# The Use of Simulation Models to Evaluate Pest Resistance Development to Refuge in the

Bag Concepts related to Pioneer Submission

Letter Report Addendum

By

Michael Caprio 1 , John A. Glaser 2

1 Misssissippi State University, Department of Entomology a nd Plant Pathology, Mississippi State, MS 39762-9775, 2 US Environmental Protection Agen cy, National Risk Management Research Laboratory, Sustainable Technology Division, Cincinnati, OH 45268

April 12, 2010

Sustainable Technology Division National Risk Management Research Laboratory US Environmental Protection Agency Cincinnati, OH 45268

A portion of the work outlined in this report was accomplished under contract Dr Michael Capri o1.0 Modeling Extensions

The original POPGEN model developed by EPA-ORD limite d dispersal to local movement based on the Pioneer data. Other researchers ( Marquardt.& .Krupke 2009; Spencer (2009); Scott et al. (2004); Naranjo (1990); Coat s et al. (1986); Van Woerkom et al. (1983); and Witkowski et al. (1975) have suggested, however, that there may be additional long distance dispersal. This dispersal was not the objective of the Pioneer stu dy and would not have been detectable in that study (Pan et al. 2009; Rood et al. 2009). For exam ple, Spencer has reported mean dispersal rates over soybean fields of more than 200m/day. Sp encer has also suggested that young females may disperse further than previously estimated. Re sults from studies indicate that some preovipositional females can disperse much further th an 20 kilometers (Coats et al., 1986). These distances are greater than the scale of our simu lations, and we simulated this dispersal via an island model (a dispersing insect is placed into a random cell without regard to distance). If we consider our simulated system (144 ha) to be one of many in the area , many of our simulated insects may move out of our system, and equal nu mber would arrive from neighboring systems. These females disperse to long distances that any correlation between refuge placement and transgenic cells would be lost, and an island model of dispersal was most appropriate. To determine the effect of this longer distance disper sal on the results of the block refuge model, we incorporated a two-phase dispersal model. On each day of the simulati on, 55% of the adults would dispersal according to the Pioneer data (except for the zero movement bin). Of the remaining 45%, 23.7% of the pre-ovipositional females dispersed long er distances per day, resulting in 25% of the origin al pre-ovipositional females disp ersing according to an islandmodel (the stage was 3 days long). Twenty simula tions were run with just the Pioneer dispersal distribution, and 20 simulations we re conducted with the two phase model. The field size was 36ha and the system size was 6400 patches (or 16 fi elds). All other parameters were defaults listed in the original report (Caprio, M; J.Glaser, 2010).

Results: There was significant difference in the time take n for resistance to evolve between the two dispersal treatments (Welch two sample t-test; t = -19.43, df = 30.48, p < 2.2e-16). The mean time for the single phase dispersal simulations was 2210.2 days (15.8 years), and 2829.7 days (20.2 years) for the dual phase simulations. Our conclu sion is that the Pioneer model underestimated the impact of long distance dispersal. As noted in discussions with Pioneer , they did this because they were focused on non-random mating. The pr e-ovipositional adults th at dispersed in our model had already mated, addressing the concer ns about non-random mating. This suggests that the primary effect of these long distance dispersants is that they fill in th e areas of fields where adults dispersing via the Pioneer m odel rarely reach. This behavior increases the effective refuge size when the refuge is moved as females were present in that new area, and, even though they mated non-randomly, oviposited eggs that “seeded ” the new refuge. These simulation results do not contradict the previous simulations in whic h mean distance had been increased compared to Pioneer data. Those simulations did not change the proportion of the population that dispersed, while these simulations significantly increased pr e-ovipositional female dispersal. The 2 phase simulations also differed because they used an island model of dispersal, increasing the mean dispersal distance.Note: Pioneer had suggested that the results of the EPA m odeling research which indicated the most likely effective refuge size of 15% to be hi gh. This value was based on a comparison of the

deterministic and stochastic model. The stochast ic model allows us to incorporate many more details about corn rootworm biology. The time to resistance was approximately 15.8 years using

the above data. If we insert similar numbers for the deterministic model, an effective refuge size of 15% (actually 16% is a better fit) gives 14 years as the time to resistance. This result shows the most likely value for the effective refuge size to be increased rather than decreased, based on

the stochastic simulation results. Note that these simulations were single deterministic

simulations run with the default Pioneer values and cannot be dire ctly compared to the time to

resistance results from the risk assessment runs . The latter simulations included uncertainty in the parameters rather than fixed parameter values.

