Comparing the diel cycles of dissolved organic matter fluorescence in a clear-water and two dark-water Wisconsin lakes: potential insights into lake metabolism
Bibliographic record
Abstract
The cycling of organic carbon is fundamental to aquatic ecosystems, reflecting processes that extend from terrestrial watersheds to fish. Here, we use embedded fluorescence sensors that sample at high frequency to investigate the daily dynamics of a proxy for the major pool of organic carbon (chromophoric dissolved organic matter, CDOM) in a clear-water Wisconsin lake (∼3 mg C·L−1). We compare the diel CDOM cycle in this lake with cycles observed previously in two dark-water lakes (10 to 20 mg C·L−1). Despite differences in DOM quality and quantity, diel fluorescence cycles were evident in the epilimnia and hypolimnia of all three lakes. The amplitude differed among lakes, but the timing of the diel cycles was similar, with increases in fluorescence during nighttime and decreases during daylight (except in the aphotic hypolimnion of the darkest lake). The amplitude of the diel cycle increased with increasing DOM concentration, and estimates of DOM turnover based on the magnitude of oscillation ranged from 0.28 mg C·L−1·day−1 in the darkest lake to 0.14 mg C·L−1·day−1 in the clear lake. Independent estimates of free water metabolism based on the daily dynamics of O2 or CO2 were in general agreement, ranging from 0.32 to 0.06 mg C·L−1·day−1. Although absolute rates of turnover varied directly with DOM concentration, relative rates were highest in clear waters (∼5%·day−1). We conclude that these daily oscillations may be a common property of lakes and that they may provide insights into internal DOM processing over short time scales.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".