PubMed · 10305058
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R E Numerof. 1977. Assertion training, part 2: learning to be assertive.. https://pubmed.ncbi.nlm.nih.gov/10305058/
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The causes of biological gigantism have received much attention, but only for individual organisms. What selection pressures might favour the evolution of gigantic societies? Here we consider the largest single-queen insect societies, those of the Old World army ant Dorylus, single colonies of which can have 20 million workers. We propose that colony gigantism in Dorylus arises as a result of an arms race and test this prediction by developing a size-structured mathematical model. We use this model for exploring and potentially explaining differences in colony size, colony aggression and colony propagation strategies in populations of New World army ants Eciton and Old World army ants Dorylus. The model shows that, by determining evolutionarily stable strategies (ESSs), differences in the trophic levels at which these army ants live feed forwards into differences in their densities and collision rates and, hence, into different strategies of growth, aggression and propagation. The model predicts large colony size and the occurrence of battles and a colony-propagation strategy involving highly asymmetrical divisions in Dorylus and that Eciton colonies should be smaller, non-combative and exhibit equitable binary fission. These ESSs are in excellent agreement with field observations and demonstrate that gargantuan societies can arise through arms races.
A single trait's fluctuating asymmetry (FA) is expected to be a poor measure of developmental instability. Hence, studies that examine associations between FA and outcomes expected to covary with developmental instability often have little power in detecting meaningful relationships. One way of increasing the power of detecting relationships between developmental instability and outcomes is through the use of multiple traits' FA. The way multiple traits have typically been used is in trait aggregates. Here, we illustrate another way of examining relationships with developmental instability using multiple traits' FA: through structural equation modelling. Covariances between measures of FA and an outcome variable are interpreted within the context of an explicit model of associations between variables, which is tested for fit and the parameters specified within the model are estimated. We used nine traits' FA as markers of a latent variable of men's developmental instability, which was associated with the number of sexual partners. The results indicate a sizeable correlation between developmental instability and men's sexual history, despite small correlations between individual traits' FA and sexual history.
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