Analysing the resilience of agricultural production systems with ResiPy, the Python production resilience estimation package

Abstract

We present ResiPy, a Python object-oriented software to compute the annual production resilience indicator. This indicator can be applied to different anthropic and natural systems, e.g., agricultural production, natural vegetation and water resources, to quantify their stabilities and the risk of adverse events. We propose an illustrative application of ResiPy to agricultural production in Europe, expressed in economic terms. After estimating the single-country or single-crop resilience, we evaluate the overall resilience of diversified production systems, composed of different crops and different cultivation areas. ResiPy also includes a powerful graphical tool to visually estimate the impact of diversity on complex production systems. The robustness of the indicator and the simplicity of the code ensure its effective applicability in many fields and with different datasets.

Keywords

• Annual production resilience indicator
• APRI
• Climate resilience
• Diversity
• Agriculture
• Commodity market