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Adaptive divergence in pigment composition promotes phytoplankton biodiversity

Author

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  • Maayke Stomp

    (University of Amsterdam)

  • Jef Huisman

    (University of Amsterdam)

  • Floris de Jongh

    (University of Amsterdam)

  • Annelies J. Veraart

    (University of Amsterdam)

  • Daan Gerla

    (University of Amsterdam)

  • Machteld Rijkeboer

    (Centre for Limnology)

  • Bas W. Ibelings

    (Centre for Limnology)

  • Ute I. A. Wollenzien

    (Centre for Estuarine and Marine Ecology)

  • Lucas J. Stal

    (Centre for Estuarine and Marine Ecology)

Abstract

The dazzling diversity of the phytoplankton has puzzled biologists for decades1,2,3,4,5. The puzzle has been enlarged rather than solved by the progressive discovery of new phototrophic microorganisms in the oceans, including picocyanobacteria6,7, pico-eukaryotes8, and bacteriochlorophyll-based9,10,11 and rhodopsin-based phototrophic bacteria12,13. Physiological and genomic studies suggest that natural selection promotes niche differentiation among these phototrophic microorganisms, particularly with respect to their photosynthetic characteristics14,15,16. We have analysed competition for light between two closely related picocyanobacteria of the Synechococcus group that we isolated from the Baltic Sea17. One of these two has a red colour because it contains the pigment phycoerythrin, whereas the other is blue-green because it contains high contents of the pigment phycocyanin. Here we report theory and competition experiments that reveal stable coexistence of the two picocyanobacteria, owing to partitioning of the light spectrum. Further competition experiments with a third marine cyanobacterium, capable of adapting its pigment composition, show that this species persists by investing in the pigment that absorbs the colour not used by its competitors. These results demonstrate the adaptive significance of divergence in pigment composition of phototrophic microorganisms, which allows an efficient utilization of light energy and favours species coexistence.

Suggested Citation

  • Maayke Stomp & Jef Huisman & Floris de Jongh & Annelies J. Veraart & Daan Gerla & Machteld Rijkeboer & Bas W. Ibelings & Ute I. A. Wollenzien & Lucas J. Stal, 2004. "Adaptive divergence in pigment composition promotes phytoplankton biodiversity," Nature, Nature, vol. 432(7013), pages 104-107, November.
  • Handle: RePEc:nat:nature:v:432:y:2004:i:7013:d:10.1038_nature03044
    DOI: 10.1038/nature03044
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    Cited by:

    1. Tsakalakis, Ioannis & Pahlow, Markus & Oschlies, Andreas & Blasius, Bernd & Ryabov, Alexey B., 2018. "Diel light cycle as a key factor for modelling phytoplankton biogeography and diversity," Ecological Modelling, Elsevier, vol. 384(C), pages 241-248.
    2. Mingyue Wan & Zhiqin Wang & Guangming Mai & Zengling Ma & Xiaomin Xia & Yehui Tan & Gang Li, 2022. "Photosynthetic Characteristics of Macroalgae Ulva fasciata and Sargassum thunbergii in the Daya Bay of the South China Sea, with Special Reference to the Effects of Light Quality," Sustainability, MDPI, vol. 14(13), pages 1-11, July.
    3. Joydev Chattopadhyay & Ezio Venturino & Samrat Chatterjee, 2013. "Aggregation of toxin-producing phytoplankton acts as a defence mechanism – a model-based study," Mathematical and Computer Modelling of Dynamical Systems, Taylor & Francis Journals, vol. 19(2), pages 159-174, April.
    4. Zhang, Haibo & Richardson, Patricia A. & Belayneh, Bruk E. & Ristvey, Andrew & Lea-Cox, John & Copes, Warren E. & Moorman, Gary W. & Hong, Chuanxue, 2015. "Characterization of water quality in stratified nursery recycling irrigation reservoirs," Agricultural Water Management, Elsevier, vol. 160(C), pages 76-83.
    5. Chuanjun Dai & Hengguo Yu & Qing Guo & He Liu & Qi Wang & Zengling Ma & Min Zhao, 2019. "Dynamics Induced by Delay in a Nutrient-Phytoplankton Model with Multiple Delays," Complexity, Hindawi, vol. 2019, pages 1-16, February.
    6. Olusoji, Oluwafemi D. & Spaak, Jurg W. & Holmes, Mark & Neyens, Thomas & Aerts, Marc & De Laender, Frederik, 2021. "cyanoFilter: An R package to identify phytoplankton populations from flow cytometry data using cell pigmentation and granularity," Ecological Modelling, Elsevier, vol. 460(C).

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