Abstract

Invertebrate forest pests and pathogens can cause considerable economic losses and modern patterns of trade have facilitated the international movement of pest species on an unprecedented level. This upsurge in trade has increased the pathways available to high risk species, facilitating entry and potential establishment in nations where they were previously absent. To support policy and pest prioritization, pest risk analyses are conducted to decide ‘if’ and ‘how’ pests should be regulated in order to prevent entry or establishment; however, they cannot be carried out for every potential pest. This paper utilizes a hierarchical clustering (HC) approach to analyse distribution data for pests of Sitka spruce (Picea sitchensis (Bong.) Carr.) in order to identify species of high risk to Ireland, as well as potential source regions of these pests. The presence and absence of almost a 1000 pests across 386 regions globally are clustered based on their similarity of pest assemblages, to provide an objective examination of the highest risk pests to Irish forestry. Regional clusters were produced for each taxon analysed including the Coleoptera, Diptera, Hemiptera, Hymenoptera, Nematoda, Lepidoptera and the Fungi. The results produced by the HC analysis were interpreted with regard to biological realism and climate. Biologically meaningful clusters were produced for each of the groups, except for the Diptera and Nematoda, and each of the species analysed were ranked within their group by a quantitative risk index specific to the island of Ireland. The impact of uncertainty in the distribution data is also examined, in order to assess its influence over the final groupings produced. The outputs from this analysis suggest that the highest risk pests for Ireland’s Sitka spruce plantations will originate from within Europe. Ultimately, Ireland could benefit from seeking regulation for some of the higher ranking pests identified in this analysis. This analysis provides the first of its type for Sitka spruce, as well as its application in Ireland. It also serves to highlight the potential utility of HC as a ‘first approach’ to assessing the risk posed by alien species to hitherto novel regions.

中文翻译：

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应用层次聚类识别锡特卡云杉的高危害虫：以爱尔兰为例

摘要

无脊椎动物的森林有害生物和病原体可能造成巨大的经济损失，现代贸易方式促进了有害生物物种国际转移的空前水平。贸易的激增为高风险物种增加了可利用的途径，便利了它们先前不在的国家的进入和潜在的建立。为了支持政策和有害生物优先排序，进行了有害生物风险分析，以确定“是否”和“如何”对有害生物进行管理，以防止其进入或定殖；但是，不能对每种潜在的有害生物都进行清除。本文利用层次聚类（HC）方法对云杉（Picea sitchensis）害虫的分布数据进行分析。（Bong。）Carr。），以便确定对爱尔兰具有高风险的物种以及这些有害生物的潜在来源地区。根据有害生物组合的相似性，将全球386个区域中近1000种有害生物的存在和不存在进行了聚类，以客观地检查爱尔兰林业中最高风险的有害生物。为每个分析的分类单元产生了区域簇，包括鞘翅目，双翅目，半翅目，膜翅目，线虫，鳞翅目和真菌。HC分析产生的结果在生物学真实性和气候方面得到了解释。除双翅目和线虫外，每个组都产生了生物学上有意义的簇，并且通过特定于爱尔兰岛的定量风险指数对所分析的每个物种进行了分组。还评估了分布数据中不确定性的影响，以评估其对最终产生的分组的影响。该分析的结果表明，爱尔兰的锡特卡云杉人工林最高风险的有害生物将来自欧洲内部。最终，爱尔兰可以从对本分析中确定的一些较高等级的有害生物寻求监管中受益。该分析为Sitka云杉提供了同类产品中的第一种，并在爱尔兰得到了应用。它还可以突出显示HC作为“第一种方法”的潜在用途，以评估外来物种对迄今新颖地区构成的风险。该分析的结果表明，爱尔兰锡特卡云杉人工林的最高风险有害生物将来自欧洲内部。最终，爱尔兰可以从对本分析中确定的一些较高等级的有害生物寻求监管中受益。该分析为Sitka云杉提供了同类产品中的第一种，并在爱尔兰得到了应用。它还可以突出显示HC作为“第一种方法”的潜在用途，以评估外来物种对迄今新颖地区构成的风险。该分析的结果表明，爱尔兰的锡特卡云杉人工林最高风险的有害生物将来自欧洲内部。最终，爱尔兰可以从对本分析中确定的一些较高等级的有害生物寻求监管中受益。该分析为Sitka云杉提供了同类产品中的第一种，并在爱尔兰得到了应用。它还可以突出显示HC作为“第一种方法”的潜在用途，以评估外来物种对迄今新颖地区构成的风险。