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Multispecies resistance and integrated management: a bioeconomic model for integrated management of rigid ryegrass (Lolium rigidum) and wild radish (Raphanus raphanistrum)

Published online by Cambridge University Press:  20 January 2017

Marta Monjardino ,
David J. Pannell  and
Stephen B. Powles
David J. Pannell
Affiliation:
Agricultural and Resource Economics Group, University of Western Australia, Crawley, WA 6009, Australia
Stephen B. Powles
Affiliation:
Western Australian Herbicide Resistance Initiative, University of Western Australia, Crawley, WA 6009, Australia
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Abstract

Rigid ryegrass and wild radish dominate and coexist throughout southern Australian dryland cropping regions. Widespread herbicide resistance in these species has led to adoption of diverse and complex integrated weed management practices, which require evaluation of their impact on farming systems. Therefore, a multispecies version of the bioeconomic model resistance and integrated management (RIM) has been developed to compare long-term economic and weed population outcomes of various integrated management scenarios. We have extended the original single-species ryegrass RIM model to include wild radish biology and additional weed management practices used to control this species. The multispecies model can be used to evaluate weed management scenarios for coexisting herbicide-resistant species by investigating the implications of different crop–pasture rotational sequences and of varying herbicide availability. Multispecies RIM shows that economic differences between the scenarios are not due to differences in weed densities but to differences in total weed control costs.

Keywords

Rigid ryegrass, Lolium rigidum Gaud. LOLRIwild radish, Raphanus raphanistrum L. RAPRAModelingweed–crop competitionherbicide resistanceintegrated weed management
Type
Weed Management
Information
Weed Science , Volume 51 , Issue 5 , October 2003 , pp. 798 - 809
Copyright
Copyright © Weed Science Society of America 

