|email - October 2015|
Caffeine kills harmful insects—but not bees.
We love people like Mick who read and then think for themselves. Just hours after posting our last newsletter, Mick sent us this email.
Subject: Caffeine and insects
I thought I'd look into caffeine being an insect-killer. Reports say that it indeed kills them, but blogs.scientificamerican.com/scicurious-brain/plants-give-bees-a-caffeine-buzz/ talks about how citruses have caffeine in their nectar, instead of the usual leaves and fruit. Bees can handle it. The one (?) kind of insect that is helpful to plants is resistant to caffeine.
One big surprise is that the blog doesn't try to use this to prove evolution.
There are two things we love about Mick’s email. The first, as we have already mentioned, is that it tells us that it inspired Mick to do some research. Our goal is to inspire thought. We don’t want people to believe everything they are told without question.
The second reason we love Mick’s email is that it gives us an excuse to address the issues about caffeine and evolutionary trees that we didn’t have space for in the last newsletter.
Mick independently noticed something we wanted to mention last month—specifically that we get caffeine from tea by brewing its leaves, but we get caffeine from coffee by brewing its beans. So, the ability to produce caffeine allegedly evolved in two different parts of different species. Furthermore, Mick has discovered that yet another, even more distantly “related” species, supposedly evolved to produce caffeine in their nectar, a third part of a plant.
There is also something else we only hinted at in last month’s newsletter. The hint was, “Suppose B1 has descendents C1 and C2, and B2 has descendents D1, D2, and D3.”
Here’s another hint. Queen Elizabeth just became the longest reigning British monarch. Here is a diagram of Her Majesty’s family tree which we found on-line. 1
Here is the caffeine cladogram from last month’s newsletter, rotated 90 degrees to make it easier for you to compare it to the Royal Family.
We have teased you long enough, hoping you will figure out for yourself why cladograms do not produce correct relationships. Here’s the proof.
Cladograms, like the one showing the relationship between coffee, tea, and cacao, are produced by a computer program. The way to test a computer program is to input data where the correct answer is known ahead of time to see if the program produces the correct output.
For example, to test a missile simulation program one has to fire a missile, track it with a radar, and use telemetry to send the missile’s guidance commands back to a ground station where they are recorded. Then the recorded guidance commands are used as the inputs to the missile simulation program to see what trajectory comes out. If the simulated trajectory doesn’t match the trajectory measured by the radar, then the simulation is wrong.
If you fed the genetic data from all the members of Britain’s Royal Family into the computer program used to produce the cladogram of plants above, it would not produce the correct family tree.
How can we be sure the program would not produce a correct genealogy for the British Royal Family? Because the algorithm is obviously flawed. The way the program is written, Queen Elizabeth would have to be the sister or cousin of Prince George, which is obviously incorrect.
How do we know that? The algorithm is clearly written using the false assumption that all living individuals are brothers, sisters, or cousins, and all their parents, grandparents, aunts, and uncles are deceased, unknown ancestors. There is no way the program could correctly tell us that Queen Elizabeth is the matriarch of the Royal Family because the algorithm is designed in such a way that it can’t produce the correct output no matter what the input is.
The program would compare the DNA of the 28 members of the Royal Family and determine which two members match most closely (using matching criteria which might not even be correct). It would then produce a mythical ancestor with a blend of the characteristics of the two closest matches. Then the program would repeat the process, comparing the 26 remaining living members plus the newly created mythical ancestor (a total of 27 individuals) to see which are the most similar, producing another mythical ancestor. The program would continue to loop through the ever decreasing data set, creating mythical ancestors of the two most similar individuals (real or imagined) until all the pairs have been established. The output would then be printed in the standard cladogram shape, not the unique shape of the Royal Family Tree.
Our hint last month was, “B2 has descendents D1, D2, and D3.” The cladogram program is written in such a way that the unknown ancestor always has two direct descendants. Queen Elizabeth has four direct descendants. That alone is proof the cladogram program can’t possibly produce a correct relationship tree for the Royal Family.
The thing to remember about computers is that they don’t have any common sense. They just blindly perform the calculations, doing what they are told to do. It would never occur to a computer that some of the living individuals are parents or grandparents, or that a couple might have some number of children other than two. If the programmer told the computer that none of the data came from an ancestor, all the ancestors are unknown, and that all the unknown ancestors had exactly two children, the computer doesn’t question that prejudicial assumption. It just fits the data into the structure assumed to be correct by the programmer using “optimal parsimony.”
Since the cladogram program doesn’t produce the correct answer when we know what the correct answer is, why should we believe it produces the correct answer when we don’t know what the correct answer is?
The Deep Green project used genetic data to produce a cladogram that “rewrote” the evolutionary history of flowering plants.
