Skip to main content
Log in

Coupling high-resolution measurements to a three-dimensional lake model to assess the spatial and temporal dynamics of the cyanobacterium Planktothrix rubescens in a medium-sized lake

  • PHYTOPLANKTON
  • Published:
Hydrobiologia Aims and scope Submit manuscript

Abstract

In a medium-sized pre-alpine lake (North Italy) the cyanobacterium Planktothrix rubescens has strongly dominated the phytoplankton assemblage since 2000, similar to many pre-alpine lakes, despite improvements in water quality. The objective of this study was to determine the factors governing the spatial distribution of P. rubescens, including the major hydrodynamic processes and the influence of long-term reduction in nutrient concentrations during a period of climate warming. We used an intensive field campaign conducted from February 2010 to January 2011, to evaluate distributions of phytoplankton phyla, as well as P. rubescens, using spectrally resolved fluorescence measurements. These data provided highly spatially and temporally resolved phytoplankton population data suitable to calibrate and validate a coupled three-dimensional hydrodynamic (ELCOM) and ecological model (CAEDYM) of the lake ecosystem. The simulations revealed the fundamental role of physiological features of P. rubescens that led to observed vertical patterns of distribution, notably a deep chlorophyll maximum, and a strong influence of lake hydrodynamic processes, particularly during high-discharge inflows in summer stratification. The simulations are used to examine growth-limiting factors that help to explain the increased prevalence of P. rubescens during re-oligotrophication.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  • Ambrosetti, W. & L. Barbanti, 1999. Deep water warming in lakes: an indicator of climatic change. Journal of Limnology 58: 1–9.

    Article  Google Scholar 

  • American Public Health Association (APHA), 1992. Standard Methods for Examination of Water and Wastewater, 18th ed. American Public Health Association, Washington, DC.

    Google Scholar 

  • Arhonditsis, G. B. & M. T. Brett, 2004. Evaluation of the current state of mechanistic aquatic biogeochemical modelling. Marine Ecology Progress Series 271: 13–26.

    Article  Google Scholar 

  • Arhonditsis, G. B., S. S. Qian, C. A. Stow, E. C. Lamon & K. H. Reckhow, 2007. Eutrophication risk assessment using Bayesian calibration of process-based models: application to a mesotrophic lake. Ecological Modelling 208: 215–229.

    Article  Google Scholar 

  • Balestrini, R., L. Galli & G. Tartari, 2000. Wet and dry atmospheric deposition at prealpine and alpine site in Northern Italy. Atmospheric Environment 4: 1455–1470.

    Article  Google Scholar 

  • Beutler, M., K. H. Wiltshire, B. Meyer, C. Moldaenke, C. Lüring, M. Meyerhöfer, U. P. Hansen & H. Dau, 2002. A fluorometric method for the differentiation of algal populations in vivo and in situ. Photosynthesis Research 72: 39–53.

    Article  PubMed  CAS  Google Scholar 

  • Boegman, L., J. Imberger, G. N. Ivey & J. P. Antenucci, 2003. High-frequency internal waves in large stratified lakes. Limnology and Oceanography 48: 895–919.

    Article  Google Scholar 

  • Bright, D. I. & A. E. Walsby, 2000. The daily integral of growth by Planktothrix rubescens calculated from growth rate in culture and irradiance in Lake Zürich. New Phytologist 146: 301–316.

    Google Scholar 

  • Brookes, J. D. & C. C. Carey, 2011. Resilience to Bloom. Science 334: 46–47.

    Article  PubMed  CAS  Google Scholar 

  • Bruce, L. C., D. Hamilton, J. Imberger, G. Gal, M. Gophen, T. Zohary & K. D. Hambright, 2006. A numerical simulation of the role of zooplankton in C, N and P cycling in Lake Kinneret, Israel. Ecological Modelling 193: 412–436.