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References

Literature Cited

Alex, J. F. 1970. Competition of Sponaria vaccaria and Sinapis arvensis in wheat. Can. J. Plant Sci 50:379–388.Google Scholar
Ball, D. A. and Shaffer, M. J. 1993. Simulating resource competition in multispecies agricultural plant communities. Weed Res 33:299–310.CrossRefGoogle Scholar
Bennett, A. L. and Pannell, D. J. 1998. Economic evaluation of a weed-activated sprayer for herbicide application to patchy weed populations. Aust. J. Agric. Res. Econ 42:389–408.Google Scholar
Blackshaw, R. P. 1986. Resolving economic decisions for the simultaneous control of two pests, diseases or weeds. Crop Prot 5:93–99.Google Scholar
Cheam, A. H. 1986. Seed production and seed dormancy in wild radish (Raphanus raphanistrum L.) and some possibilities for improving control. Weed Res 26:405–413.Google Scholar
Cheam, A., Hashem, A., Bowran, D., and Lee, A. 1998. Rigid ryegrass survival and seed production in relation to time of emergence and various control options in a wheat crop. Proceedings of the 1998 Weed Crop Updates. Perth, WA: Agriculture Western Australia. Pp. 59–60.Google Scholar
Combellack, J. H. and Friesen, G. 1992. Summary of outcomes of recommendations from the First International Weed Control Congress. Weed Technol 6:1043–1058.Google Scholar
De Wit, C. T. 1960. On competition. Versl. Landbouwkd. Onderz. Rijkslandproefstn 66:8–82.Google Scholar
Diggle, A. J., Gill, G. S., and Holmes, J. E. 1994. Delaying the Development of Herbicide Resistant Rigid Ryegrass by Using Alternative Weed Control Strategies. Perth: Agriculture Western Australia Rep. 14/93.Google Scholar
Firbank, L. G. and Watkinson, A. R. 1985. On the analysis of competition within two-species mixtures of plants. J. Appl. Ecol 22:503–517.Google Scholar
Gill, G. S. and Holmes, J. E. 1997. Efficacy of cultural control methods for combating herbicide-resistant Lolium rigidum . Pestic. Sci 51:352–358.Google Scholar
Gorddard, R. J., Pannell, D. J., and Hertzler, G. L. 1995. An optimal control model of integrated weed management under herbicide resistance. Aust. J. Agric. Econ 39:71–87.Google Scholar
Gorddard, R. J., Pannell, D. J., and Hertzler, G. 1996. Economic evaluation of strategies for management of herbicide resistance. Agric. Syst 51:281–298.Google Scholar
Haizel, K. A. and Harper, J. L. 1973. The effects of density and the timing of removal on interference between barley, white mustard and wild oats. J. Appl. Ecol 10:23–31.CrossRefGoogle Scholar
Halse, N. J. 1986. Crop management and improvement. J. Aust. Inst. Agric. Sci. 52.Google Scholar
Hamby, D. M. 1995. A comparison of sensitivity analysis techniques. Health Phys 68:195–204.Google Scholar
Hoffman, F. O. and Gardner, R. H. 1983. Evaluation of uncertainties in environmental radiological assessment models. Pages 11.1–11.55 in Till, J. E. and Meyer, H. R. eds. Radiological Assessments: A Textbook on Environmental Dose Assessment. Rep. NUREG/CR-3332. Washington, DC: US Nuclear Regulatory Commission.Google Scholar
Hume, L. 1989. Yield losses in wheat due to weed communities dominated by green foxtail [Setaria viridis (L.) BEAUV.]: a multi-species approach. Can. J. Plant Sci 69:521–529.Google Scholar
Hume, L. 1993. Development of equations for estimating yield losses caused by multispecies weed communities dominated by green foxtail [Setaria viridis (L.) BEAUV]. Can. J. Plant Sci 73:625–635.CrossRefGoogle Scholar
Kiniry, J. R., Williams, J. R., Gassman, P. W., and Debaeke, P. 1992. A general, process-orientated model for two competing plant species. Trans. ASAE 35:801–810.CrossRefGoogle Scholar
Kroh, G. C. and Stephenson, S. N. 1980. Effects of diversity and pattern on relative yields of four Michigan first year fallow field plant species. Oecologia 45:366–371.Google Scholar
Kropff, M. J. and Spitters, C. J. T. 1991. A simple model for crop loss by weed competition on basis of early observation on relative leaf area of the weeds. Weed Res 31:97–105.Google Scholar
Llewellyn, R. and Powles, S. B. 2001. High levels of herbicide-resistance in rigid ryegrass (Lolium rigidum) in the wheatbelt of Western Australia. Weed Technol 15:242–248.Google Scholar
Maxwell, B. D., Roush, M. L., and Radosevich, S. R. 1990. Predicting the evolution and dynamics of herbicide resistance in weed populations. Weed Technol 4:2–13.Google Scholar
Mortensen, D. A. and Dielman, J. A. 1998. Why weed patches persist: dynamics of edges and density. Pages 14–19 in Workshop on Precision Weed Management in Crops and Pastures, Charles Sturt University; May 5–6, 1998; Wagga Wagga, NSW, Australia. Wagga Wagga, Australia: CRC Weed Management Systems.Google Scholar
