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Candice Michelot, Akiko Kato, Thierry Raclot, Yan Ropert-Coudert. (2021). (Vol. 16).
Keywords: Animal behavior Animal sexual behavior Animal sociality Birds Foraging Nesting habits Penguins Reproductive success
Programme: 1091
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Morten Frederiksen, Olivier Gilg, Glenn Yannic. (2021). Cross-icecap spring migration confirmed in a high-Arctic seabird, the Ivory Gull Pagophila eburnea (Vol. 163).
Keywords: ecological barrier Greenland icecap high-altitude migration
Programme: 1210
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. (2021). (Vol. 13).
Abstract: The global climate shift currently underway has significant impacts on both the quality and quantity of snow precipitation. This directly influences the spatial variability of the snowpack as well as cumulative snow height. Contemporary glacier retreat reorganizes periglacial morphology: while the glacier area decreases, the moraine area increases. The latter is becoming a new water storage potential that is almost as important as the glacier itself, but with considerably more complex topography. Hence, this work fills one of the missing variables of the hydrological budget equation of an arctic glacier basin by providing an estimate of the snow water equivalent (SWE) of the moraine contribution. Such a result is achieved by investigating Structure from Motion (SfM) image processing that is applied to pictures collected from an Unmanned Aerial Vehicle (UAV) as a method for producing snow depth maps over the proglacial moraine area. Several UAV campaigns were carried out on a small glacial basin in Spitsbergen (Arctic): the measurements were made at the maximum snow accumulation season (late April), while the reference topography maps were acquired at the end of the hydrological year (late September) when the moraine is mostly free of snow. The snow depth is determined from Digital Surface Model (DSM) subtraction. Utilizing dedicated and natural ground control points for relative positioning of the DSMs, the relative DSM georeferencing with sub-meter accuracy removes the main source of uncertainty when assessing snow depth. For areas where snow is deposited on bare rock surfaces, the correlation between avalanche probe in-situ snow depth measurements and DSM differences is excellent. Differences in ice covered areas between the two measurement techniques are attributed to the different quantities measured: while the former only measures snow accumulation, the latter includes all of the ice accumulation during winter through which the probe cannot penetrate, in addition to the snow cover. When such inconsistencies are observed, icing thicknesses are the source of the discrepancy that is observed between avalanche probe snow cover depth measurements and differences of DSMs.
Keywords: arctic cryosphere moraine photogrammetry snow water equivalent snowcover spatial dynamics UAV-SfM
Programme: 1108
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G. J. Sutton, C. A. Bost, A. Z. Kouzani, S. D. Adams, K. Mitchell, J. P. Y. Arnould. (2021). Fine-scale foraging effort and efficiency of Macaroni penguins is influenced by prey type, patch density and temporal dynamics (Vol. 168).
Abstract: Difficulties quantifying in situ prey patch quality have limited our understanding of how marine predators respond to variation within and between patches, and throughout their foraging range. In the present study, animal-borne video, GPS, accelerometer and dive behaviour data loggers were used to investigate the fine-scale foraging behaviour of Macaroni penguins (Eudyptes chrysolophus) in response to prey type, patch density and temporal variation in diving behaviour. Individuals mainly dived during the day and utilised two strategies, targeting different prey types. Subantarctic krill (Euphausia vallentini) were consumed during deep dives, while small soft-bodied fish were captured on shallow dives or during the ascent phase of deep dives. Despite breeding in large colonies individuals seemed to be solitary foragers and did not engage with conspecifics in coordinated behaviour as seen in other group foraging penguin species. This potentially reflects the high abundance and low manoeuvrability of krill. Video data were used to validate prey capture signals in accelerometer data and a Support Vector Machine learning algorithm was developed to identify prey captures that occurred throughout the entire foraging trip. Prey capture rates indicated that Macaroni penguins continued to forage beyond the optimal give up time. However, bout-scale analysis revealed individuals terminated diving behaviour for reasons other than patch quality. These findings indicate that individuals make complex foraging decisions in relation to their proximate environment over multiple spatio-temporal scales.
Programme: 394
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