DOI: 10.5281/zenodo.13346065
title: Data for manuscript: A framework for integrating genomics, microbial traits, and ecosystem biogeochemistry

description: Support manuscript: A framework for integrating genomics, microbial traits, and ecosystem biogeochemistry. 

Dataset includes 1) supplemental information and 2) model and analysis. 

In the supplement information, we include the following files: 1) realtive abundance of the recovered representative genomes in Stordalen Mire, 2) Mapping rules of microbial functional groups by microTrait, 3) Minimum generation time for each genome and other results of functional group mapping, 4) Genome-inferred microbial traits including Rmax and Km , 5)The community-aggregated traits weighting by relative abundance, 6)The ranges and statistics of the inferred traits of present genomes and dominant genomes, 7)Microbial traits of different functional groups synthesized from literature and the corresponding references, and 8) Simulated and observed CH4 emissions from fen and bog site. 

In the model_analyis file, we include the ecosys model source code, the modeling runs, the modeling results, and python script that are used to analyze the simulation results.  

Acknowledgments

This research is a contribution of the EMERGE Biology Integration Institute, funded by the National Science Foundation, Biology Integration Institutes Program, Award # 2022070 (V.I.R., R.K.V., S.R.S., M.B.S., E.L.B., and the EMERGE Coordinators). Additional support for individual contributors included the following. W.J.R. was supported by the Belowground Biogeochemistry Scientific Focus Area and U.K. was supported by the Watershed Function Science Area, both funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research under contract no. DE-AC02-05CH11231. G.L.M. was supported by the LLNL "Microbes Persist" Soil Microbiome Scientific Focus Area SCW1632 and an associated KBase award SCW1746. N.J.B. was supported by the US Department of Energy, Office of Science (BER), Early Career Research Program (#FP00005182). B.J.W. was supported by an Australian Research Council Future Fellowship (#FT210100521). J.T. was supported by the Laboratory Directed Research and Development Program of Lawrence Berkeley National Laboratory. 

We thank the Swedish Polar Research Secretariat and SITES for the support of the work done at the Abisko Scientific Research Station. SITES is supported by the Swedish Research Council’s grant 4.3-2021-00164. This research used resources of the National Energy Research Scientific Computing Center (NERSC) which is a U.S. Department of Energy Office of Science user facility. This research used the Lawrencium computational cluster resource provided by the IT Division at the Lawrence Berkeley National Laboratory (Supported by the Director, Office of Science, Office of Basic Energy Sciences, of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231).

The EMERGE Coordinators are: Sarah C. Bagby (Case Western Reserve University), Jeffrey P. Chanton (Florida State University), Jessica G. Ernakovich (University of New Hampshire), Regis Ferriere (University of Arizona, Université Paris Sciences & Lettres), Suzanne B. Hodgkins (Florida State University, The Ohio State University), Virginia I. Rich (The Ohio State University), Gene W. Tyson (Queensland University of Technology), Malak M. Tfaily (University of Arizona), Ahmed A. Zayed (The Ohio State University).