Predator swamping reduces predation risk during nocturnal migration of juvenile salmon in a high‐mortality landscape
Bibliographic record
Abstract
Animal migrations are costly and are often characterized by high predation risk for individuals. Three of the most oft-assumed mechanisms for reducing risk for migrants are swamping predators with high densities, specific timing of migrations and increased body size. Assessing the relative importance of these mechanisms in reducing predation risk particularly for migrants is generally lacking due to the difficulties in tracking the fate of individuals and population-level characteristics simultaneously. We used acoustic telemetry to track migration behaviour and survival of juvenile sockeye salmon (Oncorhynchus nerka) smolts released over a wide range of conspecific outmigration densities in a river associated with poor survival. The landscape was indeed high risk; smolt survival was poor (˜68%) over 13·5 km of river examined even though migration was rapid (generally <48 h). Our results demonstrate that smolts largely employ swamping of predators to reduce predation risk. Increased densities of co-migrant conspecifics dramatically improved survival of smolts. The strong propensity for nocturnal migration resulted in smolts pausing downstream movements until the next nightfall, greatly increasing relative migration durations for smolts that could not traverse the study area in a single night. Smolt size did not appear to impact predation risk, potentially due to unique characteristics of the system or our inability to tag the entire size range of outmigrants. Movement behaviours were important in traversing this high-risk landscape and provide rare evidence for swamping to effectively reduce individual predation risk.
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".