Shifting focus from the population to the individual as a way forward in understanding, predicting and managing the complexities of evolution of resistance to pesticides

Pest Management Science

Volumn 69, Issue 2, 2013, Pages 171-175

  Renton, Michael ^a,b  

^a UNIVERSITY OF WESTERN AUSTRALIA   (Australia)

^b CSIRO   (Australia)

Author keywords

Evolution; Individual based model; Insect; Pesticide; Resistance; Weed

Indexed keywords

PESTICIDE;

ECOLOGICAL MODELING; PESTICIDE RESISTANCE; POPULATION STRUCTURE; PREDICTION; WEED CONTROL;

ANIMAL; ARTICLE; BIOLOGICAL MODEL; DRUG EFFECT; DRUG RESISTANCE; EVOLUTION; GENETICS; INSECT; WEED;

ANIMALS; BIOLOGICAL EVOLUTION; DRUG RESISTANCE; INSECTS; MODELS, BIOLOGICAL; PESTICIDES; PLANT WEEDS;

HEXAPODA;

EID: 84872812560     PISSN: 1526498X     EISSN: 15264998     Source Type: Journal    
DOI: 10.1002/ps.3341     Document Type: Article

References (41)

1. Peck SL, Simulation as experiment: a philosophical reassessment for biological modeling. Trends Ecol Evol 19: 530-534 (2004).
2. Peck SL, The hermeneutics of ecological simulation. Biol Phil 23: 383-402 (2008).
3. Gillman M and Hails R, Introduction to Ecological Modelling, 1st edition. Wiley-Blackwell, Oxford, UK (1997).
4. Soetaert K and Herman PMJ, A Practical Guide to Ecological Modelling: Using R as a Simulation Platform. Springer, New York, NY (2010).
5. O'Donovan JT, Blackshaw RE, Harker KN, Clayton GW, Moyer JR, Dosdall LM, et al, Integrated approaches to managing weeds in spring-sown crops in western Canada. Crop Prot 26: 390-398 (2007).
6. Łomnicki A, Population Ecology of Individuals. Princeton University Press, Princeton, NJ (1988).
7. Shi M and Renton M, Numerical algorithms for estimation and calculation of parameters in modelling pest population dynamics and evolution of resistance. Math Biosci 233: 77-89 (2011).
8. Berger U, Piou C, Schiffers K and Grimm V, Competition among plants: concepts, individual-based modelling approaches, and a proposal for a future research strategy. Perspect Plant Ecol Evol Syst 9: 121-135 (2008).
9. Breckling B, Middelhoff U and Reuter H, Individual-based models as tools for ecological theory and application: understanding the emergence of organisational properties in ecological systems. Ecol Model 194: 102-113 (2006).
10. DeAngelis DL and Mooij WM, Individual-based modeling of ecological and evolutionary processes. Annu Rev Ecol Evol Syst 36: 147-168 (2005).
11. Grimm V and Railsback SF, Individual-based Modeling and Ecology. Princeton University Press, Princeton, NJ (2004).
12. Delye C, Menchari Y, Guillemin J, Matejicek A, Michel S, Camilleri C, et al, Status of black grass (Alopecurus myosuroides) resistance to acetyl-coenzyme A carboxylase inhibitors in France. Weed Res 47: 95-105 (2007).
13. Dinelli G, Marotti I, Bonetti A, Catizone P, Urbano J and Barnes J, Physiological and molecular bases of glyphosate resistance in Conyza bonariensis biotypes from Spain. Weed Res 48: 257-265 (2008).
14. Schlipalius DI, Cheng Q, Reilly PEB, Collins PJ and Ebert PR, Genetic linkage analysis of the lesser grain borer Rhyzopertha dominica identifies two loci that confer high-level resistance to the fumigant phosphine. Genetics 161: 773 (2002).
15. Schlipalius D, Chen W, Collins P, Nguyen T, Reilly P and Ebert P, Gene interactions constrain the course of evolution of phosphine resistance in the lesser grain borer, Rhyzopertha dominica. Heredity 100: 506-516 (2008).
16. Gardner S, Gressel J and Mangel M, A revolving dose strategy to delay the evolution of both quantitative vs major monogene resistances to pesticides and drugs. Int J Pest Manag 44: 161-180 (1998).
17. Groeters F and Tabashnik B, Roles of selection intensity, major genes, and minor genes in evolution of insecticide resistance. J Econ Entomol 93: 1580-1587 (2000).
18. Diggle AJ, Neve PB and Smith FP, Herbicides used in combination can reduce the probability of herbicide resistance in finite weed populations. Weed Res 43: 371-382 (2003).
19. Holst N, Rasmussen I and Bastiaans L, Field weed population dynamics: a review of model approaches and applications. Weed Res 47: 1-14 (2007).
20. Neve P, Diggle A, Smith F and Powles S, Simulating evolution of glyphosate resistance in Lolium rigidum I: population biology of a rare resistance trait. Weed Res 43: 404-417 (2003).
21. Grimm V, Revilla E, Berger U, Jeltsch F, Mooij WM, Railsback SF, et al, Pattern-oriented modeling of agent-based complex systems: lessons from ecology. Science 310: 987 (2005).
