Wintertime water dynamics and moonlight disruption of the acoustic backscatter diurnal signal in an ice‐covered Northeast Greenland fjord
Bibliographic record
Abstract
Abstract Six and a half month records from three ice‐tethered Acoustic Doppler Current Profilers deployed in October 2013 in Young Sound fjord in Northeast Greenland are used to analyze the acoustic backscatter signal. The acoustic data suggest a systematic diel vertical migration (DVM) of scatters below the land‐fast ice during polar night. The scatters were likely composed of zooplankton. The acoustic signal pattern typical to DVM persisted in Young Sound throughout the entire winter including the period of civil polar night. However, polynya‐enhanced estuarine‐like cell circulation that occurred during winter disrupted the DVM signal favoring zooplankton to occupy the near‐surface water layer. This suggests that zooplankton avoided spending additional energy crossing the interface with a relatively strong velocity gradient comprised by fjord inflow in the intermediate layer and outflow in the subsurface layer. Instead, the zooplankton tended to remain in the upper 40 m layer where relatively warmer water temperatures associated with upward heat flux during enhanced estuarine‐like circulation could be energetically favorable. Furthermore, our data show moonlight disruption of DVM in the subsurface layer and weaker intensity of vertical migration beneath snow covered land‐fast ice during polar night. Finally, by using existing models for lunar illuminance and light transmission through sea ice and snow cover, we estimated under ice illuminance and compared it with known light sensitivity of Arctic zooplankton species.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".