    Google Scholar 

  • Bürgi, H. & P. Stadelmann, 2002. Change of phytoplankton composition and biodiversity in Lake Sempach before and during restoration. Hydrobiologia 469: 33–48.

    Article  Google Scholar 

  • Carmichael, W. W., 2001. Health effects of toxin producing cyanobacteria: the ‘CyanoHABS’. Human and Ecological Risk Assessment 7: 1393–1407.

    Article  Google Scholar 

  • Copetti, D., G. Tartari, G. Morabito, A. Oggioni, E. Legnani & J. Imberger, 2006. A biogeochemical model of the Lake Pusiano (North Italy) and its use in the predictability of phytoplankton blooms: first preliminary results. Journal of Limnology 65: 59–64.

    Article  Google Scholar 

  • Cuypers, Y., B. Vinçon-Leite, A. Groleau, B. Tassin & J. F. Humbert, 2011. Impact of internal waves on the spatial distribution of Planktothrix rubescens (cyanobacteria) in an alpine lake. The ISME Journal 5: 580–589.

    Article  PubMed  CAS  Google Scholar 

  • D’Alelio, D., A. Gandolfi, A. Boscaini, G. Flaim, M. Tolotti & N. Salmaso, 2011. Planktothrix populations in subalpine lakes: selection for strains with strong gas vesicles as a function of lake depth, morphometry and circulation. Freshwater Biology 56: 1481–1493.

    Article  Google Scholar 

  • Dokulil, M. T. & K. Teubner, 2000. Cyanobacterial dominance in lakes. Hydrobiologia 438: 1–12.

    Article  CAS  Google Scholar 

  • Eilers, P. H. & J. J. Goeman, 2004. Enhancing scatterplots with smoothed densities. Bioinformatics 20: 623–628.

    Google Scholar 

  • Elliot, J. A., 2010. The seasonal sensitivity of Cyanobacteria and other phytoplankton to changes in flushing rate and water temperature. Global Change Biology 16: 864–876.

    Article  Google Scholar 

  • Ernst, B., S. J. Hoeger, E. O’Brien & D. R. Dietrich, 2009. Abundance and toxicity of Planktothrix rubescens in the pre-alpine Lake Ammersee, Germany. Harmful Algae 8: 329–342.

    Article  CAS  Google Scholar 

  • Feuillade, J., M. Feuillade & P. Blanc, 1990. Alkaline phosphatase activity fluctuactions and associated factors in a eutrophic lake dominated by Oscillatoria rubescens. Hydrobiologia 207: 233–240.

    Article  CAS  Google Scholar 

  • Gal, G., M. R. Hipsey, A. Parparov, U. Wagner, V. Makler & T. Zohary, 2009. Implementation of ecological modelling as an effective management and investigation tool: Lake Kinneret as a case study. Ecological Modelling 220: 1697–1718.

    Article  CAS  Google Scholar 

  • Gorham, E., J. W. G. Lund, J. E. Sanger & W. E. Dean, 1974. Some relationships between algal standing crop, water chemistry and sediment chemistry in the English lakes. Limnology and Oceanography 19: 601–617.

    Article  CAS  Google Scholar 

  • Grayson, R. B., G. Blöschl, A. W. Western & T. A. McMahon, 2002. Advances in the use of observed spatial patterns of catchment hydrological response. Advances in Water Resources 25: 1313–1334.

    Article  Google Scholar 

  • Gupta, H. V., S. Sorooshian & P. O. Yapo, 1999. Status of automatic calibration for hydrologic models: comparison with multilevel expert calibration. Journal of Hydrologic Engineering 4: 135–143.

    Article  Google Scholar 

  • Hamilton, D. P. & S. G. Schladow, 1997. Prediction of water quality in lakes and reservoirs. Part I – model description. Ecological Modelling 96: 91–110.

    Article  CAS  Google Scholar 

  • Hamilton, D. P., K. R. O’Brien, M. A. Burford, J. D. Brookes & C. G. McBride, 2010. Vertical distributions of chlorophyll in deep, warm monomictic lakes. Aquatic Sciences 72: 295–307.