22. Grimm V, Ten years of individual-based modelling in ecology: what have we learned and what could we learn in the future? Ecol Model 115: 129-148 (1999).
23. Grimm V, Berger U, Bastiansen F, Eliassen S, Ginot V, Giske J, et al, A standard protocol for describing individual-based and agent-based models. Ecol Model 198: 115-126 (2006).
24. Renton M, Diggle A, Manalil S and Powles S, Does cutting herbicide rates threaten the sustainability of weed management in cropping systems? J Theor Biol 283: 14-27 (2011).
25. Renton M, The weeds fight back: individual-based simulation of evolution of polygenic resistance to herbicides, in 18th World IMACS Congress and MODSIM09 International Congress on Modelling and Simulation, ed. by Anderssen RS, Braddock RD and Newham LTH. MSSANZ and IMACS, Cairns, Australia, pp. 574-580 (2009).
26. Gaba S, Cabaret J, Ginot V and Silvestre A, The early drug selection of nematodes to anthelmintics: stochastic transmission and population in refuge. Parasitology 133: 345-356 (2006).
27. Gaba S, Cabaret J, Sauvé C, Cortet J and Silvestre A, Experimental and modeling approaches to evaluate different aspects of the efficacy of targeted selective treatment of anthelmintics against sheep parasite nematodes. Vet Parasitol 171: 254-262 (2010).
28. Storer NP, A spatially explicit model simulating western corn rootworm (Coleoptera: Chrysomelidae) adaptation to insect-resistant maize. J Econ Entomol 96: 1530-1547 (2003).
29. Storer NP, Peck SL, Gould F, Van Duyn JW and Kennedy GG, Spatial processes in the evolution of resistance in Helicoverpa zea (Lepidoptera: Noctuidae) to Bt transgenic corn and cotton in a mixed agroecosystem: a biology-rich stochastic simulation model. J Econ Entomol 96: 156-172 (2003).
30. Storer NP, Peck SL, Gould F, Van Duyn JW and Kennedy GG, Sensitivity analysis of a spatially-explicit stochastic simulation model of the evolution of resistance in Helicoverpa zea (Lepidoptera: Noctuidae) to Bt transgenic corn and cotton. J Econ Entomol 96: 173-187 (2003).
31. Sisterson MS, Antilla L, Carrière Y, Ellers-Kirk C and Tabashnik BE, Effects of insect population size on evolution of resistance to transgenic crops. J Econ Entomol 97: 1413-1424 (2004).
32. Cornell SJ, Isham VS, Smith G and Grenfell BT, Spatial parasite transmission, drug resistance, and the spread of rare genes. Proc Natl Acad Sci 100: 7401-7405 (2003).
33. Murphy J, Walshe R and Devocelle M, High-Performance Computing for Modelling Bacterial Communities. [Online]. Available: http://ercim-news.ercim.eu/content/view/402/641/[16 December 2011].
34. Cook SM, Khan ZR and Pickett JA, The use of push-pull strategies in integrated pest management. Annu Rev Entomol 52: 375-400 (2007).
35. Gu W, Killeen GF, Mbogo CM, Regens JL, Githure JI and Beier JC, An individual-based model of Plasmodium falciparum malaria transmission on the coast of Kenya. Trans R Soc Trop Med Hyg 97: 43-50 (2003).
36. Gu W and Novak RJ, Habitat-based modeling of impacts of mosquito larval interventions on entomological inoculation rates, incidence, and prevalence of malaria. Am J Trop Med Hyg 73: 546-552 (2005).
37. Weis AE and Hochberg ME, The diverse effects of intraspecific competition on the selective advantage to resistance: a model and its predictions. Am Nat 156: 276-292 (2000).
38. Jaffe K, Issa S, Daniels E and Haile D, Dynamics of the emergence of genetic resistance to biocides among asexual and sexual organisms. J Theor Biol 188: 289-299 (1997).
39. Renton M, Diggle A and Powles S, Low herbicide rates can lead to faster development of herbicide resistance. Proc 16th Australian Weeds Conference, Cairns, Queensland, Australia, pp. 215-217 (2008).
40. Shi M, Renton M and Collins P, Mortality estimation for individual-based simulations of phosphine resistance in lesser grain borer (Rhyzopertha dominica), in Chan F, Marinova D and Anderssen RS. (eds) MODSIM2011, 19th International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, December 2011, pp. 352-358, ISBN: 978-0-9872143-1-7. http://www.mssanz.org.au/modsim2011/A3/shi.pdf (2011).
41. Shi M, Renton M, Ridsdill-Smith J and Collins P, Constructing a new individual-based model of phosphine resistance in lesser grain borer (Rhyzopertha dominica): do we need to include two loci rather than one? J Pest Sci DOI: 10.1007/s10340-012-0421-6 (2012).