Synchronous Biodegradability and Production of Dissolved Organic Matter in Two Streams of Varying Land Use
Bibliographic record
Abstract
In aquatic ecosystems, dissolved organic matter (DOM) composition is driven by land use, microbial activity, and seasonal variation in hydrology and water temperature, and, in turn, its microbial bioavailability is expected to vary due to differences in its composition. It is commonly assumed that DOM of terrestrial origin is resistant to microbial activity because it is composed of more complex aromatic compounds. However, the effect of DOM sources on the microbial reworking and degradation of the DOM pool remains debated. We performed laboratory incubation experiments to examine how temporal changes in DOM composition influence its microbial biodegradability in two contrasting streams (agricultural and forested) in southern Ontario, Canada. Despite a more allochthonous-like DOM signature in the forest stream and a more autochthonous-like DOM signature in the agriculture stream, we found that biodegradation and production of DOC were the same in both streams and synchronous throughout the sampling period. However, the initial DOM composition impacted how the DOM pool changed upon degradation. During the incubations, both autochthonous-like and allochthonous-like fractions of the DOM pool increased. We also found that a greater change in DOM composition during the incubations induced higher degradation of carbon. Finally, temporal variation in DOC biodegradation and production over time or across streams was not related to DOM composition, although there was a significant relationship between BDOC and nutrient concentrations in the agriculture stream. This observation potentially challenges the notion that DOM origin predicts its bioavailability and suggests that broad environmental factors shape DOC consumption and production in aquatic ecosystems. More research is needed to better understand the drivers of microbial biodegradability in streams, as this ultimately determines the fate of DOM in aquatic ecosystems.
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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 | 0.001 |
| 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".