Abstract

Owing to their potentially wide-ranging adverse effects, invasive species are a growing global problem. The common ragweed (Ambrosia artemisiifolia var. elatior (L.) Desc) is one of the most important invasive plants, necessitating management because of its tendency to “spread.” Various studies and management strategies are being conducted based on the concept of “density” because of the increasing importance of the spatial perspective in this application. Although eradicating from the outliers (low-density regions) has a high efficiency, there is a lack of validation methodology for deriving both spatial and statistical results. We formed a general validation methodology by assessing various removal scenarios based on two removal strategies, namely Outside-in and Inside-out. These approaches exhibited several removal rates, and take into account the spatial perspective by considering species density. The Outside-in strategy entails the removal of species, which commences from the low-density regions, whereas the Inside-out removal initiates from the high-density regions. To classify the spatial regions for priority removal using each strategy, we defined the density level and then processed the removal of the occurrence points for each strategy to derive generalized results. We used the species distribution model MaxEnt to determine the predicted distribution of the target species for each removal strategy applied; subsequently, the final randomly generalized occurrence point results were used as model input data. Assessment analyses were conducted based on the final probability distribution and appearance level for each scenario, which included a newly proposed index was termed the “removal effect index.” Results indicated that the efficacy of the Outside-in removal strategy exceeded that of the Inside-out strategy for all assessment analyses, with the removal effect index showing a difference of about 2–5 times between strategies in each removal rate. In addition, through numerical analysis of the changed area of each scenario, the Outside-in strategy showed a successful removal effect in the “removal management priority spatial range,” whereas the Inside-out strategy showed limitations. We confirmed the efficacy of the Outside-in strategy as an optimal removal approach that takes into account spatial information of the priority spatial range for eradication in terms of the removal effect.

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