Question: Is the key problem that new species are seldom or never observed?
| September 25, 2006 | Posted by O'Leary under Intelligent Design |
A key problem with the argument over Darwinian evolution (evolution by natural selection acting on random mutations) is that so few actual examples of speciation (new species forming) have ever been observed that we really have no way of knowing for sure whether Darwin had the right idea.
I suspect that explains precisely why acceptance of Darwinism is so often treated as some kind of loyalty test for support for science in general.
That is, the Darwinist is taking a great deal on faith. And those Darwinists who also happen to be fanatics by temperament behave just as other fanatics do when they think they have found certainty: They go about like bulls looking for a fight - demanding that you too, brudder, better get saved. Otherwise, you face udder damnation …
As Jonathan Wells noted in his controversial Politically Incorrect Guide to Darwinism and Intelligent Design,
So except for polyploidy in plants, which is not what Darwin’s theory needs, there are no observed instances of the origin of species. As evolutionary biologists Lynn Margulis and Dorion Sagan wrote in 2002: “Speciation, whether in the remote Galapagos, in the laboratory cages of the drosophilosophers, or in the crowded sediments of the paleontologists, still has never been directly traced.” Evolution’s smoking gun is still missing.
- Jonathan Wells, Politically Incorrect Guide to Darwinism and Intelligent Design , p. 55, quoting Lynn Margulis and Dorion Sagan, Acquiring Genomes: A Theory of the Origin of Species (New York: Basic Books, p. 32)
In fairness to the fanatical Darwinist, unlike the Islamic extremist, he is only trying to separate doubters from their careers, not their heads.
That said, why not insist that at least one thousand obvious examples of speciation in animals – where we have a lot of information about what happened - be accumulated and studied, so that we have a study population to work with, to assess various theories of the origin of species?
 If we can’t find that within the next century, we need to assess just what role Darwinism is playing in science or society, because shedding light cannot really be the role.
125 Responses to Question: Is the key problem that new species are seldom or never observed?
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Recip Bill wrote:
Here’ s the quote that Bill included.
“To support their contention of the implausibility of adaptive protein evolution by Darwinian processes, Behe and Snoke started with an ad hoc non-Darwinian model with a highly restrictive and biologically unrealistic set of assumptions. Such extreme starting conditions guaranteed that the probability of neofunctionalization would be reduced to a minimal level. An alternative approach, adopted here, is to rely on a set of biologically justified premises and an explicit population-genetic framework.â€Â
The reason that Lynch considers their model “unDarwinian”–a reason you didn’t bother mentioning–is the fact that Behe and Snoke’s model doesn’t treat the first, of a minimum of two, amino acid (a.a.) substitution to be “advantageous”. Prescinding from the fact that Darwin knew neither about genetics nor nucleotide, nor proteins, Behe and Snoke chose that scenario for their model because the fact is, of course, that most mutations are known to be deleterious. (They, afterall, were looking for a “realistic” model; not necessarily a Darwinian one!) Lynch insists that, a la Darwin, each step of the evolutionary process must include an intermediate that is “advantageous”. And, so, he develops his own model. Well, why don’t we look at the results of his own model.
I notice that Figure 3 of his paper shows that a population size of one million, (10^6), requires, for a two a.a. substitution, with a selection pressure of 0.01, 20 billion (10^8) years to bring about this mutation. And what is this mutation? It is a protein molecule that has substituted a “peptide bond” for a covalent bond. 20 billion years to accomplish that!!! Now what is the transition time from the common chimp to man? 5 million years. And how many chimps live in a community of chimps (i.e., interbreed)? On average, 100. So, if we had 10,000 communities of chimps all breeding together at once, it would take 20 billion years to form a “peptide bond” in a protein. So, when I said that the paper was a “devastating blow to neo-Darwinism”, I should have added, “as is Michael Lynch’s paper.”
