Journal of Pest Science

, Volume 91, Issue 2, pp 523–538 | Cite as

Considering biology when inferring range-limiting stress mechanisms for agricultural pests: a case study of the beet armyworm

  • Tania Yonow
  • Darren J. Kriticos
  • Natalia Kirichenko
  • Noboru Ota
Original Paper


Reliable niche models are a cornerstone of pest risk analyses, informing biosecurity policies and the management of biological invasions. Because species can invade and establish in areas with climates that are different from those that are found in their native range, it is important to accurately capture the range-limiting mechanisms in models that project climate suitability. We examined a published niche model for the beet armyworm, Spodoptera exigua, to assess its suitability for bioeconomic analyses of its pest threat, and identified issues with the model that rendered it unreliable for this purpose. Consequently, we refitted the CLIMEX model, paying close attention to the biology underpinning the stress mechanisms. This highlighted the necessity of carefully considering how the different stress mechanisms operate, and to select mechanisms which align with knowledge on the species’ biology. We also identified the important role of irrigation in modifying habitat suitability. The refitted model accords with both distribution data and our understanding of the biology of this species, including its seasonal range dynamics. The new model identifies establishment risks to South America, Africa, the Middle East and Asia, and highlights that under current climate, Europe is only climatically suitable during warm seasons when crops are available. The modelling exercise reinforced the importance of understanding the meaning of a location record (e.g. persistent versus ephemeral populations) and of carefully exploring the role of habitat-modifying factors, such as irrigation, in allowing species to persist in otherwise inclement localities.


Bioclimatic modelling CLIMEX Niche modelling Pest risk Spodoptera exigua 



This work was led by InSTePP (International Science and Technology Practice and Policy), University of Minnesota, and CSIRO (Commonwealth Scientific and Industrial Research Organization, Australia), and was funded by the Bill and Melinda Gates Foundation by way of the HarvestChoice Project. Thanks are due to Philip Pardey and Jason Beddow for supporting the work, and to Matt Hill and Dean Paini for comments on the draft manuscript.


Work on this Project was funded by the Bill and Melinda Gates Foundation. Award No. 2010X446.UMN. Award title: HarvestChoice: Supporting Strategic Investment Choices in Agricultural Technology Development and Adoption.

Compliance with ethical standards

Conflict of interest

All authors declare that they have no conflict of interest.

Research involving human participants and/or animals

This article does not contain any studies with human participants or animals performed by any of the authors.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Supplementary material

10340_2017_938_MOESM1_ESM.pdf (521 kb)
Supplementary material 1 (PDF 521 kb)
10340_2017_938_MOESM2_ESM.pdf (392 kb)
Supplementary material 2 (PDF 391 kb)
10340_2017_938_MOESM3_ESM.pdf (392 kb)
Supplementary material 3 (PDF 391 kb)


