Authors: Elaina K. Haas, Frank A. La Sorte, Hanna M. McCaslin, Maria C. T. D. Belotti, Kyle G. Horton
Publication: Global Ecology and Biogeography
Publication Link: https://onlinelibrary.wiley.com/doi/full/10.1111/geb.13567
Keywords: bird migration, citizen science, community science, eBird, phenology, radar remote sensing
Aim: Measuring avian migration can prove challenging given the spatial scope and the
diversity of species involved. No one monitoring technique provides all the pertinent
measures needed to capture this macroscale phenomenon –emphasizing
the need for data integration. Migration phenology is a key metric characterizing large-scale
migration dynamics and has been successfully quantified using weather surveillance
radar (WSR) data and community science observations. Separately, both platforms
have their limitations and measure different aspects of bird migration. We sought to
make a formal comparison of the migration phenology estimates derived from WSR
and eBird data –of which we predict a positive correlation.
Location: Contiguous United States.
Time period: 2002–2018.
Major taxa studied: Migratory birds.
Methods: We estimated spring and autumn migration phenology at 143 WSR stations
aggregated over a 17-year period (2002–2018), which we contrast with eBird-based
estimates of spring and autumn migration phenology for 293 nocturnally migrating
bird species at the 143 WSR stations. We compared phenology metrics derived
from all species and WSR stations combined, for species in three taxonomic orders
(Anseriformes, Charadriiformes and Passeriformes), and for WSR stations in three
North American migration flyways (western, central and eastern).
Results: We found positive correlations between WSR and eBird-based
estimates of migration phenology and differences in the strength of correlations among taxonomic
orders and migration flyways. The correlations were stronger during spring migration,
for Passeriformes, and generally for WSR stations in the eastern flyway. Autumn migration
showed weaker correlation, and in Anseriformes correlations were weakest
overall. Lastly, eBird-based estimates slightly preceded those derived from WSR in
the spring, but trailed WSR in the autumn, suggesting that the two data sources measure
different components of migration phenology.