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Python code accompanying: "High-yield dairy cattle breeds improve farmer incomes, curtail greenhouse gas emissions and reduce dairy import dependency in Tanzania"

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Outline of model files for: High-yield dairy cattle breeds improve farmer incomes, curtail greenhouse gas emissions and reduce dairy import dependency in Tanzania

Hawkins, J.W., Komarek, A.M., Kihoro, E.M. et al. High-yield dairy cattle breeds improve farmer incomes, curtail greenhouse gas emissions and reduce dairy import dependency in Tanzania. Nat Food 3, 957–967 (2022). https://doi.org/10.1038/s43016-022-00633-5

Description Folder contents include:

• Excel sheets (.xlsx) used in income accounting

• Python files (.py & .ipynb) forming the components of the model used to conduct livestock production system simulations. The .py file can be run in any python environment, and the .ipynb file can be run as a notebook in Jupyter.

Contents

Excel • Income per household by district (Mufindi, Mvomero, Njombe, Rungwe) - Used to conduct dairy income calculations, changes in crop income, and uncertainty analysis for income estimates for each household type across districts

Python

• Simulation_engine.py Showing the core model code used to run LivSim and conduct land footprint and GHG accounting for each simulation unit.

• Model_run.ipynb Example of model instance and associated parameters used to run the simulations described in article.

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Python code accompanying: "High-yield dairy cattle breeds improve farmer incomes, curtail greenhouse gas emissions and reduce dairy import dependency in Tanzania"

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