ClimAg: Multifactorial causes of fodder crises in Ireland and risks due to climate change

:sparkles: ClimAg report: Streethran, N., Hickey, K., Wingler, A., and Leahy, P. (2024). ClimAg: Multifactorial Causes of Fodder Crises in Ireland and Risks due to Climate Change. Johnstown Castle: Environmental Protection Agency (EPA Research Report, 464). Available at: https://www.epa.ie/publications/research/climate-change/research-464-climag-multifactorial-causes-of-fodder-crises-in-ireland-and-risks-due-to-climate-change.php (Accessed: 17 October 2024).

ClimAg is examining past fodder crises such as the 2018 dry summer and placing them in the context of long-term climate change. ClimAg seeks to identify the multifactorial drivers of fodder crises by:

• developing a detailed understanding of the multiple interlinked drivers of previous fodder crises affecting the Irish agricultural sector
• combining datasets from 21st century climate simulations with grass growth models to predict the frequency and severity of fodder crisis events under future climate change scenarios

Documentation is available at: climag.readthedocs.io. This repository hosts Python code for the grass growth model and scripts to perform data preparation, model simulations, and analysis.

Acknowledgements

ClimAg is a three-year research project funded by the Environmental Protection Agency (EPA) Ireland under the Climate Change Research Programme grant number 2018-CCRP-MS.50, with additional funding provided under the COVID-19 research support scheme of the Higher Education Authority (HEA) Ireland.

The authors acknowledge the inputs of the ClimAg project steering committee members throughout the project. The authors thank Eoin Whelan (Met Éireann, Dublin, Ireland), Paul Nolan (Irish Centre for High-End Computing, Dublin, Ireland), and Elodie Ruelle (Teagasc, Moorepark, Ireland) for providing datasets used in this study.

The Python implementation of the ModVege pasture model adapted for use in this project was translated from Java to Python by Y. Chemin of JRC Ispra. This Python implementation was originally published as public domain software on GitHub under the Unlicence license. The Java model was provided by R. Martin of INRAE UREP Clermont-Ferrand for the original Python implementation. The original ModVege pasture model was developed by Jouven et al..

Installation

This project uses Conda with Python 3.10.

[!NOTE] Windows users should use Conda within Windows Subsystem for Linux (WSL), as some packages (e.g. CDO) are unavailable for Windows.

Clone the ClimAg repository including submodules:

sh git clone --recurse-submodules https://github.com/ClimAg/ClimAg.git

Navigate to the directory of the cloned repository:

sh cd ClimAg

Create a virtual environment and install all requirements:

sh conda env create

Activate the virtual environment:

sh conda activate ClimAg

To run tests:

sh python -m pytest --cov

To update the virtual environment:

sh conda env update

To build the documentation locally:

sh cd doc && make html

To clean build the documentation locally:

sh cd doc && make clean html

Licence

Copyright 2022-2025 N. Streethran

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

https://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.