"I have this data set (simple one-way ANOVA) that when I include the covariate it actually decreases the significance of the main effect... ?!? How is that possible and what does that mean?"
I am not an expert on this topic, but what immediately jumped out at me was correlation between the factor levels of the main effect and the covariate. I am trying to think through the math to ponder what I would do next if I was in this position at the moment. I think it would depend on what my goals were though.
(ps think about the most pathological covariate with one main effect possible: the main effect is just coding for the covariate falling into a certain range. Then the main effect could be beautifully predictive by itself while having it's statistical significance mauled by the inclusion of the actual covariate. It was just coding for the covariate in the first place!)