Spatiotemporal distribution of sudden oak death in the US and Europe

被引:1
|
作者
Kang, Xuechun [1 ,2 ,3 ]
Chen, Wei [1 ,2 ,3 ]
Li, Siliang [1 ,2 ,3 ]
Wang, Tiejun [1 ,2 ,3 ]
Yu, Le [4 ]
Singh, Ramesh P. [5 ]
机构
[1] Tianjin Univ, Inst Surface Earth Syst Sci, Sch Earth Syst Sci, Tianjin 300072, Peoples R China
[2] Haihe Lab Sustainable Chem Transformat, Tianjin 300192, Peoples R China
[3] Tianjin Bohai Rim Coastal Earth Crit Zone Natl Obs, Tianjin, Peoples R China
[4] Tsinghua Univ, Dept Earth Syst Sci, Minist Educ, Key Lab Earth Syst Modeling, Beijing, Peoples R China
[5] Chapman Univ, Schmid Coll Sci & Technol, Sch Life & Environm Sci, Orange, CA 92866 USA
基金
中国国家自然科学基金;
关键词
Sudden oak death; Spatial autocorrelation; Time series analysis; Retrospective space-time permutation scan; ENSO; Lag correlation; PHYTOPHTHORA-RAMORUM; SEASONAL-ADJUSTMENT; CLIMATE-CHANGE; FOREST; PATHOGEN; SUSCEPTIBILITY; DISTURBANCES; TRANSMISSION; TEMPERATURE; LINEAGES;
D O I
10.1016/j.agrformet.2024.109891
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Sudden Oak Death (SOD) is a devastating forest disease caused by Phytophthora ramorum, leading to rapid branch and leaf wilting. This study analyzed SOD data from various sources to study the spatiotemporal distribution of this pathogen globally. The spatial autocorrelation analysis shows that seven counties in the US have positive spatial correlations with high clustering values, whereas, the other six counties have negative correlations with low clustering values. In Europe, the regions with positive spatial correlations with high clustering values are located in England, Scotland, southern Finland, northern Germany, western France, and northern Spain, and many areas show negative correlations with low clustering values. The results of time series analysis reveal a clear seasonal pattern of pathogen incidence in the western US, with the peak of pathogen occurrences mainly in May and June. Furthermore, our spatiotemporal permutation scanning approach detects six clusters in the US and four in Western Europe during 2005-2006, 2012-2013, and 2021, providing insight into temporal dynamics and geographical hotspots of SOD. Our study also explored the impact of El Nin similar to o-Southern Oscillation (ENSO) on SOD for the first time, revealing a lag correlation up to 6 months. By improving our understanding of SOD spatiotemporal patterns and dynamics, we can better predict future trends and mitigate its impact. We recommend strengthening priority protection of host plants in areas where SOD outbreaks were clustered during La Nin similar to a events, and containing outbreak risks through effective detection, early warning and isolation of susceptible plants. This study provides a basis for global forest protection and disease prevention efforts to save susceptible plants.
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页数:11
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