A very nice post by Barry at UD struck me as worth reposting here (as I can’t post there), inspired by Neil Rickert:
Phinehas asks Neil Rickert a fascinating question about the supposed direction of evolution. Neil says he will address it in a separate thread, and I started this one for that purpose. The rest of the post is Phenehas’ question to Neil:
@Neil I also appreciate the professional tone. I am a skeptic regarding what evolution can actually accomplish. In keeping with your demonstrated patience, I’d be grateful if you would give serious consideration to something that keeps tripping me up. I’ve often thought of natural selection as the heuristic to random mutations’ exhaustive search.
A path-finding algorithm can be aided in finding a path from point A to point B by using distance to B as a heuristic to narrow the search space. Without a heuristic, you are left to blind chance. It is said that evolution has no purpose or goal, so there is no point B. It is also claimed that evolution isn’t simply the result of blind chance, so a heuristic would seem to be required. Somehow, natural selection is supposed to address both of these concerns. Nature selects for fitness, we are told, so somehow we have a heuristic even without a point B.
But what is fitness? How does it work as a heuristic? How is it defined? Evidently, it is all about reproductive success. But how does one measure reproductive success? This is where things get fuzzy for me. Surely evolution is a story about the rise of more and more complex organisms. Isn’t this how the tree of life is laid out? Surely it is the complexity of highly developed organisms that evolution seeks to explain. Surely Mt. Improbable has man near its peak and bacteria near its base. But by what metric is man more successful at reproducing than bacteria? If I am a sponge somewhere between the two extremes, how is a step toward bacteria any less of a point B for me than a step toward man? Why should the fitness heuristic prefer a step upward in complexity toward man in any way whatsoever over a step downward in complexity toward bacteria?
It seems that, under the more obvious metrics for calculating reproductive success, bacteria are hard to beat. Even more, a rise in complexity, if anything, would appear to lead to less reproductive success and not more. So how can natural selection be any sort of heuristic for helping us climb Mt Improbable’s complexity when every simpler organism at the base of the mountain is at least as fit in passing on its genes as the more complex organisms near it’s peak? And without this heuristic, how are we not back to a blind, exhaustive search?
Excellent questions.
Evolution cannot “see” point B and therefore cannot search for it. Evolution is not a search.
Evolution can only see that allele A results in more offspring (higher rate of reproduction) than allele a.
Bacteria are and always have been more successful than multi-celled organisms. So the assumption that fecundity allows better and faster adaptation is true.
Evolution does successfully argue that living things are related by descent, and it successfully argues that it could have produced the observed diversity in the alloted time.
As a lawyer Barry should be familiar with the concept of means, motive and opportunity. Incremental change is the means, differential reproduction is the motive and deep time is the opportunity.
I presume Barry is aware that attempting to attribute a crime to an unseen, unmotivated magical agent would not work in a courtroom. Barry would assign the creation of malaria to a deity, but I think he would hesitate to assign a murder to god or spirits.
Too good not to steal from AtBC. (HenryJ)
The questions were addressed to Neil, but I can’t resist having a go.
Well, it’s probably worth pointing out that mutations are not an exhaustive search, or at least not in the sense that pulling out random independent strings of nucleotides would be. Mutated genomes are highly constrained by what preceded them, so that even in the absence of selection, a highly constrained part of “solution space” will be searched. What “natural selection” “adds” is the tendency to gravitate towards the parts of “solution space” that actually contain solutions.
Not exactly. Or rather, path-finding algorithms can indeed find paths from A to B using various heuristics (including those that use distance to B), but those aren’t really relevant to evolution. A better analogy than the search for a path between two a priori points would be a heuristic that searches for summits in a landscape. One simple heuristic might be: on your next step, choose the direction that drops the least/rises the most. It’ll leave you stuck on little hillocks a lot of the time, but it will find summits, and if you have enough searchers, a few of them will find some substantial hilltops, and maybe the odd mountain summit.
