Using Bad Math to Create Bad Models to Produce Bad Results

An astute reader pointed me towards a monstrosity of pompous bogus math. It’s an oldie, but I hadn’t seen it before, and it was just referenced by my old buddy Sal Cordova in a thread on one of the DI blogs. It’s a “debate” posted online by Lee Spetner, in which he rehashes the typical bogus arguments against evolution. I’m going to ignore most of it; this kind of stuff has been refuted more than enough times. But in the course
of this train wreck, he pretends to be making a mathematical argument about search spaces and optimization processes. It’s a completely invalid argument – but it’s one which is constantly rehashed by creationists, and Spetner’s version of it is a perfect demonstration of exactly what’s wrong with the argument.

Let’s look at the relevant parts of Spetner’s argument. Spetner basically repeats himself over and over, so I’ll just quote the first repetition; you can go look at the full document to see others.

The principle message of evolution is that all life descended with modification from a
putative single primitive source. I call this the grand sweep of evolution. The mechanism
offered for the process of modification is basically the Darwinian one of a long series of
steps of random variation, each followed by natural selection. The variation is generally
understood today to be random mutations in the DNA.

For the grand process of evolution to work, long sequences of beneficial
mutations must be possible, each building on the previous one and conferring a selective
advantage on the organism. The process must be able to lead not only from one species to
another, but to the entire advance of life from a simple beginning to the full complexity
of life today. There must be a long series of possible mutations, each of which conferring
a selective advantage on the organism so that natural selection can make it take over the
population. Moreover, there must be not just one, but a great many such series.

The chain must be continuous in that at each stage a change of a single base pair
somewhere in the genome can lead to a more adaptive organism in some environmental context.
That is, it should be possible to continue to climb an adaptive hill, one base
change after another, without getting hung up on a local adaptive maximum. No one has ever
shown this to be possible.

Now one might say that if evolution were hung up on a local Maximum, a large genetic
change like a recombination or a transposition could bring it to another higher peak. Large
adaptive changes are, however, highly improbable. They are orders of magnitude less
probable than getting an adaptive change with a single nucleotide substitution, which is
itself improbable. No one has shown this to be possible either.

So – he’s trying to do the usual thing of modeling evolution as a search of a fitness landscape. It’s pretty common to model evolution that way – both real scientists and creationist bozos do it – but it is worth pointing out that while search is a useful model of evolution, it’s far from a perfect one. The classic formulation of search over a fitness landscape requires an unchanging landscape. But the “fitness landscape” that’s being traversed in an evolutionary process is not: it’s constantly changing.

He takes advantage of that flaw in the model of the fitness landscape to build a key part of his argument. Throughout the argument, he keeps making claims about getting “hung up on a local maximum”. The passage quoted above contains an example; in the full document, he comes back to that point again and again.

But it’s a completely invalid point. Even if we assume that there are local maxima where things can get hung up, the landscape is constantly changing. So a local maximum today is not necessarily a maximum tomorrow, and is almost certainly not a maximum 100 years from now. So even if we pile together his bunch of bogus assumptions without argument, we still wind up with his argument being completely and thoroughly wrong, because it’s based on the invalid assumption of an unchanging fitness landscape.

We can even show why the fixed fitness landscape is wrong. Suppose we had a
fixed fitness landscape with local maxima. Then we’ll find organisms “climbing” towards
those maxima. And when they reach a maximum, they stop moving. What this means is
that we’ll see multiple organisms climbing towards the fitness maxima; and over
time we’ll see things clustering around the maxima. With this clustering at the maxima, eventually, there will be competition for resources – meaning that the maximum isn’t a maximum anymore – suddenly it’s a hotbed of competition with some changes producing winners, and some losers. So the fitness landscape can’t be a fixed with true local maximums that become traps.

What else does he get wrong? As bad as the “fixed landscape” bogosity is, it’s not the worst of his slimy mathematical sloppiness.

