[R] Model design

[alfreda morinez]

Dear List,

I am realtively inexperienced so i apologise in advance and ask for
understanding in the simplicity of my question:

I have data on the amount of grass per km in a cell ( of which i have
lots) "grass" and for each cell i have x/y coordinates - required due
to spatial autocorrelation

Cells can be classfied in a hierarchical nature into  AREAS and STATES

i.e Cell 1, Cell 2, Cell 3 are all in AREA "A"

where as Cell 4,5 and 6 are in AREA "B"

However both area A + B are in state "S1"

I have lots of these (13000) cells which are classfied into ~2000
AREA's and ~750 STATE'S

So my question is do AREA'S differ in the amount of grass they contain
i.e does AREA A contain significantly more grass than AREA B?

I have modelled this by

area_grass <- gls(grass~AREA, correlation=corExp(form=~x+y), data = grassland

I have set the contrasts to options(contrasts = c("contr.treatment",
"contr.poly")) as there are no control groups.

What i will get ( it is taking ages!)

is

AREA A:     -0.12.... **
AREA B:      0.17....*
AREA C..


So can i then say AREA A has significantly less grass than the
average, AREA B significantly more and AREA C is not significantly
different?

Thanks

Alfreda