I think people who say this are a bit misleading (not deliberately). I think there’s accidental equivocationg between “goal” or “purpose” as in something that someone has in advance of setting out, and “goal” or “purpose” as in an “attractor”. A stone has no goal when it rolls downhill; but it is strongly constrained to roll down rather than up. Evolution has a strong tendency to maximise reproductive success. Whether you call this a “goal” or not depends on your point of view, but it is no more (or less) “blind” than the rolling stone, which may have no clue where it is going, but nonetheless is massively more likely to roll down than up.
Yes.
Yes, and it does. It is goal-less, as the stone is goal-less, but it is not “blind chance”, as the fact that the stone rolls downhill, not up, is not “blind chance”. Although the fact that it may meet a boulder that stops it, is more like “chance”. That’s why we call it a “stochastic” process – probabilistically, populations tend evolve so as to maximise reproductive success in their current environment, just as stones tend to roll down hill. But both sometimes get stuck.
Ah. There’s the problem 🙂 No, Nature doesn’t “select for fitness”. “Selection” is simply the word we give to the phenomenon by which variants that tend to reproduce better in the current environment become more prevalent in that environment. The don’t always, because accidents happen – a colony of ants that are particularly fecund because they carry a novel mutation that makes them large enough to carry off larger lumps of sugar to feed their queen may nonetheless come to naught because I spray ant-killer on the lot. Or, if that seems too much like intelligent design, a meteor lands on the anthill. So it’s not quite a tautology – but it’s almost a syllogism:
P1 Some variants have advantageous traits that enable them to produce more offspring then their peers
P2 The offspring of those variants inherit those traits
C: Those traits will come to dominate the population.
The number of viable offspring you are likely to produce
See the syllogism above.
See above (there are mathematical formulations, but that’s the gist).
Yes.
By counting the number of viable offspring. It’s usually done at population-level, and as a function of some trait, so there’s math involved, but, essentially, a fitness of 1 means that an organism bearing that trait will, on average, leave one offspring with that trait). A fitness of more than 1 for a trait means that the trait will, on average, be passed on to more than 1 offspring. Less than 1 means that it will, on average, be passed on to less than 1 offspring. It follows, then, that a trait with a fitness of more than 1 will tend to become more prevalent in the population and one with a fitness of less than 1, less prevalent.
Not really. It’s a story about the rise of fitter and fitter organisms. Sometimes fitter is more complex; sometimes fitter is less complex. But as there are more ways to go from simple to complex than there are from complex to simple, average complexity will tend to increase (a bit like entropy, oddly enough :))
Not really, although it is true that really simple organisms (the ones we postulate as ancestral to modern living things) no longer seem to exist (although who knows what we may yet discover), and it is also true that because evolutionary processes tend to “refine” solutions, that where a more complex solution is better, it will tend to evolve later. But certain simple solutions remain extremely viable – one-celled organisms may be “simpler” than multi-cellular organisms, but they remain extremely successful.
I’d say that it is the tree itself (an objective observation, as laid out by Linnaeus well-before anyone had actually considered that it might represent a family tree) that evolution seeks to explain. And the twigs of that true range from unicellular organisms and highly complex multi-cellular organisms capable even of asking the question as to where they came from! Evolutionary theory seeks to explain both change over time down a single lineage, and divergence between lineages, and does so quite well (although interestingly, although Darwin called his treatise “on the origin of species”, he didn’t really address speciation, just longitudinal evolution).
No. Mt Improbable is a mountain range with every single living population at a high point, with many peaks inhabited by extinct populations. Modern bacteria are themselves high on that range, and, alarmingly, traversing from peak to peak at almost naked-eye speed.
None. Man is less successful at reproducing than bacteria.
It isn’t. Sponges aren’t between the two extremes. You are conflating “complexity” with “fitness”. Sponges are extremely well fitted to their environment. We did not evolve from modern sponges; nor did we evolve from modern bacteria. We didn’t even evolve from ancient bacteria.
