Drs. Sanford and Carter respond to PS Scientists

GE hypothesizes death–neutral theory allowing for VSD propagation under specific circumstances does not allow GE to “work.”

We want to know how many VSDs of what effect size will result in the death of the organism.

You seem to be missing that mutations occur, segregate, and then fix.

Right and the probability of VSDs occurring and reaching fixation and cumulatively having enough VSDs to phenotypically lower fitness is astronomical. Never mind lowering fitness from phenotypically imperceptible to catastrophic extinction avoiding selection the whole way. It’s not clear how one bridges the gap between selection coefficients becoming phenotypically perceptible to natural selection and the reduction of fitness causing extinction.

Something like:

(1/2Ne * P(VSDi))^n

where P(VSDi) = P(VSDi coding) + P(VSDi noncoding)
and i = specific probability of variant type
and n = number of cumulative VSDs that must occur and reach fixation and sum to a fitness commensurate with extinction.

It also assumes that all of humankind is a single mating population–completely bogus.

It’s not clear how you want to measure absolute fitness–especially in the context of a finite population whose variants are under the control of drift and whose variants do not produce phenotypes.

How are the fitness effects of each VSD accumulating? Do we add them? Do they interact? Are they synergistic etc.

“Force” as in a mechanism of allele frequency change. In this case, the trade off between drift and selection.

How should we measure W with variants that don’t produce phenotypes and are under the control of drift in a finite population?

Right–and so how do we walk from a 20 million base pair difference on average in humans, with inordinately high numbers of private SVs, to everyone has the same set of VSDs?

I’m not sure that I am :slight_smile:

There is no such thing in created humanity with front-loaded variation. I’m not aware if this is mentioned in the book, but I couldn’t help but comment to reduce confusion.

Well, of course we can’t. Why? There must be some distribution of small departures from neutrality even if we don’t know what it is. If that distribution is biased toward negative s, as GE must assume, then neutral fixations will also be so biased, and absolute fitness will decline.

There is no need for everyone to have the same set, just approximately the same number.

It seems that this is the one question that @PDPrice, Sanford and Carter and so on need to answer.

Before you can claim that the information content in the genome is progressively declining, and certainly before you can put a time limit on how long it could last, you MUST explain how the information content in the genome is measured.

Basically, until and unless we get some equations to work with, everything else is just waffle.

9 Likes

Did you mean to say, “there IS such a thing”? Because that is the view held by Carter & Sanford.

1 Like

If GE is true, this means that any change after the first of a “kind” is a degradative step towards extinction.

So if Adam was blond, any of his descendants that had brown hair would be imperfect and degraded.

Sanford is not the first person, of course, to pursue an ideology in which all human variation can be seen in terms of who is more or less “degraded.”. It has has quite a lengthy, if deplorable, history.

3 Likes

Can you explain to me what you mean by these terms exactly? Because I actually agree with that statement, but I’m still not sure we mean the same thing by it.

You may also be interested to read Dr Eyre-Walker’s response to my question about strictly (or selectively) neutral mutations.

What in the world is “front-loaded variation”?

How about it Paul? Can you demonstrate your claim the information content of a genome is progressively declining with every generation?

Since you’re afraid of horses why not use the genome of Otzi the Iceman who lived 5300 years ago.

Complete Mitochondrial Genome Sequence of the Tyrolean Iceman

That’s roughly 250 human generations since Otzi’s time and now. Please show us how much the genome of an extant human has declined in information content from Otzi’s genome.

4 Likes

Absolute fitness is the number of offspring recruited into the population (or the expected number, if you’re talking statistically). Relative fitness is the frequency change (or expected frequency change). The relevance here is that absolute fitness can decline while relative fitness remains the same.

I don’t think your question was clear enough, and it wasn’t answered clearly either. It’s also a data-free opinion.

2 Likes

Ok, I still agree, even though I use “absolute fitness” to mean something related, but different. However, entropic decay happens in such a way that in its early stages, it won’t necessarily affect the number of offspring at all. I explained that in my debate with Dr Garret. Life is more complicated than the metric of reproduction alone. With that said, I still find you to have the clearest understanding of GE of all the participants so far. With the exception of @glipsnort, whom I believe fully understands the concepts and chooses not to accept the conclusion on the basis of a warped view of reality :wink:

I couldn’t have possibly been any more meticulously clear in my question than I was, nor was his answer in any way unclear. You simply don’t like the answer given.

Why is it that you don’t go on to explain what you mean?

What does that mean, and how does it relate to fitness?

Your opinion. And regardless of the answer, it’s still an opinion unsupported by evidence.

1 Like

Your explanations are unconvincing. Evidence would be.

Life is, fitness is not–by definition.

2 Likes

I must confess that I don’t have any understanding of genetic entropy at all.

However, I do have at least some understanding of Gibbs thermodynamic entropy and Shannon information theoretic entropy, and I happen to know that both are precise mathematical concepts rigorously defined by very specific (and similar) equations. Gibbs entropy is defined as

S = - k_B \sum_i p_i \ln p_i

and Shannon entropy is defined as

H(x) = - \sum_{i=1}^n {\mathrm{P}(x_i) \ln \mathrm{P}(x_i)}

What is the equation that defines genetic entropy, and how does it relate to Gibbs and/or Shannon entropy?

2 Likes

Yes which makes it doubly misleading that you’ve elected to label this term of yours the same as one already in established use in the very field you are trying to criticize. The term absolute fitness has a clear and well-understood definition in population genetics and evolutionary biology, and it differs substatially from yours because yours is not a measure of reproductive success, but some nebulous idea that has to do with “integrity of information in the genome” that exists in your mind only that you can’t quantify.

3 Likes

You keep saying this. As far as I know, GE hypothesizes extinction, not death. If you have reason to think otherwise, please provide it.

It’s not clear to me what you’re calculating here. It appears to be the probability that a particular set of n mutations reach fixation, which is simply not relevant. Every new effectively neutral mutation has a probability of 1/2N of fixation; the number of new neutral mutations per generation is 2nµ, where µ is the neutral mutation rate, with the result that µ mutations fix per generation at equilibrium. That translates into ~30 fixations per genome copy per generation.

Under the hypothesis of GE, almost all(*) of these are mildly deleterious (and apparently, all affect absolute fitness as much as they affect relative fitness). To be effectively neutral, these could have selection coefficients as large as, say, -6x10-4. If nothing prevents their fixation, that would amount to something like a 50% loss of fitness in a thousand generations. Natural selection is too weak to prevent the drift to fixation of any one of these. What my model (which I’m about to update) tries to do is estimate the effect of NS on bulk VSD alleles.

(*) Not all, since that would imply a perfect genome, which I’ve been told they don’t assume. So just almost all.

Bookmarking so I can come back to enjoy all this delicious math when I have more time! YUM!! :yum:

1 Like

6 posts were merged into an existing topic: Comments on Sanford and Carter respond to PS participants

Dr Sanford’s book is going to do the best job of explaining it. It boils down to what we can know about what the genome is (coded information), and what happens when you introduce undesigned changes into functional coded information.

More empirically, we know generally that most mutations are damaging because we can see what happens in mutagenesis experiments and we can look at mutational load over time. This was addressed in the joint article (OP), as well as at https://creation.com/fitness. Many would like to bait-and-switch, pretending that just because we cannot directly measure individual VSDMs, that somehow we know nothing about the distribution of most mutations in general (we do).

It is clearly you doing the bait-and-switch, saying that because we know something about mutations of large effect, we can extrapolate that to mutations of small effect.

2 Likes