Advertisement

Aquatic Sciences

, 81:19 | Cite as

Comparison of fluorometric and microscopical quantification of phytoplankton in a drinking water reservoir by a one-season monitoring program

  • A. Hartmann
  • H. Horn
  • I. Röske
  • K. RöskeEmail author
Research Article

Abstract

Phytoplankton are key components in aquatic ecosystems and therefore an important target of monitoring analyses. Microscopical counting, although providing most detailed results, is time and labor intensive and requires highly skilled analysts. In situ spectral fluorescence measurements provide a much faster analysis with a higher spatiotemporal resolution. A one-season survey of phytoplankton assemblages was performed in order to compare the results of the spectrofluorometric measurements to classical microscopical determination in different sections of a drinking water reservoir. The investigations were performed with the spectrofluorometer FluoroProbe (FP) by bbe Moldaenke GmbH (Kiel, Germany), which is designed to discriminate among diatoms, green algae, Cryptophyta and cyanobacteria. The results of phytoplankton quantification as revealed by total chlorophyll a (Chla) measurements with the FP and total biovolumes determined by microscopy showed a good correlation.The accordance between the two approaches was best for diatoms and much lower for the other spectral groups. The proportion of green algae was generally overestimated by FP measurements in comparison to biovolumes. Contrary, the percentage of cyanobacteria was often underestimated by FP compared to microscopical analyses. A clear underestimation of cyanobacteria by FP measurements even at high abundances of Microcystis sp. was observed in two samples. No influence of species composition on the congruence between microscopical analyses and FP measurements was detected.

Keywords

Phytoplankton composition Monitoring FluoroProbe Spectral fluorescence 

Notes

Acknowledgements

The authors thank A. Börner for her contribution to microscopical counting, H. Herrling and F. Ludwig for their assistance in sampling and the Saxonian State reservoir administration for general and organizational support. The study was financed by the Saxonian Academy of Sciences within the long-term research project “Biotic Structure of Reservoirs”. A. Hartmann was supported by grant no.100155061 by the European Social Fund.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

