What do you mean by highly congruent? Can you put a numerical measurement on that? Testing in molecular biology yields a statistical confidence level. Saying Darwin predicted a nested hierarchy is an abstract statement.
http://www.talkorigins.org/faqs/comdesc/section1.html#independent_convergence
In science, independent measurements of theoretical values are never exact. When inferring any value (such as a physical constant like the charge of the electron, the mass of the proton, or the speed of light) some error always exists in the measurement, and all independent measurements are incongruent to some extent. Of course, the true value of something is never known for certain in scienceâall we have are measurements that we hope approximate the true value. Scientifically, then, the important relevant questions are âWhen comparing two measurements, how much of a discrepancy does it take to be a problem?â and âHow close must the measurements be in order to give a strong confirmation?â Scientists answer these questions quantitatively with probability and statistics (Box 1978; Fisher 1990; Wadsworth 1997). To be scientifically rigorous we require statistical significance. Some measurements of a given value match with statistical significance (good), and some do not (bad), even though no measurements match exactly (reality).
So, how well do phylogenetic trees from morphological studies match the trees made from independent molecular studies? There are over 1038 different possible ways to arrange the 30 major taxa represented in Figure 1 into a phylogenetic tree (see Table 1.3.1; Felsenstein 1982; Li 1997, p. 102). In spite of these odds, the relationships given in Figure 1, as determined from morphological characters, are completely congruent with the relationships determined independently from cytochrome c molecular studies (for consensus phylogenies from pre-molecular studies see Carter 1954, Figure 1, p. 13; Dodson 1960, Figures 43, p. 125, and Figure 50, p. 150; Osborn 1918, Figure 42, p. 161; Haeckel 1898, p. 55; Gregory 1951, Fig. opposite title page; for phylogenies from the early cytochrome c studies see McLaughlin and Dayhoff 1973; Dickerson and Timkovich 1975, pp. 438-439). Speaking quantitatively, independent morphological and molecular measurements such as these have determined the standard phylogenetic tree, as shown in Figure 1, to better than 38 decimal places. This phenomenal corroboration of universal common descent is referred to as the âtwin nested hierarchyâ. This term is something of a misnomer, however, since there are in reality multiple nested hierarchies, independently determined from many sources of data.
When two independently determined trees mismatch by some branches, they are called âincongruentâ. In general, phylogenetic trees may be very incongruent and still match with an extremely high degree of statistical significance (Hendy et al . 1984; Penny et al . 1982; Penny and Hendy 1986; Steel and Penny 1993). Even for a phylogeny with a small number of organisms, the total number of possible trees is extremely large. For example, there are about a thousand different possible phylogenies for only six organisms; for nine organisms, there are millions of possible phylogenies; for 12 organisms, there are nearly 14 trillion different possible phylogenies (Table 1.3.1; Felsenstein 1982; Li 1997, p. 102). Thus, the probability of finding two similar trees by chance via two independent methods is extremely small in most cases. In fact, two different trees of 16 organisms that mismatch by as many as 10 branches still match with high statistical significance (Hendy et al . 1984, Table 4; Steel and Penny 1993). For more information on the statistical significance of trees that do not match exactly, see âStatistics of Incongruent Phylogenetic Treesâ.
The stunning degree of match between even the most incongruent phylogenetic trees found in the biological literature is widely unappreciated, mainly because most people (including many biologists) are unaware of the mathematics involved (Bryant et al . 2002; Penny et al . 1982; Penny and Hendy 1986). Penny and Hendy have performed a series of detailed statistical analyses of the significance of incongruent phylogenetic trees, and here is their conclusion:
âBiologists seem to seek the âThe One Treeâ and appear not to be satisfied by a range of options. However, there is no logical difficulty in having a range of trees. There are 34,459,425 possible [unrooted] trees for 11 taxa (Penny et al . 1982), and to reduce this to the order of 10-50 trees is analogous to an accuracy of measurement of approximately one part in 106.â (Penny and Hendy 1986, p. 414)
You can simply go and plug in the number to calculate the significance for any hypothetical situation you want using the Some Statistics of Incongruent Phylogenetic Trees tool. For example, with 15 species, 4 trees (say derived from morphology and 3 genes), and 3 incongruent branches you get a P-value of ⤠1.2969298963520442e-24
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The probabilistic resources of the system. I have not read that in Dembski so youâd have to show me the context. You did not give me probabilistic resources of your system, so I had to go with the universal probability bound of 10^150. But IDists have settled on 10^40 for genomic information. Thatâs an estimate of the total number of genomes possible in the history of life on earth. Doug Axe computed a smaller number, something like 5e26 or something like that, but he never put it in his book and I forget where he said that and what the rationale is behind it.
