Survival of a threatened salmon is linked to spatial variability in river conditions
Bibliographic record
Abstract
Extirpation of the Central Valley spring-run Chinook salmon ( Oncorhynchus tshawytscha) evolutionary significant unit (ESU) from the San Joaquin River is emblematic of salmonid declines across the western seaboard of the United States. Habitat restoration and fish reintroduction efforts are ongoing, but recent telemetry studies have revealed low outmigration survival of juveniles to the ocean. Previous investigations have focused on modeling survival relative to river discharge and geographic regions, but have largely overlooked the effects of habitat variability. To evaluate the link between environmental conditions and survival of juvenile spring-run Chinook salmon, we combined high spatial resolution habitat mapping approaches with acoustic telemetry along a 150 km section of the San Joaquin River during the spring of 2019. While overall outmigration survival was low (5%), our habitat-based classification scheme described variation in survival of acoustic-tagged smolts better than other candidate models based on geography or distance. Two regional mortality sinks were evident along the longitudinal profile of the river, revealing poor survival in areas that shared warmer temperatures but that diverged in chlorophyll a, fluorescent dissolved organic matter (fDOM), turbidity, and dissolved oxygen levels. These findings demonstrate the value of integrating river habitat classification frameworks to improve our understanding of survival dynamics of imperiled fish populations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".