Grant: Alliance Grants
Université du Québec à Rimouski
$229,001.00
Distributed acoustic sensing (DAS) for the monitoring of endangered baleen whales in the St Lawrence estuary
FY 2024-25
Summary
Every year, the St. Lawrence Estuary hosts a large number and variety of whales, which gather here to feed in these rich waters. These feeding grounds are shared with commercial fishermen, and crossed by a busy commercial shipping lane. To reduce the risk of interactions between marine activities and these animals, it is necessary to detect the whales in near-real time. An emerging monitoring technology, known as Distributed Acoustic Sensing (DAS), has the potential to answer this challenge. It converts an unused fibre-optic strand from a submarine cable into a large listening array using a specialized tool called an interrogator at the end of the cable on land. This project brings together the expertise of the ISMER-UQAR, Cornell University and Merinov, in collaboration with TELUS Canada, Parks Canada, Wolastoqiyik Wahsipekuk First Nation and the Agence Mamu Innu Kaikusseth, to assess the performances of DAS for baleen whale monitoring in the St-Lawrence estuary (SLE). In this two-year project, we want to identify optimal parameters for the detection of different species of large whales by DAS, and compare the performance of this tool with traditional monitoring methods.
Program
Alliance Grants
Recipient
Location
Quebec, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
598039-2024
Name nom
Cauchy, Pierre P
Department département
Sciences de la mer de Rimouski, Institut des
Organization id
58
Institution établissement
Université du Québec à Rimouski
Province en
Québec
Province fr
Québec
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2024
Competition year année de concours
2024
Award amount
229001
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
402
Area of application group en
Environment
Area of application group fr
Environnement
Area of application en
Oceans, seas and estuaries
Area of application fr
Océans, mers et estuaires
Research subject code
4600
Research subject group en
Oceanography
Research subject group fr
Océanographie
Research subject en
Oceanography
Research subject fr
Océanographie
Field of research list names en
Not available
Field of research list names fr
Non disponible
Socioeconomic objective list names en
Not available
Socioeconomic objective list names fr
Non disponible
Application title
Distributed acoustic sensing (DAS) for the monitoring of endangered baleen whales in the St Lawrence estuary
Keywords
baleen whale; bioacoustics; distributed acoustic sensing (das); dynamic management; entanglement risk; marine acoustics; whale conservation; whale detection; whale strike
Application summary
Every year, the St. Lawrence Estuary hosts a large number and variety of whales, which gather here to feed in these rich waters. These feeding grounds are shared with commercial fishermen, and crossed by a busy commercial shipping lane. To reduce the risk of interactions between marine activities and these animals, it is necessary to detect the whales in near-real time. An emerging monitoring technology, known as Distributed Acoustic Sensing (DAS), has the potential to answer this challenge. It converts an unused fibre-optic strand from a submarine cable into a large listening array using a specialized tool called an interrogator at the end of the cable on land. This project brings together the expertise of the ISMER-UQAR, Cornell University and Merinov, in collaboration with TELUS Canada, Parks Canada, Wolastoqiyik Wahsipekuk First Nation and the Agence Mamu Innu Kaikusseth, to assess the performances of DAS for baleen whale monitoring in the St-Lawrence estuary (SLE). In this two-year project, we want to identify optimal parameters for the detection of different species of large whales by DAS, and compare the performance of this tool with traditional monitoring methods.