Bacteria and algae in stream periphyton along a nutrient gradient
Bibliographic record
Abstract
Summary 1. Stream riffles in southern Ontario and western Quèbec were sampled for biomass (58 stations from 51 streams) and production (22 stations from 21 streams) of algae and bacteria in periphyton to test the hypothesis that bacteria in benthic biofilms compete with algae for nutrients. 2. Algal and bacterial biomass were positively correlated, as were algal and bacterial production. Bacterial production was also positively correlated to algal and bacterial biomass, but the relationship was not significant. The ratio of algal to bacterial biomass did not vary with nutrients whereas algal production tended to increase with nutrients more rapidly than bacterial production. 3. Instream nitrogen concentrations explained 38–58% of the variability in algal biomass and production. Bacterial abundance explained an additional 9–29% of the residual variance in algal production and biomass. However, the relationship between bacterial abundance and algal production and biomass, once nutrients were taken into account, was positive, in contrast to the predicted effect of competition. 4. Hence, we reject our original hypothesis that bacteria in biofilms compete with algae for nutrients and instead suggest that bacteria and algae in biofilms coexist in an association that offers space and resources to sustain production of both groups of organisms.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".