Ecosystem models for management advice: An analysis of recreational and commercial fisheries policies in Baja California Sur, Mexico
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Recreational fishing is a vital component of the tourism economy in Baja California Sur (BCS), Mexico, although several artisanal and industrial fisheries continue to operate in the region. The commercial long-liner fleet in particular is widely held to be responsible both for diminishing shark populations and declines in billfish through bycatch. Using available fisheries and ecosystem data, we develop an Ecopath with Ecosim (EwE) model to represent current ecosystem and fishing dynamics in BCS and explore the ecological and economic effects of specific fisheries policy measures. Results suggest that currently mandated bycatch limits for the longlining fleet will have little effect on marlin abundance in the area. In an overfished ecosystem, decreasing fishing effort can result in higher overall catches through population rebuilding. While perhaps ecologically justified, increases in the abundance of sharks, a top predator, can have negative effects on other valued species in the ecosystem. The effects of these trophic dynamics must not be overlooked, as they can negate or even reverse desired outcomes from fisheries management.
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.
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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it