    Article  CAS  Google Scholar 

  • Hipsey, M.R., 2008. The CWR Computational Aquatic Ecosystem Dynamics Model CAEDYM. User Manual. Centre for Water Research, The University of Western Australia.

  • Hodges, B. R., J. Imberger, A. Saggio & K. B. Winters, 2000. Modelling basin scale waves in a stratified lake. Limnology and Oceanography 45: 1603–1620.

    Article  Google Scholar 

  • Horsburgh, J. S., A. Spackman Jones, D. K. Stevens, D. G. Tarboton & N. O. Mesner, 2010. A sensor network for high frequency estimation of water quality constituent fluxes using surrogates. Environmental Modelling & Software 25: 1031–1044.

    Article  Google Scholar 

  • Howarth, R. J. & S. A. M. Earle, 1979. Application of a generalized power transformation to geochemical data. Mathematical Geology 11: 45–62.

    Article  CAS  Google Scholar 

  • Huisman, J. M., H. C. P. Matthijs & P. M. Visser, 2005. Harmful Cyanobacteria. Springer Aquatic Ecology Series 3, Dordrecht, The Netherlands.

  • Ibelings, B. W., M. Vonk, F. J. Los, D. T. Van Der Molen & W. M. Mooij, 2003. Fuzzy modeling of cyanobacterial surface water-blooms, validation with NOAA-AVHRR satellite images. Ecological Applications 13: 1456–1472.

    Article  Google Scholar 

  • Krivtsov, V., J. Corliss, E. Bellinger & D. Sigee, 2000. Indirect regulation rule for consecutive stages of ecological succession. Ecological Modelling 133: 73–82.

    Article  Google Scholar 

  • Laval, B., J. Imberger, B. R. Hodges & R. Stocker, 2003a. Modeling circulation in lakes: spatial and temporal variations. Limnology and Oceanography 48: 983–994.

    Article  Google Scholar 

  • Laval, B., B. R. Hodges & J. Imberger, 2003b. Reducing numerical diffusion effects with pycnocline filter. Journal of Hydraulic Engineering 129: 215–224.

    Article  Google Scholar 

  • Leboulanger, C., U. Dorigo, S. Jacquet, B. Leberre, G. Paolini & J.-F. Humbert, 2002. Application of a submersible spectrofluorometer for rapid monitoring of freshwater cyanobacterial blooms: a case study. Aquatic Microbial Ecology 30: 83–89.

    Article  Google Scholar 

  • Legnani, E., D. Copetti, A. Oggioni, G. Tartari, M. T. Palumbo & G. Morabito, 2005. Planktothrix rubescens seasonal and vertical distribution in Lake Pusiano (North Italy). Journal of Limnology 64: 61–73.

    Article  Google Scholar 

  • Livingstone, D. M., 2003. Impact of secular climate change on the thermal structure of a large temperate central European lake. Climatic Change 57: 205–225.

    Article  Google Scholar 

  • Mackay, E., D. J. Ian, A. M. Folkard & S. J. Thackeray, 2011. Transition zones in small lakes: the importance of dilution and biological uptake on lake-wide heterogeneity. Hydrobiologia 678: 85–97.

    Article  CAS  Google Scholar 

  • Mellard, J. P., K. Yoshiyama, E. Litchman & C. A. Klausmeier, 2011. The vertical distribution of phytoplankton in stratified water columns. Journal of Theoretical Biology 269: 16–30.

    Article  PubMed  Google Scholar 

  • Mieleitner, J. & P. Reichert, 2008. Modelling functional groups of phytoplankton in three lakes of different trophic state. Ecological Modelling 211: 279–291.

    Article  Google Scholar 

  • Missaghi, S. & M. Hondzo, 2010. Evaluation and application of a three–dimensional water quality model in a shallow lake with complex morphometry. Ecological Modelling 221: 1512–1525.

