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Searching for the True Diet of Marine Predators: Incorporating Bayesian Priors into Stable Isotope Mixing Models

Overview of attention for article published in PLOS ONE, March 2014
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Title
Searching for the True Diet of Marine Predators: Incorporating Bayesian Priors into Stable Isotope Mixing Models
Published in
PLOS ONE, March 2014
DOI 10.1371/journal.pone.0092665
Pubmed ID
Authors

André Chiaradia, Manuela G. Forero, Julie C. McInnes, Francisco Ramírez

Abstract

Reconstructing the diet of top marine predators is of great significance in several key areas of applied ecology, requiring accurate estimation of their true diet. However, from conventional stomach content analysis to recent stable isotope and DNA analyses, no one method is bias or error free. Here, we evaluated the accuracy of recent methods to estimate the actual proportion of a controlled diet fed to a top-predator seabird, the Little penguin (Eudyptula minor). We combined published DNA data of penguins scats with blood plasma δ(15)N and δ(13)C values to reconstruct the diet of individual penguins fed experimentally. Mismatch between controlled (true) ingested diet and dietary estimates obtained through the separately use of stable isotope and DNA data suggested some degree of differences in prey assimilation (stable isotope) and digestion rates (DNA analysis). In contrast, combined posterior isotope mixing model with DNA Bayesian priors provided the closest match to the true diet. We provided the first evidence suggesting that the combined use of these complementary techniques may provide better estimates of the actual diet of top marine predators- a powerful tool in applied ecology in the search for the true consumed diet.

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Mendeley readers

The data shown below were compiled from readership statistics for 170 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
South Africa 2 1%
Uruguay 1 <1%
Brazil 1 <1%
Mexico 1 <1%
Argentina 1 <1%
Spain 1 <1%
United States 1 <1%
Unknown 162 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 43 25%
Student > Master 30 18%
Researcher 28 16%
Student > Bachelor 20 12%
Professor 7 4%
Other 22 13%
Unknown 20 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 89 52%
Environmental Science 33 19%
Earth and Planetary Sciences 7 4%
Biochemistry, Genetics and Molecular Biology 3 2%
Veterinary Science and Veterinary Medicine 3 2%
Other 6 4%
Unknown 29 17%