing plants starting already at concentrations of 0.0067 µM, that are usually considered to be harmless. This study indicates that these contaminants can change size distribution of a plant population at low concentrations in the nM/µM range.

Keywords

Dose-response Growth stimulation Hormesis Low toxin doses Selective toxicity 

Notes

Acknowledgements

This study was conducted as part of a student exchange between the University of Helsinki and the University of Hohenheim within the framework of a project funded by the German Research Foundation (DFG, individual grant number BE4189/1-2 and BE4189/1-3). The language editing by Jessica Lloyd and the statistical advice by Prof. Dr Hans-Peter Piepho is greatly acknowledged.

Funding

This study was funded by the German Research Foundation (DFG, individual grant number BE4189/1-2 and BE4189/1-3). AS was funded by Business Finland (Tekes grant 40333/14).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Supplementary material

10646_2019_2069_MOESM1_ESM.pdf (136 kb)
Supplementary Tables

References

  1. Agathokleous E, Belz RG, Kitao M, Koike T, Calabrese EJ (2018) Does the root to shoot ratio show a hormetic response to stress? An ecological and environmental perspective. J For Res.  https://doi.org/10.1007/s11676-018-0863-7
  2. Aina R, Palin L, Citterio S (2006) Molecular evidence for benzo[a]pyrene and naphtalene genotoxicity in Trifolium repens L. Chemosphere 65:666–673.  https://doi.org/10.1016/j.chemosphere.2006.01.071 CrossRefGoogle Scholar
  3. An J, Zhou Q, Sun Y, Xu Z (2009) Ecotoxicological effects of typical personal care products on seed germination and seedling development of wheat (Triticum aestivum L.). Chemosphere 76:1428–1434.Google Scholar
  4. Belz RG (2008) Stimulation versus inhibition—bioactivity of parthenin, a phytochemical from Parthenium hysterophorus L. Dose-Response 6:80–96.  https://doi.org/10.2203/dose-response.07-007.Belz CrossRefGoogle Scholar
  5. Belz RG, Cedergreen N (2010) Parthenin hormesis in plants depends on growth conditions. Environ Exp Bot 69:293–301.  https://doi.org/10.1016/j.envexpbot.2010.04.010 CrossRefGoogle Scholar
  6. Belz RG, Piepho H-P (2012) Modeling effective dosages in hormetic dose-response studies. PLoS ONE 7(3):e33432.  https://doi.org/10.1371/journal.pone.0033432 CrossRefGoogle Scholar
  7. Belz RG, Piepho H-P (2013) Variability of hormetic dose responses of the antiauxin PCIB on Lactuca sativa in a plant bioassay. Weed Res 53:418–428.  https://doi.org/10.1111/wre.12038 CrossRefGoogle Scholar
  8. Belz RG, Piepho H-P (2014) Interspecies variability of plant hormesis by the antiauxin PCIB in a laboratory bioassay. J Plant Growth Regul 33:499–512.  https://doi.org/10.1007/s00344-013-9400-2 CrossRefGoogle Scholar
  9. Belz RG, Sinkkonen A (2016a) Selective toxin effects on faster and slower growing individuals in the formation of hormesis at the population level—a case study with Lactuca sativa and PCIB. Sci Total Environ 566-567:1205–1214.  https://doi.org/10.1016/j.scitotenv.2016.05.176 CrossRefGoogle Scholar
  10. Belz RG, Sinkkonen A (2016b) Herbicide hormesis to segregate a weed population?—a case study with Tripleurospermum perforatum (Mérat) Lainz. Julius-Kühn-Archiv 452:103–110.  https://doi.org/10.5073/jka.2016.452.014 Google Scholar
  11. Belz RG, Piepho H-P (2017) Predicting biphasic responses in binary mixtures: pelargonic acid versus glyphosate. Chemosphere 178:88–98.  https://doi.org/10.1016/j.chemosphere.2017.03.047 CrossRefGoogle Scholar
