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Estimating the impact of climate change on the occurrence of selected pests at a high spatial resolution: a novel approach

Published online by Cambridge University Press:  05 January 2011

E. KOCMÁNKOVÁ ,
M. TRNKA ,
J. EITZINGER ,
M. DUBROVSKÝ ,
P. ŠTĚPÁNEK ,
D. SEMERÁDOVÁ ,
J. BALEK ,
P. SKALÁK ,
A. FARDA  and
J. JUROCH
...Show all authors
E. KOCMÁNKOVÁ*
Affiliation:
Institute for Agrosystems and Bioclimatology, Mendel University of Agriculture and Forestry Brno, Czech Republic
M. TRNKA
Affiliation:
Institute for Agrosystems and Bioclimatology, Mendel University of Agriculture and Forestry Brno, Czech Republic Institute of Atmospheric Physics, Academy of Sciences of the Czech Republic, Prague, Czech Republic
J. EITZINGER
Affiliation:
Institute for Meteorology, University of Natural Resources and Applied Life Sciences (BOKU), Vienna, Austria
M. DUBROVSKÝ
Affiliation:
Institute for Agrosystems and Bioclimatology, Mendel University of Agriculture and Forestry Brno, Czech Republic Institute of Atmospheric Physics, Academy of Sciences of the Czech Republic, Prague, Czech Republic
P. ŠTĚPÁNEK
Affiliation:
Czech Hydrometeorological Institute, Brno, Czech Republic
D. SEMERÁDOVÁ
Affiliation:
Institute for Agrosystems and Bioclimatology, Mendel University of Agriculture and Forestry Brno, Czech Republic Institute of Atmospheric Physics, Academy of Sciences of the Czech Republic, Prague, Czech Republic
J. BALEK
Affiliation:
Institute for Agrosystems and Bioclimatology, Mendel University of Agriculture and Forestry Brno, Czech Republic
P. SKALÁK
Affiliation:
Czech Hydrometeorological Institute, Brno, Czech Republic
A. FARDA
Affiliation:
Czech Hydrometeorological Institute, Brno, Czech Republic
J. JUROCH
Affiliation:
State Phytosanitary Administration, Brno, Czech Republic
Z. ŽALUD
Affiliation:
Institute for Agrosystems and Bioclimatology, Mendel University of Agriculture and Forestry Brno, Czech Republic
*
*To whom all correspondence should be addressed. Email: [email protected]
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Summary

The present study is focused on the potential occurrence of the Colorado potato beetle (Leptinotarsa decemlineata, Say 1824), an important potato pest, and the European corn borer (Ostrinia nubilalis, Hübner 1796), the most important maize pest, during climate change. Estimates of the current potential distribution of both pest species as well as their distribution in the expected climate conditions are based on the CLIMEX model. The study covers central Europe, including Austria, the Czech Republic, Hungary, and parts of Germany, Poland, Romania, Slovakia, Switzerland, Ukraine, Slovenia, the northern parts of Serbia, parts of Croatia and northern Italy. The validated model of the pests’ geographical distribution was applied within the domain of the regional climate model (RCM) ALADIN, at a resolution of 10 km. The weather series that was the input for the CLIMEX model was prepared by a weather generator (WG) which was calibrated with the RCM-simulated weather series (for the period of 1961–90). To generate a weather series for two future time periods (2021–50 and 2071–2100), the WG parameters were modified according to 12 climate change scenarios produced by the pattern scaling method. The standardized scenarios derived from three global climate models (HadCM, NCAR-PCM and ECHAM) were scaled by low, middle and high values of global temperature change estimated by the Model for the Assessment of Greenhouse-gas Induced Climate Change (MAGICC) model (assuming three combinations of climatic sensitivity and emission scenarios). The results of present study suggest the likely widening of the pests’ habitats and an increase in the number of generations per year. According to the HadCM-high scenario, the area of arable land affected by a third generation per season of Colorado potato beetle in 2050 is c. 45% higher, and by a second generation of the European corn borer is nearly 61% higher, compared to present levels.

