Predicting the spatio‐temporal dynamics of biological invasions: Have rapid responses in Europe limited the spread of the yellow‐legged hornet (<i>Vespa velutina nigrithorax</i>)?

Abstract Invasive alien species can have severe impacts on biodiversity, economies, and well‐being and their long‐term management can involve massive costs. There is an increasing policy imperative to determine whether the management of biological invasions is effective, particularly at biological invasion fronts, but this can often be difficult to determine without extensive data collection. Furthermore, risk assessment frameworks are often used to guide decision‐making and management, but these can be hampered by a lack of information about the extent and dynamics of a biological invasion following an introduction within a new region. Incorporating information on the dynamics of biological invasions into these frameworks could provide useful information for decision‐makers including a baseline for evaluating ongoing management approaches. Here, we outline a generalisable mechanistic species distribution modelling framework that is informed by patterns of spread observed in other invaded regions and can provide a relatively rapid assessment of the likely spatial and temporal dynamics of a biological invasion in the absence of interventions. To demonstrate this approach, we consider the effectiveness of rapid eradications carried out in four European countries to prevent the spread of the yellow‐legged hornet ( Vespa velutina nigrithorax ) following the implementation of Regulation (EU) 1143/2014 on invasive alien species. Synthesis and applications . By predicting the extent of a biological invasion in the absence of timely interventions and comparing this to the current distribution of the yellow‐legged hornet, we found that management measures implemented in these countries appear to have been effective in limiting the spread of the species in Europe. Additionally, the model framework may be useful to inform the identification of high‐risk areas for surveillance measures to be prioritised in view of rapid detection and early eradication activities.