Raised water temperature lowers diversity of hyporheic aquatic hyphomycetes
Bibliographic record
Abstract
Summary 1. The hyporheic zone of a permanent first‐order stream was divided into a treatment and a control section using a 1 m deep sheet‐metal barrier. During a 4‐month pre‐treatment period, water temperatures in two transects of the two sections were not different. Upon heating, the water temperature in the treatment transect increased by an average of 4.3 °C over values in the control transect. 2. Eleven bimonthly core samples were taken from a treatment and a control transect, and recovered CPOM was classified as twigs, wood, grass, roots, cedar and deciduous leaves. 3. In both transects, twigs were the most common and deciduous leaves the least common substrates. The number of leaf fragments declined significantly in the heat‐treated transect. 4. Diversity and frequencies of occurrence of aquatic hyphomycetes were highest on leaves and lowest on grass and wood. On leaves, their frequency of occurrence was higher in control than in treatment samples. 5. Preliminary results with amplified and cloned 18S DNA sequences revealed many fungal taxa with high affinities to Basidiomycota, particularly to Limnoperdon incarnatum. 6. By itself, higher water temperature due to global warming is likely to lower the availability of substrates for, and therefore the occurrence of, aquatic hyphomycetes.
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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 | 0.000 | 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".