Towards a conceptual framework for explaining variation in nocturnal departure time of songbird migrants

Abstract

Most songbird migrants travel between their breeding areas and wintering grounds by a series of nocturnal flights. The exact nocturnal departure time for these flights varies considerably between individuals even of the same species. Although the basic circannual and circadian rhythms of songbirds, their adaptation to migration, and the factors influencing the birds’ day-to-day departure decision are reasonably well studied, we do not understand how birds time their departures within the night. These decisions are crucial, because the nocturnal departure time defines the potential flight duration of the migratory night. The distances covered during the nocturnal migratory flights in the course of migration in turn directly affect the overall speed of migration. To understand the factors influencing the arrival of the birds in the breeding/wintering areas, we need to investigate the mechanisms that control nocturnal departure time. Here, we provide the first conceptual framework for explaining the variation commonly observed in this migratory trait. The basic schedule of nocturnal departure is likely regulated by both the circannual and circadian rhythms of the innate migration program. We postulate that the endogenously controlled schedule of nocturnal departures is modified by intrinsic and extrinsic factors. So far there is only correlative evidence that birds with a high fuel load or a considerable increase in fuel load and significant wind (flow) assistance towards their migratory goal depart early within the night. In contrast, birds migrating with little fuel and under unfavorable wind conditions show high variation in their nocturnal departure time. The latter may contain an unknown proportion of nocturnal movements not directly related to migratory flights. Excluding such movements is crucial to clearly identify the main drivers of the variation in nocturnal departure time. In general we assume that the observed variation in the nocturnal departure time is explained by individually different reactions norms of the innate migration program to both intrinsic and extrinsic factors.

Immune function and blood parasite infections impact stopover ecology in passerine birds

“…This suggests that immune function is linked to stopover duration in accordance with our predictions. Our findings also refine the general assumption that “body condition” is linked to prolonged stopover duration (Müller et al 2016; Schmaljohann and Eikenaar 2017). In our study, stopover duration was related to complement activity (lysis), but this relationship was only evident in short-distance migrants.…”

“…On the basis of these data, we present physiological proximate mechanisms (other than hormonal regulations) that explain variation in key parameters of stopover ecology, which are crucial for optimal migration theory (Alerstam and Lindström 1990; Alerstam 2011). That immune function is a potential important determinant of stopover ecology had not been identified in recent conceptual models (Müller et al 2016; Schmaljohann and Eikenaar 2017) and our findings, therefore, may have important implications for migration research.…”

Nocturnal departure timing in songbirds facing distinct migratory challenges

“…The flight duration in turn affects the travel speed of a bird, which, together with its total stopover duration, defines total speed of migration (Nilsson, Klaassen, & Alerstam, ). Thus, nocturnal migrants may increase their total speed of migration by starting their migratory flights early at night (Müller et al., ), assuming that they cease these flights shortly before sunrise to select suitable stopover sites (e.g. Chernetsov, ), but see (Cochran, ; Cochran & Kjos, ).…”

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

“…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). …”