Abstract

Individuals often vary in their problem-solving performance, and animal personality may help explain such interindividual variation because it affects how individuals perceive and interact with their environment. Proximate factors (behavioural variety, persistence, selectivity and experience) provide behavioural mechanisms that also affect problem-solving performance. Our aim was to assess the link between personality and problem-solving performance in wild-caught, common brushtail possums, Trichosurus vulpecula, and to assess their learning capability. We tested how possums, a native marsupial inhabiting the inner urban environment of Sydney, Australia, solved an escape box problem in the field. Possums could solve this problem by either pushing (easy) or pulling (difficult) a door. We quantified personality traits, including exploration, activity and vigilance, in a separate arena test. We found that personality traits affected problem solving. Exploratory animals were more likely to succeed in their first trial irrespective of task type, but only highly exploratory individuals were likely to solve the difficult task. More active and more vigilant individuals were also more likely to succeed, regardless of task type. For mechanistic behaviours employed during the problem-solving test, individuals spending more time engaged (persistent) were less likely to succeed in the easy task, because they focused more on nonfunctional parts of the box. In contrast, persistent individuals were more likely to succeed in the difficult task. Possums learnt effectively, solving tasks substantially faster on their second attempt. Our study provides the first demonstration of problem solving in free-ranging marsupials using an ecologically relevant test. This allows future comparison of behavioural commonalities and tests of convergent evolution in problem solving among taxa. Furthermore, while personality traits influenced problem-solving capability, we suggest that the rapid improvement in problem solving by all possums through experience and learning helps explain their success in dealing with artificial or novel problems associated with the urban environment.

Full Text
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