Here’s a thought experiment. Consider something you know is intelligently designed: for example, software code for an app that flies a drone. Now let’s describe its “emergence” in Darwinian langauge:
Once assembly language emerged, it diversified into logic gates of increasing complexity, as crawling robots co-opted various functions for novel adaptations, including powered flight. The coding mechanism driving this spectacular process remains unclear. Through morphological analysis of robots in various stages of development, we identify two logic gates that act as major controllers for the topologies of drone propeller blades. Comparison of early and late drone models identifies three major transformations in drone blade evolution: (i) the appearance of stiff protrusions, (ii) further shaping of the protrusions into vanes, and (iii) specialization of the vanes into airfoils of increasing efficiency. Some of the vanes became grouped into fours separated by right angles. Besides these major transformative events, other morphological features that evolved include controlled rotation, autonomous navigation, communication with a smartphone, and so on.
All clear now? You’ll find this kind of vacuous language masquerading as scientific explanation repeatedly in the literature when evolutionists describe how complex systems “evolved.” Complex functions emerge. Novelty arises. Innovations appear. To show that our parody is not far off the mark, here are opening statements from a paper in Nature Communications about feather evolution. Notice all the words that assume evolution instead of demonstrating it. Notice also how the authors freely appropriate design words (like program, tuning):
Adaptation of feathered dinosaurs and Mesozoic birds to new ecological niches was potentiated by rapid diversification of feather vane shapes. The molecular mechanism driving this spectacular process remains unclear. Here, through morphology analysis, transcriptome profiling, functional perturbations and mathematical simulations, we find that mesenchyme-derived GDF10 and GREM1 are major controllers for the topologies of rachidial and barb generative zones (setting vane boundaries), respectively, by tuning the periodic-branching programme of epithelial progenitors…. Incremental changes of RA gradient slopes establish a continuum of asymmetric flight feathers along the wing, while switch-like modulation of RA signalling confers distinct vane shapes between feather tracts. Therefore, the co-option of anisotropic signalling modules introduced new dimensions of feather shape diversification.Major novel functions of feathers that evolved include endothermy, communication, aerodynamic flight and so on. These are achieved through stepwise retrofitting of the original feather forms. [Emphasis added.]
Yikes! “Aerodynamic flight” just evolved? The authors casually toss in three miracles as an afterthought: “major novel functions of feathers that evolved.” Let’s be clear: warm-bloodedness, communication and powered flight are not afterthoughts. Nor do they arise by “stepwise retrofitting” of feather forms. As Paul Nelson aptly says in Flight: The Genius of Birds, “You don’t just partly fly, because flight requires not just having a pair of wings, but having your entire biology coordinated towards that function.”
Then they toss out even more wonders:
Besides these major transformative events, other morphologic features that emerged during evolution include the deep follicles containing stem cells for cyclic regeneration, the hooklets and curved flanges in barbules and the solid cortex and air-filled pith in rachis and ramus. Together, these features enhanced feather mechanical strength, reduced weight, improved air-trapping efficiency and ensured renewability of feathers after damage.
Argument by assertion is not argument at all. To speak of “features that emerged during evolution” enlightens the reader only about the authors’ beliefs. It’s not a statement of science; it’s a statement of ideology.
Recall the animation of flight feathers in the Illustra film in all their glory: vanes, barbs, barbules, hooks, all interconnected to provide a firm, lightweight, water-resistant airfoil easily repaired by the bird. But having perfect feathers is not enough. Feathers have to be connected to bones, and those to muscles and nerves, and nerves to a brain programmed to know how to fly. Without everything working together, “the evolution of feathers” signifies nothing.
The researchers identified some genes and tweaked them in chickens to see what happened. In some cases, the barb angles changed. In others, the density of barbs grew or shrank. Identifying genes involved in feather “tuning” is fair game in science. It’s like reverse-engineering software to identify the logic routines used. Engineers might even run tests to see what happens when the logic routines are modified or rearranged. Those tests, however, would say nothing about the “emergence” of logic routines and complex functions.
