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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Bibliografiske detaljer
Main Authors: Wei, Chih-Lin, Rowe, Gilbert T., Escobar-Briones, Elva, Boetius, Antje, Soltwedel, Thomas, Caley, M. Julian, Soliman, Yousria, Huettmann, Falk, Qu, Fangyuan, Yu, Zishan, Pitcher, C. Roland, Haedrich, Richard L., Wicksten, Mary K., Rex, Michael A., Baguley, Jeffrey G., Sharma, Jyotsna, Danovaro, Roberto, MacDonald, Ian R., Nunnally, Clifton C., Deming, Jody W., Montagna, Paul, Lévesque, Mélanie, Weslawski, Jan Marcin, Wlodarska-Kowalczuk, Maria, Ingole, Baban S., Bett, Brian J., Billett, David S. M., Yool, Andrew, Bluhm, Bodil A., Iken, Katrin, Narayanaswamy, Bhavani E.
Format: Artigo
Sprog:Inglês
Udgivet: Public Library of Science 2010
Fag:
Research Article
Online adgang:https://ncbi.nlm.nih.gov/pmc/articles/PMC3012679/
https://ncbi.nlm.nih.gov/pubmed/21209928
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0015323
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