Evidence map›Paper›PMID 29018199›Full record

ArticleNature communications2017

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

Christian Che-Castaldo, Stephanie Jenouvrier, Casey Youngflesh, Kevin T Shoemaker, Grant Humphries, Philip McDowall, Laura Landrum, Marika M Holland, Yun Li, Rubao Ji and 1 more

Abstract read
In one paragraph

Article in Nature communications, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Christian Che-CastaldoDepartment of Ecology & Evolution, Stony Brook University, Life Sciences 106, Stony Brook, NY, 11794, USA. christian.che-castaldo@stonybrook.edu.ORCID http://orcid.org/0000-0002-7670-2178
Stephanie JenouvrierBiology Department, Mailstop 50, Woods Hole Oceanographic Institution, 266 Woods Hole Road, Woods Hole, MA, 02543, USA.ORCID http://orcid.org/0000-0003-3324-2383
Casey YoungfleshDepartment of Ecology & Evolution, Stony Brook University, Life Sciences 106, Stony Brook, NY, 11794, USA.ORCID http://orcid.org/0000-0001-6343-3311
Kevin T ShoemakerDepartment of Ecology & Evolution, Stony Brook University, Life Sciences 106, Stony Brook, NY, 11794, USA.ORCID http://orcid.org/0000-0002-3789-3856
Grant HumphriesDepartment of Ecology & Evolution, Stony Brook University, Life Sciences 106, Stony Brook, NY, 11794, USA.ORCID http://orcid.org/0000-0001-5783-9892
Philip McDowallDepartment of Ecology & Evolution, Stony Brook University, Life Sciences 106, Stony Brook, NY, 11794, USA.
Laura LandrumNational Center for Atmospheric Research, P.O. Box 3000, Boulder, CO, 80307, USA.ORCID http://orcid.org/0000-0002-6003-1146
Marika M HollandNational Center for Atmospheric Research, P.O. Box 3000, Boulder, CO, 80307, USA.
Yun LiCollege of Marine Science, University of South Florida, 140 7th Avenue South, St. Petersburg, FL, 33701, USA.ORCID http://orcid.org/0000-0002-4766-4723
Rubao JiBiology Department, Mailstop 33, Redfield 2-14, Woods Hole Oceanographic Institution, 266 Woods Hole Road, Woods Hole, MA, 02543, USA.
Heather J LynchDepartment of Ecology & Evolution, Stony Brook University, Life Sciences 106, Stony Brook, NY, 11794, USA. heather.lynch@stonybrook.edu.ORCID http://orcid.org/0000-0002-9026-1612

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.Adélie penguins are a key Antarctic indicator species, but data patchiness has challenged efforts to link population dynamics to key drivers. Che-Castaldo et al. resolve this issue using a pan-Antarctic Bayesian model to infer missing data, and show that spatial aggregation leads to more robust inference regarding dynamics.

Indexed as

Models, TheoreticalSpheniscidaeAnimalsAntarctic RegionsBayes TheoremHumansPopulation DynamicsPopulation GroupsStochastic Processes

Identifiers

PMID29018199
PMCPMC5635117

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.