One way to explain the modularity that is seen in biology is that it helps species to evolve quickly as their environment changes.
But the notion that "evolvability" can be selectively favored is tricky intellectual territory, and people can get drawn in to sloppy thinking. Just as group selection must favor more than just "the good of the species," selection for flexibility cannot be grounded in future advantages to the species. To be effective, evolutionary pressure must influence the survival of individuals in the present.
Whether this happens in practice depends on a lot of specific details. Some simulations of the effect of changing environments have not shown any effect. But at a meeting I covered last year for the New York Academy of Sciences, Uri Alon showed one model system that evolves modularity in response to a changing environment.
Alon is well known for describing of "motifs" in networks of molecular interactions. A motif is a regulatory relationship between a few molecules, for example a feed-forward loop, that is seen more frequently in real networks than would be expected by chance. It can be regarded as a building block for the network, but it is not necessarily a module because its action may depend on how it connects with other motifs.
Alon's postdoc Nadav Kashtan simulated a computational system consisting of a set of NAND gates, which perform a primitive logic function. He used an evolutionary algorithm to explore different ways to wire the gates. Wiring configurations that came closest to a chosen overall computation result were rewarded by giving making future generations more likely to resemble them. "The generic thing you see when you evolve something on the computer", Alon said, "is that you get a good solution to the problem, but if you open the box, you see that it's not modular." In general, modules cannot achieve the absolute best performance.
Kashtan then periodically changed the goal, rewarding the system for a different computational output. Over time, the structure of the surviving systems came to have a modular structure. One interesting surprise was that in response to changing goals, the simulated systems evolved much more rapidly than those exposed to a single goal.
But Alon emphasized that this was not a general feature. Instead, the different goals needed to have sub-problems in common. Evolution would then favor the development of dedicated modules to deal with these problems. It is easy to imagine the challenges facing organisms in nature also contain many recurrent tasks, such as the famous "four Fs" of behavior: feeding, fighting, fleeing, and reproducing.
So some biological modularity may reflect the evolutionary response to persistent tasks within a changing environment. But does this explain the wide prevalence of modules? In a future post, I will examine another explanation: that modularity is one of the tools that helps individual organisms adapt to the changing conditions of development and survival during their own lifetimes.