me4socDemo

me4soc - Multi-model Ensemble interface for Soil Organic Carbon predictions - is a webtool designed to run a multi-model ensemble over European forest sites. It allows to predict the effect of climate, land-use and land management changes on soil organic carbon (SOC) stocks and greenhouse gas (GHG) emissions. By benefitting from the complementarity of structurally different SOC models, it provides the level of uncertainty of the predictions.

Features

Limitations

Please note that, even though the webtool can run with open source databases, using site measurements can really improve the predictive capability of the models. Thus, when possible, measurements should be prioritized. Also, the multi-model ensemble uses default model parameter values. Models should be calibrated and validated with observed data before applying them for predictions.

Models description

Simulations of SOC stocks

Soil organic carbon models represent SOC with a conventional multi-compartmental structure that can be summarized with the following matrix equation:


$\frac{d\mathbf{C}}{dt}=\mathbf{I}(t)- ξ(t)\times \mathbf{A} \times \mathbf{K}\times \mathbf{C}(t),\mathbf{\ }\mathbf{\ } \mathbf{\ } \mathbf{\ } \mathbf{C}(t=0)=\mathbf{C}_{0},$

Where:

● $\mathbf{C}(t)$ is a nx1 vector describing the mass of SOC in the n compartments as a function of time (t);

● $\mathbf{I}(t)$ is a nx1 vector representing the C inputs to the soil;

● $ξ(t)$ is the scalar effect of the pedo-climatic conditions on the decomposition of SOC;

● $\mathbf{A}$ is a nxn matrix describing the mass flow among each compartment. Its elements ${a}_{i,j}$ represent the flow of SOC from compartment j to compartment i, for i, j = 1,...,n;

● $\mathbf{K}$ is a nxn diagonal matrix containing the decomposition coefficients of the n compartments;

● $\mathbf{C}_{0}$ is a nx1 vector representing the initial level of SOC in each compartment at t=0.


Simulations of CO2 fluxes

The CO2 fluxes can also be calculated with the SOC models as: ${r}= \mathbf{R} \times \mathbf{C}(t)$, where ${r}$ is the instantaneous release of C for all compartments and $\mathbf{R}$ is a nxn diagonal matrix with the release coefficients ${r}_{j}$ calculated from matrix $\mathbf{A}$ as: $\mathbf{r}_{j}= [1-\sum_{i=1}^{n}{(a}_{i,j}{)}]$.

Other greenhouse gases

In addition to the CO2 fluxes, CH4 uptake and N2O fluxes are also estimated using the SG models. These are simple empirical models allowing to estimate GHG fluxes using data on soil physiochemical properties, water and temperature.


Models in the ensemble

The models currently included in the ensemble are:



Schematization of the SOC models


Figure Schematization of the SOC models used in the ensemble. Each box represents a SOC compartment where the C is transferred (black arrows), or respired (red arrows). DPM, RPM BIO, HUM, IOM = decomposable plant material, resistant plant material, microbial biomass, humified organic matter, inert organic matter; AM, BM, AS, BS = aboveground metabolic, belowground metabolic; aboveground structural, and belowground structural.

Models resolution

To solve the equations of the SOC models, the initial partitioning of C in the different pools needs to be estimated.

To do that, we run the models with constant inputs until all the SOC pools reach a steady-state. That is, the annual variation of SOC in all pools is lower than 0.1% for at least 10 years. As forcing, we use the average climate and environmental conditions of the decades preceding the onset of the simulations.

Finally, we solve the matrix differential equation for the specified simulation length.

Scenarios building

The webtool allows the user to simulate and plot different scenarios of climate, land-use and land management changes, in order to see their effect on the SOC stocks and GHGs emissions. In the following paragraphs, we briefly describe how the scenarios are built and the assumptions made.


Climate change scenarios


Land-use change scenario


Land management change scenario

Figure Representation of the assumptions made to calculate the litter input following a disturbance event. The image shows the disturbance scnenario (on the left) and the control (on the right).

Data input

This is the data input required to run the multi-model ensemble.

Choose the geographical coordinates of the site, the simulation length and the initial date of the simulations.

Provide details about the soil variables. Soil variables should refer to the topsoil (i.e., 0-10, 0-20 or 0-30 cm depth), and should be at least consistent with each other.

Provide details about the plant litter inputs.

Annual aboveground C input (MgC ha-1 yr-1)

Upload a .csv or .txt file with annual aboveground C input. The file should have one column where each row refers to the annual aboveground C input

Annual belowground C input (MgC ha-1 yr-1)

Upload a .csv or .txt file with annual belowground C input. The file should have one column where each row refers to the annual belowground C input

Upload files containing the climate variables for the site. Uploading only a portion of the files is not possible as using data from different sources may lead to issues in the soil water budget. In cases where not all the data is available, model outputs from the ISIMIP repository will be used for the simulations.

Daily surface temperature (˚C)

Upload a .csv or .txt file with daily surface temperature data. The file should have one column where each row refers to the daily surface temperature

Daily precipitation (mm)

Upload a .csv or .txt file with daily precipitation data. The file should have one column where each row refers to the daily precipitations

Monthly potential evapotranspiration (mm month-1)

Upload a .csv or .txt file with monthly potential evapotranspiration. The file should have one column where each row refers to the monthly potential evapotranspiration

Daily volumetric soil water content (mm3 mm-3)

Upload a .csv or .txt file with daily volumetric soil water content. The file should have one column where each row refers to the daily volumetric soil water content

Provide details about the disturbance event, such as fires, thinning, clear-cutting and diseases.

Data visualization

This page shows the pedo-climatic conditions of the site selected in the Data input panel. Make sure to enter all the data fields. It takes a while to run due to the large amount of computations.


Soil data

Climate data

Climate, land-use and land management change scenarios

This page shows the evolution of SOC stocks and CO2 fluxes under different climate scenarios (RCP 2.6 vs RCP 6.0), land-use scenarios (year-2005 fixed land-use vs varying land-use according to SSP2), and land management scenarios (with or without disturbance). It takes a while to run because multiple soil models are launched.


Move the slider to see the effect of clay on SOC stocks and CO2 fluxes

Move the slider to see the effect of clay on SOC stocks and CO2 fluxes

Move the sliders to see how changing the mortality and harvest rates affect the SOC stocks and CO2 fluxes

Download model outputs

This page allows to download the model simulation outputs for all the scenarios built.








About the multi-model ensemble

Tutorial

Documentation

GitHub Code

Contact

ebruni93@gmail.com

Licence

References