Let’s imagine a small nano-scale particle suspended in an ideal fluid under a condition where no forces are subjected to the particle. The temperature is absolute zero. There is no motion whatsoever, even if the fluid does not become a solid.
Now let’s bring up the liquid to room temperature, then the particle starts to move in accordance with Brownian motion.
If you were to average out all the vectors of movements within all time intervals, it would equal to zero, but of course the particle does not sit still. The position it ends up in is entirely stochastic. (this is akin to evolutionary drift).
What happens if we add an additional force? A very weak force. Gravity for example. If gravity was the only factor, the particle would have a very simple, predictable, unidirectional movement. (This is akin to evolutionary selection). But in this situation, the gravitational force that is applied to the particle is very minor, in both absolute and relative terms. The forces that drive Brownian motion still dominates, such that the vast majority of the particle’s motion across time is dictated by Brownian motion (nearly neutral evolution). However, recall that the directions of all the major Brownian motions has a statistical average of zero, but the minor motions caused by gravity all have the same direction. This means that [at large time frames] there is a clear directional bias, in spite of the fact that Brownian motion dominates within every incremental time interval. This means that gravity still have an relevant effect on the average movements of small particles (They are not “un-selectable”)
Also, while we are on this subject, the physics that I just described actually applies to the (macro-)molecular processes that happens within cells. The vast majority of the motions of molecules, and even large protein-complexes, is also Brownian. However, this Brownian motion is made ever so slightly biased (average made non zero) via the conversion of energy. The last image above is from “On being the right size, revisited. The problem with engineering metaphors in molecular biology” which is a good read, and also discusses the implications of Brownian motion in biology.
My debate opponent Dr. Hancock has done me the honor of giving a very comprehensive response, and so I believe I owe him the same respect. Out of respect to those who don’t want to delve into this quite so deeply, however, I will start with the most important points first in this post, and then from there I will proceed to do what I can to address his many other statements.
It would seem that for me to continue on this thread after this response would be to beat a dead horse, because Dr. Hancock has now made public statements that amount to concessions on every single point that was under debate. I will demonstrate each of these now.
In preparation for the debate, I took the time to catalog every statement I could find that Dr. Hancock had made re: Genetic Entropy over the several years he has been publicly commenting on it. I then boiled those down to what I considered the top three most serious attacks he had made. Here are his original claims.
1) Human effective population size is around 7 billion.
Hancock has now conceded that point:
I’m very happy to update to an estimate nearer Felsenstein’s, though to be precise we’d need to consult global life-tables.
For context, Felsenstein’s number is nowhere near 7 billion - it’s 2.7 billion. He referred to his previous statement as a “spitball”, which I do believe it was.
Probably more important than this, however, was my rebuttal to his use of recent Ne, rather than long-term Ne (as Kondrashov used) in the first place. His only response to this was to retort that I didn’t believe in equilibrium population size, which was a non sequitur since long-term Ne is based on many factors, none of which include any “equilibrium”. The population size component of long-term Ne is derived from the harmonic mean of the census size, which does not depend on there being an equilibrium at any point. Since the long-term plausibility of evolution is what is under debate, it is very clearly the long-term Ne that is relevant to that question.
2) Hancock claimed his simulation represented a defeater of Genetic Entropy.
Directly quoted from Hancock & Stern Cardinale’s Paper:
Our results act only to demonstrate that, in a stochastic
demographic model with a DFE inspired by empirical studies, populations will not be
driven to extinction due to the pressure from deleterious mutations, contrary to B&S
Not only does this represent a claim to refute Sanford, it also represents a claim to solve Kondrashov’s paradox, since this exact thing is the definition of the paradox. Kondrashov showed that realistic parameters for LMEs when applied to population genetics theory consistently demonstrate fitness decline (which would ultimately result in extinction). This is why Kondrashov considered this a paradox that “needs a resolution”.
Retroactively, Hancock is now attempting to create a false distinction between Sanford and Kondrashov that he should have known all along never existed. Sanford quoted liberally from Kondrashov in his book, and made it clear that Kondrashov’s Paradox was a big part of what he was calling “genetic entropy”.
Now, Hancock has conceded that his simulation did not solve the paradox (and that means it also didn’t refute Sanford, either).
If GE = Kondrashov’s paradox, as Paul plainly states, then these simulations are irrelevant.
