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Dietary analysis of the House Swift, Apus nipalensis, in Hong Kong using prey DNA in faecal samples

Cite this dataset

Chung, Chun Ting et al. (2021). Dietary analysis of the House Swift, Apus nipalensis, in Hong Kong using prey DNA in faecal samples [Dataset]. Dryad.



            To understand the dietary composition of the highly aerial swift (Apodidae), ecologists conventionally depend on the morphological identification of prey items from food boluses or stomach contents, but these techniques are often invasive, require expertise in identification, and often cannot produce accurate identifications at the species level.


            In this study, DNA barcoding was used to analyse the dietary composition of House Swifts (Apus nipalensis) in Hong Kong. Faecal samples from five different colonial nest sites were collected between 2019 and 2020. We used universal primers to amplify a region of the cytochrome c oxidase gene from prey DNA in the faecal samples for identification purposes.


            Ten different orders and 44 families from three different classes of Arthropoda were identified in the faecal samples collected. Hymenoptera, Hemiptera and Diptera were the most prevalent groups of prey found in the samples. Differences in the dietary composition of House Swifts during the breeding (April to September) and non-breeding (October to March) seasons were also found. Hymenoptera, particularly ants (Formicidae), were predominant in the diet during the breeding season, whereas Diptera and Hemiptera were predominant during the non-breeding season.


            The prey groups identified in this study were similar to those identified in a previous study of the diet of House Swifts, which suggests a possible role of House Swifts in reducing the numbers of local insect pests. This study demonstrates the usefulness of applying molecular tools for the dietary analysis of aerial feeders. Conserving local forested areas may be crucial for the maintenance of the House Swift population.


School of Life Sciences, The Chinese University of Hong Kong, Award: 5501703