Quantifying the effects of stream habitat on populations of breeding Pacific salmon
Bibliographic record
Abstract
Recognizing the mechanisms by which environmental conditions drive population dynamics can greatly benefit conservation and management. For example, reductions in densities of spawning Pacific salmon (Oncorhynchus spp.) have received considerable attention, but the role of habitat characteristics on population sizes of breeding salmon is not fully understood. We studied relationships between habitat characteristics and stream population densities of spawning chum (Oncorhynchus keta) and pink (Oncorhynchus gorbuscha) salmon in 44 streams in the Great Bear Rainforest of coastal British Columbia, Canada, with individual streams as the unit of comparison. Our results indicate that a small number of habitat characteristics are important in predicting population density of spawning chum and pink salmon in streams, namely pH for chum salmon and riparian slope and large wood volume for pink salmon. This is the largest multivariable comparison to examine habitat–population relationships in adult spawning salmon and may provide useful quantitative emphasis in guiding management.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".