Modeling mixoplankton along the biogeochemical gradient of the Southern North Sea

Schneider, Laura; Gypens, Nathalie; Troost, Tineke A.; Stolte, Willem

doi:10.1016/j.ecolmodel.2021.109690

Cited by 6 publications

(3 citation statements)

References 72 publications

(108 reference statements)

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“…The clean dataset resulted in ~6 millions reads that were grouped in 5,042 total amplicon sequence variants (ASVs). Trophic strategies were manually annotated and curated based on the currently accepted forms of protistan plankton nourishment (Flynn et al, 2019;Schneider et al, 2021).…”

Section: Bioinformatic Pipelinementioning

confidence: 99%

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Community dynamics and co-occurrence relationships of pelagic ciliates and their potential prey at a coastal and an offshore station in the ultra-oligotrophic Eastern Mediterranean Sea

2023

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Ciliates have been recognized as one of the major components of the microbial food web, especially in ultra-oligotrophic waters, such as the Eastern Mediterranean Sea, where nutrients are scarce and the microbial community is dominated by pico- and nano-sized organisms. For this reason, ciliates play an important role in these ecosystems since they are the main planktonic grazers. Regardless the importance of these organisms, little is known about the community structure of heterotrophic and mixotrophic ciliates and how they are associated to their potential prey. In this study, we used 18S V4 rRNA gene metabarcoding to analyze ciliate community dynamics and how the relationship with potential prey changes according to different seasons and depths. Samples were collected seasonally at two stations of the Eastern Mediterranean Sea (HCB: coastal, M3A: offshore) from the surface and deep chlorophyll maximum (DCM) layers. The ciliate community structure varied across depths in HCB and across seasons in M3A, and the network analysis showed that in both stations, mixotrophic oligotrichs were positively associated with diatoms and showed few negative associations with ASVs annotated as marine Stramenopiles (MAST). On the other hand, heterotrophic tintinnids showed negative relationships in both HCB and M3A stations, mostly with Ochrophyta and Chlorophyta. These results showed, in first place that, although the two stations are close to each other, the ciliate dynamics differed between them. Moreover, mixotrophic and heterotrophic ciliates may have different ecological niches since mixotrophic ciliates may be more selective compared to heterotrophic species regarding their prey. These findings are the first glimpse into an understanding of the dynamics between heterotrophic and mixotrophic ciliates and their role in microbial assemblages and dynamics of ultra-oligotrophic environments.

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Section: Bioinformatic Pipelinementioning

confidence: 99%

“…Based on their trophic strategy, protists were divided into autotrophs, mixotrophs, heterotrophs and unknown (NA), according to Schneider et al (2021).…”

Section: Bioinformatic Pipelinementioning

confidence: 99%

Community dynamics and co-occurrence relationships of pelagic ciliates and their potential prey at a coastal and an offshore station in the ultra-oligotrophic Eastern Mediterranean Sea

2023

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“…The seasonal cycle of phytoplankton and zooplankton has been well studied across aquatic systems and climate regimes for decades, particularly through long-term monitoring stations that collect plankton data alongside other environmental factors. However, mixoplankton have largely been an overlooked part of the plankton community, limiting our ability to understand drivers of plankton temporal patterns and further predict community response to climate change (Schneider et al, 2021). One way to address this research gap is through reanalyzing long-term monitoring of plankton microscopy and imaging data.…”

Section: How Do Mixoplankton Presence and Activity Vary Across Large ...mentioning

confidence: 99%

Recommendations for advancing mixoplankton research through empirical-model integration

Millette,

Leles,

Johnson

et al. 2024

Front. Mar. Sci.

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Protist plankton can be divided into three main groups: phytoplankton, zooplankton, and mixoplankton. In situ methods for studying phytoplankton and zooplankton are relatively straightforward since they generally target chlorophyll/photosynthesis or grazing activity, while the integration of both processes within a single cell makes mixoplankton inherently challenging to study. As a result, we understand less about mixoplankton physiology and their role in food webs, biogeochemical cycling, and ecosystems compared to phytoplankton and zooplankton. In this paper, we posit that by merging conventional techniques, such as microscopy and physiological data, with innovative methods like in situ single-cell sorting and omics datasets, in conjunction with a diverse array of modeling approaches ranging from single-cell modeling to comprehensive Earth system models, we can propel mixoplankton research into the forefront of aquatic ecology. We present eight crucial research questions pertaining to mixoplankton and mixotrophy, and briefly outline a combination of existing methods and models that can be used to address each question. Our intent is to encourage more interdisciplinary research on mixoplankton, thereby expanding the scope of data acquisition and knowledge accumulation for this understudied yet critical component of aquatic ecosystems.

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Mathematical Basis for Diatom Growth Modeling

Sardari

2023

The Mathematical Biology of Diatoms

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Modeling mixoplankton along the biogeochemical gradient of the Southern North Sea

Cited by 6 publications

References 72 publications

Community dynamics and co-occurrence relationships of pelagic ciliates and their potential prey at a coastal and an offshore station in the ultra-oligotrophic Eastern Mediterranean Sea

Community dynamics and co-occurrence relationships of pelagic ciliates and their potential prey at a coastal and an offshore station in the ultra-oligotrophic Eastern Mediterranean Sea

Recommendations for advancing mixoplankton research through empirical-model integration

Mathematical Basis for Diatom Growth Modeling

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