Data for “Fast-decaying plant litter enhances soil carbon in temperate forests, but not through microbial physiological traits”

Craig, Matthew; Brzostek, Edward; Geyer, Kevin; Liang, Chao; Phillips, Richard

doi:10.15485/1835182

Title: Data for “Fast-decaying plant litter enhances soil carbon in temperate forests, but not through microbial physiological traits”

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Abstract

This data package contains data and code used in the paper “Fast-decaying plant litter enhances soil carbon in temperate forests, but not through microbial physiological traits”. This paper details results from two studies: 1) a laboratory leaf litter incubation experiment (lab experiment) and 2) a multi-site observational field study (field study). Both studies were designed to test the relationships among litter quality, microbial physiological traits, and mineral-associated soil carbon (C). In the lab experiment, we incubated 16 temperate tree litters of differing chemical quality with isotopically distinct soil, measuring microbial physiological traits and the flow of litter-derived C into the mineral-associated soil C pool. In the field study, we sampled soils (0-5 cm) across six eastern US temperate forests, measuring microbial physiological traits, soil abiotic properties, and leaf litter chemistry. The analysis data are provided in two .csv files corresponding to either the lab experiment or field study. Both files contain data on litter chemistry, microbial physiological traits (growth and turnover rates, and carbon use efficiency [CUE]), and the mineral-associated soil C pool. The lab experiment dataset additionally contains litter-derived versus soil-derived soil C, respiration, and litter decomposition parameters. The field study dataset additionally contains site-level climatic information, ectomycorrhizal dominancemore »« less

Authors:

;

Indiana University; Oak Ridge National Laboratory; Oak Ridge National Laboratory
West Virginia University
University of New Hampshire
Chinese Academy of Sciences
Indiana University

Publication Date:: Thu Dec 31 23:00:00 EST 2020

Research Org.:: Environmental System Science Data Infrastructure for a Virtual Ecosystem; The Carbon-Nutrient Economy of the Rhizosphere: Improving Biogeochemical Prediction and Scaling Feedbacks From Ecosystem to Regional Scales

Sponsoring Org.:: U.S. DOE > Office of Science > Biological and Environmental Research (BER)

Subject:: 54 ENVIRONMENTAL SCIENCES; EARTH SCIENCE > BIOSPHERE > ECOLOGICAL DYNAMICS > ECOSYSTEM FUNCTIONS > DECOMPOSITION; EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS; EARTH SCIENCE > LAND SURFACE > SOILS; EARTH SCIENCE > LAND SURFACE > SOILS > NITROGEN; EARTH SCIENCE > LAND SURFACE > SOILS > ORGANIC MATTER; EARTH SCIENCE > LAND SURFACE > SOILS > SOIL CHEMISTRY; EARTH SCIENCE > LAND SURFACE > SOILS > SOIL PH; EARTH SCIENCE > LAND SURFACE > SOILS > SOIL RESPIRATION; EARTH SCIENCE > LAND SURFACE > SOILS > SOIL TEXTURE; carbon; carbon mass flux into soil from litter; decomposition; microbial carbon use efficiency; mineral-associated organic matter; soil organic matter

OSTI Identifier:: 1835182

DOI:: https://doi.org/10.15485/1835182

Citation Formats


                    Craig, Matthew, Brzostek, Edward, Geyer, Kevin, Liang, Chao, and Phillips, Richard. Data for “Fast-decaying plant litter enhances soil carbon in temperate forests, but not through microbial physiological traits”.  United States: N. p., 2020. 
        Web.  doi:10.15485/1835182.

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                    Craig, Matthew, Brzostek, Edward, Geyer, Kevin, Liang, Chao, & Phillips, Richard. Data for “Fast-decaying plant litter enhances soil carbon in temperate forests, but not through microbial physiological traits”.  United States.  doi:https://doi.org/10.15485/1835182

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                    Craig, Matthew, Brzostek, Edward, Geyer, Kevin, Liang, Chao, and Phillips, Richard. 2020.  
"Data for “Fast-decaying plant litter enhances soil carbon in temperate forests, but not through microbial physiological traits”".  United States.  doi:https://doi.org/10.15485/1835182.  https://www.osti.gov/servlets/purl/1835182. Pub date:Thu Dec 31 23:00:00 EST 2020

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@article{osti_1835182,

  title        = {Data for “Fast-decaying plant litter enhances soil carbon in temperate forests, but not through microbial physiological traits”},

  author       = {Craig, Matthew and Brzostek, Edward and Geyer, Kevin and Liang, Chao and Phillips, Richard},

  abstractNote = {This data package contains data and code used in the paper “Fast-decaying plant litter enhances soil carbon in temperate forests, but not through microbial physiological traits”. This paper details results from two studies: 1) a laboratory leaf litter incubation experiment (lab experiment) and 2) a multi-site observational field study (field study). Both studies were designed to test the relationships among litter quality, microbial physiological traits, and mineral-associated soil carbon (C). In the lab experiment, we incubated 16 temperate tree litters of differing chemical quality with isotopically distinct soil, measuring microbial physiological traits and the flow of litter-derived C into the mineral-associated soil C pool. In the field study, we sampled soils (0-5 cm) across six eastern US temperate forests, measuring microbial physiological traits, soil abiotic properties, and leaf litter chemistry. The analysis data are provided in two .csv files corresponding to either the lab experiment or field study. Both files contain data on litter chemistry, microbial physiological traits (growth and turnover rates, and carbon use efficiency [CUE]), and the mineral-associated soil C pool. The lab experiment dataset additionally contains litter-derived versus soil-derived soil C, respiration, and litter decomposition parameters. The field study dataset additionally contains site-level climatic information, ectomycorrhizal dominance of plots, and plot-level soil properties. Also provided is the R code and output reproducing the results in the related publication. Analyses were originally performed using R version 3.6.1 using the package "lavaan" and the packages listed on lines 5-7 in the file "data.R".},

  doi          = {10.15485/1835182},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Thu Dec 31 23:00:00 EST 2020},

  month        = {Thu Dec 31 23:00:00 EST 2020}

}

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DOI: https://doi.org/10.15485/1835182

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