{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,12]],"date-time":"2026-09-12T12:39:58Z","timestamp":1789216798724,"version":"build-2803163510"},"reference-count":44,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T00:00:00Z","timestamp":1774656000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T00:00:00Z","timestamp":1774656000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100002965","name":"Northeast Forestry University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100002965","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["scijournals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Pest Management Science"],"published-print":{"date-parts":[[2026,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>BACKGROUND<\/jats:title>\n                    <jats:p>Pine wilt disease (PWD) poses a severe threat to the stability of China's ecosystems and their carbon sequestration capacity. However, the complex interactions between natural and anthropogenic spread pathways remain poorly quantified. By analyzing epidemic subcompartment records from 2014 to 2023, this study established quantitative thresholds to distinguish natural from anthropogenic spread, simulated the historical anthropogenic spread process, and identified the spatiotemporal drivers underlying both spread patterns.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>The research findings indicate a maximum natural spread distance of 2.725\u2009km per year. Distances beyond this threshold were attributed to anthropogenic spread. Across the decade, anthropogenic spread averaged 36.916\u2009km\u2009year, peaking at 91.959\u2009km in outbreak intensive years. A geodetector analysis revealed that natural spread was primarily influenced by normalized difference vegetation index (NDVI), wind speed, and temperature, whereas anthropogenic spread was influenced by road density. By integrating road hierarchy data, wood processing plant locations and wood transportation logistics, the study simulated the anthropogenic spread pattern and mapped cross\u2010regional long\u2010distance spread corridors.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>CONCLUSION<\/jats:title>\n                    <jats:p>This study provides the distance\u2010based quantitative criterion distinguishing natural and anthropogenic PWD spread, and demonstrates that long\u2010distance dispersal is overwhelmingly driven by human activities. The integrated probability modeling and road network framework offers an operational tool for identifying high\u2010risk pathways and supports targeted surveillance, quarantine design, and regional management strategies for PWD and other human\u2010vectored forest pests. \u00a9 2026 Society of Chemical Industry.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/ps.70755","type":"journal-article","created":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T12:49:07Z","timestamp":1774702147000},"page":"6758-6774","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Quantitative analysis of the spread pattern of pine wilt disease from the Yangtze River Basin in China"],"prefix":"10.1002","volume":"82","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-1966-7898","authenticated-orcid":false,"given":"Haochang","family":"Hu","sequence":"first","affiliation":[{"name":"College of Computer and Control Engineering, 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