Because, you see, the chances of there being an actual local maximum in an evolutionary fitness landscape is something amazing close to nil. Sure, there are probably some, sometimes. But the thing is, “fitness” in the evolutionary sense is really a function of not just one or two variables, but of dozens, or hundreds, or even thousands of variables. We’re not talking about a two-dimensional counter where there are hills and valleys. An evolutionary fitness landscape is a surface with dozens of dimensions. To be a true local maximum – that is, a point in the landscape with no smooth upward paths out requires the surface to be at a maximum in all dimensions at the same point: it means that if you slice a plane through the surface to get a two-dimensional view, no matter how you orient the plane in those dozens of dimensions, it will always produce a hill shape with the maximum at the same place. Why would all of the dimensions coincide on a maximum like that? If we’re playing probability games – and this argument of his is ultimately probabilistic – then the deadlocking local maxima are incredibly improbable – less likely than the things that he’s ruling out as being too unlikely.

And even that isn’t his worst mistake. Suppose you’re looking at evolution as a search
over a landscape. So you’ve got an organism at some point in the landscape. To consider
where it can go in its traversal of the landscape, you need to consider how it can “move”: where can it go in one step from its present location?

Spetner requires that the only permissible “motions” are single point changes which produce immediate effects. He explicitly disallows
consideration of multiple concurrent changes; he disallows consideration of changes that don’t present an immediate benefit; he disallows consideration of any change other than single-base changes – no duplications, no rearrangements, no changes of any kind except single-base point mutations. In other words, he deliberately creates a search model that does not match observed reality, and then uses it to conclude that his search model cannot match observed reality. (Where’s Dr. Egnor when you need him? This is exactly the kind of tautology that Dr. Egnor claims to like to knock down!)

And even that isn’t his worst mistake. If you look at how Spetner formulates the search, he basically treats an evolutionary search as if it’s a single organism traversing the fitness landscape. He demands that changes work in a strict stepwise fashion. One change happens; that one change produces a selective advantage; the selective advantage causes that change to propagate and become fixed in the population; and then the next change can occur. That is not an accurate model of reality: reality is a population of many individuals, with many changes happening at the same time – some neutral, some beneficial, some harmful – and those changes accumulate and propagate through the population, with some individuals surviving, and some not. In other words, it’s an even more blatant example of the Egnor error: create a model that does not match observed reality, claim that it’s an accurate model of the theory you want to criticize, and then declare triumph when the predictions of your model cannot match reality.

Pure bogosity. Pure slop. Pure bad math.

0 thoughts on “Using Bad Math to Create Bad Models to Produce Bad Results”

  1. I think theres a little bit of truth in his arguments. Lets suppose that there are considerable periods of time during which the fitness landscape is quasi-staionary. You’ll get quasi-staionary ecology. Now occasionally the environment changes substantially -perhaps because of climate change. Now the system struggles to come to a new equilibrium.
    That sounds a lot like punctuated equilibrium – or a bit like using
    simulated anealing -where we change something in the (search) environment to break things out of local maxima.
    I’m not convinced that actual local maxima (or at least quasi-maxima) don’t exist. In fact we have some specicies such as scorpions, whose form has been remarkably stable over more than a hundred million years.

  2. Stuart Kauffman’s books “At Home In The Universe” and “Investigations” have really clear discussions of why evolutionary fitness landscapes can change over time, along with some nice experimentation with simple models of those systems. Worth a look, if only to point out to people like Spenter.

  3. “In fact we have some specicies such as scorpions, whose form has been remarkably stable over more than a hundred million years.”
    That doesn’t necessarily point to a local maxima. All this talk of point mutations discounts the much larger and more important changes caused by variation within the breeding population. This provides a reservoir of variation that can be used up.
    If there is no variation in genes within the scorpion population (at least for those genes that would move the scorpion to a different place on the putative fitness landscape) then it cannot evolve even in the face of evolutionary pressure.
    Organisms do get trapped like this and species do go extinct, as nearly all of them have.
    Even if Spetner’s arguments were entirely relevant all he would really be saying is that it’s incredibly unlikely that a species will survive for long as it’ll get caught at a local maxima. This is exactly what we do see anyway.
    The reality of how the landscape model works is more complex than Mark depicts and there are constraints that serve to reduce the dimensions that are being searched at any given time, but it isn’t just the landscape that changes over time, the dimensions that are being searched across also changes.
    However, none of this alters Mark’s conclusion and the landscape model, when properly applied, does go a long way towards understanding how evolution works.

