Recovery Potential Assessment for the Endangered Cultus Lake Sockeye Salmon (Oncorhynchus Nerka) (2019)
Bibliographic record
Abstract
Cultus Lake Sockeye Salmon (Oncorhynchus nerka) were first assessed as endangered by the Committee on the Status of Endangered Wildlife in Canada (COSEWIC) in 2002 in an emergency assessment and confirmed as such in 2003. Owing largely to socioeconomic considerations Cultus Lake Sockeye Salmon were not listed under Schedule 1 of the Species at Risk Act (SARA) at this time. In 2017, as part of a COSEWIC assessment of 24 Fraser Sockeye Designatable Units (DUs), Cultus Lake Sockeye was again assessed as endangered. This Recovery Potential Assessment (RPA) provides an overview of Cultus Lake Sockeye biology, habitat requirements, threats, and limiting factors in Elements 1-11, and identifies recovery targets, population projections, mitigation assessments and recommendations on allowable harm in Elements 12-22. Threats to persistence with the highest population risks include degradation of critical freshwater habitats from anthropogenic forcings, and direct population losses due to harvests in the mixed stock fishery. Lake eutrophication, in particular, and its interactions with climate change, are newly-understood since the last assessment, and are quantified, and highly-influential mechanisms of population depression. Feasible options for mitigation of the various pathways and nutrient loadings to Cultus Lake have been developed both in the literature and this RPA, and are viewed as essential to population recovery, requiring targeted, interdisciplinary and inter-jurisdictional actions. Recognizing the distinction between recovery and survival of a population or species, an abundance target of 7,000 spawners (four-year average) is proposed for recovery of the Cultus Lake Sockeye Salmon DU, and a generational average of 2,500 spawners is proposed as a survival target. Model results suggest that without hatchery supplementation the population will be unable to sustain itself under the current threats and limiting factors, and is predicted to continue to decline over the next three generations (12 years). With ongoing supplementation, extinction is averted, but the population is unlikely to reach survival or recovery targets within this timeframe, without active threat mitigation. Addressing fisheries-related mortality and mitigating freshwater habitat threats (i.e. lake eutrophication), in particular, are anticipated to improve population trends and are highly recommended.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".