Anthropogenic Carbon Increase has Caused Critical Shifts in Aragonite Saturation Across a Sensitive Coastal System
Bibliographic record
Abstract
Abstract Estuarine systems host a rich diversity of marine life that is vulnerable to changes in ocean chemistry due to addition of anthropogenic carbon. However, the detection and impact of secular carbon trends in these systems is complicated by heightened natural variability as compared to open‐ocean regimes. We investigate biogeochemical changes between the pre‐industrial (PI) and modern periods using a high‐resolution, three‐dimensional, biophysical model of the Salish Sea, a representative Northeast Pacific coastal system. While the seasonal amplitude of the air‐sea difference in pCO2 has increased on average since pre‐industrial times, the net CO2 source has changed little. Our simulations show that inorganic carbon has increased throughout the model domain by 29–39 mmol m−3 (28–38 µmol kg−1) from the pre‐industrial to present. While this increase is modest in a global context, the region's naturally high inorganic carbon content and the low buffering capacity of the local carbonate system amplify the resultant effects. Notably, this increased carbon drives the estuary toward system‐wide undersaturation of aragonite, negatively impacting shell‐forming organisms. Undersaturation events were rare during the pre‐industrial experiment, with 10%–25% of the domain undersaturated by volume throughout the year, while under present‐day conditions, the majority (55%–75%) of the system experiences corrosive, undersaturated conditions year‐round. These results are extended using recent global coastal observations to show that estuaries throughout the Pacific Rim have already undergone a similar saturation state regime shift.
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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 | 0.001 | 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 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".