Fisheries escape, temperature, and infectious agents: multiple stressors impacting wild sockeye salmon spawning migrations
Bibliographic record
Abstract
Across the globe animals that engage in migration are exposed to many threats.This is exemplified by the decline of Pacific salmon populations.Understanding causes behind declines of migratory Pacific salmon populations will help mitigate the threats these fish face during their iconic migrations.Spawning migrations return adult salmon from ocean feeding grounds to natal freshwater habitats to spawn and complete their lifecycle.These spawning migrations are naturally challenging, but due to human activity salmon are now also forced to navigate a gauntlet of fishing gears and dams, all while water temperatures are rising.This thesis aims to investigate how fishing gear escape, water temperature, and infectious agents affect a population of Fraser River sockeye salmon (Oncorhynchus nerka) during their spawning migration.Approximately half of all fish that experienced a simulated gillnet entanglement were capable of volitional escape, suggesting gear escape is a frequent event for in-river fisheries.Despite finding no impact of fisheries escape on migration or spawning success, I did find novel evidence of behavioural thermoregulation following escape.High water temperatures confounded results of fisheries interactions due to exceptionally high mortality.During a year of warm river temperatures, fish showed increased expression of thermal stress biomarkers, dramatically reduced survival, and differences in infectious agent profiles compared with a cooler year.Infectious agent profiles were also analyzed in fish that perished below a dam, and differences in certain infectious agent prevalence and loads were found when compared with live fish, suggesting a possible involvement of infectious agents in en-route mortality.Behavioural thermoregulation was also observed in fish with higher overall infectious agent burden.This thesis adds further evidence demonstrating the severe consequences of high water temperatures for Pacific salmon.In an era of warming waters, thermal selection may be an increasingly important behaviour to improve survival and spawning success.I also demonstrate that escape from fishing gear can be a common occurrence that is currently unaccounted for in escapement estimates.Fisheries managers should consider incorporating gear escape consequences in escapement estimate models, and protecting thermal refuges along migration corridors, to help protect Pacific salmon 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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".