To this, Hancock states that his simulation was only attempting to mimick the parameters Basener and Sanford used, but as I showed in the livestreamed debate, they bore little to no resemblance to one another.
3) Hancock stated that population geneticists don’t take their own models as gospel.
During our livestreamed debate, I quoted from Dr. Lynch who made it clear that not only does he take population genetics theory as gospel, he insists that if any claim about evolution cannot be shown to be feasable according to the established population genetics models, it should be held in doubt!
During the crossexam, at around timestamp 53:18, I asked Dr. Hancock if he agreed with Lynch’s statement. His response:
“Yes, of course.”
I’m unsure if he realized this contradicted his earlier statements, but in any case this was a concession on point number 3.
So that concludes all three of the points I brought up in the debate. But what about the topic of the debate as a whole? "Are mutational effects a problem for evolution?" Well it turns out that Dr. Hancock has conceded on that now as well! In the debate, he made the claim (again, during crossexam) that Kondrashov’s paradox had been solved. But now he has changed his mind on that:
Paul is correct that I said “we have resolved” in the debate – this is a incorrect and I appreciate Paul pointing it out. What I should have said is that we have resolutions to the paradox.
So, let’s try to make some sense of this doublespeak. In the debate, he gave a clear answer, yes, the paradox is resolved. Now he says that was a mistake. Apparently, there are “resolutions”, but the paradox is not actually resolved. I suppose what he means is that people have attempted to resolve the paradox, but there is no conclusive answer. To which I would not offer any disagreement. Certainly, there are attempts to resolve the paradox. Kondrashov offered several in his own paper as well.
Since both parties now agree that Kondrashov’s paradox is not solved, we can also readily agree that mutational effects are indeed a problem for evolution. With that, I will end this initial response (which should be the final chapter of this Price - Hancock debate of 2026).
It is in fact supported by the evidence, in exactly those experiments where Sanford and Rupe wrote GE must be happening anyway. It’s this inconvenient fact that has caused creationists such as yourself to subsequently change the idea of GE to suggest perhaps bacteria are immune to GE.
I should also note here with regards to your Sanford quote from his book:
That statement there doesn’t make logical sense.
First of all “theorists” like Hancock usually work on computers, doing modeling (not “microbial samples”). To be sure, they they do get data from experimentalists, and some times from doing their own field work.
But they don’t “prefer to use microbial samples” out of some nefarious plot to ignore populations with less effective population sizes (as Sanford suggests here), but because growing a billion bacteria takes a day, and you can measure their relative fitness over the course of a few hours.
Though the genetic manipulations required to engineer specific mutations so you can compare their relative effects across different environments and genetic contexts is definitely more complicated, and takes weeks if not months of work.
But growing a billion cows/sheep/mice/fruitflies, engineering their mutations and ensuring they’re being tested in identical genetic contexts, and measuring their relative fitness is… a bit of a challenge.
You understand the massive increase in difficulty is why biologists do most of their work on smaller organisms with much shorter generation times right? It’s not what Sanford suggests here. What he is insinuation with that line seems rather deceptive to me.
You misunderstand me here. I am not claiming that the idea that single large-effect beneficial mutations compensating for numerous small-effect deleterious ones is a novel idea at all.
I am talking about the idea of a DFE changing with fitness (the phenomenon called diminishing-returns epistasis) as a solution to Kondrashov’s paradox, being a novel idea.
And just to stave off any possible confusion about whether I think I have some unique insights people in the field should listen to, the only reason I suggest it is because I did some google scholar searches to see if I could find anyone suggesting such a thing, but didn’t find any.
Considering how even Fisher’s geometric model (and fitness landscape theory), which implies a DFE changing with fitness, to my mind suggests an obvious solution to the problem, I was all the more surprised I couldn’t find any such suggestions in the literature and was speculating on why that could be.
To be sure, my searches could just be incomplete. While the search terms yielded thousands of papers I could not find any that obviously related to the idea by quickly scanning a few dozen results.
And while on that topic, I am much less concerned about your replies (no hate) Paul, than I am about those of @talkpopgen here. He is, after all, quite obviously the one actual specialist in the field participating in this thread.
I take your point about ENCODE, and it’s definitely true that the world is full of self-appointed experts, with tangential credentials at best, opining on their latest revolutions of evolutionary biology.
