Show simple item record

dc.contributor.advisorLindstrøm, Ulf
dc.contributor.advisorBiuw, Martin
dc.contributor.advisorLowther, Andrew
dc.contributor.authorOllus, Victoria Marja Sofia
dc.date.accessioned2021-10-19T07:13:26Z
dc.date.available2021-10-19T07:13:26Z
dc.date.issued2021-08-16en
dc.description.abstractSeabird distributions reflect physical and biological features of the marine environment and their variability on different spatial and temporal scales. Different species assemblages are associated with specific oceanic habitats and concentrations of birds typically occur in areas of high biological productivity. Here I explore seabird distributions and habitat use relative to biophysical cues of biological productivity throughout the Antarctic Peninsula and Scotia Sea in austral summer. Data on seabird at-sea distributions were collected through strip-transect counts using tourism vessels as opportunistic sampling platforms. Multivariate statistical methods and generalized additive models (GAM) were used to relate seabird guild composition, abundance, and species richness to environmental covariates. Sea surface temperature (SST) and distance to coast were the most important predictors of seabird distributions. Species assemblages differed between oceanographic zones and increased abundance and species richness were encountered in generally productive areas, such as coastal regions and oceanographic fronts. Coastal areas, particularly South Georgia, were important for seabirds at the time of our survey, which coincided with the breeding season for several bird species in the area. These findings highlight the importance of environmental features on seabird distributions and habitat use. Fine-resolution community-level data on marine top predator distributions are needed when assessing change, predicting habitat shifts, and ultimately to base successful conservation measures and management decisions on. This study shows that seabird distribution data collected cost-effectively using tourism vessels as platforms of opportunity can be a valuable addition to structured surveys.en_US
dc.identifier.urihttps://hdl.handle.net/10037/22776
dc.language.isoengen_US
dc.publisherUiT Norges arktiske universitetno
dc.publisherUiT The Arctic University of Norwayen
dc.rights.holderCopyright 2021 The Author(s)
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/4.0en_US
dc.rightsAttribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)en_US
dc.subject.courseIDBIO-3950
dc.subjectVDP::Matematikk og Naturvitenskap: 400::Zoologiske og botaniske fag: 480::Marinbiologi: 497en_US
dc.subjectVDP::Mathematics and natural science: 400::Zoology and botany: 480::Marine biology: 497en_US
dc.subjectVDP::Matematikk og Naturvitenskap: 400::Zoologiske og botaniske fag: 480::Økologi: 488en_US
dc.subjectVDP::Mathematics and natural science: 400::Zoology and botany: 480::Ecology: 488en_US
dc.subjectVDP::Matematikk og Naturvitenskap: 400::Zoologiske og botaniske fag: 480::Zoogeografi: 486en_US
dc.subjectVDP::Mathematics and natural science: 400::Zoology and botany: 480::Zoogeography: 486en_US
dc.titleSeabird guild composition and distribution relative to biophysical cues throughout the Antarctic Peninsula and Scotia Seaen_US
dc.typeMaster thesisen
dc.typeMastergradsoppgaveno


File(s) in this item

Thumbnail
Thumbnail

This item appears in the following collection(s)

Show simple item record

Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)