Coherent population dynamics associated with sockeye salmon juvenile life history strategies
Bibliographic record
Abstract
Although the importance of diversity to maintaining metapopulation stability is widely recognized, the ecological characteristics that lead to synchronous dynamics within population aggregates are often unclear. We used a constrained dynamic factor analysis to explore patterns of covariance in productivity among 16 Fraser River sockeye salmon (Oncorhynchus nerka) conservation units (CUs). Specifically, we tested whether coherent trends in productivity covaried with five distinct ecological attributes: physical characteristics of nursery lakes, large-scale management interventions, genetic similarity, adult migration phenology, or juvenile migratory traits. The top-ranked model had two trends based on nursery lake characteristics and juvenile migratory traits. One trend represented the dynamics of CUs that rear in nursery lakes prior to ocean entry and undergo relatively rapid marine migrations. The second included a sea-type CU, Harrison River, which enters the marine environment without rearing in a nursery lake and migrates more slowly. The uniform response of lake-type CUs, as well as Harrison River CU’s unique life history, suggests that coherent trends are structured by traits that covary with broad life history type, rather than fine-scale characteristics. Furthermore, we document substantial temporal variability in the strength of synchronous dynamics among Fraser River CUs. Greater synchrony in recent years suggests that the importance of shared regional drivers, relative to local processes, may have increased.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".