Exploring controls on the timing of the phytoplankton bloom in western Baffin Bay, Canadian Arctic
Bibliographic record
Abstract
In the Arctic Ocean the peak of the phytoplankton bloom occurs around the period of sea ice break-up. Climate change is likely to impact the bloom phenology and its crucial contribution to the production dynamics of Arctic marine ecosystems. Here we explore and quantify controls on the timing of the spring bloom using a one-dimensional biogeochemical/ecosystem model configured for coastal western Baffin Bay. The model reproduces the observations made on the phenology and the assemblage of the phytoplankton community from an ice camp in the region. Using sensitivity experiments, we found that two essential controls on the timing of the spring bloom were the biomass of phytoplankton before bloom initiation and the light under sea ice before sea ice break-up. The level of nitrate before bloom initiation was less important. The bloom peak was delayed up to 20 days if the overwintering phytoplankton biomass was too low. This result highlights the importance of phytoplankton survival mechanisms during polar winter to the pelagic ecosystem of the Arctic Ocean and the spring bloom dynamics.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".