Are changing diver characteristics important for coral reef conservation?
Bibliographic record
Abstract
Abstract Scuba (self ‐ contained underwater breathing apparatus) diving can act as an incentive ‐ based conservation mechanism and protect reefs by funding conservation and replacing more consumptive uses. However, diving must be sustainable. One challenge to sustainability is changing reef conditions and diving clientele over time. This paper examines these changes with respect to diving on the Andaman coast of Thailand using a Wildlife Tourism Model. In 2012 a questionnaire was administered to 591 scuba divers and compared with 506 questionnaires collected in 2000. Findings include: the 2012 industry has a higher proportion of low and medium specialization visitors that have lower expectations and lower overall satisfaction, yet remain willing to return; the average per capita economic contribution of divers to the local economy and to dive companies declined by more than 30% by 2012; Andaman coast diving continued to grow in 2012, dominated by mass ‐ market tourism that had diversified into several niches; the results verify the use of the Wildlife Tourism Model as a tool to understand industry sustainability, and suggest further development of the model to capture the extension into specific, niche markets. Changes to diver characteristics in 2012 restrict the ability of diving to fund conservation, provide alternative livelihoods, support environmental choices by operators, and control dive pressure exerted on reefs. Results suggest the operationalization of Limits of Acceptable Change by both managers and dive operators to grow the conservation value of diving. The results of this study suggest that the Wildlife Tourism Model can be used to inform management choices in emerging dive destinations. For instance, creating spatial zones that target the tourist composition most appropriate to meet the conservation goals of each reef system. Copyright © 2015 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.008 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".