I have a dataset of fish species abundances collected from 6 different habitats over the course of 30 years. Fish were collected multiple times per year and environmental variables were recorded at the time of sampling. I am running a multivariate GLM through the R package mvabund because I want to include the whole species matrix. How do I control for the fact that the samples are not independent from each other (i.e. are part of a time series data set collected at the same locations over 30 years)?. Mvabund doesn't have the ability to run the model with random factors. Would running the model with site included as a fixed factor and year included as a blocking variable be a valid approach?
I'm not sure about the setup you are using. One way to analyse repeated measures designs is to treat each time series as a replicate and analyse them using multivariate methods. See Clarke KR, Somerfield PJ, Airoldi L, Warwick RM (2006) Exploring interactions by second-stage community analyses. J. Exp. Mar. Biol. Ecol. 338:179-192.
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