Marine Mammal Monitoring: Methods, Technologies, and Opportunities for Innovation

Dorrian, N.; Ferguson, E.; Scala, L.; Wright, A.; Noseworthy, A.; Kitchiner, A. (2025). Marine Mammal Monitoring: Methods, Technologies, and Opportunities for Innovation. Report by Institute of Marine Engineering, Science and Technology (IMarEST). Report for Institute of Marine Engineering, Science and Technology (IMarEST).

@techreport{Dorrian-2025-2084390,
author = {Dorrian, N and Ferguson, E and Scala, L and Wright, A and Noseworthy, A and Kitchiner, A},
title = {Marine Mammal Monitoring: Methods, Technologies, and Opportunities for Innovation},
institution = {Institute of Marine Engineering, Science and Technology (IMarEST)},
year = {2025},
month = {jul},
address = {London, UK},
url = {https://www.imarest.org/resource/marine-mammal-monitoring-methods-technologies-and-opportunities-for-innovation.html},
keywords = {Wind Energy, Avoidance, Entanglement, Habitat Change, Noise, Vessel Strike, Marine Mammals},
}

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TY - RPRT
TI - Marine Mammal Monitoring: Methods, Technologies, and Opportunities for Innovation
AU - Dorrian, N
AU - Ferguson, E
AU - Scala, L
AU - Wright, A
AU - Noseworthy, A
AU - Kitchiner, A
AB - The Marine Mammal Monitoring: Methods, Technologies, and Opportunities for Innovation project, led by the Institute of Marine Engineering, Science & Technology’s (IMarEST) Marine Mammal Special Interest Group (MMSIG) in collaboration with the Department for Environment, Food and Rural Affairs (Defra) under the Marine Natural Capital and Ecosystem Assessment (mNCEA) programme, evaluated current methodologies and emerging technologies in marine mammal monitoring. The project methodology included a comprehensive literature review, stakeholder survey with 133 respondents, a horizon scan, and a dedicated online workshop attended by 188 subject matter experts from academia, industry, government, and conservation organisations. Evaluated technologies included artificial intelligence (AI), passive acoustic monitoring (PAM), environmental DNA (eDNA), satellite-based detection, and automated data integration. Key findings from the study identified gaps in current monitoring approaches and highlighted opportunities for greater interdisciplinary collaboration and automation to enhance monitoring efficiency and scalability. The horizon scan specifically pinpointed near-term advancements focusing on automation and extended geographic coverage, with long-term priorities aimed at developing multi-sensor integrated monitoring systems. Principal challenges include data standardisation, adaptation of regulatory frameworks, and securing sustained funding. The stakeholder workshop identified the importance of AI-driven analytics, integration of PAM, eDNA, and satellite detection methodologies, alongside the establishment of open-access data frameworks and standardised protocols. Discussions also emphasised the necessity of robust, long-term funding mechanisms, public-private partnerships, and alignment with regulatory frameworks to accelerate innovation and optimise monitoring effectiveness.This report highlights the transformative potential of automation, AI analytics, and multi-modal monitoring techniques in marine mammal conservation. It provides strategic recommendations aimed at adopting innovative technologies, real-time data processing, and robust data-sharing frameworks. Implementation of these recommendations will significantly strengthen the UK’s marine mammal conservation efforts, improve decisionmaking capabilities, and support comprehensive marine environmental management aligned with national and international conservation priorities.Supplementary Material:Marine Mammal Monitoring MatrixMarine Mammal Monitoring Stakeholder Survey
CY - London, UK
DA - 2025/07//
PY - 2025
SP - 69
PB - Institute of Marine Engineering, Science and Technology (IMarEST)
UR - https://www.imarest.org/resource/marine-mammal-monitoring-methods-technologies-and-opportunities-for-innovation.html
LA - English
KW - Wind Energy
KW - Avoidance
KW - Entanglement
KW - Habitat Change
KW - Noise
KW - Vessel Strike
KW - Marine Mammals
ER -

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Abstract

The Marine Mammal Monitoring: Methods, Technologies, and Opportunities for Innovation project, led by the Institute of Marine Engineering, Science & Technology’s (IMarEST) Marine Mammal Special Interest Group (MMSIG) in collaboration with the Department for Environment, Food and Rural Affairs (Defra) under the Marine Natural Capital and Ecosystem Assessment (mNCEA) programme, evaluated current methodologies and emerging technologies in marine mammal monitoring.

The project methodology included a comprehensive literature review, stakeholder survey with 133 respondents, a horizon scan, and a dedicated online workshop attended by 188 subject matter experts from academia, industry, government, and conservation organisations. Evaluated technologies included artificial intelligence (AI), passive acoustic monitoring (PAM), environmental DNA (eDNA), satellite-based detection, and automated data integration.

Key findings from the study identified gaps in current monitoring approaches and highlighted opportunities for greater interdisciplinary collaboration and automation to enhance monitoring efficiency and scalability. The horizon scan specifically pinpointed near-term advancements focusing on automation and extended geographic coverage, with long-term priorities aimed at developing multi-sensor integrated monitoring systems. Principal challenges include data standardisation, adaptation of regulatory frameworks, and securing sustained funding.

The stakeholder workshop identified the importance of AI-driven analytics, integration of PAM, eDNA, and satellite detection methodologies, alongside the establishment of open-access data frameworks and standardised protocols. Discussions also emphasised the necessity of robust, long-term funding mechanisms, public-private partnerships, and alignment with regulatory frameworks to accelerate innovation and optimise monitoring effectiveness.

This report highlights the transformative potential of automation, AI analytics, and multi-modal monitoring techniques in marine mammal conservation. It provides strategic recommendations aimed at adopting innovative technologies, real-time data processing, and robust data-sharing frameworks. Implementation of these recommendations will significantly strengthen the UK’s marine mammal conservation efforts, improve decisionmaking capabilities, and support comprehensive marine environmental management aligned with national and international conservation priorities.

Supplementary Material: