Differential fall migratory routes of adult and juvenile Ipswich Sparrows (Passerculus sandwichensis princeps)

Abstract

BackgroundIsland breeding birds present an ideal system for studying migratory movements in passerines because their populations are clearly demarcated, and individuals must depart on migration from a single location. The Ipswich Sparrow (Paserculus sandwichensis princeps) is a subspecies of the Savannah Sparrow that breeds exclusively on Sable Island, Nova Scotia, Canada and winters along the Atlantic coast of North America. We used a network of 34 automated VHF telemetry receivers to track radio-tagged adult and juvenile Ipswich Sparrows from their breeding island southward through the first half of their fall migratory journey.ResultsWe compared adult to juvenile timing and routes. We show that juveniles leave the island approximately 24 days prior to adults and remain temporally separated from them during migration through Nova Scotia. Juveniles have different overwater orientations that result in migratory routes with shorter ocean crossings and a longer overall distance travelled compared to adults. Juveniles also have more frequent and longer stopovers, and displayed some reverse migration.ConclusionWe demonstrate that migratory routes differ between adults and juveniles, suggesting that routes change as individuals age, possibly through learning or social interactions. These differential routes also suggest that sparrows experience risk in different ways with juveniles selecting shorter overwater flights with less navigational risk at the cost of increased time spent in migration.Electronic supplementary materialThe online version of this article (doi:10.1186/s40462-016-0067-8) contains supplementary material, which is available to authorized users.

Prolonged stopover and consequences of migratory strategy on local-scale movements within a regional songbird staging area

“…Adults select tailwinds more effectively (Mitchell et al 2015), refuel faster (Seewagen et al 2013), make fewer and shorter stopovers (Crysler et al 2016), and migrate more rapidly than juveniles (Ellegren 1993). However, it is unlikely that age is the primary cause of prolonged stopovers in our study, given that adults comprise nearly every instance of prolonged stopovers documented to date in geolocator studies.…”

The Motus Wildlife Tracking System: a collaborative research network to enhance the understanding of wildlife movement

“…For any species, the use of closely-spaced grids allows activity levels (e.g., stopover duration, departure timing, diel activity) and local-and broadscale movement parameters (e.g., migratory speed, timing, orientation) to be estimated. Transient receivers on moving/ floating platforms can capture movements of birds at sea (Crysler 2015, Loring 2016Ronconi, Taylor, Crysler, et al, unpublished manuscript).…”

“…The ability to estimate these parameters has led to advancements in our understanding of the movement behavior of small animals, including the spatial and temporal scale of migratory stopover , Mann et al 2017, Neima 2017, the influence of ecological barriers on movement behaviour , Crysler 2016, Dossman et al 2016, postfledging dispersal movements (Brown andTaylor 2015, Crysler 2015), migratory connectivity (McKellar et al 2015), the proximate mechanisms of orientation and navigation (Kishkinev et al 2016), and effects of availability of roosting habitat on duration of stay (Mann et al 2017). We have also gained understanding of how movements are influenced by intrinsic and extrinsic factors, including age (Brown and Taylor 2015, Crysler et al 2016, Dossman et al 2016, Kennedy et al 2016, sex (Falconer et al 2016), physiological condition (Dossman et al 2016, Eikenaar et al 2017, habitat (Woodworth et al 2014), and weather , Dossman et al 2016, Loring 2016, Neima 2017.…”

“…We have also gained understanding of how movements are influenced by intrinsic and extrinsic factors, including age (Brown and Taylor 2015, Crysler et al 2016, Dossman et al 2016, Kennedy et al 2016, sex (Falconer et al 2016), physiological condition (Dossman et al 2016, Eikenaar et al 2017, habitat (Woodworth et al 2014), and weather , Dossman et al 2016, Loring 2016, Neima 2017.…”

“…This wealth of data has led to comprehensive and diverse applications in the study of breeding and postbreeding dispersal, stopover and migration behavior, and overwintering ecology. For example, detection data from Motus collaborators have been used to estimate stopover duration (Dossman et al 2016, Mann et al 2017, Neima 2017, activity level, e.g., onset of diel activity, stopover versus active migration (Crysler et al 2016;Morbey et al, unpublished data), regional and site fidelity during migratory stopover (Mann et al 2017, Neima 2017, precise departure and arrival times , Dossman et al 2016, Müller et al 2016), departure and flight orientation , Crysler et al 2016, Kishkinev et al 2016, Neima 2017, flight distance, time, and therefore flight speed (Woodworth et al 2014, 2015, Brown and Taylor 2015, Crysler et al 2016, Falconer et al 2016, colony attendance patterns (Loring 2016), and types of movements, e.g., migratory, relocation (Woodworth et al 2014, 2015, Crysler et al 2016). …”