Reduced recruitment of Chinook salmon in a leveed bar-built estuary
Bibliographic record
Abstract
Estuaries are commonly touted as nurseries for salmonids, providing numerous advantages for smolts prior to ocean entry. In bar-built estuaries, sandbars form at the mouth of rivers during periods of low stream flow, closing access to the ocean and preventing outmigration. We evaluated how summer residency in a leveed bar-built estuary affects the growth, survival, and recruitment of a Chinook salmon (Oncorhynchus tshawytscha) population. We performed a mark–recapture study on outmigrants to determine juvenile estuary abundance, growth, and survival. We used returning adult scales and otoliths to determine the relative proportion of summer estuary residents in spawning adults. Juveniles in the estuary grew less after mouth closure, and ultimately summer estuary residents had lower smolt-to-adult survival and contributed disproportionately less to the spawning population than juveniles that reared in the ocean their first summer. Mouth closure may lower food availability and deteriorate estuary conditions by reducing marine prey influx and estuary circulation. This research demonstrates the complexity of estuary dynamics and function as salmonid nurseries, particularly when considering the extensive modification of estuaries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".