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Hydrobiologia

, Volume 809, Issue 1, pp 53–63 | Cite as

How length of light exposure shapes the development of riverine algal biomass in temperate rivers?

  • G. Várbíró
  • J. Padisák
  • Z. Nagy-László
  • A. Abonyi
  • I. Stanković
  • M. Gligora Udovič
  • V. B-Béres
  • G. Borics
Primary Research Paper

Abstract

The impact of cumulative daily solar radiation (CDSR) on the biomass of river phytoplankton (Chl-a) in the growing season was studied using a large dataset of rivers in the Carpathian Basin. The amount of solar radiation was cumulated over the range of 1–60 days. The CDSR–Chl-a relationship could be described by linear regression and appeared to be significant for almost all watercourses with the exception of rivers with short water residence time. To determine the most relevant time period of CDSR impacting phytoplankton biomass, the slopes of regressions were plotted against the accumulating number of days of light exposure (1–60). Two characteristic shapes were obtained: unimodal for rhithral rivers with hard substrate and steady increase for lowland potamal rivers with fine substrate. In both cases, there is an increasing tendency in the slope values with water residence time (WRT). It was demonstrated that CDSR has a pronounced impact on river phytoplankton biomass even in cases when WRT was shorter than the cumulated solar radiation period. These results indicate that development of phytoplankton within the river channel is a complex process in which meroplankton dynamics may have significant impacts. Our results have two implications: First, CDSR cannot be neglected in predictive modelling of riverine phytoplankton biomass. Second, climate models forecast increased drought with subsequently increased CDSR in several regions globally, which may trigger a rise in phytoplankton biomass in light-limited rivers with high nutrient concentrations.

Keywords

Cumulative daily solar radiation Phytoplankton Residence time 

Notes

Acknowledgements

Authors are financially supported by the GINOP-2.3.2-15-2016-00019 Project and by the MTA Postdoctoral Research Program (PD-019/2016). Partial support was provided by the Hungarian National Research, Development and Innovation Office (NKFIH K-120595).

Supplementary material

10750_2017_3447_MOESM1_ESM.docx (46 kb)
Supplementary material 1 (DOCX 45 kb)

