A Review of Factors Potentially Contributing to the Long-Term Decline of Atlantic Salmon in the Conne River, Newfoundland, Canada
Bibliographic record
Abstract
Species extinction and population extirpation are now widespread across aquatic ecosystems with many diadromous species, including Atlantic salmon (Salmo salar), in decline throughout much of the North Atlantic. Declines can occur simultaneously at both large and small regional scales rendering factors driving the decreases more elusive. On the south coast of Newfoundland abundance of Atlantic salmon at Conne River fell by 92% over a period of almost four decades in contrast with most other populations in the region suggesting local factors may be contributing to the decline. Here factors potentially contributing to the long-term decline of salmon are reviewed by (1) examining long-term trends in abundance and survival at different life stages, (2) presenting a synopsis on the presence and absence of factors impacting survival and productivity of this population, (3) using a semi-quantitative two dimensional classification system, based on expert opinion, to rank factors potentially contributing to the decline, and (4) utilizing a quantitative Random Forest analysis to complement the expert opinion approach in identifying factors possibly affecting salmon abundance in this south coast Newfoundland population. Results from both qualitative and quantitative analyses identified factors associated with salmon aquaculture as a possible driver of the decline. Additional factors include the influence of both climate change and predation in freshwater and marine habitats. As various Atlantic salmon populations across the native range approach extirpation, the results further highlight the necessity of river-specific analyses in addition to long-term monitoring and fine-scale demographic and threat information in the prioritization of research necessary for conserving or restoring endangered populations.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".