Crop Rotation Strategies for the Management of herbicide-resistant Giant Ragweed
Jared Goplen
29 April 2013
Throughout the world, agricultural weeds have historically been one of the most widespread and problematic factors influencing agriculture. In the United States alone, weeds annually cause a 12% overall reduction in yield, equating to approximately $33 billion in lost crop production(Pimentel et al. 2005). Weeds increase the cost of production through reduced crop yield and quality, the increased necessity of tillage, and require theadded expense of herbicideswhich cost an additional $8 billion annually(Pimentel et al., 2005; USDA ERS, 2012). In addition to the current cost of weeds, the development of herbicide resistance adds additional economic and ecological concern. Currently, there are 400 biotypes within 217 species of weeds known to have herbicide resistance worldwide (Heap, 2013).In the Midwest alone, glyphosate resistant biotypes of common waterhemp, horseweed, kochia, common ragweed and giant ragweed have been identified and are becoming problematic (Heap, 2013). Several of these species, including giant ragweed (Ambrosia trifida), have resistance to multiple herbicides.Weeds with multiple resistances reduce the efficacy of existing and developing herbicide-resistant crop technologies, limit options for weed control, and decrease profitability.
The use of weed control strategies that rely on weed emergence patterns and the seed-bank represent ideal targets for integrated weed control. By using crop rotations that promote weed seed-bank depletion via seed decay and predation, there is large potential to effectively manage herbicide resistant weeds over the long term. Seed predation has been shown to remove as much as 88% of giant ragweed seed over the course of one year in no-tillage corn (Harrison et al. 2003). Higher levels of seed predation have also been shown to occur in small grain and alfalfa, since the rate of seed predation tends to increase as the crop canopy develops (Westerman et al. 2005; Hartzler et al. 2007). Crop rotations that vary in patterns of resource competition, soil disturbance and mechanical damage also create environments hostile to any particular weed species, including those with herbicide resistance (Liebman and Dyck, 1993).
Incorporating alfalfa into crop rotations not only limits soil erosion, but alsoreduces the development and persistence of herbicide-resistant weed populations through frequent harvests, whichlimit seed production of annual weeds adapted to corn-soybean systems(Olmstead & Brummer, 2008). Wheat, on the other hand, breaks the cycle of adapted weeds since it is established earlier than corn or soybean and is planted at higher densities in narrow rows, giving it a competitive advantage over giant ragweed seedlings (Buhler, 2002). Herbicides with alternative modes of action that are used in wheat alsocan be used to diversify weed control and control resistant weeds. Wheat is harvested earlier than corn or soybean, which providesmany chemical or mechanical options for post-harvest weed control. Additionally, both wheat and alfalfa provide a favorable habitat for a variety of insects, rodents, and fungi that prey on weed seeds within the soil (Meiss et al. 2010a; Meiss et al. 2010b; Kaufman, and Kaufman, 1990; Hartzler et al. 2007).
Accurately predicting seedling emergence using emergence models allows growers to optimize cultivation schedules, planting dates, and herbicide applications to target weeds when they are most vulnerable, further enhancing weed control (Menalled & Schonbeck, 2011).Several current giant ragweed emergence models are available. However, there is little information on how different crops and rotations influence giant ragweed emergence. Different crops influence the soil environment differently, specifically in the amount of light reaching the surface, soil temperature, and soil moisture, which all can influence seedling emergence (Liebman and Dyck, 1993). Analyzing these factors in respect to existing giant ragweed emergence models will allow the verification of previous models in addition to providing a new model specifically designed for giant ragweed emergence in specific crops and rotations.
Our research includesa variety of crop rotations common to the Midwest, which incorporate corn, soybean, wheat, and alfalfa. The depletion of giant ragweed seed in the seed-bank will be monitored to determine how various crop rotations differentially affect seed-bank depletion. Additionally, emergence will be monitored in each crop rotation over the course of the growing season to confirm applicability of previous emergence models as well as to develop a new model focusing on giant ragweed emergence in alternative crops. Understanding the rotation effects on the weed seed bank and emergence patterns in addition to developing reliable weed emergence models will provide growers with both proactive and reactive options to manage herbicide-resistant weeds.