References

  1. Abonyi, A., M. Leitão, I. Stanković, G. Borics, G. Várbíró & J. Padisák, 2014. A large river (River Loire, France) survey to compare phytoplankton functional approaches: do they display river zones in similar ways? Ecological Indicators 46: 11–22.CrossRefGoogle Scholar
  2. Angstrom, A., 1924. Solar and terrestrial radiation. Quarterly Journal of the Royal Meteorological Society 50: 121–126.CrossRefGoogle Scholar
  3. Birge, E. A., 1916. The work of the wind in warming a lake. Transactions of the Wisconsin Academy of Sciences, Arts, and Letters 18: 341–391.Google Scholar
  4. Bolgovics, Á., É. Ács, G. Várbíró, K. T. Kiss, B. A. Lukács & G. Borics, 2015. Diatom composition of the rheoplankton in a rhithral river system. Acta Botanica Croatica 74: 303–316.CrossRefGoogle Scholar
  5. Bolgovics, Á., G. Várbíró, É. Ács, Z. Trábert, K. T. Kiss, V. Pozderka, J. Görgényi, P. Boda, B. A. Lukács, Z. Nagy-László, A. Abonyi & G. Borics, 2017. Phytoplankton of rhithral rivers: its origin, diversity and possible use for quality-assessment. Ecological Indicators 81: 587–596.CrossRefGoogle Scholar
  6. Borics, G., I. Grigorszky, S. Szabó & J. Padisák, 2000. Phytoplankton associations in a small hypertrophic fishpond in East Hungary during a change from bottom-up to top-down control. The Trophic Spectrum Revisited. Springer, Netherlands: 79–90.CrossRefGoogle Scholar
  7. Borics, G., J. Görgényi, I. Grigorszky, Z. László-Nagy, B. Tóthmérész, E. Krasznai & G. Várbíró, 2014. The role of phytoplankton diversity metrics in shallow lake and river quality assessment. Ecological Indicators 45: 28–36.CrossRefGoogle Scholar
  8. Bukaveckas, P. A., A. MacDonald, A. Aufdenkampe, J. H. Chick, J. E. Havel, R. Schultz, T. R. Angradi, D. W. Bolgrien, T. M. Jicha & D. Taylor, 2011. Phytoplankton abundance and contributions to suspended particulate matter in the Ohio, Upper Mississippi and Missouri Rivers. Aquatic Sciences 73: 419–436.CrossRefGoogle Scholar
  9. Cole, J. J., N. F. Caraco & B. L. Peierls, 1992. Can phytoplankton maintain a positive carbon balance in a turbid freshwater, tidal estuary? Limnology and Oceanography 37: 1608–1617.CrossRefGoogle Scholar
  10. Dai, A., 2011. Drought under global warming: a review. WIREs Climate Change 2: 45–65.CrossRefGoogle Scholar
  11. Descy, J. P. & V. Gosselain, 1994. Development and ecological importance of phytoplankton in a large lowland river (River Meuse, Belgium). Phytoplankton in Turbid Environments: Rivers and Shallow Lakes. Springer, Netherlands: 139–155.CrossRefGoogle Scholar
  12. Descy, J. P., P. Servais, J. S. Smitz, G. Billen & E. Everbecq, 1987. Phytoplankton biomass and production in the River Meuse (Belgium). Water Research 21: 1557–1566.CrossRefGoogle Scholar
  13. Desortová, B. & P. Punčochář, 2011. Variability of phytoplankton biomass in a lowland river: response to climate conditions. Limnologica—Ecology and Management of Inland Waters 41: 160–166.CrossRefGoogle Scholar
  14. Dokulil, M. T. & U. Donabaum, 2014. Phytoplankton of the Danube river: composition and long-term dynamics. Acta Zoologica Bulgarica 7: 147–152.Google Scholar
  15. Erős, T., V. Bammer, Á. I. György, L. Pehlivanov, M. Schabuss, H. Zornig, A. Weiperth & Z. Szalóky, 2016. Typology of a Great River using fish assemblages: implications for the bioassessment of the Danube River. River Research and Applications 33: 37–49.CrossRefGoogle Scholar
  16. Graf, W., B. Csányi, P. Leitner, M. Paunovic, G. Chiriac, I. Stubauer, T. Ofenböck & F. Wagner, 2008. Macroinvertebrate. In: I. Liška, F. Wagner, J. Slobodnik, Joint Danube Survey 2—Final Scientific Report, ICPDR—International Commission for The Protection of The Danube River, Vienna, 41–47.Google Scholar
  17. Hutchinson, G. E., 1961. The paradox of the plankton. The American Naturalist 95: 137–145.CrossRefGoogle Scholar
  18. Istvánovics, V. & M. Honti, 2011. Phytoplankton growth in three rivers: the role of meroplankton and the benthic retention hypothesis. Limnology and Oceanography 56: 1439–1452.CrossRefGoogle Scholar
  19. Kirk, J. T., 1985. Light and Photosynthesis in Aquatic Ecosystems. Cambridge University Press, Cambridge: 401.Google Scholar
  20. Lengyel, E., J. Padisák & C. Stenger-Kovács, 2015. Establishment of equilibrium states and effect of disturbances on benthic diatom assemblages of the Torna-stream, Hungary. Hydrobiologia 750: 43–56.CrossRefGoogle Scholar
  21. Lucas, L. V., J. K. Thompson & L. R. Brown, 2009. Why are diverse relationships observed between phytoplankton biomass and transport time? Limnology and Oceanography 54: 381–390.CrossRefGoogle Scholar
  22. MSZ ISO 10260:1993 Water quality. Measurement of biochemical parameters. Spectrometric determination of the chlorophyll-a concentration.Google Scholar
  23. Ochs, C. A., O. Pongruktham & P. V. Zimba, 2013. Darkness at the break of noon: phytoplankton production in the Lower Mississippi River. Limnology and Oceanography 58: 555–568.CrossRefGoogle Scholar
