Migration in seabirds: seasonal structure in space and environment across species, populations and individuals

• Published in: Biology Letters
• Main Author: Merkel, Benjamin
• Format: Doctoral or Postdoctoral Thesis
• Language: English
• Published: UiT The Arctic University of Norway 2019
• Subjects: VDP::Mathematics and natural science: 400::Zoology and botany: 480::Ecology: 488; VDP::Matematikk og Naturvitenskap: 400::Zoologiske og botaniske fag: 480::Økologi: 488; VDP::Mathematics and natural science: 400::Zoology and botany: 480::Marine biology: 497; VDP::Matematikk og Naturvitenskap: 400::Zoologiske og botaniske fag: 480::Marinbiologi: 497; VDP::Mathematics and natural science: 400::Zoology and botany: 480::Zoogeography: 486; VDP::Matematikk og Naturvitenskap: 400::Zoologiske og botaniske fag: 480::Zoogeografi: 486; common guillemot; Northeast Atlantic; Uria aalge; Uria lomvia; uria
• Online Access: https://hdl.handle.net/10037/15239

Identifying drivers of population trends in migratory species is difficult, as they can face many stressors while moving through different areas and environments during the annual cycle. Their population response to environmental change may in addition be affected by consistent differences in individual behaviour, which are widespread in free-living populations. An understanding of the structure of migration in space and time across species, populations and individuals is necessary to identify potential plasticity and constraints for migratory species in a rapidly transforming physical and biological environment. This thesis uses two congeneric long-distance migrants of the genus Uria , the common ( Uria aalge ) and Brünnich’s guillemot ( Uria lomvia ) to address these questions. To this end, I utilized a large light-level geolocator tracking dataset of 887 individual guillemots breeding at 16 colonies across the Northeast Atlantic, tracked over 10 years resulting in 1740 annual tracks. Through the development of a novel method to estimate locations from twilight timings, I was able to correct biased estimates for part of my dataset, which made the overall dataset comparable. Further, with the inclusion of information about the species’ biology as well as several spatial masks, the method was able to estimate locations also during times of equinox. This in turn made it possible to investigate migratory connectivity (i.e. the connection between breeding and no-breeding regions) and individual migration strategy fidelity (i.e. consistency of individual migratory behaviour) throughout the non-breeding period. Both guillemot species are comprised of space use specialists selecting for specific sites rather than habitats. They breed in colonies displaying strong migratory connectivity, within and between species. This was apparent through a combination of colony-specific seasonal space use and occupied environmental niches, grouping Northeast Atlantic Brünnich’s guillemot populations into two and common guillemot ...