Biological Responses to Ocean Acidification Are Changing the Global Ocean Carbon Cycle
Bibliographic record
Abstract
Abstract Increased oceanic uptake of CO 2 due to rising anthropogenic emissions has caused lowered pH levels (ocean acidification) that are hypothesized to diminish biotic calcification and reduce the export of total alkalinity ( A T ) as carbonate minerals from the surface ocean or their burial in coastal sediments. This “CO 2 ‐biotic calcification feedback” is a negative feedback on atmospheric CO 2 , as elevated levels of surface A T increase the ocean's capacity to uptake CO 2 . We detect signatures of this feedback in the global ocean for the first time using repeat hydrographic measurements and seawater property prediction algorithms. Over the course of the past 30 years, we find an increase in global surface A T of 0.072 ± 0.023 μmol kg −1 yr −1 , which would have caused approximately 20 Tmol of additional A T to accumulate in the surface ocean. This finding suggests that anthropogenic CO 2 emissions are measurably perturbing the cycling of carbon on a planetary scale by disrupting biological patterns. More observations of A T would be required to understand the effects of this feedback on a regional basis and to fully characterize its potential to reduce the efficiency of marine carbon dioxide removal technology.
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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 | 0.001 |
| 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 | 0.000 |
| 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".