The main reason for my suggestion, as I explained to Paul in another reply, was really that I couldn’t find any articles obviously discussing the phenomenon of diminishing-returns epistasis as a potential solution to Kondrashov’s paradox (or mutational load).
And yet there is good biological data coming from evolution experiments (though pretty much all of these are microbiology for reasons we shouldn’t have to explain, but creationists misrepresent it when we don’t so here we are) that shows how populations that climb novel fitness peaks have numerous large-effect mutations available to them.
This is in-part a moderation error. One of the ground rules here is we should not tell others what their faith is. I should not have accepted that portion of Paul’s comment. I can’t fix it now, but the mods will be more careful going forward, and we will cut off that line of discussion.
Taking a wild stab in the dark, I suspect instead he means that a consensus on which one (if any) of the many proposed solutions, or perhaps a combination, will be the one the population genetics community coalesces around.
Any one or even a combination of them might be entirely conclusive.
Mutations happen independently, so if selection is going to purify them before they have a chance to proliferate in the segregating load, selection will indeed need to operate on them independently. Its inability to actually do this in most cases is the foundation of neutral theory.
I note here also that you are mistaken: my simulation does include epistasis (synergistic epistasis among deleterious alleles). I deliberately did not include antagonistic epistasis among beneficials in order to be charitable to the theory of evolution and give it at least a fighting chance.
The genetic load is a measure of the relative fitness difference between a population with no mutations and one with mutations. For example, a load of 50% means that the loaded population has 50% the number of offspring as a hypothetical population with no mutations. (Ask yourself: how many is that, exactly?)
This seems to be a strained use of the term “relative”, but in any case I won’t quibble. The point is that we are comparing the state of having mutations to the state of not having mutations. That makes plenty of conceptual sense, and it is indeed how these simulations (including yours) works.
Notice the use of the words universal, specifically, and his emphasis on the word never. Furthermore, note that the first quote is the only time Sanford gives a definition of GE in the book. When you define a concept, it should be exact.
The term “universal” that Sanford used in that quote was describing “entropy”, not “genetic entropy”. Sanford was careful to explain that GE happens as a result of mutations, which are an outworking of the universal law of entropy. And he’s correct here. Mutations happen in all lifeforms, not just LMEs. But the question of whether they accumulate to cause eventual extinction is dependent upon the parameters of that particular lifeform. That’s why Sanford was careful to clarify the difference between LMEs and microbial lifeforms with respect to GE.
Hence, unselectable literally means “not selectable,” which implies a total lack of selection.
What word would you suggest we use instead?
Consider the case in which Ns = 0.5 (beneficial, near neutral) and Ns = -0.5 (deleterious, near neutral). The former is 7.38 times more likely to fix than the latter, and 2.31 times more likely to fix than a strictly neutral mutation. This seems nothing like “unselectable”, in any sense of the word.
This seems like mathematical obfuscation. Perhaps it would be helpful for you to come out and openly state your view on this crucial topic. Is there, or is there not, such a thing as a class of mutations whose ultimate fates are determined by drift rather than selection? Do effectively neutral mutations exist at all? If so, how are they different from “regular” mutations, or what I would normally call “selectable” mutations?
If we imagine a mutation-free superhuman, how many children would they have on average? Maybe they’d have 50 children! But a typical loaded human, with only 11% their fitness, can have a max of 5.5.
That’s not an accurate representation of how the code works in SLiM, or of the mutation load model more generally. It’s not as if mutation-free individuals are assumed to produce massive numbers of offspring. In my simulation, there are discrete generations. The parents are killed after reproducing, and each set of parents has 8 offspring in my model. This represents the realistic human dynamics that reproductive cohorts are generally discrete in humans. We generally reproduce with people near our own age, and certainly not with our own children.
What you seem to be forgetting is that fitness is not just about reproduction, it’s also about probability of survival. In my code, there is culling that happens before reproduction for individuals with low fitness values. They didn’t survive to reproduce (or they were insufficiently fit to find a partner, etc.). This is another point that I can show directly from the literature:
“Although biologists have offered a staggering number of definitions of fitness, they agree broadly on the essence of the idea. In the crudest terms, fitness involves the ability of organisms — or, more rarely, of populations or species — to survive and reproduce in the environment in which they find themselves.”
