Skull Modularity in Neotropical Marsupials and Monkeys: Size Variation and Evolutionary Constraint and Flexibility

An organism is built through a series of contingent factors, yet it is determined by historical, physical, and developmental constraints. A constraint should not be understood as an absolute obstacle to evolution, as it may also generate new possibilities for evolutionary change. Modularity is, in this context, an important way of organizing biological information and has been recognized as a central concept in evolutionary biology bridging on developmental, genetics, morphological, biochemical, and physiological studies. In this article, we explore how modularity affects the evolution of a complex system in two mammalian lineages by analyzing correlation, variance/covariance, and residual matrices (without size variation). We use the multivariate response to selection equation to simulate the behavior of Eutheria and Metharia skulls in terms of their evolutionary flexibility and constraints. We relate these results to classical approaches based on morphological integration tests based on functional/developmental hypotheses. Eutherians (Neotropical primates) showed smaller magnitudes of integration compared with Metatheria (didelphids) and also skull modules more clearly delimited. Didelphids showed higher magnitudes of integration and their modularity is strongly influenced by within-groups size variation to a degree that evolutionary responses are basically aligned with size variation. Primates still have a good portion of the total variation based on size; however, their enhanced modularization allows a broader spectrum of responses, more similar to the selection gradients applied (enhanced flexibility). Without size variation, both groups become much more similar in terms of modularity patterns and magnitudes and, consequently, in their evolutionary flexibility. J. Exp. Zool. (Mol. Dev. Evol.) 314B:663-683, 2010. (C) 2010 Wiley-Liss, Inc.

Augmented Lagrangian methods under the constant positive linear dependence constraint qualification

Two Augmented Lagrangian algorithms for solving KKT systems are introduced. The algorithms differ in the way in which penalty parameters are updated. Possibly infeasible accumulation points are characterized. It is proved that feasible limit points that satisfy the Constant Positive Linear Dependence constraint qualification are KKT solutions. Boundedness of the penalty parameters is proved under suitable assumptions. Numerical experiments are presented.