# Disproving Evolution – Part 4.5 – Complex Traits Versus Natural Selection

Disproving Evolution – Part 4.5 – Complex Traits Versus Natural Selection May 7, 2015

Continuing the rebuttal of the article,  “9 Scientific Facts Prove that “The Theory of Evolution” is wrong.

The author has a basic argument against natural selection: “I think natural selection predicts X and not Y, but in reality, we see Y and not X. Therefore, it’s falsified.

I’m going to another stab at this, and abstract it out to hopefully show where the author goes wrong. If you already get why, feel free to skip this post.

More specifically, the argument is basically:

If natural selection is true, we’d expect darker-skinned people in polar areas, so they can absorb more solar heat in colder regions, and we’d expect lighter-skinned people in the equatorial regions, so they can reflect that heat, and keep cool. We don’t find that is the case, so natural selection doesn’t happen.

On the surface, it may seem like a decent approach. After all, hypothesis-testing is important in science. It’s how we figure out whether there’s any truth to a claim. So if you don’t dig any deeper, this may seem like a convincing argument.

The author’s problem is that the argument has insufficient resolution… like showing a photo that’s only 1×1 pixels, saying “1 out of 1 pixels in this photo are green, which is inconsistent with the color of a cat, so it can’t be a photo of a cat“, without considering that, with more pixels, we might find out that it’s a photo of a cat on a green background, but the green took dominance.

## Prediction in Complex Models

I’m going to attempt to explain this is a quasi-pseudomath way, and try to keep it as straight forward as possible.

### The threshold, and the contributing factors

In order for our model’s “activation state” to engage (in natural selection’s case, survival to reproduction), we have a number of contributing factors.

Contributing Factor A increases the ability of reaching that threshold by 1 unit… or written another way:  A[+1]

But we don’t have just that one factor, we have many:

Factors: { A[+1],  B[+5],  C[-3],  D[+2] }

Not all factors contribute. C is detracting by 3, in the above context… but generally, if all the factors add up to the point that the threshold is met, we’ve achieved the activation state (survival).

Suppose our threshold is 10, and our contributing factors are:

{ A[+3],  B[+5],  C[-3],  D[+2],  E[+3],  F[+5] } – Total: 15

Despite C, we’ve still met the threshold, which means all the factors are individually benign. C could actually worsen to -8, and we’ll still activate. If we’re running this through a natural selection algorithm, C may not necessarily be weeded out, because it’s not preventing the activation state.

When it comes to evolution, however, a simple summation of values doesn’t really work. Instead of adding/subtracting towards a hard threshold, it’d be better to establish these as altering the probability of achieving the activation state… so our contributing factors would be more like:

{ A[+3%],  B[+5%],  C[-3%], D[+2%],  E[+3%],  F[+5%] }

Suppose instead of having a set value of 10 for our threshold, instead we’re starting with something like a 50% chance of activation. After we’ve added in the factors, we have a 65% chance of activation (meaning in evolution, we have a 65% chance of survival to reproduction).

When we look at the author’s argument, it can still work here. We’d expect the positive traits to be reinforced, and the negative traits to be diminished, as the generations continue.

### Complex Factors

Consider now that each factor, such as our A[+3%], can be actually more complex than a single value. Each factor can positively or negatively contribute in different ways:

Factor A {

Modifier A: -3%

Modifier B: +4%

} (Net: +1%)

In other words, we can have a trait/factor, that can increase the probability in one respect, and decrease the probability in another. If our trait/factor increases by 4% and decreases by 3%, the net result is that this trait/factor, overall, increases our probability of activation by 1%. This means that despite Modifier A‘s disadvantage, the trait/factor is still favored by natural selection.

If we look at the example of fur, the numbers could be something like this:

Trait: Fur {

Survival chance modifier due to thermal insulation: +5%

Survival chance modifier due to parasite issues: -4%

} (Net: +1%)

So despite the parasites, we’d still expect that fur would be favored by natural selection. What the author was doing was basically focusing on the parasites, and insisting that all creatures should evolve to become hairless… without considering that other variables may exist, and take precedence.

### Multiple, Overlapping Traits

The author’s position is even weaker than that. We can have more than one trait that assists with dealing with a specific problem.

Factor A {

Modifier for Problem A: -6%

Modifier for Problem B: +4%

}

Factor B {

Modifier for Problem A: +4%

}

If we only consider Factor A, it’d be reasonable to conclude that Factor A would be reduced by natural selection. On the other hand, if Factor B assists with Problem A, the combination of the two would be:

Combined Factors A & B {

Modifier for Problem A: -2%

Modifier for Problem B: +4%

}

Because B alleviates A‘s problem, A can continue to be favored by natural selection.

Cats have their comb-like tongues that help comb-out parasites. This helps mitigate a problem with fur, and therefore, natural selection will still favor the fur’s benefits towards survival.

### Back to the example of dark versus light skin, in sunny regions

I could add another section discussing how different environments can change what the modifier values are, but I don’t think that’ll be needed here. We can focus simply on this one trait in this one environment.

Again, I’m making up these numbers, but it’s still adequate towards explaining how natural selection isn’t as simple as the author thinks. In order for the author’s argument to work, he/she would need to demonstrate that the heat absorption issue trumps the other variables.

Trait: High-melanin skin {

Modifier for dealing with damaging solar radiation: +5%

Modifier for dealing with heat exhaustion: -4%

Modifier for dealing with Vitamin D production: -2%

}

Trait: The ability to sweat {

Modifier for dealing with heat exhaustion: +10%

}

Combined Traits: High-melanin skin & ability to sweat {

Modifier for dealing with damaging solar radiation: +5%

Modifier for dealing with heat exhaustion: +6%

Modifier for dealing with Vitamin D production: -2%

} (Net: +9%)

Thus, we would expect natural selection to produce high-melanin skin, and maintain it, in sunny regions.

I’m not going to say that the author’s argument was a lie by omission. I think it’s most likely that she/he just doesn’t understand the topic enough to realize where the problem arises. Through Reductionism, we can break down the understanding of a complex topic into easier-to-understand chunks… but it’s still a very complex topic. You can’t just toss out variables.

If our model/theory was that human survival needs three things: food, shelter and water… you can’t merely decide that the water-requirement is the only one that matters, and if our model is true, we’d expect people to be living at the bottom of the lake, where the water is maximized, and since we don’t, therefore, the model is wrong.

… but that’s essentially what the author is doing. I feel like I’m beating a dead horse, but apparently it needs to be thoroughly explained.

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