And it’s time for the other papers I promised.
Moving on, let’s look at the more recent papers. Let’s look first at the abstract of the Adami et al paper:
To make a case for or against a trend in the evolution of complexity in biological evolution, complexity needs to be both rigorously defined and measurable. A recent information-theoretic (but intuitively evident) definition identifies genomic complexity with the amount of information a sequence stores about its environment. We investigate the evolution of genomic complexity in populations of digital organisms and monitor in detail the evolutionary transitions that increase complexity. We show that, because natural selection forces genomes to behave as a natural ‘‘Maxwell Demon,’’ within a fixed environment, genomic complexity is forced to increase .
Oh look. A point I’ve been arguing for a long time here, namely that a rigorous definition of complexity is needed in order to be able to make precise categorical statements about complexity . I also note with interest that the authors of this paper perform detailed experiments via simulation in order to establish the fact that complexity can arise from simple systems (the behaviour of the Verhust Equation I’ve mentioned here frequently establishes this, and indeed, the investigation of such systems as the Verhulst Equation and similar dynamical systems is now the subject of its own branch of applied mathematics ).
The authors open their paper thus:
Darwinian evolution is a simple yet powerful process that requires only a population of reproducing organisms in which each offspring has the potential for a heritable variation from its parent. This principle governs evolution in the natural world, and has gracefully produced organisms of vast complexity. Still, whether or not complexity increases through evolution has become a contentious issue. Gould (1), for example, argues that any recognizable trend can be explained by the ‘‘drunkard’s walk’’ model, where ‘‘progress’’ is due simply to a fixed boundary condition. McShea (2) investigates trends in the evolution of certain types of structural and functional complexity, and finds some evidence of a trend but nothing conclusive. In fact, he concludes that ‘‘something may be increasing. But is it complexity?’’ Bennett (3), on the other hand, resolves the issue by fiat, defining complexity as ‘‘that which increases when self-organizing systems organize themselves.’’ Of course, to address this issue, complexity needs to be both defined and measurable .In populations of such sequences that adapt to their world (inside of a computer’s memory), noisy self-replication coupled with finite resources and an information-rich environment leads to a growth in sequence length as the digital organisms incorporate more and more information about their environment into their genome. Evolution in an information-poor landscape, on the contrary, leads to selection for replication only, and a shrinking genome size as in the experiments of Spiegelman and colleagues (8). These populations allow us to observe the growth of physical complexity explicitly, and also to distinguish distinct evolutionary pressures acting on the genome and analyze them in a mathematical framework .
Moving on, the authors directly address a favourite canard of creationists (though they do not state explicitly that they are doing this), namely that information somehow constitutes a “non-physical” entity. Here’s what the authors have to say on this subject:
Information Theory and Complexity . Using information theory to understand evolution and the information content of the sequences it gives rise to is not a new undertaking. Unfortunately, many of the earlier attempts (e.g., refs. 12–14) confuse the picture more than clarifying it, often clouded by misguided notions of the concept of information (15). An (at times amusing) attempt to make sense of these misunderstandings is ref. 16. Perhaps a key aspect of information theory is that information cannot exist in a vacuum; that is, information is physical (17). This statement implies that information must have an instantiation (be it ink on paper, bits in a computer’s memory, or even the neurons in a brain) . Furthermore, it also implies that information must be about something. Lines on a piece of paper, for example, are not inherently information until it is discovered that they correspond to something, such as (in the case of a map) to the relative location of local streets and buildings. Consequently, any arrangement of symbols might be viewed as potential information (also known as entropy in information theory), but acquires the status of information only when its correspondence, or correlation, to other physical objects is revealed .
Nice. In brief, the authors clearly state that information requires a physical substrate to reside upon , and a mechanism for the residence of that information upon the requisite physical substrate , in such a manner that said information constitutes a mapping from the arrangement of the physical substrate upon which it resides, to whatever other physical system is being represented by that mapping . I remember one creationist claiming that because the mass of a floppy disc doesn’t change when one writes data to it, this somehow “proves” that information is not a physical entity: apparently said creationist didn’t pay attention in the requisite basic physics classes, or else he would have learned that the information stored on a floppy disc is stored by materially altering the physical state of the medium, courtesy of inducing changes in the magnetic orientation of the ferric oxide particles in the disc medium . In other words, a physical process was required to generate that information and store it on the disc . I am indebted to the above authors for casting this basic principle in the appropriate (and succinct) general form.
