Timing and magnitude of spring bloom and effects of physical environments over the Grand Banks of Newfoundland
Bibliographic record
Abstract
Abstract Spring bloom is a dominant feature of seasonal phytoplankton cycles in the northwest Atlantic continental shelf. In this study, we investigate temporal and spatial variations of spring‐bloom timing and intensity over the Grand Banks of Newfoundland, using satellite ocean color data and other oceanographic measurements from January 1998 to December 2009. The spring bloom has strong interannual and meridional changes in its timing and intensities. Physical oceanographic conditions including the sea surface temperature (SST), wind speed, and mixed layer depth (MLD) also show evident interannual variations. The spring boom starts first in the southern Bank in February–March and often in the central and northern Bank in April, respectively. An early initiation of spring blooms is generally associated with high SST, weak winds, and shallow MLD at the beginning stage of the spring blooms, and tends to result in stronger intensities. However, the photosynthesis available radiance does not seem to affect the bloom initiation in the southern area or the bloom intensity over the entire Banks. In the southern area, higher SST does not lead to larger bloom magnitude. Our analysis shows that the effect of the SST in the northern area is primarily through the earlier ice melting. It also indicates that Sverdrup's critical depth criteria are suitable for conditions over the Grand Banks. The present study points to the significant sub‐bank‐scale differences in the timing and magnitude of the spring bloom attributable to underlying physical environments, important for the integrated management of the Grand Banks ecosystem.
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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 | 0.001 |
| 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".