Type
Climate Change and Agriculture
Information
The Journal of Agricultural Science , Volume 149 , Issue 2 , April 2011 , pp. 185 - 195
Copyright
Copyright © Cambridge University Press 2011

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References

REFERENCES

Anderson, T. E., Kennedy, G. G. & Stinner, R. E. (1982). Temperature-dependent models of ECB (Lepidoptera: Pyralidae) development in North Carolina. Environmental Entomology 11, 1145–1150.CrossRefGoogle Scholar
Baker, R. H. A., Sansford, C. E., Jarvis, C. H., Cannon, R. J. C., Macleod, A. & Walters, K. F. A. (2000). The role of climatic mapping in predicting the potential geographical distribution of non-indigenous pests under current and future climates. Agriculture, Ecosystems and Environment 82, 57–71.CrossRefGoogle Scholar
Bell, N. L. & Willoughby, B. E. (2003). A review of the role of predatory mites in the biological control of Lucerne flea, Sminthurus viridis (L.) (Collembola: Sminthuridae) and their potential use in New Zealand. New Zealand Journal of Agricultural Research 46, 141–146.Google Scholar
Berry, P. M., Dawson, T. P., Harrison, P. A. & Pearson, G. (2002). Modelling potential impacts of climate change on the bioclimatic envelope of species in Britain and Ireland. Global Ecology and Biogeography 11, 453–462.Google Scholar
Birova, H., Brestovsky, J., Jakubcin, P. & Longauerova, J. (1990). Skúsenosti s vypúšťaním Trichogramy hnedej, Trichogramma evanescens, proti vijačke kukuričnej, Ostrinia nubilalis, na cukrovej kukurici. Ochrana Rostlin 26, 29–36.Google Scholar
Carlevaris, B., Gomboc, S. & Milevoj, L. (2003). Study on European corn borer (Ostrinia nubilalis, Hübner) on different corn hybrids in Goriska region. In Zbornik predavanj in referatov 6. Slovenskega Posvetovanje o Varstvu Rastlin, Zrece, Slovenije, pp. 176–182.Google Scholar
Carpenter, G., Gillison, A. N. & Winter, J. (1993). DOMAIN: a flexible modelling procedure for mapping potential distributions of plants and animals. Biodiversity and Conservation 2, 667–680.CrossRefGoogle Scholar
Carrol, A. L., Régnière, J., Logan, J. A., Taylor, S. W., Bentz, B. J. & Powell, J. A. (2006). Impacts of climate change on range expansion by the Mountain pine beetle. Mountain Pine Beetle Initiative Working Paper 2006–14. Victoria, British Columbia, Canada: Natural Resources Canada & Canadian Forest Service.Google Scholar
Dubrovsky, M., Buchtele, J. & Zalud, Z. (2004). High-frequency and low-frequency variability in stochastic daily weather generator and its effect on agricultural and hydrologic modelling. Climatic Change 63, 145–179.CrossRefGoogle Scholar
Dubrovsky, M., Nemesova, I. & Kalvova, J. (2005). Uncertainties in climate change scenarios for the Czech Republic. Climate Research 29, 139–156.Google Scholar
Dubrovsky, M., Zalud, Z. & Stastna, M. (2000). Sensitivity of CERES-Maize yields to statistical structure of daily weather series. Climatic Change 46, 447–472.CrossRefGoogle Scholar
EPPO (2007). Plant Quarantine Data Retrieval System, PQR – version 4.6. Available online at: http://www.eppo.org/DATABASES/pqr/pqr.htm (verified 2 September 2010).Google Scholar
Gates, W. L., Henderson-Sellers, A., Boer, G. J., Folland, C. K., Kitoh, A., McAvaney, B. J., Semazzi, E., Smith, N., Weaver, A. J. & Zeng, Q.-C. (1996). Climate models – evaluation. In Climate Change 1995: the Science of Climate Change. Contribution of Working Group I to the Second Assessment Report of the Intergovernmental Panel on Climate Change (Eds Houghton, J. T., Meira Filho, L. G., Callander, B. A., Harris, N., Kattenberg, A. & Maskell, K.), pp. 229–284. Cambridge, UK: Cambridge University Press.Google Scholar
Goldammer, J. G. & Price, C. (1998). Potential impacts of climate change on fire regimes in the tropics based on MAGICC and a GISS GCM-derived lightning model. Climate Change 39, 273–296.Google Scholar
Gomboc, S., Milevoj, L. & Celar, F. (1996). Actualities on European corn borer (Ostrinia nubilalis Hbn.) in corn growing in Slovenia. In Simpozij Novi izzivi v poljedelstvu (Proceedings of the Symposium on New Challenges in Field Crop Production), 9–10 December, Radenci, Slovenia.Google Scholar