  24. Phillips, G., O. P. Pietiläinen, L. Carvalho, A. Solimini, A. L. Solheim & A. C. Cardoso, 2008. Chlorophyll–nutrient relationships of different lake types using a large European dataset. Aquatic Ecology 42: 213–226.CrossRefGoogle Scholar
  25. Platts, W.S., 1983. Vegetation requirements for fisheries habitats. USDA Forest Service, General Technical Report INT, 157.Google Scholar
  26. Reynolds, C. S., 1984. The Ecology of Freshwater Phytoplankton. Cambridge University Press, Cambridge Reynolds.Google Scholar
  27. Reynolds, C. S., 2006. The Ecology of Phytoplankton. Cambridge University Press, Cambridge.CrossRefGoogle Scholar
  28. Reynolds, C. S. & J. P. Descy, 1996. The production, biomass and structure of phytoplankton in large rivers. Archiv für Hydrobiologie, Supplement Large Rivers 113: 161–187.Google Scholar
  29. Reynolds, C. S., A. Elliott & T. Irish, 2004. Modelling the dynamics of phytoplankton with the needs of the end user in mind. In Freshwater Forum 23: 38–47.Google Scholar
  30. R Core Team, 2016. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/.
  31. Rowell, D. P., 2009. Projected midlatitude continental summer drying: North America versus Europe. Journal of Climate 22: 2813–2833.CrossRefGoogle Scholar
  32. Rowell, D. P. & R. G. Jones, 2006. Causes and uncertainty of future summer drying over Europe. Climate Dynamics 27: 281–299.CrossRefGoogle Scholar
  33. Roy, S. & J. Chattopadhyay, 2007. Towards a resolution of ‘the paradox of the plankton’: a brief overview of the proposed mechanisms. Ecological Complexity 4: 26–33.CrossRefGoogle Scholar
  34. Schmidt, A., 1994. Main characteristics of the phytoplankton of the Southern Hungarian section of the River Danube. Phytoplankton in Turbid Environments: Rivers and Shallow Lakes. Springer, Netherlands: 97–108.CrossRefGoogle Scholar
  35. Soballe, D. M. & B. L. Kimmel, 1987. A large-scale comparison of factors influencing phytoplankton abundance in rivers, lakes, and impoundments. Ecology 68: 1943–1954.CrossRefPubMedGoogle Scholar
  36. Sommer, U., 1989. The role of competition for resources in phytoplankton succession. Plankton Ecology. Springer, Berlin Heidelberg: 57–106.CrossRefGoogle Scholar
  37. Sommer, U., Z. M. Gliwicz, W. Lampert & A. Duncan, 1986. The PEG-model of seasonal succession of planktonic events in fresh waters. Archiv für Hydrobiologie 106: 433–471.Google Scholar
  38. Stanković, I., T. Vlahović, M. Gligora Udovič, G. Várbíró & G. Borics, 2012. Phytoplankton functional and morpho-functional approach in large floodplain rivers. Hydrobiologia 698: 217–231.CrossRefGoogle Scholar
  39. Sterner, R., S. S. Kilham, F. A. Johnson, R. W. Winner, T. Keeling, R. Yeager & M. P. Farrell, 1996. Factors regulating phytoplankton and zooplankton biomass in temperate rivers. Limnology and Oceanography 41: 1572–1577.CrossRefGoogle Scholar
  40. Szász, G. 1997. Meteorológia—Mezőgazdasági Kiadó, Budapest, 267–280.Google Scholar
  41. Talling, J. F., 1957. The phytoplankton population as a compound photosynthetic system. New Phytologist 56: 133–149.CrossRefGoogle Scholar
  42. Talling, J. F., 1971. The underwater light climate as a controlling factor in the production ecology of freshwater phytoplankton. Verhandlungen des Internationalen Verein Limnologie 19: 214–243.Google Scholar
  43. Tapolczai, K., A. Bouchez, C. Stenger-Kovács, J. Padisák & F. Rimet, 2016. Trait-based ecological classifications for benthic algae: review and perspectives. Hydrobiologia 776: 1–17.CrossRefGoogle Scholar
  44. Van Nieuwenhuyse, E. E. & J. R. Jones, 1996. Phosphorus chlorophyll relationship in temperate streams and its variation with stream catchment area. Canadian Journal of Fisheries and Aquatic Sciences 53: 99–105.CrossRefGoogle Scholar
  45. Várbíró, G., É. Ács, G. Borics, K. Érces, G. Fehér, I. Grigorszky, T. Japport, G. Kocsis, E. Krasznai, K. Nagy, Z. Nagy-László & Z. Pilinszky, 2007. Use of Self-Organizing Maps (SOM) for characterization of riverine phytoplankton associations in Hungary. Archiv für Hydrobiologie 17: 383–394.Google Scholar
  46. Whitehead, P. G., A. Howard & C. Arulmani, 1997. Modelling algal growth and transport in rivers: a comparison of time series analysis, dynamic mass balance and neural network techniques. Hydrobiologia 349: 39–46.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2017

Authors and Affiliations

  1. 1.Department of Tisza River ResearchMTA Centre for Ecological Research, Danube Research InstituteDebrecenHungary
  2. 2.GINOP Sustainable Ecosystems GroupMTA Centre for Ecological ResearchTihanyHungary
  3. 3.Department of LimnologyUniversity of PannoniaVeszprémHungary
  4. 4.MTA-PE Limnoecology Research GroupVeszprémHungary
  5. 5.Hrvatske vode, Central Water Management LaboratoryZagrebCroatia
  6. 6.Department of Biology, Faculty of ScienceUniversity of ZagrebZagrebCroatia

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