Global patterns and predictions of seafloor biomass using random forests.

CL, Wei; GT, Rowe; E, Escobar-Briones; A, Boetius; T, Soltwedel; MJ, Caley; Y, Soliman; F, Huettmann; F, Qu; Z, Yu; CR, Pitcher; RL, Haedrich; MK, Wicksten; MA, Rex; JG, Baguley; J, Sharma; R, Danovaro; IR, MacDonald; CC, Nunnally; JW, Deming; P, Montagna; M, Lévesque; JM, Weslawski; M, Wlodarska-Kowalczuk; BS, Ingole; BJ, Bett; DS, Billett; A, Yool; BA, Bluhm; K, Iken; BE, Narayanaswamy

doi:10.1371/journal.pone.0015323

Public

Global patterns and predictions of seafloor biomass using random forests.

Shared by NobleBlocks on Dec 30, 2010 • 12:00 AM UTC

Authors:

Wei CL

Rowe GT

Escobar-Briones E

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 pr...

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