Then, while testing spatial relationship between vegetation and environmental boundaries, I show that significance based randomized and restricted permutation tests do not assume the same underlying ecological processes. Here, randomization is found to be a more conservative test than restricted permutation test for detecting significant spatial relationship. Quantities such as population growth rate, sensitivities, and elasticities are complicated functions of this underlying data structure. This complexity has hampered efforts to test the significance of differences in demographic statistics. This provides, at best, only an approximate significance test.
Randomization tests provide a much more rigorous way to test demographic hypotheses.
Although both randomization tests and the bootstrap involve computer resampling of the original data, they resample in different ways and for different purposes. I will show examples drawn from studies of Daphnia, polychaetes, and killer whales. Sequential methods in randomization and bootstrap tests. Randomization and bootstrap methods are increasingly commonly used for statistical inference in ecology. These methods are computationally intensive and, in some situations, the computational demands are extreme or even prohibitive.