 Dear R-eco'ers, I am about to analyze a dataset with population trends from
two decades (1990's and 2000's) for about 500 populations.

I would like to incorporate both trends in the same model (as the response
variable) to get an idea of how the populations respond to different
environmental conditions (the explanatory variables being the environment
experienced in each decade).

So far the best design I can come up with is to do a mixed effects linear
model with the population ID as a random effect. In this I would also use
the inverse error term of the slope to weight each observation. So something
like:
*lme(trend ~ winter_ndvi * summer_ndvi * land_use_change, random = 1|popID,
weights = (1/trend_SE))*

I guess and other option is to do a more explicit repeated measures model.
Any suggestions and comments on improvement of the model design are very
welcome.

Best,

Peter

Peter Søgaard Jørgensen
Student, Master of Science
Office: +45 35 32 12 30
Cell: +45 60 24 95 79
US-cell: (001)-510-316-2201

Center for Macroecology, Evolution and Climate
Section for Ecology and Evolution, Department of Biology
University of Copenhagen
Universitetsparken 15, Building 12
DK-2100 Copenhagen

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