Ecological study with pseudoreplication, should I use t.tests with bonferonni correction or a repeated measures ANOVA? I have a study where I will treat two ponds and measure changes in soil texture. I only have access to the two ponds, but will collect soil at 15 points in each pond. One pond will be flooded and dried over the course of a year, the other pond will serve as a control and remain flooded throughout. I will sample 6 times over the course of the year.
I would like to compare, at each sampling event whether a difference in soil texture exists. I was intending to do ttests to compare the control to the treated pond at each sampling event, with a bonferonni correction. Does this seem like a good course of action?
POND A Dried and reflooded monthly
15 points are sampled 6 times in the year
POND B Never dried (Control)
15 points are sampled 6 times in the year

First, a simple Bonferroni correction is seldom a good idea. It's easy to think about and to code, but it's not as powerful as the Holm modification.
Second, whenever you are doing multiple comparisons you need to account for them in some way. Even if you think about the 15 samples per pond as technical replicates, if you do 6 separate comparisons between the ponds you need some correction for those 6 comparisons.
The most powerful way to do this would be to go beyond either of the methods you propose. Repeated-measures ANOVA will pose a problem if you ever miss a measurement. Consider generalized least squares, or a mixed model that treats sites within a pond as random effects. Continuous modeling with respect to time, rather than 6 separate comparisons between the ponds, would minimize the multiple comparisons problem.
