Dear Christy,
I'm not sure I understood the part on doing it "using specimens and
not species".
As you know, Mitteroecker & Bookstein (2011) suggest between-group
principal components. Personally, I have used this technique multiple
times (e.g., Fruciano et al 2014 - Biological Journal of the Linnean
Society; Fruciano et al 2016 - Ecology and Evolution), and I'm very
happy with it. I see no special reason, in normal situations, to show
both between-group PCA and CVA ordinations as the ordinations of the
latter show overly "optimistic" separation of groups.
Having said that, species/group means are means so if that's what
you're visualizing shape change as differences between group means it
doesn't really matter (notice, for instance, how MorphoJ produces,
under the module "Discriminant Analysis" a plot of differences between
group means).
Perhaps, if the number of your groups is small enough you want to
consider a visualization like the one we did for bats (Schmieder et al
2015 - Plos One; Fig. 3) where we show both shape change associated
with between-group PC1 and each species mean compared to the grand
mean. Pairwise comparisons of species/group means are another
alternative, depending on the number of groups and, most importantly,
the point you want to make.
I hope this helps,
Carmelo
--
Carmelo Fruciano
Postdoctoral Fellow - Queensland University of Technology - Brisbane,
Australia
Honorary Fellow - University of Catania - Catania, Italy
e-mail c.fruci...@unict.it
http://www.fruciano.it/research/
Christy Hipsley <chips...@museum.vic.gov.au> ha scritto:
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
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