how good is optimality?

Evolution is, undoubtedly, the key principle of theoretical biology. Here's an example to illustrate why it is such a powerful idea.

Imagine that I start off with a whole bunch of animals, 1/2 of which are red, 1/2 of which are blue. Every year, every red animal has 2 babies, and then dies. Every year, each blue animal has 1 baby, and then dies. Well, in this (very simple!) scenario, the number of blue animals stays constant, while the number of red animals increases very fast (it doubles every year!). It's not hard to see that, if I wait a long time, and then look at the population, it will consist of mostly red animals: the population "evolved" to be more red.

This example illustrates the basic idea: over time, populations change to resemble those animals that have the most babies.

If you are constructing a theoretical model of how animals look, or behave (or whatever), then, you have a seemingly easy task: for any property (say, size, for example) of the animal, estimate how many babies an animal with any value for that property (100lbs vs 50 lbs, etc.) will have, then choose the value that maximizes the number of babies.

The problem is that it's often not very clear how to estimate the number of babies based on one particular property. In fact, often different properties will be in conflict. For example, it would be, in principle, good for me to have a much bigger brain. However, then I would require more food (brains consume a lot of energy), so I would be more prone to starvation. How does nature balance these conflicting goals? And, how does brain size relate to number of babies?

Most of the time, theoretical biologists ignore these complications.

Instead of thinking about the number of babies an animal produces, they just postulate some "goal" for the system they are studying, and then figure out the best way to meet that goal. They usually also ignore that fact that different aspects of the animal might have competing interests.

For example, one line of research might go something like this: "The goal of vision is to allow the brain to form an accurate model of the external environment. So, I theorize that the visual system should look like the best possible camera (or whatever) for making high-fidelity images of the world."

So far, I have probably come off as being very critical of this optimality approach. However, it's an approach that I use quite often (and the "line of research" in quotations above is one that I am currently pursuing), because it is relatively straightforward, and often gives useful insights into the workings of complicated biological systems.

The whole point of theoretical biology is to make (educated) guesses about how stuff might work, and how it might all fit together. These guesses will (hopefully) inform new experiments that will let us make better models, and the cycle continues. In that sense, a theory that's "wrong" is still useful, so long as it leads people to ask questions that generate new insights.

So what's my point here? Well, for one thing, it's actually pretty tough to do good work in theoretical biology. Also, while it may be a fine starting point to consider parts of the animal in isolation, we eventually need to assemble all the pieces, and consider the way evolution acts on individual animals, and on populations of animals.