Fungal parasitism on diatoms alters formation and bio-physical properties of sinking aggregates
Bibliographic record
Abstract
Phytoplankton forms the base of aquatic food webs and element cycling in diverse aquatic systems. The fate of phytoplankton-derived organic matter, however, often remains unresolved as it is controlled by complex, interlinked remineralization and sedimentation processes. We here investigate a rarely considered control mechanism on sinking organic matter fluxes: fungal parasites infecting phytoplankton. We demonstrate that bacterial colonization is promoted 3.5-fold on fungal-infected phytoplankton cells in comparison to non-infected cells in a cultured model pathosystem (diatom Synedra, fungal microparasite Zygophlyctis, and co-growing bacteria), and even >= 17-fold in field-sampled populations (Planktothrix, Synedra, and Fragilaria). Additional data obtained using the Synedra-Zygophlyctis model system reveals that fungal infections reduce the formation of aggregates. Moreover, carbon respiration is 2-fold higher and settling velocities are 11-48% lower for similar-sized fungal-infected vs. non-infected aggregates. Our data imply that parasites can effectively control the fate of phytoplankton-derived organic matter on a single-cell to single-aggregate scale, potentially enhancing remineralization and reducing sedimentation in freshwater and coastal systems.Fungal parasites are found to effectively control the fate of phytoplankton-derived organic matter, potentially enhancing remineralization and reducing sedimentation in freshwater and coastal systems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".