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 Today we looked at two different computer models that simulate population dynamics in animals. The first was a simulation of an ant colony with three different roles for the ants to assume: foragers, debris cleaners, and border patrol. Roles were determined by position in the ant world (i.e. ants on the left were always foragers, ants on the upper right were always debris cleaners, and ants on the lower right were always border patrol). All the ants in the simulation secreted task-specific hydrocarbons constantly: foragers secreted forager hydrocarbons, debris cleaners secreted debris cleaner hydrocarbons, and border patrol ants secreted border patrol hydrocarbons. When ants came in contact with the hydrocarbons of other ants they responded to them; forager ants were repelled by the hydrocarbons of debris cleaners and border patrol, etc. In this way the secretion of hydrocarbons became a kind of inter-ant communication.

Conclusions from this section are as follows: 

Ants inform/create their environment by secreting specific hydrocarbons. They are affected by the information (hydrocarbons) put into the world by other ants. We can logically extend these findings to a metaphor of life. Biology (represented by the hydrocarbons and their secretion, a totally blind, unconscious process) informs the environment of an organism. The change in environment initiated by the organism (and the organisms around it) affects the expression of that organism's biology. In this way, our experience of life (i.e. our identity) is a dialogue between biology and experience. It seems to be some sort of compromise.

The difference between human life and ant life is consciousness, or self-awareness. Consciousness would be responsible for the synthesis of both sides of experience (biology and environment) into a "story" of reality. This consciousness would also be responsible for the introduction of intention on a system. Intentionality would in turn affect the environment, further entwining the world and our experience of it.

The second computer model we examined was a predator/prey relationship between sheep and wolves. Grass could also be added as another variable to the environment. Unlike the ant population, this simulation shows the delicate natural balance between populations in an area, and how different factors such as reproduction rate and energy gained from food affected these dynamics. Unlike the almost automatically stabilizing population of ants, the sheep-wolf system was less likely to return to population equilibrium after an environmental shift, which in some situations resulted in the extinction of one of both populations. This difference in the probability of equilibrium between the two systems highlights the importance of reciprocal interactions (i.e. the sheep cannot "bite back," they can't affect the wolf population directly, and thus reducing the probability of equilibrium).

Two things struck us as interesting after observing both of these experiments. Both of these experiments stress a lack of a directional force, and show the random nature of biology. However, the ants ended up in an incredibly organized and effective pattern while half the time either the wolves or the wolves and the sheep ended up dead. One contributing factor to this difference is the presence of more variables and the interdependence of a ecological system as opposed to a single population.

Julia Stuart & David Richardson