Using fine-scale field data modelling for planning the management of invasions of Oenothera stucchii in coastal dune systems

Invasive alien species risk assessment and adaptive management are often hindered by a lack of information for most species. This work aims at predicting the probability successful establishment invasion Oenothera stucchii Soldano, neophyte invasive belonging to sect. subsect. Oenothera, in xerophilous grasslands grey dunes. Based on fine-scale field data, we modelled O. presence/absence abundance as function environmental factors, human disturbance, attributes recipient community through zero-inflated Poisson model. The success depended combination factors which differed when considering either patterns occurrence (species presence/absence) or those abundance. While human-driven disturbance strongly influenced stucchii, were mostly driven biotic features. Attributes remarkably both presence determined mechanisms drive spatial provided quantitative thresholds identify susceptible areas dune habitats prone invasion, combine (distance from nearest beach access), resident (resident vegetation cover structure), (foredune ridge height). These results provide useful insights be used plan cost-effective measures prevent spread sandy coastal systems. Our model may also applied closely related congener included sharing similar biological ecological traits.