We consider belief change in a situation where agents have full memory of all information that has been reported over time. In this context, we no longer have an a priori initial belief state. Instead, we have a history of past reports along with a trust state that indicates how strongly each information source is trusted. If we have a static model of trust, then this approach is essentially gives a variation of regular iterated revision. However, we introduce a model of trust change, where trust levels can increase or decrease based on agreement between sources. In this case, we end up with a new kind of belief change operator. The new operator can abandon sources and re-integrate them over time, while maintaining beliefs are justified both by trust and an underlying Darwiche-Pearl operator.