In his response to Lynch’s paper and critique, Behe notes that the figure both of them (i.e., both Behe and Lynch) used for the rate of ‘duplicated genes’ appears, due to a new paper, to be on the high side (by a few orders of magnitude), thus rendering both their devastating results to be on the optimistic side of things.
I too suggest reading the papers closely, and understanding the implications of the numbers they arrive at, and you’ll see that is not I who is “fulminating”.
Recip Bill:
Whether this model of Behe and Snoke (as well as Lynch’s) represents “one of the most difficult pathways imaginable” or not, it nonetheless is the only route to the origination of true genetic information that I–or anyone else–knows of. Transposons, recombination, and gene duplication all simply move nucleotide sequences from one location to another. Now chimps and humans share 97% of the same genes. But how did the other 3% arise?
I suggest you ruminate what I’ve written.
Chris Hyland:
I did a simple google search. It immediately popped up. Here it is: http://darwin.gruts.com/docs/origin-1/diagram/
I don’t agree with Elsberry’s analysis, and, hence, his numbers. His equation is:
EFR = (NSTP * NSPP * AP * SEVR * FSDP)
and
ETF = EFR * OFS
where EFR is the “expected fossil ratio”,
NSTP is the “natural selection time proportion”,
NSPP is the “natural selection population proportion”,
AP is the “area proportion”,
SEVR is the “subsidence vs. elevation variation ratio”,
FSDP is the “formation to species duration proportion”,
ETF is the “expected number of transitional fossils”,
and OFS is the number of “observed fossil species”.
Darwin, referring to his diagram, writes:
“In the diagram, each horizontal line has hitherto been supposed to represent a thousand generations, but each may represent a million or a hundred million generations, and likewise a section of the successive strata of the earth’s crust including extinct remains. . . the diagram throws light on the affinities of extinct beings, which, though generally belonging to the same orders, or families, or genera, with those now living, yet are often, in some degree, intermediate in character between existing groups; and we can understand this fact, for the extinct species lived at very ancient epochs when the branching lines of descent had diverged less.”
Thus, we can, per Darwin, choose these intervals to be up to a 100 million years old. If that’s the case, there’s no reason for Elsberry to include the NSTP since obviously over such a long period of geologic time natural selection will have taken place. This makes NSTP now equal to 1.
NSSP is meant to account for the fact that NS occurs only on a few “inhabitants” at a time (Darwin’s words); however, again consulting Darwin’s own diagram, we see that over the time frame he indicates (that is, at every step of the way beginning with time period I, and then II, and then III, and so forth) the average number of “diverging” species shown on his diagram(which are “intermediate” from the preceding interval–remember, again, these intervals are now, with Darwin’s permission, 100 million years long) are, on average (from IX down: 5/7; 6/8; 8/10; 6/9; 5/9; 4/7; 4/7; 4/9; 3/11; 2/11) 0.53. But, let’s be more conservative and say 0.4.
For AP, Elsberry shows 0.1. But if we look at Darwin’s quote we see that he was talking about the fact that in his own day the fossils that had been recovered were mainly from just Europe. (The fossil record was somewhat sparse at the time, and Darwin was counting on a more ample fossil record to buttress his theory. That didn’t happen.) But that is no longer true. Fossils have been found in Antartica, China, Australia, etc. , etc. So, if a main branch had an extensive range, there’s an extremely good chance that almost all of their fossil remains had a chance of showing up. So, the AP is much closer to 1.0 than it is to 0.1. Again, fairly conservative, let’s make this 0.85.
SEVR is something that is hard to quantify. But, again, we’re not living in Darwin’s time. Fossils have been found most everywhere. And so whether there was subsidence or not matters very little. So, again, conservatively, let’s make this number, what, 0.5? OK, I guess that’s as good a guess as you can make.
FSDP, Elsberry tells us, is o.5. It’s anybody’s guess. Although we’re now dealing with a very long time interval, nonetheless, the “intermediate” forms that Darwins indicates on his diagram don’t have to be of a fine character. So, it sort of balances out. So let’s use 0.5.
