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Potential Distribution and Relative Abundance of Swede Midge, Contarinia Nasturtii, an Invasive Pest in Canada O

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Potential Distribution and Relative Abundance of Swede Midge, Contarinia Nasturtii, an Invasive Pest in Canada O Blackwell Publishing Ltd Potential distribution and relative abundance of swede midge, Contarinia nasturtii, an invasive pest in Canada O. Olfert1*, R. Hallett2, R.M. Weiss1, J. Soroka1 & S. Goodfellow2 1Agriculture and Agri-Food Canada, Saskatoon Research Centre, 107 Science Place, Saskatoon, Saskatoon S7N 0X2, Canada and 2Department of Environmental Biology, University of Guelph, Guelph, Ontario N1G 2W1, Canada Accepted: 11 May 2006 Key words: Contarinia nasturtii, Diptera, Cecidomyiidae, crop pest, cruciferous crops, bioclimatic model Abstract The swede midge, Contarinia nasturtii (Kieffer) (Diptera: Cecidomyiidae), is a pest of most cultivated Brassicaceae such as broccoli, canola, cauliflower, cabbage, and Brussels sprouts. The species primarily has a Palaearctic distribution and occurs throughout Europe and southwestern Asia to the Caucasus. Between 1996 and 1999, producers of cruciferous vegetables in Ontario, Canada, reported crop damage that was consistent with damage symptoms characteristic of C. nasturtii feeding and in 2000, field studies confirmed that this damage was caused by C. nasturtii. A bioclimatic model was developed to predict potential range and relative abundance of C. nasturtii in Canada in order to determine the impact of the establishment and spread of C. nasturtii populations. Model output indicated that C. nasturtii could potentially become established in all provinces of Canada, with the risk being greatest in southwestern British Columbia, southern Ontario and Quebec, New Brunswick, Nova Scotia, and Prince Edward Island. Results indicated that C. nasturtii population growth in the Prairie Ecozone of western Canada would be greatest in years with above average precipitation. lay eggs, in clusters of 2–50, on the surface of actively growing Introduction plants. Larvae feed on actively growing stems, leaves, and Swede midge, Contarinia nasturtii (Kieffer) (Diptera: flowers, then drop to the soil to pupate. During the growing Cecidomyiidae), is a pest of cruciferous plants (Brassi- season, adults can emerge within 2 weeks or larvae enter caceae) (Barnes, 1946). This species primarily has a diapause in autumn. Depending on temperature and soil Palaearctic distribution which includes Austria, Belgium, moisture, C. nasturtii may have 2–5 generations (Read- Britain, Bulgaria, Czech Republic, Denmark, France, shaw, 1961, 1966; Rygg & Braekke, 1980; Hallett & Heal, Germany, Hungary, Ireland, Italy, Latvia, Lithuania, 2001). Temperature and moisture have been identified to be Norway, Poland, Portugal, Romania, Russia, Slovakia, the two most important factors responsible for popula- Slovenia, Spain, Sweden, Switzerland, The Netherlands, tion distribution, growth, and control. Population growth Turkey, Ukraine, Yugoslavia, and southwestern Asia to the was greatest in warm, moist seasons and reduced in cool or Caucasus (Skuhrava, 1986; Darvas et al., 2000; Garland, dry seasons (Readshaw, 1961). 2002; Fauna Europaea Web Service, 2004). The recent introduction of C. nasturtii to North America Plant hosts include cruciferous weeds and most culti- presents a risk to widely grown cruciferous crops including vated crucifers such as broccoli, canola, cauliflower, broccoli, canola, and cabbage. As early as 1996, producers cabbage, and Brussels sprouts (Stokes, 1953; Darvas et al., of cruciferous vegetables in southern Ontario, Canada, 2000). Plant damage is caused by larval feeding; symptoms reported crop damage that was consistent with symptoms include misshapen plants and the formation of galls on characteristic of C. nasturtii. Field studies in 2000 con- leaves and flowers (Bardner et al., 1971). The larval stage firmed that this damage was caused by C. nasturtii (Hallett overwinters in the soil, adults emerge in May and females & Heal, 2001). In 2005, the Canadian Food Inspection Agency (CFIA) survey detected C. nasturtii in 15 counties *Correspondence: O. Olfert, Agriculture and Agri-Food Canada, in Ontario and 20 regulated areas in Quebec (CFIA, 2005). Saskatoon Research Centre, 107 Science Place, Saskatoon, SK S7N Bioclimatic simulation models have been used success- 0X2, Canada. E-mail: [email protected] fully to predict the distribution and extent of insect © 2006 Agriculture & Agri-Food Canada (AAFC) Entomologia Experimentalis et Applicata 120: 221–228, 2006 Journal compilation © 2006 The Netherlands Entomological Society 221 222 Olfert et al. establishment in new environments (McKenney et al., developed by iteratively adjusting parameter values to 2003; Olfert et al., 2004; Sutherst & Maywald, 2005). produce mapped results that closely approximated Bioclimatic