Pretending that fitness is only about number of offspring, and not about survival, is not realistic.
It does not, it’s a mathematical certainty given our genome size. For such an individual to exist at equilibrium – which is what the stochastic load is measuring, to be clear – would require population sizes so large as to ensure that an individual could be born without any mutations.
I cannot figure out what you’re talking about here. Mutation rates exist because all individuals are born with mutations. That is a fact that is always true regardless of population size. The only way an individual could be born without any mutations is if that individual was the first individual of the species. To be clear, this is exactly how both of our SLiM models work. All individuals are born with mutations, the question is, will the mutation be on the road to fixation, or loss?
Consider a mutation that kills you as a zygote with a probability of 0.0001. … These mutations can still be inferred in the DFE because they will be slightly less represented in adults relative to their rate of occurrence.
This is a fair enough point, but I am not sure how it’s relevant to either of our models, since our models don’t try to measure the quantity of resources directly. It’s just an even deeper level of complexity that we don’t need to see the big picture of what is going on.
You did not model soft selection in SLiM – you modelled hard selection. Both our simulations are irrelevant to soft selection. This is because each mutation had an effect on fitness irrespective of any other member of the population (i.e., density-independent). Ecological theory (e.g., Haldane (1956); Wallace (1975)) can’t just be thrown out. As any ecologist will tell you, most selection is density-dependent, driven by competition for space, resources, and mates.
I’m not sure why you’re saying this. You should know that both of our simulations had density-dependent fitness scaling relative to a set carrying capacity. The whole point of that is to account for competition for limited resources. We both included that in our simulations.
As I explained, when selection is soft, the load is greatly reduced because it is drive solely by fitness variance, which is small in natural populations.
This is Charlesworth’s sleight of hand. Fitness is not merely about the number of offspring. It is also about probability of survival. Reducing the genetic load down to variance in number of offpsring is simply not correct.
This is where it becomes necessary to remind the audience, as well as Dr. Hancock, that mutational effects are they way they are for an underlying reason. The reason is that they destroy functional complexity. Even when mutations do not immediately affect the number of offspring, they do affect probability of survival (even if only by a small amount) by destroying the information content of the genome.
“The entire agricultural enterprise is built on the fact that “traits” are selectable.”
Within an agricultural context, what is being selected, and by what or whom?
The answer is that traits useful to humans are being artificially selected by intelligent actors. This is not natural selection, and you cannot equivocate between “trait” and “allele” as you are doing here.
Traits are subjectively decided to exist by people. Alleles exist objectively.
“The point of quantitative genetics is that mutational fitness effects are contextual.”
That’s true, but equivocation is a danger here, too. What do you mean by “context”? Do you mean genomic context? Then yes, you’re correct. Do you mean environmental context? Then no. Most fitness effects in LMEs especially are going to be acting on life processes and biological functions that aren’t environmentally dependent. A human being needs a heartbeat and respiration regardless of environment.
“As Hledick et al. (2022) demonstrate, stabilizing selection on a great many alleles of extremely small effects maintained information with greater efficiency than strong selection. If you think this is incorrect, you need to demonstrate: 1) traits are not as polygenic as we think; 2) mutational effects are independent of genomic context; and 3) mutations have larger effects than we think they do.”
They state:
Our findings are complementary to the point raised by Kondrashov (41), that the survival of populations could be threatened by large numbers of weakly deleterious mutations (Ns < 1). While selection cannot purge them, it can perturb the allele frequency distribution of each by a small amount, and thus shift the distribution of higher-level traits very far from neutrality. This is similar to the resolution by Charlesworth (55).
Emphasis mine. They are admitting that selection cannot purge near neutral mutations (that’s exactly what you need it to be able to do). You got around this in your simulation by simply taking near neutrals out of the picture, but that’s not realistic.
What they are saying is that the sum of many small mutations can ultimately result in very large and damaging changes in phenotype. That’s not a resolution to Kondrashov’s paradox, it’s a restatement of it!
They do appear to be offering this as a resolution to the paradox, but it’s not at all clear how it is supposed to actually work as a resolution. They have admitted selection cannot purge the weakly deleterious mutations. That means they will accumulate through drift.
