Divergent Responses of Western Alaska Salmon to a Changing Climate, 2023
Bibliographic record
Abstract
Pacific salmon populations in western Alaska have responded differently to recent climatic changes, with Chinook salmon (Oncorhynchus tshawytscha) and chum salmon (O. keta) reaching record low abundance levels, while sockeye salmon (O. nerka) have attained record high abundance levels since 2020. Why these species have responded differently has important implications for the future of Pacific salmon in a warming Arctic. Here, we refer to “western Alaska” salmon as those spawning in watersheds that drain into the eastern Bering Sea. Indigenous Peoples in this region, including First Nations communities residing along Canadian tributaries to the Yukon River, have been tied to salmon for at least 12,000 years, while commercial fisheries have been economic mainstays since the late 1800s (Carothers et al. 2021). Salmon populations in this region have global significance, producing over half of the world’s commercial catch of sockeye salmon from Bristol Bay and have historically supported the world’s largest subsistence fisheries for Chinook and chum salmon in the Yukon and Kuskokwim watersheds. These species, and to a lesser extent, pink (O. gorbuscha) and coho (O. kisutch) salmon, remain a critical source of food, employment and cash income, and cultural practices essential for communities’ well-being and traditional ways of life (Brown and Godduhn et al. 2015). We report evidence of these changes primarily through the lens of western science, focusing on a few well-studied stocks, and we acknowledge this essay does not convey the breadth of perspectives or the complexity of ecological changes across the region.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 | 0.002 |
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".