Range‐Wide Selection of Catchments for Pacific Salmon Conservation
Bibliographic record
Abstract
Freshwater ecosystems are declining in quality globally, but a lack of data inhibits identification of areas valuable for conservation across national borders. We developed a biological measure of conservation value for six species of Pacific salmon (Oncorhynchus spp.) in catchments of the northern Pacific across Canada, China, Japan, Russia, and the United States. We based the measure on abundance and life-history richness and a model-based method that filled data gaps. Catchments with high conservation value ranged from California to northern Russia and included catchments in regions that are strongly affected by human development (e.g., Puget Sound). Catchments with high conservation value were less affected by agriculture and dams than other catchments, although only 1% were within biodiversity reserves. Our set of high-value areas was largely insensitive to simulated error, although classification remained uncertain for 3% of catchments. Although salmon face many threats, we propose they will be most likely to exhibit resilience into the future if a complementary mosaic of conservation strategies can be proactively adopted in catchments with healthy salmon populations. Our analysis provides an initial map of where these catchments are likely to be located.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".