Impact of advection loss due to wind and estuarine circulation on the timing of the spring phytoplankton bloom in a fjord
Bibliographic record
Abstract
Abstract A coupled biophysical model is used to explore the physical controls involved in the timing of the spring phytoplankton bloom in fjords. Observations from Rivers Inlet, British Columbia, are used to force and evaluate the model. It is found that the interannual variation in timing is due primarily to variations in retention, in particular, to variations in horizontal advection out of the fjord. The two dominant processes are (i) strong outflow winds rapidly advecting the surface layer and thus the phytoplankton population out of the fjord and (ii) losses due to high river flux increasing the estuarine circulation. Both processes delay the timing of spring bloom. Smaller effects on the interannual variation are due to increased wind mixing which deepens the mixing layer and reduces light to phytoplankton, and increased river flow which increases the stratification and decreases the mixing layer depth. Observed interannual variations in cloudiness were small. Strong outflow winds are common in winter along the British Columbia coast, but generally cease after the spring wind transition. Thus, observed interdecadal variations in the spring transition date probably imply strong variations in the timing of spring phytoplankton blooms in British Columbia fjords.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".