Abstract
The lack of refined spatial detail on bird distribution in China has hindered further research due to the large geographic unit (provincial level) in existing national bird distribution data. Based on multi-source bird distribution data, we built a more spatially detailed distribution database for every bird species (1,371 species) in China, covering 2,908 counties. The sources on bird distribution are grouped into six categories: Handbooks, Literature; Fauna, Avifauna; Paper; Citizen Science data by ornithologists or birders; GPS tracing; and Website data. The database contains the following records: taxonomy, distribution data, suspicious species information, and data sources. Our database recorded 835 species (61%) appearing outside the distribution range previously known. The use of provincial boundaries as the smallest geographical unit has created misleading distribution results due to geographic aggregation for most species. The new database was built based on increased observational frequency and individuals observed in previously undetected areas particularly in Western China and towards higher altitudes and latitudes. They coincided with the discovery of the range expansion of some waterfowls into Xinjiang. The dataset provides a new base for Chinese and international ornithology studies, especially for those requiring more detailed distribution information for many taxa and large-scale regional research.
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Acknowledgements
This work was supported by the National Research Program of Ministry of Science and Technology of the People’s Republic of China (2016YFA0600104). The authors thank the following members who took part in the work of conceptualization, datacuration, and methodology, Lu Dong from Beijing Normal University. We thank Luzhang Ruan from Nanchang University and the Bird Report Center with the website link (http://www.birdreport.cn) for data support.
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Dai, S., Feng, D., Chan, K.K.Y. et al. A spatialized digital database for all bird species in China. Sci. China Life Sci. 62, 661–667 (2019). https://doi.org/10.1007/s11427-018-9419-2
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DOI: https://doi.org/10.1007/s11427-018-9419-2