Response of the Cache Creek macroinvertebrates during the first 10 years following disturbance by the 1988 Yellowstone wildfires
Bibliographic record
Abstract
We evaluated the effects of disturbance on stream benthic macroinvertebrates at the ecological scales of time, stream size, and burn extent in six segments of Cache Creek over the first 10 postfire years. Postfire changes in macroinvertebrate taxa richness, density, and dominant taxa in the burn streams were significantly different from those in the reference stream. Chironomidae and Baetis typically comprised 4060% of the macroinvertebrate assemblages of burned streams but only 1518% of the assemblage in the reference site. Coefficients of variation for the 10-year period indicated that richness, density, biomass, and Baetis abundance were more variable (1.23.5 times higher) in the burn streams than in the reference stream and that variability in Chironomidae abundance in burn sites increased with stream size. Fire effects were not attenuated progressively with increasing stream size, probably because the proportion of the catchment burned did not decrease. However, similar-sized streams in which 6871% of their catchments burned were more severely disturbed than those in which only 3947% burned. Long-term effects on the macroinvertebrate community were due largely to the loss of terrestrial vegetation and increased runoff, which caused severe alterations in stream channel conditions and large-scale bedload movement.
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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 | 0.002 |
| 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".