Mechanistic model of drying soils and desert biocrusts

This repository includes source codes of the desert biocrust model (DBM) under dynamic hydration conditions. This work is a continuation of the DBM at a static hydration condition [1]. You can find the main codes of this work at https://github.com/minsughim/DBM--Biogeoscience. To excute this model, follow the instruction there and excute the main code, Main_BSC_biogeoscience.m.

The model for drying soils [2] uses the output of Main_BSC_biogeoscience.m as an initial condition. This ensures that distribtuion and activity of microbial communities are stabilised under given conditions (Think of sampling a real soil and performing experiments under desired conditions!). The stabilised communities undergo dry and dark conditions for 3 days (enough to exhaust carbon sources and nitrification activity becomes dominant). After the population dynamics reaches to a psuedo-steady state, a wet-dry cycle (duration of 24 hours) is applied.

The main difference to the Main_BSC_biogeoscience.m is the dynamic update of hydration condition (assigned with matric potential). During wetting or drying, the domain conserves the masses of all compunds, leading to changes in concentrations and gases efflux.

Usage

STEP 0. MATLAB Installation and download all files in the entire folder named 'codes'

STEP 1. Inoculation of microbial cells at field capacity (-3kPa)

Excute Main_BSC_biogeoscience.m and obtain the stabilised microbial community at field capacity.
For this, you need four input arguments;

1. Time for the dynamics (examineDays)
2. matric potential for unsaturated soils (pot1, with the unit of [-kPa])
3. time interval for output (plottt, with the unit of mins.)
4. index for ensemble averages (indexS, any integer to indicate a simulation) For example, to get the results of 5 days of simulation with output for every 5 mins at the matric potential of -3kPa, you excute in Matlab

examineDay = 5; 
pot1 = 3; % at field capcity
plottt = 5; 
indexS = 0;
Main_BSC_biogeoscience(examineDay, pot1, plottt, indexS)

This code will generate a folder named "HT_BSC_Day5_Pot3.0_index0". Once the simulation is completed, there will be numtiple mat files in the folder, indluding:

Parameters.mat (physical domain, chemical parameters, and biological parameters will be saved here) HTBioCrustCNcycleHour##.mat (intermediate results, that are saved with 12 hours interval:: only saves essential, population distribution, concentraiton of chemical compounds, etc.) Final.mat (The final result with all parameters to continue the simulation under different conditions:: about 1.5~2G depending on microbial population size)

STEP 2. Microbial activity at fully saturated condtions

Once STEP1 is done, the simulation will continue for wetting of the domain by excuting following with two new input parameters: For this, you need four input arguments;

1. switch on and off the light conditions: There are three possbilities, complete darkness, constant light condition, and diurnal cycle
2. Time for dynamics under fully saturated conditions

examineDay = 5; 
pot1 = 3; % at field capcity
plottt = 5; 
indexS = 0;

lightOn = 2; % 0 for complete darkness, 1 for constant light condition, any other numbers are for simulating diurnal cycles
examineDay2 = 5; %How many days to immerse the soil system in water?
Main_BSC_immerse(lightOn,examineDay,examineDay2 pot1, plottt, indexS)

We note that the primary results up to STEP 2 are published in [1].

STEP 3, Incubation of the dry domain under darkness and apply a wetting-drying cycle

The work of [2] is related to this STEP, drying and incubating and wetting of the soil system (biocrusts). Here 4 more inputs can be applied to change the boudnary conditions:

1. mixing ratio of NH3 in ppb
2. mixing ratio of HONO in ppb
3. drying patterns (Pre-calculated matric potential changes with 13 different rates are given in desiccation_biocrst.mat)
4. temperature (in this work, the effect of temperature was not explored, but possible in the model).

NH3ppb = 5; %atmospheric level of NH3 in ppb
HONOppb = 1; %atmospheric level of HONO in ppb
desiccationIndex = 4; %pre-calcuated drying patterns for 24 hours duration (should be integer between 1 and 13)
newT = 25; %changing ambient temperature is also possible (degree celcius)
examineDay = 5; 
pot1 = 3; % at field capcity
indexS = 0;
Main_BSC_wet_dry(NH3ppb, HONOppb,desiccationIndex, newT, examineDay, pot1, indexS)

STEP 4, Post processing of results

hono = 1;
nh3 = 20;
desiccationIndex = 4;
newT = 25;
numberOfSamples = 8; % number of simulations under 1 boundary conditions
Process_results(hono, nh3,desiccationIndex,newT,numberOfSamples)

Example model excution

To simulate a biocrust under p[HONO] = 1ppb, p[NH3] = 5ppb, at 25 degree celcius with the slow drying (presented in Figure 6 in [2]), you can run Matlab with the following command

examineDay = 5; 
pot1 = 3; % at field capcity
plottt = 5; % write dynamics every 5 mins.
indexS = 0;
numberOfSamples = 8;
for indexS = 0:numberOfSamples
  Main_BSC_biogeoscience(examineDay, pot1, plottt, indexS)
  lightOn = 2; % 0 for complete darkness, 1 for constant light condition, any other numbers are for simulating diurnal cycles
  examineDay2 = 5; %How many days to immerse the soil system in water?
  Main_BSC_immerse(lightOn,examineDay,examineDay2 pot1, plottt, indexS)
  NH3ppb = 5; %atmospheric level of NH3 in ppb
  HONOppb = 1; %atmospheric level of HONO in ppb
  desiccationIndex = 4; %pre-calcuated drying patterns for 24 hours duration (should be integer between 1 and 13)
  newT = 25; %changing ambient temperature is also possible (degree celcius)
  Main_BSC_wet_dry(NH3ppb, HONOppb,desiccationIndex, newT, examineDay, pot1, indexS)
end

Process_results(HONOppb, NH3ppb,desiccationIndex,newT,numberOfSamples)

The final result file will be created with the name 'HT_BSC_newT25_NH35_HONO1_Drying4.mat' (about 700MB) with all variables, population sizes and distribution, concentrations of chemical compunds, gaseous efflux of CO2, O2, HONO, NH3, and N2O, and, of course the dynamics of the local pH distribution in the soil domain.

Note

1. The DBM is computationally very expensive and rather slow on local desktops. For instance, using 32 cores in a computing cluster requires 4-5 days to complete a single simulation from STEP 1 to STEP 3

2. The main code includes mex files that are complied for Mac and Linux systems only (tested on MATLAB 2017b (9.3.0.713579) 64-bit)

Reference

[1] Kim, M. and Or, D.: Hydration status and diurnal trophic interactions shape microbial community function in desert biocrusts, Biogeosciences, 14, 5403-5424, https://doi.org/10.5194/bg-14-5403-2017, 2017.

[2] Kim, M. and Or, D.: Microscale pH variations during drying of soils and desert biocrusts affect HONO and NH3 emissions, Nature Communications, 10:3944, https://doi.org/10.1038/s41467-019-11956-6, 2019.