Hare, J. D. (1990). Ecology and management of the Colorado potato beetle. Annual Review of Entomology 35, 81–100.CrossRefGoogle Scholar
Harvey, L. D. D., Gregory, J. M., Hoffert, M., Jain, A. K., Lal, M., Leemans, R., Raper, S. B. C., Wigley, T. M. L. & De Wolde, J. (1997). An Introduction to Simple Climate Models used in the IPCC Second Assessment Report. IPCC Technical Paper 2 (Eds Houghton, J. T., Meira Filho, L. G., Griggs, D. J. & Maskell, K.). Geneva, Switzerland: Intergovernmental Panel on Climate Change.Google Scholar
Hill, J. K., Thomas, C. D., Fox, R., Telfer, M. G., Willis, S. G., Asher, J. & Huntley, B. (2002). Responses of butterflies to twentieth century climate warming: implications for future ranges. Proceedings of the Royal Society of London, Series B, Biological Sciences 269, 2163–2171.Google Scholar
Hill, J. K., Thomas, C. D. & Huntley, B. (1999). Climate and habitat availability determine 20th century changes in a butterfly's range margin. Proceedings of the Royal Society of London, Series B, Biological Sciences 266, 1197–1206.CrossRefGoogle Scholar
Houghton, J. T., Ding, Y., Griggs, D. J., Noguer, M., Van Der Linden, P. J., Dai, X., Maskell, K. & Johnson, C. A. (2001). Climate Change 2001: the Scientific Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change (IPCC). Cambridge, UK: Cambridge University Press.Google Scholar
Hulme, M., Wigley, T. M. L., Barrow, E. M., Raper, S. C. B., Centella, A., Smith, S. & Chipanshi, A. C. (2000). Using a Climate Scenario Generator for Vulnerability and Adaptation Assessments: MAGICC and SCENGEN Version 2.4 Workbook. Norwich, UK: Climatic Research Unit.Google Scholar
Kocmankova, E., Trnka, M., Zalud, Z., Semeradova, D., Dubrovsky, M., Muska, F. & Mozny, M. (2008). The comparison of mapping methods of European corn borer (Ostrinia nubilalis) potential distribution. Plant Protection Science 44, 49–56.Google Scholar
Kont, A., Jaagus, J. & Aunap, R. (2003). Climate change scenarios and the effect of sea-level rise for Estonia. Global and Planetary Change 36, 1–15.CrossRefGoogle Scholar
Kriticos, D. J., Sutherst, R. W., Brown, J. R., Adkins, S. W. & Maywald, G. F. (2003). Climate change and the potential distribution of an invasive alien plant: Acacia nilotica ssp. indica in Australia. Journal of Applied Ecology 40, 111–124.Google Scholar
Lockett, C. J. & Palmer, W. A. (2003). Rearing and release of Homichloda barkeri (Jacoby) (Coleoptera: Chrysomelidae: Alticinae) for the biological control of prickly acacia, Acacia nilotica ssp. indica (Mimosaceae) in Australia. Australian Journal of Entomology 42, 287–293.CrossRefGoogle Scholar
Nix, H. (1986). A biogeographic analysis of Australian Elapid snakes. In Snakes: Atlas of Elapid Snakes of Australia (Ed. Longmore, R.), pp. 4–15. Australian Flora and Fauna Series No. 7. Canberra: Australian Government Publishing Service.Google Scholar
Oerke, E.-C. (2006). Crop losses to pests. Journal of Agricultural Science, Cambridge 144, 31–43.Google Scholar
Olfert, O. & Weiss, R. M. (2006). Impact of climate change on potential distributions and relative abundances of Oulema melanopus, Meligethes viridescens and Ceutorhyncus obstrictus in Canada. Agriculture, Ecosystems and Environment 113, 295–301.CrossRefGoogle Scholar
Parmesan, C., Ryrholm, N., Stefanescu, C., Hill, J. K., Thomas, C. D., Descimon, H., Huntley, B., Kaila, L., Kullberg, J., Tammaru, T., Tennent, W. J., Thomas, J. A. & Warren, M. (1999). Poleward shifts in geographical ranges of butterfly species associated with regional warming. Nature 399, 579–583.Google Scholar
Pearson, R. G., Dawson, T. P., Berry, P. M. & Harrison, P. A. (2002). SPECIES: a spatial evaluation of climate impact on the envelope of species. Ecological Modeling 154, 289–300.CrossRefGoogle Scholar
Pearson, R. G., Dawson, T. P. & Liu, C. (2004). Modelling species distributions in Britain: a hierarchical integration of climate and land-cover data. Ecography 27, 285–298.CrossRefGoogle Scholar