  4. Grammar dork alert.
    “The principle message of evolution is that all life descended with modification from a putative single primitive source.”
    He also misused the word “principle.” The spelling used refers to tenets or ideals where the context clearly refers to a key point ans so should be spelled ‘principal.’ If a sixth grader can learn it, grown-ups can, too.

  5. Spetner’s blather is one of the reasons I really really dislike the search metaphor for biological evolution. It’s a snare and a deception. My company uses genetic algorithms as search algorithms, and they are different in important respected from biological evolution. To give but one difference, in the GAs we create a population of random critters and run them against some fitness function. Over generations the initially random population coalesces on multiple fitness peaks on the landscape.
    An evolving biological population, on the other hand, starts on a “solution” — if it’s reproducing it’s far enough up some slope to be viable. And it does not sample from the whole of the “search” space but rather preferentially samples the neighborhood defined by one application of an evolutionary operator, that neighborhood also being a viable place with some relatively high probability. All of Dembski’s blather about search and displacement and the allegedly teeny weeny probability that random search will find viable phenotypes in a humongous volume depend on ignoring that point. (Yeah, I know, I know, one can screw around with the search metaphor to take account of that, but in my view that’s wasted effort to salvage a fundamentally flawed metaphor.)

  6. math dork alert. 🙂
    a convex optimization will always have a unique extremum, no matter how many dimensions there are. I’m not complaining about your tearing the argument to shreds, but I don’t quite understand why the mere fact of multiple dimensions should make a maxima any *more* unlikely than the numerous other reasons one might supply

  7. If there is no variation in genes within the scorpion population (at least for those genes that would move the scorpion to a different place on the putative fitness landscape) then it cannot evolve even in the face of evolutionary pressure.

    This reminds me of the articles of studies on island sheep. Now, you see articles that conflicts with each other, but here is what one says about a specific population:

    Fitness increased with birth weight, and with environmental quality, but the positive relationship between fitness and birth weight–indicating the strength of selection–became weaker in better environments. Environmental quality shapes the trajectories for both genetic variance and the strength of selection. Lambs are not growing bigger and bigger because there’s a lack of heritable variation for selection to act on in harsh environments and there’s a lack of selection to act on higher genetic variation during favorable conditions. [Bold added.]

    ( http://www.eurekalert.org/pub_releases/2006-06/plos-nsi060706.php )
    So as I understand it, this report finds that the sheep they studied are trapped due current lack of variation, and they keep their size even when the environment changes.
    But getting back to the scorpions, have they really been stable? There are quite a lot of species, 2000 of them. I note that they have 3 to 4 pairs of of legs, and a lot of other variations:

    In conformity with their wide dispersal, scorpions have become adapted to diverse conditions of existence, some thriving in rainforests, others on open plains, others in sandy deserts and a few even at high altitudes where the ground is covered with snow throughout the winter. In the tropics, they aestivate at times of drought; and in the Alps, they pass the cold months of the year in a state of hibernation.

    ( http://en.wikipedia.org/wiki/Scorpion )
    The general form seems to be a good solution. This is supported by that there are also similar arachnids, pseudoscorpions. Where I live (Sweden) we have one such species, the “book scorpion” (Chelifer cancroides, described by Linné 1758), of an imposing 4 mm length, half of which is ridiculously long arms. It has no tail and lives on molds, but looks otherwise very much like a miniature scorpion.

  8. a convex optimization will always have a unique extremum, no matter how many dimensions there are.

    True, but we were discussing local extrema here. Higher dimensionality makes them less likely to find. (And, I think, ‘smoother’ when they exist.)
    If you look at Spetner he doesn’t object to finding (and, I guess, in principle tracking a slowly varying) global maximum in fitness.

  9. This is a case where over-simplification is terribly misleading. Spetner is probably imagining a space with just one or a few dimensions — something easily displayed in a cartoon graph of the kind we see in mass media — an up-and-down roller coaster ride along a single axis. When one realizes that there are literally thousands (millions?) of axes, the whole argument falls apart.
    Interestingly, the argument that local maxima exist even in a massively-multidimensional space does not prevail either. Any species that gets stuck in a local maximum for too long will simply go extinct — an event which is the norm, not the exception.
    However, it is refreshing that Spetner at least understands about the role of natural selection and the fact that fitness standards change over time. Perhaps he might be one of the guys we could actually reach?

