Contrasted effects of temperature during defoliation vs. refoliation periods on the infection of rubber powdery mildew (
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ORIGINAL PAPER
Contrasted effects of temperature during defoliation vs. refoliation periods on the infection of rubber powdery mildew (Oidium heveae) in Xishuangbanna, China De-Li Zhai 1
&
Jing Wang 2 & Philippe Thaler 1,3,4 & Yiqi Luo 5 & Jianchu Xu 1,6
Received: 12 February 2020 / Revised: 1 July 2020 / Accepted: 7 July 2020 # ISB 2020
Abstract Rubber powdery mildew caused by the foliar fungi Oidium heveae is one of the main diseases affecting rubber plantations (Hevea brasiliensis) worldwide. It is particularly serious in sub-optimal growing areas, such as Xishuangbanna in SW China. To prevent and control this disease, fungicides causing serious environmental problems are widely used. Strong correlations between the infection level and the temperature variables were reported previously, but they were related to monthly data that did not allow unraveling the patterns during the entire sensitive period. We correlated the infection level of powdery mildew of rubber trees recorded over 2003–2011 with antecedent 365 days daily temperature variables using partial least squares (PLS) regression. Our PLS regression results showed that the infection level of powdery mildew responded differently to the temperature variables of the defoliation and refoliation periods. Further analysis with Kriging interpolation showed that the infection level increased by 20% and 11%, respectively, per 1 °C rise of the daily maximum and mean temperature in the defoliation season, while it decreased by 8% and 10%, respectively, per 1 °C rise of the daily maximum and temperature difference in the refoliation season. This pattern was likely linked to the effects of temperature on leaf phenology. It seems highly possible that the infection level of powdery mildew increases, as increasing trends of maximum temperature and mean temperature during the defoliation continue. Keywords Rubber plantation . Hevea brasiliensis . Partial least squares (PLS) regression . Phenology . Xishuangbanna
Electronic supplementary material The online version of this article (https://doi.org/10.1007/s00484-020-01969-y) contains supplementary material, which is available to authorized users. * De-Li Zhai [email protected]
2
Tiantong National Forest Ecosystem Observation and Research Station & Research Center for Global Change and Ecological Forecasting, School of Ecological and Environmental Sciences, East China Normal University, Shanghai 200062, China
3
CIRAD, UMR Eco&Sols, F-34398 Montpellier, France
4
Eco&Sols, CIRAD, INRAE, Institut Agro, IRD, University of Montpellier, Montpellier, France
5
Center for Ecosystem Science and Society, Department of Biological Sciences, Northern Arizona University, Arizona, Flagstaff, AZ 86011, USA
6
East and Central Asia Office, World Agroforestry Centre (ICRAF), 132 Lanhei Road, Kunming 650201, Yunnan, China
* Jianchu Xu [email protected] Jing Wang [email protected] Philippe Thaler [email protected] Yiqi Luo [email protected] 1
Key Laboratory for Economic Plants and Biotechnology, Kunming Insti
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