An \epsilon-test for a property P of functions from
{\cal D}=\{1,\ldots,d\} to the positive integers is a randomized
algorithm, which makes queries on the value of an input function at
specified locations, and distinguishes with high probability between the
case of the function satisfying P, and the case that it has to be
modified in more than \epsilon d places to make it satisfy P.

We prove that an \epsilon-test for any property defined in terms of the
order relation, such as the property of being a monotone nondecreasing
sequence, cannot perform less queries (in the worst case) than the best
\epsilon-test which uses only comparisons between the queried values. In
particular, we show that an adaptive algorithm for testing that a sequence
is monotone nondecreasing performs no better than the best non-adaptive
one, with respect to query complexity. From this follows a tight lower
bound on tests for this property.