  12. Belz RG, Patama M, Sinkkonen A (2018) Low doses of six toxicants change plant size distribution in dense populations of Lactuca sativa. Sci Total Environ 631-632:510–523.  https://doi.org/10.1016/j.scitotenv.2018.02.336 CrossRefGoogle Scholar
  13. Bolz U, Hagenmeier W, Körner W (2001) Phenolic xenoestrogens in surface water, sediments, and sewage sludge from Baden-Württemberg, south-west Germany. Environ Pollut 115:291–301.  https://doi.org/10.1016/S0269-7491(01)00100-2 CrossRefGoogle Scholar
  14. Brooke D, Johnson I, Mitchell RJ, Watts C (2005) Environmental risk evaluation report: 4-tert-Octylphenol. Environment Agency, BristolGoogle Scholar
  15. Brain P, Cousens R (1989) An equation to describe dose responses where there is stimulation of growth at low doses. Weed Res 29:91–96.  https://doi.org/10.1111/j.1365-3180.1989.tb00845.x CrossRefGoogle Scholar
  16. Calabrese ED (2008) Hormesis: why it is important to toxicology and toxicologists. Environ Toxicol Chem 27:1451–1474CrossRefGoogle Scholar
  17. Calabrese ED, Howe KJ (1976) Stimulation of growth of peppermint (Metha pipertita) by phosfon, a growth retardant. Physiol Plant 37:163–165CrossRefGoogle Scholar
  18. Calabrese ED, Blain RB (2009) Hormesis and plant biology. Environ Pollut 157:42–48.  https://doi.org/10.1016/j.envpol.2008.07.028 CrossRefGoogle Scholar
  19. Castellano D, Macías F, Castellano M, Cambronero R (2001) FITOMED (automated system for the measurement of variable lengths) (Spain Patent No. P9901565)Google Scholar
  20. Cedergreen N, Ritz C, Streibig JC (2005) Improved empirical models describing hormesis. Environ Toxicol Chem 24:3166–3172.  https://doi.org/10.1897/05-014R.1 CrossRefGoogle Scholar
  21. Cedergreen N, Streibig JC, Kudsk P, Matthiasen K, Duke SO (2007) The occurrence of hormesis in plants and algae. Dose-Response 5:150–162.  https://doi.org/10.2203/dose-response.06-008.Cedergreen CrossRefGoogle Scholar
  22. Cedergreen N, Olesen CF (2010) Can glyphosate stimulate photosynthesis? Pestic Biochem Physiol 96:140–148.  https://doi.org/10.1016/j.pestbp.2009.11.002 CrossRefGoogle Scholar
  23. Chen W, Xu J, Lu S, Jiao W, Wu L, Chang AC (2013) Fates and transport of PPCPs in soil receiving reclaimed water irrigation. Chemosphere 93:2621–2630.  https://doi.org/10.1016/j.chemosphere.2013.09.088 CrossRefGoogle Scholar
  24. Chu CJ, Maestre FT, Xiao S, Weiner J, Wang YS, Duan ZH, Wang G (2008) Balance between facilitation and resource competition determines biomass-density relationships in plant populations. Ecol Lett 11:1189–1197.  https://doi.org/10.1111/j.1461-0248.2008.01228.x CrossRefGoogle Scholar
  25. Chu CJ, Weiner J, Maestre FT, Xiao S, Wang YS, Li Q, Yuan JL, Zhao LQ, Ren ZW, Wang G (2009) Positive interactions can increase size inequality in plant populations. J Ecol 97:1401–1407.  https://doi.org/10.1111/j.1365-2745.2009.01562.x CrossRefGoogle Scholar
  26. Damesa TM, Möhring J, Forkman J, Piepho HP (2018) Modeling spatially correlated and heteroscedastic errors in Ethiopian maize trials. Crop Sci 58:1575–1586.  https://doi.org/10.2135/cropsci2017.11.0693 CrossRefGoogle Scholar
  27. Duke S, Cedergreen N, Belz RG, Velini ED (2006) Hormesis: is it an important factor in’herbicide use and allelopathy? Outlooks Pest Manag 17:29–33.  https://doi.org/10.1564/16feb10 Google Scholar
