Implications of porpoise echolocation and dive behaviour on passive acoustic monitoring

Jamie Donald John Macaulay*, Laia Rojano-Doñate, Michael Ladegaard, Jakob Tougaard, Jonas Teilmann, Tiago A. Marques, Ursula Siebert, Peter Teglberg Madsen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
4 Downloads (Pure)


Harbour porpoises are visually inconspicuous but highly soniferous echolocating marine predators that are regularly studied using passive acoustic monitoring (PAM). PAM can provide quality data on animal abundance, human impact, habitat use, and behaviour. The probability of detecting porpoise clicks within a given area ( P ̂ ) is a key metric when interpreting PAM data. Estimates of P ̂ can be used to determine the number of clicks per porpoise encounter that may have been missed on a PAM device, which, in turn, allows for the calculation of abundance and ideally non-biased comparison of acoustic data between habitats and time periods. However, P ̂ is influenced by several factors, including the behaviour of the vocalising animal. Here, the common implicit assumption that changes in animal behaviour have a negligible effect on P ̂ between different monitoring stations or across time is tested. Using a simulation-based approach informed by acoustic biologging data from 22 tagged harbour porpoises, it is demonstrated that porpoise behavioural states can have significant (up to 3× difference) effects on P ̂ . Consequently, the behavioural state of the animals must be considered in analysis of animal abundance to avoid substantial over- or underestimation of the true abundance, habitat use, or effects of human disturbance.

Original languageEnglish
Pages (from-to)1982-1995
Number of pages14
JournalJournal of the Acoustical Society of America
Issue number4
Publication statusPublished - 2 Oct 2023


Dive into the research topics of 'Implications of porpoise echolocation and dive behaviour on passive acoustic monitoring'. Together they form a unique fingerprint.

Cite this