The role of conservation physiology in mitigating social-ecological traps in wildlife-provisioning tourism: a case study of feeding stingrays in the Cayman Islands
Bibliographic record
Abstract
In feeding marine wildlife, tourists can impact animals in ways that are not immediately apparent (i.e. morbidity vs. mortality/reproductive failure). Inventorying the health status of wildlife with physiological indicators can provide crucial information on the immediate status of organisms and long-term consequences. However, because tourists are attempting to maximize their own satisfaction, encouraging the willingness to accept management regulations also requires careful consideration of the human dimensions of the system. Without such socio-ecological measures, the wildlife-tourism system may fall into a trap—a lose–lose situation where the pressure imposed by the social system (tourist expectations) has costs for the ecological system (maladaptive behaviours, health), which in turn feed back into the social system (shift in tourist typography, loss of revenue, decreased satisfaction), resulting in the demise of both systems (exhaustion). Effective selection and communication of physiological metrics of wildlife health is key to minimizing problem-causing and problem-enhancing feedbacks in social-ecological systems. This guiding principle is highlighted in the case study presented here on the socio-ecological research and management success of feeding southern stingrays (<italic>Hypanus americanus</italic>) as a marine tourism attraction at Grand Cayman, Cayman Islands.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".