In Microbial-Explicit-Model/MEMC: Microbial Explicit Model Comparison

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>", 
  fig.width = 8, 
  fig.height = 5
)

library(ggplot2)
theme_set(theme_bw(base_size = 14))

MEMC is a R package that allows users to explore various representation of soil organic matter (SOM) flux dynamics within a consistent SOM pool model structure.

Installation

MEMC may be installed using the install_github function from the remotes package.

# Install the remotes package if needed, and then
# remotes::install_github("Microbial-Explicit-Model/MEMC") 

# Load the installed MEMC package
library(MEMC)

Example 1: Run `MEMC` MEND

The package ships with several already defined model configurations; use help(configurations) to see a list. Currently there are six configurations included as internal MEMC package data, with each using different representations for DOM uptake, POM decomposition, and MB decay.

All MEMC model configurations are listed in the memc_all_configs and are listed in the summary table.

summary(memc_all_configs)

Let's try using MEND, the microbial enzyme-mediated decomposition model originally developed by Wang et al. 2014.

You can type help("MEND_config") for more details about the pre-built configuration.

# Printing this MEMC model configuration will return a list giving the 
# run name, a table of the flux dynamics, parameter values, and initial
# SOM pool sizes. 
print(MEND_config)

Perform a model run using the memc_solve function, whose inputs are:

mod. A MEMC model object, either one of the model configurations included with the package or created using the memc_configure(); and
times. A numeric vector of the time sequence for which the model will be solved; the first value of times is the initial time.

mend_out <- memc_solve(mod = MEND_config, time = 0:600)

The model run results are saved in the mend_out data frame.

# Preview the run results
head(mend_out)

Visualize the run results:

library(ggplot2)
ggplot(data = mend_out) + 
  geom_line(aes(time, value, color = name), linewidth = 0.75) + 
  facet_wrap("variable", scales = "free") + 
  labs(y = "mg C/g soil", 
       x = "time (days)", 
       title = "MEND Run Results")

Example 2: Build your own model

With MEMC, users are able not only to easily run simulations with the provided model configurations, but also build toy model of their own design by selecting any combination of the supported flux dynamics. See here for an example for how to use memc_configure to build your own SOM model.

The MEMC package includes default parameter and initial pool values that are included as package data that are based on Wang et al. 2015^[Wang, G., Jagadamma, S., Mayes, M. et al. Microbial dormancy improves development and experimental validation of ecosystem model. ISME J 9, 226–237 (2015). https://doi.org/10.1038/ismej.2014.120]. This example will use these values.

Before setting up the model configuration, take a look at these defaults:

print(memc_initial_state) # this is MEMC::memc_initial_state

print(memc_params) # data(memc_params) or MEMC::memc_params

Set up the model configuration:

# Running memc_configure will print a table describing the model configuration. 
my_config <- memc_configure(params = memc_params, 
                            state = memc_initial_state, 
                            name = "my model", 
                            DOMuptake = "MM", 
                            POMdecomp = "LM", 
                            MBdecay = "LM")

Use memc_solve to run our model...

my_out <- memc_solve(mod = my_config, time = 0:500)
head(my_out)

...and compare our toy model results with the MEND results:

ggplot(data = rbind(mend_out, my_out)) + 
  geom_line(aes(time, value, color = name), linewidth = 0.75) + 
  facet_wrap("variable", scales = "free") + 
  labs(y = "mg C/g soil", 
       title = "Comparing Model Results", 
       x = "time (days)") +
  theme(legend.title = element_blank())