Verbal and quantitative genetic models of sexually antagonistic coevolution suggest that coevolutionary arms races should be common. Sexual selection favors exaggeration of male persistence traits that are costly to females, and females, in turn, are selected to resist these traits. The heightened resistance by females is thought to then favor further exaggeration in the male trait, leading to an escalating coevolutionary arms race between persistence and resistance traits. Much of this theory, however, is based on an (implicit) assumption that there are tight constraints on how female resistance can evolve. We develop a theory that identifies and relaxes these constraints, allowing female resistance to evolve in a fashion that better reflects known empirical patterns in the evolution of female preference functions (the resistance trait). Our results suggest that evolutionary arms races that lead to the exaggeration of persistence and resistance will be much less common than formerly predicted. Females sometimes evolve indifference to male traits rather than resistance and can even evolve to discriminate against these traits. These alternative outcomes depend on the existence of genetic variance in the components of the female sensory system underlying female resistance and on the strength of natural selection acting on these components. Female indifference tends to evolve when natural selection on the sensory system is weak, and under these conditions, sexually antagonistic coevolution tends not to reduce female fitness significantly at equilibrium. When natural selection on the female sensory system is strong, however, then arms races are more likely, and female fitness is then sometimes significantly depressed at equilibrium. Sexually antagonistic coevolution is thus likely to have strong deleterious effects on population fitness only when female sensory traits are under strong natural selection to perform functions in addition to those involved with mating. Together, these results suggest that identifying the nature of genetic variation in and the strength of natural selection on female resistance should be a central goal of future studies of sexual conflict.
This paper describes the implementation and performance of PBPI, a parallel implementation of Bayesian phylogenetic inference method for DNA sequence data. By combining the Markov Chain Monte Carlo (MCMC) method with likelihood-based assessment of phylogenies, Bayesian phylogenetic inferences can incorporate complex statistic models into the process of phylogenetic tree estimation. However, Bayesian analyses are extremely computationally expensive. PBPI uses algorithmic improvements and parallel processing to achieve significant performance improvement over comparable Bayesian phylogenetic inference programs. We evaluated the performance and accuracy of PBPI using a simulated dataset on System X, a terascale supercomputer at Virginia Tech. Our results show that PBPI identifies equivalent tree estimates 1424 times faster on 256 processors than a widely-used, best-available (albeit sequential), Bayesian phylogenetic inference program. PBPI also achieves linear speedup with the number of processors for large problem sizes. Most importantly, the PBPI framework enables Bayesian phylogenetic analysis of large datasets previously impracticable.
Few age-structured models of species dynamics incorporate variability and uncertainty in population processes. Motivated by laboratory data for an insect and its parasitoid, we investigate whether such assumptions are appropriate when considering the population dynamics of a single species and its interaction with a natural enemy. Specifically, we examine the effects of developmental variability and demographic stochasticity on different types of cyclic dynamics predicted by traditional models. We show that predictions based on the deterministic fixed-development approach are differentially sensitive to variability and noise in key life stages. In particular, we find that the demonstration of half-generation cycles in the single-species model and the multigeneration cycles in the host-parasitoid model are sensitive to the introduction of developmental variability and noise, whereas generation cycles are robust to the intrinsic variability and uncertainty that may be found in nature.
Background: This study examines the characteristics and needs of 69 youth who are homeless, or at risk of homelessness at Pathway's Home Base Youth Drop-In Centre in the affluent suburb of
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