Like Charlesworth, they are changing the subject away from the actual problem, which is the accumulation of VSDMs. Now they want to talk about higher-level traits (which is a subjective concept). But what they are not really addressing is that large gulf of mutational accumulation that exists between “Higher Level Trait A” and “Higher Level Trait B”. It’s not as if each VSDM is going to suddenly create a selectable phenotypic effect. They cannot be purged!
“But when traits are controlled by a very large number of genes, the underlying assumptions of classic population genetics fails.”
No, I don’t think so. But at least now you are admitting that you are rejecting “classic population genetics”. When traits are controlled by a very large number of genes, it reinforces the fact that individual mutations will have very slight effects when considered individually. And in order to purge them, you need to be able to consider them individually, as they happen.
“Joanna would say the same thing, as noted in Matheson et al. (2025), which offers one such resolution.”
What Dr. Masel demonstrably does say is that we still don’t have an answer to Kondrashov’s Paradox, and that it is still not known how populations persist under a load. I have already commented on how the Matheson et al. paper does not actually simulate mutation load or fitness decline, and does not seem to be even attempting to do so. The parameters they used were not realistic to actual human parameters.
“Paul is flustered that there are so many possible responses to Kondrashov’s paradox, but the fact is that there simply a multitude of possible resolutions. I listed a few in the OP, Joanna has others, and Kondrashov himself has his own (he suggests synergistic epistasis).”
Actually, I modeled synergistic epistasis and showed that it actually speeds up fitness decline. This was presented in the debate.
“The lingering question is which is correct – that is, which of these resolves the paradox? Likely it is a mix. It is “unresolved” insofar as we don’t yet know which of the many resolutions is actually the solution. This is an empirical question, and empirical work always lags behind theory.”
Be honest – are you getting lessons in doublespeak from Richard Dawkins? This reminds me of his famous quote, “Evolution has been observed. It’s just that it hasn’t been observed while it’s happening.”**
**
You’re seemingly saying, “We know Kondrashov’s paradox is resolved, we just don’t know what the resolution actually is.”
“Under the infinitesimal model, Fisher’s geometric model of adaptation works beautifully.”
That might be, I’m not sure. But in the real world, FGM works very poorly, and the reason is that it was concocted in a time before we had any solid understanding of how genetics actually works.
“Fisher’s model did not accurately reproduce empirical landscapes in six of nine biological systems tested …This leads to rejection of Fisher’s model even with data sets of modest size.”
Blanquart, F., & Bataillon, T. (2016). Epistasis and the structure of fitness landscapes: Are experimental fitness landscapes compatible with Fisher’s geometric model? Genetics, 203(2), 847–862. https://doi.org/10.1534/genetics.115.182691
I suppose this is good company to be in. Brian Charlesworth is perhaps the most famous living population geneticist (Joe, who I know is on this forum, is definitely in the running) with over 74,000 citations. His doctoral advisor was John Maynard Smith, who was the student of Haldane himself. Seems like it’d be worth it to read his work a little more carefully.
I don’t know if I’m mutated or what, but this attempt at an implicit argument from authority had no effect on me.
The argument I presented during the debate is what I consider the strongest argument against GE – that is, that most complex traits are highly polygenic, and thus selection is exceptionally effective despite being weak on each individual allele (e.g., Barton 2022). I chose this argument because it is much broader than Hancock & Cardinale (2024), is not restricted to a response to a single paper (Basener & Sanford 2018), and does not suffer from modelling assumptions (which we extensively discuss in the paper!). Furthermore, the infinitesimal predicts real, biological data, and has immense practical importance in agriculture.
It’s odd that you think an equivocation between artificial selection and natural selection could somehow be the strongest refutation of GE. Even wierder that you didn’t think to defend your paper in a debate about mutational effects, in a background context where you had been challenging creationists for years to rebut your paper!
When you are in the affirmative, you build a case – the negative deconstructs your case. Paul spent a great deal of his affirmative deconstructing things I had not said during the debate.
This is a half-truth. It’s true I did deconstruct your paper during my initial presentation, but that’s not the first thing I did. The first thing I did was to build a case, just as you have suggested. I explained the background of GE in the literature, and I explained why and how it happens. I then built what is, to my limited knowledge at least, the most accurate forward-time simulation on mutation load in humans that has ever been put out. If you can point to a better one, I’d be happy to see it.
I certainly don’t agree that your previously-published work on the question of genetic entropy should be off-limits in a debate about genetic entropy.
