, Volume 831, Issue 1, pp 101–117 | Cite as

Old sins have long shadows: climate change weakens efficiency of trophic coupling of phyto- and zooplankton in a deep oligo-mesotrophic lowland lake (Stechlin, Germany)—a causality analysis

  • Géza B. SelmeczyEmail author
  • András Abonyi
  • Lothar Krienitz
  • Peter Kasprzak
  • Peter Casper
  • András Telcs
  • Zoltán Somogyvári
  • Judit Padisák


Analysis of a long-term (1994–2014) data set of phytoplankton and zooplankton in the deep, dimictic, oligo-mesotrophic Lake Stechlin (Germany) revealed trend-like changes: phytoplankton biomass and resource use efficiency increased with proliferation of heterocytic cyanobacteria (Dolichospermum spp. and Aphanizomenon flos-aquae), and those of especially large-sized zooplankton (Eudiaptomus, Eurytemora) decreased. These reverse trends are clear eutrophication symptoms and suggest a long-term trophic decoupling with potential decrease in energy transport towards higher tropic levels. Total phosphorus increased significantly over time; however, there is no known external P load for Lake Stechlin. Causality analysis enabled us to identify the primary reason of the observed changes. According to the results, stronger and longer-lasting stratification (measured as relative water column stability) drove the observed changes and the gradual regime shift was initiated by an extreme weather event—both indicating that climate change has been the crucial driver of the planktic community in this lake. Our study also documents that there might be decadal delays between cause and consequences in aquatic food webs, supporting the essential importance of long-term monitoring efforts.


Stratification patterns Trophic interactions Functional community composition Resource use efficiency Thermal pollution 



We thank Michael Sachtleben, Maren Lentz, Uta Mallok, Monika Papke, Elfie Huth and Adelheid Scheffler for their field and laboratory assistance. Data processing and causality analysis were supported by the National Research Development and Innovation Office (NKFIH K120595, NKFIH-K113147, NN118902, Hungarian National Brain Research Program II., 2017-1.2.1-NKP-2017-00002). Trend analysis of environmental and biological parameters in relation to ecosystem functioning at each trophic level was supported by the National Research Development and Innovation Office (NKFIH PD 124681).


  1. Abonyi, A., É. Ács, A. Hidas, I. Grigorszky, G. Várbíró, G. Borics & K. T. Kiss, 2018. Functional diversity of phytoplankton highlights long-term gradual regime shift in the middle section of the Danube River due to global warming, human impacts and oligotrophication. Freshwater Biology 63: 456–472.CrossRefGoogle Scholar
  2. Bednarska, A. & M. Ślusarczyk, 2013. Effect of non-toxic, filamentous cyanobacteria on egg abortion in Daphnia under various thermal conditions. Hydrobiologia 715: 151–157.CrossRefGoogle Scholar
  3. Benincà, E., J. Huisman, R. Heerkloss, K. D. Jöhnk, P. Branco, E. H. Van Nes, M. Scheffer & S. P. Ellner, 2008. Chaos in a long-term experiment with a plankton community. Nature 451: 822–825.CrossRefGoogle Scholar
  4. Bottrell, H. H., A. Duncan, Z. M. Gliwicz, E. Grygierek, A. Herzig, A. Hillbricht-Illkowskaja, H. Kurasawa, P. Larsson & T. Wenglenska, 1976. A review of some problems in zooplankton production studies. Norwegian Journal of Zoology 24: 419–456.Google Scholar
  5. Bozkurt, A. & S. Akin, 2012. First record of Eudiaptomus gracilis (G.O. Sars, 1863) (Copepoda: Diaptomida) in the inland waters of Turkey. Turkish Journal of Zoology 36: 503–511.Google Scholar
  6. Butcher, J. B., D. Nover, T. E. Johnson & M. C. Christopher, 2015. Sensitivity of lake thermal and mixing dynamics to climate change. Climatic Change 129: 295–305.CrossRefGoogle Scholar
