Evolution with Stochastic Fitness and Stochastic Migration

Migration between local populations plays an important role in evolution - influencing local adaptation, speciation, extinction, and the maintenance of genetic variation. Like other evolutionary mechanisms, migration is a stochastic process, involving both random and deterministic elements. Many models of evolution have incorporated migration, but these have all been based on simplifying assumptions, such as low migration rate, weak selection, or large population size. We thus have no truly general and exact mathematical description of evolution that incorporates migration.We derive an exact equation for directional evolution, essentially a stochastic Price equation with migration, that encompasses all processes, both deterministic and stochastic, contributing to directional change in an open population. Using this result, we show that increasing the variance in migration rates reduces the impact of migration relative to selection. This means that models that treat migration as a single parameter tend to be biassed - overestimating the relative impact of immigration. We further show that selection and migration interact in complex ways, one result being that a strategy for which fitness is negatively correlated with migration rates (high fitness when migration is low) will tend to increase in frequency, even if it has lower mean fitness than do other strategies. Finally, we derive an equation for the effective migration rate, which allows some of the complex stochastic processes that we identify to be incorporated into models with a single migration parameter.As has previously been shown with selection, the role of migration in evolution is determined by the entire distributions of immigration and emigration rates, not just by the mean values. The interactions of stochastic migration with stochastic selection produce evolutionary processes that are invisible to deterministic evolutionary theory

Delineation of Violence from Functional Aggression in Mice: An Ethological Approach

The present study aims at delineating violence from aggression, using genetically selected high (SAL, TA, NC900) and low (LAL, TNA NC100) aggressive mouse strains. Unlike aggression, violence lacks intrinsic control, environmental constraints as well as functional endpoints. Conventional measures namely latency, frequency and duration were used initially to accomplish the objective of delineation using the above strains. However, these quantitative measures fail to reveal further details beyond the magnitude of differential aggression, especially within the high aggressive mouse strains. Hence, it was necessary to analyze further, the behavioral sequences that make up the agonistic encounter. Novel measures such as threat/(attack + chase) (T/AC) and offense/withdrawal (O/W) ratios, context dependency and first-order Markov chain analysis were used for the above purpose. Our present analyses reveal clear qualitative behavioral differences between the three high aggressive selection strains based on the following facets namely structure and context in an agonistic interaction. Structure refers to a detailed study of the agonistic interaction components (ritualistic display, offense and sensitivity to the opponent submission cues) between any two subjects (inter-male interaction for the present study). Context refers to the capacity to identify an opponent by nature of its state (free moving/anesthetized), sex and the environment (home/neutral territory). NC900 displayed context dependency and structurally a rich repertoire of agonistic interaction components with an opponent. SAL failed to show discrimination and its inter-male agonistic behavior is restricted to a repetitive and an opponent-insensitive pattern of attack and chase. TA was comparable to SAL in terms of the structure but sensitive to context variables. Thus, SAL seems to display a violent form of aggressive behavior, while NC900 display ‘functional’ hyperaggression against a docile opponent in an inter-male agonistic interaction.