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Data and R code used for the GLMM and NBDA analyses in 'Captive Asian short-clawed otters (Aonyx cinereus) learn to exploit unfamiliar natural prey'

Citation

Saliveros, A. M.; Bowden-Parry, M.; McAusland, F.; Boogert, N. J. (2022), Data and R code used for the GLMM and NBDA analyses in 'Captive Asian short-clawed otters (Aonyx cinereus) learn to exploit unfamiliar natural prey', Dryad, Dataset, https://doi.org/10.5061/dryad.4f4qrfjfd

Abstract

Foraging plays a vital role in animal life histories, learning whether unfamiliar food items are palatable is a key part of this process. Animals that engage in extractive foraging must also learn how to overcome the protective measures of their prey. While otters (subfamily Lutrinae) are a taxon known for their extractive foraging behaviour, how they learn about prey palatability and acquire extractive foraging techniques remains poorly understood. Here we investigated: (i) how captive Asian short-clawed otters (Aonyx cinereus) learned to interact with, and extract meat from, unfamiliar natural prey, and (ii) how their exploitation of such prey compared to their ability to overcome artificial foraging tasks containing familiar food rewards. Network-based diffusion analysis showed that otters learned to interact with unfamiliar natural prey by observing their group mates. However, once interacting with the prey, they learned to extract the meat mainly asocially. In addition, otters took longer to overcome the protective measures of unfamiliar natural prey than those of extractive food puzzles. Asian short-clawed otter populations are declining in the wild. Increasing our understanding of how they learn to overcome novel foraging challenges could help develop pre-release training procedures as part of reintroduction programmes for otter conservation.

Methods

See section 2 in main text of 'Captive Asian short-clawed otters (Aonyx cinereus) learn to exploit unfamiliar natural prey' for detailed decription of data collection proceedures.

Funding

Royal Society, Award: DH140080