Synchronous timing of return to breeding sites in a long-distance migratory seabird with ocean-scale variation in migration schedules

Abstract

Background: Migratory birds generally have tightly scheduled annual cycles, in which delays can have carry-over effects on the timing of later events, ultimately impacting reproductive output. Whether temporal carry-over effects are more pronounced among migrations over larger distances, with tighter schedules, is a largely unexplored question.

Methods: We tracked individual Arctic Skuas Stercorarius parasiticus, a long-distance migratory seabird, from eight breeding populations between Greenland and Siberia using light-level geolocators. We tested whether migration schedules among breeding populations differ as a function of their use of seven widely divergent wintering areas across the Atlantic Ocean, Mediterranean Sea and Indian Ocean.

Results: Breeding at higher latitudes led not only to later reproduction and migration, but also faster spring migration and shorter time between return to the breeding area and clutch initiation. Wintering area was consistent within individuals among years; and more distant areas were associated with more time spent on migration and less time in the wintering areas. Skuas adjusted the period spent in the wintering area, regardless of migration distance, which buffered the variation in timing of autumn migration. Choice of wintering area had only minor effects on timing of return at the breeding area and timing of breeding and these effects were not consistent between breeding populations.

Conclusion: The lack of a consistent effect of wintering area on timing of return between breeding areas indicates that individuals synchronize their arrival with others in their population despite extensive individual differences in migration strategies.

Keywords: Stercorarius parasiticus; Annual cycle; Arctic Skua; Carry-over effects; Migratory connectivity; Parasitic Jaeger; Phenology.

Fig. 1

Conceptual framework of the two interrelated measures of carry-over effects between events in the annual cycle. The framework assumes the population mean represents the overall optimal timing, while throughout the range of timings different advantages and disadvantages can be attributed. A Here an example delay ($d_1$) relative to the population mean timing (${\overline{x}}_{t_1}$) of event 1 affects the timing of a subsequent event $t_2$ relative to the population mean ${\overline{x}}_{t_2}$ to different degrees. The resulting degree of advancement or delay in event ($t_2$) is the net of carry-over effects and is described by its strength as partial, complete, or amplified carry-over effect, or a complete compensation. The strength of the carry-over effect can be quantified as the slope between $t_1$ and $t_2$ (B), or, between $t_1$ and the duration of the period between $t_1$ and $t_2$ (C)

Fig. 2

Wintering areas of Arctic Skuas tracked from breeding areas between East Greenland and West Siberia. Dots represent centroids of wintering positions for each track, coloured per wintering area (boxes). Green shaded areas reflect the breeding range, with red-filled dots showing the studied breeding sites, which are enlarged in the upper panel to show pie charts representing the proportion of individuals wintering in each of the seven wintering areas, with the size corresponding to the total number of individuals tracked. Sample sizes are shown as the number of tracks/number of individuals. The main stopover in the North Atlantic is shown as a dark green polygon. Abbreviations for breeding sites are SVA = Svalbard, KVP = Karupelv, HOC = Hochstetter Forland, ICE = Iceland, FAR = Faroe Islands, FAI = Fair Isle, ROU = Rousay, SVA = Svalbard, SLE = Slettnes, BRH = Brensholmen, TOB = Tobseda, ERK = Erkuta and FIN = Finland, and for breeding areas are GRE = Greenland, SCO = Scotland, NOR = mainland Norway and RUS = Russia. Abbreviations for wintering areas are PAT = Patagonian Shelf, BEN = Benguela region, GUL = Gulf of Guinea, CAR = Caribbean region, CAN = Canary Current, MED = Mediterranean Sea and IND = Indian Ocean. Sites within countries were merged for statistical analyses

Fig. 3

Relation between breeding latitude and timing (upper panels) or duration (lower panels) in Arctic Skuas tracked from breeding areas between East Greenland and West Siberia to wintering areas in the Atlantic. Shaded areas are 95% HDIs

Fig. 4

Parameter estimates of the timing of events (upper panels) or duration of phases (lower panels) per breeding and wintering area for Arctic Skuas tracked from breeding areas in the North Atlantic to wintering areas in the Atlantic. Breeding areas are ordered from South (SCO) to North (SVA) and wintering areas from North (CAN) to South (PAT). Error bars show 95% HDIs. Within breeding areas, estimates accompanied by a common letter are equivalent based on whether 0 was included in the 95% HDI of their contrast posterior distribution (values are in Additional file 1: Table S1). Filled squares on the right y-axes indicate that the 95% HDI was outside the ROPE of birds from the same colony wintering elsewhere. Colours correspond to the wintering areas in Fig. 2

Fig. 5

Marginal repeatability (upper panels) and squared posterior means of model variance components of GLMMs of timing and duration (lower panels) of timing of events (left) and duration of phases (right) in the annual cycle of Arctic Skuas tracked from breeding areas in the North Atlantic to wintering areas in the Atlantic

Fig. 6

The relationship between duration of each period and the timing of its start in Arctic Skuas tracked from breeding areas in the North Atlantic to wintering areas in the Atlantic. Thick lines show overall slope estimates, thin lines show regression lines per combination of breeding and wintering area. Note that the aspect ratio of all plots is 1, but the axis scales differ