Citation

Courter JR, Johnson RJ, Stuyck CM, Lang BA, Kaiser EW. Int. J. Biometeorol. 2013; 57(5): 715-720.

Affiliation

Department of Earth and Environmental Science, Taylor University, 236 W. Reade Ave., Upland, IN, 46989, USA, jason_courter@taylor.edu.

Copyright

(Copyright © 2013, International Society of Biometeorology, Publisher Holtzbrinck Springer Nature Publishing Group)

DOI

10.1007/s00484-012-0598-7

PMID

23104424

Abstract

Studies of bird phenology can help elucidate the effects of climate change on wildlife species but observations over broad spatial scales are difficult without a network of observers. Recently, networks of citizen volunteers have begun to report first arrival dates for many migratory species. Potential benefits are substantial (e.g., understanding ecological processes at broad spatial and temporal scales) if known biases of citizen data reporting are identified and addressed. One potential source of bias in bird phenology studies is the tendency for more "first" migratory arrivals to be reported on weekends than on weekdays. We investigated weekend bias in data reporting for five common bird species in North America (Baltimore Oriole, Icterus galbula; Barn Swallow, Hirundo rustica; Chimney Swift, Chaetura pelagica; Purple Martin, Progne subis; and Ruby-throated Hummingbird, Archilochus colubris), and assessed whether this bias affected mean arrival dates reported using data from historical (1880-1969; N = 25,555) and recent (1997-2010; N = 63,149) Citizen Science databases. We found a greater percentage of first arrivals reported on weekends and small but significant differences in mean arrival dates (approximately 0.5 days) for four of five species. Comparing time periods, this weekend bias decreased from 33.7 % and five species in the historical time period to 32 % and three species in the recent, perhaps related to changes in human activity patterns. Our results indicate that weekend bias in citizen data reporting is decreasing over time in North America and including a 'day of week' term in models examining changes in phenology could help make conclusions more robust.

Language: en