Lake browning counteracts cyanobacteria responses to nutrients: Evidence from phytoplankton dynamics in large enclosure experiments and comprehensive observational data

Lakes worldwide are affected by multiple stressors, including climate change. This includes massive loading of both nutrients and humic substances to lakes during extreme weather events, which also may disrupt thermal stratification. Since multi-stressor effects vary widely in space and time, their combined ecological impacts remain difficult to predict. Therefore, we combined two consecutive large enclosure experiments with a comprehensive time-series and a broad-scale field survey to unravel the combined effects of storm-induced lake browning, nutrient enrichment and deep mixing on phytoplankton communities, focusing particularly on potentially toxic cyanobacterial blooms. The experimental results revealed that browning counteracted the stimulating effect of nutrients on phytoplankton and caused a shift from phototrophic cyanobacteria and chlorophytes to mixotrophic cryptophytes. Light limitation by browning was identified as the likely mechanism underlying this response. Deep-mixing increased microcystin concentrations in clear nutrient-enriched enclosures, caused by upwelling of a metalimnetic Planktothrix rubescens population. Monitoring data from a 25-year time-series of a eutrophic lake and from 588 northern European lakes corroborate the experimental results: Browning suppresses cyanobacteria in terms of both biovolume and proportion of the total phytoplankton biovolume. Both the experimental and observational results indicated a lower total phosphorus threshold for cyanobacterial bloom development in clearwater lakes (10-20 μg P L-1 ) than in humic lakes (20-30 μg P L-1 ). This finding provides management guidance for lakes receiving more nutrients and humic substances due to more frequent extreme weather events.

[1]  Intergovernmental Panel on Climate Change.  Climate Change 2021 – The Physical Science Basis , 2023 .

[2]  Lesley B. Knoll,et al.  Blooms also like it cold , 2023, Limnology and Oceanography Letters.

[3]  E. Litchman.  Understanding and predicting harmful algal blooms in a changing climate: A trait‐based framework , 2022, Limnology and Oceanography Letters.

[4]  Samuel B. Fey,et al.  Environmental variability in aquatic ecosystems: Avenues for future multifactorial experiments , 2022, Limnology and Oceanography Letters.

[5]  J. Köhler,et al.  From minute to day: Ecophysiological response of phytoplankton to fluctuating light exposure during vertical mixing , 2022, Limnology and Oceanography.

[6]  E. Peltomaa,et al.  Metabolic plasticity of mixotrophic algae is key for their persistence in browning environments , 2022, Molecular ecology.

[7]  S. Van den Wyngaert,et al.  Seasonality of parasitic and saprotrophic zoosporic fungi: linking sequence data to ecological traits , 2022, The ISME Journal.

[8]  F. Hellweger,et al.  Models predict planned phosphorus load reduction will make Lake Erie more toxic , 2022, Science.

[9]  I. Creed,et al.  Performance and competitiveness of red vs. green phenotypes of a cyanobacterium grown under artificial lake browning , 2021, Algae.

[10]  Jorrit P. Mesman,et al.  Cyanobacterial blooms in oligotrophic lakes: Shifting the high‐nutrient paradigm , 2021, Freshwater Biology.

[11]  J. Graham,et al.  The extent and variability of storm‐induced temperature changes in lakes measured with long‐term and high‐frequency data , 2021, Limnology and Oceanography.

[12]  I. Creed,et al.  Trade-offs Between Light and Nutrient Availability Across Gradients of Dissolved Organic Carbon Lead to Spatially and Temporally Variable Responses of Lake Phytoplankton Biomass to Browning , 2021, Ecosystems.

[13]  I. Laurion,et al.  Effects of phytoplankton blooms on fluxes and emissions of greenhouse gases in a eutrophic lake. , 2021, Water research.

[14]  S. Bertilsson,et al.  Comprehensive analysis of chemical and biological problems associated with browning agents used in aquatic studies , 2021, bioRxiv.

[15]  L. Carvalho,et al.  Making waves. Bridging theory and practice towards multiple stressor management in freshwater ecosystems. , 2021, Water research.

[16]  I. Creed,et al.  Lake browning may fuel phytoplankton biomass and trigger shifts in phytoplankton communities in temperate lakes , 2021, Aquatic Sciences.

[17]  J. Harrison.  Corrigendum , 2020, Global change biology.

[18]  S. Jacquet,et al.  Advances in forecasting harmful algal blooms using machine learning models: A case study with Planktothrix rubescens in Lake Geneva. , 2020, Harmful algae.

[19]  T. Rohrlack,et al.  The success of Gonyostomum semen (Raphidophyceae) in a boreal lake is due to environmental changes rather than a recent invasion , 2020 .

[20]  M. Lürling.  Grazing resistance in phytoplankton , 2020, Hydrobiologia.

[21]  Todd R. Miller,et al.  A first assessment of cyanobacterial blooms in oligotrophic Lake Superior , 2020, Limnology and Oceanography.

[22]  J. Lenters,et al.  Global lake responses to climate change , 2020, Nature Reviews Earth & Environment.

