Assessing and mitigating the impacts of whale-watching activities on humpback whales in Iceland
Vessel-based whale-watching is a potential source of disturbance for target cetacean populations, with responses including avoidance and the disruption of key activities such as feeding, resting and communication. However, management of this industry to mitigate potential negative impacts is often u...
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| Other Authors: | , , , |
| Format: | Doctoral or Postdoctoral Thesis |
| Language: | English |
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The University of Edinburgh
2024
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| Subjects: | |
| Online Access: | https://hdl.handle.net/1842/41350 https://doi.org/10.7488/era/4085 |
| Summary: | Vessel-based whale-watching is a potential source of disturbance for target cetacean populations, with responses including avoidance and the disruption of key activities such as feeding, resting and communication. However, management of this industry to mitigate potential negative impacts is often undermined by a lack of site-specific ecological information regarding baseline population processes, the responses of whales to vessels and future ecosystem change. My thesis aims to address some of these knowledge gaps for humpback whales (Megaptera novaeangliae [Borowski 1781]) in Iceland, an important North Atlantic feeding ground with an established whale-watching industry, to inform future policy. From a conservation perspective, whale-watching activities in Iceland are currently under-regulated, with a voluntary code of conduct primarily informed by impact assessments from other regions. First, I assessed the behavioural responses of humpback whales to variable whale-watching practices in Skjálfandi Bay, in which the second largest fleet in Iceland operates (Chapter 2). Over three summer seasons (633 hours of survey effort), visual observations and positional measurements were collected from 210 whales during 727 focal follows. These data were used to construct seven behavioural variables, while whale-watching vessel movements were quantified using a novel combination of coarse-scale AIS and fine-scale GPS positional data. I then applied generalised additive mixed models (GAMMs) to determine that whale behaviour was influenced by vessel speed, the number of vessels and encounter duration. For example, dive times increased with increasing vessel speed and when more than four whale-watching vessels were present, indicating vertical avoidance; while prolonged encounters led to changes in movement patterns, possibly representing horizontal avoidance, and feeding disruption. Meanwhile, compliance to speed–distance restrictions in the code of conduct appeared to limit behavioural disturbance. However, behavioural ... |
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