Food Security and Conservation of Yukon River Salmon: Are We Asking Too Much of the Yukon River?
Bibliographic record
Abstract
By the terms set by international agreements for the conservation of Yukon River salmon, 2009 was a management success. It was a devastating year for many of the Alaska Native communities along the Yukon River, however, especially in up-river communities, where subsistence fishing was closed in order to meet international conservation goals for Chinook salmon. By the end of summer, the smokehouses and freezers of many Alaska Native families remained empty, and Alaska’s Governor Sean Parnell petitioned the US Federal Government to declare a fisheries disaster. This paper reviews the social and ecological dimensions of salmon management in 2009 in an effort to reconcile these differing views regarding success, and the apparently-competing goals of salmon conservation and food security. We report local observations of changes in the Chinook salmon fishery, as well as local descriptions of the impacts of fishing closures on the food system. Three categories of concern emerge from our interviews with rural Alaskan participants in the fishery and with federal and state agency managers: social and ecological impacts of closures; concerns regarding changes to spawning grounds; and a lack of confidence in current management methods and technologies. We show how a breakdown in observation of the Yukon River system undermines effective adaptive management and discuss how sector-based, species-by-species management undermines a goal of food security and contributes to the differential distribution of impacts for communities down and up river. We conclude with a discussion of the merits of a food system and ecosystem-based approach to management, and note existing jurisdictional and paradigmatic challenges to the implementation of such an approach in Alaska.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".