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  Global Patterns and Predictions of Seafloor Biomass Using Random Forests

Wei, C.-L., Rowe, G. T., Escobar-Briones, E., Boetius, A., Soltwedel, T., Caley, M. J., et al. (2010). Global Patterns and Predictions of Seafloor Biomass Using Random Forests. PLoS One, 5(12), 1-15.

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 Creators:
Wei, Chih-Lin, Author
Rowe, Gilbert T., Author
Escobar-Briones, Elva, Author
Boetius, Antje1, Author           
Soltwedel, Thomas1, Author           
Caley, M. Julian, Author
Soliman, Yousria, Author
Huettmann, Falk, Author
Qu, Fangyuan, Author
Yu, Zishan, Author
Affiliations:
1HGF MPG Joint Research Group for Deep Sea Ecology & Technology, Max Planck Institute for Marine Microbiology, Max Planck Society, ou_2481702              

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 Abstract: 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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Language(s): eng - English
 Dates: 2010-12-30
 Publication Status: Issued
 Pages: 15
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: eDoc: 545822
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Title: PLoS One
Source Genre: Journal
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Publ. Info: San Francisco, CA : Public Library of Science
Pages: - Volume / Issue: 5 (12) Sequence Number: - Start / End Page: 1 - 15 Identifier: ISSN: 1932-6203
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000277850