This always reverts back to the same point that Darwin originally argued; that common descent is simpler to imagine than special creation. Itâs not tested to a number and confidence level.
If homology is defined as observed similarity no one can accuse evolutionary biology of stretching this claim. I donât think it does anything to hurt the theory and will take away the target creationists are shooting at. Thanks for the discussion.
Oh lawd not this hilarious nonsense again. Get a jar, put 200 standard six-sided dice in it, now toss them all on the floor. Youâve now generated a sequence of die-rolls the total improbability of which is beyond what Dembski estimates should be possible to generate in the entire history of the universe.
I canât begin to tell you how unfathomably bunk and stupid Dembskiâs âuniversal probability boundâ is.
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this part from talkorigin is nonsense since mammals for instance already sharing many similar genes in common. thus its not surprising that a tree that was made from a gene from a mammal species will give us the same tree as other gene.
Why should mammals share many similar genes in common? Why should different mammal genes show the same nested hierarchy? I have an explanation. But whatâs yours?
12 posts were merged into an existing topic: SCDâs argument about Cars and Nested Hierarchy
You need several species in order to form a nested hierarchy.
What does that even mean?
The same way Linnaeus did it over 200 years ago. He didnât assume common descent and he was able to recognize homologous structures. We could point to homologous structures shared between cars and trucks without needing to assume they descended from a common ancestor.
So the tested hierarchy does not test the claim that two species share a common ancestor?
It tests the claim that all the species in the analysis share a common ancestor, so it would also test whether any two species you pick out from that crowd also share a common ancestor. Itâs disturbing that after all these years of argument you are still asking such simple-minded questions.
It tests the claim that a group of species shares common ancestors and does not share uncommon ancestors. For example, all apes share a common ancestor, but chimps and humans share a common ancestor that is not shared by gorillas and orangutans.
You canât test for a tree like structure with just two species. Can you show us a tree with multiple branches with just two species?
There are other pieces of evidence for testing the hypothesis that two species share a common ancestor, such as this evidence:
https://biologos.org/articles/testing-common-ancestry-its-all-about-the-mutations
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What is the null hypothesis you are testing against? What data would tell you that a group of animals do not share a common ancestor?
The null hypothesis is generally that the data donât fit a particular tree better than they fit any random tree, i.e. that the data donât have nested hierarchical structure. Now, there are reasons for a lack of structure other than separate creation, so itâs not strictly speaking a null hypothesis separate descent. But if you do reject the null hypothesis, that definitely supports common descent, as there is no other reason for the presence of structure.
Then again, Theobald 2010 actually did have a null hypothesis of no common descent. Why do you never remember anything that weâve been over before?
Let me link Kooninâs critique of Theobald 2010 again.
Conclusion
A formal demonstration of the Universal Common Ancestry hypothesis has not been achieved and is unlikely to be feasible in principle. Nevertheless, the evidence in support of this hypothesis provided by comparative genomics is overwhelming.
@colewd, you forgot Theobaldâs reply to Koonin:
K&W make three distinct claims based on their simulated data:
(1) the model selection tests prefer UCA solely due to the high similarity of the protein sequences, regardless of genealogical history,
(2) their simulation corresponds to a convergent, independent ancestry model, and therefore the model selection tests err in choosing common ancestry for the simulated sequences,
(3) the demonstration of UCA is dependent on the assumption that proteins with highly similar sequences share common ancestry.
All of these claims are incorrect, and I consider each of them in turn below.
From this paper.
You are welcome to explain to us how Theobald is mistaken.
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As well as you are welcome to explain why Koonin is mistaken.
When weâre done we still have no real explanation for the novelty in eukaryotic cells except that it all is in the common ancestor like you once suggested. In my opinion sequence similarity does not tell you anything about ancestry if design is considered a viable alternative. If not then of course common descent wins by default because you have to explain the sequence similarity and we have nothing else yet to compete with this. Itâs just a limited explanation at best.
We are really not testing anything of significance either way unless we can demonstrate cell division and variation creating significant cellular novelty. A test of the mechanism itself vs looking at a pattern and making an inference without considering separate creation as Darwin did.
Theobald already did.
And Koonin had explained why Theobald was mistaken. I will offer you a draw 
Universal common ancestry is a claim that initially cell division and sexual reproduction plus natural variation explain the diversity of life. Do you agree? If so do you really think Theobald tested this claim?