Development of flight and foraging behaviour in a juvenile seabird with extreme soaring capacities

Abstract

The early life of animals is a period of high mortality, when foraging capacities are assumed to be improved progressively. In birds, this critical period involves the improvement of the flight. How do young birds gain these capacities has rarely been studied in natural conditions especially in seabirds that spend most of their life at sea. We used detailed GPS and body acceleration data on 37 great frigatebirds (Fregata minor), to test the hypothesis that juveniles starting their first flights have lower flying capacities than adults, but that these capacities will improve during a long learning period, before independence from parents, specific to this seabird that can spend months on the wing at sea. We found that most flight components improved over time to tend towards those of adults, especially the travel speed, range, duration and maximum altitude of trips. However, unexpectedly, juveniles had higher ascent rates, soaring and gliding capacities above the sea than adults. Moreover, energy expenditure of juveniles was similar to adults during low cost travelling movements and during active foraging, but juveniles spent more time foraging actively than adults. Our results suggest that flight tactics based on long‐distance effortless movements specific to this family are acquired during a long period, but soaring and gliding capacities are already inherited by juveniles and possibly favoured by morphological adaptations specific to juveniles. These adaptations might explain the extreme dispersive capacities of juveniles.

Diel at‐sea activity of two species of great albatrosses: the ontogeny of foraging and movement behaviour

“…In this paper, we provided the first comparison of changes in movement and foraging parameters, by day and night, through the first weeks of independence at sea of two closely related species of Diomedea albatrosses. This learning period, is a topic of growing interest among seabirds (Yoda et al 2004, Riotte‐Lambert and Weimerskirch 2013, Votier et al 2017, Sherratt and Morand‐Ferron 2018, Campioni et al 2019, Collet et al 2020, Corbeau et al 2020).…”

Environmental drivers of movement in a threatened seabird: insights from a mechanistic model and implications for conservation

“…Young individuals of other petrel and albatross species also disperse rapidly away from their natal colony, suggesting an innate ability to orientate with respect to wind direction, and fly with a high level of efficiency immediately after fledging (Alderman et al, 2010;de Grissac et al, 2016;Riotte-Lambert & Weimerskirch, 2013). This is not typical of other seabird taxa, however, which instead show progressive improvements in their flight performance with the number of days since fledging (Corbeau, Prudor, Kato, & Weimerskirch, 2019;Mendez, Prudor, & Weimerskirch, 2019;Yoda et al, 2004).…”

Biologging Special Feature

“…Conversely, Corbeau et al (2020) combine GPS with measures of altitude and tri-axial acceleration to identify different flight behaviours (e.g. soaring, flapping) in great frigatebirds and quantify energy expenditure during those phases.…”

“…Corbeau et al (2020) demonstrate how juvenile great frigatebirds progressively improve their flight skills in the first few months following their first flight. Combining GPS and accelerometers to distinguish between different flight behaviours (e.g.…”

“…2020) using such metrics to quantify the cost of dispersal in roe deer Capreolus capreolus,and Corbeau, Prudor, Kato, and Weimerskirch (2020) to quantify and compare average energy expenditure during different flight phases (soaring and flapping flight) in juvenile and adult great frigatebirds Fregata minor during their foraging trips, to study the ontogeny of flight and foraging behaviour. Bonnot et al (2020) use activity sensors in roe deer to disentangle the contrasting effects of predator density and human disturbance on diel activity patterns, whereas Nuijten, Gerrits, Shamoun-Baranes and Nolet (2020) present a new data compression approach for accelerometer data to overcome limitations in storage and energy capacity of loggers and aid data transmission while preserving the behavioural signal in the data.…”