Introduction

Repeated observations of experimental units are frequently used in many areas of ecological research. A special case is the replicated BACI (before after control impact) design, in which the units (plots) are sampled first before the experimental treatment is imposed on some of them. In this way, you obtain ‘baseline’ data, i.e. the data where differences between the sampling units are caused solely by random variability. After the treatment is imposed, the units are sampled once or several times to reveal the difference in the development (dynamics) of manipulated and control units.

To analyse a univariate response (e.g. number of species, or total biomass) in this design, you can usually apply the repeated measurements model of ANOVA. There are in fact two possibilities for analysing such data. You can use a split-plot ANOVA with time, i.e. the repeated measures factor, being the ‘within plot’ factor or you can analyse the data using MANOVA. Although the theoretical distinction between those two approaches is complicated, the first option (often called a ‘univariate repeated measurements ANOVA’) is usually adopted, because it provides a stronger test. But it also has stronger assumptions for its validity (see e.g. von Ende 1993; Lindsey 1993), which are not always fulfilled. The interaction between time and the treatment reflects the difference in the development of the units between treatments.