A large‐scale survey of bird plumage colour aberrations reveals a collection bias in Internet‐mined photographs. (19th September 2020)

• Record Type: Journal Article
• Authors: Zbyryt, Adam; Mikula, Peter; Ciach, Michał; Morelli, Federico; Tryjanowski, Piotr
• Is Part Of: Ibis. Volume 163:Number 2(2021)
• Page Start: 566
• Page End: 578
• Publication Date: 2020-09-19
• Subjects: albinism -- citizen science -- collection bias -- colour mutations -- Google Images -- leucism -- phenotypic variation; Birds -- Periodicals; 598
• DOI: 10.1111/ibi.12872
• Languages: English
• ISSNs: 0019-1019

Abstract

Abstract : Birds with plumage colour aberrations are of interest to both the general public and scientists. However, due to their rarity in nature, information on the presence of colour aberrations is rarely found in the peer‐reviewed literature. Exploration of public observations using modern information technologies such as Internet‐based search engines could facilitate cost‐effective and rapid broad‐scale collection of data on phenotypic aberrations in animals but may also be prone to the same problems as fieldwork, including systematic collection bias. We used Google Images and also asked birdwatchers and ornithologists, via naturalists' forums and social media, to collate a unique dataset of photographs of 936 aberrantly coloured birds of 74 species from Poland. Phylogenetically informed analyses, which included species both with and without reported colour aberrations, revealed that the number of colour aberrations was higher in species with larger populations in Poland, those with larger body size, and those associated with human settlements. Colour aberrations were also more often reported for species with a wider habitat breadth and those which do not migrate over long distances. Habitat openness and diet type were not related to the number of colour aberrations across species in multivariate models. Our study emphasizes not only the power of novel sources to collect large datasets on relatively rare phenotypic aberrations in animals but also the importance of vigilance when using data mined from public sources because the observed patterns may reflect collection bias rather than the nature of the studied phenomena.