It doesn’t. That’s why bacteria are still alive and kicking ass. The “fitness heuristic” only “prefers” what maximises fitness in the current environment. If simple works, simple will do just fine. If more complex works, then more complex will do fine. If more complex is a problem, then simpler may be possible (for instance, leglessness, or eyelessness, may be fitter than legs/eyes, under some environmental constraints).
Indeed. And so multicellularity must have had a specific advantage in a specific environment. I think the confusion here (not helped by biology text books often) is between evolution within a population, and speciation. Speciation happens when a sub-population starts to evolve independently of the main population, and can therefore take advantage of an new ecological niche – can find that on this island, longer legs work better; or in this part of the lagoon, ankles come in handy.
Yes. But remember, a population only has to maintain its size – increasing size can actually lead to population collapse (this happens with bacteria too). Some species do have a sustainable boom-bust cycle, but more often, co-existing organisms within an ecosystem reach equilbrium, with all species essentially maintaining population size, at least in the medium term. And there are various ways that two parents can average two children – from producing millions of which, on average, only two survive, or from producing only two that have a high chance of surviving to breed themselves. Not surprisingly, top predators (sharks, bears, us) tend to have small litters, while those at the bottom of the food chain have large litters.
Well, I hope I have answered your questions 🙂 To summarise:
Bravo, excellent summary. Let me add a couple of points:
1. The surface of Mount Improbable is not fixed — it changes through time, mostly slowly but sometimes not. It is also a surface in a high number of dimensions, perhaps 10,000 of them, which means that there may be many ways to go higher, even though most ways from the current location lead downwards. And evolution takes stochastic steps that are biased upwards, but sometimes go downwards. Furthermore it occurs in populations, not just individuals, so the movement is not just in the space of genotypes but in the space of distributions of genotypes. In that sense Richard Dawkins’s mountain is too simple an analogy, because it is a hill rising above a plain of genotypes, while an adaptive surface rises above a plain whose coordinates describe possible distributions.
2. Success of different populations are measured in success at survival and reproduction. But the successful growth of moss on rocks on a mountain does not mean that sea anemones in the ocean are outcompeted. It’s called ecology — for growth of one population to decrease the success of another they have to be in strong competition (we even call it “perfect competition”). And fundamentally, that’s why there are still monkeys.
They really are an excellent set of questions. I hope Phinehas will drop by if he has any more 🙂
I have two questions about the analogy with the falling rock. Gravity is the force that make the rock go dowhill, or better to the earth center of gravity, wich is the force that makes life evolve? Second for the rock or any other determined process we know there is an end, usually when I asked if it is possible that “evolution” got an end with horror they answered no impossible, evolution is still going on, do you think that evolution will end at some point?
Good question – I’m trying to think of the best answer to fit the gravity analogy. I think it would have to be: “reproductive competition”. If a population isn’t reproducing, it won’t go anywhere, and if it isn’t reproducing competitively (if all the variants are equally good/bad at reproducing) it’ll be as likely to go up hill as down (perhaps like a helium balloon that’s nearly lost all its helium, bobbing around on a bumpy plain).
Not while things keep reproducing. No reason for it to stop. If populations stop reproducing competitively there won’t be any net increase in fitness, but there will still be change over time (“drift” – as with the helium balloon again), and sometimes this happens to populations that hit maximum fitness within a specific niche (like the rock that hits a boulder on its way down hill). But as Joe Felsenstein says, the topography is always changing (to stick with the gravity analogy), so what was a boulder one day may be a flat place, or even a hollow after a while has elapsed. And in fact, the evolving population itself is part of the topography – as the population changes, so do the competitive stakes! What was enough to give an individual the edge in one generation, may be the minimum for survival a few generations down the line.
Lizzie,
Downhill is simply a metaphor for in the direction of an attractor.
The attractor metaphor is somewhat unfortunate for a number of reasons. For one thing. population do not have any sensory apparatus that allows them to determine a desired direction.
On the other hand, it has some usefulness, ans in explaining how water finds the bottom of a pond, complete with all its irregularities.
I tried to make a GA having multiple attractors. In fact the attractors include all the words found in a Scrabble dictionary.
http://itatsi.com
The interesting thing is that with multiple dimensions of selection, strings are formed that are not any of the attractors.
