changed between 1987 and 1988. We do not wish to test the more general question of whether kangaroo populations remain stable with time. The anova shows that of the three main effects, the three first-order interactions, and the one second-order interaction, only the main effect of kangaroo species is significant. We conclude therefore that the two species certainly differed in density but that there was insufficient evidence to identify a day effect or a change in density between years. Neither did any factor appear to interact with any other.
16.7 Summary Testing of wildlife management treatments requires rigorous definition of the expected outcome of the treatments. Once a verifiable outcome is posed as a hypothesis, the data to test it can be collected by following the logic of experimental design. Insufficient replication of treatments to sample the range of natural variability is a common shortcut, but it nullifies the point of the exercise.
The principles illustrated in this chapter can be summarized as the basic rules of experimental design. There are exceptions to several of them, but until the manager or researcher learns how and in what circumstances they may safely be varied, these should be followed in full.
1 To determine whether a factor affects the response variable under study, more than one level of that factor should be examined. The levels may be zero (control) and some non-zero amount, or they may be two or more categories (e.g. habitat types) or non-zero quantities (e.g. altitudinal bands).
2 "Before" is a poor control for "after," because subsequent trends can be caused by other influences unrelated to the treatment under study.
3 Treatments must be replicated, not subsampled. (See Hurlbert (1984) for an excellent exposition of the pitfalls of "pseudo-replication" in ecological research.)
4 The number of replications per treatment (including the control treatment) should be as close as possible to equal across treatments.
5 Treatments must be interspersed in time and space. Do not run the replications of treatment A and then the replications of treatment B. Mix up the order. Do not site the replications of treatment A in the north of the study region and the replications of treatment B in the south. Mix them up.
6 If the influence of more than one factor is of interest, each level of each factor should be examined in combination with each level of every other factor (factorial design).
7 If an extraneous influence (site in the quail example) is likely to be correlated with one of the designated factors, either it should be declared a factor in its own right and the design modified accordingly or its range should be covered at random by
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