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Validation of an automated data collection method for quantifying social networks in collective behaviours

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Abstract

The social network of preferences among group members can affect the distribution and consequences of collective behaviours. However, the behavioural contexts and taxa in which social network structure has been described are still limited because such studies require extensive data. Here, we highlight the use of an automated passive integrated transponder (PIT)-tag monitoring system for social network analyses and do so in a novel context—nestling provisioning in an avian cooperative breeder, for which direct observation of social behaviours is difficult. First, we used observers and cameras to arrive at a suitable metric of nest visit synchrony in the PIT-tag data. Second, we validated the use of this metric for social network analyses using internal nest video cameras. Third, we used hierarchical regression models with ‘sociality’ parameter to investigate structure of networks collected from multiple groups. Use of PIT tags led to nest visitation duration and frequency being obtained with a high degree of accuracy for all group members, except for the breeding female for whom accurate estimations required the use of a video camera due to her high variability in visitation time. The PIT-tag dataset uncovered significant variability in social network structure. Our results highlight the importance of combining complementary observation methods when conducting social network analyses of wild animals. Our methods can also be generalised to multiple contexts in social systems wherever repeated encounters with other individuals in closed space have ecological implications.

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Acknowledgments

We are very grateful to D. Croft, the Dowling family and Z. Turner for logistical support at Fowlers Gap; E. Berg, M. Hall, B. Rose, J. Savage, S. Sharp, E. Sorato, I. Stewart and B. Woodward for invaluable assistance with fieldwork; M. Magrath and S. Zabramski for help with the PIT-tag system; and L. A. Rollins for assistance with lab work. We are also grateful to three anonymous referees for their comments on the early version of the manuscript. We thank M. T. Kimura for helpful advice throughout the study. Funding was provided by grants from Natural Environment Research Council (studentship, LEB; New Investigators, AFR), Australian Research Council (AFR, SCG), the Royal Society University Fellowship Scheme (AFR), and the Japan Society for the Promotion of Science (FYN).

Ethical standards

Fieldwork was carried out under the approval of the UNSW Animal Care and Ethics Committee (license number 06/40A) and the authority of NSW National Parks and Wildlife Service and the Australian Bird and Bat Banding Scheme. We did not detect any harmful effects of the tags on the birds, which are consistent with studies on different, but similarly sized passerines (Nicolaus et al. 2008; Schroeder et al. 2011).

Conflict of interest

The authors declare that they have no conflict of interest.

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Authors and Affiliations

  1. Graduate School of Environmental Sciences, Hokkaido University, Sapporo, 0600810, Japan

    Fumiaki Y. Nomano

  2. Department of Zoology, University of Cambridge, Cambridge, CB2 3EJ, UK

    Lucy E. Browning

  3. Fowlers Gap Arid Zone Research Station, School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, NSW 2052, Australia

    Lucy E. Browning

  4. Department of Zoology, University of Otago, Dunedin, 9054, New Zealand

    Shinichi Nakagawa

  5. Department of Biological Sciences, Macquarie University, Sydney, NSW 2109, Australia

    Simon C. Griffith

  6. Centre for Ecology and Conservation, College of Life and Environmental Sciences, University of Exeter, Penryn, TR10 9FE, Cornwall, UK

    Andrew F. Russell

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  1. Fumiaki Y. Nomano
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  2. Lucy E. Browning
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  3. Shinichi Nakagawa
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  4. Simon C. Griffith
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  5. Andrew F. Russell
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Correspondence to Fumiaki Y. Nomano.

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Communicated by L. Z. Garamszegi

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Nomano, F.Y., Browning, L.E., Nakagawa, S. et al. Validation of an automated data collection method for quantifying social networks in collective behaviours. Behav Ecol Sociobiol 68, 1379–1391 (2014). https://doi.org/10.1007/s00265-014-1757-0

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