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.

中文翻译：

---

从空间角度验证入侵物种的管理策略：大韩民国的普通豚草

摘要 由于其潜在的广泛不利影响，入侵物种是一个日益严重的全球问题。普通豚草 (Ambrosia artemisiifolia var. elatior (L.) Desc) 是最重要的入侵植物之一，由于其易于“传播”而需要管理。由于空间视角在此应用中的重要性日益增加，因此正在根据“密度”的概念进行各种研究和管理策略。尽管消除异常值（低密度区域）的效率很高，但缺乏用于推导空间和统计结果的验证方法。我们通过基于两种移除策略（即由外向内和由内向外）评估各种移除场景，形成了通用验证方法。这些方法表现出几种去除率，并通过考虑物种密度来考虑空间视角。由外而内的策略需要从低密度区域开始去除物种，而由内而外的去除则是从高密度区域开始。为了使用每种策略对优先移除的空间区域进行分类，我们定义了密度级别，然后处理每种策略的发生点的移除以得出广义结果。我们使用物种分布模型 MaxEnt 来确定应用的每个去除策略的目标物种的预测分布；随后，将最终随机泛化的发生点结果作为模型输入数据。根据每个场景的最终概率分布和出现水平进行评估分析，其中包括一个新提出的指数，称为“去除效果指数”。结果表明，在所有评估分析中，Outside-in 去除策略的效果超过了 Inside-out 策略的效果，去除效果指数显示每种去除率策略之间的差异约为 2-5 倍。此外，通过对每个场景的变化区域进行数值分析，Outside-in策略在“去除管理优先空间范围”中表现出成功的去除效果，而Inside-out策略则表现出局限性。我们确认了由外而内策略作为一种最佳去除方法的有效性，该方法考虑了根除效果方面的优先空间范围的空间信息。结果表明，在所有评估分析中，Outside-in 去除策略的效果超过了 Inside-out 策略的效果，去除效果指数显示，每种去除率的策略之间的差异约为 2-5 倍。此外，通过对每个场景的变化区域进行数值分析，Outside-in策略在“去除管理优先空间范围”中表现出成功的去除效果，而Inside-out策略则表现出局限性。我们确认了由外而内策略作为一种最佳去除方法的有效性，该方法考虑了根除效果方面的优先空间范围的空间信息。结果表明，在所有评估分析中，Outside-in 去除策略的效果超过了 Inside-out 策略的效果，去除效果指数显示，每种去除率的策略之间的差异约为 2-5 倍。此外，通过对每个场景的变化区域进行数值分析，Outside-in策略在“去除管理优先空间范围”中表现出成功的去除效果，而Inside-out策略则表现出局限性。我们确认了由外而内策略作为一种最佳去除方法的有效性，该方法考虑了根除效果方面的优先空间范围的空间信息。去除效果指数显示每种去除率策略之间的差异约为2-5倍。此外，通过对每个场景的变化区域进行数值分析，Outside-in策略在“去除管理优先空间范围”中表现出成功的去除效果，而Inside-out策略则表现出局限性。我们确认了由外而内策略作为一种最佳去除方法的有效性，该方法考虑了根除效果方面的优先空间范围的空间信息。去除效果指数显示每种去除率策略之间的差异约为2-5倍。此外，通过对每个场景的变化区域进行数值分析，Outside-in策略在“去除管理优先空间范围”中表现出成功的去除效果，而Inside-out策略则表现出局限性。我们确认了由外而内策略作为一种最佳去除方法的有效性，该方法考虑了根除效果方面的优先空间范围的空间信息。