Spring bloom dynamics in a subarctic fjord influenced by tidewater outlet glaciers (Godthåbsfjord, SW Greenland)
Bibliographic record
Abstract
Abstract In high‐latitude fjord ecosystems, the spring bloom accounts for a major part of the annual primary production and thus provides a crucial energy supply to the marine food web. However, the environmental factors that control the timing and intensity of these spring blooms remain uncertain. In 2013, we studied the spring bloom dynamics in Godthåbsfjord, a large fjord system adjacent to the Greenland Ice Sheet. Our surveys revealed that the spring bloom did not initiate in the inner stratified part of the fjord system but only started farther away from tidewater outlet glaciers. A combination of out‐fjord winds and coastal inflows drove an upwelling in the inner part of the fjord during spring (April–May), which supplied nutrient‐rich water to the surface layer. This surface water was subsequently transported out‐fjord, and due to this circulation regime, the biomass accumulation of phytoplankton was displaced away from the glaciers. In late May, the upwelling weakened and the dominant wind direction changed, thus reversing the direction of the surface water transport. Warmer water was now transported toward the inner fjord, and a bloom was observed close to the glacier terminus. Overall, our findings imply that the timing, intensity, and location of the spring blooms in Godthåbsfjord are controlled by a combination of upwelling strength and wind forcing. Together with sea ice cover, the hydrodynamic regime hence plays a crucial role in structuring food web dynamics of the fjord ecosystem.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".