Global Patterns and Predictions of Seafloor Biomass Using Random Forests

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

doi:10.1371/journal.pone.0015323

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.

Highlights

Rationale A ‘census’, according to our dictionaries, was originally a counting of individuals for the purpose of taxation
Partial linear regressions Our results confirmed the conclusions of Rex et al [8] and suggested significantly negative log-linear relationships of biomass, abundance, and body size for 3 large size classes with depth; none of these parameters showed statistically significant depth dependency for bacteria (Table 2)
Our regression y-intercepts were slightly lower than the previous synthesis (2.4 vs. 2.5 for bacteria; 2.2 vs. 2.3 for meiofauna; 3.1 vs. 3.2 for macrofauna; 1.8 vs. 2.3 for megafauna.), while the rate of decline biomass with depth was steeper for meiofauna (22.461024 vs. 21.761024) and macrofauna (25.261024 vs. 24.561024), but more gradual for megafauna (23.161024 vs. 23.961024, Table 2)

Summary

Introduction

Rationale A ‘census’, according to our dictionaries, was originally a counting of individuals for the purpose of taxation. A natural by-product of CoML has been new tabulations of animal abundances and biomass by CoML field projects The purpose of this CoML biomass synthesis has been to capture all the new information on biomass that has been uncovered during CoML into a single data base, independent of species composition. This project has archived and mapped a broad spectrum of biomass data from CoML projects from around the world, added data from a number of previous comprehensive reviews, and, as a result, produced maps of biomass of a limited number of size groups living on the sea floor on a world wide basis

Methods

Results

Discussion

Conclusion