Opportunities and limitations of Canada's Species at Risk Act for protecting Pacific salmonids: lessons learned from the case of the Thompson River steelhead
Bibliographic record
Abstract
Imperilled species legislation is a critical tool at various levels of government for biodiversity conservation. In this article, we examine the opportunities and limitations of Canada's Species at Risk Act (SARA) to protect a highly threatened population of Pacific salmonid in British Columbia—the Thompson River steelhead ( Oncorhynchus mykiss). To date, no Pacific salmonids have been listed under Canada's SARA despite critical population declines. The case of Thompson River steelhead is relevant because this species is often viewed as the “canary in the coal mine” for other Canadian Pacific salmonids and recently went through the Canadian listing process for imperilled native species. Thompson River steelhead, which is a culturally and socio-economically valuable migratory salmonid species, was deemed to be “endangered” by the Committee on the Status of Wildlife in Canada (COSEWIC) following an emergency assessment completed in February of 2018. The assessment noted population declines of 79% over the last three generations, yet Thompson River steelhead were ultimately not listed under Canada's SARA. Our analysis of this case is based on semi-structured interviews with individuals involved with, or knowledgeable about, the COSEWIC and SARA listing process for Thompson River steelhead ( N = 17). Findings from these interviews point to several structural and institutional reasons why this species was not listed despite its precarious status: (1) spillover effects from listing species under SARA, (2) time required to complete listing processes, (3) reactive rather than proactive emergency listing processes, (4) listing decisions based on socioeconomic considerations rather than conservation science, and (5) lack of transparency in listing processes. Interview participants suggested several solutions to overcome these limitations, including (1) allowing for the management of co-migratory stocks following SARA listings, (2) expediting listing timelines, (3) making listing processes more pro-active, and (4) ensuring transparent, science-based decision-making. Our analysis demonstrates the potential of SARA listings to protect aquatic species and suggests paths forward to improving the effectiveness of Canada's SARA.
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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 | 0.015 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.035 | 0.022 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.008 | 0.014 |
| Insufficient payload (model declined to judge) | 0.003 | 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".