Dear all,

I'm investigating the spatial and temporal variability for some biological
features of stream fish communities (e.g. richness, diversity), modelled
under future climate change according different 5 climate model outputs
(GCM) and 3 emissions scenarios (SRES)...

One of my goal is to highlight graphically the spatial (characterized by
"Gradient" as a quantitative predictor) and temporal (characterized by
"Years" from 2005 to 2100 as an ordinal predictor) differences in species
richness (Richness) according to the 3 future scenarios. One idea was to
fit, individually for each scenario, a generalized additive model, namely
Rich.fit=gam(Richness ~ s(gradient) + s(year)), so that the Richness could
then be interpolated on a regular xy grid o highlight spatio-temporal
patterns of variability.

The 'problem' is that I expect some indirect effects in the modelled
patterns of richness related to GCM. In this context, I would be interested
to remove the effect from these GCM in my models to get a more consistent
ideas about the 'real' patterns of differences between scenarios... Do you
have any idea for doing that?

Best regards,

Clement

-- 
Clement Tisseuil - PhD student

Laboratoire  "Evolution et Diversité Biologique" (EDB)
UMR 5174 - Université Paul Sabatier CNRS
118 route de Narbonne, Bât 4R3, Porte 112
31062 Toulouse Cedex 9 - France
Phone : +33 5 61 55 67 35
Fax: +33 5 61 55 67 28
webpage: http://www.clement-tisseuil.eu

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