Spatial Variability in the Primary Production Rates and Biomasses (Chl a) of Sea Ice Algae in the Canadian Arctic–Greenland Region: A Review
Bibliographic record
Abstract
The aims of this review are to elucidate the spatial variation in the primary production rates and biomasses (Chl a) of sea ice algae in the Canadian Arctic–Greenland region, characterized by its comparable physical settings. A database was compiled from 30 studies of the production rates and biomasses (Chl a) of sea ice algae, the snow and ice thicknesses, ice types, nutrients (Si(OH)4, PO4, (NO3 + NO2)), and NH4 concentrations in the ice and below the ice from the region. Production rates were significantly higher (463 mg C m−2 d−1) in Resolute Bay and Northern Baffin Bay (317 mg C m−2 d−1), both in the Canadian Arctic, compared to a rate of 0.2 mg C m−2 d−1 in northeast Greenland. The biomasses reached 340 mg Chl a m−2 in Resolute Bay in comparison to 0.02 mg Chl a m−2 in southwest Greenland. Primary production at other Canadian and Greenland sites was comparable, but sea ice Chl a was higher (15.0 ± 13.4 mg Chl a m−2) at Canadian sites compared to Greenland ones (0.8 ± 0.5 mg Chl a m−2). Resolute and Northern Baffin Bay production rates were significantly higher when compared to other Arctic Ocean sites outside the studied region. The review concludes that the high production rates and biomasses in Resolute and Northern Baffin Bay are related to the inflow and mixing of nutrient-rich waters of Pacific origin. A conceptual model with drivers and inhibitors of the primary production of sea ice algae is proposed, and the database is compiled into a dataset of published data for further studies.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".