Assuming a conclusion is no way to begin a syllogism. ID seems to love sneaking in premises that can only be the subject of research. Upright Biped is the master of this.
Nonsense. Evolution is a search for alleles that leave the most offspring.
Phinehas says:
Dave says: Evolution’s “heuristic” is to make only tiny changes to the genome. For instance, suppose a yeast cell has a million base-pairs in its DNA and it’s doing all right. The DNA directs the yeast cell so that it eats, excretes, stays out of trouble and does all the other things a fully functional yeast cell does, including budding off an occasional daughter cell. If the budding works right, the daughter cell’s DNA will be identical to its mother’s DNA and the daughter cell should do just as well as its mother, at least as far as the DNA goes.
Because the offspring’s DNA is identical to the parent’s, both organisms exist at the same point on the fitness landscape.
Now, suppose there’s a copying error during budding and a single base-pair of the daughter’s DNA gets changed. Because the parent and daughter cells have different DNA, they occupy two different points on the fitness landscape.
Since the daughter’s DNA is different from her mother’s, evolution is now searching this second point of the fitness landscape.
However, 999,999 of the daughter’s base-pairs are identical to her mother’s. Only one base-pair differs. This makes the daughter’s DNA 99.9999% identical to the mother’s so they are very very close to each other on the fitness landscape.
Thus evolution can only search very nearby positions on the fitness landscape when only a very small percentage of the offspring’s DNA is changed.
See? Searching only nearby positions on the fitness landscape is automatic and no intelligence whatsoever is necessary. Just make SMALL changes to the DNA.
F/N KF likes to tell us that a 500 base-pair DNA string has 1000 bits of information in it, which means there are 2e+1000 or 1e+300 different possible configurations for that DNA. He then correctly informs us that it would take that organism billions of years to explore even a tiny fraction of those configurations using a blind search.
Have you ever wondered how an organism would blindly explore such an enormous fitness landscape? I think that if you think about it, you’ll realize that the only way to do a blind search of a fitness landscape is to randomly change every base pair in the genome on every reproduction event. Do you know of any organism that has ever existed that randomly changes every single base-pair in its DNA every time it tries to reproduce?
Why don’t you bring this up to KF sometime. Ask him for an example of such an organism. That should be good for at least twenty pages, 156 sub-headings, 23 footnotes and several “Onlookers…”
davemullenix, I tried to look at your comment but my eyes hurt — in it were complete posts by Lizzie and by me.
Please find a way to quote the parts of them that are important and leave the others out, so we can see what you say and what items in others’ comments you are commenting on. As is, your comment is unreadable.
Right now the interface is not easily available, but you can at least enclose others’ quotes in the comment box when you type, with the tags
<blockquote>
and
</blockquote>
and erase all the parts you don’t really need to quote.
No. Alleles don’t leave offspring; organisms do. Evolution simply stumbles around, either taking up residence on a point, or hitting nearby ones, in the space of viable configurations. When an allele helps its carriers leave more offspring than alternatives, it tends to become the dominant allele at its locus, but something becomes the dominant allele at a locus irrespective of fitness effects.
Life goes to great lengths to prevent evolution (because it starts with mutation, which is often a Bad Thing). But it is not capable of turning it off entirely. It is not really ‘searching’ for anything – it’s already found it: a viable genome. But it responds to the environment, where that rewards alleles differentially, which gives a sense of populations tracking shifting local optima.
Dave, I edited out what seemed to be an inadvertent c&p of the whole screen, and left what I assume you meant to post, to make it easier to read! Hope that was OK.
Me:
‘course, I don’t mean ‘dominant’ in opposition to ‘recessive’ …
Thanks for your answer Lizzie but I´m not sure to understand part of it. You said what moves the evolution rock is “reproductive competition” but exist also reproduction without competition that “moves evolution”: drift .
So what really moves evolution is reproductive change, competion or not will determine the speed and the direction.
