Atlantic salmon (Salmo salar) smolt and early post-smolt migration and survival inferred from multi-year and multi-stock acoustic telemetry studies in the Gulf of St. Lawrence, northwest Atlantic
Bibliographic record
Abstract
Abstract The migration dynamics and inter-annual variation in early at-sea survival of Atlantic salmon (Salmo salar) smolts over 14 years of study are reported for four river populations located in the Gulf of St. Lawrence (Canada). Acoustically tagged smolts were monitored at three points along their migration from freshwater to the Labrador Sea, a migration extending more than 800 km at sea and a period of 2 months. A hierarchical state-space version of the Cormack–Jolly–Seber model was used to estimate apparent survival rates from incomplete acoustic detections at key points. There was a positive size-dependent probability of survival through the freshwater and estuary areas; the odds of survival of a 16 cm smolt were 1.5–1.7 times higher than for a 13.5 cm smolt, length at tagging. Length adjusted (centred to the mean fork length of smolts during the study of 14.6 cm) survivals through the estuary and nearshore waters were estimated to range between 67 and 90% for the two river populations migrating through Chaleur Bay in contrast to lower survival estimates of 28–82% for the two populations from the neighbouring Miramichi Bay. Across the 14 years of study, survival estimates varied without trend for the populations of Chaleur Bay, but declined for the populations migrating through Miramichi Bay. Survival through the Gulf of St. Lawrence was variable but generally high among years and rivers, ranging from 96% day−1 to 99% day−1. Long term, replicated studies at multiple sites using acoustically tagged smolts can provide empirical data to examine hypotheses of the location and timing of factors contributing to smolt and post-smolt mortality of salmon at sea.
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 | 0.001 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".