So. Evolution question.

[CP]

I was chating with a friend the other day and we got on the subject of dating and sex, which quickly led to evolution (this always happens; we're biology students). Anyway, my friend remarks that strong, confrontational male herd animals (in general; we weren't discussing a particular species) are "fitter" than sneaky fuckers. Thing is, the situation we were discussing is one where the genetics of the herd are relatively stable and the average strength, speed, whatever does not increase over time. We were also considering the situation that they were like this for a very long time and thus, presumably, had reached an evolutionarily stable equilibrium.

My argument was this: if they're in equilibrium, so the frequencies aren't changing in any significant way over many generations, then there is no reason to assume that one strategy is more successful than the other. Indeed, if there is a direct genetic link to the strategy, then they are exactly as successful as each other; this is rather harder to predict if an individual's behaviour depends on the others around him, but there's still no reason to assume one is more successful. After some thought, I think I see where our difference of opinion arises from.

I've been looking at the rate of spread of an allele, whereas I think he was looking at the overall frequency of the allele. For instance, if a particular locus for a gene in a breeding population was filled by allele A 90% of the time and allele B 10% of the time, and this did not change over several generations, my friend would declare allele A to be fitter (since there are more), whereas I would declare them to be equally valid (because they are propogating at the same rate).

So after all that, my question is -- what is the correct way to compare alleles or traits like this? After a moment's thought I can see how using the majority looks like a valid strategy, but it seems so... simplistic when it comes to strategies (or alleles, or whatever) that are strongly influenced by the existence of each other. I've always assumed that rate of propogation was the relevant thing.

[FedUpWithFaith]

CP,

Those are good questions. As you indicate species population fitness and individual fitness are not the same thing and what's more, they interact. And then there are assumptions on the stability of the environment where I'm sure you know that changes in environmental equilibria will lead to different equilibria in traits and allele frequencies. A trait that is more adaptive in one environment can become less adaptive in another.

Even if we assume trait and allele frequencies are identical, optimum population fitness can be evaluated by the maximum diversity in environmental penetration AND the maximal sustainable population across the environmental equilibria. If the same environment can support a higher equilibrium population when the traits are split 80%-20% instead of 90%-10% then population fitness actually improves when the population of "sneaky" individuals increases. However, keep increasing the population of sneaky individuals to 70%-30% and the overall equilibrium population may go down again. The sneaky individuals in this example obviously offer their population an optimal fitness at a 20% distribution in the population. The non-linear properties of inhibition and cooperativity always come into play. Perhaps if you removed all the sneaky individuals the population would collapse, rendering the fitness of all the individuals lower as a result.

Measuring fitness is all about context. I tend to take your view of things though.

[CP]

The problem with something being "all about context" is that it takes three minutes to explain what you mean every single time you want to talk about it. Why does biology have to be so damn complex and diverse?! I move for a planet filled entirely with a single species of protist! Then biology would be easy! Although much less fun.

[FedUpWithFaith]

Frankly, I love the complexity and ambiguity. All the nuance and beauty of life emerge from them I think. Plus, it gives me lots of mineable wisdom for my line of work. I often use genetic algorithms to evolve highly dimensional solutions to complex modeling problems. So the beauty is, you can leverage the power of genetics and natural selection in algorithms to better understand their how they work in real life.