An Economic Perspective on Policies to Save the Vaquita: Conservation Actions, Wildlife Trafficking, and the Structure of Incentives
Bibliographic record
Abstract
The Upper Gulf of California is a diverse and highly productive ecosystem supporting some of the most important fisheries in Mexico, yet a history of weak fisheries management and illegal fishing threaten the area’s biodiversity and undermine human well-being in the communities along its shores. The vaquita ( Phocoena sinus) is endemic to these waters and is on the brink of extinction due to incidental entanglement in gillnets used by small-scale fishers. The resurgence of an illegal gillnet fishery for totoaba ( Totoaba macdonaldi ), whose swim bladders are highly prized in Hong Kong and continental China, has accelerated the steep decline of the vaquita population. Vaquita is one of a growing number of cases linking illegal wildlife trade, organized crime, and biodiversity decline. This paper provides a summary of key reflections of a panel of fisheries economists gathered at the ninth forum of the North American Association of Fisheries Economists (NAAFE) to evaluate the policies implemented in the Upper Gulf through an economic lens and updated to reflect more recent developments. The panel recognized that poor fisheries management, lack of effective enforcement, distant demand for an illegal product, corruption, and few viable economic alternatives confound efforts to address vaquita bycatch. The complexity of these problems requires a holistic, multidisciplinary approach, combining top-down, direct regulation and bottom-up, participatory and incentive-based instruments. Addressing chronic deficiencies in enforcement, particularly in the very small area where the remaining vaquitas are found, is crucial to prevent imminent extinction. Equally crucial are sustained actions to support legal fishers able to make a good living – with a direct stake in healthy marine ecosystems – as key components of policies to address bycatch and reduce wildlife trafficking. The situation in the Upper Gulf of California is dire, yet similar threats to other marine mammals and wildlife trafficked species may benefit from the experience of the vaquita.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".