ABSTRACT Selection experiments play an increasingly important role in comparative and evolutionary physiology. However, selection experiments can be limited by relatively low statistical power, in part because replicate line is the experimental unit for analyses of direct or correlated responses (rather than number of individuals measured). One way to increase the ability to detect correlated responses is through a meta-analysis of studies for a given trait across multiple generations. To demonstrate this, we applied meta-analytic techniques to two traits (body mass and heart ventricle mass, with body mass as a covariate) from a long-term artificial selection experiment for high voluntary wheel-running behavior. In this experiment, all four replicate High Runner (HR) lines reached apparent selection limits around generations 17–27, running approximately 2.5- to 3-fold more revolutions per day than the four non-selected Control (C) lines. Although both traits would also be expected to change in HR lines (relative heart size expected to increase, expected direction for body mass is less clear), their statistical significance has varied, despite repeated measurements. We compiled information from 33 unique studies and calculated a measure of effect size (Pearson's R). Our results indicate that, despite a lack of statistical significance in most generations, HR mice have evolved larger hearts and smaller bodies relative to controls. Moreover, plateaus in effect sizes for both traits coincide with the generational range during which the selection limit for wheel-running behavior was reached. Finally, since reaching the selection limit, absolute effect sizes for body mass and heart ventricle mass have become smaller (i.e. closer to 0). 
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                            Does Behavior Evolve First? Correlated Responses to Selection for Voluntary Wheel-Running Behavior in House Mice
                        
                    
    
            How traits at multiple levels of biological organization evolve in a correlated fashion in response to directional selection is poorly understood, but two popular models are the very general “behavior evolves first” (BEF) hypothesis and the more specific “morphology-performance-behavior-fitness” (MPBF) paradigm. Both acknowledge that selection often acts relatively directly on behavior and that when behavior evolves, other traits will as well but most with some lag. However, this proposition is exceedingly difficult to test in nature. Therefore, we studied correlated responses in the high-runner (HR) mouse selection experiment, in which four replicate lines have been bred for voluntary wheel-running behavior and compared with four non-selected control (C) lines. We analyzed a wide range of traits measured at generations 20–24 (with a focus on new data from generation 22), coinciding with the point at which all HR lines were reaching selection limits (plateaus). Significance levels (226 P values) were compared across trait types by ANOVA, and we used the positive false discovery rate to control for multiple comparisons. This meta-analysis showed that, surprisingly, the measures of performance (including maximal oxygen consumption during forced exercise) showed no evidence of having diverged between the HR and C lines, nor did any of the life history traits (e.g., litter size), whereas body mass had responded (decreased) at least as strongly as wheel running. Overall, results suggest that the HR lines of mice had evolved primarily by changes in motivation rather than performance ability at the timethey were reaching selection limits. In addition, neither the BEF model nor the MPBF model of hierarchical evolution provides a particularly good fit to theHRmouse selection experiment. 
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                            - Award ID(s):
- 2038528
- PAR ID:
- 10508995
- Publisher / Repository:
- Ecological and Evolutionary Physiology
- Date Published:
- Journal Name:
- Ecological and Evolutionary Physiology
- Volume:
- 97
- Issue:
- 2
- ISSN:
- 2993-7965
- Page Range / eLocation ID:
- 97 to 117
- Subject(s) / Keyword(s):
- adaptation artificial selection behavior life history performance trade-off
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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