Migratory Timing and Rates of Chinook Salmon Bound for the Kwethluk and Kisaralik Rivers
Bibliographic record
Abstract
Abstract Detailed information regarding migratory behavior (i.e., phenology and rate of travel) of specific Pacific salmon Oncorhynchus spp. substocks can be used to design management strategies focused on protecting substocks from harvest when desired; however, this information is often lacking. The Kwethluk and Kisaralik rivers are two tributaries of the lower Kuskokwim River that originate and flow through the Yukon Delta National Wildlife Refuge in western Alaska. Although these two systems are the primary Chinook Salmon–producing tributaries within the Yukon Delta National Wildlife Refuge, little is known about migratory behavior of Chinook Salmon destined for these rivers. In 2015 and 2016, 119 Chinook Salmon tagged with radio telemetry transmitters entered either the Kwethluk or Kisaralik Rivers and were tracked throughout their migration to their assumed final spawning location using both ground- and aerial-based tracking methods. We compared migration timing and swim speeds between fish bound for these two rivers and between fish of different sizes and compared the consistency among the 2 y. In general, we found that fish bound for the Kwethluk and Kisaralik rivers exhibited similar migration behaviors in 2015 and 2016, including entry timing into the Kuskokwim River and migration rates once in the tributaries. A key finding was that Chinook Salmon swam fastest (range of means between years: 20–45 km/d) in the main-stem Kuskokwim River and slowed significantly (4–15 km/d) upon entry into lower portions of the tributaries. Our findings have relevance for harvest management strategies; for example, temporal fishery closures will impact Chinook Salmon bound for both the Kwethluk and Kisaralik rivers equally given their broad overlap in entry timing, and individuals will remain vulnerable to harvest for longer periods when located in tributaries rather than the portion of the main-stem directly below the tributary confluences.
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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 | 0.001 |
| 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) | 0.001 | 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".