Damian,

 It is an interesting question and a very common one, and I have some 
suggestions (which I think will cause a few other people to chime in). 
However, before you focus too much on whether you need to consider the 
issue of what to do when you have seperate shape ~ size relationships 
across different groups or species, it is worth asking (beyond just 
significance testing) whether any differences in those relationships are 
meaningful across the range of observed sizes in your data.  There are (at 
least) two points I suggest considering.

1 - If you have sufficiently large sample sizes, truly trivial differences 
in the "slope" (really the vector of coefficients associated with the size 
predictor) may be significantly different. So a common thing to examine 
next is whether the direction of effects are that different. There are a 
variety of ways of examining this, but perhaps the easiest is examining the 
vector correlation (or the angle which can be derived from the correlation) 
between the allometric vectors for species A and B. If the vector 
correlation between them is "close" to 1 (or the angle close to 0), then 
you be able to assume common allometry. There are a few things to consider 
along with this, but this is a good starting place. One thing that is hard 
to pin down is how "close" to 1 is "close enough". This can depend on the 
range of sizes within and among species among other considerations. If you 
were working on Drosophila wings I can tell you from experience that 
generally above about 0.93  or 0.95 and you are probably ok making this 
assumption, but I am not prepared to generalize this.

2 - As always, just as a double check, did you account for the effects of 
phylogeny in the assessment? If not, take care about what the 
"significance" really means.

3 - In general for ontogenic or evolutionary allometry, it is generally 
recommended to use logCS. Hopefully you have done this. The effect of this 
means that you are examining proportional differences, not absolute 
differences. But for such interspecific comparisons, I believe (rest of 
morphmet chime in...) that this is generally reasonable. If you are dealing 
with a very large size range this can be very useful, BUT if you have some 
VERY small individuals in the mix, it can cause some issues in terms of 
mean- variance relationships (but there are corrections for this). 


So what happens if after all of this (using logCS, accounting for effects 
of phylogeny) the vector correlations between shape and size are 
substantially different between species? Well, it will depend on exactly 
what you may wish to do. One reasonably sensible thing you can do is 
predict shape values for individuals of each species at comparable sizes 
(say at mean size for species A, and then again for mean size of species B) 
along their species specific shape ~ size relationships (but from a single 
unified model) and assess shape differences (magnitudes etc). In 
combination with some bootstrapping you can use this to generate plausible 
distributions of shape differences given these (there is a bit more to it, 
but hopefully the idea is clear). If you are a Bayesian (and even if you 
are not), there are some clever ways of integrating over the posterior 
distribution for these. 

If you have other goals, let us know.

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