Im struggling to figure out which statistical test i need to use on my data and then also how to carry this out in R or SPSS....

I have a time-series of measurements of pollutant levels on leaves from 4 different plant species that were re-sampled twelve times over a period of 5 weeks. This occured at three sampling locations.

So therefore i have 4 measurements (average of 2 plant samples for each species) at 3 locations on 12 separate occasions.

Graphs of the results show clear species and site differences in pollutant levels but i just need to show these differences statistically now.

My research so far has pointed me towards longitudinal analysis with perhaps an investigation of how the pollutant levels have changed from the baseline (the first measurement when the 'clean' plants were placed in each of the 3 polluted sites), but im really not sure how to do this! A book im reading mentions constructing matrices of correlation and covariance but this is too confusing for me.

Ive also considered derived attribute analysis - perhaps looking at the differences in gradient of slope of regression lines when a regression of pollutant level on time is performed. But this feels a little basic and clumsy.

Any help would be greatly appreciated!

Andy