A dataset of the national distribution of Pine Wilt Disease (PWD) epidemic areas in China (2016–2024)
Year: 2025
Type: article
Abstract: Since its first introduction into China in 1982, the pine wood nematode (Bursaphelenchus xylophilus) has spread rapidly, posing an unprecedented threat to more than 70 species of conifers (including pines), and seriously threatening the security of the forest resources and the balance of its ecological environment in China. Against the background of climate change and intensified human activities, the spread of the pine wilt disease (PWD) caused by this nematode has further accelerated, making prevention and control situation increasingly challenging. This dataset focuses on the distribution and spread of this globally devastating forest disease agent, the pine wood nematode, in China. The data came from the annual announcements of the PWD epidemic areas and their cancellation announcements released by the National Forestry and Grassland Administration. Using ArcGIS software, we edited and processed the attribute values of county-level administrative divisions based on the national 1:100,000-scale basic geographic information data. The resulting outputs are annual county-level datasets of the PWD epidemic area distributions, accompanied by thematic maps. The data production process covers the entire process, including data collection from sources, data sorting and merging, compliance with reference specifications and standards, thematic mapping, output, review and verification of the results, ensuring both accuracy and professional cartographic quality. The dataset provides detailed geographic distribution that comprehensively reflects the spatial and temporal dynamics of PWD spread and its severity across different regions of China from 2016 to 2024. The dataset helps local authorities to identify epidemic risk points in time and deliver early warning information for prevention and control efforts, assess impacts of the epidemic on natural landscapes, ecological environments, and socio-economic development, and support the formulation of targeted prevention and control measures.
Source: China Scientific Data
Language: English
Subfield: Plant Science
Domain: Life Sciences
SDG: Life on land
Open Access status: diamond
OpenAlex ID: W4414584903