[23]  Dick de Zwart,et al.  Impacts of multiple stressors on freshwater biota across spatial scales and ecosystems , 2020, Nature Ecology & Evolution.

[24]  L. Rudstam,et al.  Storm impacts on phytoplankton community dynamics in lakes , 2020, Global change biology.

[25]  T. Asaeda,et al.  Effects of Light Intensity and Exposure Period on the Growth and Stress Responses of Two Cyanobacteria Species: Pseudanabaena galeata and Microcystis aeruginosa , 2020, Water.

[26]  S. Polasky,et al.  Ecosystem services of Earth’s largest freshwater lakes , 2020 .

[27]  M. Järvinen,et al.  Phosphorus thresholds for bloom-forming cyanobacterial taxa in boreal lakes , 2019, Hydrobiologia.

[28]  J. M. Schuurmans,et al.  Changes in water color shift competition between phytoplankton species with contrasting light‐harvesting strategies , 2019, Ecology.

[29]  M. Kelly,et al.  Nutrient criteria for surface waters under the European Water Framework Directive: Current state-of-the-art, challenges and future outlook , 2019, The Science of the total environment.

[30]  J. Smol,et al.  The browning and re-browning of lakes: Divergent lake-water organic carbon trends linked to acid deposition and climate change , 2019, Scientific Reports.

[31]  Leah Jackson-Blake,et al.  Predicting Lake Quality for the Next Generation: Impacts of Catchment Management and Climatic Factors in a Probabilistic Model Framework , 2019, Water.

[32]  T. Richardson,et al.  Light capture and pigment diversity in marine and freshwater cryptophytes , 2019, Journal of phycology.

[33]  J. Karlsson,et al.  Light and nutrient control phytoplankton biomass responses to global change in northern lakes , 2019, Global change biology.

[34]  H. Grossart,et al.  Environmental drivers of mixotrophs in boreal lakes , 2019, Limnology and Oceanography.

[35]  Ryan S. Mueller,et al.  Anabaena/Dolichospermum as the source of lethal microcystin levels responsible for a large cattle toxicosis event , 2018, Toxicon: X.

[36]  S. Langenheder,et al.  High abundances of the nuisance raphidophyte Gonyostomum semen in brown water lakes are associated with high concentrations of iron , 2018, Scientific Reports.

[37]  Mirco Migliavacca,et al.  To replicate, or not to replicate - that is the question: how to tackle nonlinear responses in ecological experiments. , 2018, Ecology letters.

[38]  Lesley B. Knoll,et al.  Browning-related oxygen depletion in an oligotrophic lake , 2018, Inland Waters.

[39]  H. Paerl,et al.  Cyanobacterial blooms , 2018, Nature Reviews Microbiology.

[40]  J. Köhler,et al.  Influence of vertical mixing on light‐dependency of phytoplankton growth , 2018 .

[41]  L. Hansson,et al.  Primary producers or consumers? Increasing phytoplankton bacterivory along a gradient of lake warming and browning , 2018 .

[42]  J. Boenigk,et al.  Cryptophyta as major bacterivores in freshwater summer plankton , 2018, The ISME Journal.

[43]  J. Monnet.  Corrigendum , 2017 .

[44]  M. Gessner,et al.  Thermocline deepening boosts ecosystem metabolism: evidence from a large‐scale lake enclosure experiment simulating a summer storm , 2017, Global change biology.

[45]  A. Deininger,et al.  Phytoplankton response to whole lake inorganic N fertilization along a gradient in dissolved organic carbon. , 2017, Ecology.

[46]  M. Kile,et al.  Tiltaksorientert overvåking i vannområde Mjøsa. Årsrapport for 2016 , 2017 .

[47]  M. Gessner,et al.  Extreme Weather Event Triggers Cascade Towards Extreme Turbidity in a Clear-water Lake , 2017, Ecosystems.

[48]  E. Jeppesen,et al.  Lake Restoration and Management in a Climate Change Perspective: An Introduction , 2017 .

[49]  H. Laudon,et al.  Current Browning of Surface Waters Will Be Further Promoted by Wetter Climate , 2016 .

[50]  C. Stow,et al.  The dual role of nitrogen supply in controlling the growth and toxicity of cyanobacterial blooms. , 2016, Harmful algae.

[51]  C. Brown,et al.  Interactions among ecosystem stressors and their importance in conservation , 2016, Proceedings of the Royal Society B: Biological Sciences.

[52]  P. Hanson,et al.  Response of boreal lakes to episodic weather-induced events , 2016 .

[53]  Lesley B. Knoll,et al.  Ecological consequences of long-term browning in lakes , 2015, Scientific Reports.

[54]  Jef Huisman,et al.  Artificial mixing to control cyanobacterial blooms: a review , 2015, Aquatic Ecology.

[55]  S. Diehl,et al.  An experimental demonstration of the critical depth principle , 2015 .

[56]  L. Krienitz,et al.  Presence of Potential Toxin-Producing Cyanobacteria in an Oligo-Mesotrophic Lake in Baltic Lake District, Germany: An Ecological, Genetic and Toxicological Survey , 2014, Toxins.

[57]  T. Mehner,et al.  A feedback loop links brownification and anoxia in a temperate, shallow lake , 2014 .

