Slow dam passage in adult Columbia River salmonids associated with unsuccessful migration: delayed negative effects of passage obstacles or condition-dependent mortality?
Bibliographic record
Abstract
The relationships among behavior, environment, and migration success in anadromous fishes are poorly understood. We monitored migration behavior at eight Columbia and Snake river dams for 18 286 adult Chinook salmon (Oncorhynchus tshawytscha) and steelhead (sea-run Oncorhynchus mykiss) over 7 years using radiotelemetry. When statistically controlling for variation in flow, temperature, fisheries take, and other environmental variables, we observed that unsuccessful individuals — those not observed to reach spawning areas — had longer passage times at nearly all dams than fish that eventually reached tributaries. In many cases, times were also longer for unsuccessful adults passing through a multiple-dam reach. Four ecological mechanisms may have contributed to these patterns: (i) environmental factors not accounted for in the analyses; (ii) inefficient responses by some fish to passage conditions at dams that resulted in slowed passage, energetic depletion, and unsuccessful migration; (iii) ongoing selection for traits needed to pass obstructions; and (or) (iv) passage rate was not directly linked to migration success, but rather, both resulted from relatively poor phenotypic condition upon river entry in unsuccessful migrants. Overall, these results illustrate the need for a mechanistic understanding of the factors that influence migration success and the need for fitness-based criteria to assess the effects of dams on anadromous fishes.
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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 | 0.002 |
| 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".