1000_SOIL_CHEMODIVERSITY

Table of Contents

• Overview
• Project Structure
  • Project Index
• Getting Started
  • Prerequisites
  • Installation
  • Usage
  • Testing
• Project Roadmap
• Contributing
• License
• Acknowledgments

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Overview

This repository contains all scripts and analysis workflows associated with our study:“Dissolved Organic Matter Chemodiversity as a Predictor of Microbial Metabolism and Soil Respiration.” In this study, we investigated how the molecular complexity of dissolved organic matter (DOM) influences microbial metabolism and soil respiration across diverse soil ecosystems. We integrated high-resolution DOM chemistry, characterized using Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FTICR-MS), with potential soil respiration rates from sites across the United States.

Using data from the Molecular Observation Network (MONet), specifically the 1000 Soils Pilot Dataset, we pursued two main objectives:

1. To evaluate statistical relationships between DOM chemodiversity indices and microbial respiration.

2. To test the predictive performance of empirical and kinetic models incorporating DOM chemistry and soil biogeochemical variables.

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Project Structure

└── 1000_soil_chemodiversity/
    ├── 1000Soil_data
    │   ├── 1000S_Dataset_Biogeochem_Biomass_Tomography_WEOM_2023_06_12.xlsx
    │   ├── 1000Soils_Metadata_Site_Mastersheet_v1.xlsx
    │   ├── Readme File_v2.xlsx
    │   ├── icr_v2_corems2.csv
    │   └── md5sums.txt
    ├── Figure3_4.R
    ├── LICENSE
    ├── README.md
    ├── SI_figres.py
    ├── figs
    │   ├── Figure1A.html
    │   ├── Figure1B.svg
    │   ├── Figure1C.png
    │   ├── Figure2.png
    │   ├── Figure5.png
    │   ├── figure3.png
    │   ├── figure4.png
    │   └── SI
    │  		├── FigureS1-12
    │  		├── regression_table_R1.docx
    ├── figures_1_2_5.py
    ├── my_functions.py
    └── processed_data
        ├── df_BG_ICR.csv
        └── icr_by_class.csv

Project Index

1000_SOIL_CHEMODIVERSITY/

__root__

my_functions.py	❯ REPLACE-ME
Figure3_4.R	❯ REPLACE-ME
SI_figres.py	❯ REPLACE-ME
figures_1_2_5.py	❯ REPLACE-ME

figs

Figure1A.html

❯ REPLACE-ME

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Getting Started

Prerequisites

Before getting started with 1000_soil_chemodiversity, ensure your runtime environment meets the following requirements:

• Programming Language: Python

Installation

Install 1000_soil_chemodiversity using one of the following methods:

Build from source:

1. Clone the 1000_soil_chemodiversity repository:

❯ git clone https://github.com/ArjunChakrawal/1000_soil_chemodiversity

2. Navigate to the project directory:

❯ cd 1000_soil_chemodiversity

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License

This project is protected under the MIT License License.

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Acknowledgments

“Soil data were provided by the Molecular Observation Network (MONet) at the Environmental Molecular Sciences Laboratory (https://ror.org/04rc0xn13), a DOE Office of Science user facility sponsored by the Biological and Environmental Research program under Contract No. DE-AC05-76RL01830. The work (proposal: 10.46936/10.25585/60008970) conducted by the U.S. Department of Energy, Joint Genome Institute (https://ror.org/04xm1d337), a DOE Office of Science user facility, is supported by the Office of Science of the U.S. Department of Energy operated under Contract No. DE-AC02-05CH11231. The Molecular Observation Network (MONet) database is an open, FAIR, and publicly available compilation of the molecular and microstructural properties of soil. Data in the MONet open science database can be found at https://sc-data.emsl.pnnl.gov/.The National Ecological Observatory Network is a program sponsored by the National Science Foundation and operated under cooperative agreement by Battelle. A portion of soil samples collected for this research were obtained through NEON Research Support Services."

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