Becoming creatures of habit: among‐ and within‐individual variation in nesting behavior shifts with age

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2020-09-08
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Delaney, David
Hoekstra, Luke
Janzen, Fredric
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Janzen, Fredric
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Ecology, Evolution and Organismal Biology
Abstract

The quantification of repeatability has enabled behavioral and evolutionary ecologists to assess the heritable potential of traits. For behavioral traits that vary across life, age-related variation should be accounted for to prevent biasing the microevolutionary estimate of interest. Moreover, to gain a mechanistic understanding of ontogenetic variation in behavior, among- and withinin- individual variance should be quantified across life. We leveraged a 30-year study of painted turtles (Chrysemys picta) to assess how age contributes to variation in the repeatability of nesting behaviors. We found that four components of nesting behavior were repeatable, and that accounting for age increased the repeatability estimate for maternal choice of canopy cover over nests. We detected canalization (diminished within-individual variance with age) of canopy cover choice in a reduced dataset despite no shift in repeatability. Additionally, random regression analysis revealed that females became more divergent from each other in their choice of canopy cover with age. Thus, properly modeling age-related variance should more precisely estimate heritable potential, and assessing among- and within-individual variance components in addition to repeatability will offer a more mechanistic understanding of behavioral variation across age.

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This is the peer reviewed version of the following article: Delaney, David M., Luke A. Hoekstra, and Fredric J. Janzen. "Becoming creatures of habit: among‐and within‐individual variation in nesting behavior shifts with age." Journal of Evolutionary Biology (2020), which has been published in final form at doi: 10.1111/jeb.13701. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.

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Wed Jan 01 00:00:00 UTC 2020
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