modelling software, such as CLIMEX observed distribution for C. nasturtii in Europe. Model (Sutherst et al., 2004), enables the development of models parameterization was conducted for Belgium, Britain, that describe the potential distribution and relative France, Germany, Switzerland, Norway, and The Nether- abundance of a species based on climate (Sutherst, 2000). lands. The remaining European countries were treated as Inferential models infer a species response to climate, based an independent data set and used for model validation. Once on its geographic range, phenology, relative abundance, the European distribution was defined, based on a visual and empirical data. CLIMEX models allow researchers to comparison of model output with observed distribution, develop an overview of climatic factors that affect species EI values were compared to reported data on relative abun- distribution and abundance and permit identification of dance. Published results related to abundance were used to non-climatic factors that limit species distribution refine parameter values so that highest EI values occurred (Sutherst & Maywald, 2005). Sensitivity analysis can be where C. nasturtii was known to cause damage and lower used to test hypotheses related to the effect of varying values occurred when the species was less prevalent. climate variables (i.e., warmer/cooler or wetter/dryer than The model was validated by comparing output to normal conditions) on the species distribution and reported distributions and seasonal phenology and tested abundance. for consistency with empirical data. Three methods were The objective of the study was to develop a bioclimatic used to validate the model first, the model was applied to model to predict potential range and relative abundance of predict the population distribution of C. nasturtii in eastern C. nasturtii in Canada, to identify areas in Canada that are Europe (Bulgaria, Czech Republic, Hungary, Poland, at risk for establishment of the swede midge, and to use the Romania, Slovakia, Ukraine, and Yugoslavia), Asia, southern model to develop a better understanding of how climate Ontario, and New York State. Model output for these affects C. nasturtii populations. regions was compared to known distributions as reported by Skuhrava (1986), Darvas et al. (2000), Garland (2002), Fauna Europaea Web Service (2004), and CFIA (2005). Methods Second, model output for phenology and number of The bioclimatic modeling process has been previously generations was compared to published reports for described (Vera et al., 2002; Mason et al., 2003; Olfert Europe (Readshaw, 1961, 1966; Rygg & Braekke, 1980; et al., 2004; Sutherst & Maywald, 2005). CLIMEX models Bouma, 1996). Third, model results which related to insect derive Ecoclimatic Index (EI) values that describe the phenology, based on southern Ontario weather data as climatic suitability, in terms of insect survival and input, were compared to field data collected by R. Hallett reproduction, of specific locations. The Growth Index (GI) (unpubl.). is a function of weekly temperature – TI, diapause – DI, The CLIMEX model required five meteorological light – LI, and moisture – MI indices. Stress indices are inputs: temperature (maximum and minimum), precipi- related to factors that limit geographical distribution tation, and relative humidity (at 09:00 and 15:00 hours). and include stress associate with temperature (heat stress – The Compare Locations function required monthly HS, cold stress – CS) and moisture (wet stress – WS, dry long-term average climatic variables. Climate data from stress – DS). Each index value is derived from functions New et al. (1999) were used as an input for the Compare that are based on 2–5 parameters. Indices and related Locations function. The data set represents a splined 0.5° parameters are illustrated in Table 1. The EI value world grid data set. Models were run for Europe (n = 6416 integrates annual growth with annual stress to produce grids) and Canada (south of 65°N latitude, n = 4472 grids). a single value (between 1 and 100) for each location. EI The moisture index (MI) is based on a calculated soil values near 0 indicate that the location’s climate is not moisture value. CLIMEX used a hydrological submodel to suitable for long-term establishment of the species. An EI compute a weekly soil moisture balance. Soil moisture value greater than 30 indicates a very favourable climate. balance was based on soil moisture from the previous Initial parameter values were based on published data week, and current week values for precipitation and evapo- that resulted from laboratory and field studies (Stokes, transpiration. CLIMEX used a degree-day model, based on 1953; Readshaw, 1961, 1966; Bardner et al., 1971; Rygg & the algorithm published by Baskerville & Emin (1969) to Braekke, 1980; Bouma, 1996) and are defined in Table 1. compute the temperature index (TI) and
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