Application of hierarchical clustering to identify high risk pests to Sitka spruce: Ireland as a case study

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.

Automated summary

This paper uses a hierarchical clustering approach to analyze distribution data for pests of Sitka spruce in order to identify high-risk species for Ireland and potential source regions of these pests. The analysis suggests that the highest risk pests for Sitka spruce plantations in Ireland are likely to originate from Europe. The study highlights the potential utility of hierarchical clustering in assessing the risk posed by alien species to new regions.