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How and why are some species so smart? A comment on Rowe & Healy
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Alex Thornton*
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Penryn Campus, Treliever Road, Penryn TR10 9FE, UK
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Address correspondence to A. Thornton. E-mail: alex.thornton@exeter.ac.uk
Centre for Ecology and Conservation, Department of Biosciences, University of Exeter,
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Examining how individual cognitive variation relates to fitness holds the promise of
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providing a richer understanding of how cognitive traits evolve (Thornton and Lukas 2012).
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However, as Rowe and Healy (2014) point out (see also Thornton, Isden, and Madden 2014
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in this issue), this endeavour is rife with pitfalls, and requires more psychological rigour than
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has been employed in most studies to date. I agree wholeheartedly with them that arbitrary
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“problem-solving” tasks should be abandoned in favour of psychologically-grounded tests
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targeting specific cognitive mechanisms (Thornton, Isden, and Madden 2014) and hope that
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future work will heed their advice in designing tests and accounting for non-cognitive
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influences. Here I want to focus on two additional, interrelated issues: which species should
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we focus on, and what cognitive mechanisms should we examine?
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Choices of study species will largely be determined by practical considerations such as the
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need for an adequate sample size. Abundant, tractable, yet seemingly cognitively
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unsophisticated model systems may prove useful in developing methods and testing general
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principles. Such animals have long been a cornerstone of experimental psychology and could
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be tested in the field to illuminate general principles including trade-offs in cognitive
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processing (e.g. speed vs. accuracy; Sih and Del Giudice 2012) or between cognition and
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other traits (e.g. (Mery and Kawecki 2003) in the face of natural selective pressures. I would
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argue that yet greater insights may be gained by examining the fitness consequences of
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cognitive variation in animals whose cognitive abilities appear in some way remarkable.
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Given the costs of investment in neural tissue, what are the fitness benefits that generate
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selection for these abilities? Food-storing birds provide the paradigmatic example, as there is
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strong evidence linking the challenges of retrieving stored food with elevated hippocampal
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volume and long-term memory retention (see Rowe and Healy 2014). Spatial memory tests
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may offer similar opportunities in other animals, such as female brood parasites, which must
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remember the locations of potential hosts’ nests (Reboreda, Clayton, and Kacelnik 1996),
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though the relevant facets of spatial memory are yet to be determined. Here, individual-based
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studies can help pinpoint which, if any, aspects of spatial memory confer fitness advantages
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and specify what those advantages may be.
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Arguably, an even greater mystery is the striking performance of some species not only in a
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single, ecologically predictable cognitive domain, but across domains. For instance, meta-
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analyses show that some primate species consistently outperform others across different
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laboratory tasks (Deaner, van Schaik, and Johnson 2006). Among birds, corvids may also
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exhibit similar cross-context cognitive prowess, with evidence for remarkable abilities in
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memory, planning, rule learning, inferential reasoning and aspects of physical and social
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cognition (Seed, Emery, and Clayton 2009). One fruitful avenue of research may be to test
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the performance of wild individuals across batteries of tasks targeting different cognitive
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processes (c.f. Isden et al. 2013). While it is difficult to generate straightforward predictions,
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such work may help elucidate the mechanistic structure of cognition (e.g. the extent to which
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general mechanisms explain individual performance across different tasks) and understand
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whether selection acts on cognitive mechanisms as discrete traits or part of an inter-related
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complex.
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As Rowe and Healy (2014) remind us, it would be naïve to suppose that individual cognitive
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performance will necessarily correlate positively with fitness. However, exploring the
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relationships between suites of cognitive measures and multiple fitness components may help
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build a picture of the costs and benefits of cognitive traits. We have argued that there is much
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to be learned from psychometrics, a branch of psychology specifically concerned with
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quantifying individual cognitive differences (Thornton, Isden, and Madden 2014). In
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particular, psychometric tests aim to reduce the influence of non-cognitive factors and
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generate continuous measures of cognitive performance. These tests typically specify clear
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criteria as to what constitutes a “correct” outcome, but apparent mistakes will also be
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informative, for example in revealing individual differences in sampling strategies (Seed et
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al. 2012). By uniting psychometric approaches with conceptual and methodological tools
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from behavioural ecology, we can start to hone in on trade-offs and understand whether and
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how selection acts on cognitive variation.
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Funding
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A.T. was supported by a BBSRC David Phillips Fellowship (BB/H021817/1).
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Acknowledgements
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I am grateful to J. Madden for helpful comments on previous drafts of the paper.
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References
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