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Modeling the life cycle of four types of phytoplankton and their bloom mechanisms in a benthic-pelagic coupled ecosystem

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  • Sohma, Akio
  • Imada, Riku
  • Nishikawa, Tetsuya
  • Shibuki, Hisashi

Abstract

Harmful diatom (Coscinodiscus waillesi and Eucampia zodiacus) blooms frequently occur in the western coastal area of Japan from late autumn to early spring, causing discoloration of edible seaweed nori (Pyropia yezoensis). One of the causes of the discoloration is thought to be nutrient depletion (oligotrophication) due to nutrient uptake by diatoms. The goal of our study was to elucidate the mechanisms underlying phytoplankton blooms and the effects of such blooms on comprehensive nutrient cycles in the benthic-pelagic ecosystem. We developed a new ecosystem model, EMAGIN-L.P., simultaneously representing phytoplankton life cycle and the benthic-pelagic ecosystem. The life cycles of four types of phytoplankton—dinoflagellates (DFL), small diatoms (SDA), Coscinodiscus wailesii (CDW), and Eucampia zodiacus (EZ)—were numerically modeled and incorporated into an existing ecosystem model, ECOHYM (Sohma et al., 2008a), representing the food web among the benthic and pelagic systems and carbon-nitrogen-phosphorus-oxygen-coupled cycles driven by biogeochemical and physical processes. The model was applied to the Harima-Nada Sea where the discoloration of nori frequently occurs. The model reproduced the differences in timing and scale of the four phytoplankton blooms, and each bloom could be explained by a combination of temperature suitability, light availability, nutrient limitation, and vertical mixing within the water column. Furthermore, through a sensitivity analysis, competition for nutrient uptake among different types of phytoplankton was observed in the model. That is, from June to October, when DFL and SDA blooms occur, the SDA nutrient uptake rate is high and SDA suppresses the DFL bloom, while from November to March, when CDW and EZ blooms occur, the nutrient uptake rate of EZ is high and the CDW bloom is slightly suppressed. The developed model representing the phytoplankton bloom mechanisms in the whole benthic-pelagic coupled ecosystem will be a useful tool for revealing the mechanisms underlying the nutrient cycle and the contribution of harmful diatom blooms to the discoloration of nori. The modeling approach presented in this paper (i.e., categorizing different types of major phytoplankton and incorporating their life cycle into the entire benthic-pelagic coupling ecosystem) can be an effective method to understand, predict, and manage the problems caused by harmful diatom blooms across different damage types, harmful diatom species, and ocean areas.

Suggested Citation

  • Sohma, Akio & Imada, Riku & Nishikawa, Tetsuya & Shibuki, Hisashi, 2022. "Modeling the life cycle of four types of phytoplankton and their bloom mechanisms in a benthic-pelagic coupled ecosystem," Ecological Modelling, Elsevier, vol. 467(C).
  • Handle: RePEc:eee:ecomod:v:467:y:2022:i:c:s0304380022000102
    DOI: 10.1016/j.ecolmodel.2022.109882
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    References listed on IDEAS

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    1. Sohma, Akio & Shibuki, Hisashi & Nakajima, Fumiyuki & Kubo, Atsushi & Kuwae, Tomohiro, 2018. "Modeling a coastal ecosystem to estimate climate change mitigation and a model demonstration in Tokyo Bay," Ecological Modelling, Elsevier, vol. 384(C), pages 261-289.
    2. Vanhoutte-Brunier, Alice & Fernand, Liam & Ménesguen, Alain & Lyons, Sandra & Gohin, Francis & Cugier, Philippe, 2008. "Modelling the Karenia mikimotoi bloom that occurred in the western English Channel during summer 2003," Ecological Modelling, Elsevier, vol. 210(4), pages 351-376.
    3. Yamamoto, Tamiji & Hiraga, Naoyuki & Takeshita, Kuniaki & Hashimoto, Toshiya, 2008. "An estimation of net ecosystem metabolism and net denitrification of the Seto Inland Sea, Japan," Ecological Modelling, Elsevier, vol. 215(1), pages 55-68.
    4. Sohma, Akio & Sekiguchi, Yasuyuki & Kuwae, Tomohiro & Nakamura, Yoshiyuki, 2008. "A benthic–pelagic coupled ecosystem model to estimate the hypoxic estuary including tidal flat—Model description and validation of seasonal/daily dynamics," Ecological Modelling, Elsevier, vol. 215(1), pages 10-39.
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    Cited by:

    1. Yuanlin Ma & Xingwang Yu, 2022. "Stationary Probability Density Analysis for the Randomly Forced Phytoplankton–Zooplankton Model with Correlated Colored Noises," Mathematics, MDPI, vol. 10(14), pages 1-11, July.
    2. Theng, Vouchlay & Sith, Ratino & Uk, Sovannara & Yoshimura, Chihiro, 2023. "Phytoplankton productivity in a tropical lake-floodplain system revealed by a process-based primary production model," Ecological Modelling, Elsevier, vol. 479(C).

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