Title: Estimating resilience of crop production systems: From theory to practice
Citation: SCIENCE OF THE TOTAL ENVIRONMENT vol. 735 p. 139378
Publication Year: 2020
JRC N°: JRC114499
ISSN: 0048-9697 (online)
URI: https://www.sciencedirect.com/science/article/pii/S0048969720328953?via%3Dihub
DOI: 10.1016/j.scitotenv.2020.139378
Type: Articles in periodicals and books
Abstract: Agricultural production systems are sensitive to weather and climate anomalies and extremes as well as to other environmental and socio-economic adverse events. An adequate evaluation of the resilience of such systems helps to assess food security and the capacity of society to cope with the effects of global warming and the associated increase of climate extremes. Here, we propose and apply a simple indicator of resilience of annual crop production that can be estimated from crop production time series. First, we address the problem of quantifying resilience in a simplified theoretical framework, focusing on annual crops. This results in the proposal of an indicator, measured by the reciprocal of the squared coefficient of variance, which is proportional to the return period of the largest shocks that the crop production system can absorb, and which is consistent with the original ecological definition of resilience. Subsequently, we show the sensitivity of the crop resilience indicator to the level of management of the crop production system, to the frequency of extreme events as well as to simplified socio-economic impacts of the production losses. Finally, we demonstrate the practical applicability of the indicator using historical production data at national and sub-national levels for France. The results show that the value of the resilience indicator steeply increases with crop diversity until six crops are considered, and then levels off. The effect of diversity on production resilience is highest when crops are more diverse (i.e. as reflected in less well correlated production time series). In the case of France, the indicator reaches about 60% of the value that would be expected if all crop production time-series were uncorrelated.
JRC Directorate:Sustainable Resources

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