[R-sig-eco] Spatial sampling simulations

[Sarah Goslee]

Erika,

This article: http://dx.doi.org/10.1007/s11258-005-3495-x
 Behavior of Vegetation Sampling Methods in the Presence of Spatial
Autocorrelation
Plant Ecology Volume 187, Number 2 / December, 2006
used the gstat package to generate spatial patterns, and then sampled them using
different quadrat layouts.

The basic workflow:
Use gstat to generate fake vegetation patterns.
Sample the data using your quadrat layout.
Analyze as if it were real data.

You need to decide in advance how big a pixel is, so how many
pixels per quadrat your samples are: that will depend on the size
of the plants you are working on.

More detailed help would require knowing more about what you
are trying to do.

Sarah


On Thu, Nov 20, 2008 at 2:34 PM, Erika Mudrak <mudrak at wisc.edu> wrote:
> Hi everyone,
>
> I am trying to investigate how well a certain (quirky) quadrat layout will uncover underlying spatial phenomenon of plant locatons.  I am using the geoR package to generate variograms, but I am noticing some interesting trends that may be artifacts of the sampling design rather than the natural phenomenon.
>
> I would like to conduct simulations where I generate a known spatial pattern, superimpose the quadrat layout, sample from that, and analyze the resulting variogram.  I see that geoR has a sample.geodata() function, but I don't want to pick random samples, I want to easily determine what my data would look like if I could only see it through the quadrat layout.   Is there any function where I can easily do this?
>
> [I realize that there is a lot of literature about preferred quadrat layouts, but the data was taken before I arrived at school, handed to me, and if I can figure out how to work with it, then I get a prize - a degree!]
>
> Thanks
> Erika
>

-- 
Sarah Goslee
http://www.functionaldiversity.org