The authors move on with this:
In biological systems the instantiation of information is DNA, but what is this information about? To some extent, it is the blueprint of an organism and thus information about its own structure. More specifically, it is a blueprint of how to build an organism that can best survive in its native environment, and pass on that information to its progeny. This view corresponds essentially to Dawkins’ view of selfish genes that ‘‘use’’ their environment (including the organism itself), for their own replication (18). Thus, those parts of the genome that do correspond to something (the non-neutral fraction, that is) correspond in fact to the environment the genome lives in. Deutsch (19) referred to this view by saying that ‘‘genes embody knowledge about their niches.’’ This environment is extremely complex itself, and consists of the ribosomes the messages are translated in, other chemicals and the abundance of nutrients inside and outside the cell, and the environment of the organism proper (e.g., the oxygen abundance in the air as well as ambient temperatures), among many others. An organism’s DNA thus is not only a ‘‘book’’ about the organism, but is also a book about the environment it lives in, including the species it co-evolves with. It is well known that not all of the symbols in an organism’s DNA correspond to something. These sections, sometimes referred to as ‘‘junk-DNA,’’ usually consist of portions of the code that are unexpressed or untranslated (i.e., excised from the mRNA). More modern views concede that unexpressed and untranslated regions in the genome can have a multitude of uses, such as for example satellite DNA near the centromere, or the polyC polymerase intron excised from Tetrahymena rRNA. In the absence of a complete map of the function of each and every base pair in the genome, how can we then decide which stretch of code is ‘‘about something’’ (and thus contributes to the complexity of the code) or else is entropy (i.e., random code without function)?Mycoplasma mycoides , for example (which causes pneumonialike respiratory illnesses), has a complexity of somewhat less than one million base pairs in our nasal passages, but close to zero complexity most everywhere else, because it cannot survive in any other environment—meaning its genome does not correspond to anything there. A genetic locus that codes for information essential to an organism’s survival will be fixed in an adapting population because all mutations of the locus result in the organism’s inability to promulgate the tainted genome, whereas inconsequential (neutral) sites will be randomized by the constant mutational load. Examining an ensemble of sequences large enough to obtain statistically significant substitution probabilities would thus be sufficient to separate information from entropy in genetic codes. The neutral sections that contribute only to the entropy turn out to be exceedingly important for evolution to proceed, as has been pointed out, for example, by Maynard Smith (20).C (i), pG (i), pA (i), pT (i)}, [1]- = -[chr]931[/chr]C,G,A,T j pj (i) log pj (i) [2]i = 0 for that site according to Eq. 2. The amount of information per site is thus (see, e.g., ref. 23)max - Hi [3]l base pairs the complexity isl - [chr]931[/chr]i H(i) [4]g p(g|E) log p(g|E) [5]Appendix.
Quite a substantial mathematical background, I think everyone will agree. I’ll let everyone have fun reading the rest of the details off-post, as they are substantial, and further elaboration here will not be necessary in the light of my providing a link to the full paper.
Moving on to the Kaila and Annila paper, here’s the abstract:
The second law of thermodynamics is a powerful imperative that has acquired several expressions during the past centuries. Connections between two of its most prominent forms, i.e. the evolutionary principle by natural selection and the principle of least action, are examined. Although no fundamentally new findings are provided, it is illuminating to see how the two principles rationalizing natural motions reconcile to one law. The second law, when written as a differential equation of motion, describes evolution along the steepest descents in energy and, when it is given in its integral form, the motion is pictured to take place along the shortest paths in energy. In general, evolution is a non-Euclidean energy density landscape in flattening motion.
Ah, this dovetails nicely with Thomas D. Schneider’s presentation of a form of the Second Law of Thermodynamics applicable to biological systems that I’ve covered in past posts. This can be read in more detail here . Note that Thomas D. Schneider is not connected with Eric D. Schneider whose paper is cited above.