Pannell, D. J. 1990. Model of wheat yield response to application of diclofop-methyl to control annual ryegrass (Lolium rigidum). Crop Prot 9:422–428.Google Scholar
Pannell, D. J. 1995. Optimal herbicide strategies for weed control under risk aversion. Rev. Agric. Econ 17:337–350.Google Scholar
Pannell, D. J. 1997. Sensitivity analysis of normative economic models: theoretical framework and practical strategies. Agric. Econ 16:139–152.Google Scholar
Pannell, D. J. and Bennett, A. L. 1998. Economic feasibility of precision weed management: is it worth the investment?. Pages 138–150 in Workshop on Precision Weed Management in Crops and Pastures, Charles Sturt University; May 5–6, 1998; Wagga Wagga, NSW, Australia. Wagga Wagga, Australia: CRC Weed Management Systems.Google Scholar
Pannell, D. J. and Gill, G. S. 1994. Mixtures of wild oats (Avena fatua) and annual ryegrass (Lolium rigidum) in wheat: competition and optimal economic control. Crop Prot 13:371–375.Google Scholar
Pannell, D. J., Stewart, V., Bennett, A., Monjardino, M., Schmidt, C., and Powles, S. 2003. RIM: a bio-economic model for integrated weed management. Agric. Syst. In press.Google Scholar
Parker, L. and Murdoch, A. J. 1996. Mathematical modelling of multi-species weed competition in spring wheat. Pages 153–158 in 2nd International Weed Control Congress; Copenhagen, Denmark. Volume 1. Copenhagen, Denmark: Dept. of Weed Control and Pesticide Ecology.Google Scholar
Poole, M. L. and Gill, G. S. 1987. Competition between crops and weeds in Southern Australia. Weed Science Society of Victoria Symposium: Weed Control in Cropping Areas—When Is It Worthwhile? Bendigo, Vic.: Bendigo CAE. Bendigo, Australia: Weed Science Society.Google Scholar
Powles, S. B. 1997. Success from adversity: herbicide resistance can drive changes to sustainable weed management systems. Pages 1119–1125 in The 119 Brighton Crop Protection Conference—Weeds; Brighton, Great Britain. Brighton, U.K.: British Protection Council.Google Scholar
Powles, S. B., Preston, C., Bryan, I. B., and Jutsum, A. R. 1997. Herbicide resistance: impact and management. Adv. Agron 58:57–98.Google Scholar
Preston, C. 2000. Herbicide mode of action and herbicide resistance. Sindel, B. M., ed. Pages 209–226 in Australian Weed Management Systems. Melbourne: R. G. and F. J. Richardson.Google Scholar
Reeves, T. G., Code, G. R., and Piggin, C. M. 1981. Seed production and longevity, seasonal emergence and phenology of wild radish (Raphanus raphanistrum L). Aust. J. Exp. Anim. Husb 21:524–530.Google Scholar
Sattin, M., Berti, A., and Zanin, G. 1996. Crop yield loss in relation to weed time of emergence and removal analysis of the variability with mixed weed infestations. Pages 67–72 in 2nd International Weed Control Congress; Copenhagen, Denmark. Volume 1. Copenhagen, Denmark: Dept. of Weed Control and Pesticide Ecology.Google Scholar
Schmidt, C. and Pannell, D. J. 1996. Economic issues in management of herbicide-resistant weeds. Rev. Market. Agric. Econ 64/3:301–308.Google Scholar
Street, J. E., Snipes, C. E., McGuire, J. A., and Buchanan, G. A. 1985. Competition of a binary weed system with cotton (Gossypium hirsutum). Weed Sci 33:807–809.Google Scholar
Swinton, S. M., Buhler, D. D., Forcella, F., Gunsolus, J. L., and King, R. P. 1994. Estimation of crop yield loss due to interference by multiple weed species. Weed Sci 42:103–109.Google Scholar
Trenbath, B. R. and Stern, W. R. 1995. WASP—A Virtual Farm. Miscellaneous Publication 13/95. Perth, Australia: Agriculture Western Australia. 146 p.Google Scholar
Van Acker, R. C., Lutman, P. J., and Froud-Williams, R. J. 1998. Additive infestation model (AIM) analysis for the study of two-weed species interference. Weed Res 38:275–281.Google Scholar
Walsh, M. J., Duane, R. D., and Powles, S. B. 2001. High frequency of chlorsulfuron resistant wild radish (Raphanus raphanistrum L.) populations across the Western Australian wheatbelt. Weed Technol 15:199–203.Google Scholar
Wilkerson, G. G., Modena, S. A., and Coble, H. D. 1991. HERB: decision model for postemergence weed control in soybean. Agron. J 83:413–417.Google Scholar
Young, K. and Cousens, R. 1999. Factors affecting the germination and emergence of wild radish (Raphanus raphanistrum) and their effect on management options. Pages 179–182 in 12th Australian Weeds Conference; Hobart, Tasmania, Australia. Hobart, Australia: Tasmanian Weed Society.Google Scholar