    Article  CAS  Google Scholar 

  • Mooij, W. M., et al., 2010. Challenges and opportunities for integrating lake ecosystem modelling approaches. Aquatic Ecology 44: 633–667.

    Article  Google Scholar 

  • Nash, J. E. & J. V. Sutcliffe, 1970. River flow forecasting through conceptual models. Part I. A discussion of principles. Journal of Hydrology 10: 282–290.

    Article  Google Scholar 

  • Padisák, J., L. O. Crossetti & L. Naselli-Flores, 2009. Use and misuse in the application of the phytoplankton functional classification: a critical review with updates. Hydrobiologia 621: 1–19.

    Article  Google Scholar 

  • Paerl, H. W. & J. Huisman, 2008. Blooms like it hot. Science 320: 57–58.

    Article  PubMed  CAS  Google Scholar 

  • Pannard, A., B. E. Beisner, D. F. Bird, J. Braun, D. Planas & M. Bormans, 2011. Recurrent internal waves in a small lake: potential ecological consequences for metalimnetic phytoplankton populations. Limnology & Oceanography: Fluids & Environments 1: 91–109.

    Google Scholar 

  • Reynolds, C. S., 1971. The ecology of planktonic blue-green algae in the North Shropshire meres. Field Studies 3: 409–432.

    Google Scholar 

  • Reynolds, C. S., 2006. The Ecology of Phytoplankton. Cambridge University Press, Cambridge.

    Book  Google Scholar 

  • Reynolds, C. S., V. Huszar, C. Kruk, L. Naselli-Flores & S. Melo, 2002. Towards a functional classification of the freshwater phytoplankton. Journal of Plankton Research 24: 417–428.

    Article  Google Scholar 

  • Rigosi, A., R. Marcé, C. Escot & F. J. Rueda, 2011. A calibration strategy for dynamic succession models including several phytoplankton groups. Environmental Modelling & Software 26: 697–710.

    Google Scholar 

  • Rinke, K., P. Yeates & K. O. Rothhaupt, 2010. A simulation study of the feedback of phytoplankton on thermal structure via light extinction. Freshwater Biology 55: 1674–1693.

    Google Scholar 

  • Robson, B. J. & D. P. Hamilton, 2004. Three-dimensional modelling of a Microcystis bloom event in the Swan River estuary, Western Australia. Ecological Modelling 174: 203–222.

    Article  CAS  Google Scholar 

  • Robson, B. J., D. P. Hamilton, I. T. Webster & T. Chan, 2008. Ten steps applied to development and evaluation of process-based biogeochemical models of estuaries. Environmental Modelling & Software 23: 369–384.

    Article  Google Scholar 

  • Salerno, F. & G. Tartari, 2009. A coupled approach of surface hydrological modelling and Wavelet Analysis for understanding the baseflow components of river discharge in karst environments. Journal of Hydrology 376: 295–306.

    Article  Google Scholar 

  • Salmaso, N., 2010. Long-term phytoplankton community changes in a deep subalpine lake: responses to nutrient availability and climatic fluctuations. Freshwater Biology 55: 825–846.

    Article  Google Scholar 

  • Serra, T., J. Vidal, J. Colomer, X. Casamitjana & M. Soler, 2007. The role of surface vertical mixing in phytoplankton distribution in a stratified reservoir. Limnology and Oceanography 52: 620–634.

    Article  Google Scholar 

  • Trolle, D., H. Skovgaard & E. Jeppesen, 2008. The Water Framework Directive: setting the phosphorus loading target for a deep lake in Denmark using the 1D lake ecosystem model DYRESM–CAEDYM. Ecological Modelling 219: 138–152.

    Article  CAS  Google Scholar 

  • Van Nes, E. H. & M. Scheffer, 2005. A strategy to improve the contribution of complex simulation models to ecological theory. Ecological Modelling 185: 153–164.