I’m going to skip commenting on your drama re: Matheson and his son. Anything I say will probably just result in a moderator strike, so I’m not commenting any further.
And we have documented such cases of ‘rescue / suppressor / compensatory mutations’ which establishes a genetic background where otherwise lethal mutations are rendered less harmful or virtually harmless.
Abstract: Here, we measure the fitness effects of ~ 1,100 temperature‐sensitive alleles of yeast essential genes in the context of variation from ten different natural genetic backgrounds and map the modifiers for 19 combinations. Altogether, fitness defects for 149 of the 580 tested genes (26%) could be suppressed by genetic variation in at least one yeast strain. Suppression was generally driven by gain‐of‐function of a single, strong modifier gene, and involved both genes encoding complex or pathway partners suppressing specific temperature‐sensitive alleles, as well as general modifiers altering the effect of many alleles. The emerging frequency of suppression and range of possible mechanisms suggest that a substantial fraction of monogenic diseases could be managed by modulating other gene products.
That last sentence reminds me of a landmark study that surveyed 589,306 individuals and identified 13 otherwise healthy adults who carry known genotypes (homozygous recessive or heterozygous dominant) for 8 “severe Mendelian childhood disorders”… the authors use the term ‘Mendelian disorders’, but that is ironic since their results show that these disorders are not Mendelian (monogenic).
Also a relevant paragraph from this excellent review paper:
Many genes, when mutated, actually do cause a phenotype. Unless the mutation is lethal, one can keep growing the strains carrying the mutation. Would such strains eventually recover from the loss of the gene and become healthy again? Several groups have now systematically explored this question with stunning results. In yeast, about two-thirds of 180 genotypes with measurable knockout phenotypes reached near wild-type fitness through accumulation of adaptive mutations elsewhere in the genome (Szamecz et al. 2014). Another study in yeast found that losing highly connected genes increased the evolutionary potential by facilitating the emergence of a more diverse array of phenotypes, some even fitter than the original cells (Helsen et al. 2020), and even new cellular morphologies and growth characteristics can evolve in yeast cells as a by-product of such compensatory evolution (Farkas et al. 2022). In E. coli, the effects of mutations in fundamental metabolic genes can be rescued in laboratory evolution experiments, resulting in the rewiring of existing hardwired networks (McCloskey et al. 2018). A similar phenomenon—called “transcriptional adaptation,” becomes increasingly evident in the context of knockout experiments in medically motivated studies, blurring the concepts of clear genotype–phenotype relationships (Jakutis and Stainier 2021). While second-site suppressor screens have been highly successful in model organisms like Drosophila, it is generally also possible to modify phenotypes simply by backcrossing mutations into different wild-type backgrounds (Gibson and Dworkin 2004).
I can’t cosign the post to which I am responding (Zach’s long response to Paul) hard enough. I had another comment in the moderation queue but anything else I might say is extraneous. This whole topic is the opposite of a scientific debate or disagreement; it’s a bunch of people who understand the relevant science trying over and over to explain it to someone who has an active interest in misunderstanding it, nothing more.
Secondly, you’ve switched from points he made to points you made.
Thirdly, since the debate was approx a couple of hours long, unless you sat there and listened there is no possibility whatsoever that those are the only three points you made.
So it’s not even necessary to examine the specific points covered before rejecting this as deceptive garbage.
There’s no such thing as “the first individual” of ANY species. Like most creationists, at best you haven’t bothered to learn how evolution works before wildly attacking.
You appear to be ignoring existing polymorphism. Does the term “incomplete lineage sorting” mean anything to you?
Have you ever used the terms “allele” or “polymorphism” in an original sentence?
Since you’re talking about “how evolution works”, can you explain Hancock’s statement about population sizes being sufficiently large to allow individuals to be born without mutations?
I’ll leave it to those smarter than I to figure out how any new species could ever come into being without there being a first.
Obviously in evolution you’ve got a segregating load at all times, but that’s exactly the problem. You’ve got no mechanism to explain how you prevent that load from causing unending fitness decline through Ohta’s Ratchet.
That has nothing to do with your claim that first of species exists. It’s certain that some individuals will be born without any new germline mutations in large populations. It’s painfully and simply obvious from probability.
It’s a basic understanding that you lack.