The rest of the paper has very little to say about Darwinian evolution — certainly nothing about mutation and natural selection.
Another paper generalizes the error. In the Proceedings of the National Academy of Sciences, two American evolutionists strive to learn about “Emergence of function from coordinated cells in a tissue.” Emergence again. It’s a favorite word among evolutionists, obviating any need to identify causation. In this paper, the authors show that by repeatedly stating that something “gives rise to” something else.
A basic problem in biology is understanding how information from a single genome gives rise to function in a mature multicellular tissue. Genome dynamics stabilize to give rise to a protein distribution in a given cell type, which in turn gives rise to the identity of a cell. We build a highly idealized mathematical foundation that combines the genome (within cell) and the diffusion (between cell) dynamical forces. The trade-off between these forces gives rise to the emergence of function. We define emergence as the coordinated effect of individual components that establishes an objective not possible for an individual component. Our setting of emergence may further our understanding of normal tissue function and dysfunctional states such as cancer.
It “may further our understanding,” but then again, it may not. This paragraph only makes sense in light of intelligent design (or else what could “an objective” refer to?). Information in a gene can “give rise to” function if and only if it was programmed to do so. Read the paragraph that way, and it makes sense. In fact, the whole paper can be read that way. We would understand cells taking shape as tissues, and tissues “giving rise to” their preprogrammed functions the way the designer intended.
Unfortunately, this is not what the authors appear to be saying. They speak only of forces, distributions, and equilibria — blind, unguided natural processes.
You can find forces, distributions, and equilibria in rocks or ocean currents, but no “function” could be expected to “emerge” by unguided processes. Function implies a programmed response for the good of the whole in a coordinated, robust fashion, such that the whole organism can move, metabolize, and reproduce.
One might point to the “emergence” of nuclear fission in certain radioactive deposits, like the natural Oklo reactor in Gabon, Africa (Scientific American) as a kind of function. One might consider ocean currents driven by the moon to show the “emergence” of a cycle. Those cases, however, stretch the definition of “function” because they have no objective. A muscle tissue has an objective to generate force according to the will of the controlling brain behind it, for the purpose of movement, metabolism or reproduction. That’s the kind of function these two mathematicians are talking about. They think a liver’s function “emerges” from natural forces in the tissues it contains, and the protein distribution of each cell in the tissue. There’s no thought of a program in their discussion.
Our main theorem (Theorem 5) establishes that monotonicity, a property that we introduce here, implies global convergence of the tissue dynamics to the equilibrium, where all cells have the same protein distribution. This gives a biological justification for our framework and a model for “emergence of function,” as well as suggestions for studying the passage from emergence to morphogenesis. On the other hand one could see the emergence described here as a final stage of morphogenesis, completing a cycle.Our model could give some support to obtaining more insights. Further questions, where quantitative support is expected, are also suggested: (i) To what extent is there a common equilibrium of proteins in each cell in a tissue? (ii) How do cells in a tissue cooperate to give rise to function? And (iii) how do we measure the diffusion between the cells?
One might as well speak of the emergence of metals “giving rise to” the morphogenesis of a bicycle, and the morphogenesis of the bicycle “giving rise to” the emergence of function like locomotion, “completing a cycle.” Is something missing in this description?
The math in the paper looks pretty recondite. But no amount of scholarly dressing can overcome a bad premise. If there is no mention of a design plan, program, or purpose in their model, then their concept of “morphogenesis” cannot extend beyond the repetitive patterns in crystals and currents. Snowflakes — lovely and intricate as they are — present no function beyond falling and melting. The dynamics of currents can lead to standing waves and cycles; laws of nuclear reactions can “give rise to” sustained fission. None of these non-biological cases exhibit the kind of emergence of function the authors are trying to model. (They specifically refer to examples like skeletal muscle and the liver.)
Rather than increasing our understanding, these authors decrease it by reducing it to vacuous concepts of emergence and morphogenesis which, when stripped of programmed design, cannot “give rise to” a feather, much less an Arctic tern.
Source: Evolution News & Views