Predicting the climatic risk of myrtle rust during its first year in New Zealand

  • Robert M. Beresford Plant & Food Research
  • Richard Turner NIWA
  • Andrew Tait NIWA
  • Vijay Paul NIWA
  • Gregor Macara NIWA
  • Zhidong D. Yu MPI
  • Lorin Lima MPI
  • Rebecca Martin MPI
Keywords: Guava rust, eucalypt rust, disease detection, incursion response, biosecurity, climatology, numerical weather forecasting, Climex model, MaxEnt model, ensemble model, unified model

Abstract

After the first detection of myrtle rust (Austropuccinia psidii) on mainland New Zealand in May 2017, the Ministry for Primary Industries sought information about how weather conditions would affect regional and seasonal risk of disease establishment to help plan the incursion response. Using internationally published information, a pathogen-process model was developed to predict infection, latent period and sporulation in relation to weather variables (temperature, relative humidity and solar radiation). This Myrtle Rust Process Model (MRPM) was implemented by the National Institute of Water and Atmospheric Research Limited using numerical weather model data to produce weekly maps of potential risk. Predicted risk was greatest in northern North Island and decreased further south, but was still substantial in coastal areas of the north-western South Island during summer and autumn. Risk was low in southern coastal areas of the South Island and the lowest risk occurred in mountainous areas, particularly in the South Island. Retrospective analysis of surveillance data showed that the MRPM accurately predicted geographic risk and it is currently in use for tactical planning of incursion surveillance and organism management.

 

References

Alfenas AC, Demuner NL, Barbosa MM 1989. A ferrugem e as opções de controle. Correio Agrícola 1:18–20.

Alvares CA, Sentelhas PC, Mattos EM, Miranda AC, Moraes WB, Silva PHM Furtado EL, Stape JL 2017. Climatic favourability zones for Eucalyptus rust in Brazil. Forest Pathology 47(1) https://doi.org/10.1111/efp.12301

Beresford RM 1986. Epidemiological studies on the forecasting of barley brown rust (Puccinia hordei) in England. Ph.D. thesis, University of Bristol, January 1986, 161 p.

Beresford RM, Mulholland RI 1987. Mint rust on cultivated peppermint in Canterbury: Disease cycle and control by flaming. New Zealand Journal of Experimental Agriculture 15: 229–233. https://doi.org/10.1080/03015521.1987.10425564

Beresford RM, Royle DJ 1988. Relationships between leaf emergence and latent period for leaf rust (Puccinia hordei) on barley spring barley, and their significance for disease monitoring. Zeitschrift fur Pflanzenkrankheiten und Pflanzenschutz 95: 361–371.

Booth TH, Jovanovic T 2012. Assessing vulnerable areas for Puccinia psidii (eucalyptus rust) in Australia. Australasian Plant Pathology 41: 425–429. https://doi.org/10.1007/s13313-012-0130-x

Carnegie AJ, Glen M, Mohammed C 2010. Rapid screening of commercial forestry species to Uredo rangelii (myrtle rust) and distinguishing U. rangelii from Puccinia psidii (guava rust). Project No: PRC179-0910. August 2010. Report prepared for Forest & Wood Products Australia. www.fwpa.com.au. 22 p.

Davies, T, Cullen, MJP, Malcolm, A, Mawson, MH, Staniforth, A, White, AA, Wood, N, 2005. A new dynamical core for the Met Office's global and regional modelling of the atmosphere, Quarterly Journal of the Royal Meteorological Society 131:1759-1782. https://doi.org/10.1256/qj.04.101

Guy N, Barry M 2017. Response underway following myrtle rust find. https://beehive.govt.nz/release/response-underway-following-myrtle-rust-find. 5 May 2017.

Glen M, Alfenas AC, Zauza EAV, Wingfield MJ, Mohammed C 2007. Puccinia psidii: a threat to the Australian environment and economy–a review. Australasian Plant Pathology 36(1): 1–16.
https://doi.org/10.1071/AP06088

GLOBE Task Team and Hastings, DA, Dunbar, PK, Elphingstone, GM, Bootz, M, Murakami, H, Maruyama, H, Masaharu, H, Holland, P, Payne, J, Bryant, NA, Logan, TL, Muller, J-P, Schreier, G, MacDonald, JS, eds. 1999. The Global Land One-kilometer Base Elevation (GLOBE) Digital Elevation Model, Version 1.0. National Oceanic and Atmospheric Administration, National Geophysical Data Center, Colorado, USA. http://www.ngdc.noaa.gov/mgg/topo/globe.html.

