Beluga (Delphinapterus leucas) response to personal watercraft and motorized whale watching vessels in the Churchill River estuary
Bibliographic record
Abstract
As interest in tourism and conservation grows worldwide, whale-watching has become a popular means of educating the public about wildlife conservation. The short-term impact of ecotourism industries on observed species has been widely studied with findings that indicate responses are most often behavior alterations or avoidance. Close vessel interactions with beluga whales (Delphinapterus leucas) are a major draw for whale-watching ecotourism in Churchill, Manitoba, Canada. As the Churchill River estuary and surrounding waters are assessed for a Marine Protected Area, information on the response of belugas to vessels are needed to inform management. To assess this, an oblique time-lapse camera system with a 5-minute photo interval was set up overlooking a section of the Churchill River estuary that is shared by belugas and tourist vessels. Measurements calculated from photos were used to compare the distance between belugas and kayaks, paddleboards, motorboats, and Zodiac whale-watching vessels. These distances were compared to an expected distribution generated from locations of belugas in photos without the presence of vessels. We found evidence that belugas are attracted to kayaks, avoid paddleboards, and are neutral regarding motorboats and Zodiacs. This is the first study to quantify the behavioral response of cetaceans to tourist vessels using a camera system and a distance-based analysis. Results could inform the development of a site-specific management system that accounts for beluga-vessel relationships.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".