Hi Toni,

What about some predictive mapping?

See for example Dorman et al (2007) and the supplementary R material.
http://onlinelibrary.wiley.com/doi/10.1111/j.2007.0906-7590.05171.x/abstract

You can try also the biomod package in R and the interface to Maxent 
in the dismo package.

HTH,
Marcelino


At 13:23 05/03/2012, TM wrote:
>Hi,
>I want to create a biodiversity species (probability) map of Spain 
>from presence(1)-absence(0) data (approx. 100 sites, and 3 species) 
>and also I have data from 400 metereological stations in Spain 
>(Coordinates, temperature, rain, hight, etc). I have been looking at 
>using indicator kriging on each species layer.
>
>Can I transform this data somehow to still be able to krige? (i.e 
>can I use Universal Kriging on binary data?)
>
>If some form of kriging is appropriate, I presume I should model the 
>variogram to the same (overall) distance for each species. Is it ok 
>to have a different lag distance/number of lags for each species or 
>all species? Are there general rules for specifying lag distances?
>
>I also have some metereological data which I could use as a 
>covariate. Is Cokriging appropriate to use when one dataset is 
>binary and the other is continuous? Does the data need to be co-located?
>
>Are there better statistical methods (in R or other software) to use 
>when interpolating presence-absence data, including with a trend and 
>covariate? Any references or code in R etc would be much appreciated.
>
>At last, How can I add time dimension to probability map, because I 
>have also temperature and rain time series?
>
>Apologies for quite so many questions. Thanks very much
>
>Toni
>Departament of Statistics
>University of Barcelona
>
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____________________________________

Marcelino de la Cruz Rot
Depto. Biologia Vegetal
EUIT Agricola
Universidad Politecnica de Madrid

tel: 34 + 913365435
____________________________________  
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