Current state and trends in Canadian Arctic marine ecosystems: I. Primary production
Bibliographic record
Abstract
During the International Polar Year (IPY), large international research programs provided a unique opportunity for assessing the current state and trends in major components of arctic marine ecosystems at an exceptionally wide spatio-temporal scale: sampling covered most regions of the Canadian Arctic (IPY-Canada’s Three Oceans project), and the coastal and offshore areas of the southeastern Beaufort Sea were monitored over almost a full year (IPY-Circumpolar Flaw Lead project). The general goal of these projects was to improve our understanding of how the response of arctic marine ecosystems to climate warming will alter the productivity and structure of the food web and the ecosystem services it provides to Northerners. The present paper summarizes and discusses six key findings related to primary production (PP), which determines the amount of food available to consumers. (1) Offshore, the warming and freshening of the surface layer is leading to the displacement of large nanophytoplankton species by small picophytoplankton cells, with potentially profound bottom-up effects within the marine food web. (2) In coastal areas, PP increases as favourable winds and the deeper seaward retreat of ice promote upwelling. (3) Multiple upwelling events repeatedly provide food to herbivores throughout the growth season. (4) A substantial amount of pelagic PP occurs under thinning ice and cannot be detected by orbiting sensors. (5) Early PP in the spring does not imply a trophic mismatch with key herbivores. (6) The epipelagic ecosystem is very efficient at retaining carbon in surface waters and preventing its sedimentation to the benthos. While enhanced PP could result in increased fish and marine mammal harvests for Northerners, it will most likely be insufficient for sustainable large-scale commercial fisheries in the Canadian Arctic.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".