Climatic Change

, Volume 141, Issue 2, pp 347–361 | Cite as

Is the future of large shallow lakes blue-green? Comparing the response of a catchment-lake model chain to climate predictions

  • Fabien CremonaEmail author
  • Sirje Vilbaste
  • Raoul-Marie Couture
  • Peeter Nõges
  • Tiina Nõges


We constructed a model chain into which regional climate-related variables (air temperature, precipitation) and a lake’s main tributary hydrological indicators (river flow, dissolved inorganic carbon) were employed for predicting the evolution of planktonic blue-green algae (cyanobacteria) and zooplankton (rotifer) biomass in that lake for the mid-21st century. Simulations were based on the future climate predicted under both the Representative Concentration Pathways 4.5 and 8.5 scenarios which, combined with three realistic policy-making and basin land-use evolution lead to six scenarios for future water quality. Model outputs revealed that mean annual river flow is expected to decline between 3 and 20%, depending on the scenario. Concentration of river dissolved inorganic carbon is predicted to follow the opposite trend and might soar up to twice the 2005–2014 average concentration. Lake planktonic primary producers will display quantitative changes in the future decades whereas zooplankters will not. A 2 to 10% increase in mean cyanobacteria biomass is accompanied by a stagnation (−3 to +2%) of rotifer biomass. Changes in cyanobacteria and rotifer phenology are expected: a surge of cyanobacteria biomass in winter and a shortening of the rotifer biomass spring peak. The expected quantitative changes on the biota were magnified in those scenarios where forested area conversions to cropland and water abstraction were the greatest.


Phytoplankton Dissolve Inorganic Carbon Shallow Lake Water Abstraction Geophysical Fluid Dynamics Laboratory 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors are grateful to Katri Rankinen (Finnish Environment Institute) for providing copies of the INCA-C and PERSiST executable, Alo Laas (Estonian University of Life Sciences) and Ivo Saaremäe (Estonian Environment Agency) for assistance in data collection. Cayetano Gutierrez (Cardiff University) was very helpful with the empirical modelling process. RMC acknowledges funding from the Norwegian Research Council project “Lakes in Transition” (244558). This research was supported by Start-Up Personal Research Grant PUT 777 to FC and IUT 21–2 of the Estonian Ministry of Education and Research, and by MARS project (managing aquatic ecosystems and water resources under multiple Stress) funded under the 7th EU Framework Programme, Theme 6 (Environment including Climate Change), Contract No.: 603378 (

Supplementary material

10584_2016_1894_MOESM1_ESM.docx (118 kb)
ESM 1 (DOCX 118 kb)


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Copyright information

© Springer Science+Business Media Dordrecht 2017

Authors and Affiliations

  • Fabien Cremona
    • 1
    Email author
  • Sirje Vilbaste
    • 1
  • Raoul-Marie Couture
    • 2
    • 3
  • Peeter Nõges
    • 1
  • Tiina Nõges
    • 1
  1. 1.Centre for Limnology, Institute of Agricultural and Environmental SciencesEstonian University of Life SciencesTartuEstonia
  2. 2.Norwegian Institute for Water ResearchOsloNorway
  3. 3.Ecohydrology Research Group, Water Institute and Department of Earth and Environmental SciencesUniversity of WaterlooWaterlooCanada

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