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Utility of the CLIMEX ‘match climates regional’ algorithm for pest risk analysis: an evaluation with non-native ants in New Zealand

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Abstract

Pest risk analysts frequently ask if the climate of a pest risk analysis area could be suitable for the establishment of an organism of concern. Species distribution models can help to answer this question, but constructing them is technically complex, time consuming, and uninformative for additional non-modelled species. A quicker more broadly applicable approach involves using environmental distance metrics, including climate matching algorithms such as the ‘match climates regional’ function of CLIMEX (CLIMEX-MCR), to generate indices of climatic similarity between different locations without reference to particular species. Several studies have shown that various environmental distance metrics can provide biologically meaningful results. However, the veracity of the CLIMEX-MCR algorithm remains unevaluated, despite its application in numerous published studies. We used CLIMEX-MCR and high resolution New Zealand climate data to measure climatic similarities between New Zealand and the rest of the world. We then tested the veracity of the climatic match estimates by evaluating if their predictions regarding the suitability of New Zealand’s climate for 43 non-native ant species corresponded with empirical observations of those species in New Zealand. Non-native ants that are, or were once, established outdoors in New Zealand had overseas distributions that were climatically well matched with New Zealand. In contrast, species that either are established only indoors in New Zealand, or were observed to temporarily nest outdoors then die in New Zealand, had overseas distributions that were poorly matched. Species that are frequently intercepted at New Zealand’s border, but are not established there, generally also had overseas distributions with low climatic similarities to New Zealand. We also measured climatic similarities between New Zealand’s 13 national parks and the rest of the world. The overseas distributions of the non-native ants showed poor climatic matches with New Zealand’s national parks, which was consistent with the absence of persistent outdoor non-native ant populations in those parks. Our results support the utility of CLIMEX-MCR algorithm for pest risk analysis.

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Acknowledgements

We thank Dr Darren Ward (Landcare Research) for providing unpublished information about the status of non-native ant species in New Zealand and reviewing the manuscript; Dr Chikako van Koten (AgResearch) for statistical advice and reviewing the manuscript; Drs Shona Lamoureaux (AgResearch), Senait Senay (University of Minnesota), Darren Kriticos (CSIRO) and two anonymous referees for reviewing the manuscript; and Dr Federico Tomasetto (AgResearch) for assistance with data processing. The research was supported by AgResearch Ltd via its contribution to the Better Border Biosecurity (B3) research collaboration, www.b3nz.org.

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Authors and Affiliations

  1. AgResearch Ltd, Lincoln, New Zealand

    Craig B. Phillips

  2. Better Border Biosecurity http://www.b3nz.org

    Craig B. Phillips, John M. Kean & Jocelyn A. Berry

  3. AgResearch Ltd, Ruakura, New Zealand

    John M. Kean

  4. Canterbury Museum, Christchurch, New Zealand

    Cor J. Vink

  5. Ministry for Primary Industries, Wellington, New Zealand

    Jocelyn A. Berry

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  1. Craig B. Phillips
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Phillips, C.B., Kean, J.M., Vink, C.J. et al. Utility of the CLIMEX ‘match climates regional’ algorithm for pest risk analysis: an evaluation with non-native ants in New Zealand. Biol Invasions 20, 777–791 (2018). https://doi.org/10.1007/s10530-017-1574-2

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