Abstract
The importance of measurement error in studies of asymmetry has been acknowledged for a long time. It is now common practice to acquire independent repeated measurements of trait values and to estimate the degree of measurement error relative to the amount of asymmetry. Methods also allow obtaining unbiased estimates of asymmetry, both at the population and individual level. One aspect that has been ignored is potential between-individual variation in measurement error. In this paper, I develop a new method to investigate this variation in measurement error and to generate unbiased estimates of individual asymmetries. Simulations show that variation in measurement error can indeed result in biased estimates of individual asymmetry and that the proposed method adequately provides unbiased estimates. The method is applied to two empirical datasets and shows that, at least in some traits, substantial variations in measurement occur. The limitations of the model are discussed.
Highlights
Developmental instability (DI), i.e., the sensitivity of a developing trait to random perturbations [1], is most often estimated by subtle, directionally random asymmetries (fluctuating asymmetry (FA))
The coefficient of determination of the regression analysis of the estimated and true underlying individual asymmetries decreased with the increasing degree of measurement error (Figure 1)
I expanded upon the traditional mixed model approach to allow for between-individual variation in measurement error implementing a mixture approach [11,12]
Summary
Developmental instability (DI), i.e., the sensitivity of a developing trait to random perturbations [1], is most often estimated by subtle, directionally random asymmetries (fluctuating asymmetry (FA)). For over half a century, DI and FA have been studied in relation to stress and fitness, and the results have been equivocal [2,3]. Symmetry 2015, 7 population FA was related to genetic and environmental stress. This was motivated by the results of a study on male tail asymmetry and their attractiveness to females in barn swallows [4] and presumed as evidence for a genetic basis of developmental instability [5]. In spite of a large body of research in a variety of species, research relating FA to measures of individual phenotypic quality and fitness remains highly equivocal [6,7]. This study does not aim to add to that specific aspect, but aims at developing a statistical model that may improve the estimation of individual asymmetries increasing the power of the analysis of associations between individual FA and measures of quality or health
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