The seeding of ice algal blooms in Arctic pack ice: The multiyear ice seed repository hypothesis
Bibliographic record
Abstract
During the Norwegian young sea ICE expedition (N-ICE2015) from January to June 2015 the pack ice in the Arctic Ocean north of Svalbard was studied during four drifts between 83° and 80°N. This pack ice consisted of a mix of second year, first year, and young ice. The physical properties and ice algal community composition was investigated in the three different ice types during the winter-spring-summer transition. Our results indicate that algae remaining in sea ice that survived the summer melt season are subsequently trapped in the upper layers of the ice column during winter and may function as an algal seed repository. Once the connectivity in the entire ice column is established, as a result of temperature-driven increase in ice porosity during spring, algae in the upper parts of the ice are able to migrate toward the bottom and initiate the ice algal spring bloom. Furthermore, this algal repository might seed the bloom in younger ice formed in adjacent leads. This mechanism was studied in detail for the dominant ice diatom Nitzschia frigida. The proposed seeding mechanism may be compromised due to the disappearance of older ice in the anticipated regime shift toward a seasonally ice-free Arctic Ocean.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".