Hi,

I have a question regarding the nesting structure in linear mixed models of data, which is spatially and at the same time temporally correlated.

So far I have tried to get around the problem by averaging out the temporal component but I would really like to keep everything in the model.

Here is the experimental set-up:
We have measured insect abundance in two different islands, each having 5 sites, each site having 4 plots, in which each we have 5 collection points (traps). The sampling was repeated 5 times. Two times in 2011 and 3 times in 2012.

After averaging the temporal correlation out I composed the following model for the abundance:

model<-lme(abundance~continous_explanatory_variable,random=~1|island/site/plot/trap,method="REML")

This works fine but I have problems making a model that allows the temporal component to stay in.
How can I do this using the function lme?

I know with lmer I could do this:

model2<-lmer(abundance~continous_variable+(1|island/site/distance/triplet)+(1|year/round))
but I really want to use the function lme. How can I insert multiple levels of grouping in lme?

Any help is very much appreciated!
Best,

Thomas

______________________________________

Dr Thomas Tscheulin
Laboratory of Biogeography and Ecology
University of the Aegean
Department of Geography
University Hill
GR-81100 Mytilene
Greece

Tel.:    +30 22510 36463 (or 36423)
Fax:    +30 22510 36423
Email:  t.tscheulin@geo.aegean.gr<mailto:t.tscheulin@geo.aegean.gr>
Laboratory website: http://www2.aegean.gr/lab_biogeography-ecology
ISI ResearcherID: http://www.researcherid.com/rid/B-9722-2011
Google Scholar Profile: http://scholar.google.com/citations?user=hKmpu-EAAAAJ

"Ο σκοπός της φύσης δεν είναι η διαιώνιση του ανθρώπινου είδους αλλά η διασφάλιση της βιοποικιλότητας των ειδών" Θεόφραστος (372-287 π.Χ.)


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