  10. I’m with RBH in really disliking the search metaphor, since it’s so easily used to imply that evolution must somehow be goal-directed (i.e. that the search is *for* something), rather than working with what it finds at the moment. That leads to the equally invidious “chain” metaphor, e.g., Spetner’s statement that “For the grand process of evolution to work, long sequences of beneficial mutations must be possible, each building on the previous one….”
    Nah, not so. Sequences are only necessary if you embrace the fallacy of goal-direction. Or to put it another way, if one link in the chain is broken, evolution doesn’t collapse, you simply achieve a different evolutionary result. So for example, when the dinosaur link is broken (at least for dinosaurs qua big reptiles), evolution doesn’t stop, it simply continues on an alternate path than it would have in a world where the K-T event (or whatever you believe responsible for the Cretaceous extinction) had never occurred.

  11. It seems to me that aside from failing to view the fitness landscape as a multidimensional boiling cauldron of dynamics, Spetner also has some pretty lousy views about local maxima. Aside from competing organisms’ abilities to alter the fitness landscape of other organisms, local maxima are generally staples of the ecosystem. You can see it repeatedly in evolution – species fit into niche environments that may not be ideal, but because the spot was available, it was a local maxima. Lemurs fit all kinds of niche environments in madagascar. Grazing has been a pretty popular niche environment since grasses took root. As such, getting trapped in a local maxima isn’t such a bad thing – BECAUSE its a maxima.
    Forgive me for quoting wikipedia, because I don’t currently have the time or resources to check their sources:
    The ground breaking theoretical investigations of Kauffman (1993)[17] and Wolfram (2002)[18] also suggest the existence of a vast number of vacant niches. Using different approaches, both have shown that species rarely if ever reach global adaptive optima. Rather, they get trapped in local optima from which they cannot escape, i.e., they are not perfectly adapted. As the number of potential local optima is almost infinite, the niche space is largely unsaturated and species have little opportunity for interspecific competition. Kauffman (p.19) writes: ” ..many conceivable useful phenotypes do not exist” and: (p.218) “Landscapes are rugged and multipeaked. Adaptive processes typically become trapped on such optima”. (from http://en.wikipedia.org/wiki/Vacant_niches; see also http://en.wikipedia.org/wiki/Ecological_niche)

  12. This is also why it doesn’t matter whether you get “stuck” in a local maximum or not. You can live quite comfortably in a local maximum. Until the landscape shifts, anyway.
    If you were using this kind of optimizing search in an engineering problem, of course you’d prefer to find the global maximum, the best solution. But local maxima *still work* – maybe not as well, but better than a lot of other things. Any organism that is, in fact, alive works well enough to stay that way. And that’s all you really need.
    Evolution isn’t “looking” for the best possible organism; it’s just a collection of good-enough organisms. That’s why we have appendicitis and pareidolia and sometimes mistake our dreams for real events – we’re *not* a perfect organism.
    So why should we be surprised at a process that produces imperfection? Imperfection is what we have. A process that would be expected to produce perfection would fit the observed data *worse*.

  13. Jebub:
    Congratulations, you just got yourself banned, you miserable little shit.
    Folks, I’m really sorry that link got left there for so long. A couple of assholes have been targeting me with antisemitic shit like that lately. It’s mostly been in email; this is the first time they’ve shown up on the blog. (Interestingly, the antisemitic shit shows an astonishing relationship with George Shollenberger… Each time he posts something with my name in it, I get a couple of vile anti-semitic emails.)

  14. BigTom:
    Even if you accept the idea of transient maxima and minima, Spetner’s arguments don’t work. One of the constraints that he demands is that there are no neutral changes and no delayed selection.
    The punctuated equilibria idea is based on the idea that when a population reaches a certain level of “good enough”, it becomes stable. During the stable period, changes occur in the populations genes, which produce the diversity that seeds the process of change when the stable period ends: during the stable period, genetic diversity accumulates in the form of neutral or nearly-neutral changes. Then when the stability ends, selection acts on the existing diversity, “choosing” the individuals whose traits are best suited to the changing conditions.
    Spetner explicitly disallows that possibility, even though we observe it on a regular basis. He disallows any genetic changes that don’t produce an immediate advantage.

