In the cold light of day: the potential importance of under-ice convective mixed layers to primary producers
Bibliographic record
Abstract
Temperate lakes are ice covered for much of the year; however, winter lake conditions have not been well studied and are undergoing rapid change. Using data collected during ice-on periods from 4 north-temperate water bodies, we report observations of stable surface layers, solar-induced convective mixed layers, and their potential impacts on phytoplankton. The convective mixed layer is defined as the region where the convective Richardson number (Ri) is ≤1. In the absence of a convective mixed layer, peaks in chlorophyll a were near the ice–water interface. Light conditions here seemed sufficient to support phytoplankton biomass accrual in the short-term in 50% of our measurements, although snow depths >13.5 cm may lead to light limitation. When a convective mixed layer was present, light conditions were sufficient for biomass accrual in 37.5% of cases. The frictional timescale for damping averaged 15 minutes, indicative of a lack of mixing at night. Convective mixing depths and velocity increased as snow declined, and results demonstrated the potential for rapid convective mixed layer deepening (up to 6.6 m h−1), underscoring the highly dynamic physical environment under ice. Although declining periods of ice cover have been subject to much attention, changes in snow cover may have equally important implications for primary producers and the potential for under-ice blooms. This link between physics and biology must be further explored to better understand how changing winters will affect water bodies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 teacher head, 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".