Why would removing a variable in adaboost decrease error rate?
Imagine that one of the column is just random data -- then it's not informative at all, so no classifier will be improved by including it.

However, ada's stochastic boosting implementations will always have some chance of including that variable in the classifier it generates. As a result, removing it has the potential to improve the classifiers generated.

(In your case, you might check whether that variable is part of the final model generated.)