  15. A nice article. Let’s not take our eyes off the ball, however:
    When speaking to a neophyte who might be sucked in by the stupidity or mendacity of creationists, it is important to remind them of an even more basic fact before trashing the pseudo-math: Science must account for observations. There is overwhelming empirical evidence for evolution – extended over many orders of magnitude in time and genetic variation. No purely mathematical argument can change the facts. Any argument that attempts to do so, no matter how sophisticated its appearance, is ultimately irrelevant. The most that can be accomplished is a change in the mechanistic details used to understand the facts. As soon as an irreproducible mechanism is introduced (i.e., intelligent design, or whatever other euphemism these charlatans devise) we leave the realm of science.
    Why do religious fundamentalists feel it necessary to put forward pitiful “science” like creationism or such transparent non sequiturs like “intelligent design”? They do so because the history of the past 500 years or so has forced them to. 500 years ago, when religious men ruled the Western world, the plague, smallpox, and tuberculosis decimated whole populations. The human race was relatively powerless; the so-called moral superiority of these men of faith allowed and even encouraged war and slavery – albeit without the efficiency enabled by modern technology. A scientific front is necessary for fundamentalists because even they know that SCIENCE WORKS. The pronouncements of priests, mullahs, and witch doctors are transparently ineffectual when pitted against the power of reason, implemented via the scientific method and amplified by the compounding of knowledge and information of a few centuries of application.

  16. Another argument against fixed landscapes is the molecular evidence of population bottlenecks. If there is any correlation between relative fitness and absolute fitness, then most species have undergone rapid ‘walks’ down fitness peaks. The only way I see that happening is through an environmental change (that, or Fisher’s Fundamental Theorem ain’t so fundamental).

  17. Since we have exclusively discussed selection, we should not forget the other side of the coin, genetic drift. It can happen over time as alleles shows up and drift to fixation, especially in small populations. If the selective pressures are small, drift can dominate.
    It is responsible for some phenomena around population bottlenecks and founder effects as well.

    Drifting alleles usually have a finite lifetime. As the frequency of an allele drifts up and down over successive generations, eventually it drifts until fixation – that is, it either reaches a frequency of zero, and disappears from the population, or it reaches a frequency of 100% and becomes the only allele in the population. Subsequent to the latter event, the allele frequency can only change by the introduction of a new allele by a new mutation.
    […]
    Genetic drift and natural selection rarely occur in isolation from each other; both forces are always at play in a population. However, the degree to which alleles are affected by drift and selection varies according to circumstance.
    In a large population, where genetic drift occurs very slowly, even weak selection on an allele will push its frequency upwards or downwards (depending on whether the allele is beneficial or harmful). However, if the population is very small, drift will predominate. In this case, weak selective effects may not be seen at all as the small changes in frequency they would produce are overshadowed by drift.

    ( http://en.wikipedia.org/wiki/Genetic_drift )

    the “book scorpion”

    Um, I forgot to explain the funny name. It is often seen in old and musty libraries or book shelves, which is probably why it got its name.

  18. Mark, thank you for this, it is a beautifully constructed, concise discussion of precisely what is wrong with this kind of pseudo-scientific, pseudo-mathematical argument. Not that I’m becoming a fawning fan or anything…
    But anyway, don’t we see organisms at least temporarily “stuck” at local maxima which are not necessarily a global maximum, like, all the time?

  19. Mark C wrote:

    He also misused the word “principle.” The spelling used refers to tenets or ideals where the context clearly refers to a key point ans so should be spelled ‘principal.’ If a sixth grader can learn it, grown-ups can, too.

    Yep. As I recall it from sixth grade, the mnemonic goes something like this: ‘The head of a school is a not your enemy, he’s your pal. He’s the principal.’
    Thus, the head or primary of anything is the principal.
    A quick googling confirms my recollection.
    Of course, simple correctness has never been a strong point for these folks. Nor is confirmation of their guesses.