  1. Adamczyk J Jr, Williams M, Reed J, Hubbard D, Hardee D (2003) Spatial and temporal occurrence of beet armyworm (Lepidoptera: Noctuidae) moths in Mississippi. Fla Entomol 86:229–232CrossRefGoogle Scholar
  2. Ali A, Gaylor M (1992) Effects of temperature and larval diet on development of the beet armyworm (Lepidoptera: Noctuidae). Environ Entomol 21:780–786CrossRefGoogle Scholar
  3. Atapour M, Moharramipour S (2014) Cold hardiness process of beet armyworm larvae, Spodoptera exigua (Lepidoptera: Noctuidae). J Crop Prot 3:147–158Google Scholar
  4. Baker R, Sansford C, Jarvis C, Cannon R, MacLeod A, Walters K (2000) The role of climatic mapping in predicting the potential geographical distribution of non-indigenous pests under current and future climates. Agr Ecosyst Environ 82:57–71CrossRefGoogle Scholar
  5. Butler GD Jr (1966) Development of the beet armyworm and its parasite Chelonus texanus in relation to temperature. J Econ Entomol 59:1324–1327CrossRefPubMedGoogle Scholar
  6. Carlson E (2010) Spodoptera exigua. Center for Invasive Species and Ecosystem Health. Accessed 16 June 2016
  7. Chamberlin TC (1965) The method of multiple working hypotheses. Science 148:754–759. CrossRefPubMedGoogle Scholar
  8. De Villiers M, Hattingh V, Kriticos D (2013) Combining field phenological observations with distribution data to model the potential distribution of the fruit fly Ceratitis rosa Karsch (Diptera: Tephritidae). Bull Ent Res 103:60–73CrossRefGoogle Scholar
  9. De Villiers M, Hattingh V, Kriticos DJ, Brunel S, Vayssières J-F, Sinzogan A, Billah M, Mohamed S, Mwatawala M, Abdelgader H (2016) The potential distribution of Bactrocera dorsalis: considering phenology and irrigation patterns. Bull Ent Res 106:19–33. CrossRefGoogle Scholar
  10. Eghtedar E (1989) Some biological researches on beet army worm (Spodoptera exigua Hb) in Shiraz region [Iran]. Entomol Phytopathol Appl (Iran) 56:57–63Google Scholar
  11. Elith J, Simpson J, Hirsch M, Burgman M (2013) Taxonomic uncertainty and decision making for biosecurity: spatial models for myrtle/guava rust. Australas Plant Pathol 42:43–51CrossRefGoogle Scholar
  12. El-Refai S, Degheele D (1988) Development time of the beet armyworm, Spodoptera exigua (Hübner) and the tobacco budworm, Heliothis virescens (F.) (Lepidoptera, Noctuidae) in function of temperature. Mededelingen van de Faculteit Landbouwwetenschappen Rijksuniversiteit Gent (Belgium)Google Scholar
  13. Ezumah H, Knight A (1978) Some notes on the mealybug, Phenacoccus manihoti Mat. Ferr. incidence on manioc (Manihot esculenta) in Bas-Zaïre. In: Proceedings of the international workshop on the cassava mealybug, Phenacoccus manihoti Mat. Ferr, pp 26–29Google Scholar
  14. FAO (2006) International standards for phytosanitary measures: 1 to 24. Secretariat of the International Plant Protection Convention, RomeGoogle Scholar
  15. Farahani S, Talebi AA, Fathipour Y (2012) Life table of Spodoptera exigua (Lepidoptera: Noctuidae) on five soybean cultivars. Psyche (Camb Mass), p 7.
  16. Feng H-Q, Wu K-M, Cheng D-F, Guo Y-Y (2003) Radar observations of the autumn migration of the beet armyworm Spodoptera exigua (Lepidoptera: Noctuidae) and other moths in northern China. Bull Ent Res 93:115–124CrossRefGoogle Scholar
  17. French R (1969) Migration of Laphygma exigua Hübner (Lepidoptera: Noctuidae) to the British Isles in relation to large-scale weather systems. J Anim Ecol 38:199–210CrossRefGoogle Scholar
  18. Fye R (1978) Pupation preferences of bollworms, tobacco budworms, and beet armyworms and impact on mortality resulting from cultivation of irrigated cotton. J Econ Entomol 71:570–572CrossRefGoogle Scholar
  19. Fye R, Carranza R (1973) Cotton pests: overwintering of three lepidopterous species in Arizona. J Econ Entomol 66:657–660CrossRefGoogle Scholar