Now it’s time for math: EFR=(NSTP*NSPP*AP*SEVR*FSDP)
=1.0*0.4*0.85*0.5*0.5=0.085
and EFP=EFR*OFS=0.085*250,000 fossil species, =21,250 fossil species!!!
I guess Stanley Gish was right!
Believe it was Scott who posted:
That the information is pre-coded to abruptly unfold new species at given intervals. Like a computer algorithm. Couldn’t this make sense since we find code wrapped in code, at the cellular level? And wouldn’t this be more consistent with the fossil record we observe?
I think this is a very interesting area and would appreciate further thoughts besides these…
1) Speciation occurs, brought about by pre-coded instructions, hence the lack of transitional fossils. Also overcomes the problem that if n=1 for a new species where there is no one to mate with. (this is known to cause depression and suicide, leading to early extinction.)
2) Descent with modification occurs, brought about by pre-coded instructions, hence similar structures, similar building blocks, similar DNA in some cases. As noted before, descent with modification does not require a RM & NS causal model.
3) Irreducible complex systems and complex specified information exist because pre-coded information contains the CSI and instructions to build the IC structures.
4) Mutations occur, but generally have a negative effect on the pre-coded information, much like a random error in a software program is seldom a useful feature.
5) Natural selection occurs, generally preserving the original coded information and weeding out negative mutations.
Note:
- This in an inference to intelligence, not the supernatural.
- This model does not deny mutations and natural selection, but places them into the causal category where we observe them performing today.
- Micro evolution exists caused by both pre-coded information and mutations
- Macro evolution exists caused by pre-coded information.
Here is a listing of features compiled by Hugh Ross that favor ID methodology and seem to fit in well with this mode.
Chicken-and-egg systems: Many biochemical systems are called chicken-and-egg systems (after the old conundrum, “Which came first: the chicken or the egg?”) because they consist of components that require each other for the components to be produced. For example, ribosomes make proteins, yet they in turn consist of proteins. Proteins can’t be formed without ribosomes (proteins), and ribosomes (proteins) can’t be made without proteins!
Fine-tuning and high precision: Long recognized as design features, fine-tuning and high precision traditionally signify a device’s superior engineering and craftsmanship. Many biochemical structures and activities depend on precise location and orientation of chemical groups in three-dimensional space, just-right chemical composition, and exacting chemical rates. Molecular fine-tuning is a defining property of life’s chemical systems.
Molecular motors: These protein complexes are found inside the cell and are literal machines. Many possess an eerie resemblance to man-made machines. A new special issue of Journal of Physics: Condensed Matter edited by Joseph Klafter and Michael Urbakh contains invited papers from some of the world’s greatest experts on molecular motors. Macro-scale thermodynamic engines convert the random motion of fuel-produced heat into directed motion. Such engines cannot be downsized to the nanometer scale, because thermodynamics does not apply to single atoms or molecules, only large assemblies of them. A great challenge for the field of nanotechnology is the design and construction of microscopic motors that can transform input energy into directed motion and perform useful functions such as transporting of cargo. Today’s nanotechnologists can only look in envy at the biological world, where molecular motors of various kinds (linear, rotary) are very common and fulfill essential roles.
Biochemical information systems: Experience teaches that intelligible messages come from intelligent sources. The cell’s biochemical machinery (proteins, DNA, RNA, and oligosaccharides) is information-based and therefore its logical to infer that it comes from an intelligent source.
Genetic code: Encoded information indicates intelligence beyond the mere presence of information. An intelligent being must develop and employ the code. The cell’s information exists in a coded format that defines the cell’s information systems.
Genetic code fine-tuning: The rules that comprise the genetic code are better designed than any conceivable alternative code to resist error caused by mutations. This fine-tuning powerfully indicates that a superior intelligence developed the cell’s information systems.
