Communication networks of wild zebra finches (Taeniopygia castanotis)

Communication networks are widespread across species, permitting information flow and facilitating social connections across space and time. In birds, communication networks are well studied in territorial species with long-range songs connecting individuals across space, where unintended listeners extract information from others signalling interactions. Yet acoustic signals also play important social roles at short range, forming communication networks that connect individuals within larger social units. Wild zebra finches (Taeniopygia castanotis) provide a unique model system to examine such communication networks in a non-territorial species with multiple males singing at shared locations in close temporal proximity. Zebra finches breed in loose colonies in the Australian arid zone, typically stay near their partner, move around in pairs or small groups, and gather at social hotspots, thus forming dynamic, potentially multi-level, societies. Here, we used the individually distinctive male song, recorded over 1,835 song bouts at two breeding sub-colonies and three social hotspots to quantify singing activity. We identified 163 males based on spectrographic similarities, verified by a deep learning model (BirdNET), and constructed communication networks based on temporal singing proximity at shared locations, social hotspots and the breeding colony. We reveal higher singing activity at social hotspots, with no dawn song and singing peaking at different times of day between breeding sites and social hotspots. Communication networks, with distinct males singing in close temporal proximity, were apparent in both contexts, with larger networks at hotspots. These networks were not strongly nested, yet many individuals met repeatedly at either the hotspot or breeding sites and some even maintained associations across breeding colonies and hotspots, providing building blocks for a multi-level society. These networks may facilitate synchronized foraging and breeding as adaptations to a harsh and unpredictable environment. Additionally, our approach offers a novel road map for widening the understanding of communication networks.