Global patterns and predictions of seafloor biomass using random forests.

A comprehensive seafloor biomass and abundance database has been constructed from 24 oceanographic institutions worldwide within the Census of Marine Life (CoML) field projects. The machine-learning algorithm, Random Forests, was employed to model and predict seafloor standing stocks from surface pr...

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Auteurs principaux:	Chih-Lin Wei, Gilbert T Rowe, Elva Escobar-Briones, Antje Boetius, Thomas Soltwedel, M Julian Caley, Yousria Soliman, Falk Huettmann, Fangyuan Qu, Zishan Yu, C Roland Pitcher, Richard L Haedrich, Mary K Wicksten, Michael A Rex, Jeffrey G Baguley, Jyotsna Sharma, Roberto Danovaro, Ian R MacDonald, Clifton C Nunnally, Jody W Deming, Paul Montagna, Mélanie Lévesque, Jan Marcin Weslawski, Maria Wlodarska-Kowalczuk, Baban S Ingole, Brian J Bett, David S M Billett, Andrew Yool, Bodil A Bluhm, Katrin Iken, Bhavani E Narayanaswamy
Format:	article
Langue:	EN
Publié:	Public Library of Science (PLoS) 2010
Sujets:	Medicine R Science Q
Accès en ligne:	https://doaj.org/article/bcb9d2ef25d947e98497c9ceea866276
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Global patterns and predictions of seafloor biomass using random forests.

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