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Biological Invasions

, Volume 20, Issue 9, pp 2599–2622 | Cite as

Estimating the potential geographical range of Sirex noctilio: comparison with an existing model and relationship with field severity

  • Kylie B. Ireland
  • Lindsay Bulman
  • Andrew J. Hoskins
  • Elizabeth A. Pinkard
  • Caroline Mohammed
  • Darren J. Kriticos
Original Paper

Abstract

The Sirex woodwasp, Sirex noctilio, is a significant pest of exotic stands of Pinus species in the southern hemisphere, and an emerging threat in north-eastern America. The potential global distribution of S. noctilio was assessed using the process-oriented niche modelling software CLIMEX. Model parameters were inferred from S. noctilio’s known native distribution in Eurasia and northern Africa, its exotic range in Brazil, New Zealand and South Africa, and from ecophysiological laboratory observations of both S. noctilio and its symbiotic wood-decay fungus, Amylostereum areolatum. Model predictions were validated using independent distribution data from Australia, New Zealand, South Africa and the Americas. Damage significance and spatial distribution data of S. noctilio infestations in New Zealand were compared with growth and suitability outputs of the model, to explore if the impact of S. noctilio could be related to climate. However, no correlation between modelled climate suitability and field infestation severity were found. The resulting model indicated that S. noctilio is currently occupying a fraction of its potential climatic niche in the regions it has invaded. Taking into account areas where suitable hosts occur, results suggest that S. noctilio could further extend its range into additional plantations in southern Queensland in Australia and central Brazil, and into native and exotic stands of Pinus throughout north-east America. Stands of Pinus that are isolated at present from current S. noctilio infestations, such as those in California, Central America and Western Australia, may also be at risk if control measures are ineffective in preventing its spread. Differences in parameter selection and risk projections of our model and a previously published CLIMEX model of S. noctilio are discussed.

Keywords

Climate European wood wasp Forest pest Invasive species 

Notes

Acknowledgements

The authors would like to thank Rodrigo Ahumada, Richard Bashford, Angus Carnegie, Rob Favrin, Ulf Gärdenfors, Ilaria Germishuizen, Edson Iede, Natalia Kirchenko, Vicky Klasmer, Frank Koch, Victoria Lantschner, Matthew Nagel, Juho Paukkunen, Charlma Phillips, Trond Rafoss, David Smith, Geoff Tribe, Tim Wardlaw, Michael Watt and A. Woods for assistance with obtaining point location data for S. noctilio and host distribution data. Muchas gracias to Victoria Lantschner for sharing shape files of her project work on S. noctilio actual and projected distribution and Pinus host distribution. Thanks also to Jody Bruce for assistance with ArcGIS. The authors would like to acknowledge the support of the Australian Government, Department of Agriculture and Water Resources (Department of Agriculture, Fisheries and Forestry at the time; Project No. M18799). We would also like to acknowledge the efforts of Chris Ware and two anonymous reviewers and thank them for their valuable feedback.

Supplementary material

10530_2018_1721_MOESM1_ESM.xlsx (66 kb)
Figure S1. Spatial distribution of a pest (e.g. Sirex noctilio) at the forest stand level, as attributed within the Scion and New Zealand Forest Owners Association Forest Health Database (XLSX 66 kb)
10530_2018_1721_MOESM2_ESM.tif (332 kb)
Figure S2. Annual Growth Index (GI; climatic suitability without stress) for Sirex noctilio as modelled using CLIMEX with the CliMond dataset of historical climate normals centred on 1975. Climatic conditions are classified as being unfavourable for growth when GI = 0, marginally favourable when GI = 1–10, moderately favourable when GI = 11–20 and highly favourable when GI > 20. The GI does not factor in climatic stress and therefore does not represent the potential distribution of S. noctilio, only growth during non-stressful periods of the year (TIFF 332 kb)
10530_2018_1721_MOESM3_ESM.tif (298 kb)
Figure S3. Heat Stress (HS) for Sirex noctilio as modelled using CLIMEX with the CliMond dataset of historical climate normals centred on 1975. Where HS = 0, heat does not limit the distribution of S. noctilio and where HS > 0 heat stress is represented by a factor of 1000, with increasing limitation as HS increases (TIFF 299 kb)
10530_2018_1721_MOESM4_ESM.tif (288 kb)
Figure S4. Dry Stress (DS) for Sirex noctilio as modelled using CLIMEX with the CliMond dataset of historical climate normals centred on 1975. Where DS = 0, soil dryness does not limit the distribution of S. noctilio and where DS > 0 dry stress is represented by a factor of 1000, with increasing limitation as DS increases (TIFF 288 kb)
10530_2018_1721_MOESM5_ESM.tif (275 kb)
Figure S5. Hot-Wet Stress (HWS) for Sirex noctilio as modelled using CLIMEX with the CliMond dataset of historical climate normals centred on 1975. Where DS = 0, soil dryness does not limit the distribution of S. noctilio and where DS > 0 dry stress is represented by a factor of 1000, with increasing limitation as DS increases (TIFF 275 kb)
10530_2018_1721_MOESM6_ESM.tif (244 kb)
Figure S6. Cold Stress (CS) for Sirex noctilio as modelled using CLIMEX with the CliMond dataset of historical climate normals centred on 1975. Where CS = 0, cold does not limit the distribution of S. noctilio and where CS > 0 cold stress is represented by a factor of 1000, with increasing limitation as CS increases (TIFF 244 kb)
10530_2018_1721_MOESM7_ESM.tif (703 kb)
Figure S7. Projected suitability for Sirex noctilio in the contiguous USA as modelled by Ireland et al. (this paper) using CLIMEX for climatic suitability (A) and by the Forest Health and Technology Enterprise Team (FHTET) (FHTET 2006) of the USDA Forest Service (B–D). The FHTET models are for susceptibility (B), which is a function of introduction potential (C) and establishment potential on suitable hosts (D) (FHTET 2006). Increased darkness in shading identifies areas at greater risk of S. noctilio establishment and persistence. Darker areas in all maps indicate greater climatic suitability (A) or risk (B–D) (TIFF 703 kb)

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Kylie B. Ireland
    • 1
    • 2
  • Lindsay Bulman
    • 3
  • Andrew J. Hoskins
    • 4
  • Elizabeth A. Pinkard
    • 5
  • Caroline Mohammed
    • 1
  • Darren J. Kriticos
    • 2
  1. 1.Tasmanian Institute for Agricultural ResearchUniversity of TasmaniaHobartAustralia
  2. 2.Health and BiosecurityCommonwealth Scientific and Industrial Research Organisation (CSIRO)CanberraAustralia
  3. 3.Scion (New Zealand Forest Research Institute)RotoruaNew Zealand
  4. 4.Land and WaterCSIROCanberraAustralia
  5. 5.Land and WaterCSIROHobartAustralia

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