Predicting resilience through the lens of competing adjustments to vegetation function

Manon E. B. Sabot, Martin G. De Kauwe, Andy J. Pitman, David S. Ellsworth, Belinda E. Medlyn, Silvia Caldararu, Sönke Zaehle, Kristine Y. Crous, Teresa E. Gimeno, Agnieszka Wujeska-Klause, Mengyuan Mu, and Jinyan Yang.

Overview

Repository containing all the code to reproduce the results in Sabot et al. (2022): Predicting resilience through the lens of competing adjustments to vegetation function. Plant, Cell, & Environment, Accepted.

 

General instructions

⚠ Only the model and analysis codes are stored in this github repository. If you also want to access the data files, they are available from zenodo.

 

To make sure the model and support files are properly set up, simply type:

make -f setup.mk

N.B.1: You need anaconda to use the existing environment files within which to run the model. By default, python 3.8 will be used to run the model. If you would rather install the dependencies locally, you will need python.

N.B.2: There are issues with the automated install of the dominance-analysis package used in the analysis section, so it is commented out from the environment file. If you cannot easily install it, you can download this file into the current repository (i.e., Competing_Optimal_Adjustments) and then type pip install dominance_analysis-1.0.0-py3-none-any.whl in the command line, which should manage the install.

 

If you have already setup the environment, simply type:

conda activate competing_opts

 

To regenerate all our results and figures, type:

make

N.B.1: In this demo version, the simulation scripts called by Makefile are setup to run on very CPUs (4 to 6 for most machines, depending on your machine). This will be very slow, so it would be worth adding defining a higher number of CPUs to use by parsing the -c Nargument after each of the.sh` simulation scripts, shall you wish to recreate our results.

N.B.2: In the current Makefile, the commands used to calibrate the input file parameters (in preparation) and to run the model simulations (in simulations) are commented out, as this takes a long time without parallelisation, and the outputs are already written to files stored in input/ and output/

 

To recalculate and recalibrate the model parameters alone, uncomment the Makefile and type:

make preparation

To rerun the model simulations only, uncomment the Makefile and type:

make simulations

To perform the various analyses on the output again:

make analyses

Finally, to simply recreate our figures:

make plots

And to clean up old log files from the src/tmp/ folder, type:

make clean

 

The model

The model used here is a new version of the TractLSM (Sabot et al., 2019), which originally only embedded a canopy gas exchange optimisation approach. The new version of the model: (i) also includes a scheme that optimises leaf nitrogen allocation, thus V_cmax25 and J_max25; and (ii) incorporates a representation of legacy effects from sustained hydraulic damage.

Different model configurations can optimise canopy gas exchange, plus leaf nitrogen allocation and/or hydraulic legacies over various timescales, as summarised in the schematics below:

 

 

All our model experiments are detailed in the associated publication, and for anyone interested, the code is thoroughly commented.

For more details on the model, you can also refer to src/TractLSM/ReadMe.

 

To go further...

If you wish to further explore model behaviour, simply make changes to src/irun.txt (similar to a namelist) and type:

src/ExecTractLSM src/irun.txt

 

Data Files

Available from .

Please see input/ReadMe in the zenodo repository for more detail.

 

License

This project is licensed under the MIT License - see the License file.

 

Contact

Manon Sabot: [email protected]