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Updated: Nov 8, 2025

A Video Surveillance System to Monitor Breeding Colonies of Common Terns Sterna Hirundo
Published on: July 22, 2018
Large-scale assessment of intra- and inter-annual breeding success using a remote camera network
Casey Youngflesh1, Fiona M Jones2, Heather J Lynch3
1Department of Ecology and Evolutionary Biology University of California Los Angeles CA 90095 USA.
Abstract:
Changes in the physical environment along the Antarctic Peninsula have been among the most rapid anywhere on the planet. In concert with environmental change, the potential for direct human disturbance resulting from tourism, scientific programs, and commercial fisheries continues to rise in the region. While seabirds, such as the gentoo penguin Pygoscelis papua, are commonly used to assess the impact of these disturbances on natural systems, research efforts are often hampered by limited spatial coverage and lack of temporal resolution. Using a large-scale remote time-lapse camera network and a modeling framework adapted from capture-recapture studies, we assess drivers of intra- and inter-annual dynamics in gentoo penguin breeding success across nearly the entire species' range in the Atlantic sector of the Southern Ocean. We quantify the precise timing of egg/chick mortality within each season and examine the role of precipitation events, tourism visitation, and fishing activity for Antarctic krill Euphausia superba (a principal prey resource in the Antarctic) in these processes. We find that nest failure rates are higher in the egg than the chick stage and that neither krill fishing nor tourism visitation had a strong effect on gentoo penguin breeding success. While precipitation events had, on average, little effect on nest mortality, results suggest that extreme weather events can precipitate sharp increases in nest failure. This study highlights the importance of continuous ecosystem monitoring, facilitated here by remote time-lapse cameras, in understanding ecological responses to environmental stressors, particularly with regard to the timing of events such as extreme weather.
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