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The potential for acoustic individual identification in mammals

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12310%2F22%3A43906134" target="_blank" >RIV/60076658:12310/22:43906134 - isvavai.cz</a>

  • Result on the web

    <a href="https://link.springer.com/article/10.1007/s42991-021-00222-2" target="_blank" >https://link.springer.com/article/10.1007/s42991-021-00222-2</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/s42991-021-00222-2" target="_blank" >10.1007/s42991-021-00222-2</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    The potential for acoustic individual identification in mammals

  • Original language description

    Many studies have revealed that animal vocalizations, including those from mammals, are individually distinctive. Therefore, acoustic identification of individuals (AIID) has been repeatedly suggested as a non-invasive and labor efficient alternative to mark-recapture identification methods. We present a pipeline of steps for successful AIID in a given species. By conducting such work, we will also improve our understanding of identity signals in general. Strong and stable acoustic signatures are necessary for successful AIID. We reviewed studies of individual variation in mammalian vocalizations as well as pilot studies using acoustic identification to census mammals and birds. We found the greatest potential for AIID (characterized by strong and stable acoustic signatures) was in Cetacea and Primates (including humans). In species with weaker acoustic signatures, AIID could still be a valuable tool once its limitations are fully acknowledged. A major obstacle for widespread utilization of AIID is the absence of tools integrating all AIID subtasks within a single package. Automation of AIID could be achieved with the use of advanced machine learning techniques inspired by those used in human speaker recognition or tailored to specific challenges of animal AIID. Unfortunately, further progress in this area is currently hindered by the lack of appropriate publicly available datasets. However, we believe that after overcoming the issues outlined above, AIID can quickly become a widespread and valuable tool in field research and conservation of mammals and other animals.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10613 - Zoology

Result continuities

  • Project

    <a href="/en/project/GF21-04023K" target="_blank" >GF21-04023K: Does intra-sexual selection drive evolution of individual identity in animal signals?</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2022

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Mammalian Biology

  • ISSN

    1616-5047

  • e-ISSN

  • Volume of the periodical

    102

  • Issue of the periodical within the volume

    3

  • Country of publishing house

    DE - GERMANY

  • Number of pages

    17

  • Pages from-to

    667-683

  • UT code for WoS article

    000780714500001

  • EID of the result in the Scopus database

    2-s2.0-85127606911