Measuring individual identity information in animal signals: Overview and performance of available identity metrics

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00027014%3A_____%2F19%3AN0000117" target="_blank" >RIV/00027014:_____/19:N0000117 - isvavai.cz</a>

Alternative codes found

RIV/68081766:_____/19:00505878 RIV/60460709:41210/19:79544 RIV/60460709:41320/19:79544 RIV/60460709:41330/19:79544 and 2 more

Result on the web

<a href="https://vuzv.cz/_privat/19116.pdf" target="_blank" >https://vuzv.cz/_privat/19116.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1111/2041-210X.13238" target="_blank" >10.1111/2041-210X.13238</a>

Result language

angličtina

Original language name

Measuring individual identity information in animal signals: Overview and performance of available identity metrics

Original language description

Identity signals have been studied for over 50 years but, and somewhat remarkably, there is no consensus as to how to quantify individuality in animal signals. While there is a variety of different metrics to quantify individuality, these methods remain un-validated and the relationships between them unclear. We contrasted three univariate and four multivariate identity metrics (and their different computational variants) and evaluated their performance on simulated and empirical datasets. Of the metrics examined, Beecher's information statistic (HS) performed closest to theoretical expectations and requirements for an ideal identity metric. It could be also easily and reliably converted into the commonly used discrimination score (and vice versa). Although Beecher's information statistic is not entirely independent of study sampling, this problem can be considerably lessened by reducing the number of parameters or by increasing the number of individuals in the analysis. Because it is easily calculated, has superior performance, can be used to quantify identity information in single variable or in a complete signal and because it indicates the number of individuals who can be discriminated given a set of measurements, we recommend that individuality should be quantified using Beecher's information statistic in future studies. Consistent use of Beecher's information statistic could enable meaningful comparisons and integration of results across different studies of individual identity signals. © 2019 The Authors. Methods in Ecology and Evolution

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10614 - Behavioral sciences biology

Project

<a href="/en/project/GA14-27925S" target="_blank" >GA14-27925S: Ontogenetic and social determinants of pig vocal individuality</a><br>

Continuities

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

Publication year

2019

Confidentiality

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

Name of the periodical

Methods in Ecology and Evolution

ISSN

2041-210X

e-ISSN

—

Volume of the periodical

10

Issue of the periodical within the volume

9

Country of publishing house

GB - UNITED KINGDOM

Number of pages

13

Pages from-to

1558-1570

UT code for WoS article

000483699600017

EID of the result in the Scopus database

2-s2.0-85068530736