An Assessment of Commercial Fleet Applications of Management Measures in Clayoquot Sound, British Columbia, Canada, Aimed to Mitigate Whale-watching Impacts
Bibliographic record
Abstract
The interactions between wildlife tourism operators and the animals that they rely on are complex. For commercial whale watching, the recognition of the potential disturbance from the vessels generates uncertainty regarding the effectiveness of management strategies for it to remain a "no-take" practice. This warrants further evaluation. In this study, we analyzed the activities of the whale-watching fleet in Tofino, Vancouver Island, British Columbia, Canada, to evaluate industry sustainability and its ability to meet legislated conservation objectives. Visual observations gave context to an analysis of the communications of the fleet, made using very high frequency (VHF) marine radio. Transcription of these communications demonstrated three main themes: whale location, whale "transfers" between operators, and encounter or "show" quality. Cumulative encounter times from the fleet far exceeded the 30-min limit recommended in the whale-watching guidelines. Killer whales ( Orcinus orca ) were subject to the longest periods of vessel presence, with an average time spent in active encounters of 4.21 ±1.96 hr. This extended to almost the full operating day if whales remained within a feasible traveling distance of Tofino. Humpback ( Megaptera novaeangliae ) and gray whale ( Eschrichtius robustus ) encounters also exceeded the suggested time limit by 2.40 ± 1.73 hr and 1.31 ± 1.07 hr, respectively. Increased education and the addition of spatial and temporal restrictions in management regimes could address the shortcomings of the current system to minimize potential disturbance to whales from commercial whale-watching encounters and facilitate sustainable industry practices.
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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 | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".