Here’s how Kaila and Annila introduce their work:
1. Introduction
I advise readers to exercise some caution before diving into this paper in full, as it involves extensive mathematics from the calculus of variations, and a good level of familiarity with Lagrangian and Hamiltonian mechanics is a pre-requisite for understanding the paper in full.
In the meantime, let’s take a look at the Schneider & Kay paper. Here’s their introduction:
Introduction What is Life? (Schrödinger, 1944), he attempted to draw together the fundamental processes of biology and the sciences of physics and chemistry. He noted that life was comprised of two fundamental processes; one “order from order ” and the other “order from disorder ”. He observed that the gene generated order from order in a species, that is, the progeny inherited the traits of the parent. Over a decade later Watson and Crick (1953) provided biology with a research agenda that has lead to some of the most important findings of the last fifty years.order from disorder premise. This was an effort to link biology with the fundamental theorems of thermodynamics (Schneider, 1987). He noted that living systems seem to defy the second law of thermodynamics which insists that, within closed systems, the entropy of a system should be maximized. Living systems, however, are the antithesis of such disorder. They display marvelous levels of order created from disorder. For instance, plants are highly ordered structures, which are synthesized from disordered atoms and molecules found in atmospheric gases and soils.Schrödinger solved this dilemma by turning to nonequilibrium thermodynamics . He recognized that living systems exist in a world of energy and material fluxes. An organism stays alive in its highly organized state by taking high quality energy from outside itself and processing it to produce, within itself, a more organized state. Life is a far from equilibrium system that maintains its local level of organization at the expense of the larger global entropy budget . He proposed that the study of living systems from a nonequilibrium perspective would reconcile biological self-organization and thermodynamics. Furthermore he expected that such a study would yield new principles of physics.order from disorder research program proposed by Schrödinger and expands on his thermodynamic view of life. We explain that the second law of thermodynamics is not an impediment to the understanding of life but rather is necessary for a complete description of living processes . We expand thermodynamics into the causality of the living process and show that the second law underlies processes of self-organization and determines the direction of many of the processes observed in the development of living systems .
Finally, I’ll wind up by introducing Emory F. Bunn’s paper, which is a particular killer for creationist canards, because it involves direct mathematical derivation of the thermodynamic relationships involved in evolutionary processes, and a direct quantitative analysis demonstrating that evolution is perfectly consistent with the Second Law of Thermodynamics . Here’s the abstract:
Skeptics of biological evolution often claim that evolution requires a decrease in entropy, giving rise to a conflict with the second law of thermodynamics. This argument is fallacious because it neglects the large increase in entropy provided by sunlight striking the Earth. A recent article provided a quantitative assessment of the entropies involved and showed explicitly that there is no conflict. That article rests on an unjustified assumption about the amount of entropy reduction involved in evolution. I present a refinement of the argument that does not rely on this assumption.
Here’s the opening gambit:
I. INTRODUCTION 1 He correctly explained that this claim rests on misunderstandings about the nature of entropy and the second law. The second law states that the total entropy of a closed system must never decrease. However, the Earth is not a closed system and is constantly absorbing sunlight, resulting in an enormous increase in entropy, which can counteract the decrease presumed to be required for evolution. This argument is known to those who defend evolution in evolution-creationism debates,2 but it is usually described in a general, qualitative way. Reference 1 filled this gap with a quantitative argument.In the following I present a more robust quantitative argument . We begin by identifying the appropriate closed system to which to apply the second law. We find that the second law requires that the rate of entropy increase due to the Earth’s absorption of sunlight, (dS/dt)sun , must be sufficient to account for the rate of entropy decrease required for the evolution of life, (dS/dt)life (a negative quantity). As long assun + (dS/dt)life [chr]8805[/chr] 0,sun and (dS/dt)life to show that the inequality (1) is satisfied, but his argument rests on an unjustified and probably incorrect assumption about (dS/dt)life .1 I will present a modified version of the argument which does not depend on this assumption and which shows that the entropy decrease required for evolution is orders of magnitude too small to conflict with the second law of thermodynamics .
Once again, I’ll let you all have fun reading the paper in full.
So, that’s five scientific papers containing detailed rebuttals of creationist canards about the Second Law of Thermodynamics. I think that’s sufficient to establish that the creationist canards ARE canards, don’t you?