  7. Carey, C. C., B. W. Ibelings, E. P. Hoffmann, D. P. Hamilton & J. D. Brookes, 2012. Eco-physiological adaptations that favour freshwater cyanobacteria in a changing climate. Water Research 46: 1394–1407.CrossRefGoogle Scholar
  8. Carpenter, S. R. & J. F. Kitchell, 1996. The trophic cascade in lakes. Cambridge University Press, Cambridge.Google Scholar
  9. Casper, S. J. (ed.), 1985. Lake Stechlin. A temperate oligotrophic lake. Dr. W. Junk Publishers, Dordrecht.Google Scholar
  10. Dadheech, P. K., G. B. Selmeczy, G. Vasas, J. Padisák, W. Arp, K. Tapolczai, P. Casper & L. Krienitz, 2014. Presence of potential toxin-producing cyanobacteria in an oligo-mesotrophic lake in Baltic Lake District, Germany: an ecological, genetic and toxicological survey. Toxins 6: 2912–2931.CrossRefGoogle Scholar
  11. DeMott, W. R., R. D. Gulati & E. van Donk, 2001. Daphnia food limitation in three hypereutrophic Dutch lakes: evidence for exclusion of large-bodied species by interfering filaments of cyanobacteria. Limnology and Oceanography 46: 2054–2060.CrossRefGoogle Scholar
  12. Elser, J. J. & S. R. Carpenter, 1988. Predation-driven dynamics of zooplankton and phytoplankton communities in a whole-lake experiment. Oecologia 76: 148–154.CrossRefGoogle Scholar
  13. Filstrup, C. T., H. Hillebrand, A. J. Heathcote, S. W. Harpole & J. A. Downing, 2014. Cyanobacteria dominance influences resource use efficiency and community turnover in phytoplankton and zooplankton communities. Ecology Letters 17: 464–474.CrossRefGoogle Scholar
  14. Floury, M., P. Usseglio-Polatera, M. Ferreol, C. Delattre & Y. Souchon, 2013. Global climate change in large European rivers: long-term effects on macroinvertebrate communities and potential local confounding factors. Global Change Biology 19: 1085–1099.CrossRefGoogle Scholar
  15. Gallina, N., N. Salmaso, G. Morabito & M. Beniston, 2013. Phytoplankton configuration in six deep lakes in the peri-Alpine region: are the key drivers related to eutrophication and climate? Aquatic Ecology 47: 177–193.CrossRefGoogle Scholar
  16. Ger, K. A., S. J. Teh & C. R. Goldman, 2009. Microcystin-LR toxicity on dominant copepods Eurytemora affinis and Pseudodiaptomus forbesi of the upper San Francisco Estuary. Science of The Total Environment 407: 4852–4857.CrossRefGoogle Scholar
  17. Ger, K. A., P. Arneson, C. R. Goldman & S. J. Teh, 2010. Species specific differences in the ingestion of Microcystis cells by the calanoid copepods Eurytemora affinis and Pseudodiaptomus forbesi. Journal of Plankton Research 32: 1479–1484.CrossRefGoogle Scholar
  18. Ger, K. A., L.-A. Hansson & M. Lürling, 2014. Understanding cyanobacteria–zooplankton interactions in a more eutrophic world. Freshwater Biology 59: 1783–1798.CrossRefGoogle Scholar
  19. Ghadouani, A., B. Pinel-Alloul & E. E. Prepas, 2003. Effects of experimentally induced cyanobacterial blooms on crustacean zooplankton communities. Freshwater Biology 48: 363–381.CrossRefGoogle Scholar
  20. Gonsiorczyk, T., P. Casper & R. Koschel, 1998. Phosphorus-binding forms in the sediment of an oligotrophic and an eutrophic hardwater lake of the Baltic Lake District (Germany). Water Science and Technology 37: 51–58.CrossRefGoogle Scholar
  21. Gonsiorczyk, T., P. Casper & R. Koschel, 2001. Mechanisms of phosphorus release from the bottom sediment of the oligotrophic Lake Stechlin: importance of the permanently oxic sediment surface. Archiv für Hydrobiologie 151: 203–219.CrossRefGoogle Scholar
  22. Gonsiorczyk, T., P. Casper & R. Koschel, 2003. Long-term development of the phosphorus accumulation and oxygen-consumption in the hypolimnion of oligotrophic Lake Stechlin and seasonal variations in the pore water chemistry of the profundal. Archiv für Hydrobiologie, Special Issues Advances in Limnology 58: 73–86.Google Scholar
  23. Gulati, R. D. & W. R. DeMott, 1997. The role of food quality for zooplankton: remarks on the state-of-the-art, perspectives and priorities. Freshwater Biology 38: 753–768.CrossRefGoogle Scholar
