Data

Data from: Sex and boldness explain individual differences in spatial learning in a lizard

Macquarie University
Dani Chandrasoma (Aggregated by) Daniel W. A. Noble (Aggregated by) Martin J. Whiting (Aggregated by) Pau Carazo (Aggregated by)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.5061/dryad.j83c0&rft.title=Data from: Sex and boldness explain individual differences in spatial learning in a lizard&rft.identifier=10.5061/dryad.j83c0&rft.publisher=Macquarie University&rft.description=Understanding individual differences in cognitive performance is a major challenge to animal behaviour and cognition studies. We used the Eastern water skink (Eulamprus quoyii) to examine associations between exploration, boldness and individual variability in spatial learning, a dimension of lizard cognition with important bearing on fitness. We show that males perform better than females in a biologically relevant spatial learning task. This is the first evidence for sex differences in learning in a reptile, and we argue that it is probably owing to sex-specific selective pressures that may be widespread in lizards. Across the sexes, we found a clear association between boldness after a simulated predatory attack and the probability of learning the spatial task. In contrast to previous studies, we found a nonlinear association between boldness and learning: both ‘bold’ and ‘shy’ behavioural types were more successful learners than intermediate males. Our results do not fit with recent predictions suggesting that individual differences in learning may be linked with behavioural types via high–low-risk/reward trade-offs. We suggest the possibility that differences in spatial cognitive performance may arise in lizards as a consequence of the distinct environmental variability and complexity experienced by individuals as a result of their sex and social tactics.Usage NotesLearning_models_dataData file containing three worksheets. One worksheet with data for GLM analyses and multi-model averaging. Second file for learning curve analyses and third file for generating Figure 1.&rft.creator=Dani Chandrasoma&rft.creator=Daniel W. A. Noble&rft.creator=Martin J. Whiting&rft.creator=Pau Carazo&rft.date=2015&rft_rights= https://creativecommons.org/publicdomain/zero/1.0/&rft_subject=Other education not elsewhere classified&rft_subject=alternative reproductive strategies&rft_subject=social specialisation&rft_subject=spatial learning&rft_subject=lizards&rft.type=dataset&rft.language=English Access the data

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Understanding individual differences in cognitive performance is a major challenge to animal behaviour and cognition studies. We used the Eastern water skink (Eulamprus quoyii) to examine associations between exploration, boldness and individual variability in spatial learning, a dimension of lizard cognition with important bearing on fitness. We show that males perform better than females in a biologically relevant spatial learning task. This is the first evidence for sex differences in learning in a reptile, and we argue that it is probably owing to sex-specific selective pressures that may be widespread in lizards. Across the sexes, we found a clear association between boldness after a simulated predatory attack and the probability of learning the spatial task. In contrast to previous studies, we found a nonlinear association between boldness and learning: both ‘bold’ and ‘shy’ behavioural types were more successful learners than intermediate males. Our results do not fit with recent predictions suggesting that individual differences in learning may be linked with behavioural types via high–low-risk/reward trade-offs. We suggest the possibility that differences in spatial cognitive performance may arise in lizards as a consequence of the distinct environmental variability and complexity experienced by individuals as a result of their sex and social tactics.

Usage Notes


Learning_models_dataData file containing three worksheets. One worksheet with data for GLM analyses and multi-model averaging. Second file for learning curve analyses and third file for generating Figure 1.

Issued: 12 02 2015

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