Coupled-Social-and-Land-Dynamics

The python scripts and data in this repository correspond to the manuscript titled -

"Coupled social and land use dynamics affect dietary choice and agricultural land-use extent" - Saptarshi Pal, Chris T. Bauch, Madhur Anand

Information about the repository:

1. The folder 'figdata' contains the data used to generate the figures in main text in csv format.
2. The folder 'data' contains all model output data generated by the coupled social land use model in csv format.
3. The folder 'code' contains the code necessary for parameterizing the coupled model and making projections with the parameterized model.

Prerequisite for code:

Packages required:

lmfit (install with pip in terminal: pip install lmfit) pandas (install with pip in terminal: pip install pandas) scipy (install with pip in terminal: pip install scipy)

Data download:

In order to run projecitons.py the user needs to download a dataset and save it as 'IPCC_Projections.csv' in the subfolder.

The dataset can be found in the publicly accessible database:

https://tntcat.iiasa.ac.at/SspDb/

Go to Download tab and register as a user. Download the dataset titled

SspDb_country_data_2013-06-12.csv.zip

labelled under Basic Elements.

Instructions about code:

The folder contains two python scripts - projecitons.py and parameter_estimation.py

The script parameter_estimation.py estimates the coupled social and land model parameters for a country provided the starting and the ending period of the parameterization are mentioned. To run this script from terminal one needs to run the following as an example:

python parameter_estimation.py 231 1961 2013

231 refers to the FAO country code of the United States of America (for more details on FAO country codes see http://www.fao.org/faostat) 1961 and 2013 are the beginning and ending years of the parameterization period. The results of the parameter estimation will be saved in the folder 'results' as a csv file.

Results of all parameters for all countries included in our analysis can be found under /code/loaddata/parameters.csv

The script projections.py projects global land use and proportion of eco-conscious consumers in all countries considered in our analysis from 2011 till 2100 under SSP scenarios of population and income and f scenarios of yield. To run this script from terminal one needs to run the following as an example:

python projections.py 0 0 0 SSP3 0.4

for baseline projections (indicated by 0 0 0) under SSP3 population and income scenario at the yield scenario of f = 0.4

For questions please contact owner of repository or email at s24pal@uwaterloo.ca