  24. Hardenbicker, P., S. Rolinski, M. Weitere & H. Fischer, 2014. Contrasting long-term trends and shifts in phytoplankton dynamics in two large rivers. International Review of Hydrobiology 99: 287–299.CrossRefGoogle Scholar
  25. Havens, K. E., T. L. East & J. R. Beaver, 1996. Experimental studies of zooplankton–phytoplankton–nutrient interactions in a large subtropical lake (Lake Okeechobee, Florida, U.S.A.). Freshwater Biology 36: 579–597.CrossRefGoogle Scholar
  26. Hillebrand, H., C.-D. Dürselen, D. Kirschtel, U. Pollingher & T. Zohary, 1999. Biovolume calculation for pelagic and benthic microalgae. Journal of Phycology 35: 403–424.CrossRefGoogle Scholar
  27. Hong, J., S. Talapatra, J. Katz, P. A. Tester, R. J. Wagett & A. R. Place, 2012. Algal toxins alter copepod feeding behavior. PLoS ONE 7: e36845.CrossRefGoogle Scholar
  28. IPCC, 2013. Climate Change 2013: The Physical Science Basis. In Stocker, T. F., et al. (eds), Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambrigde.Google Scholar
  29. Istvánovics, V., 2008. The role of biota in shaping the phosphorus cycle in lakes. Freshwater Reviews 1: 143–174.CrossRefGoogle Scholar
  30. Kasprzak, P., 1984. Bestimmung des Körperkohlenstoffs von Planktoncrustaceen. Limnologica 15: 191–194.Google Scholar
  31. Kasprzak, P. & D. Ronneberger, 1982. Vergleichende Untersuchungen zur Struktur und Dynamik des Zooplanktons im Stechlinsee, Nehmizsee und Haussee 1978/1979. Limnologica 14: 263–295.Google Scholar
  32. Kasprzak, P., C. Reese, R. Koschel, M. Schulz, I. Hambaryan & J. Mathes, 2005. Habitat characteristics of Eurytemora lacustris (Poppe, 1887) (Copepoda, Calanoida): the role of lake depth, temperature, oxygen concentration and light intensity. International Review of Hydrobiology 90: 292–309.CrossRefGoogle Scholar
  33. Kasprzak, P., T. Shatwell, M. O. Gessner, T. Gonsiorczyk, G. Kirillin, G. Selmeczy, J. Padisák & C. Engelhardt, 2017. Extreme weather event triggers cascade towards extreme turbidity in a clear-water lake. Ecosystems 20: 1407–1420.CrossRefGoogle Scholar
  34. Kirillin, G., T. Shatwell & P. Kasprzak, 2013. Consequences of thermal pollution from a nuclear plant on lake temperature and mixing regime. Journal of Hydrology 496: 47–56.CrossRefGoogle Scholar
  35. Koschel, R., J. Benndorf, G. Proft & F. Recknagel, 1983. Calcite precipitation as a natural control mechanism of eutrophication. Archiv für Hydrobiologie 98: 380–408.Google Scholar
  36. Koschel, R., T. Gonsiorczyk, L. Krienitz, J. Padisák & W. Scheffler, 2002. Primary production of phytoplankton and nutrient metabolism during and after thermal pollution in a deep, oligotrophic lowland lake (Lake Stechlin, Germany). Verhandlungen des Internationalen Verein Limnologie 28: 569–575.Google Scholar
  37. Kurmayer, R. & F. Jüttner, 1999. Strategies for the co-existence of zooplankton with the toxic cyanobacterium Planktothrix rubescens in Lake Zürich. Journal of Plankton Research 21: 659–683.CrossRefGoogle Scholar
  38. Lampert, W., 1987. Laboratory studies on zooplankton cyanobacteria interactions. New Zealand Journal of Marine and Freshwater Research 21: 483–490.CrossRefGoogle Scholar
  39. 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.CrossRefGoogle Scholar
  40. Lund, J. W. G., C. Kipling & E. D. Le Cren, 1958. The inverted microscope method of estimating algal numbers and the statistical basis of estimations by counting. Hydrobiologia 11: 143–170.CrossRefGoogle Scholar
  41. Maier, G., B. Speth, W. Arp, M. Bahnwart & P. Kasprzak, 2011. New records of the rare glacial relict Eurytemora lacustris (Poppe 1887) (Copepoda; Calanoida) in atypical lake habitats of northern Germany. Journal of Limnology 70: 145–148.CrossRefGoogle Scholar
  42. McLeod, A. I., 2011. Kendall: Kendall rank correlation and Mann-Kendall trend test. R package version 2.2. [available on internet].