Pethybridge, S. J., Nelson, M. E. & Wilson, C. R. (2003). Forecasting climate suitability of Australian hop-growing regions for establishment of hop powdery and downy mildews. Australasian Plant Pathology 32, 493–497.CrossRefGoogle Scholar
Pollard, E., Moss, D. & Yates, T. J. (1995). Population trends of common British butterflies at monitored sites. Journal of Applied Ecology 32, 9–16.CrossRefGoogle Scholar
Pollard, E. & Yates, T. J. (1993). Monitoring Butterflies for Ecology and Conservation. London: Chapman and Hall.Google Scholar
Porter, J. H., Parry, M. L. & Carter, T. R. (1991). The potential effects of climatic change on agricultural insect pests. Agriculture and Forest Meteorology 57, 221–240.CrossRefGoogle Scholar
Rafoss, T. & Sæthre, M. G. (2003). Spatial and temporal distribution of bioclimatic potential for the codling moth and the Colorado potato beetle in Norway: model predictions versus climate and field data from the 1990s. Agricultural and Forest Entomology 5, 75–86.CrossRefGoogle Scholar
Régnière, J., Cooke, B. & Bergeron, V. (1995). BioSIM: A Computer-based Decision Support Tool for Seasonal Planning of Pest Management Activities. User's Manual. Information Report LAU-X-116. Quebec, Canada: Laurentian Forestry Service.Google Scholar
Régnière, J. & Sharov, A. (1998). Phenology of Lymantria dispar (Lepidoptera: Lymantriidae), male flight and the effect of moth dispersal in heterogenous landscapes. International Journal of Biometeorology 41, 161–168.Google Scholar
Rodda, G. H., Reed, R. N. & Jarnevich, C. S. (2007). Climate matching as a tool for predicting potential north American spread of brown treesnakes. In Managing Vertebrate Invasive Species: Proceedings of an International Symposium, Fort Collins, Colorado, 7–9 August 2007 (Eds Witmer, G. W., Pitt, W. C. & Fagerstone, K. A.), pp. 137–145. Fort Collins, CO: National Wildlife Research Center.Google Scholar
Sutherst, R. W. (2000 a). Climate change and invasive species – a conceptual framework. In Invasive Species in a Changing World (Eds Mooney, H. A. & Hobbs, R. J.), pp. 211–240. Washington, DC: Island Press.Google Scholar
Sutherst, R. W. (2000 b). Climate variability, seasonal forecasting and invertebrate pests – the need for a synoptic view. In Applications of Seasonal Climate Forecasting in Agricultural and Natural Ecosystems. The Australian Experience (Eds Hammer, G. L., Nicholls, N. & Mitchell, C.), pp. 381–397. Dordrecht, The Netherlands: Kluwer Academic Publishers.Google Scholar
Sutherst, R. W. & Maywald, G. F. (1985). A computerised system for matching climates in ecology. Agriculture Ecosystems and Environment 13, 281–299.Google Scholar
Sutherst, R. W., Maywald, G. F., Bottomley, W. & Bourne, A. (2004). CLIMEX v2: User's Guide. Queensland, Australia: CSIRO Publishing.Google Scholar
Trnka, M., Muska, F., Semeradova, D., Dubrovsky, M., Kocmankova, E. & Zalud, Z. (2007). European corn borer life stage model: regional estimates of pest development and spatial distribution under present and expected climate. Ecological Modeling 207, 61–84.Google Scholar
Trnka, M., Zalud, Z., Dubrovsky, M., Muska, F., Semeradova, D. & Kocmankova, E. (2005). Modelling of the European Corn Borer climatic niche under expected climate conditions. In Sborník referátů z mezinárodní vědecké konference Bioklimatologie současnosti a budoucnosti, Křtiny, 12–14 September 2005 (Eds Roznovsky, J. & Litschmann, T.). Křtiny, Czech Republic: Czechoslovak Bioclimatological Society [CD ROM].Google Scholar
Walker, P. A. & Cocks, K. D. (1991). HABITAT A procedure for modelling a disjoint environmental envelope for a plant or animal species. Global Ecology and Biogeography Letters 1, 108–118.Google Scholar
Yamamura, K. & Yokozawa, M. (2002). Prediction of a geographical shift in the prevalence of rice stripe virus disease transmitted by the small brown planthopper, Laodelphax striatellus (Fallen) (Hemiptera: Delphacidae), under global warming. Applied Entomology and Zoology 37, 181–190.Google Scholar
Zalucki, M. P. & Furlong, M. J. (2005). Forecasting Helicoverpa populations in Australia: a comparison of regression based models and a bio-climatic based modelling approach. Insect Science 12, 45–56.Google Scholar