ALBERT

All Library Books, journals and Electronic Records Telegrafenberg

feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Publication Date: 2018-03-26
    Description: Mobile animal groups provide some of the most compelling examples of self-organization in the natural world. While field observations of songbird flocks wheeling in the sky or anchovy schools fleeing from predators have inspired considerable interest in the mechanics of collective motion, the challenge of simultaneously monitoring multiple animals in the field has historically limited our capacity to study collective behaviour of wild animal groups with precision. However, recent technological advancements now present exciting opportunities to overcome many of these limitations. Here we review existing methods used to collect data on the movements and interactions of multiple animals in a natural setting. We then survey emerging technologies that are poised to revolutionize the study of collective animal behaviour by extending the spatial and temporal scales of inquiry, increasing data volume and quality, and expediting the post-processing of raw data. This article is part of the theme issue ‘Collective movement ecology’.
    Print ISSN: 0962-8436
    Electronic ISSN: 1471-2970
    Topics: Biology
    Published by The Royal Society
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 2
    Publication Date: 2022-11-07
    Description: © The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Lehmann, K. D. S., Jensen, F. H., Gersick, A. S., Strandburg-Peshkin, A., & Holekamp, K. E. Long-distance vocalizations of spotted hyenas contain individual, but not group, signatures. Proceedings of the Royal Society B: Biological Sciences, 289(1979), (2022): 20220548, https://doi.org/10.1098/rspb.2022.0548.
    Description: In animal societies, identity signals are common, mediate interactions within groups, and allow individuals to discriminate group-mates from out-group competitors. However, individual recognition becomes increasingly challenging as group size increases and as signals must be transmitted over greater distances. Group vocal signatures may evolve when successful in-group/out-group distinctions are at the crux of fitness-relevant decisions, but group signatures alone are insufficient when differentiated within-group relationships are important for decision-making. Spotted hyenas are social carnivores that live in stable clans of less than 125 individuals composed of multiple unrelated matrilines. Clan members cooperate to defend resources and communal territories from neighbouring clans and other mega carnivores; this collective defence is mediated by long-range (up to 5 km range) recruitment vocalizations, called whoops. Here, we use machine learning to determine that spotted hyena whoops contain individual but not group signatures, and that fundamental frequency features which propagate well are critical for individual discrimination. For effective clan-level cooperation, hyenas face the cognitive challenge of remembering and recognizing individual voices at long range. We show that serial redundancy in whoop bouts increases individual classification accuracy and thus extended call bouts used by hyenas probably evolved to overcome the challenges of communicating individual identity at long distance.
    Description: This work was supported by National Science Foundation grant nos OISE1853934 and IOS1755089, Carlsberg Foundation grant no. CF 15-0915 and Human Frontier Science Program grant no. RGP0051/2019. K.D.S.L. was supported by a Graduate Research Fellowship from NSF. A.S.P. received additional funding from the Gips-Schüle Stiftung, the Max Planck Institute of Animal Behaviour, and the Zukunftskolleg at the University of Konstanz. F.H.J. was funded through an AIAS-COFUND fellowship from Aarhus Institute of Advanced Studies under the FP7-PEOPLE programme of the EU (agreement no. 609033).
    Keywords: Long-distance signals ; Animal communication ; Group signatures ; Individual signatures
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...