Colourful coexistence of red and green picocyanobacteria in lakes and seas
Bibliographic record
Abstract
Hutchinson's paradox of the plankton inspired many studies on the mechanisms of species coexistence. Recent laboratory experiments showed that partitioning of white light allows stable coexistence of red and green picocyanobacteria. Here, we investigate to what extent these laboratory findings can be extrapolated to natural waters. We predict from a parameterized competition model that the underwater light colour of lakes and seas provides ample opportunities for coexistence of red and green phytoplankton species. To test this prediction, we sampled picocyanobacteria of 70 aquatic ecosystems, ranging from clear blue oceans to turbid brown peat lakes. As predicted, red picocyanobacteria dominated in clear waters, whereas green picocyanobacteria dominated in turbid waters. We found widespread coexistence of red and green picocyanobacteria in waters of intermediate turbidity. These field data support the hypothesis that niche differentiation along the light spectrum promotes phytoplankton biodiversity, thus providing a colourful solution to the paradox of the plankton.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".