Recreational anglers in Norway report widespread dislike of invasive pink salmon
Bibliographic record
Abstract
Abstract Pink salmon have returned to Norwegian rivers at high abundance in recent odd‐numbered years (2017, 2019, 2021, 2023), presenting potential threats to native biodiversity and ecosystem services, including major sport fishing tourism for Atlantic salmon and sea‐run brown trout in Norway. Presently, there exists a knowledge gap on angler perceptions and attitudes towards the presence of pink salmon in Norwegian rivers, resulting in difficulty assessing the socioeconomic repercussions of their invasion. We distributed an online questionnaire to anglers who purchased the national salmon fishing licence in Norway in 2020 to assess their perceptions of pink salmon and the intentions of anglers to modify their fishing practices. There were widespread negative perceptions of pink salmon in Norway. Perceptions were matched with intentions to modify fishing behaviour among some of the anglers, with 41% saying that they would modify fishing to increase the catch of pink salmon to help remove them before they spawned in the rivers. However, anglers were more prone to say they would decrease fishing effort if both pink salmon catches and fishing licence costs were to increase or if pink salmon were to dominate their catch. Salmon anglers in Norway were strongly oriented towards their chosen recreational activity and do not plan to stop fishing their preferred rivers. They also do not want pink salmon to become established in Norway and are prepared to volunteer for stewardship roles that intervene against pink salmon. However, they overwhelmingly reported not wanting to eat pink salmon. Fisheries managers must take into account the widespread desire for management intervention against pink salmon, even though eradication is not likely no matter how intensive removal efforts become. Efforts to change narratives about pink salmon to encourage fishers to harvest pink salmon from the fjords and rivers for consumption might lead to effective population control, relieving native salmon, trout and charr from potential negative impacts of this prolific colonizer. Read the free Plain Language Summary for this article on the Journal blog.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".