Beyond fish: Social outcomes of Maritimes region atlantic salmon hatcheries and stocking programs through a social-ecological systems lens
Bibliographic record
Abstract
Atlantic salmon and people have been inextricably linked in North American since time immemorial. Interactions between salmon and humans are social-ecological systems comprised of complex interactions between social and biophysical agents interacting at heterogeneous spatial and temporal scales, and through technologies such as hatchery and stocking programs. As salmon populations have declined in the Maritime provinces, hatcheries have been viewed as both solution and challenge toward restoring Atlantic salmon populations. While the multifaceted ecological and genetic impacts of salmon stocking are well established in the scientific literature, hatcheries are still operational and valued by communities in the Maritime provinces today. A growing body of social science literature has explored the psychological, social, and conservation reasons for continued use of these facilities for salmon conservation, and the present study contributes to that discussion through a relational lens. We find that hatcheries and stocking programs are contributing to human-salmon relationships in socially desirable ways, including as a tangible conservation action for stakeholders dealing with ecological grief and anxiety, economic loss, and stewardship loss due to declining regional salmon populations. We demonstrate how hatcheries could be understood to contribute to social resilience during ecological loss, though they may simultaneously detract from ecological (particularly genetic) resilience. We conclude with a discussion of whether and how these social outcomes can be considered by decision makers in a time of evolving salmon conservation policy in the region. • Atlantic salmon hatcheries in the Maritimes Region produce social and ecological outputs. • In these areas, hatchery and stocking programs appear to be facilitating multi-faceted human-salmon relationships. • Some stakeholder engagement in salmon stocking is linked to coping with ecological grief or anxiety. • The programs appear to support aspects of social resilience, with potentially negative impacts on ecological resilience. • Management for future conservation salmon stocking should consider social and ecological outputs of hatchery programs.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".