  20. GBIF Global Biodiversity Information Facility. Free and open access to biodiversity data. Accessed 6 Dec 2013
  21. Greenberg S, Sappington T, Legaspi B, Liu T, Setamou M (2001) Feeding and life history of Spodoptera exigua (Lepidoptera: Noctuidae) on different host plants. Ann Entomol Soc Am 94:566–575CrossRefGoogle Scholar
  22. Guerra A, Ouye M (1968) Hatch, larval development, and adult longevity of four lepidopterous species after thermal treatment of eggs. J Econ Entomol 61:14–16CrossRefGoogle Scholar
  23. Hall M, Wall R (1995) Myiasis of humans and domestic animals. Adv Parasit 35:257–334CrossRefGoogle Scholar
  24. Han L, Zhai B, Zhang X (2002) Life table of the laboratory population of Spodoptera exigua (Hübner) at different temperatures. Acta Entomol Sin 46:184–189Google Scholar
  25. Herren HR, Neuenschwander P (1991) Biological control of cassava pests in Africa. Annu Rev Entomol 36:257–283. CrossRefGoogle Scholar
  26. Hogg DB, Gutierrez AP (1980) A model of the flight phenology of the beet armyworm (Lepidoptera: Noctuidae) in central California. Hilgardia 48:1–36CrossRefGoogle Scholar
  27. Hutchinson M, Xu T, Houlder D, Nix H, McMahon J (2009) ANUCLIM 6.0 user’s guide. Australian National University, Fenner School of Environment and Society, CanberraGoogle Scholar
  28. Jiang X-F, Luo L-Z, Li K-B, Zhao T-C, Hu Y (2001) A study on the cold hardiness of the beet armyworm, Spodoptera exigua. Acta Ecol Sin 21:1576–1583Google Scholar
  29. Jiang X, Zhai H, Wang L, Luo L, Sappington TW, Zhang L (2011) Cloning of the heat shock protein 90 and 70 genes from the beet armyworm, Spodoptera exigua, and expression characteristics in relation to thermal stress and development. Cell Stress Chaperon 17:67–80CrossRefGoogle Scholar
  30. Karimi-Malati A, Fathipour Y, Talebi A, Bazoubandi M (2012) Comparative life table parameters of beet armyworm, Spodoptera exigua (Lep.: Noctuidae), on four commercial sugar beet cultivars. J Entomol Soc Iran 32:109–124Google Scholar
  31. Karimi-Malati A, Fathipour Y, Talebi AA (2014a) Development response of Spodoptera exigua to eight constant temperatures: linear and nonlinear modeling. J Asia Pac Entomol 17:349–354. CrossRefGoogle Scholar
  32. Karimi-Malati A, Fathipour Y, Talebi AA, Bazoubandi M (2014b) Life table parameters and survivorship of Spodoptera exigua (Lepidoptera: Noctuidae) at constant temperatures. Environ Entomol 43:795–803CrossRefPubMedGoogle Scholar
  33. Kim Y, Kim N (1997) Cold hardiness in Spodoptera exigua (Lepidoptera: Noctuidae). Environ Entomol 26:1117–1123CrossRefGoogle Scholar
  34. Kriticos DJ (2016) CLIMEX publications up until April 2015. CSIRO, Canberra, p 37Google Scholar
  35. Kriticos DJ, Leriche A (2010) The effects of climate data precision on fitting and projecting species niche models. Ecography 33:115–127. CrossRefGoogle Scholar
  36. Kriticos D, Sutherst R, Brown J, Adkins S, Maywald G (2003a) Climate change and biotic invasions: a case history of a tropical woody vine. Biol Invasions 5:147–165CrossRefGoogle Scholar
  37. Kriticos D, Sutherst R, Brown J, Adkins S, Maywald G (2003b) Climate change and the potential distribution of an invasive alien plant: Acacia nilotica ssp. indica in Australia. J Appl Ecol 40:111–124CrossRefGoogle Scholar
  38. Kriticos D, Yonow T, McFadyen R (2005) The potential distribution of Chromolaena odorata (Siam weed) in relation to climate. Weed Res 45:246–254CrossRefGoogle Scholar
  39. Kriticos DJ, Potter KJ, Alexander NS, Gibb AR, Suckling D (2007) Using a pheromone lure survey to establish the native and potential distribution of an invasive Lepidopteran, Uraba lugens. J Appl Ecol 44:853–863CrossRefGoogle Scholar
  40. Kriticos DJ, Webber BL, Leriche A, Ota N, Macadam I, Bathols J, Scott JK (2012) CliMond: global high-resolution historical and future scenario climate surfaces for bioclimatic modelling. Methods Ecol Evol 3:53–64CrossRefGoogle Scholar
