Nature‐based marine tourism in the Gulf of California and Baja California Peninsula: Economic benefits and key species
Bibliographic record
Abstract
Abstract Ecotourism can incentivize social and environmental benefits through marine conservation, in parallel with efforts to better manage fisheries, coastal development, and other human pressures. In Mexico's Gulf of California and Baja California Peninsula (GCBP), marine ecosystems support tourism activities in many communities, but to date there have been no region‐wide studies to estimate their benefits or identify key species. Based on data collected in this study, each year nature‐based marine tourism in the GCBP results in 896,000 visits, US$518 million in expenditures and at least 3,575 direct jobs from formal operations. In interviews with operators, over 40 species groups were named as important; sea lions, whale sharks, whales, and marlin were the highest ranked, highlighting the importance of ecosystem‐wide health for nature‐based tourism sustainability. Local employment and the ability to make economic and conservation goals compatible were noted by operators as significant opportunities provided by nature‐based marine tourism; challenges included pollution and declines in ecosystem health, a lack of infrastructure, poor resource management policies, and high operating costs. As nature‐based marine tourism expands, a wider transition to true ecotourism, a focus on equitable benefits and collaboration between stakeholders and a cross‐scale and ecosystem approach to management will be vital for achieving potential sustainable social, ecological and economic benefits.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".