Automatic identification of bird females using egg phenotype

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68081766%3A_____%2F22%3A00548861" target="_blank" >RIV/68081766:_____/22:00548861 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/60076658:12310/22:43906062 RIV/00216208:11310/22:10446491 RIV/00216224:14310/22:00125955

Výsledek na webu

<a href="https://academic.oup.com/zoolinnean/advance-article-abstract/doi/10.1093/zoolinnean/zlab051/6357656?redirectedFrom=fulltext" target="_blank" >https://academic.oup.com/zoolinnean/advance-article-abstract/doi/10.1093/zoolinnean/zlab051/6357656?redirectedFrom=fulltext</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1093/zoolinnean/zlab051" target="_blank" >10.1093/zoolinnean/zlab051</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Automatic identification of bird females using egg phenotype

Popis výsledku v původním jazyce

Individual identification is crucial for studying animal ecology and evolution. In birds this is often achieved by capturing and tagging. However, these methods are insufficient for identifying individuals/species that are secretive or difficult to catch. Here, we employ an automatic analytical approach to predict the identity of bird females based on the appearance of their eggs, using the common cuckoo (Cuculus canorus) as a model species. We analysed 192 cuckoo eggs using digital photography and spectrometry. Cuckoo females were identified from genetic sampling of nestlings, allowing us to determine the accuracy of automatic (unsupervised and supervised) and human assignment. Finally, we used a novel analytical approach to identify eggs that were not genetically analysed. Our results show that individual cuckoo females lay eggs with a relatively constant appearance and that eggs laid by more genetically distant females differ more in colour. Unsupervised clustering had similar cluster accuracy to experienced human observers, but supervised methods were able to outperform humans. Our novel method reliably assigned a relatively high number of eggs without genetic data to their mothers. Therefore, this is a cost-effective and minimally invasive method for increasing sample sizes, which may facilitate research on brood parasites and other avian species.

Název v anglickém jazyce

Automatic identification of bird females using egg phenotype

Popis výsledku anglicky

Individual identification is crucial for studying animal ecology and evolution. In birds this is often achieved by capturing and tagging. However, these methods are insufficient for identifying individuals/species that are secretive or difficult to catch. Here, we employ an automatic analytical approach to predict the identity of bird females based on the appearance of their eggs, using the common cuckoo (Cuculus canorus) as a model species. We analysed 192 cuckoo eggs using digital photography and spectrometry. Cuckoo females were identified from genetic sampling of nestlings, allowing us to determine the accuracy of automatic (unsupervised and supervised) and human assignment. Finally, we used a novel analytical approach to identify eggs that were not genetically analysed. Our results show that individual cuckoo females lay eggs with a relatively constant appearance and that eggs laid by more genetically distant females differ more in colour. Unsupervised clustering had similar cluster accuracy to experienced human observers, but supervised methods were able to outperform humans. Our novel method reliably assigned a relatively high number of eggs without genetic data to their mothers. Therefore, this is a cost-effective and minimally invasive method for increasing sample sizes, which may facilitate research on brood parasites and other avian species.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10613 - Zoology

Projekt

<a href="/cs/project/GA17-12262S" target="_blank" >GA17-12262S: Reprodukční strategie obligátního hnízdního parazita: výběr hostitele, alokace pohlaví mláďat a individuální úspěšnost</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název periodika

Zoological Journal of the Linnean Society

ISSN

0024-4082

e-ISSN

1096-3642

Svazek periodika

195

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

12

Strana od-do

33-44

Kód UT WoS článku

000764863400001

EID výsledku v databázi Scopus

2-s2.0-85132996913