Abstract Plant invasions are a growing threat to biodiversity, and effective prevention depends on identifying their underlying drivers. Urban areas are often assumed to be the main sources of non‐native plant introductions and spread, prompting conservation policies that restrict their use in cities to prevent escape into surrounding landscapes. However, the mechanisms driving spread across the urban–rural gradient remain poorly understood. Historical analysis of urban ornamentals that have become widespread invasive species—such as Ailanthus altissima —shows that many invasions attributed to urban escape can originate, at least in part, from rural sources. Plantings for beautification, landscaping, erosion control, timber production and other purposes can substantially increase propagule pressure in rural settings, a key determinant of invasion risk. Spread from such deliberate rural introductions can mimic or reinforce urban‐driven invasions, and may precede them. However, most invasion models estimate propagule pressure indirectly using urban‐based proxies, such as distance from cities. This urban‐centred approach systematically overlooks rural legacy sources, introducing bias into model outputs, inflating perceived spread rates and overstating the role of cities as invasion foci. The ‘Diffuse Legacy Source Model’, established here for deliberately planted species, integrates spatially distributed and historically layered planting data—both urban and rural—into invasion analyses, enabling more accurate attribution of introduction pathways and improving predictive performance. Combining ecological data with cultural‐historical research and other social science perspectives provides a comprehensive basis for evaluating the legacies of past introductions. Synthesis and applications . Addressing both urban and rural planting legacies in invasion models advances understanding of spread dynamics across landscapes. A transdisciplinary approach that links ecological methods with cultural‐historical perspectives is essential for accessing, interpreting and incorporating historical data into predictive tools. Broadening the analytical lens beyond urban sources will enable more spatially informed and historically grounded strategies, improving resource allocation for prevention, targeted management and sustainable use of non‐native plants in both urban and rural contexts.
Ingo Kowarik (Thu,) studied this question.