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Analysing the resilience of the European commodity production system with PyResPro, the Python Production Resilience package

Author

Listed:
  • Matteo Zampieri
  • Andrea Toreti
  • Andrej Ceglar
  • Pierluca De Palma
  • Thomas Chatzopoulos

Abstract

This paper presents a Python object-oriented software and code to compute the annual production resilience indicator. The annual production resilience indicator can be applied to different anthropic and natural systems such as agricultural production, natural vegetation and water resources. Here, we show an example of resilience analysis of the economic values of the agricultural production in Europe. The analysis is conducted for individual time-series in order to estimate the resilience of a single commodity and to groups of time-series in order to estimate the overall resilience of diversified production systems composed of different crops and/or different countries. The proposed software is powerful and easy to use with publicly available datasets such as the one used in this study.

Suggested Citation

  • Matteo Zampieri & Andrea Toreti & Andrej Ceglar & Pierluca De Palma & Thomas Chatzopoulos, 2020. "Analysing the resilience of the European commodity production system with PyResPro, the Python Production Resilience package," Papers 2006.08976, arXiv.org, revised Jun 2020.
    • Handle: RePEc:arx:papers:2006.08976
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    References listed on IDEAS

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    1. Qunying Luo, 2011. "Temperature thresholds and crop production: a review," Climatic Change, Springer, vol. 109(3), pages 583-598, December.
    2. Tamara Ben-Ari & Julien Boé & Philippe Ciais & Remi Lecerf & Marijn Van der Velde & David Makowski, 2018. "Causes and implications of the unforeseen 2016 extreme yield loss in the breadbasket of France," Nature Communications, Nature, vol. 9(1), pages 1-10, December.
    3. Delphine Renard & David Tilman, 2019. "National food production stabilized by crop diversity," Nature, Nature, vol. 571(7764), pages 257-260, July.
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