So evolution is sometimes a rock (replicator) falling by gravity (replication errors) , sometimes free falling (change selected by competition) sometimes bouncing here or there waiting to find a free fall pass. (Drift).
Is it not possible that it’s all or some of those? My understanding is the fitness landscape can have thousands of dimensions, all of which contribute via the mechanisms you’ve noted to the overall landscape.
Hello fellow skeptics!
Lizzie said:
I think I get that, although I would be curious to know more about the numbers. For instance, what percentage of the time are postulated ancestral organism more complex than the organisms that follow on? How well does this percentage line up with the probabilities suggested by the proposed explanation that there are fewer paths toward simplicity?
But I think all of that may slightly miss the point of what I am asking. What is it exactly that puts the Improbable in Mt. Improbable? If we are merely talking about change, then what is so improbable about that? Or what is improbable about the survival of the fit enough? What is the gravity that must be struggled against that makes moving up the slope more difficult or unlikely? What is it that would lead us to even feel a need to explain this struggle by appealing to gradualism?
Phinehas,
Phinehas,
I’m glad to see you here. Lizzie’s response to your question at UD was a lucid explanation of some important core concepts. It’s great that you’ve joined us to discuss it further.
You ask “What is it exactly that puts the Improbable in Mt. Improbable?” Dawkins uses the metaphor to explain how complexity can be arrived at via tiny, gradual changes. What is improbable, to some, is that a particular organism could be the result of natural processes. The comparison that Dawkins uses is that of looking at a cliff face. Getting to the top seems quite improbable until one realizes that there is a gentle path up the other side of the mountain.
I highly recommend the book. It will answer many of your questions.
Again, welcome!
Phinehas,
:
Gould wrote an entire book on this question. “Full House”
His answer is that increasing complexity occurs almost, but not quite, never.
The norm is stasis. How often does simplification occur? good question, but it appears to happen.
The book “Climbing Mount Improbable” is actually a good read. Have you read it? I suspect it would help clarify this question.
Here’s my 2c. Gradualism is “appealed to” as it’s not possible for evolution to do anything except explore what is right next door already. So all (almost) change is gradual. The mountain is climbed one step at a time.
It’s is of course more complex then this (hopeful monsters etc) but you get the idea.
ID on the other hand should be able to show “nothing” then “something” with no precursors to that “something”. That is in fact not what we see.
OMagain,
The first 80 years after Darwin was pretty much devoted to the question of hopeful monsters and saltation. Since the discovery of DNA, much attention has been paid to the question of whether the observed differences in related organisms can be accounted for by the time available since divergence.
@Patrick
Indeed. This is exactly how I read the analogy as well. It is from this perspective that I said:
Does that make more sense?
In other words, it seems to me that gradualism + natural selection is evolution’s answer to the improbability inherent in climbing upward toward complexity.
Is this right? Or does natural selection really play no role in overcoming this improbability?
Evolution is not “a story about the rise of more and more complex organisms.” If it’s “about” anything, it’s about high-but-not-perfect fidelity of replication of heritable traits leading to differential reproductive success.
I suppose you could say that some evolutionary biologists are working on discovering how “the complexity of highly developed organisms” arose, but that’s not the essence of evolutionary theory.
Do those clarifications make sense? If so, what questions do you still have?
Phinehas,
There’s a couple of dozen pages of CMI here: http://www.amazon.co.uk/Climbing-Mount-Improbable-Richard-Dawkins/dp/0141026170
which might be of interest.
Phinehas,
The “climb” is a label applied by humans.
If you look at the see from a distance it appears flat. If you get up close you see waves.
Are the peaks of the waves “climbing”?
Suppose one peak splashes onto the top of a rock. Has the water climbed to the top of the rock?
OMagain said:
Interestingly enough, this is also exactly how path finding algorithms explore a problem space: Every neighbor node is tested for a solution, branching ever outward. For some algorithms, nothing is known about the destination, so it must be “discovered” through an exhaustive search of all the possibilities. (Of course, even these path finding algorithms can keep track of nodes they’ve already visited to help shorten the search.)
