The Prokaryotic and Eukaryotic Microbiome of Pacific Oyster Spat is Shaped by Ocean Warming but not Acidification
Bibliographic record
Abstract
Abstract Pacific oysters ( Magallana gigas, also known as Crassostrea gigas ), the most widely farmed oysters, are under threat from climate change and emerging pathogens. In part, their resilience may be affected by their microbiome, which, in turn, may be influenced by ocean warming and acidification. Consequently, for three weeks, we exposed early-development Pacific oyster spat to different temperatures (18 and 24 °C) and p CO 2 levels (800, 1600 and 2800 µ atm) in a fully crossed design. Under all conditions, the microbiome developed over time, with potentially pathogenic ciliates ( Uronema marinum ) greatly reduced in all treatments, suggesting that the spat’s microbiome undergoes adaptive shifts as the oysters age. The microbiome composition also differed significantly with temperature, but not acidification, indicating that M. gigas spat microbiomes can be altered by ocean warming but resilient to ocean acidification in our experiments. These findings highlight the spat microbiome’s flexibility to environmental changes as well as its “protective” capability against potentially pathogenic microbes.
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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 | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".