Monk parakeets appear to be able to recognise each others' distinct voices

Embargoed until: Publicly released: 2023-10-04 10:01

Australia; International; ACT

Photo by Tania Malréchauffé on Unsplash

Monk parakeets appear to have distinct 'voice-prints' that they likely can use to recognise each other, according to international and Australian experts. The team recorded 5599 bird calls from 229 parakeets in Spain, which included five distinct different types of call. They say they found evidence the parakeets had distinct 'voice-prints' that could be identified across different types of bird call, which suggests they can use vocal cues to identify themselves to each other.

Media release

From: The Royal Society

Evidence for vocal signatures and voice-prints in a wild parrot

Royal Society Open Science

While we know humans recognize each other based on so-called voice-prints across, we don’t know if other species can also do this. We recorded 5599 vocalizations from 229 marked monk parakeets over two years, studying five call types. We found individual signatures in three call types. Contact calls were surprisingly variable, challenging previous assumptions about stable individual signatures. We also discovered voice-prints across call types. This suggests monk parakeets recognize each other using vocal cues, transcending vocalization types and explains how they can stay recognisable while imitating others.

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Journal/
conference: Royal Society Open Science

Research:Paper

Organisation/s: The Australian National University, Max Planck Institute of Animal Behavior, Germany

Funder: S.Q.S. received funding from the International Max Planck Research School for Quantitative Behaviour, Ecology and Evolution. L.M.A. was funded by a Max Planck Research Group Leader Fellowship, and is currently supported by the Swiss State Secretariat for Education, Research and Innovation (SERI) under contract number MB22.00056. Research funding was provided to S.Q.S. and L.M.A. by the Centre for the Advanced Study of Collective Behaviour (CASCB), funded by the Deutsche Forschungsgemeinschaft (DFG) under Germany’s Excellence Strategy (EXC 2117-422037984). J.C.S. was supported by a research project from the Ministry of Science and Innovation (CGL-2020 PID2020-114907GB-C21).

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