The interaction of environmental factors increases the risk of spatiotemporal transmission of pine wilt disease

• Main Authors: Fang, G. (Author), Huang, J. (Author), Li, X. (Author), Liu, D. (Author), Lu, X. (Author)
• Format: Article
• Language: English
• Published: Elsevier B.V. 2021
• Subjects: Autocorrelation; China; condition factor; disease incidence; disease transmission; Ecology; ecosystem function; environmental factor; Environmental factors; forest ecosystem; Forestry; Geodetector; Macroscales; NDVI; Normalized difference vegetation index; Pine wilt disease; Rivers; Spatial autocorrelation; Spatial autocorrelations; spatiotemporal analysis; Spatiotemporal transmission; Study areas; Sunshine Hour; Transmissions; Watersheds; wilt; Wind; Yangtze Basin; Yangtze River basin
• Online Access: View Fulltext in Publisher

 The Yangtze River basin contains one-third of the important ecological function areas in China. In recent years, pine wilt disease (PWD) has broken out in many provinces in this region, causing serious damage to the forest ecological environment. There have been many studies on the risk attribution of PWD at the stand scale but few macroscale studies. In this study, 1104 county-level administrative regions in the Yangtze River basin constituted the study area. We surveyed the epidemic of PWD and environmental factor data for the region. Taking into account the spatial heterogeneity of the risk of PWD occurrence, we conducted a macroscale attribution study on the risk of PWD outbreaks using GeoDetector. In 2000, 2005, 2010 and 2015, there were 51, 100, 101 and 126 affected counties in the Yangtze River basin, and the global Moran's I index of the incidence of PWD was 0.445, 0.220, 0.151 and 0.143, respectively. The spatial autocorrelation of the incidence of PWD has been decreasing annually, showing a trend with multi-point bursts. The number of affected counties has continued to increase in the central and western parts of the Yangtze River basin, and the mean centre of the affected areas has continued to move to the southwest. The risk detector shows that areas with high wind speed and many sunshine hours are the potential high-risk areas for PWD. The factor detector shows that the normalized difference vegetation index (NDVI), average wind speed and sunshine hours have the strongest effect on the incidence of PWD, with explanatory power of 20.5%, 20.3% and 10.4%, respectively. The interaction between average wind speed and NDVI and the interaction between average relative humidity and sunshine hours show a significant nonlinear enhancement effect, with their explanatory power reaching 64.7% and 60.8%, respectively. Analysis of the spatiotemporal data on PWD in the Yangtze River basin revealed a westward transmission pattern of PWD in the study area, and the interaction of environmental factors could increase the risk of this disease. © 2021