Abstract：
BACKGROUND: The spread of Vespa velutina Lepeletier, 1836 (Asian hornet) in South Korea poses a threat to biodiversity and agriculture. Traditional species interaction models often fail to capture the complexity of invasive species dynamics. This study used association rule learning (ARL) and clustering analyses to explore the interactions of V. velutina with native Vespidae species in South Korea, with the aim of uncovering patterns of coexistence and competition.
RESULTS: Over 4 years (2020-2023), 304 traps were strategically placed across South Korea to collect data on Vespidae species. Our findings showed that Vespula flaviceps, Vespa crabro, and Vespula koreensis were the most frequently encountered species. V. velutina was also widespread, suggesting its successful integration into local ecosystems. The ARL analysis, using the \'apriori\' algorithm, identified significant co-occurrence patterns and potential interactions. The rules generated indicated both competitive and coexistent relationships with varying levels of association strength across different regions. Clustering analyses, including hierarchical and k-means clustering, grouped species based on their occurrence similarities. The distinct clusters formed in the analysis highlighted the unique ecological roles and interactions of V. velutina and other Vespidae species in South Korean ecosystems.
CONCLUSIONS: This study confirms the successful establishment of V. velutina in diverse South Korean ecosystems and highlights its complex interactions with native species. These findings support the need for nuanced management strategies that consider the intricate ecological relationships of V. velutina. This approach is crucial for the effective management of invasive species and ecosystem conservation. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
RESULTS: Over 4 years (2020-2023), 304 traps were strategically placed across South Korea to collect data on Vespidae species. Our findings showed that Vespula flaviceps, Vespa crabro, and Vespula koreensis were the most frequently encountered species. V. velutina was also widespread, suggesting its successful integration into local ecosystems. The ARL analysis, using the \'apriori\' algorithm, identified significant co-occurrence patterns and potential interactions. The rules generated indicated both competitive and coexistent relationships with varying levels of association strength across different regions. Clustering analyses, including hierarchical and k-means clustering, grouped species based on their occurrence similarities. The distinct clusters formed in the analysis highlighted the unique ecological roles and interactions of V. velutina and other Vespidae species in South Korean ecosystems.
CONCLUSIONS: This study confirms the successful establishment of V. velutina in diverse South Korean ecosystems and highlights its complex interactions with native species. These findings support the need for nuanced management strategies that consider the intricate ecological relationships of V. velutina. This approach is crucial for the effective management of invasive species and ecosystem conservation. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
摘要：
背景：VespavelutinaLepeletier的传播，1836年（亚洲大黄蜂）在韩国对生物多样性和农业构成威胁。传统的物种相互作用模型通常无法捕获入侵物种动力学的复杂性。这项研究使用关联规则学习（ARL）和聚类分析来探索V.velutina与韩国本土Vespidae物种的相互作用，目的是揭示共存和竞争的模式。
结果：超过4年（2020-2023年），在韩国各地战略性地放置了304个陷阱，以收集有关Vespidae物种的数据。我们的研究结果表明，维斯普拉人，Vespacrabro,和Koreensis是最常遇到的物种。V.velutina也很普遍，表明它成功地融入了当地的生态系统。ARL分析，使用“apriori”算法，确定了重要的共现模式和潜在的相互作用。生成的规则表明竞争关系和共存关系，不同地区的关联强度水平各不相同。聚类分析，包括分层聚类和k均值聚类，根据它们的发生相似性对物种进行分组。分析中形成的不同簇突出了V.velutina和其他Vespidae物种在韩国生态系统中的独特生态作用和相互作用。
结论：这项研究证实了V.velutina在不同的韩国生态系统中的成功建立，并强调了其与本地物种的复杂相互作用。这些发现支持需要考虑V.velutina复杂的生态关系的细致入微的管理策略。这种方法对于有效管理入侵物种和生态系统保护至关重要。©2024作者（S）。害虫管理科学由JohnWiley&SonsLtd代表化学工业学会出版。
结果：超过4年（2020-2023年），在韩国各地战略性地放置了304个陷阱，以收集有关Vespidae物种的数据。我们的研究结果表明，维斯普拉人，Vespacrabro,和Koreensis是最常遇到的物种。V.velutina也很普遍，表明它成功地融入了当地的生态系统。ARL分析，使用“apriori”算法，确定了重要的共现模式和潜在的相互作用。生成的规则表明竞争关系和共存关系，不同地区的关联强度水平各不相同。聚类分析，包括分层聚类和k均值聚类，根据它们的发生相似性对物种进行分组。分析中形成的不同簇突出了V.velutina和其他Vespidae物种在韩国生态系统中的独特生态作用和相互作用。
结论：这项研究证实了V.velutina在不同的韩国生态系统中的成功建立，并强调了其与本地物种的复杂相互作用。这些发现支持需要考虑V.velutina复杂的生态关系的细致入微的管理策略。这种方法对于有效管理入侵物种和生态系统保护至关重要。©2024作者（S）。害虫管理科学由JohnWiley&SonsLtd代表化学工业学会出版。
