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

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 reso...

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Autores principales: 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.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5635117/
https://www.ncbi.nlm.nih.gov/pubmed/29018199
http://dx.doi.org/10.1038/s41467-017-00890-0
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author 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.
author_facet 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.
author_sort Che-Castaldo, Christian
collection PubMed
description 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.
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spelling pubmed-56351172017-10-12 Pan-Antarctic analysis aggregating spatial estimates of Adélie penguin abundance reveals robust dynamics despite stochastic noise 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. Nat Commun Article 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. Nature Publishing Group UK 2017-10-10 /pmc/articles/PMC5635117/ /pubmed/29018199 http://dx.doi.org/10.1038/s41467-017-00890-0 Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
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.
Pan-Antarctic analysis aggregating spatial estimates of Adélie penguin abundance reveals robust dynamics despite stochastic noise
title Pan-Antarctic analysis aggregating spatial estimates of Adélie penguin abundance reveals robust dynamics despite stochastic noise
title_full Pan-Antarctic analysis aggregating spatial estimates of Adélie penguin abundance reveals robust dynamics despite stochastic noise
title_fullStr Pan-Antarctic analysis aggregating spatial estimates of Adélie penguin abundance reveals robust dynamics despite stochastic noise
title_full_unstemmed Pan-Antarctic analysis aggregating spatial estimates of Adélie penguin abundance reveals robust dynamics despite stochastic noise
title_short Pan-Antarctic analysis aggregating spatial estimates of Adélie penguin abundance reveals robust dynamics despite stochastic noise
title_sort pan-antarctic analysis aggregating spatial estimates of adélie penguin abundance reveals robust dynamics despite stochastic noise
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5635117/
https://www.ncbi.nlm.nih.gov/pubmed/29018199
http://dx.doi.org/10.1038/s41467-017-00890-0
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