Pan-Antarctic analysis aggregating spatial estimates of Adélie penguin abundance reveals robust dynamics despite stochastic noise

• Published in: Nature Communications
• Main Authors: Che-Castaldo, Christian, Jenouvrier, Stephanie, Youngflesh, Casey, Shoemaker, Kevin T., Humphries, Grant, McDowall, Philip, Landrum, Laura, Holland, Marika M., Li, Yun, Ji, Rubao, Lynch, Heather J.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Nature Publishing Group 2017
• Subjects: Antarctic; Southern Ocean; The Antarctic; Antarc*; National Science Foundation Office of Polar Programs
• Online Access: https://hdl.handle.net/1912/9307

© The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Nature Communications 8 (2017): 832, doi:10.1038/s41467-017-00890-0. Colonially-breeding seabirds have long served as indicator species for the health of the oceans on which they depend. Abundance and breeding data are repeatedly collected at fixed study sites in the hopes that changes in abundance and productivity may be useful for adaptive management of marine resources, but their suitability for this purpose is often unknown. To address this, we fit a Bayesian population dynamics model that includes process and observation error to all known Adélie penguin abundance data (1982–2015) in the Antarctic, covering >95% of their population globally. We find that process error exceeds observation error in this system, and that continent-wide “year effects” strongly influence population growth rates. Our findings have important implications for the use of Adélie penguins in Southern Ocean feedback management, and suggest that aggregating abundance across space provides the fastest reliable signal of true population change for species whose dynamics are driven by stochastic processes. H.J.L., C.C.-C., G.H., C.Y., and K.T.S. gratefully acknowledge funding provided by US National Aeronautics and Space Administration Award No. NNX14AC32G and U.S. National Science Foundation Office of Polar Programs Award No. NSF/OPP-1255058. S.J., L.L., M.M.H., Y.L., and R.J. gratefully acknowledge funding provided by US National Aeronautics and Space Administration Award No. NNX14AH74G. H.J.L., C.Y., S.J., Y.L., and R.J. gratefully acknowledge funding provided by U.S. National Science Foundation Office of Polar Programs Award No. NSF/PLR-1341548. S.J. gratefully acknowledges support from the Dalio Explore Fund.