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


    Duffy, Catriona and Tuffen, Melanie G and Fealy, Rowan and Griffin, Christine T (2020) Application of hierarchical clustering to identify high risk pests to Sitka spruce: Ireland as a case study. Forestry: An International Journal of Forest Research, 94 (1). pp. 86-101. ISSN 0015-752X

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    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.

    Item Type: Article
    Additional Information: Cite as: Catriona Duffy, Melanie G Tuffen, Rowan Fealy, Christine T Griffin, Application of hierarchical clustering to identify high risk pests to Sitka spruce: Ireland as a case study, Forestry: An International Journal of Forest Research, Volume 94, Issue 1, January 2021, Pages 86–101, https://doi.org/10.1093/forestry/cpaa014
    Keywords: Invertebrate forest pests; pathogens; Irish forestry; Sitka spruce;
    Academic Unit: Faculty of Science and Engineering > Research Institutes > National Centre for Geocomputation, NCG
    Faculty of Social Sciences > Geography
    Faculty of Social Sciences > Research Institutes > Irish Climate Analysis and Research Units, ICARUS
    Faculty of Social Sciences > Research Institutes > Maynooth University Social Sciences Institute, MUSSI
    Item ID: 15804
    Identification Number: https://doi.org/10.1093/forestry/cpaa014
    Depositing User: Rowan Fealy
    Date Deposited: 12 Apr 2022 09:05
    Journal or Publication Title: Forestry: An International Journal of Forest Research
    Publisher: Advance Access Publication
    Refereed: Yes
    URI:

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