  28. Hansi M, Weidenhamer JD, Sinkkonen A (2014) Plant growth responses to inorganic environmental contaminants are density-dependent: experiments with copper sulfate, barley and lettuce. Environ Pollut 184:443–448.  https://doi.org/10.1016/j.envpol.2013.09.027 CrossRefGoogle Scholar
  29. HERA Human & Environmental Risk Assessment on ingredients of Household Cleaning Products (2004) Polycyclic musks AHTN (CAS 1506-02-1) and HHCB (CAS 1222-05-05). Version 2.0. HERA. http://www.heraproject.com/files/29-hh-04-pcm%20hhcb%20hera%20human%20health%20discl%20ed2.pdf. Accessed 7 July 2017
  30. Hernando MD, Mezcua M, Gómez MJ, Malato O, Agüera A, Fernández-Alba AR (2004) Comparative study of analytical methods involving gas chromatography-mass spectrometry after derivatization and gas chromatography-tandem mass spectrometry for the determination of selected endocrine disrupting compounds in wastewaters. J Chromatogr A 1047:129–135CrossRefGoogle Scholar
  31. Höhne C, Püttmann W (2008) Occurrence and temporal variations of the xenoestrogens bisphenol A, 4-tert-octylphenol, and tech. 4-nonylphenol in two German waste water treatment plants. Environ Sci Pollut Res 15:405–416.  https://doi.org/10.1007/s11356-008-0007-2 CrossRefGoogle Scholar
  32. Klaschka U, von der Ohe PC, Bschorer A, Krezmer S, Sengl M, Letzel M (2012) Occurrences and potential risks of 16 fragrances in five German sewage treatment plants and their receiving waters. Environ Sci Pollut Res Int 20:2456–2471.  https://doi.org/10.1007/s11356-012-1120-9 CrossRefGoogle Scholar
  33. Kupper T, Berset JD, Etter-Holzer R, Furrer R, Tarradellas J (2004) Concentrations and specific loads of polycyclic musks in sewage sludge originating from a monitoring network in Switzerland. Chemosphere 54:1111–1120.  https://doi.org/10.1016/j.chemosphere.2003.09.023 CrossRefGoogle Scholar
  34. Litz NT, Müller J, Böhmer W (2007) Occurrence of polycyclic musks in sewage sludge andtheir behaviour in soils and plants. J Soils Sediments 7:36–44.  https://doi.org/10.1065/jss2006.10.187.1 CrossRefGoogle Scholar
  35. Osborne JW (2010). Improving your data transformations: applying the BoxCox transformation. Practical Assessment, Research & Evaluation 15(12). http://pareonline.net/getvn.asp?v=15&n=12
  36. Pablos MV, García-Hortigüela P, Fernández C (2015) Acute and chronic toxicity of emerging contaminants, alone or in combination, in Chlorella vulgaris and Daphnia magna. Environ Sci Pollut Res 22:5417–5424.  https://doi.org/10.1007/s11356-015-4119-1 CrossRefGoogle Scholar
  37. Perla V (2016). Data normalization for dummies using SAS®. Philadelphia Area SAS Users Group (PhilaSUG) Winter 2016 Meeting. Philadelphia University, Philadelphia, PA, USAGoogle Scholar
  38. Piepho HP (2009) Data transformation in statistical analysis of field trials with changing treatment variance. Agron J 101:865–869.  https://doi.org/10.2134/agronj2008.0226x CrossRefGoogle Scholar
  39. Płociniczak T, Sinkkonen A, Romantschuk M, Piotrowska-Seget Z (2013) Characterization of Enterobacter intermedius MH8b and its use for the enhancement of heavy metals uptake by Sinapis alba L. Appl Soil Ecol 63:1–7.  https://doi.org/10.1016/j.apsoil.2012.09.009 CrossRefGoogle Scholar
  40. Płociniczak T, Sinkkonen A, Romantschuk M, Sułowicz S, Piotrowska-Seget Z (2016) Rhizospheric bacterial strain Brevibacterium casei MH8a colonizes plant tissues and enhances Cd, Zn, Cu phytoextraction by white mustard. Front Plant Sci 7:1–10.  https://doi.org/10.3389/fpls.2016.00101 Google Scholar
