Understanding historical and projected compound change on the Northwest Atlantic shelf
Bibliographic record
Abstract
Increasing atmospheric carbon dioxide concentrations are accompanied by ocean acidification, oxygen loss, and warming of the global ocean. However, in coastal environments, local processes that occur on small spatial scales can moderate or exacerbate these trends. These processes are not well represented in global climate models. Therefore, downscaled tools are useful to decipher carbonate system drivers and predict conditions. Here we describe the application of a ROMS based regional model of the northwest Atlantic shelf, stretching from Florida to Newfoundland, with ~7 km horizontal resolution. The biogeochemical model relies on the Carbon, Ocean Biogeochemistry and Lower Trophics (COBALT) model in combination with regional empirical models to reconstruct the carbon variables. Using a 30-year historical simulation, model results are evaluated against in situ observations and then used to estimate anthropogenic carbon inventories for the region. Historical trends differ between surface and bottom conditions with bottom trends identified as more severe. Circulation and changes in the water column metabolism amplify local rates of change historically, while warming and water mass changes act to dampen these changes. Regional locations of accelerated carbon storage and accumulation are identified and described to be modified by coastal processes. A time-varying dynamic delta forced future projection out to 2098 under SSP5-8.5 projects how these trends will continue and indicates future acceleration of trends. Observing compound change, or multiple stressors changing in concert or closely, requires not only over-constraint on the carbon cycle parameters, but also multiple co-existing biogeochemical observations to refine the mechanisms responsible for local climate variability.
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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 | 0.001 | 0.001 |
| 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".