Stream acidification and mortality of brook trout (<i>Salvelinus fontinalis</i>) in response to timber harvest in Catskill Mountain watersheds, New York, USA
Bibliographic record
Abstract
Effects of clear-cut and timber-stand improvement (TSI) harvests on water chemistry and mortality of caged brook trout (Salvelinus fontinalis) were evaluated in a study of three Catskill Mountain streams, 19942000. Harvests removed 73% of tree basal area (BA) from a clearcut subbasin, 5% BA from a TSI subbasin, and 14% BA at a site below the confluence of both streams. A fourth nonharvested site served as a control. Water quality and trout mortality were affected only in the clearcut stream. Acidity and concentrations of nitrate and inorganic monomeric aluminum (Alim) increased sharply during high flows after the first growing season (fall 1997). AcidAlim episodes were severe during this period and decreased steadily in magnitude and duration thereafter. All trout at this site died within 7 days during spring 1998 and 85% died during spring 1999. Only background mortality was observed in other years at this site and at the other three sites during all tests. The absence of mortality in TSI watersheds indicates that limited harvests should not harm brook trout populations in acid-sensitive streams. Effects of tree harvests on fish communities are of concern, however, because many stream-dwelling species are more sensitive to acidified waters than brook trout.
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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".