Streaming Media
Presentation Abstract
Commercial boat-based whale-watching is a very important touristic sector in the Salish Sea, taking thousands of people to view and experience up close the natural beauty and wildlife of the area. This sector provides economic benefits to local communities and opportunities for education and increase awareness for nature protection. The recent growth of whale-watching activities also can bring potential negative effects such as disturbances to wildlife. To achieve a sustainable commercial whale-watching sector, it is important to gain a good understanding of the footprint this activity has on the marine environment. For this, we assessed the spatio-temporal distribution of whale watching activities and their overlap with sensitive ecological areas. First, we developed an algorithm that classifies Automatic Identification System (AIS) vessel data from known commercial whale-watching vessels into wildlife viewing and transiting positions based on vessel speeds. Data analysed included AIS data collected in 2018, 2019, 2020 and 2021 in the Salish Sea. Wildlife viewing positions were used to estimate whale-watching effort based on the cumulative time whale-watching vessels spend wildlife viewing in a location. We then used marine protected areas and other area-based conservation measures to determine the degree of overlap between whale watching effort and ecologically sensitive areas. Results show areas consistently visited by whale-watching vessels during the study period, while other whale-watching hotspots are more dynamic and vary depending on the time of the year and targeted species. We conclude that the presented methodology applied to AIS data can provide a valuable tool to assess whale-watching activities and their potential effect to coastal environments.
Session Title
Poster Session 2: The Salish Sea Food Web and Cycles of Life
Conference Track
SSE14: Posters
Conference Name
Salish Sea Ecosystem Conference (2022 : Online)
Document Type
Event
SSEC Identifier
SSE-posters-7
Start Date
26-4-2022 4:30 PM
End Date
26-4-2022 5:00 PM
Rights
Copying of this document in whole or in part is allowable only for scholarly purposes. It is understood, however, that any copying or publication of this document for commercial purposes, or for financial gain, shall not be allowed without the author's written permission.
Type
Text
Language
English
Mapping whale-watching effort using AIS data in the Salish Sea
Commercial boat-based whale-watching is a very important touristic sector in the Salish Sea, taking thousands of people to view and experience up close the natural beauty and wildlife of the area. This sector provides economic benefits to local communities and opportunities for education and increase awareness for nature protection. The recent growth of whale-watching activities also can bring potential negative effects such as disturbances to wildlife. To achieve a sustainable commercial whale-watching sector, it is important to gain a good understanding of the footprint this activity has on the marine environment. For this, we assessed the spatio-temporal distribution of whale watching activities and their overlap with sensitive ecological areas. First, we developed an algorithm that classifies Automatic Identification System (AIS) vessel data from known commercial whale-watching vessels into wildlife viewing and transiting positions based on vessel speeds. Data analysed included AIS data collected in 2018, 2019, 2020 and 2021 in the Salish Sea. Wildlife viewing positions were used to estimate whale-watching effort based on the cumulative time whale-watching vessels spend wildlife viewing in a location. We then used marine protected areas and other area-based conservation measures to determine the degree of overlap between whale watching effort and ecologically sensitive areas. Results show areas consistently visited by whale-watching vessels during the study period, while other whale-watching hotspots are more dynamic and vary depending on the time of the year and targeted species. We conclude that the presented methodology applied to AIS data can provide a valuable tool to assess whale-watching activities and their potential effect to coastal environments.
