https://github.com/bioatmosphere/an_emergent_soil_enzyme_decomposition_model

Source data and code supporting model-based analysis of emergent properties (ECA) of soil enzyme-driven organic matter decomposition

https://github.com/bioatmosphere/an_emergent_soil_enzyme_decomposition_model

Science Score: 13.0%

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Keywords

eca ecological-scaling ecosystem-model emergent enzyme equilibrium-chemistry-approximation heterogeneity jupyter jupyter-notebook michaelis-menten soil
Last synced: 6 months ago · JSON representation

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Source data and code supporting model-based analysis of emergent properties (ECA) of soil enzyme-driven organic matter decomposition

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eca ecological-scaling ecosystem-model emergent enzyme equilibrium-chemistry-approximation heterogeneity jupyter jupyter-notebook michaelis-menten soil
Created about 7 years ago · Last pushed about 3 years ago
Metadata Files
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README.md

Emergent properties of organic matter decomposition by soil enzymes

This repository deposits source data and code supporting our model-based analysis of Emergent properties of organic matter decomposition by soil enzymes:

Wang, B., & Allison, S. D. (2019). Emergent properties of organic matter decomposition by soil enzymes. Soil Biology and Biochemistry, 107522.

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Emergent Enzyme Kinetics

In detail, this repository stores data & code following the order of figures occurring in our manuscript:

For each figure (seven in total, of which 3 are supporting figures), the source data (.csv) and the corresponding code (.ipynb) doing the statistical analyses (in R/Python) and drawing the figures (in Python 3.6) in Jupyter Notebook are deposited in a seperate folder. More importantly, all 'real' source data, which are literally model outputs, are provided in the /Source Data folder. These source data have the potential to be further tapped into for other analyses.

With JupyterNotebook, step-by-step analyses are demonstrated, facilitating reproducible analyses. Some essential Python packages (Pandas and Numpy, as well as Matplotlib), of course, should be installed before any real re-runs of these notebooks.

Any questions should be directed to B. Wang at wbwenwu@gmail.com or bw8my@virginia.edu


File Strucure

Publication/

The pulished manuscript in pdf and supporting material in .docx.

Source Data/

Data from the model outputs of DEMENT, in contrast to the data presented below which is processed (but just literally data extraction) and derived from these data. How to extract data from these outputs, the code used, is demonstrated in Jupyter Notebooks with R. In addition, parameters setting up the DEMENT is listed.

Figure_1/

All data and jupyter notebooks pertaining to the Figure 1

Figure_2/

Similarly, all data and jupyter notebooks pertaining to the Figure 2. And the supporting Fig.1 can be derived from here.

Figure_3/

Similarly, all data and jupyter notebooks pertaining to the Figure 3

Figure_4/

Similarly, all data and jupyter notebooks pertaining to the Figure 4. And the supporting Fig.2 and Fig.3 can be derived from here.

Owner

  • Name: Bin Wang
  • Login: bioatmosphere
  • Kind: user
  • Location: Oak Ridge

Studying biosphere-atmosphere interactions with interwoven theory- and data-driven approaches

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