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 Caprio1, John A. Glaser2

1

Misssissippi State University, Department of Entomology and Plant Pathology, Mississippi 

State, MS 39762-9775, 2US Environmental Protection Agency, 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 Caprio
1.0 Modeling Extensions 

The original POPGEN model developed by EPA-ORD limited dispersal to local movement 

based on the Pioneer data. Other researchers (Marquardt.& .Krupke 2009; Spencer (2009); Scott 

et al. (2004); Naranjo (1990); Coats 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 study and would not have been detectable in that 

study (Pan et al. 2009; Rood et al. 2009). For example, Spencer has reported mean dispersal rates 

over soybean fields of more than 200m/day. Spencer has also suggested that young females may 

disperse further than previously estimated. Results from studies indicate that some preovipositional females can disperse much further than 20 kilometers (Coats et al., 1986). These 

distances are greater than the scale of our simulations, 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 number 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 dispersal on the results of the block refuge model, we 

incorporated a two-phase dispersal model. On each day of the simulation, 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 longer distances per day, 

resulting in 25% of the original pre-ovipositional females dispersing according to an island 
model (the stage was 3 days long). Twenty simulations were run with just the Pioneer dispersal 

distribution, and 20 simulations were conducted with the two phase model. The field size was 

36ha and the system size was 6400 patches (or 16 fields). All other parameters were defaults 

listed in the original report (Caprio, M; J.Glaser, 2010). 

Results: 

There was significant difference in the time taken 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 conclusion 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 pre-ovipositional adults that dispersed in our 

model had already mated, addressing the concerns about non-random mating. This suggests that 

the primary effect of these long distance dispersants is that they fill in the areas of fields where 

adults dispersing via the Pioneer model 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 which 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 pre-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 modeling research which indicated the most 

likely effective refuge size of 15% to be high. This value was based on a comparison of the 

deterministic and stochastic model. The stochastic 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 directly 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 Evaluation 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. Dispersal 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 International, 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-Bred 
International, 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 Simulating 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 flight 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 Akhmedov, 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 looked that the USDA NASS Census of 

Agriculture for 2007 and found that there is significant field acreage for sizes of 32 hectares and 

less. 

Doraiswamy, P.C., A. J. Stern, and B. Akhmedov, 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, Spain 
Kenneth Copenhaver, Phone conversation with J Glaser, March 2010 

Lance Meinke, Phone conversation with J Glaser, March 2010 

USDA NASS Census of Agriculture 2007 http://www.agcensus.usda.gov/