It is well established that animal communication signals have adapted to the evolutionary pressures of their environment. For example, the low-frequency vocalizations of the elephant are tailored to long-range communications, whereas the high-frequency trills of birds are adapted to their more localized acoustic niche. Like the voice, the human face transmits social signals about the internal emotional state of the transmitter. Here, we address two main issues: First, we characterized the spectral composition of the facial features signaling each of the six universal expressions of emotion (happiness, sadness, fear, disgust, anger, and surprise). From these analyses, we then predicted and tested the effectiveness of the transmission of emotion signals over different viewing distances. We reveal a gradient of recognition over viewing distances constraining the relative adaptive usefulness of facial expressions of emotion (distal expressions are good signals over a wide range of viewing distances; proximal expressions are suited to closer-range communication).