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Remote sensing of emperor penguin abundance and breeding success

Author

Listed:
  • Alexander Winterl

    (Friedrich-Alexander Universität Erlangen-Nürnberg)

  • Sebastian Richter

    (Friedrich-Alexander Universität Erlangen-Nürnberg)

  • Aymeric Houstin

    (Friedrich-Alexander Universität Erlangen-Nürnberg
    Woods Hole Oceanographic Institution
    IPHC UMR 7178)

  • Téo Barracho

    (IPHC UMR 7178
    IRD
    Department of Biology)

  • Matthieu Boureau

    (IPHC UMR 7178)

  • Clément Cornec

    (IPHC UMR 7178
    University of Saint-Etienne)

  • Douglas Couet

    (IPHC UMR 7178)

  • Robin Cristofari

    (IPHC UMR 7178
    University of Helsinki)

  • Claire Eiselt

    (IPHC UMR 7178)

  • Ben Fabry

    (Friedrich-Alexander Universität Erlangen-Nürnberg)

  • Adélie Krellenstein

    (IPHC UMR 7178)

  • Christoph Mark

    (Friedrich-Alexander Universität Erlangen-Nürnberg)

  • Astrid Mainka

    (Friedrich-Alexander Universität Erlangen-Nürnberg)

  • Delphine Ménard

    (IPHC UMR 7178)

  • Jennifer Morinay

    (IPHC UMR 7178)

  • Susie Pottier

    (IPHC UMR 7178)

  • Elodie Schloesing

    (IPHC UMR 7178)

  • Céline Le Bohec

    (IPHC UMR 7178
    IRD
    Département de Biologie Polaire)

  • Daniel P. Zitterbart

    (Friedrich-Alexander Universität Erlangen-Nürnberg
    Woods Hole Oceanographic Institution)

Abstract

Emperor penguins (Aptenodytes forsteri) are under increasing environmental pressure. Monitoring colony size and population trends of this Antarctic seabird relies primarily on satellite imagery recorded near the end of the breeding season, when light conditions levels are sufficient to capture images, but colony occupancy is highly variable. To correct population estimates for this variability, we develop a phenological model that can predict the number of breeding pairs and fledging chicks, as well as key phenological events such as arrival, hatching and foraging times, from as few as six data points from a single season. The ability to extrapolate occupancy from sparse data makes the model particularly useful for monitoring remotely sensed animal colonies where ground-based population estimates are rare or unavailable.

Suggested Citation

  • Alexander Winterl & Sebastian Richter & Aymeric Houstin & Téo Barracho & Matthieu Boureau & Clément Cornec & Douglas Couet & Robin Cristofari & Claire Eiselt & Ben Fabry & Adélie Krellenstein & Christ, 2024. "Remote sensing of emperor penguin abundance and breeding success," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-48239-8
    DOI: 10.1038/s41467-024-48239-8
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    References listed on IDEAS

    as
    1. Christophe Barbraud & Henri Weimerskirch, 2001. "Emperor penguins and climate change," Nature, Nature, vol. 411(6834), pages 183-186, May.
    2. Stéphanie Jenouvrier & Marika Holland & Julienne Stroeve & Mark Serreze & Christophe Barbraud & Henri Weimerskirch & Hal Caswell, 2014. "Projected continent-wide declines of the emperor penguin under climate change," Nature Climate Change, Nature, vol. 4(8), pages 715-718, August.
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