Hanna JW, Neves Graça R, Kim M-S, Ross-Davis AL, Hauff RD, Uchida JY, Kadooka CY, Rayamajhi MB, Arguedas Gamboa M, Lodge DJ, Medel Ortiz R, Lopez Ramírez A, Cannon PG, Alfenas AC, Klopfenstein NB 2012. A bioclimatic approach to predict global regions with suitable climate for Puccinia psidii. In: Zeglen S, Palacios P, comp. Proceedings of the 59th Annual Western International Forest Disease Work Conference, October 2011, Washington USA. Pp. 131–136.

Hernandez Nopsa J, Pfender WF 2014. A latent period duration model for wheat stem rust. Plant Disease 98: 1358–1363. https://doi.org/10.1094/PDIS-11-13-1128-RE

Kim KS, Beresford RM 2008. Use of a spectrum model and satellite cloud data in the simulation of wheat stripe rust (Puccinia striiformis) dispersal across the Tasman Sea in 1980. Agricultural and Forest Meteorology 148: 1374–1382. https://doi.org/10.1016/j.agrformet.2008.04.004

Kriticos DJ, Morin L, Leriche A, Anderson RC, Caley P 2013. Combining a climatic niche model of an invasive fungus with its host species distributions to identify risks to natural assets: Puccinia psidii sensu lato in Australia. PLoS ONE 8: e64479. https://doi.org/10.1371/journal.pone.0064479

Magarey RD, Sutton TB, Thayer CL 2005. A simple generic infection model for foliar fungal plant pathogens. Phytopathology 95: 92-100. https://doi.org/10.1094/PHYTO-95-0092

MPI 2017. Serious fungal plant disease found on Raoul Island trees. 04 April 2017. https://www.mpi.govt.nz/news-and-resources/media-releases/serious-fungal-plant-disease-found-on-raoul-island-trees/.

Narouei-Khandan HA 2014. Ensemble models to assess the risk of exotic plant pathogens in a changing climate. Ph.D. thesis, Lincoln University, New Zealand. 280 p.

Pegg GS, Brawner JT, Lee DJ 2014. Screening Corymbia populations for resistance to Puccinia psidii. Plant Pathology 63: 425-436. https://doi.org/10.1111/ppa.12097

Plant Biosecurity Cooperative Research Centre (PBCRC) 2018. http://www.pbcrc.com.au/news/2016/pbcrc/myrtle-rust-threat-australian-landscape-and-plant-industries. Accessed 15 May 2018.

Rossi V, Racca P, Pancaldi D, Alberti I 1996. Appearance of Puccinia recondita f. sp. tritici on winter wheat: a simulation model. EPPO Bulletin 26: 555–566. https://doi.org/10.1111/j.1365-2338.1996.tb01498.x

Ruiz RAR, Alfenas AC, Ferreira FA, do Vale FXR 1989. Influencia da temperature, do tempo molhamento foliar, fotoperiodo e da intensidade de luz sobre a infeccao de Puccinia psidii em eucalipto. Fitopatologia Brasileira 14: 55–64.

Sentelhas PC, Dalla Marta A, Orlandini S, Santos EA, Gillespie TJ, Gleason ML 2008. Suitability of relative humidity as an estimator of leaf wetness duration. Agricultural and Forest Meteorology 148: 392-400. https://doi.org/10.1016/j.agrformet.2007.09.011

Teng PS, Close RC 1978. Effect of temperature and uredium density on urediniospore production, latent period, and infectious period of Puccinia hordei Otth. New Zealand Journal of Agricultural Research 21: 287–296. https://doi.org/10.1080/00288233.1978.10427413

Xavier AA, Costa da Silva A, Mauro da Silva Guimarães L, Matsuoka K, Hodges CS, Alfenas AC 2015. Infection process of Puccinia psidii in Eucalyptus grandis leaves of different ages. Tropical Plant Pathology 40: 318–325. https://doi.org/10.1007/s40858-015-0043-7

Zadoks JC 1971. Systems analysis and the dynamics of epidemics. Phytopathology 61: 600-610.
Published
2018-07-25
How to Cite
Beresford, R., Turner, R., Tait, A., Paul, V., Macara, G., Yu, Z., Lima, L., & Martin, R. (2018). Predicting the climatic risk of myrtle rust during its first year in New Zealand. New Zealand Plant Protection, 71, 332-347. https://doi.org/https://doi.org/10.30843/nzpp.2018.71.176
Section
Vol 71 Rust Pathogens 2018

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