Caprio, M; J.Glaser 2010 Simulation Models Ev aluation of Pest Resistance Development to Refuge in the Bag Concepts Related to Pioneer Submission EPA/600/R-10/055. Coats SA, JA Mutchmor, and JJ Tollefson. 1986. Study of migratory flight in the western corn rootworm (Coleoptera: Chrysomeldiae). Environ. Entomol. , 15: 620-625 Marquardt. P.T., C.H.Krupke 2009. Di spersal and Mating Behavior of Diabrotica virgifera virgifera (Coleoptera: Chrysomelidae) in Bt Cornfields, Environ. Entomol . 38(1): 176-182. Meinke , L.J., T.W. Sappington , D. W. Onstad , T. Guillemaud , N. J. Miller, J. Komáromi , N. Levay , L. Furlan , J. Kiss and F. Toth, Western corn rootworm ( Diabrotica virgifera virgifera LeConte) population dynamics, 2009. Agri. Forest Entomol. 11: 29–46 Pan, Z., DW Onstad, BH Stanley, JL Flexner, Q Chen, and SA Lefko, 2009. Addendum to: A Spatially Explicit Computer Simulation Study of Corn Rootworm, Diabrotica spp. [Coleoptera: Chrysomelidae], Pioneer Hi-Bred Inte rnational, Inc., Study ID: PHI-2009-125 Rood, T, Z Pan, D Onstad, B Stanley, JL Flexner, Q Chen, T Nowatzki, M Ziegler, and S Lefko, 2009. Additional Addendum to MRID 473567-08: A Spatially Explicit Computer Simulation Study of Corn Rootworm, Diabrotica spp. [Coleoptera: Chrysomelidae], Pioneer Hi-BredInternational, Inc., Study Number: PHI-2009-197 Spencer J. 2009. Personal communication. E-mail response and summary of unpublished data submitted to J.C. Martinez (EPA), dated December 28, 2009. Scott IA, JL Spencer, TR Mabry, and E Levine . 2004. Influence of atmospheric conditions on high-elevation flight of Western corn rootworm (Choleoptera: Chrysomelidae), Environ. Entomol. , 33(3):650-656. Storer, N.P.2003.A Spatially Explicit Model Simu lating Western Corn Rootworm (Coleoptera: Chrysomelidae) Adaptation to Insect-Resistant Maize, J. Econ. Entomol. 96 (5): 1530-1547. Van Woerkom GJ, FT Turpin, & JR Barret Jr . 1983. Wind effect on western corn rootworm (Coleoptera: Chrysomelidae) flight behavior. Environ. Entomol.12: 196-200. Witkowski JF, JC Owens, and JJ Tollefson. 1975. Diel activity and vertical f light distribution of adult western corn rootworms in Iowa cornfields. J.Econ. Entomol .. 68: 351-352.

2.0 Corn Field Size Determination The use of MODIS imagery at 250m resolution obscures any smaller field dimensions.as depicted in Doraiswamy, Stern, and Akhme dov, 2007. Furthermore, their selection of 64 hectares as the representative corn field appears to be a default selection. I have spoken with Kenneth Copenhaver of the University of Illinois at Chicago about the corn field sizes in Illinois and he indicated that there was a range field sizes and the median acreage was 32 hectares. Smaller field sizes are prominent for corn and soybeans. I called Lance Meinke at the University

of Nebraska to ask him to assess the corn field size found in Nebraska. Lance said that there was a gradient of field sizes starting at 32 hectares in the eastern part of the state to 64 hectare fields in the west where pivot irrigation was important. I also look ed that the USDA NASS Census of Agriculture for 2007 and found that th ere is significant field acreag e for sizes of 32 hectares and

less.

Doraiswamy, P.C., A. J. Stern, and B. Akhm edov, 2007 Crop Classification in the U.S. Corn Belt Using MODIS Imagery, Presentation at the International Geoscience and Remote Sensing Symposium, July 19 – 27, 2007, Barcelona, SpainKenneth Copenhaver, Phone conversation with J Glaser, March 2010 Lance Meinke, Phone conversati on with J Glaser, March 2010 USDA NASS Census of Agriculture 2007 http://www.agcensus.usda.gov/