Hello,
I'm helping someone with some spatial analyses for some data with plant
species data across a set of natural pools. We are trying to determine
whether there is spatial autocorrelation, but am not sure what test to
run.
At first I was advised that perhaps using the Moran's I index would work,
but I have had some folks suggest that Moran's I works best for adjacent
polygons or raster data. I am using an ArcView polygon data layer.
Another recommendation was to use semivariograms included in
Geostatistical Analyst with ArcView 8.1, which I will attempt in the
coming week.
I have a few questions.
My first question is: What is the appropriate test that should be employed
to determine whether there is spatial autocorrelation given this scenario?
There are approximately 100 natural pools that
have varying abundances of the plant in question. However, only 32 pools
were sampled. It was not a random sampling...out of the 100 pools, these
were the only ones that were not damaged by construction. The other pools
are still functional, however, and do contain the plant being studied.
On one end of the site most of the pools were sampled, whereas on the other
end of the site only a few pools were sampled.
So my second question is: Can I really test for spatial autocorrelation if
we do not have any data for the damanged pools? My concern is that we will
have a sampled pool with high plant density next to 4 or 5 non-sampled
pools...will we get the wrong outcome?
I don't know if this makes sense...it's difficult to explain virtually!
If anyone has any suggestions I'd really appreciate it!
Thanks very much in advance,
Sue
-----------------------
Sue Rodriguez-Pastor
Dept. of EPO Biology
University of Colorado
email address: [EMAIL PROTECTED]
-----------------------
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