Future ATM systems will rely on automation to make operations more efficient. Creating insight into the inner-workings of automation, also known as agent transparency, is expected to play an important role for effective human-machine collaboration. This research proposes an ecological approach to increase agent transparency in automated rerouting for en-route traffic. For the purpose of this study, an ecological interface for the rerouting task, developed in a previous study, was visually augmented with the constraints guiding the behavior of an experimental path-planning algorithm. This was done in two different ways: a top-down and bottom-up approach. The top-down approach starts at the goal of the system and subsequently adds information related to the physical implications, while the bottom-up approach has the reversed order. The design was tested in a human-in-the-loop experiment with ten participants. Results show that higher levels of transparency significantly increased actual and perceived understanding of the agent’s decisions. Furthermore, the top-down approach performed significantly better in questions related to the strategy of automation, while the bottom-up approach was found more useful for making predictions about the agent’s rationale for making certain decisions. Future research should investigate how agent and domain transparency could be combined and should test situation awareness in addition to understanding of automation. Additionally, because only static situations were investigated in this study, the effects of a dynamic work domain featuring various time-critical situations should be analyzed in future research.