Characterization of bird formations using fuzzy modelling

Author:

Perinot Elisa12ORCID,Fritz Johannes23ORCID,Fusani Leonida13ORCID,Voelkl Bernhard24ORCID,Nobile Marco S.56ORCID

Affiliation:

1. Konrad Lorenz Institute of Ethology, Department of Interdisciplinary Life Sciences, University of Veterinary Medicine, Vienna 1160, Austria

2. Waldrappteam Conservation and Research, 6162 Mutters, Austria

3. Department of Behavioural and Cognitive Biology, University of Vienna, Vienna 1010, Austria

4. Animal Welfare Division, University of Bern, 3012 Bern, Switzerland

5. Department of Environmental Sciences, Informatics and Statistics, Ca’ Foscari University of Venice, 30123 Venezia, Italy

6. Bicocca Bioinformatics, Biostatistics and Bioimaging research center (B4), 20900 Monza, Italy

Abstract

The investigation of the emergent collective behaviour in flying birds is a challenging task, yet it has always fascinated scientists from different disciplines. In the attempt of studying and modelling line formation, we collected high-precision position data of 29 free-flying northern bald ibises (Geronticus eremita) using Global Navigation Satellite System loggers, to investigate whether the spatial relationships within a flock can be explained by birds maintaining energetically advantageous positions. Specifically, we exploited domain knowledge and available literature information to model by means of fuzzy logic where the air vortices lie behind a flying bird. This allowed us to determine when a leading bird provides the upwash to a following bird, reducing its overall effort. Our results show that the fuzzy model allows to easily distinguish which bird is flying in the wake of another individual, provides a clear indication about flying flock dynamics and also gives a hint about birds' social relationships.

Funder

Austrian Science Fund

LIFE European Union

Publisher

The Royal Society

Subject

Biomedical Engineering,Biochemistry,Biomaterials,Bioengineering,Biophysics,Biotechnology

Reference61 articles.

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1. Characterization of bird formations using fuzzy modelling;Journal of The Royal Society Interface;2023-02

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