Towards the Acoustic Recognition of Individual Animals Within a Species

Automated passive acoustic monitoring of wildlife is a powerful tool for ecological research that has, to date, largely focused on species-level identification. The capacity to monitor at the individual level offers a non-invasive alternative to traditional marking methods, promising deeper insights into population demographics, social dynamics and behavior. This thesis provides the methodological foundation to transition automated acoustic individual identification from a proof-of-concept to a practical ecological tool, enabling a new level of understanding of individual animal lives.