  41. Kriticos DJ, Jarošik V, Ota N (2014) Extending the suite of bioclim variables: a proposed registry system and case study using principal components analysis. Methods Ecol Evol 5:956–960CrossRefGoogle Scholar
  42. Kriticos DJ, Maywald GF, Yonow T, Zurcher EJ, Herrmann NI, Sutherst RW (2015a) CLIMEX version 4: exploring the effects of climate on plants, animals and diseases. CSIRO, CanberraGoogle Scholar
  43. Kriticos DJ, Ota N, Hutchison WD, Beddow J, Walsh T, Tay WT, Borchert DM, Paula-Moreas SV, Czepak C, Zalucki MP (2015b) The potential distribution of invading Helicoverpa armigera in North America: is it just a matter of time? PLoS ONE 10:e0119618CrossRefPubMedPubMedCentralGoogle Scholar
  44. Kurdov M (1986) Prognosis of massive multiplication of the small ground moth Spodoptera exigua Hbn. (Laphygma exigua Hbn.) in Turkmenistan. (Prognoz massovogo razmnozheniya maloj nazemnoj sovki Spodoptera exigua (Laphygma exigua Hbn.) v Turkmenistane) Isvestiia Akademii Nauk Turkmenskoi SSR Seriia biologicheskikh nauk 1:25–28Google Scholar
  45. Lawson BE, Day MD, Bowen M, van Klinken RD, Zalucki MP (2010) The effect of data sources and quality on the predictive capacity of CLIMEX models: an assessment of Teleonemia scrupulosa and Octotoma scabripennis for the biocontrol of Lantana camara in Australia. Biol Control 52:68–76CrossRefGoogle Scholar
  46. Lee S, Ahn S, Cho W, Choi K (1991) Effects of temperature on the development of beet armyworm, Spodoptera exigua Hübner (Lepidoptera: Noctuidae). Res Rep Rural Dev Adm (Crop Prot) 33:58–62Google Scholar
  47. Mikkola K (1970) The interpretation of long-range migrations of Spodoptera exigua Hb. (Lepidoptera: Noctuidae). J Anim Ecol 39:593–598CrossRefGoogle Scholar
  48. Mitchell E (1979) Migration by Spodoptera exigua and S. frugiperda, North American style. In: Rabb R, Kennedy G (eds) Movement of highly mobile insects: concepts and methodology in research. North Carolina State University, Raleigh, pp 386–393Google Scholar
  49. Portmann FT, Siebert S, Döll P (2010) MIRCA2000—global monthly irrigated and rainfed crop areas around the year 2000: a new high-resolution data set for agricultural and hydrological modeling. Glob Biogeochem Cycles 24:24. CrossRefGoogle Scholar
  50. Rodda GH, Jarnevich CS, Reed RN (2009) What parts of the US mainland are climatically suitable for invasive alien pythons spreading from Everglades National Park? Biol Invasions 11:241–252CrossRefGoogle Scholar
  51. Shelford VE (1963) The ecology of North America. University of Illinois Press, UrbanaGoogle Scholar
  52. Singh T (1982) The mealybug problem and its control. In: Root crops in Eastern Africa. Proceedings of a workshop held in Kigali, Rwanda, 23–27 November 1980. International Development Research Centre, Ottowa, pp 70–72Google Scholar
  53. Sparks JA, Riley DG (2015) Beet armyworm. University of Georgia College of Agricultural and Environmental Sciences. Accessed 16 June 2016
  54. Sutherst RW (2003) Prediction of species geographical ranges. J Biogeogr 30:805–816CrossRefGoogle Scholar
  55. Sutherst RW (2014) Pest species distribution modelling: origins and lessons from history. Biol Invasions 16:239–256CrossRefGoogle Scholar
  56. Sutherst R, Bourne A (2009) Modelling non-equilibrium distributions of invasive species: a tale of two modelling paradigms. Biol Invasions 11:1231–1237CrossRefGoogle Scholar
  57. Sutherst RW, Maywald GF (1985) A computerised system for matching climates in ecology. Agr Ecosyst Environ 13:281–299CrossRefGoogle Scholar
  58. Trumble JT, Baker TC (1984) Flight phenology and pheromone trapping of Spodoptera exigua (Hübner) (Lepidoptera: Noctuidae) in southern coastal California. Environ Entomol 13:1278–1282CrossRefGoogle Scholar
