The 82nd Annual Meeting of the American Association of Physical Anthropologists (2013)

The evolution of brain size and longevity in mammals


1Department of Evolutionary Anthropology, Duke University, 2Center for the Study of Human Origins, Department of Anthropology, New York University

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Large brains are metabolically expensive and require extended developmental periods, resulting in increased risks of offspring mortality and delayed sexual maturity. Despite this, encephalization has occurred many times independently in mammals. Hypotheses to explain the evolution of encephalization must account for its adaptive value in spite of the associated costs of a longer period of development.

One hypothesis (cognitive buffer) to explain the association between brain size and longevity argues that encephalization would allow more behavioral flexibility to respond to ecological challenges, thus reducing extrinsic mortality and allowing for the evolution of an extended lifespan. An alternative hypothesis (delayed benefits) argues that the costs of delayed reproduction can be outweighed by benefits later in life. If the opportunity to evolve and develop a large brain is available, it might be acted upon despite its costs because the learning it allows provides obvious fitness benefits later in life. Accordingly, long-lived organisms have more to gain from investment in a large brain.

To test these competing hypotheses, we analyze a large dataset of average, sex-pooled brain and body masses and maximum lifespan records from 792 mammalian species. We calculate encephalization and longevity quotients using OLS regression on body mass. T-tests are then conducted when z-standardized EQ-LQ>|1.96|. Results demonstrate that while high LQs are associated with significantly high EQs, the reverse is not true. Results remain unchanged even when potentially problematic orders are removed, suggesting that increases in longevity precede encephalization as a general rule in mammals, thus supporting the delayed benefits hypothesis.

This study was supported by a Beckman Institute for Advanced Science and Technology Cognitive Science/AI Award.

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