Phytoplankton adapt to changing ocean environments
Bibliographic record
Abstract
Model projections indicate that climate change may dramatically restructure phytoplankton communities, with cascading consequences for marine food webs. It is currently not known whether evolutionary change is likely to be able to keep pace with the rate of climate change. For simplicity, and in the absence of evidence to the contrary, most model projections assume species have fixed environmental preferences and will not adapt to changing environmental conditions on the century scale. Using 15 y of observations from Station CARIACO (Carbon Retention in a Colored Ocean), we show that most of the dominant species from a marine phytoplankton community were able to adapt their realized niches to track average increases in water temperature and irradiance, but the majority of species exhibited a fixed niche for nitrate. We do not know the extent of this adaptive capacity, so we cannot conclude that phytoplankton will be able to adapt to the changes anticipated over the next century, but community ecosystem models can no longer assume that phytoplankton cannot adapt.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".