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Accès ouvert déclaré 2020 preprint

Automatic identification of bird females using egg phenotype

3Citations signalées — pas une note de qualité
7Institutions déclarées
2Pays d’affiliation déclarés

Résumé fourni par la source

Abstract Identification of individuals greatly contributes to understanding animal ecology and evolution, and in many cases can only be achieved using expensive and invasive techniques. Advances in computing technology offer alternative cost-effective techniques which are less invasive and can discriminate between individuals based on visual and/or acoustic cues. Here, we employ human assessment and an automatic analytical approach to predict the identity of common cuckoo ( Cuculus canorus ) females based on the appearance of their eggs. The cuckoo’s secretive brood parasitic strategy makes studying its life history very challenging. Eggs were analysed using calibrated digital photography for quantifying spotting pattern, size and shape, and spectrometry for measuring colour. Cuckoo females were identified from genetic sampling of their nestlings, allowing us to determine the accuracy of human and automatic female assignment. Finally, we used a novel ‘same-different’ approach that uses both genetic and phenotypic information to assign eggs that were not genetically analysed. Our results supported the ‘constant egg-type hypothesis’, showing that individual cuckoo females lay eggs with a relatively constant appearance and that eggs laid by different females differ more than eggs laid by the same female. The accuracy of unsupervised hierarchical clustering was comparable to assessments of experienced human observers. Supervised random forest analysis showed better results, with higher cluster accuracy. Same-different analysis was able to assign 22 of 87 unidentified cuckoo eggs to seven already known females. Our study showed that egg appearance on its own is not sufficient for identification of individual cuckoo females. We therefore advocate genetic analysis to be used for this purpose. However, supervised analytical methods reliably assigned a relatively high number of eggs without genetic data to their mothers which can be used in conjunction with genetic testing as a cost-effective method for increasing sample sizes for eggs where genetic samples could not be obtained.

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Contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
Automatic identification of bird females using egg phenotype
Date Crossref
26/11/2020
Éditeur
openRxiv
Type
posted-content

Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude et ne compte pas comme une seconde source scientifique indépendante.

Institutions déclarées

Une affiliation ne permet pas de déduire la nationalité d’un auteur.

Sujets associés

Avian ecology and behaviorWildlife Ecology and ConservationAnimal Vocal Communication and Behavior

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