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Shade-tolerant non-native invasive plant species may make deep incursions into natural plant communities, but detecting such species is challenging because occurrences are often sparse. We developed Bayesian models of the distribution of Microstegium vimineum in natural plant communities of the southern Blue Ridge Mountains, USA to address three objectives: (1) to assess local and landscape factors that influence the probability of presence of M. vimineum; (2) to quantify the spatial covariance error structure in occurrence that was not accounted for by the environmental variables; and (3) to synthesize our results with previous findings to make inference on the spatial attributes of the invasion process. Natural plant communities surrounded by areas with high human activity and low forest cover were at highest risk of M. vimineum invasion. The probability of M. vimineum presence also increased with increasing native species richness and soil pH, and decreasing basal area of ericaceous shrubs. After accounting for environmental covariates, evaluation of the spatial covariance error structure revealed that M. vimineum is invading the landscape by a hierarchical process. Infrequent long-distance dispersal events result in new nascent sub-populations that then spread via intermediate- and short-distance dispersal, resulting in 3-km spatial aggregation pattern of sub-populations. Containment or minimisation of its impact on native plant communities will be contingent on understanding how M. vimineum can be prevented from colonizing new suitable habitats. The hierarchical invasion process proposed here provides a framework to organise and focus research and management efforts.

Predicting Microstegium vimineum invasion in natural plant communities of the southern Blue Ridge Mountains, USA