For plant taxonomists, the new data strike a blow to the foundation of their discipline … because many plants presumed by their appearance to be closely related—such as the water lily and the lotus—are in fact quite different genetically. … Moreover, Mishler says, the brown, red, and green plants each arose independently from a common single-celled ancestor and thus deserve their own kingdoms. Overall, he claims, at least half the [accepted] Linnaean classifications are wrong. 2
Since the cladogram didn’t produce the accepted answer, other evolutionists said,
In response to the article “Deep Green rewrites evolutionary history of plants” by Kathryn S. Brown … The new cladistic analyses of plant evolutionary relationships deserve to be reported, but it is vital that all realize that every cladogram is a hypothesis and, perhaps more important, that such hypotheses depend on both the algorithm used to generate the hypotheses … and on the character matrix used as the basis of the analysis … . The character matrices are themselves evolving rapidly and are affected by additions of new characters, such as new gene sequences, and by the selection and definition of morphological-structural characters. Thus, the phylogeny presented as the basis for a radical shift in our understanding of green plant relationships is a transitory hypothesis that likely will be replaced by other different hypotheses. 3
You were probably taught a simplified, incorrect story about how evolution occurs. Most people were taught that a new species arises when one breeding pair had a mutant offspring that was more suited for survival. The descendants of that mutant offspring (that is, the new species) thrived, driving the normal offspring (the old species) to extinction. Creationists try to debunk this oversimplified, incorrect explanation of evolution by saying, “If man evolved from monkeys, why are there still monkeys?” The evolutionists turn this false argument back on the creationists by saying that creationists don’t really understand how evolution works.
Humans did not evolve from monkeys. Humans are more closely related to modern apes than to monkeys, but we didn't evolve from apes, either. Humans share a common ancestor with modern African apes, like gorillas and chimpanzees. Scientists believe this common ancestor existed 5 to 8 million years ago. Shortly thereafter, the species diverged into two separate lineages. One of these lineages ultimately evolved into gorillas and chimps, and the other evolved into early human ancestors called hominids. 4
How do evolutionists come to this conclusion? Obviously, if the new species drives the old species to extinction immediately, then the number of different living species can’t increase. That is, the old species is simply replaced by new species, so the number of living species would remain the same. Evolutionists need to explain how the first living species evolved into the innumerable species living today.
Evolutionists are forced to believe that the new species doesn’t drive the old species to extinction immediately. The old species has to hang around long enough to beget another new species, too, and then the old species goes extinct.
But why couldn’t the old species, like Queen Elizabeth (begging Your pardon, Your Majesty) have four descendants? Why just two descendants? Or, why can’t the old species have Elizabethan longevity and still be living today, along with multiple descendents?
The answer to these questions goes back to gene dilution and Darwin’s basic assumption of survival of the fittest, which is equivalent to extinction of the less fit.
If the new species isn’t sufficiently better to drive the old species to extinction, the novel mutation will rapidly disappear from the gene pool because of gene dilution.
The first parent with the mutant gene (mutant allele, for the nit-pickers) has only a 50-50 chance of passing that mutant gene to its child because half of a child’s genes come from the normal parent, and the other half come from the mutant parent. Therefore, only half of the children in the first generation are capable of passing the gene along. Statistically, only half of their children will get the new gene, so 1/4 of the second generation will have the mutant gene, and 1/8 of the third generation will have it—unless natural selection biases the percentages.
If the new gene doesn’t provide a sufficient survival advantage, the odds are that after several generations a very small percentage of the population will have the gene. That, coupled with the fact that more creatures are born than reach reproductive age, makes it statistically likely that all the individuals with the new gene will sooner or later be eliminated from the population.
On the other hand, if the new gene provides a great survival advantage, all the individuals without the gene will quickly go extinct.
For the Theory of Evolution to work, the mutation has to fall into the Goldilocks Zone, where the mutation has enough survival advantage to drive the original species to extinction, but doesn’t cause the original species to go extinct before mutating into a second time, and doesn’t drive that second mutation to extinction either. (The second mutation has to fall in the Goldilocks Zone, too.)
That’s why the cladogram algorithm is based on the assumption that each species mutates twice before going extinct.
(We are just telling you what the assumption is and why that assumption is made. Don’t ask us to defend the evolutionary assumption! )
Cladograms produce nice, neat, impressive- looking evolutionary relationships—but the results are often nonsense! The independent evolution of caffeine and results of Deep Green are just two examples in this month’s newsletter. Last month, the genetic analysis of the octopus genome was another example. The octopus geneome brings us to this month’s second Email column.
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2 Kathryn S. Brown, Science, 13 August 1999, “Deep Green Rewrites Evolutionary History of Plants”, pp. 990-991, http://www.sciencemag.org/content/285/5430/990.full?sid=18f8fd9f-ad7a-4e83-9ffa-e96d375028d4
3 Niklas, et al., Science, 10 September 1999, “Early Plant History: Something Borrowed, Something New?”, p. 1673, http://www.sciencemag.org/content/285/5434/1673.2.full?sid=9efbda76-4f55-4f24-b5eb-d914bdf4abc3