  20. Strongly tempted as I am to write something clever as an ex-Math professor, or as a mathematical Biologist, or as a fan of Stuart Kauffman, I find myself instead quoting something which is more to the point regrading mind-set:
    “I utterly disbelieve in statistics as a science and am never myself guided by any long-winded statement of figures from a Chancellor of the Exchequer or such like big-wigs… Figures, when they go beyond six in number, represent to me not facts, but dreams, or sometimes worse than dreams.”
    [Anthony Trollope, in Anthony Trollope: A Victorian in His World]

  21. This is probably totally wrong, but I was just reading the Wikipedia article on scorpions, and it mentions that they might have very good resistance to radiation. If so, it’s possible that they simply mutate less than other species.
    Like I said, probably wrong. 🙂

  22. If so, it’s possible that they simply mutate less than other species.

    It could be, IIRC the radiation resistant Deinococcus radiodurans has repair mechanisms that fixes other damage too.
    A difference could be that an organism with several chromosomes could be more susceptible/have chromosomal mutations during cell divisions. (Seems radiodurans have two chromosomes, though I don’t know how plasmids, typically circular, behave in contrast to linear chromosomes. http://mmbr.asm.org/cgi/content/full/65/1/44 )
    Still, 2000 species is quite a lot of speciation, whenever it happened with this assumed stable form. Accepting a 100 Myr time frame and assuming that stability was apparent, not real, it is roughly on average 10 Myr between speciations (assuming binary branching and no extinctions).
    While hominids perhaps have 2 Myr between (assuming around 30 species in 10 Myr). Of course, we can also probably not compare speciations closely between widely different lineages et cetera, but it gives a rough idea of the rough rates, I hope.
    In any case, it could be wrong to claim they can’t or don’t evolve, is all this poor layman is saying.

  23. I think there is another point where Sal Cordova’s argument is flawed.
    In his argument, he assumes that single gene mutations will only induce infinitisimal changes of position on the search field. Otherwise stated: a small step in the genome sequence equals a small step in any dimension of the search field.
    Although this is a very natural assumption to make, it actually is not. A single genome mutation could very well send the species a huge distance away from the starting position on the search field.

  24. MarkCC:

    With this clustering at the maxima, eventually, there will be competition for resources – meaning that the maximum isn’t a maximum anymore

    Whoa! So basically, if I understood you correctly, you’re saying that populations collectively climb toward a maximum, which makes that maximum crowded, which introduces more stringent selection, which makes other criteria more important, and therefore the maximum ceases to be a maximum because it was a maximum.
    That’s a terribly elegant idea, IMHO. Is it true?

  25. The fitness function, which summarizes a relationship between a population and its environment, plus Natural Selection, plus noise, plus other factors, causes changes in the allele frequences of the population which are the very definition of evolution.
    The evolution changes the interaction between a population and its environment, for various reasons. These include changes to the environment, speciation, chaotic interactions between different species, and changes in which species are in which niches, which themselves have a fractal distribution over space.
    The feedback is very hard to describe neatly, because there are so many different effects, each usually analyzed with a different quantitative model. Mark CC was correct, but that does oversimplify, maybe to our benefit.
    Yes, the fitness function (and fitness landcape) is VERY high in dimensionality, and DOES itself change over time. Absolutely. I’d say that 100% of scientists agree about this, which doesn’t itself make it right, but does show the sort of broad consensus which ID folks love to attack as spuriously collapsing, when the 100% uses slightly different terminology and slightly different interpretation of field data.
    An attempt to discuss these feedbacks in terms of Shannon entropy was kicked off my Sal Cordova, turned into a draft paper of mine on first in this blog, now on a wiki.
    I’ve been interrupted in completing the paper, due to medical, legal (I’m eyewitness in an unrelated civil trial and criminal trial), tax (bad quantitative models by state tax entity), and medical (my professor wife is now out of the hospital, the bloody malady still not diagnosed well).
    Biology is very interesting. See other Science Blogs for the reaction to 3 of 10 GOP Presidential candidates in debate raising their hands to indicate that they don’t believe in Evolution.
    There’s a fine line between anti-science Woo and antiscience politics.

