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. (2020). Ocean sentinel albatrosses locate illegal vessels and provide the first estimate of the extent of nondeclared fishing (Vol. 117).
Keywords: bio-logging conservation illegal fisheries seabird vessel attraction
Programme: 109
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. (2019). Sub-mesoscale fronts modify elephant seals foraging behavior (Vol. 4). Bachelor's thesis, , .
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Amandine Gamble, Henri Weimerskirch, Thierry Boulinier. (2020). Seabirds blinded by ticks (Vol. 18). Bachelor's thesis, , .
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Andrea Chiang, Gene A. Ichinose, Doug S. Dreger, Sean R. Ford, Eric M. Matzel, Steve C. Myers, W. R. Walter. (2018). (Vol. 89). Bachelor's thesis, , .
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John P. Whiteman, Seth D. Newsome, Paco Bustamante, Yves Cherel, Keith A. Hobson. (2021). Quantifying capital versus income breeding: New promise with stable isotope measurements of individual amino acids (Vol. 90).
Keywords: carbon-13 compound-specific isotope analysis CSIA discrimination fasting fractionation nitrogen-15
Programme: 109
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. (2019). Coastal Sea Level and Related Fields from Existing Observing Systems (Vol. 40).
Abstract: We review the status of current sea-level observing systems with a focus on the coastal zone. Tide gauges are the major source of coastal sea-level observations monitoring most of the world coastlines, although with limited extent in Africa and part of South America. The longest tide gauge records, however, are unevenly distributed and mostly concentrated along the European and North American coasts. Tide gauges measure relative sea level but the monitoring of vertical land motion through high-precision GNSS, despite being essential to disentangle land and ocean contributions in tide gauge records, is only available in a limited number of stations. (25% of tide gauges have a GNSS station at less than 10 km.) Other data sources are new in situ observing systems fostered by recent progress in GNSS data processing (e.g., GPS reflectometry, GNSS-towed platforms) and coastal altimetry currently measuring sea level as close as 5 km from the coastline. Understanding observed coastal sea level also requires information on various contributing processes, and we provide an overview of some other relevant observing systems, including those on (offshore and coastal) wind waves and water density and mass changes.
Programme: 688
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Afsaneh Mohammadzaheri, Karin Sigloch, Kasra Hosseini, Mitchell G. Mihalynuk. (2021). Subducted Lithosphere Under South America From Multifrequency P Wave Tomography (Vol. 126).
Keywords: Andes intra-arc intra-oceanic subduction seismic tomography South America structure of the mantel
Programme: 133
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. (2019). Tracking Five Millennia of Horse Management with Extensive Ancient Genome Time Series (Vol. 177).
Keywords: ancient DNA animal breeding diversity domestication equestrian civilizations extinct lineages horses management mules selection
Programme: 1038
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Christophe Sauser, Karine Delord, Christophe Barbraud. (2021). Demographic sensitivity to environmental forcings: a multi-trait, multi-colony approach (Vol. 130).
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. (2021). Landfast ice: a major driver of reproductive success in a polar seabird (Vol. 17).
Abstract: In a fast-changing world, polar ecosystems are threatened by climate variability. Understanding the roles of fine-scale processes, and linear and nonlinear effects of climate factors on the demography of polar species is crucial for anticipating the future state of these fragile ecosystems. While the effects of sea ice on polar marine top predators are increasingly being studied, little is known about the impacts of landfast ice (LFI) on this species community. Based on a unique 39-year time series of satellite imagery and in situ meteorological conditions and on the world's longest dataset of emperor penguin (Aptenodytes forsteri) breeding parameters, we?studied the effects of fine-scale variability of LFI and weather conditions on?this?species' reproductive success. We found that longer distances to the LFI edge (i.e. foraging areas) negatively affected the overall breeding success but also the fledging success. Climate window analyses suggested that chick mortality was particularly sensitive to LFI variability between August and November. Snowfall in May also affected hatching success. Given the sensitivity of LFI to storms and changes in wind direction, important future repercussions on the breeding habitat of emperor penguins are to be expected in the context of climate change.
Keywords: breeding success climate window analysis emperor penguin nonlinear effect sea ice
Programme: 109
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