[R-sig-Geo] MEM : Spatial structures detection issues

[David Bauman]

Hi everyone,

I am facing a problem I really do not know how to resolve about
detecting significant spatial structures in a region I am studying.

The study is about the Miombo forest (wooded savanna). I am working in
a 10 ha permanent forest plot, where all trees are mapped and
identified. I sampled 24 more or less regulately scattered plots of 25
x 25 m over the 10 ha. In each plot of 25 x 25 m I got 5 soil samples
on which I will measure a battery of variables (the explanatory
variables).
What I want to study is the bêta-diversity of the ectomycorrhizal
community, so that in each plot I got about 15 pieces of root
containing some ectomycorrhizal fungus on it (response variables).

My purpose is to explain the spatial variation of the ectomycorrhizal
diversity thanks to the soil variables I will have measured.

To do so, I want to use a PCNM (or MEM).

My problem is that :

All the 24 plots are considered as points, so that the euclidean
distance between them is overestimated. Two adjacent, contiguous,
plots are considered to be 25 m far from each other, while the
distance should be 0, since they "touch" each other.
This leads me to the problem that the truncation threshold distance is
to high to allow the RDA of the response dataframe on the spatial PCNM
variables to detect a significant linear link between both matrices
(function anova.cca()).

So the question is : How can I do so that the area of my plots are
taken into account, and they are not considered as points anymore ?
This would lower the truncation distance and probably allow me to
detect spatial structures that, I really think, do exist.

I hope someone with some experience and good ideas will be able to help.

If you want some more concrete information about the study, do not
hesitate to ask it to me.

Thanks a lot,

David Bauman