Robustness of crop disease response to climate change signal under modeling uncertainties. (February 2020)

• Record Type: Journal Article
• Authors: Launay, Marie; Zurfluh, Olivier; Huard, Frederic; Buis, Samuel; Bourgeois, Gaétan; Caubel, Julie; Huber, Laurent; Bancal, Marie-Odile
• Is Part Of: Agricultural systems. Volume 178(2020)
• Publication Date: 2020-02
• Subjects: Global warming -- Models -- Infection -- Puccinia triticina -- Multimodel; Agricultural systems -- Periodicals; Agriculture -- Environmental aspects -- Periodicals; 338.16
• DOI: 10.1016/j.agsy.2019.102733
• Languages: English
• ISSNs: 0308-521X

Abstract

Highlights: Six combinations of models offered future trends for leaf rust of wheat. Climatic risk indicators assessed the intensity, frequency & duration of leaf rust. Future climatic conditions in the autumn and winter would favor leaf rust infection. A distinct drop should be expected in the summer enabling a longer risk-free period. Abstract: Crop fungal diseases threaten food security in the dual context of a growing global population and a warming climate. Leaf rust is one of the most important wheat diseases which can result in yield losses of more than 40 %. When considering these crucial questions, innovative approaches to crop cultivation are clearly required. One essential prerequisite before the development of adaptive strategies to climate change, is to understand and forecast the potential impact of this change on fungal diseases, based on the use of modelling approaches. However, numerous epidemiological models are available; they vary considerably in terms of their complexity, and are based on hypotheses that oversimplify factors that influence the prediction of epidemics. During this study, we implemented six combinations of leaf wetness duration and infection efficiency models to simulate the future evolution of leaf rust of wheat, and compared the resulting trends. Daily and seasonal climatic indicators were inferred from the simulated infection efficiencies, from 1950 to 2100, with two contrasted Representative Concentration Pathways, RCP 4.5 and RCP 8.5, at three sites representative of traditional French wheat production areas. The inferred indicators characterize the intensity and frequency of leaf rust infection, the length and calendar positioning of the longest sequences without infection, and the relevant microclimate. Their absolute values varied considerably depending on the model combinations used, even more than between the present and future climatic periods or RCP scenarios. However, the same trends were observed in the future, with climate change being a significant explanatory variable of the evolution of the six climatic indicators simulated. The results of combining these models showed that the climatic risk of both the frequency and intensity of leaf rust infection would increase during the autumn and winter seasons, and a distinct drop should be expected during the summer, enabling a longer risk-free period. Some important common trends were thus highlighted, reinforcing confidence in the robustness of the results. These findings should be taken into account when designing adaptive strategies that will sustain production under future abiotic stresses while minimizing sanitary risks.