[R-sig-eco] Reducing spatial autocorrelation

[Corrado]

Dear Matthew,

thanks for your kind answer!

The first approach you describe is the one I have been looking at until now.

I am puzzled about the second one: I do not really understand it. What model 
are you talking about, when you say "incorporate the spatial variation in the 
model"? At the moment I have no model, just the data and I am trying to reduce 
autocorrelation before analysing the data.

Do you have any good reference (articles or books) about the approach you 
mention?

Thanks in advance


On Wednesday 14 October 2009 13:11:04 Matthew Landis wrote:
> Corrado:
>
> The simplest way would be to take a subset of sites to maximize the
> distance between them.  Say, choose 400 sites evenly spread over the
> study area.  That would minimize autocorrelation to the greatest extent
> possible, but you would be throwing away data.
>
> The second thing you could try would be to incorporate the spatial
> variation in the model to control for it.  This way you can also study
> the autocorrelation, see what spatial scales it is operating and what it
> looks like and try to learn something from it.  Legendre, Borcard, Dray
> and colleagues have developed some really interesting ways of dealing
> with multivariate data and decomposing the variance into spatial
> component vs. explanatory variables.  I believe it is called PCNM and
> can be found in the spacemakeR package (don't think it is on CRAN - have
> to do a google search).
>
> Good luck!
>
> Matthew Landis
>
> Corrado wrote:
> > Dear friends,
> >
> > I have a large matrix of species (first 1100 columns) and environmental
> > variables (last 36 columns) for approx 2000 sites.
> >
> > The distance between sites varies. Some sites are near to each other,
> > others are far.
> >
> > I would like to select a subset of N sites (for example: 400 sites) with
> > the minimum spatial autocorrelation. The aim is to obtain a significant
> > number of sites to carry out some statistical analysis, but with spatial
> > autocorrelation significantly reduced.
> >
> > Is there a procedure to do so in R? How would you approach the problem?
> >
> > The aim of the "reduction" is to then work on dissimilarities between
> > sites that have the lowest possible spatial autocorrelation.
> >
> > Thanks



-- 
Corrado Topi

Global Climate Change & Biodiversity Indicators
Area 18,Department of Biology
University of York, York, YO10 5YW, UK
Phone: + 44 (0) 1904 328645, E-mail: ct529 at york.ac.uk