References

  1. Beutler M, Wiltshire K, Meyer B, Moldaenke C, Lüring C, Meyerhöfer M, Hansen U-P, Dau H (2002) A fluorometric method for the differentiation of algal populations in vivo and in situ. Photosynth Res 72:39–52.  https://doi.org/10.1023/A:1016026607048 CrossRefPubMedGoogle Scholar
  2. Beutler M, Wiltshire K, Reineke C, Hansen U-P (2004) Algorithms and practical fluorescence models of the photosynthetic apparatus of red cyanobacteria and Cryptophyta designed for the fluorescence detection of red cyanobacteria and cryptophytes. AME 35:115–129.  https://doi.org/10.3354/ame035115 CrossRefGoogle Scholar
  3. Buchaca T, Felip M, Catalan J (2005) A comparison of HPLC pigment analyses and biovolume estimates of phytoplankton groups in an oligotrophic lake. J Plankton Res 27(1):91–101.  https://doi.org/10.1093/plankt/fbh154pap CrossRefGoogle Scholar
  4. Catherine A, Escoffier N, Belhocine A, Nasri A, Hamlaoui S, Yéprémian C, Bernard CT (2012) On the use of the FluoroProbe (R), a phytoplankton quantification method based on fluorescence excitation spectra for large-scale surveys of lakes and reservoirs. Water Res 46:1771–1784.  https://doi.org/10.1016/j.watres.2011.12.056 CrossRefPubMedGoogle Scholar
  5. Chang D-W, Hobson P, Burch M, Lin T-F (2012) Measurement of cyanobacteria using in-vivo fluoroscopy—effect of cyanobacterial species, pigments and colonies. Water Res (46): 5037–5048Google Scholar
  6. Desortová B (1981) Relationship between chlorophyll-a concentration and phytoplankton biomass in several reservoirs in Czechoslovakia. Int Revue ges Hydrobiol 66(2):153–169.  https://doi.org/10.1002/iroh.19810660202 CrossRefGoogle Scholar
  7. EC (2000) European Commission Directive 2000/60/EC of the European Parliament and of the council of 23 October 2000 establishing a framework for Community action in the field of water policy. Off J Eur Commun L327: 1–72Google Scholar
  8. Escoffier N, Bernard C, Hamlaoui S, Groleau A, Catherine A (2015) Quantifying phytoplankton communities using spectral fluorescence: the effects of species composition and physiological state. J Plankton Res 1:233–247.  https://doi.org/10.1093/plankt/fbu085 CrossRefGoogle Scholar
  9. Felip M, Catalan J (2000) The relationship between phytoplankton biovolume and chlorophyll in a deep oligotrophic lake: decoupling in their spatial and temporal maxima. J Plankton Res 22(1):91–106.  https://doi.org/10.1093/plankt/22.1.91 CrossRefGoogle Scholar
  10. Ghadouani A, Smith R (2005) Phytoplankton distribution in Lake Erie as assessed by a new in situ spectrofluorometric technique. J Great Lakes Res 31:154–167.  https://doi.org/10.1016/S0380-1330(05)70311-7 CrossRefGoogle Scholar
  11. Goldman EA, Smith EM, Richardson TL (2013) Estimation of chromophoric dissolved organic matter (CDOM) and photosynthetic activity of estuarine phytoplankton using a multiple-fixedwavelength spectral fluorometer. Water Res 47:1616–1630.  https://doi.org/10.1016/j.watres.2012.12.023 CrossRefPubMedGoogle Scholar
  12. Gregor J, Maršálek B (2004) Freshwater phytoplankton quantification by chlorophyll a: a comparative study of in vitro, in vivo and in situ methods. Water Res 38(3):517–522.  https://doi.org/10.1016/j.watres.2003.10.033 CrossRefPubMedGoogle Scholar
  13. Gregor J, Geriš R, Maršálek B, Heteš J, Marvan P (2005) In situ quantification of phytoplankton in reservoirs using a submersible spectrofluorometer. Hydrobiologia 548:141–151.  https://doi.org/10.1007/s10750-005-4268-1 CrossRefGoogle Scholar
  14. Horn H, Horn W, Paul L, Uhlmann D, Röske I (2006) Drei Jahrzehnte kontinuierliche Untersuchungen an der Talsperre Saidenbach. Fakten, Zusammenhänge, Trends. Abschlussbericht zum Projekt “Langzeitstabilität der biologischen Struktur von Talsperren-Ökosystemen. Sächsische Akademie der Wissenschaften zu LeipzigGoogle Scholar
  15. Horn H, Paul L, Horn W, Uhlmann D, Röske I (2015) Climate change impeded the re-oligotrophication of the Saidenbach reservoir. Int Rev Hydrobiol 100:43–60.  https://doi.org/10.1002/iroh.201401743 CrossRefGoogle Scholar
  16. Leboulanger C, Dorigo U, Jacquet S, Le Berr B, Paolini G, Humbert J-F (2002) Application of a submersible spectrofluorometer for rapid monitoring of freshwater cyanobacterial blooms: a case study. AME 30:83–89.  https://doi.org/10.3354/ame030083 CrossRefGoogle Scholar
  17. Liu X, Huang BL, Wang L, Wei H, Li C, Huang Q (2012) High-resolution phytoplankton diel variations in the summer stratified central Yellow Sea. J Oceanogr 68:913–927.  https://doi.org/10.1007/s10872-012-0144-6 CrossRefGoogle Scholar
  18. Llewelyn CA, Gibb SW (2000) Intra-class variability in the carbon, pigment and biomineral content of prymnesiophytes and diatoms. Mar Ecol Prog Ser 193:33–44.  https://doi.org/10.3354/meps193033 CrossRefGoogle Scholar
  19. MacIntyre HL, Kana TM, Anning T, Geider RJ (2002) Photoacclimation of photosynthesis irradiance response curves and photosynthetic pigments in Microalgae and Cyanobacteria. J Phycol 38:17–38.  https://doi.org/10.1046/j.1529-8817.2002.00094.x CrossRefGoogle Scholar
  20. Mackey M, Mackey D, Higgins HW (1996) CHEMTAX—A program for estimating class abundances from chemical markers: application to HPLC measurements of phytoplankton. Mar Ecol Prog Ser 144:265–283.  https://doi.org/10.3354/meps144265 CrossRefGoogle Scholar
  21. R Development Core Team (2008) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. http://www.R-project.org/
  22. Richardson T, Lawrenz E, Pinckney J, Guajardo R, Walker E, Paerl H, MacIntyre HI (2010) Spectral fluorometric characterization of phytoplankton community composition using the Algae online analyser. Water Res 44:2461–2472.  https://doi.org/10.1016/j.watres.2010.01.012 CrossRefPubMedGoogle Scholar
  23. Rolland A, Rimet F, Jacquet S (2010) A 2-year survey of phytoplankton in the Marne reservoir (France): a case study to validate the use of an in situ spectrofluorometer by comparison with algal taxonomy and chlorophyll a measurements. Knowl Manag Aquat Ecosyst.  https://doi.org/10.1051/kmae/2010023 CrossRefGoogle Scholar
  24. See JH, Campbell L, Richardson TL, Pinckney JL, Shen R, Guinasso NL (2005) Combining new technologies for determination of phytoplankton community structure in the northern Gulf of Mexico. J Phycol 41:305–310.  https://doi.org/10.1111/j.1529-8817.2005.04132.x CrossRefGoogle Scholar
  25. Utermöhl H (1958) Zur Vervollkommnung der quantitativen Phytoplankton-Methodik. Mitt Int Verein Limnol 9:1–39Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Sächsische Akademie der Wissenschaften zu LeipzigLeipzigGermany
  2. 2.Sächsische Akademie der Wissenschaften zu Leipzig, Ökologische Station NeunzehnhainLengefeldGermany

Personalised recommendations