Re: Intensity of selection
- From: an588@xxxxxxxxxxxxxxxxxxx (Catherine Woodgold)
- Date: Sun, 2 Jul 2006 02:09:54 -0400 (EDT)
"Perplexed in Peoria" (jimmenegay@xxxxxxxxxxxxx) writes:
Our y-axis variable is W - the 'reproductive success'
of each individual. Simply a count of offspring (divided by 2
to account for sexual reproduction). If you are John Edser, you
will prefer to only include sexually mature individuals in your
sample N; you will also prefer to only count offspring that reach
sexual maturity themselves. If you are not Edser, you may prefer
to count immature individuals in N, and also to count similarly
immature offspring. The concept works either way.
Our x-axis variable is something I will call G - the 'genetic
fitness' of each individual. This is the value that an omniscient
scientist, armed with a knowlege of the individual's genome, would
predict as his best estimate of what W for that individual will
turn out to be. Of course, his estimate is only an estimate, and
his prediction of W will often be wrong. Reproductive success
does depend on having good genes, but it also sometimes depends
on having good luck.
Ok, does everybody have this scattergram fixed in their imagination?
Wonderful. Now imagine a regression (least squares) line running
through the diagram. Got that? Great! Let me point out some of
the interesting features of this diagram.
First, we note that the slope of the regression line is very close
to 1.0. High G individuals are more successful in their sex lives
than are low G individuals. But they are no more lucky. But it
is an interesting observation that if we had exchanged the axes and
put G on the y axis and W on the x-axis, then the regression line
slope would not be close to 1.0. High W individuals are luckier at
love than low W individuals. That is part of the reason they became
high W.
You can define G as the average W or expected value of
W for individuals with a certain set of genes.
If you do this, you get exactly 1. for the regression line
plotted in one direction. Or approximately 1., as you
say, for a real situation in which luck causes things to
vary from the predicted average.
.
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