Phinehas,
The important thing to keep in mind is that only a small fraction of the total solution space is/can be explored. In addition accidents of history may prevent productive paths being followed.
This renders somewhat meaningless KF’s calculation of all possible states and the fact that it would take many times longer then the universe to find a particular state by randomly exploring. Nobody disagrees with that.
As not all states are explored, the probability of finding yourself in the current state is much reduced (I’m not explaining this well)
KF does not want you realize that however, his “needle in a haystack the size of the cosmos” is pure misdirection.
@Patrick
I apologize for the confusion. It may not be the essence of evolutionary theory, but it is certainly the essence of my skepticism and would appear the be the essence of what Dawkins’ saw as enough of an (apparent) obstacle to justify the titular Mt. Improbable. (You’ll forgive me if I assumed that the skeptical zone would be interested in discussing the parts of evolutionary theory that engender skepticism more so than the less controversial parts that form its essence. 🙂 ) As you pointed out:
As to questions or clarification, I really would like to understand this better:
Hello Phinehas, and welcome to TSZ!
I’ve given you posting rights, so feel free to start your own thread if you wish. But in the mean time, this is probably a good one to discuss your really excellent questions.
Well, to answer that question, we’d need an operational definition of “complex”, in other words a definition that gives us a quantity that can be objectively measured, yet captures what you mean by “complex”. For example, a snake is in some senses less “complex” than a lizard, in that it has no legs, whereas a lizard has four, but genetically, it almost certainly has genes for four plus a configuration of regulatory genes that prevent those genes from being expressed during development. So phenotypically it is less complex, but genotypically, more complex. Maybe. This is why I said that complexity was a bit like entropy, in the context of evolution. If “complexity” is defined to mean something like “the number biochemical signalling events that occur between conception and adulthood” then that will tend to increase rather than diminish, for the same reason as a Word document in which you are Tracking Changes tends to get larger and larger on file even when what you are doing trying to shorten it. Once something is in, it tends to take additional information to leave it ou! Which I guess is another way of saying that if it is better for snakes to have smaller, or no, legs, then changes that to genes that affect the rate of growth of legs during development will tend to be more readily modified than genes that make legs are to be deleted in toto (especially as those same genes are probably involved in all kinds of other stuff as well) .
Nothing! And that’s really the point of Dawkins metaphor – although it may seem improbable that a person could walk to the top of a vast mountain, step by step, she can get there (well, with some help from her friends). Similarly, although a fully functioning human being may seem an extraordinarily “improbably” pattern of matter to have resulted spontaneously from physics and chemistry, if we consider the process step by step from the simplest possible self-replicator onwards, then it turns out not to be so improbable after all. Or, rather, something as complex as a human being turns out not to be so improbable – but human beings specifically are almost vanishingly improbable, just as any given sequence of 52 cards is almost vanishingly improbable, although the probability of getting at least one of those vastly improbably sequences when you spread them is near 1 (well, there are always meteorites or earthquakes, or even small children, who could get in the way…)
I’ve always thought it counterintuitive to think of evolution as a “climb”. It’s only a “climb” if we plot fitness as positive. If we reverse the axis, and plot fitness as “lack of fitness”, then fitness is the depths of the valleys, and the first self-replicators were on the highest summit. The only “gravity” is competitive reproduction, and that is pulling populations towards maximal fitness. Not much stops populations descending to the valleys, although some get stuck in lakes and combs.
You’re welcome, Blas, and welcome to TSZ. I’ll give you author rights as well, in case you want to post an OP.
Yes, more or less. That’s been one of the big changes since Darwin’s day – the realise that a lot of change is simply drift – and indeed that “natural selection” serves to keep things at optimum – constrain change – if the nearby states are less good than the status quo. That’s why certain species, especially top predators, have stayed so similar for so long (sharks, crocodiles, for instance).
Hi Lizzie! Thanks for the welcome and the response.
If I could, I’d like to zero in on the part that, again, is engendering skepticism.
