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The pragmatic management of invasive alien species should integrate two essential items: 1) management interventions and 2) a spatially explicit management plan. Predicting the future expansion of target species in a region at the early invasion stage is an important step toward the establishment of a spatially explicit management plan. However, information regarding the distributions of target species is limited, making it challenging to predict range expansions. In the present study, we established a simulation model that could predict the future expansion of the invasive insect Aromia bungii, which is harmful to Prunus trees (including cherry trees [Cerasus × yedoensis]), in Japan. We employed a virtual ecology approach that simulated species dynamics based on a simple model in Saitama Prefecture, which is in the Kanto region of Japan. Since the first record of the species in this region of Japan in 2013, its range has expanded dramatically. Three candidate pathways and combinations of these for the range expansion of A. bungii were tested to identify the major proxies of expansion for this species, followed by the validation of these results using occurrence records for the species through 2019. Both the river density model and combined river and road density models showed good predictive performance. Using these models, we established a predictive map of the future expansion of this species in the wider range of the simulation area. Based on the results, we recommend concentration of management efforts in the mid-northeast region of the Saitama Prefecture. [ABSTRACT FROM AUTHOR]

In this study, we propose a method for estimating the risk of agricultural damage caused by an invasive species when species-specific information is lacking. We defined the 'risk' as the product of the invasion probability and the area of potentially damaged crop for production. As a case study, we estimated the risk imposed by an invasive weed, Sicyos angulatus, based on simple cellular simulations and governmental data on the area of crop that could potentially be damaged in Miyagi Prefecture, Japan. Simulation results revealed that the current distribution range was sufficiently accurate for practical purposes. Using these results and records of crop areas, we present risk maps for S. angulatus in agricultural fields. Managers will be able to use these maps to rapidly establish a management plan with minimal cost. Our approach will be valuable for establishing a management plan before or during the early stages of invasion. [ABSTRACT FROM AUTHOR]