maybe this has been discussed already a lot but I would still dare to ask:
To me it seems that for taxonomists, the use of individual partial warps comes largely from the need to interpret the CVA analysis and find the most informative characters to differentiate the species. These variables later can be used in further taxonomic work. In the "traditional" morphometrics one can add/remove variables one by one and leave the most informative ones - a widely used practice, I believe. With geometric morphometrics, for the mathematical reasons discussed before, one will conduct CVA on relative warp scores The results will tell that the most important variable for differentiating the two species is RW5. But this is not a variable a taxonomist would like to use. OK, I can go back to RW analysis and explore shape variation related to RW5. Still it is speculative, compared with the rigorous statistical procedure of selecting "traditional" variables by their within to among group variance (or vice versa?). One can also remove a certain part of landmarks manually and do the analysis again, but this is also subjective. Probably it does not make much sense to choose the most important landmarks, because the shape is analysed as a whole, in relation to other landmarks? There may not be one or two "the most informative" landmarks, which could be informative alone? Yet, I wonder whether there is there any accepted statistical procedure to select the most useful characters (landmarks) for species differentiation? Thanks, Asta Audzijonyte -- Replies will be sent to the list. For more information visit http://www.morphometrics.org
