Dear Morphmet-ers, I'm seeking advice on methods for visualizing shape features that distinguish multiple groups using GM. I know CVA has fallen out of favor for a number of reasons discussed here - e.g., more variables than groups, nonisotropic variation:
Mitteroecker, P., and Bookstein, F. 2011. Linear discrimination, ordination, and the visualization of selection gradients in modern morphometrics. Evol. Biol. 38:100–114. Klingenberg, C. P., and Monteiro, L. R. 2005. Distances and directions in multidimensional shape spaces: Implications for morphometric applications. Syst. Biol. 54:678–688. Although given these limitations, is it really expected to give completely false results regarding the visualization of shape changes? In my study sytem, I show that ecological groups have statistically different cranial shapes, using both Procrustes ANOVA and PGLS. Now I simply want to visualize what the main features are that distinguish them, preferably using warps or wireframes, so that those changes must be directly relateable to the original landmark coordinates. I did that using individual specimens instead of species means, so I have 161 individuals vs 144 variables (48 landmarks*3D). I also did a between-group PCA on the species means which shows the same pattern, so is it technically "wrong" to show both? Thanks for any feedback on this issue, and I would appreciate to hear any alternative methods that people might use. I use MorphoJ and Geomorph for analyses. Best, Christy -- MORPHMET may be accessed via its webpage at http://www.morphometrics.org --- You received this message because you are subscribed to the Google Groups "MORPHMET" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected].
