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

TL;DR

This paper introduces PyResPro, a Python software package designed to compute resilience indicators for various natural and anthropic systems, demonstrated through an agricultural resilience case in Europe.

Contribution

The paper presents a new Python-based tool for assessing resilience in diverse systems, enabling detailed analysis of individual and grouped time-series data.

Findings

Effective resilience analysis of European agricultural production

Software is user-friendly and compatible with public datasets

Can evaluate resilience of single commodities and diversified systems

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.