The increasing prevalence of herbicide-resistant weeds hasresulted in the need fornew weed control technologies, including those which are nonchemical (Walsh et al, 2012).However, many new weed control technologies require an increased understanding of basic weed biology and ecology (Wyse, 1992). An additional study involves monitoring the seed-rain of giant ragweed in a field setting over the course of the fall season to gain an understanding of basic giant ragweed biology. This research used seed collection traps to monitor the seed rain of giant ragweed at weekly intervals. Preliminary results show that giant ragweed seed tends to remain on the plant well into the fall season, with 78% of the potentially viable seed remaining on the plant through the month of October. Determining when giant ragweed drops seed provides insight into what types of alternative weed management practices might be effective, including those relying on capturing weed seed during crop harvest to prevent weeds like giant ragweed from replenishing the seed-bank.
References
Buhler, D. D. (2002). 50th Anniversary—Invited Article: Challenges and opportunities for integrated weed management. Weed Science, 50(3), 273–280.
Harrison, S. K., Regnier, E. E., & Schmoll, J. T. (2003). Postdispersal predation of giant ragweed (Ambrosia trifida) seed in no-tillage corn. Weed Science, 51(6), 955–964.
Hartzler, B., Liebman, M., & Westerman, P. (2007). Weed seed predation in agricultural fields. Iowa State University Extension.
Heap, I. 2013. International Survey of Herbicide-Resistant Weeds. Accessed April 19, 2013
Kaufman, D. W., & Kaufman, G. A. (1990). Small Mammals of Wheat Fields and Fallow Wheat Fields in North-Central Kansas. Transactions of the Kansas Academy of Science (1903-), 93(1/2), 28–37.
Liebman, M., & Dyck, E. (1993). Crop Rotation and Intercropping Strategies for Weed Management. Ecological Applications, 3(1), 92–122.
Meiss, H., Le Lagadec, L., Munier-Jolain, N., Waldhardt, R., & Petit, S. (2010). Weed seed predation increases with vegetation cover in perennial forage crops. Agriculture, Ecosystems & Environment, 138(1–2), 10–16.
Meiss, H., Médiène, S., Waldhardt, R., Caneill, J., & Munier-Jolain, N. (2010). Contrasting weed species composition in perennial alfalfas and six annual crops: implications for integrated weed management. Agronomy for Sustainable Development, 30(3), 657–666.
Menalled, F., Schonbeck, M. (2011). Manage the weed seed bank—minimize “deposits” and maximize “withdrawals”. Extension. Available at:
Olmstead, J., & Brummer, E. C. (2008). Benefits and Barriers to Perennial Forage Crops in Iowa Corn and Soybean Rotations. Renewable Agriculture and Food Systems, 23(02), 97–107.
Pimentel, D., Zuniga, R., & Morrison, D. (2005). Update on the environmental and economic costs associated with alien-invasive species in the United States. Ecological Economics, 52(3), 273–288.
USDA Economic Research Service (2012). (April 19, 2013)
Walsh, M. J., Harrington, R. B., Powles, S. B. (2012). Harrington Seed Destructor: A New Nonchemical Weed Control Tool for Global Grain Crops. Crop Science, 52(3), 1343–1347.
Westerman, P. R., Liebman, M., Menalled, F. D., Heggenstaller, A. H., Hartzler, R. G., & Dixon, P. M. (2005). Are many little hammers effective? Velvetleaf (Abutilon theophrasti) population dynamics in two- and four-year crop rotation systems. Weed Science, 53(3), 382–392.
Wyse, D. L. (1992). Future of Weed Science Research. Weed Technology, 6(1), 162–165.