Data from: Identification of migratory bird flyways in North America using community detection on biological networks

Migratory behavior of waterfowl populations in North America has
traditionally been broadly characterized by four north-south flyways, and
these flyways have been central to the management of waterfowl populations
for more than 80 years. However, previous flyway characterizations are not
easily updated with current bird movement data and fail to provide
assessments of the importance of specific geographical regions to the
identification of flyways. Here, we developed a network model of migratory
movement for four waterfowl species —mallard (Anas platyrhnchos), northern
pintail (A. acuta), American green-winged teal (A. carolinensis), and
Canada goose (Branta canadensis) — in North America using bird band and
recovery data. We then identified migratory flyways using a community
detection algorithm and characterize the importance of smaller geographic
regions in identifying flyways using a novel metric, the consolidation
factor. We identified four main flyways for mallards, northern pintails,
and American green-winged teal with the flyway identification in Canada
geese exhibiting higher complexity. For mallards, flyways were relatively
consistent through time. However, consolidation factors revealed that for
mallards and green-winged teal the presumptive Mississippi flyway was
potentially a zone of high mixing between other flyways. Our results
demonstrate that the network approach provides a robust method for flyway
identification that is widely applicable given the relatively minimal data
requirements and is easily updated with future movement data to reflect
changes in flyway definitions and management goals.