I’m just not understanding how the improbability of going from LUCA to Homo sapiens is lessened by a step by step process unless that step by step process has some sort of directionality to guide it or help it along.
I’m not an expert on probabilities by any means, but my intuition (which could totally be wrong!) is telling me that the odds of getting a hundred with a 0-100 random number generator would not improve significantly by introducing a scheme where you start at zero and roll a 0-3 rng where a three bumps you toward 100, a two leaves you where you are, and a zero drops you back toward zero.
Phinehas,
There is no target. There is no directional towards humans.
What if instead of Homo sapiens we were descended from Dinosaurs, we’d still be having this exact same conversation.
Throw in this…
…and the situation becomes worse, since I might have to modify my 0-3 rng such that increasing complexity has much less than a 33% chance of occurring.
Please create a model that performs as you describe, then link it to some observed biological process. Otherwise I’m afraid I’ve no idea what you are talking about!
You keep thinking about rolling a dice and getting some improbable result. Rather you roll the dice and get some result, of which some will be more improbable then others. But there is always a result, even if it is “death”.
You can calculate the odds of winning the lottery, they are very high odds. But someone always wins.
@OMagain
I understand there is no target. But surely complexity is an issue that begs an explanation for the skeptically inclined. Why else would Lizzie try to explain it with…
Why else would Dawkins try to explain it with Mt. Improbable?
Somehow, evolution got from LUCA’s complexity to the complexity of Homo sapiens. That seems improbable to me, and I dare say to other skeptics as well. I am merely trying to express that improbability by imagining LUCA with near zero complexity and Homo sapiens with near 100 complexity. It seemed to this skeptical layman that natural selection was an idea intended to address the improbability, and I’m just trying to figure out how that works exactly.
Phinehas,
It is improbable. It’s very improbable. Likewise, the chance of any given atom being exactly where it is right now is also improbable.
Yet all atoms are somewhere, despite that improbability.
I’ll ask again, have you actually read Dawkin’s book CMI? If not, perhaps you should! I’m not saying that to end this conversation, no doubt somebody better equipped to answer your questions will be along shortly, but given that what you are trying to understand is what the book is about….
Absolutely correct. “Fitness”, mathematically, at least in population, is applied to the a subset of a population that bear a particular trait. And, yes, it’s relative. A trait that renders an individual more likely to bear viable offspring than her peers may be one that is out-competed by other traits in the next generation-but-three. And yes, it is measured after-the-fact. But that isn’t any kind of problem for it as a concept. It’s just that it’s a statistical concept, not one that one can apply to an individual. We can say that people with a set of alleles that tend to result in earlier peak fertility are likely to have fewer children in an era of family planning than those whose genes tend to result in later peak fertility, but there will be plenty of women (like me) who peak early, yet manage to produce a baby on her last eg, and women who peak late, but choose not to have children at anyway.
Nonetheless, alleles that tend to promote a later fertility window are likely to become more prevalent in the human population, and there is <a href=http://www.time.com/time/health/article/0,8599,1931757,00.html>at least some evidence</a> that this is happening already. We are evolving right now!
OMagain:
Well, it is entirely possible that I have no idea what I’m talking about either! So I don’t hold that against you. I’m just trying to muddle through my own skepticism to the best of my ability.
Lizzie made this positive statement:
That just doesn’t seem right to me. Unless the random walk is given some sort of directional help (from natural selection?), I don’t think it is any more likely to get from LUCA to a fully functioning human with many small steps (in a random direction) than it is to get there with one giant leap. I’m trying to come up with a thought experiment that would break the issue down in a way that was a bit more manageable and understandable. If what I proposed isn’t coherent in that regard, I’m certainly open to other suggestions.
Phinehas,
On gradualism, it’s important to note that not all changes are point mutations that only affect a single base pair. Chromosome mutations, wherein whole sections of genes can be moved, duplicated, deleted or inverted, affect the number and position of dozens if not thousands of base pairs in one generation.
On a related note, a recent paper in the journal Science documented lab-grown Salmonella enterica gaining a new functional gene, by way of duplicating, amplifying and then mutating a parental gene’s weak secondary function, over the course of 3000 generations.