  43. Mehner, T., J. Padisák, P. Kasprzak, R. Koschel & L. Krienitz, 2008. A test of food web hypotheses by exploring time series of fish, zooplankton and phytoplankton in an oligo-mesotrophic lake. Limnologica 38: 179–188.CrossRefGoogle Scholar
  44. NOAA, N. O. a. A. A., 2016. Extended reconstructed sea surface temperature (ERSST.v4). National Centers for Environmental Information.Google Scholar
  45. Oksanen, J., F. G. Blanchet, R. Kindt, P. Legendre, P. R. Minchin, R. B. O’Hara, G. L. Simpson, P. Solymos, M. Henry, H. Stevens & H. Wagner, 2015. vegan: Community Ecology Package.Google Scholar
  46. OPTICOUNT, 2008. [available on internet].
  47. Pace, M. L., J. J. Cole & S. R. Carpenter, 1998. Trophic cascades and compensation: differential responses of microzooplankton in whole-lake experiments. Ecology 79: 138–152.CrossRefGoogle Scholar
  48. Padisák, J., L. Krienitz, R. Koschel & J. Nedoma, 1997. Deep-layer autotrophic picoplankton maximum in the oligotrophic Lake Stechlin, Germany: origin, activity, development and erosion. European Journal of Phycology 32: 403–416.CrossRefGoogle Scholar
  49. Padisák, J., W. Scheffler, P. Kasprzak, R. Koschel & L. Krienitz, 2003a. Interannual changes (1994–2000) of phytoplankton of Lake Stechlin. Archiv für Hydrobiologie, Special Issues Advances in Limnology 58: 101–133.Google Scholar
  50. Padisák, J., W. Scheffler, C. Sípos, P. Kasprzak, R. Koschel & L. Krienitz, 2003b. Spatial and temporal pattern of development and decline of the spring diatom populations in Lake Stechlin in 1999. Archiv für Hydrobiologie, Special Issues Advances in Limnology 58: 135–155.Google Scholar
  51. Padisák, J., O. L. 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.CrossRefGoogle Scholar
  52. Padisák, J., É. Hajnal, L. Krienitz, J. Lakner & V. Üveges, 2010. Rarity, ecological memory, rate of floral change in phytoplankton—and the mystery of the Red Cock. Hydrobiologia 653: 45–64.CrossRefGoogle Scholar
  53. Paerl, H. W. & V. J. Paul, 2012. Climate change: links to global expansion of harmful cyanobacteria. Water Research 46: 1349–1363.CrossRefGoogle Scholar
  54. Pomati, F., C. Tellenbach, B. Matthews, P. Venail, B. W. Ibelings & R. Ptacnik, 2015. Challenges and prospects for interpreting long-term phytoplankton diversity changes in Lake Zurich (Switzerland). Freshwater Biology 60: 1052–1059.CrossRefGoogle Scholar
  55. Ptacnik, R., A. G. Solimnini, T. Andersen, T. Tamminen, P. Brettum, L. Lepistö, E. Willén & S. Rekolainen, 2008. Diversity predicts stability and resource use efficiency in natural phytoplankton communities. Proceedings of the National Academy of Sciences of the United States of America 105: 5134–5138.CrossRefGoogle Scholar
