CO2 effects on taxonomic composition and nutrient utilization in an Equatorial Pacific phytoplankton assemblage
Bibliographic record
Abstract
We report the results of a field incubation experiment demonstrating a substantial shift in the taxonomic composition of Equatorial Pacific phytoplankton assemblages exposed to CO 2 levels of 150 and 750 ppm (dissolved CO 2 ~3 to 25 M). By the end of the experiment, the phytoplankton community in all samples was dominated by diatoms and Phaeocystis sp. However, the relative abundance of these phytoplankton taxa differed significantly between CO 2 treatments. Taxonomic pigment analysis and direct microscopic examination of samples revealed that the abundance of diatoms decreased by ~50% at low CO 2 relative to high CO 2 , while the abundance of Phaeocystis increased by ~60% at low CO 2 . This CO 2 -dependent shift was associated with a significant change in nutrient utilization, with higher ratios of nitrate:silicate (N:Si) and nitrate:phosphate (N:P) consumption by phytoplankton in the low CO 2 treatment. Despite the significant changes in taxonomic composition and nutrient consumption ratios, total biomass and primary productivity did not differ significantly between the CO 2 treatments. Our results suggest that CO 2 concentrations could potentially influence competition among marine phytoplankton taxa and affect oceanic nutrient cycling.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".