    Article  Google Scholar 

  • Vilhena, L. C., I. Hillmer & J. Imberger, 2010. The role of climate change in the occurrence of algal blooms: Lake Burragorang, Australia. Limnology and Oceanography 55: 1188–1200.

    Article  Google Scholar 

  • Vuillermoz, E., E. Legnani, D. Copetti & G. Tartari, 2006. Limnological evolution of Pusiano Lake (1972–2004). Verhandlungen des Internationalen Verein Limnologie 29: 2009–2014.

    Google Scholar 

  • Walsby, A. E. & M. J. Booker, 1980. Changes in buoyancy of a planktonic blue-green alga in response to light intensity. European Journal of Phycology 15: 311–319.

    Article  Google Scholar 

  • Walsby, A. E. & F. Schanz, 2002. Light-dependent growth rate determines changes in the population of Planktothrix rubescens over the annual cycle in Lake Zurich, Switzerland. New Phytologist 154: 671–687.

    Article  Google Scholar 

  • Walsby, A. E., P. K. Hayes, R. Boje & L. J. Stal, 1997. The selective advantage of buoyancy provided by gas vesicles for planktonic cyanobacteria in the Baltic Sea. New Phytologist 136: 407–417.

    Article  Google Scholar 

  • Walsby, A. E., F. Schanz & M. Schmid, 2006. The Burgundy-blood phenomenon: a model of buoyancy change explains autumnal waterblooms of Planktothrix rubescens in Lake Zurich. New Phytologist 169: 109–122.

    Article  PubMed  Google Scholar 

  • Wurtsbaugh, W. A., H. P. Gross, P. Budy & C. Luecke, 2001. Effects of epilimnetic versus metalimnetic fertilization on the phytoplankton and periphyton of a mountain lake with a deep chlorophyll maxima. Canadian Journal of Fisheries and Aquatic Sciences 58: 2156–2166.

    Article  Google Scholar 

  • Zhang, W. & G. B. Arhonditsis, 2009. A Bayesian hierarchical framework for calibrating aquatic biogeochemical models. Ecological Modelling 220: 2142–2161.

    Article  CAS  Google Scholar 

  • Zhang, M., H. Duan, X. Shi, Y. Yu & F. Kong, 2011. Contributions of meteorology to the phenology of cyanobacterial blooms: implications for future climate change. Water Research. doi:10.1016/j.watres.2011.11.013.

    Google Scholar 

Download references

Acknowledgments

The authors wish to thank Maurizio Maierna and Fabio Buzzi (Regional Agency for Environmental Protection, Department of Lecco—ARPAL) for the precious collaboration in phytoplankton cells identification and counting, Giuseppe Morabito (Institute of Ecosystem Study-CNR) for the support of a second Fluroprobe and Marco Seminara (University La Sapienza of Rome) for the zooplankton survey. A special thank is due to Franceso Spada, Alessandro Perotto and EPSON Meteo Centre (http://www.meteo.it/) for the computational support to modelling, to Mr. Giudici for his fundamental contribute during field activities, to Vladimir Krivtsov for kindly revealing the key-role of Diatoms in any ecosystem and to Laura Marziali for a unique and precious support.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Elisa Carraro.

Additional information

Guest editors: N. Salmaso, L. Naselli-Flores, L. Cerasino, G. Flaim, M. Tolotti & J. Padisák / Phytoplankton responses to human impacts at different scales: 16th workshop of the International Association of Phytoplankton Taxonomy and Ecology (IAP)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Carraro, E., Guyennon, N., Hamilton, D. et al. Coupling high-resolution measurements to a three-dimensional lake model to assess the spatial and temporal dynamics of the cyanobacterium Planktothrix rubescens in a medium-sized lake. Hydrobiologia 698, 77–95 (2012). https://doi.org/10.1007/s10750-012-1096-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10750-012-1096-y

Keywords

Navigation