Assessing Spatiotemporal Patterns and Wind-Driven Dispersal of E.prolifera in the South Yellow Sea by Multi-Index Decision Fusion in South Yellow Sea, China

Assessing Spatiotemporal Patterns and Wind-Driven Dispersal of E.prolifera in the South Yellow Sea by Multi-Index Decision Fusion in South Yellow Sea, China | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Assessing Spatiotemporal Patterns and Wind-Driven Dispersal of E.prolifera in the South Yellow Sea by Multi-Index Decision Fusion in South Yellow Sea, China Kai Luo, Ping Zuo, Qitong Ma, Yujun Zheng, Xiruo Li, Hu Chang, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4661029/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Since 2007, the coastal areas of Shandong have frequently experienced green tides caused by Enteromorpha prolifera ( E.prolifera ). Our study utilized long-term MODIS remote sensing data and multi-index decision fusion technology to analyze the distribution of E.prolifera in the South Yellow Sea from 2008 to 2022. This approach enabled us to detail the spatiotemporal distribution, including data on centroid movement paths and coverage areas. Further application of Moran's Index for spatial autocorrelation analysis revealed four distinct drift patterns of E.prolifera , stretching from the coast of Jiangsu Province to the Shandong Peninsula. These patterns are significantly influenced by the wind speed and direction in the region, with the maximum centroid drift speed dependent on the wind's magnitude. Before 2018, the coverage area and distribution range of E.prolifera showed an exponential expansion trend. This research provides essential spatiotemporal data for understanding the drift dynamics and ecological impact of E.prolifera in the region. Earth and environmental sciences/Ocean sciences/Marine biology Earth and environmental sciences/Natural hazards E.prolifera Spatiotemporal characteristics Centroid drift patterns Wind speed and direction Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4661029","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":332312402,"identity":"c9e5bc4d-5e24-43fd-8999-efb7920c12fe","order_by":0,"name":"Kai Luo","email":"","orcid":"","institution":"Nanjing University","correspondingAuthor":false,"prefix":"","firstName":"Kai","middleName":"","lastName":"Luo","suffix":""},{"id":332312403,"identity":"f5386046-d27d-4021-b329-0d9c817bb187","order_by":1,"name":"Ping 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