[R-sig-Geo] how to test for effect of spatial scale

[Anna Marburg]

Dear Maurizio -

it sounds as though your data are what my spatial stats teacher called
"lattice" data.

The particular analysis you propose - repeatedly aggregating different
blocks of data together and then comparing across scales; sounds like
the "grieg-smith" approach to testing for spatial randomness; and the
"two term local quadrat variance (TTLQV)" approach for identifying
patches.

For more a general background on lattice (aka areal) data, try chapter
9 in Bivand et al (2009) Applied spatial data analysis with R and
section 2.6 in Fortin and Dale (2005) Spatial Analysis: A guide for
Ecologists.

It may also be that the spatially explicit nature of your data is a
red herring in this case and what you're really after is something
like rarefaction or bootstrapping.

Cheers,

Anna

> [...]
> My objective is to detect at what spatial scale would such a
> theoretical
> prediction begin to break down, i.e., if I begin to disaggregate the
> data to include all the (n-1) plots close to each other, all the
> (n-2),
> etc., down to statistics collected independently for each plot, when
> does the mean distribution calculated for all possible combinations at
> that scale begin to depart significantly from the expected curve.
> I cannot figure out how to approach the problem. It is not point
> pattern, nor does it seem to be geostatistics (building a semi
> variogram
> would help but only partially). The question is really about data
> aggregation at different spatial scales for plots that are close to
> each
> other.
>
> Any help appreciated.
>
> thanks
> Maurizio Mencuccini
> school of Geosciences
> University of Edinburgh (UK)

Dr. Anna E.  Marburg

Postdoctoral researcher
Ecosystem Processes Team
Landcare Research
P O Box 40
Lincoln 7640
NEW ZEALAND

phone + 64  3 321 9729
MarbugA at landcareresearch.co.nz




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