A commentary on the role of hatcheries and stocking programs in salmon conservation and adapting ourselves to less‐than‐wild futures
Bibliographic record
Abstract
Abstract Hatcheries and stocking programs serve a variety of objectives, including the conservation of salmon populations. Much attention has been given to the importance of genetic integrity and adaptive capacity of salmon stocks, particularly as they interact with hatchery‐origin fish. Literature on hatchery and stocking programs has increasingly focused on genetic indicators of quality and success, with genetically ‘wild’ salmon valued over hatchery‐influenced salmon. However, conservation in the Anthropocene is challenging paradigms of wildness and definitions of conservation success. For salmon populations that exist on the ragged edge of climate change where threats are unlikely to be remediated to the status of ecologies past, definitions of ‘wild’ and the role of conservation hatcheries and stocking becomes convoluted. If definitions of ‘wild’ or ‘natural’ salmon depend on salmon archetypes situated in historic ecologies, then what do salmon futures look like? In that context, we argue to expand from primarily genetic criteria for conservation stocking to additional criteria cognizant of hybrid ecosystems and future human‐salmon relationships. We draw on the concept of adaptive epistemologies within the context of conservation‐oriented hatchery and stocking programs to critically reflect on knowledge paradigms and values that underlie salmon conservation stocking efforts and the changing ecosystems in which they are situated. We critique ‘wild’ discourses rooted in western thought and make suggestions toward a reimagining of salmon conservation‐via‐hatchery in the Anthropocene that allows for expansive human‐salmon futures. Critically, we conclude with warnings against using the arguments in this paper as social permission to use hatcheries as a conservation panacea.
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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 | 0.021 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.015 | 0.020 |
| Scholarly communication | 0.008 | 0.013 |
| Open science | 0.007 | 0.005 |
| Research integrity | 0.061 | 0.069 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".