Socio-ecological Studies of Inland Recreational Rainbow Trout Fisheries Facing Anthropogenic Stressors: Implications for Fisheries Management and Policy Development
Bibliographic record
Abstract
This thesis takes a trans-disciplinary approach to studying the management of the socioeconomically valuable, socio-ecological system that is the recreational B.C. rainbow trout and steelhead (Oncorhynchus mykiss) fishery.Chapters are presented under a novel framework to studying the management of socio-ecological systems in a changing world, and is organized under three pillars: A) Identifying the capacity for aquatic ecosystems and ecosystem users to overcome climate change induced stressors (bottom-up conservation management) and providing solutions to encourage and facilitate bottom-up conservation management, B) Determining the capacity for current government-mandated management strategies and policies at protecting aquatic Canadian species, as well as providing solutions to foster the betterment of top-down conservation management of socioeconomically valuable aquatic species, and C) Providing strategies and avenues forward that can facilitate the incorporation of findings from pillars A and B into the management of socioeconomically valuable aquatic species.Chapters two and three (pillar A) provide evidence that steelhead are more susceptible to the negative effects of multiple angling events under predicted water temperatures, and that recreational anglers are likely to engage in pro-environmental behaviours whilst fishing (offsetting ecological impacts of angling), especially if they hold high environmental threat perceptions because of targeted species or chosen fishing locations.Chapters four and five (pillar B) provide evidence that current management strategies in place to protect steelhead in B.C. at both the provincial and federal level IV have significant limitations inhibiting the successful management of this species, and can be significantly improved.Overlaps in jurisdictional management and faults in imperilled species legislation in Canada should be addressed and improved to allow for the conservation of Pacific salmonid species.Chapters six and seven (pillar C) share initiatives and best practices for incorporating scientific evidence into and improving conservation management.Chapter six highlights the importance of both individual and collective actions, cross-scale collaborations, and adaptive management in successful environmental management.Chapter seven echoes the need for collaboration and suggests facilitating communication between decision-makers and knowledge generators to ensure the proper management and delivery of scientific findings, and credibility behind scientific findings when incorporating environmental scientific evidence into management decision-making.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".