Preplanning: Planning ahead indicates purpose and reflects design. Many biochemical processes consist of a sequence of molecular events and chemical reactions. Often the initial steps of these pathways elegantly anticipate the final steps.
Quality control: Designed processes incorporate quality-control procedures to ensure efficient and reproducible manufacture of quality product. Many biochemical operations employ sophisticated quality control processes.
Molecular convergence: Several biochemical systems and/or biomolecules found in different organisms are structurally, functionally, and mechanistically identical. Yet they appear to have independent origins. Given the complexity of these systems, it is not rational to conclude that blind, random, natural processes independently produced them.
Questions:
What areas of natural history don’t fit well with this model?
Are there other important areas or bodies of evidence that don’t fit will with NDE but do with this model?
Thanks, I’ve enjoyed reading everyone’s posts on this topic, all 122!
Lee Penick
Lee asks, vis front loading, “What areas of natural history don’t fit well with this model?”
If I understand the ‘front loading’ hypothesis correctly, it proposes that, for 2 thousand million years, each of an uncountable number of single-celled, prokaryotic organisms, lacking nuclei, carried within information sufficient not only to code for its own development, but sufficient to specify the development of every one of the millions of descendent species that followed over earth’s subsequent history, including every multicelluar plant and animal species living today as well as the 99.9 percent that are now extinct. The overwhelming majority of this information was not expressed as phenotype, and hence was not subject to stabilizing selection – yet remained undegraded over eons of time and practically infinite numbers of replications. Packed within each prokaryote were adaptations to countless future successions of contingent natural geographic, environmental, climatic, and ecological contexts, awaiting triggering signals/circumstances for their expression, including innumerable adaptations of one organism to another in predator prey, symbiotic, parasitical, and other relationships – all to be triggered in synchrony. And on and on.
This is proposed because some do not believe that natural selection can shape complex adaptations – too improbable.
RB
too improbable.
An argument from incredulity? Shame on you. At least you know how I feel about abiogenesis as the given answer to the OOL problem.
The answers to your objections become more apparent only when you first take design as a given. Since FL is a design theory we can do that. Design is that which is to be proven.
So from a design theoretic view:
-simpler first is not an axiom, designs can begin at any arbitrary level of complexity
So in answer to your question about prokaryotes carrying all the unexpressed genetic information we must first ask what evidence argues against a complex eukaryote first and bacteria cleaved off from that.
I can’t find any compelling evidence that prokaryotes had to come first. The fossil evidence from 3.5bya is pretty slim. All it tells us is at best is that bacteria were found then. If there were populations of say ameoba 3.5bya that were the designed entry point should we expect the fossil evidence to be elusive? I think so. Would an ecology of amoeba and bacteria work out on the early earth? Sure. Vast numbers of photosynthetic bacteria as primary producers with a much smaller number of much larger amoeba feeding on them. It still happens to this day. What also still happens to this day is an amoeba species with a measured amount of DNA 200 times that of the human genome. Amoeba dubia. Look it up. Keep in mind that we’ve only measured the amount of DNA in only a tiny sampling of what’s out there yet to find extant. At least, dubia’s existence means an organism can successfully carry around that much DNA and still be a survivor.
Now to your objection about carrying all that unexpressed DNA around and no selection pressure to keep it accurate. Once again, if we look at it from a design theoretic view, we must ask if there are other reasonable ways the unexpressed genome can be preserved. Sure there are. We use error detection algorithms in computer data storage of any arbitrary reliability we need. It’s a tradeoff between replication speed and reliability is all. Not a problem. DNA replication is accurate now to some one in 10^7 through one in 10^9 with prokaryotes the more mutagenic and that’s before selection does anything. And just in the small number of organisms we checked. Improving that error rate by several orders of magnitude isn’t really difficult. In fact the same mechanisms that get the error rates above can be employed redundantly so there’s not even anything we haven’t already observed, just more of it.