Fluorescent dissolved organic matter in lakes: Relationships with heterotrophicmetabolism
Bibliographic record
Abstract
Characterizing dissolved organic matter (DOM) composition remains a major unresolved problem in aquatic ecology and is one of the key impediments to developing a good understanding of DOM production and consumption by heterotrophic bacteria. Fluorescence spectroscopy has been proposed as a promising method for characterizing DOM, but few links have been demonstrated between DOM fluorescence and DOM composition or the processes affected by DOM composition. In 28 southern QueÂbec lakes, tryptophan‐like DOM fluorescence (TFDOM) was found to be a much better descriptor of rates of heterotrophic bacterial metabolism than dissolved organic carbon, describing 52%, 44%, 51%, and 55% of the variability in bacterial production, bacterioplankton respiration, total bacterial carbon consumption, and total plankton community respiration, respectively. In addition, evidence from a series of bacterial regrowth cultures suggests that T‐FDOM represents a product of bacterial activity as well as, to a lesser extent, a bioavailable substrate. Our results instead raise the intriguing possibility that TFDOM concentration reflects a balance between its production and consumption by bacteria. We demonstrate here that fluorescence spectroscopy can be used to identify a highly dynamic fraction of DOM related to bacterial metabolism in lakes.
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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 | 0.000 | 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 | 0.000 | 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".