Constructing and evaluating a continent‐wide migratory songbird network across the annual cycle

Abstract

Determining how migratory animals are spatially connected between breeding and non‐breeding periods is essential for predicting the effects of environmental change and for developing optimal conservation strategies. Yet, despite recent advances in tracking technology, we lack comprehensive information on the spatial structure of migratory networks across a species’ range, particularly for small‐bodied, long‐distance migratory animals. We constructed a migratory network for a songbird and used network‐based metrics to characterize the spatial structure and prioritize regions for conservation. The network was constructed using year‐round movements derived from 133 archival light‐level geolocators attached to Tree Swallows (Tachycineta bicolor) originating from 12 breeding sites across their North American breeding range. From these breeding sites, we identified 10 autumn stopover nodes (regions) in North America, 13 non‐breeding nodes located around the Gulf of Mexico, Mexico, Florida, and the Caribbean, and 136 unique edges (migratory routes) connecting nodes. We found strong migratory connectivity between breeding and autumn stopover sites and moderate migratory connectivity between the breeding and non‐breeding sites. We identified three distinct “communities” of nodes that corresponded to western, central, and eastern North American flyways. Several regions were important for maintaining network connectivity, with South Florida and Louisiana as the top ranked non‐breeding nodes and the Midwest as the top ranked stopover node. We show that migratory songbird networks can have both a high degree of mixing between seasons yet still show regionally distinct migratory flyways. Such information will be crucial for accurately predicting factors that limit and regulate migratory songbirds throughout the annual cycle. Our study highlights how network‐based metrics can be valuable for identifying overall network structure and prioritizing specific regions within a network for conserving a wide variety of migratory animals.

Spatially explicit network analysis reveals multi‐species annual cycle movement patterns of sea ducks

“…, Knight et al. ). One such effort is the Atlantic and Great Lakes Sea Duck Migration Study (Sea Duck Joint Venture ), which has focused on the collection of satellite telemetry data from individual sea ducks (tribe: Mergini) across multiple species in eastern North America, in order to understand landscape‐scale movement patterns and migratory habitat linkages.…”

“…), landscape‐scale population structure (Knight et al. ), and the importance of stopover sites along migration routes (Shimazaki et al. ).…”

“…One of the challenges inherent in these types of applications is that the locations of nodes within the network has to be inferred from the data themselves, except in the case of telemetry studies with receivers in fixed locations (Jacoby et al 2012, Stehfest et al 2013). However, targeted applications of network analysis to individual movement data have provided insights into the spread of disease (Tian et al 2015), landscape-scale population structure (Knight et al 2018), and the importance of stopover sites along migration routes (Shimazaki et al 2004).…”

Offspring mass variation in tree swallows: A case of bet‐hedging?

“…, Knight et al. ). Their migratory behavior, combined with the large spatio‐temporal changes in food availability linked to agricultural landscapes (Rioux Paquette et al.…”

Wind‐associated detours promote seasonal migratory connectivity in a flapping flying long‐distance avian migrant

“…Knowledge of its extent and causes is essential to understand processes affecting populations of migrants throughout the annual cycle (Boulet & Norris, ; Hewson, Thorup, Pearce‐Higgins, & Atkinson, ; Webster & Marra, ), and to implement effective conservation efforts (Cresswell, ; Marra, Norris, Haig, Webster, & Royle, ; Vickery et al, ). Acknowledging that events outside the breeding season may affect individual fitness and thereby limit or regulate population numbers, studies on migratory connectivity focus on describing the spatial relationship between wintering and breeding locations (Finch et al, , but see Cohen et al, ; Delmore, Fox, & Irwin, ; Knight et al, ; Trierweiler et al, ). However, also decisions made during the migration period could influence fitness by affecting survival (Klaassen et al, ; Sillett & Holmes, ) and arrival timing to breeding sites (Tøttrup et al, ).…”