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 [[alternative HTML version deleted]]
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