Spatially overlapping salmon species have varied population response to early life history mortality from increased peak flows
Bibliographic record
Abstract
In the Pacific Northwest, USA, climate change is expected to result in a shift in average hydrologic conditions and increase variability. The relative vulnerabilities to peak flow changes among salmonid species within the same basin have not been widely evaluated. We assessed the impacts of predicted increases in peak flows on four salmonid populations in the Chehalis River basin. Coupling observations of peak flows, emissions projections, and multi-stage Beverton–Holt matrix-type life cycle models, we ran 100-year simulations of spawner abundance under baseline, mid-century, and late-century climate change scenarios. Coho (Oncorhynchus kisutch) and spring Chinook salmon (Oncorhynchus tshawytscha) shared the highest projected increase in interannual variability (SD = ±15%). Spring Chinook salmon had the greatest reduction in median spawner abundance (–13% to –15%), followed by coho and fall Chinook salmon (–7% to –9%), then steelhead (Oncorhynchus mykiss) (–4%). Our results show that interspecies and life history variability within a single basin is important to consider. Species with diverse age structures are partially buffered from population variability, which may increase population resilience to climate change.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".