Influence of velocity and chlorophyll standing stock on periphyton δ<sup>13</sup>C and δ<sup>15</sup>N in the Ste. Marguerite River system, Quebec
Bibliographic record
Abstract
In a previous laboratory experiment, water velocity had a strong negative effect on periphyton δ13C and δ15N, probably reflecting the effect of flow on boundary-layer exchange. To determine whether similar patterns could be detected in situ at different spatial scales, we examined several reaches, each with a wide range in water velocity and chlorophyll standing stock. Periphyton samples were uniform in composition, composed predominantly of living and dead diatoms of very few species. δ13C signatures were more variable (–17.7 to –31.5) than δ15N signatures (–0.4 to 5.7). Velocity and chlorophyll were significant predictors of periphyton δ13C within reaches, mainly at medium scales (10–500 m) where persistent alternations between fast and slow current (riffles–runs–pools) produced inverse fluctuations of periphyton δ13C. However, none of the variability in δ15N could be explained, possibly a result of severe boundary-layer N depletion. Similarly, the velocity and chlorophyll predictors could not explain the among-reach signature differences for either isotope. δ13C signatures tended to be13C-depleted in the tributary streams and13C-enriched in the downstream reaches.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".