Migration timing affects the foraging ecology of Fraser River sockeye salmon stocks in coastal waters of British Columbia, Canada
Bibliographic record
Abstract
Coastal migrations of juvenile Pacific salmon Oncorhynchus spp. have evolved to take advantage of optimal ocean foraging conditions and maximize early marine growth and survival. The growth and survival of salmon during the early marine period is affected by both the diversity of encountered coastal habitats, with varying productivity and plankton phenology, and stock-specific migration timings that determine the match-mismatch with their prey. In 2015 and 2016, we investigated temporal and spatial patterns in environmental conditions and zooplankton prey as well as diets and stock composition of juvenile Fraser River sockeye O. nerka during their outmigration through the tidally mixed Discovery Islands and Johnstone Strait in British Columbia (Canada). Three groups of sockeye diet profiles reflected variations in environmental conditions and prey communities. First, in the Discovery Islands, earlier migrating stocks primarily encountered and foraged on small, energy-poor zooplankton prey (barnacles and cladocerans). Second, later migrating stocks foraged mainly on larger, more energy-rich copepod and larvacean prey. And third, in the highly mixed waters of Johnstone Strait, large energy-rich calanoid copepods dominated diets irrespective of migration timing and year. Foraging success was typically low throughout the areas sampled and across the migration period, which may amplify the importance of prey nutritional quality. Our findings highlight the importance of accounting for spatial and temporal differences in foraging environments for migrating species such as juvenile salmon. Furthermore, we demonstrate that the timing of stock migration affects the foraging conditions experienced.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".