Hmmm. You seem to be assuming one RNG here (i.e., no reproduction, no processes running in parallel), and you also seem to be overlooking the effect of selection. Granted, ignoring selection isn’t really a problem in the absence of reproduction—but if your scenario doesn’t incorporate reproduction, it’s missing out on a fairly significant feature of living critters, hence its applicability to biological phemomena is likely to be low, if not nonexistent. So let me take your “0-3 RNG” scenario, and add some features to it which should make it more applicable to biological phemonena.
Reproduction: Let’s say your RNG makes copies of itself.
Heredity: Let’s say that each daughter-RNG starts out with whatever numerical figure its parent had (and the original RNG started out with a numerical figure of zero).
Modification: Let’s say that the RNG’s result, whether that result be 0, 1, 2, or 3, adds onto the numerical figure it inherited from its parent. Your scenario specifies that a result of 0 “adds” a negative number onto the RNG’s inherited numerical figure, but that’s okay; we all know that some mutations are harmful, right?
Selection: Let’s say that whatever ‘environment’ these RNGs exist in, that environment ‘rewards’ RNGs with higher numerical figures in some way—maybe by letting higher-numerical-figure RNGs ‘live’ longer than lower-numerical-figure RNGs.
Given those additions to your baseline RNG scenario, what does your intuition say about the likelihood of some RNGs achieving a numerical figure of 100?
I can’t have been clear, sorry. Yes, in order to get a steady climb/descent towards fitness there needs to be natural selection – which is another way of saying that to get increased fitness, there needs to be variation in heritable reproductive success. Without that, you won’t get any steady progress towards increased fitness.
But as long as occasional novelties of a kind that affect reproductive succes are introduced during reproduction, so that offspring differ from their parents in ways that affect their chances of successful reproduction themselves, in the current environment, then evolutionary change will tend to have a direction.
Phinehas,
To use the RNG analogy, suppose the positive “bump” moves n 3 positions closer to 100. A duplication of that process would results in n moving 6 (3×2) positions at once. And if the duplication resulted in amplification, then n could shift 9 positions (3^2) at a time. Starting at 0, the first example would require a minimum of 34 generations to find 100, the second 17 generations, and the third 12 generations. Then again if “3” itself were duplicated so that the bump became “33,” then the minimum would only be 4 generations.
Lizzie,
This “down” vs “up” business is important to keep straight! If fitness is like gravity, down is fit; if fitness is like the the top of Mt Improbably, then up is good – but in that case, we have to dispense with “gravity” in our metaphor, and replace it by a bias towards stepping to higher (or less low) ground at each stride.
But it’s also important to remember, in the metaphor, that it is populations, not individuals, that do the moving.”
Let me make a better analogy, evolution is like a set of small raund rocks that falls by gravity (replication with errors) until they found a screen with star holes (a peak of fitness) gravity makes that part of the rocks changes until part of them get the star form that passes troguht the star holes of the screen until they found again a screeng with half moon holes and the process repeats.
Phinehas,
I could be mistaken, but I’m getting the impression that you are still viewing humans as a specific target. Your example of a random walk is a good one — it’s going to get somewhere after n steps, but the space of possible somewheres gets increasingly larger as n grows.
As OMagain pointed out, if we were the descendants of dinosaurs instead of mammals, we’d be having the same conversation based on sauromorphism. Homo sapiens isn’t the goal of evolution.
Phinehas seems to be locked out! Not sure whether it’s a temporary glitch or somethign I did wrong when I changed his posting status to author.
I’ll keep trying to sort it.
As Lizzie noted, there are more ways to be complex than there are ways to be simple. So, rather than a linear continuum, imagine a vast tree-like structure. At any one node, there is one route towards simplicity and three-to-ten (say) routes towards greater complexity. “Random” walks will tend to end up nearer the extremities than the trunk. The analogy to entropy is apt.
Also, more often than not, natural selection nudges beasties towards greater complexity because we are made of FOOD.
Test.