[58]  Anne Lyche Solheim,et al.  Sustaining recreational quality of European lakes: minimizing the health risks from algal blooms through phosphorus control , 2013 .

[59]  D. Hering,et al.  The WISER way of organising ecological data from European rivers, lakes, transitional and coastal waters , 2013, Hydrobiologia.

[60]  Miquel Lürling,et al.  Beyond the Plankton Ecology Group (PEG) Model : Mechanisms Driving Plankton Succession , 2012 .

[61]  Oliver Köster,et al.  Harmful filamentous cyanobacteria favoured by reduced water turnover with lake warming , 2012 .

[62]  D. Dionysiou,et al.  The Effects of Sample Matrices on Immunoassays to Detect Microcystin-LR in Water , 2012 .

[63]  A. Nicklisch,et al.  Temperature and photoperiod effects on phytoplankton growing under simulated mixed layer light fluctuations , 2012 .

[64]  C. Sayer,et al.  Zooplankton as indicators in lakes: a scientific-based plea for including zooplankton in the ecological quality assessment of lakes according to the European Water Framework Directive (WFD) , 2011, Hydrobiologia.

[65]  N. Swenson,et al.  Eco‐evolutionary differences in light utilization traits and distributions of freshwater phytoplankton , 2011 .

[66]  David R. Anderson,et al.  AIC model selection and multimodel inference in behavioral ecology: some background, observations, and comparisons , 2011, Behavioral Ecology and Sociobiology.

[67]  S. Wood.  Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models , 2011 .

[68]  L. Krienitz,et al.  Rarity, ecological memory, rate of floral change in phytoplankton—and the mystery of the Red Cock , 2010, Hydrobiologia.

[69]  S. Diehl,et al.  Water temperature and stratification depth independently shift cardinal events during plankton spring succession , 2010 .

[70]  J. Komárková,et al.  Polyphasic characterization of eight planktonic Anabaena strains (Cyanobacteria) with reference to the variability of 61 Anabaena populations observed in the field , 2010, Hydrobiologia.

[71]  Z. Dubinsky,et al.  Photoacclimation processes in phytoplankton: mechanisms, consequences, and applications , 2009 .

[72]  Brian J. Soden,et al.  Model projected changes of extreme wind events in response to global warming , 2009 .

[73]  A. Zuur,et al.  Mixed Effects Models and Extensions in Ecology with R , 2009 .

[74]  O. Pietiläinen,et al.  Chlorophyll–nutrient relationships of different lake types using a large European dataset , 2008, Aquatic Ecology.

[75]  R. Ptáčník,et al.  REBECCA databases: experiences from compilation and analyses of monitoring data from 5,000 lakes in 20 European countries , 2008, Aquatic Ecology.

[76]  L. Carvalho,et al.  Quantitative responses of lake phytoplankton to eutrophication in Northern Europe , 2008, Aquatic Ecology.

[77]  Lucas J Stal,et al.  Colourful coexistence of red and green picocyanobacteria in lakes and seas. , 2007, Ecology letters.

[78]  J. Huisman,et al.  Competition for Light between Toxic and Nontoxic Strains of the Harmful Cyanobacterium Microcystis , 2007, Applied and Environmental Microbiology.

[79]  Stella A. Berger,et al.  Light supply, plankton biomass, and seston stoichiometry in a gradient of lake mixing depths , 2006 .

[80]  M. Jansson,et al.  Occurrence of mixotrophic flagellates in relation to bacterioplankton production, light regime and availability of inorganic nutrients in unproductive lakes with differing humic contents , 2003 .

[81]  Colin S. Reynolds,et al.  Towards a functional classification of the freshwater phytoplankton , 2002 .

[82]  G. Habermehl,et al.  Toxic Cyanobacteria in Water , 2001 .

[83]  Franz J. Weissing,et al.  Critical depth and critical turbulence: Two different mechanisms for the development of phytoplankton blooms , 1999 .

[84]  A. Walsby,et al.  Gas vesicle formation in the dark, and in light of different irradiances, by the cyanobacterium Microcystis sp. , 1990 .

[85]  Colin S. Reynolds,et al.  Phytoplankton periodicity: the interactions of form, function and environmental variability , 1984 .

[86]  Priyanka,et al.  Cyanobacteria , 2020, Abatement of Environmental Pollutants.

[87]  S. Langenheder,et al.  Increased water colour affects freshwater plankton communities in a mesocosm study , 2017 .

[88]  D. Caron,et al.  Defining Planktonic Protist Functional Groups on Mechanisms for Energy and Nutrient Acquisition: Incorporation of Diverse Mixotrophic Strategies. , 2016, Protist.

[89]  L. Krienitz,et al.  Spatial- and niche segregation of DCM-forming cyanobacteria in Lake Stechlin (Germany) , 2015, Hydrobiologia.

[90]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[91]  T. Christiansen,et al.  European waters assessment of status and pressures 2018. , 2012 .

[92]  Val H. Smith,et al.  Light and Nutrient Effects on the Relative Biomass of Blue-Green Algae in Lake Phytoplankton , 1986 .