  41. Rodriguez M, Snoek LB, Riksen JA, Bevers RP, Kammenga JE (2012) Genetic variation for stress-response hormesis in C. elegans lifespan. Exp Gerontol 47:581–587.  https://doi.org/10.1016/j.exger.2012.05.005 CrossRefGoogle Scholar
  42. Sauvé S, Desrosiers M (2014) A review of what is an emerging contaminant. Chem Cent J 8:1–7.  https://doi.org/10.1186/1752-153X-8-15 CrossRefGoogle Scholar
  43. Schabenberger O, Tharp BE, Kells JJ, Penner D (1999) Statistical test for hormesis and effective dosage in herbicide dose-response. Agron J 91:713–721.  https://doi.org/10.2134/agronj1999.914713x CrossRefGoogle Scholar
  44. Seber G, Wild C (1989) Nonlinear regression. John Wiley & Sons, New YorkGoogle Scholar
  45. Streibig JC (1988) Herbicide bioassay. Weed Res 28:479–484.  https://doi.org/10.1111/j.1365-3180.1988.tb00831.x CrossRefGoogle Scholar
  46. Streibig, JC, Jensen JE (2000) Actions of herbicides in mixture. In: Cobb AH, Kirkwood RC (eds) Herbicides and their mechanisms of action. Sheffield Academic Press Ltd, Sheffield, p 295Google Scholar
  47. Sinkkonen A (2001) Density-dependent chemical interference—an extension of the biological response model. J Chem Ecol 27:1513–1523.  https://doi.org/10.2203/dose-response.09-045.Sinkkonen CrossRefGoogle Scholar
  48. Sinkkonen A (2003) A model describing chemical interference caused by decomposing residues at different densities of growing plants. Plant Soil 250:315–322.  https://doi.org/10.1023/A:1022841503476 CrossRefGoogle Scholar
  49. Sinkkonen A, Strömmer R, Penttinen O-P (2008) Low toxicant concentrations decrease the frequency of fast-growing seedlings at high densities of annual baby’s breath (Gypshophila elegans). Environ Pollut 153:523–525.  https://doi.org/10.1016/j.envpol.2008.02.020 CrossRefGoogle Scholar
  50. Sinkkonen A, Penttinen O-P, Strömmer R (2009) Testing the homogenizing effect of low copper sulfate concentrations on the size distribution of Portulaca oleracea seedlings in vitro. Sci Total Environ 407:4461–4464.  https://doi.org/10.1016/j.envpol.2008.02.020 CrossRefGoogle Scholar
  51. Sinkkonen A, Myyrä M, Penttinen O-P, Rantalainen A-L (2011) Selective toxicity at low doses: experiment with three plant species and toxicants. Dose-Response 9:130–143.  https://doi.org/10.2203/dose-response.09-045.Sinkkonen CrossRefGoogle Scholar
  52. Tao X, Tang C, Wu P, Han Z, Zhang C, Zhang Y (2011) Occurrence and behavior of nonylphenol and octylphenol in Nanming River, Guiyang City, China. J Environ Monit 13:3269–3276.  https://doi.org/10.1039/c1em10471c CrossRefGoogle Scholar
  53. Vichi P, Tritton TR (1989) Stimulation of growth in human and murine cells by adriamycin. Cancer Res 49:2679–2682Google Scholar
  54. Weidenhamer JD, Hartnett DC, Romeo JT (1989) Density-dependent phytotoxicity: distinguishing resource competition and allelopathic interference in plants. J Appl Ecol 26:613–624CrossRefGoogle Scholar
  55. Yu D, Sinkkonen A, Hui N, Kurola JM, Kukkonen S, Parikka P, Vestberg M, Romantschuk M (2015) Molecular profile of microbiota of Finnish commercial compost suppressive against Pythium disease on cucumber plants. Appl Soil Ecol 92:47–53.  https://doi.org/10.1016/j.apsoil.2015.03.005 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.University of Hohenheim, Hans-Ruthenberg Institute, Agroecology UnitStuttgartGermany
  2. 2.University of Helsinki, Department of Environmental Sciences, Environmental Ecology UnitLahtiFinland

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