Investigating the role of larval behavioural ecology in the conservation of an endangered amphibian

The understanding of a species' phenotypic behavioural traits and their flexibility with reference to other biological and environmental factors is more important than ever given the current state of biodiversity globally and the rate at which species - and, in particular, amphibians - are declining due to anthropogenic threats to their environment which underpins their survival.

I propose to empirically test behavioural indicators of welfare and factors influencing evolutionary fitness in Alytes muletensis, a species of conservation concern for whom vital information required for conservation applications is currently missing from the existing scientific literature.

My approach will utilise a broad range of methodologies, including the use of machine learning, to understand key evolutionary processes - namely the expression of predator avoidance behaviours.

The application of these findings in designing in-situ conservation measures and optimising ex-situ management of captive animals has the potential to increase the overall welfare of individuals, facilitate the operation of natural processes, and mitigate the devastating declines in amphibian populations observed globally.