Seasonal patterns of microbial diversity across the world oceans
Bibliographic record
Abstract
Abstract Understanding the patterns of marine microbial diversity (Bacteria + Archaea) is essential, as variations in their alpha‐ and beta‐diversities can affect ecological processes. Investigations of microbial diversity from global oceanographic expeditions and basin‐wide transects show positive correlations between microbial diversity and either temperature or productivity, but these studies rarely captured seasonality, especially in polar regions. Here, using multiannual alpha‐diversity data from eight time series in the northern and southern hemispheres, we show that marine microbial community richness and evenness generally correlate more strongly with daylength than with temperature or chlorophyll a (a proxy for photosynthetic biomass). This pattern is observable across time series found in the northern and southern hemispheres regardless of collection method, DNA extraction protocols, targeted 16S rRNA hypervariable region, sequencing technology, or bioinformatics pipeline.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".