Population dynamics and asynchrony at fine spatial scales: a case history of sockeye salmon (<i>Oncorhynchus nerka</i>) population structure in Alaska, USA
Bibliographic record
Abstract
Pacific salmon (Oncorhynchus spp.) exemplify the ways in which populations are structured by homing and the abiotic factors affecting their dynamics in discrete breeding and rearing habitats. What is the finest spatial scale of their population structure, and where do clusters of spatially proximate breeding groups lie along the continuum from isolated populations – metapopulation – patchy panmictic population? To investigate these questions, we monitored sockeye salmon, Oncorhynchus nerka, spawning in a complex of habitats ~1 km apart, joining to form a single stream flowing into Iliamna Lake, Alaska, USA. Annual surveys revealed levels of asynchrony in productivity that were comparable with values reported for sockeye salmon spawning in separate streams flowing into lakes elsewhere in Bristol Bay. A mark–recapture study revealed very little movement of spawning adults among habitats. The ponds occupied at highest density varied among years, and salmon consistently arrived and spawned later in one pond than the others. These results are consistent with the hypothesis that the salmon structured as a small-scale metapopulation rather than a single panmictic population.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".