Angling for endangered fish: conservation problem or conservation action?
Bibliographic record
Abstract
Abstract Recreational angling has been implicated in population declines of some marine and freshwater fish, but this activity is rarely considered as a threat or even halted when endangered species are targeted. Indeed, in some cases, anglers are drawn to fish for rare or endangered species. Conservation‐oriented behaviours such as catch‐and‐release are often practiced voluntarily due to the ethics of anglers, yet even in these cases, some fishing mortality occurs. Nonetheless, there are many indirect conservation benefits associated with recreational angling. Here, we present a series of case‐studies and consider whether catch‐and‐release angling for endangered fish is a conservation problem or a conservation action. If recreational angling activities contribute to population‐level consequences that are contrary to recovery strategies, then angling for endangered species would seem to be a poor option. However, as revealed by several case‐studies, there is much evidence that anglers are vocal and effective proponents of fish and habitat conservation, and for endangered species, they are often the only voice when other stakeholders are not engaged. Anglers may contribute directly to conservation actions via user fees (e.g. licences), philanthropic donations or by volunteering in research, education and restoration activities. However, it is important to quantify post‐release mortality as well as understand the full suite of factors influencing a given population or species to know the potential risks. A risk assessment approach outlined in the paper may be used by managers to determine when the benefits of angling for endangered species outweigh the risks.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".