  59. van der Ploeg RR, Kirkham M (1999) On the origin of the theory of mineral nutrition of plants and the law of the minimum. Soil Sci Soc Am J 63:1055–1062CrossRefGoogle Scholar
  60. Van Klinken RD, Lawson BE, Zalucki MP (2009) Predicting invasions in Australia by a Neotropical shrub under climate change: the challenge of novel climates and parameter estimation. Glob Ecol Biogeogr 18:688–700CrossRefGoogle Scholar
  61. Venette RC, Kriticos DJ, Magarey R, Koch F, Baker RHA, Worner S, Gómez Raboteaux NN, McKenney D, Dobesberger E, Yemshanov D, De Barro P, Hutchison WD, Fowler G, Kalaris T, Pedlar J (2010) Pest risk maps for invasive alien species: a roadmap for improvement. Bioscience 80:349–362CrossRefGoogle Scholar
  62. Webber BL, Yates CJ, Le Maitre DC, Scott JK, Kriticos DJ, Ota N, McNeill A, Le Roux JJ, Midgley GF (2011) Modelling horses for novel climate courses: insights from projecting potential distributions of native and alien Australian acacias with correlative and mechanistic models. Divers Distrib 17:978–1000CrossRefGoogle Scholar
  63. Weedon GP, Balsamo G, Bellouin N, Gomes S, Best MJ, Viterbo P (2014) The WFDEI meteorological forcing data set: WATCH forcing data methodology applied to ERA-interim reanalysis data. Water Resour Res 50:7505–7514CrossRefGoogle Scholar
  64. Wilson J (1932) Notes on the biology of Laphygma exigua Hübner. Fla Entomol 16:33–39CrossRefGoogle Scholar
  65. Xu J, Zhipeng H, Yueping Y, Xiong G (1998) The bionomics and control effects of chemical insecticides for Spodoptera exigua. J Fujian Agric Univ (Nat Sci) 1:73–77Google Scholar
  66. Xu J, Xiong G, Zhipeng H, Yueping Y (1999) Effects of temperature on development of experimental beet armyworm population. Acta Phytophylacica Sin 26:20–24Google Scholar
  67. Yonow T, Sutherst RW (1998) The geographical distribution of the Queensland fruit fly, Bactrocera (Dacus) tryoni, in relation to climate. Aust J Agric Res 49:935–953CrossRefGoogle Scholar
  68. Yonow T, Hattingh V, de Villiers M (2013) CLIMEX modelling of the potential global distribution of the citrus black spot disease caused by Guignardia citricarpa and the risk posed to Europe. Crop Prot 44:18–28CrossRefGoogle Scholar
  69. Yonow T, Kriticos DJ, Ota N, Van Den Berg J, Hutchison WD (2017) The potential global distribution of Chilo partellus, including consideration of irrigation and cropping patterns. J Pest Sci 90:459–477CrossRefGoogle Scholar
  70. Zheng X-L, Cong X-P, Wang X-P, Lei C-L (2011a) A review of geographic distribution, overwintering and migration in Spodoptera exigua Hübner (Lepidoptera: Noctuidae). J Ent Res Soc 13:39–48Google Scholar
  71. Zheng X, Cheng W, Wang X, Lei C (2011b) Enhancement of supercooling capacity and survival by cold acclimation, rapid cold and heat hardening in Spodoptera exigua. Cryobiology 63:164–169CrossRefPubMedGoogle Scholar
  72. Zheng X-L, Wang P, Cheng W-J, Wang X-P, Lei C-L (2012) Projecting overwintering regions of the beet armyworm, Spodoptera exigua in China using the CLIMEX model. J Insect Sci 12:13CrossRefPubMedPubMedCentralGoogle Scholar
  73. Zheng X-L, Wang P, Lei C-L, Lu W, Xian Z-H, Wang X-P (2013) Effect of soil moisture on overwintering pupae in Spodoptera exigua (Lepidoptera: Noctuidae). Appl Entomol Zool 48:365–371CrossRefGoogle Scholar
  74. Zhu G, Bu W, Gao Y, Liu G (2012) Potential geographic distribution of brown marmorated stink bug invasion (Halyomorpha halys). PLoS ONE 7:e31246CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.HarvestChoice, InSTePPUniversity of MinnesotaSt. PaulUSA
  2. 2.CSIROCanberraAustralia
  3. 3.Forest Zoology Department, Siberian Branch of the Russian Academy of SciencesSukachev Institute of ForestKrasnoyarskRussia
  4. 4.Siberian Federal UniversityKrasnoyarskRussia
  5. 5.CSIROWembleyAustralia

Personalised recommendations