Search

Longitudinal data are important in exposure and risk assessments, especially for pollutants with long half-lives in the human body and where chronic exposures to current levels in the environment raise concerns for human health effects. It is usually difficult and expensive to obtain large longitudinal data sets for human exposure studies. This article reports a new simulation method to generate longitudinal data with flexible numbers of subjects and days. Mixed models are used to describe the variance-covariance structures of input longitudinal data. Based on estimated model parameters, simulation data are generated with similar statistical characteristics compared to the input data. Three criteria are used to determine similarity: the overall mean and standard deviation, the variance components percentages, and the average autocorrelation coefficients. Upon the discussion of mixed models, a simulation procedure is produced and numerical results are shown through one human exposure study. Simulations of three sets of exposure data successfully meet above criteria. In particular, simulations can always retain correct weights of inter- and intrasubject variances as in the input data. Autocorrelations are also well followed. Compared with other simulation algorithms, this new method stores more information about the input overall distribution so as to satisfy the above multiple criteria for statistical targets. In addition, it generates values from numerous data sources and simulates continuous observed variables better than current data methods. This new method also provides flexible options in both modeling and simulation procedures according to various user requirements. [ABSTRACT FROM AUTHOR]

Environmental perturbations of many kinds influence growth and development. Little is known, however, about the influence of environmental factors on the patterns of phenotypic integration observed in complex morphological traits. We analyze the changes in phenotypic variance-covariance structure of the rat skull throughout the early postnatal ontogeny (from birth to weaning) and evaluate the effect of intrauterine growth retardation (IUGR) on this structure. Using 2D coordinates taken from lateral radiographs obtained every 4 days, from birth to 21 days old, we show that the pattern of covariance is temporally dynamic from birth to 21 days. The environmental perturbation provoked during pregnancy altered the skull growth, and reduced the mean size of the IUGR group. These environmental effects persisted throughout lactancy, when the mothers of both groups received a standard diet. More strikingly, the effect grew larger beyond this point. Altering environmental conditions did not affect all traits equally, as revealed by the low correlations between covariance matrices of treatments at the same age. Finally, we found that the IUGR treatment increased morphological integration as measured by the scaled variance of eigenvalues. This increase coincided and is likely related to an increase in morphological variance in this group. This result is expected if somatic growth is a major determinant of covariance structure of the skull. In summary, our findings suggest that environmental perturbations experienced in early ontogeny alter fundamental developmental processes and are an important factor in shaping the variance-covariance structure of complex phenotypic traits. [ABSTRACT FROM AUTHOR]

• Floral integration has been deemed an adaptation to increase the benefits of animal pollination, yet no attempts have been made to estimate its adaptive value under natural conditions. • Here, the variation in the magnitude and pattern of phenotypic floral integration and the variance–covariance structure of floral traits in four species of Rosaceae were examined. The intensity of natural selection acting on floral phenotypic integration was also estimated and the available evidence regarding the magnitude of floral integration reviewed. • The species studied had similar degrees of floral integration, although significant differences were observed in their variance–covariance structure. Selection acted on subsets of floral traits (i.e. selection on intrafloral integration) rather than on the integration of the whole flower. Average integration was 20% and similar to the estimated mean value of flowering plants. • The review indicated that flowering plants present lower integration than expected by chance. Numerical simulations suggest that this pattern may result from selection favouring intrafloral integration. Phenotypic integration at the flower level seems to have a low adaptive value among the species surveyed. Moreover, it is proposed that pollinator-mediated selection promotes the evolution of intrafloral integration. [ABSTRACT FROM AUTHOR]