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Global patterns and predictions of seafloor biomass using random forests

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 and Narayanaswamy, Bhavani E. (2010) Global patterns and predictions of seafloor biomass using random forests PLoS ONE, 5, (12), e15323. (doi:10.1371/journal.pone.0015323).

Record type: Article


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 primary production, water-column integrated and export particulate organic matter (POM), seafloor relief, and bottom water properties. The predictive models explain 63% to 88% of stock variance among the major size groups. Individual and composite maps of predicted global seafloor biomass and abundance are generated for bacteria, meiofauna, macrofauna, and megafauna (invertebrates and fishes). Patterns of benthic standing stocks were positive functions of surface primary production and delivery of the particulate organic carbon (POC) flux to the seafloor. At a regional scale, the census maps illustrate that integrated biomass is highest at the poles, on continental margins associated with coastal upwelling and with broad zones associated with equatorial divergence. Lowest values are consistently encountered on the central abyssal plains of major ocean basins The shift of biomass dominance groups with depth is shown to be affected by the decrease in average body size rather than abundance, presumably due to decrease in quantity and quality of food supply. This biomass census and associated maps are vital components of mechanistic deep-sea food web models and global carbon cycling, and as such provide fundamental information that can be incorporated into evidence-based management.

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Published date: 2010
Organisations: Marine Systems Modelling, Marine Biogeochemistry


Local EPrints ID: 174937
ISSN: 1932-6203
PURE UUID: 6cdae65c-01a6-4e48-b44b-6418a22f13f6

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Date deposited: 18 Feb 2011 10:07
Last modified: 18 Jul 2017 12:10

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Author: Chih-Lin Wei
Author: Gilbert T. Rowe
Author: Elva Escobar-Briones
Author: Antje Boetius
Author: Thomas Soltwedel
Author: M. Julian Caley
Author: Yousria Soliman
Author: Falk Huettmann
Author: Fangyuan Qu
Author: Zishan Yu
Author: C. Roland Pitcher
Author: Richard L. Haedrich
Author: Mary K. Wicksten
Author: Michael A. Rex
Author: Jeffrey G. Baguley
Author: Jyotsna Sharma
Author: Roberto Danovaro
Author: Ian R. MacDonald
Author: Clifton C. Nunnally
Author: Jody W. Deming
Author: Paul Montagna
Author: Mélanie Lévesque
Author: Jan Marcin Weslawski
Author: Maria Wlodarska-Kowalczuk
Author: Baban S. Ingole
Author: Brian J. Bett
Author: David S.M. Billett
Author: Andrew Yool
Author: Bodil A. Bluhm
Author: Katrin Iken
Author: Bhavani E. Narayanaswamy

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