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Evaluating cognition and thermal physiology as components of the pace-of-life syndrome
- Goulet, Celine T., Michelangeli, Marcus, Chung, Melinda, Riley, Julia L., Wong, Bob B. M., Thompson, Michael B., Chapple, David G.
- Evolutionary ecology 2018 v.32 no.5 pp. 469-488
- Lampropholis delicata, body temperature, cognition, learning, lizards, metabolism, models, prediction, social behavior
- The pace-of-life syndrome (POLS) suggests that behavioral traits are correlated and integrate within a fast–slow physiological continuum. At the fast extreme, individuals having higher metabolic rates are more active, exploratory, and bold with the opposite suite of traits characterizing those at the slow physiological extreme. A recent framework suggests that behavioral types may also differ consistently in their cognitive style. Accordingly, we propose that cognition could be further incorporated into the POLS framework comprised of behavioral and thermal physiological traits. Under this premise, fast behavioral types having high thermal traits are predicted to acquire a novel task faster but at the cost of accuracy while slow behavioral types with low thermal traits would be more attentive, responding to cues at a slower rate leading to higher accuracy and flexibility. This was tested by measuring physiological and behavioral traits in delicate skinks (Lampropholis delicata) and testing their learning ability. Correlations were detected between cognition and behavior but not thermal physiology. Contrary to our predictions, individual positioning along these axes opposed our predicted directions along the fast–slow continuum. Fast lizards preferring lower body temperatures expressed higher activity, exploration, sociality, and boldness levels, and learned the discrimination learning task at a slower rate but made the most errors. Additionally, modelling results indicated that neither thermal physiology, behavior, or their interaction influenced cognitive performance. Although the small number of animals completing the final stages of the learning assays limits the strength of these findings. Thus, we propose that future research involving a greater sample size and number of trials be conducted so as to enhance our understanding into how the integration of cognitive style, behavior, and physiology may influence individual fitness within natural populations.