Uncertainty, anxiety, and optimism: Diverse perspectives of rainbow and steelhead trout fisheries governance in British Columbia
Bibliographic record
Abstract
Inland fisheries are complex social-ecological systems that can generate important nutritional, economic, cultural, and recreational benefits. Effective management of these systems for multiple user-groups requires an understanding of the complex natural and human dimensions interactions within them. We examine the perceptions of stakeholders, Indigenous rightsholders, and regulatory/governance groups on the current and future status of Oncorhynchus mykiss (including their resident form – rainbow trout – and their anadromous form – steelhead) populations and fisheries in British Columbia (BC), Canada from 65 qualitative interviews and 1029 quantitative survey responses. Participants generally did not believe resident rainbow trout were threatened at the provincial level but were definitive in assessing anadromous steelhead trout as threatened. Habitat alterations, water temperature extremes, and climate change, were key threats identified for all forms of O. mykiss while bycatch in commercial fisheries and predation pressure from pinnipeds were specifically identified threats for steelhead trout. Anglers did not perceive recreational fishing pressure as a key threat in contrast to regulatory and governance groups. Fisheries managers were praised for stocking programs and managing small lakes fisheries but criticized for not doing enough to protect fish populations, for an unwillingness to challenge or confront commercial and Indigenous interests which infringe on conservation, and for a lack of aquatic monitoring. Three factors identified by participants contribute to fishery mismanagement, inaction, and decision paralysis: (1) insufficient resources (funding, staff, time), (2) confusion in jurisdictional authority between provincial and federal governments, and (3) organizational structure of natural resource management agencies which are not autonomous from competing commercial and industrial objectives and directions. Despite conservation being purported as the highest priority of fisheries managers, economic, social, and political drivers are perceived as increasingly influencing conservation decisions and actions. These findings can inform fisheries management and conservation decisions, policies and practices to ensure that they are more salient, robust, legitimate, and effective.
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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 | 0.003 | 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 | 0.013 | 0.009 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 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".