Medicine and Health Sciences Commons^™

Integrating Data Types To Estimate Spatial Patterns Of Avian Migration Across The Western Hemisphere, Timothy D. Meehan, Sarah P. Saunders, William V. Deluca, Nicole L. Michel, Joanna Grand, Jill L. Deppe, Miguel F. Jimenez, Erika J. Knight, Nathaniel E. Seavy, Melanie A. Smith, Lotem Taylor, Chad Witko, Michael E. Akresh, David R. Barber, Erin M. Bayne, James C. Beasley, Jerrold L. Belant, Richard O. Bierregaard, Keith L. Bildstein, Than J. Boves, John N. Brzorad, Steven P. Campbell, Antonio Celis-Murillo, Hilary A. Cooke, Robert Domenech, Laurie Goodrich, Elizabeth A. Gow, Aaron Haines, Michael T. Hallworth, Jason M. Hill, Amanda E. Holland, Scott Jennings, Roland Kays, Tommy King, Stuart A. Mackenzie, Peter P. Marra, Rebecca A. Mccabe, Kent P. Mcfarland, Michael J. Mcgrady, Ron Melcer, D. Ryan Norris, Russell E. Norvell, Olin E. Rhodes, Christopher C. Rimmer, Amy L. Scarpignato, Adam Shreading, Jesse L. Watson, Chad R. Wilsey

USDA Wildlife Services: Staff Publications

For many avian species, spatial migration patterns remain largely undescribed, especially across hemispheric extents. Recent advancements in tracking technologies and high-resolution species distribution models (i.e., eBird Status and Trends products) provide new insights into migratory bird movements and offer a promising opportunity for integrating independent data sources to describe avian migration. Here, we present a three-stage modeling framework for estimating spatial patterns of avian migration. First, we integrate tracking and band re-encounter data to quantify migratory connectivity, defined as the relative proportions of individuals migrating between breeding and nonbreeding regions. Next, we use estimated connectivity proportions along with eBird occurrence …