Forestry influences on salmonid habitat in the North Thompson River watershed, British Columbia
Bibliographic record
Abstract
Freshwater ecosystems that support juvenile salmonids can be degraded by human pressures such as forestry. Forestry activities can alter water temperatures and the delivery and storage of water, nutrients, wood, and sediment in streams, resulting in changes to the habitat, growth, and survival of juvenile salmon. Previous research on forestry impacts on habitat has focused on small, intensively monitored coastal systems. Here, we examined forestry activities, watershed characteristics, physical habitat, and stream temperature for 28 mid-sized tributaries of the North Thompson River to examine relationships between forestry and juvenile coho stream habitat in interior watersheds. Forest harvest had a positive correlation to maximum summer stream temperature. Streams with 35% of the riparian area harvested since 1970 had maximum summer temperatures 3.7 °C higher on average than those with 5% harvested. Stream gradient explained most of the variation in physical habitat and had negative correlations to pool cover, pool depth, and fine sediment cover. Taken together, these results indicate that watershed characteristics drive physical habitat, but forest harvest can be a primary driver of water temperatures.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".