Physical associations to spring phytoplankton biomass interannual variability in the U.S. Northeast Continental Shelf
Bibliographic record
Abstract
Abstract The continental shelf of the Northeast United States and Nova Scotia is a productive marine ecosystem that supports a robust biomass of living marine resources. Understanding marine ecosystem sensitivity to changes in the physical environment can start with the first‐order response of phytoplankton (i.e., chlorophyll a), the base of the marine food web. However, the primary physical associations to the interannual variability of chlorophyll a in these waters are unclear. Here we used ocean color satellite measurements and identified the local and remote physical associations to interannual variability of spring surface chlorophyll a from 1998 to 2013. The highest interannual variability of chlorophyll a occurred in March and April on the northern flank of Georges Bank, the western Gulf of Maine, and Nantucket Shoals. Complex interactions between winter wind speed over the Shelf, local winter water levels, and the relative proportions of Atlantic versus Labrador Sea source waters entering the Gulf of Maine from the previous summer/fall were associated with the variability of March/April chlorophyll a in Georges Bank and the Gulf of Maine. Sea surface temperature and sea surface salinity were not robust correlates to spring chlorophyll a. Surface nitrate in the winter was not a robust correlate to chlorophyll a or the physical variables in every case suggesting that nitrate limitation may not be the primary constraint on the interannual variability of the spring bloom throughout all regions. Generalized linear models suggest that we can resolve 88% of March chlorophyll a interannual variability in Georges Bank using lagged physical data.
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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 | 0.001 | 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) | 0.001 | 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".