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Re: Martin 2004 critique (somewhat lengthy)

Sorry for the delay, I had been timed out...

----- Original Message -----
From: "Jaime A. Headden" <qilongia@yahoo.com>
Sent: Saturday, June 04, 2005 4:01 AM

David Marjanovic (david.marjanovic@gmx.at) wrote:

<Parsimony and likelihood methods -- together: cladistics -- don't make any
sense except in phylogenetics. Neighbor-joining, UPGMA, WPGMA and so on,
on the other hand, are not cladistics -- they are phenetics. It follows that
cladistics is the tool to find a phylogeny.>

One can apply parsimony without any sort of math, since its an essential
logical argument, and one can apply likelihood and its many maths, without ever
trodding on the field of phylogeny recovery. That they are used to analyze data
to produce phylogeny is only a logical output of their existence.

That's all true. But if you make a tree using parsimony, that tree can only be a phylogenetic hypothesis. Sorry for having dropped the tree aspect.

Likelihood: "Likelihood is the hypothetical probability that an event that
has already occurred would yield a specific outcome. The concept differs from
that of a probability in that a probability refers to the occurrence of future
events, while a likelihood refers to past events with known outcomes." From
Mathworld: http://mathworld.wolfram.com/Likelihood.html

In the case of phylogeny, it's "not the probability of the tree given the data, but the probability of the data given the tree". Because a phylogenetic tree represents the outcome of a series of events, while a phenogram doesn't, likelihood approaches can be applied in phylogenetics but not in phenetics.

As I also stated before, it's possible but often ignored to use parsimony or
likelihood methods to test datasets that are designed to produce a phylogenetic
hypothesis, but applied to non-phylogenetic criteria. Examples include studying
gene recombination, gene family origins (which often require NO phylogeny in
testing bacterial lateral transfer to study how recombination events operate in
steps to produce new genes without any phylogenetic "splitting" occuring), even
languages, which operate much the same way above.

These examples of course involve phylogeny -- the phylogeny of genes (as opposed to entire organisms) in the first case, the phylogeny of languages (although in these lateral "gene" transfer of words, but also grammar and sounds, is so common that programs should be used that can generate trees with some degree of reticulation).

They can also be used to test
absolute phenetic similarity, without any phylogenetic inferrence involved, but
which may then be applied phylogenetically.

But for this you can't use parsimony or likelihood methods. For this you need phenetic methods. Probably UPGMA is the method of choice (e. g. for measuring the similarity of different faunas -- a valuable tool of paleoecology).

As I stated in my first reply, was that cladistics is the study of how parts
of data sets are compared to other parts of the same data sets, and that is all
these programs are capable of doing. Any phylogenetic extension of this data is
secondary and external to the programming.

Cladograms, as opposed to phenograms, make no sense except if interpreted as phylogenetic hypotheses.

Further in his reply, David seems to have misconstrued an innate similarity
between phylogeny and phenetics. While they seem related, it should be noted
that shared descent may utilize an observable phenetic paradigm, but the
phenetics is separate from the association of commonj descent. 

Er... yes, and cladistics is not phenetics...

I think we two don't understand each other. I thought _you_ had misconstrued an innate similarity between cladistics and phenetics, while they don't share much more than the use of math, and differ greatly in the fact that cladistics is phylogenetics while phenetics is not. ~:-|

Quoting from above:
"The maximum parsimony method is a typical representative of the cladistic
approach, whereas the UPGMA method is a typical phenetic method. The other
methods, however, cannot be classified easily according to the above
criteria. For example, the transformed distance method and the neighbors
relation method have often been said to be phenetic methods, but this is not
an accurate description. Although these methods use similarity (or
dissimilarity, i.e., distance) measures, they do not assume a direct
connection between similarity and evolutionary relationship, nor are they
intended to infer phenetic relationships."

If "neighbors relation method" means "neighbor-joining" (I'm just guessing), then I'd say that it _is_ intended to measure phenetic similarity ("relationship" makes no sense here) -- although the phenetic similarity of characters that are thought to be phylogenetically informative. It's sort of an attempt to cheat oneself. (I hasten to add, however, that neighbor-joining [very fast!] and parsimony [slow!] give the same unrooted tree when there's sufficiently little homoplasy in the data set -- but the amount of homoplasy can't be preassumed, it must be found out by using phylogenetic methods.)

Indeed, one can observe the similarities among cars and arrive at a cladogram
of phenetic similarity 

This is _not_ a cladogram, but a _phenogram_.

among all car makes ever made and aquire a "tree" that
has nothing at all to do with phylogeny (cars don't breed) which may even group
most cars by their makes or even years (the Nissan Z series, perhaps, or Ford's
early models). What this output is not, however, is an hypothesis of common
derivation

Indeed not. It is a measure of phenetic similarity. It is a phenogram and not a cladogram -- because no attempt is made to tell plesio- and apomorphies apart and to treat them differently.

I can, for example, create a phenetic diagram
by grouping colors by their frequencies, and arrive at a (theoretically)
sequentially nested phyllogram, or a "bush", which relates only to closeness
of the numbers to one another. 

That's not a phylogram but (again) a phenogram.

Such is the same with gene trees.

Depends on the method which found them.