  56. R Core Team, 2015. A language and environment for statistical computing. [available on internet].
  57. Reynolds, C. S., 1989. Physical determinants of phytoplankton succiession. In Sommer, U. (ed.), Plankton ecology: succession in plankton communities. Brock-Springer Series in Contemporary Bioscience, Berlin, Heidelberg: 9–56.CrossRefGoogle Scholar
  58. Reynolds, C. S., 2006. The ecology of phytoplankton. Cambridge University Press, Cambridge.CrossRefGoogle Scholar
  59. 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.CrossRefGoogle Scholar
  60. Riccardi, N. & G. Rossetti, 2007. Eudiaptomus gracilis in Italy: how, where and why. Journal of Limnology 66: 64–69.CrossRefGoogle Scholar
  61. Rocha, O. & A. Duncan, 1985. The relationship between cell carbon and cell volume in freshwater algal species used in zooplanktonic studies. Journal of Plankton Research 7: 279–294.CrossRefGoogle Scholar
  62. Roelke, D. L., T. Zohary, K. D. Hambright & J. V. Montoya, 2007. Alternative states in the phytoplankton of Lake Kinneret, Israel (Sea of Galilee). Freshwater Biology 52: 399–411.CrossRefGoogle Scholar
  63. Rose, K. A., G. L. Swartzman, A. C. Kindig & F. B. Taub, 1988. Stepwise iterative calibration of a multi-species phytoplankton–zooplankton simulation model using laboratory data. Ecological Modelling 42: 1–32.CrossRefGoogle Scholar
  64. Sarnelle, O. & A. E. Wilson, 2005. Local adaptation of Daphnia pulicaria to toxic cyanobacteria. Limnology and Oceanography 50: 1565–1570.CrossRefGoogle Scholar
  65. Scilab Enterprises, 2012. Scilab: Free and Open Source software for numerical computation (OS, Version 5.XX) [Software]. [available from:].
  66. Selmeczy, G. B., 2017. Biodiversity of phytoplankton in Lake Stechlin (Germany). PhD thesis, University of Pannonia.Google Scholar
  67. Selmeczy, G. B., L. Krienitz, P. Casper & J. Padisák, 2018. Phytoplankton response to experimental thermocline deepening: a mesocosm experiment. Hydrobiologia 805: 259–271.CrossRefGoogle Scholar
  68. Smol, J. P., A. P. Wolfe, H. J. B. Birks, M. S. V. Douglas, V. J. Jones, A. Korhola, R. Pienitz, K. Ruhland, S. Sorvari, D. Antoniades, S. J. Brooks, M. A. Fallu, M. Hughes, B. E. Keatley, T. E. Laing, N. Michelutti, L. Nazarova, M. Nyman, A. M. Paterson, B. Perren, R. Quinlan, M. Rautio, E. Saulnier-Talbot, S. Siitoneni, N. Solovieva & J. Weckstrom, 2005. Climate-driven regime shifts in the biological communities of arctic lakes. Proceedings of the National Academy of Sciences of the United States of America 102: 4397–4402.CrossRefGoogle Scholar
  69. Sommer, U., R. Adrian, L. D. S. Domis, J. J. Elser, U. Gaedke, B. W. Ibelings, E. Jeppensen, M. Lürling, J. C. Molinero, W. M. Mooij, E. Donk & M. Winder, 2012. Beyond the plankton ecology group (PEG) model: mechanisms driving plankton succession. Annual Review of Ecology, Evolution, and Systematics 43: 429–448.CrossRefGoogle Scholar
  70. Sugihara, M. R., H. Ye, C. H. Hsieh, E. Deyle, M. Fogarty & S. Munch, 2012. Detecting causality in complex ecosystems. Science 338: 496–500.CrossRefGoogle Scholar
  71. Sukenik, A., A. Quesada & N. Salmaso, 2015. Global expansion of toxic and non-toxic cyanobacteria: effect on ecosystem functioning. Biodiversity and Conservation 24: 889–908.CrossRefGoogle Scholar
  72. Szabó, B., J. Padisák, G. B. Selmeczy, L. Krienitz, P. Casper & C. Stenger-Kovács, 2017. Spatial and temporal patterns of benthic diatom flora in Lake Stechlin, Germany. Turkish Journal of Botany 41: 211–222.CrossRefGoogle Scholar
  73. Takens, F., 1980. Detecting strange attractors in turbulence. In Rand, D. A. & L.-S. Young (eds), Dynamical Systems and Turbulence. Springer Lecture Notes in Mathematics, Vol. 898. Springer, New York, Heidelberg, Berlin: 361–381. Google Scholar
