Hennig on spatial characters
John Grehan
jrg13 at PSU.EDU
Thu Jul 4 10:54:02 CDT 2002
Pierre wrote a while back
But I don't remember that Hennig suggested to put characters of spatial
location inside the data matrix of *taxa + inheritable biological traits*
in order to infer the phylogeny. I remember Hennig reasoning in terms of
"oriented dispersal" when a morphocline for some characters fitted to a
series of spatially oriented locations for these taxa. This can be extended
from morphocline for a character to phylogenetic relationships between taxa
(which the morphocline was supposed to fit).
I admit to not being a scholar of Hennig's works so I would appreciate any
insight to my current understanding of Hennig's use of geographic
characters. What I was referring to is his 'vicariance criterion'. In the
Craw et al book we quote Hennig as follows:
"The geographic distribution of organisms provides another way of checking
the reliability of systematic results. Following the principle of
reciprocal clarification it is possible to reverse order to use geographic
distribution for determining the phylogenetic relationships themselves. In
general, two taxonomic groups that standing spatial vicariance relationship
to each other are more closely related than either is to any other
taxonomic group".
Here at least is one explicit model for generating spatial characteristics.
Agreed, this is not combining spatial and biological data at the outset,
but using one to check on the other. I applied Hennig's procedure (without
being aware of Hennig's formulation at the time) with some moths where two
vicariant genera were geographically adjacent to each other. I proposed
that they were more closely related to each other than to many other
members of their family. At the time all they obviously shared was a common
feeding mode as there were no morphological character studies. Subsequently
morphological character analysis corroborates the prediction although a
thorough character analysis admittedly has yet to be produced.
John Grehan
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