Early Stuart sockeye salmon metapopulation data
Bibliographic record
Abstract
There is a need to explicitly consider metapopulation dynamics in the development of conservation strategies for spatially-structured populations. We examined the spatial dynamics of sockeye salmon (Oncorhynchus nerka) that spawn in 36 streams of the Stuart River watershed in British Columbia, Canada, using a 69-year record of spawner abundance and a demographically-based Bayesian dynamic occupancy model. We identified a set of 12 streams with good habitat conditions that were occupied >90% of years despite large year-to-year changes in abundance. Over 85% of spawners were concentrated in these streams. Many other streams with poorer habitat had small populations that were not persistent over time and were periodically recolonized by dispersers from other streams. Although it is often assumed population diversity and resiliency is maximized when all available habitats are used, for this salmon metapopulation, resiliency is due to the core streams of higher habitat quality. Currently other streams make only small contributions to population abundance, however, some may have conservation value if their habitats become more suitable for spawning in the future.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.012 |
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".