  74. Tallberg, P., J. Horppila, A. Väisänen & L. Nurminen, 1999. Seasonal succession of phytoplankton and zooplankton along a trophic gradient in a eutrophic lake—implications for food web management. Hydrobiologia 412: 81–94.CrossRefGoogle Scholar
  75. Tandonléké, R. D., J. Lazzarotto, O. Anneville & J.-C. Druart, 2009. Phytoplankton productivity increased in Lake Geneva despite phosphorus loading reduction. Journal of Plankton Research 31: 1179–1194.CrossRefGoogle Scholar
  76. Trumpickas, J., B. J. Shuter & C. K. Minns, 2009. Forecasting impacts of climate change on Great Lakes surface water temperatures. Journal of Great Lakes Research 35: 454–463.CrossRefGoogle Scholar
  77. Utermöhl, H., 1958. Zur Vervollkommnung der quantitativen Phytoplankton-Methodik. Mitteilungen der internationalen Vereinigung für theoretische und angewandte. Limnologie 9: 1–38.Google Scholar
  78. Üveges, V., K. Tapolczai, L. Krienitz & J. Padisák, 2012. Photosynthetic characteristics and physiological plasticity of an Aphanizomenon flos-aquae (Cyanobacteria, Nostocaceae) winter bloom in a deep oligo-mesotrophic lake (Lake Stechlin, Germany). Hydrobiologia 698: 263–272.CrossRefGoogle Scholar
  79. Vadstein, O., A. Jensen, Y. Olsen & H. Reinertsen, 1988. Growth and phosphorus status of limnetic phytoplankton and bacteria. Limnology and Oceanography 33: 489–503.CrossRefGoogle Scholar
  80. Von Elert, E. & T. Wolffrom, 2001. Supplementation of cyanobacterial food with polyunsaturated fatty acids does not improve growth of Daphnia. Limnology and Oceanography 46: 1552–1558.CrossRefGoogle Scholar
  81. Welch, E. B., 1992. Ecological Effects of Waste Water. CRC Press, London.Google Scholar
  82. Wilson, A. E., O. Sarnelle & A. R. Tillmanns, 2006. Effects of cyanobacterial toxicity and morphology on the population growth of freshwater zooplankton: meta-analyses of laboratory experiments. Limnology and Oceanography 51: 1915–1924.CrossRefGoogle Scholar
  83. Winberg, G. G., K. H. Mann, J. F. Talling, H. L. Golterman & P. Blaska, 1971. Symbols, units and conversion factors in studies of freshwater productivity. International Biological Program, Productivity of Fresh Waters, IBP Office, London.Google Scholar
  84. Winder, M. & D. A. Hunter, 2008. Temporal organization of phytoplankton communities linked to physical forcing. Oecologia 156: 179–192.CrossRefGoogle Scholar
  85. Winder, M. & D. E. Schindler, 2004. Climate change uncouples trophic interactions in an aquatic ecosystem. Ecology 85: 2100–2106.CrossRefGoogle Scholar
  86. Winder, M. & U. Sommer, 2012. Phytoplankton response to a changing climate. Hydrobiologia 698: 5–16.CrossRefGoogle Scholar
  87. Ye, H., E. R. Deyle, L. J. Gilarranz & G. Sugihara, 2015. Distinguishing time-delayed causal interactions using convergent cross mapping. Scientific Reports 5: 14750.CrossRefGoogle Scholar

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© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Géza B. Selmeczy
    • 1
    Email author
  • András Abonyi
    • 2
  • Lothar Krienitz
    • 3
  • Peter Kasprzak
    • 3
  • Peter Casper
    • 3
  • András Telcs
    • 4
    • 5
  • Zoltán Somogyvári
    • 5
    • 6
  • Judit Padisák
    • 1
    • 7
  1. 1.Department of LimnologyUniversity of PannoniaVeszprémHungary
  2. 2.Institute of Ecology and Botany, MTA Centre for Ecological ResearchVácrátótHungary
  3. 3.Department of Experimental LimnologyLeibniz-Institute of Freshwater Ecology and Inland FisheriesStechlinGermany
  4. 4.MTA-PE Budapest Ranking Research GroupVeszprémHungary
  5. 5.Theoretical Neuroscience and Complex Systems Research Group, Department of Computational SciencesMTA Wigner Research Center for PhysicsBudapestHungary
  6. 6.Neuromicrosystems LTDBudapestHungary
  7. 7.MTA-PE Limnoecology Research GroupVeszprémHungary

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