Behavioural changes in female Indo-Pacific bottlenose dolphins in response to boat-based tourism
Bibliographic record
Abstract
We investigated the behavioural changes of Indo-Pacific bottlenose dolphins Tursiops aduncus in response to boat-based tourism at both group and individual levels. The behaviour, movement and dive patterns of nursing females off the south coast of Zanzibar were investigated between January and March 2000 to 2002 and statistical comparisons were made between observations made at different levels of tourist activity. Behavioural data was collected during boat surveys using scan sampling of groups and focal individual follows of 5 female dolphins with calves. The movement patterns of dolphin groups were not affected by the presence of a few (1 to 2) tourist boats without swimmers. However, the groups displayed a significantly larger proportion of erratic (non-directional) movements as tourist activities increased and when swimmers were present. The proportion of active, peduncle, tail-out and porpoise dives also increased as tourist activity increased. Further, females travelled more frequently as tourist activities increased; this may have a negative effect on the time available for females to nurse their calves. Intense non-regulated dolphin tourism in this area may lead to a shift in habitat use by nursing females, and the apparent changes in dolphin behaviour due to the increased levels of tourism may ultimately reduce fitness at both individual and population levels. We urge that the guidelines already issued by the Department of Fisheries and Marine Products, Zanzibar, be implemented and complied with as a first important step towards sustainable dolphin tourism.
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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 | 0.000 |
| 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 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".