Harmonizing recreational fisheries and conservation objectives for aquatic biodiversity in inland waters
Bibliographic record
Abstract
The importance of recreational fisheries to local and national economies, and as a generator of immense social welfare throughout the developed world, is well established. Development in the sector and its interaction with non-fishery-related nature conservation objectives for aquatic biodiversity, however, have the potential to generate conflict. This article reviews the intersection between recreational fisheries and nature conservation goals for aquatic biodiversity with specific reference to inland waters in industrialized countries, and the principal management activities and constraints that can lead to conflicts. A SWOT (strengths, weaknesses, opportunities and threats) analysis was used to review the issues facing sectoral development and identify options for future advancement of recreational fisheries to ameliorate potential conflicts with nature conservation goals. It is concluded that reconciliation of recreational fisheries and modern conservation perspectives is both possible and desirable, because many conservation problems also benefit fisheries quality. Angler buy-in to conservation is probable if (1) management scales are small, (2) threats to conservation originate from outside the fisheries sectors and (3) ecological awareness for the conservation problem is high. If these aspects are not present, reconciliation of recreational fisheries and nature conservation goals is less likely, risking both the aquatic biodiversity and the future of angling. To address these issues, enforcement of legislation and continued communication with angler communities is necessary, as well as development of integrated management policies that build on the instrumental values of aquatic biodiversity for recreational fisheries, while curtailing the more insidious threats to such biodiversity that originate directly from the recreational fisheries sector.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| 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".