  26. arensb:
    Yes, it is true – and it is awfully beautiful, isn’t it?
    One of the things that I find saddest about fundie evolution denialism is that they use their alleged belief in something as a way of denying the actual beauty and complexity of the world. They claim to be seeing more to the world because of their religion – but in fact they’re closing their eyes to some amazing things.
    Evolution is an amazingly elegant process. It’s truly an awe inspiring and beautiful process when you look at it. To deny it is to close your eyes to something fascinating and beautiful.

  27. Clearly local optima do exist, which is why there are different species. It also explains such suboptimal solutions as the panda’s thumb and the reversed vertebrate retina. Kaufman’s simulations suggest that as the number of interacting components increases, the fitness landscape become rougher and more uncorrelated, arguing that there may be an upper limit to the complexity of an organism that is capable of efficient evolution. Of course, there is likely selection for the capacity to evolve. An organism may sit happily in a local optima for a while, but eventually something changes and that optimum goes away. An organism that has lost the capacity to evolve efficiently, through overly effective DNA repair or loss of sexual reproduction and recombination will be unable to “track” shifts in the fitness landscape, and may go extinct.

  28. arguing that there may be an upper limit to the complexity of an organism that is capable of efficient evolution

    Interesting. There are probably physical limits as well, at least in organisms as we know them today. Apparently DNA size correlates well with cell size. (Though not with genome size directly, as much DNA can be junk.)
    And cell size sets some constraints. For example, many lineages have nucleated blood cells unlike us. Effects of the resulting often much larger size will be less efficient oxygenation (area/volume ratio of cells), likely higher pressure used, likely higher clot risk, et cetera. I believe some species even compensate (or perhaps replace) with loose oxygenating molecules in the blood stream.
    Also, the eukaryotic cell is AFAIK already employing dense chemistry in comparison with bacterias. (So it needs a lot of membranes to compartmentalize, while bacterias do not, IIRC.)
    But the most successful design is the simplest, as in many other cases. Counting either individuals or biomass, monocellular life forms are the winners in the evolutionary process of procreating life.

    An organism that has lost the capacity to evolve efficiently, through overly effective DNA repair or loss of sexual reproduction and recombination will be unable to “track” shifts in the fitness landscape, and may go extinct.

    That reminds me of the brief web discussions on life under red dwarfs after the recent discovery of Gliese 581c and d, Earth size worlds one of which lies in the habitable zone. Since it was new but the statistics already tentatively promises many such worlds, the speculations about life conditions raged a while.
    Less UV radiation and relative surface calmness and stability of red dwarfs was mentioned as a possible problem for getting enough variation. But the same conditions also tells of less need. This could be a partly self regulating sector of evolutionary biology in several senses.

  29. I see that search metaphor is easy to fall prey to hidden value judgements and goal seeking.
    The essence of all creationist arguments IMO is a distinctive thinking-human search for meaning and (e)valuating human position and role in the Universe, with a bent towards assuming and then proving it to be something unique and special. Once this approach finds anything that resembles the proof that it is impossible (or at least very hard) to achieve this special status, creation is offered as the ‘logical’ answer.
    Implicit value judgements are hard to miss in these ‘arguments’.
    If we, as the species, are unlucky enough few years or decades from now may prove scorpions local maxima to serve ‘the aim’ of the evolution quite well.
    We humans are just not very good at accepting the fact that our very existence may be meaningless and may have no purpose. Just another temporary local maxima.
    Apart from the fear of losing individual sense of purpose (at the megalomaniacal scale of the individual purpose in the entire Universe or Creation if you wish) another guiding fear is the one of social disorder that may follow if the lack of the supranatural goal has no scientific proof and, more importantly, gets accepted by the wide population. In such an environment it may be impossible to promote the infallible, glorious Leader.

  30. Well, apart the discussion about local and absolute maxima’s, the creationist are asking the wrong questions. Because, if really He exist, and if so, He’s perfect, don’t would be more easy make an organism that could mutate and adapt to the environmental conditions over something “intelligent designed”? It’s like making a computer virus and let them spread into the web over infecting every computer by our hands…
    Ironically such a “virus” would be an intelligent virus.
    oh, and sorry for the bad english 🙁

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