Wildfire in western Oregon increases stream temperatures, benthic biofilms, and juvenile coastal cutthroat trout size and densities with mixed effects on adult trout and coastal giant salamanders
Bibliographic record
Abstract
Wildfire has become increasingly common and severe across forested landscapes. Shortly after wildfire, loss of riparian cover along streams and subsequent increases in light can elevate stream temperatures, a key control on metabolic rates of biota. Increased light can also increase autotrophic basal resource availability with potential bottom-up effects. We evaluated wildfire impacts on aquatic ecosystems in a replicated Before-After Control-Impact study 1 year after a severe wildfire in western Oregon, U.S. Stream temperature, chlorophyll a accrual, and age-0 coastal cutthroat trout size, density, and biomass increased in all three burned streams relative to changes in three unburned references. When streams were evaluated collectively, fire did not have an effect on larger vertebrate density or biomass. However, considering streams individually, two severely burned sites had substantial temperature increases and declines in larger vertebrate density and biomass, but the moderately burned site had modest temperature increases and adult cutthroat trout and Pacific giant salamanders increased. The loss of riparian canopies post-fire increased temperature and algae, but fish responses varied with age class and larger vertebrate responses were inconsistent.
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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".