Anthropogenic Carbon Increase has Caused Critical Shifts in Aragonite Saturation Across a Sensitive Coastal System
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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 pCO 2 has increased on average since pre‐industrial times, the net CO 2 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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 | 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 it