Yet polymorphism exists, is now routinely measured, and differs dramatically between populations of humans. How do you explain that?
“Smarter” might not be the right word. More knowledgeable, more accustomed to learning, less blinkered by dogma, perhaps.
There isn’t a first individual of a species because evolution happens to populations, as alleles spread through them. Speciation is gradual. There is no single moment when a population stops belonging to one species and starts belonging to another.
There are exceptions, e.g. allopolyploid speciation, which can happen in one individual plant.
Can you explain why that would be certain? The reason there is a mutation rate is that replication is never 100% perfect. LMEs in particular have much higher mutation rates compared to things like bacteria.
I would say that is less of a claim and more of a logical necessity.
I don’t know what you’re asking me to explain exactly. Historically, there’s a lot that is different between different people groups. Patriarchal drive refers to how older men produce offspring with more mutations, so if a particular subgroup had a lot of older men reproducing, that could explain higher levels of mutations. Also a history of being much more geographically isolated with a smaller effective population size, etc. There are many reasons why the mutation load would not be perfectly homogenous across isolated groups. It’s certainly not because selection is removing all of it.
Logically, there would have to be, since evolution happens in time, which is a string of moments. So either no species ever come into being, or they do and there is a moment when it happens.
You seem to be conflating the existence of an event with our ability to pinpoint that event ourselves. You’re also dancing around the problem that there really is no solid and universal definition of “species” to begin with, so of course we cannot say when one begins because we don’t even know what we’re talking about when we say it.
It’s shocking that you don’t understand this. There is no moment at which the first wolverine is born, just a gradual transformation of a population that’s not wolverines into one that is wolverines. There is no single wolverine allele that defines wolverine-ness. where you define the boundary is arbitrary, and if you set an arbitrary definition there will be a point at which wolverine-ness is polymorphic in the population. Where on the spectrum does green become blue? As someone else mentioned, when in history does Latin become French, and who did the first French speaker talk to? Similarly, what bird did the first mallard mate with? Did a mallard lay the first mallard egg, or was the bird that laid it not a mallard? What is a species, come to that, and how do you tell which species an organism belongs to?
The most common mutations, transitions, are most commonly caused by keto-enol tautomerization of the substrate. They are in no way errors. If you believe that God directly designed life, God designed the reason for the vast majority of mutations. Therefore, the concept of perfection is irrelevant.
That’s precisely my point. Polymorphism, an important concept that you don’t understand. Your focus on mutation blinds you to it. Ironically, polymorphism, not mutation, is what Darwin observed.
You obviously don’t understand. My challenge to you to explain polymorphism has absolutely nothing to do with mutations, unless you’re trying to claim that wildly different mutation rates are responsible. Are you?
That’s absurd. One can see its absurdity by applying it to language. Languages evolve over time, which is a string of moments. So either no languages ever come into being, or they do and there is a moment when it happens.
So, Paul, when was the moment that a person first spoke French?
So, two things you obviously don’t understand.
Evolution only happens to populations, never individuals.
Most drift and selection acts upon existing polymorphisms, which outnumber the new mutations you’re so obsessed with by ??? to one.
I suggest that you learn what that ratio is for humans before pontificating any more. It is an objective, empirical fact.
Using a mutation rate of 1e-8, a genome size of 6e9 and a population of 7e9, the probability of there being an individual with no germline mutations is:
1-((1-((1-(1e-8))^6e9))^7e9)
which (if I’ve successfully negotiated my calculator’s reluctance to handle such small numbers) is 6e-17, or 1 chance in 16 quadrillion {US}.
If a population is large enough, some individuals will be born without any mutations… relative… to… their… AN-CES-TOR! Not relative to any supposed “first individual” of any species.
When water freezes, there is no individual water molecule that is the first in a solid state. In fact, one cannot speak of an individual water molecule being in a solid, liquid or a gaseous state since phases are properties of aggregates and phase transition happens on the aggregate level.
What if we are dealing with evolution across a spatial dimension, such as ring species where population A and B are the same species, and population B and C are also the same species, but C and A are not. That tells us that there is no discrete spatial coordinate where one species becomes another, but the transition still occurs nevertheless. The same applies to the temporal dimension. There is no temporal coordinate when one species becomes the next. There could be a few exceptions of sudden transitions, such as the case of speciation via whole genome duplication, but it is not necessary.
