THIRD WORLD NETWORK BIOSAFETY INFORMATION SERVICE
Dear Friends and Colleagues
Herbicide-resistant weeds increase weed management costs for GE cotton farmers
Genetically engineered herbicide-resistant crops were introduced in the United States in 1996. In 2015, 10% of the U.S. cotton area was planted with herbicide resistant cotton, and 79% of the cotton area was planted with stacked gene varieties that included herbicide-resistant traits. Growers rapidly adopted glyphosate-resistant varieties because the technology initially provided a cost effective system for managing weeds.
However, increased reliance on glyphosate for weed control and a decline in the use of other weed management practices have contributed to the evolution of herbicide-resistant weed populations. Glyphosate-resistant weeds increase weed control and other production costs. In Georgia (USA), for instance, cotton growers spend US$100 million annually to manage them.
A study of upland U.S. cotton producers analyzes the before and after weed management costs following the emergence of weed resistance on their farms, and determines the factors contributing to changes in such costs. Post-resistance weed management costs for surveyed cotton farmers ranged between $25.37 and $53.19 million, depending on the types of adopted practices. The average costs of managing weeds increased by $98 ha−1following the establishment of herbicide-resistant weeds.
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“RESISTANCE IS FUTILE”: ESTIMATING THE COSTS OF MANAGING HERBICIDE RESISTANCE AS A FIRST-ORDER MARKOV PROCESS AND THE CASE OF U.S. UPLAND COTTON PRODUCERS
Lambert, D. M., Larson, J. A., Roberts, R. K., English, B. C., Zhou, X., Falconer, L. L., … & Reeves, J. M. (2017)
Agricultural Economics
DOI: 10.1111/agec.12341
http://onlinelibrary.wiley.com/doi/10.1111/agec.12341/full
Abstract
A 2012 survey of upland U.S. cotton producers was analyzed to determine the factors contributing to changes in weed management costs (WMCs) after the identification of herbicide-resistant weeds. An ordered probit regression estimated changes in WMC as a first-order Markov process. The most important determinants of post-resistance cost increases were initial WMCs, adoption of labor-intensive remedial practices, and wick application of herbicides. Cultivation and mechanical/chemical-intensive practices did not increase WMCs. Post-resistance changes in WMC ranged between $85 and $138 ha−1, depending on the practices adopted. WMCs increased by $88 ha−1 when cost-neutral practices were adopted. The in-sample aggregate costs of managing herbicide resistance ranged between $25 and $53 million, depending on the types of adopted practices.
Conclusions
Cotton producers continue to experiment with a variety of practices to manage herbicide-resistant weeds. This study used a survey of upland U.S. cotton producers who identified herbicide-resistant weeds on their farm and reported changes in WMCs pre- and post-resistance. The most important factors determining transitions to higher cost states were WMCs before herbicide resistance, the labor-intensive practice of manual weeding, and wick application treatments. Other chemical/mechanical and cultivation-intensive practices do not appear to increase costs. Cotton farmers with low initial WMCs were less likely to experience higher post-resistance WMCs. When cost-neutral technologies were adopted, and when initial WMCs were low, the highest possible cost state was realized more slowly. Post-resistance WMCs for surveyed cotton farmers ranged between $25.37 and $53.19 million. Average costs of managing weeds increased by $98 ha−1following the establishment of herbicide-resistant weeds. Post-resistance changes in WMC ranged between $85 and $138 ha−1, depending on the combination of adopted practices. WMCs increased by $88 ha−1when cost-neutral practices were adopted. These estimates are within the range of estimates reported in recent research analyzing changes in WMCs following the emergence of herbicide-resistant weeds. The findings provide a framework for continued investigation of the dynamics of herbicide-resistant weed population expansion, farmer adaptations, and management costs. The efficacy of remedial practices will vary geographically, depending on the degree to which herbicide-resistant genes have established themselves in weed populations but also management costs.
There are caveats to this study. The survey design targeted producers in regions most likely impacted by weed resistance, and the number of respondents reporting before- and after resistance WMCs was relatively small. Inference to a broader set of row-crop producers remains challenging. A productive avenue of research could explore how local farmer information networks affect containment of herbicide-resistant weeds and potentially moderate the risk of incurring higher WMCs. Indeed, research by Heal et al. (2004) suggests that policies oriented toward promoting crop diversity through coordinated planting decisions among producers could moderate the transmission risks of pathogenic plants. Livingston et al. (2015) found that the economic gains in managing weed resistance are greater for individual producers when neighbors concomitantly manage herbicide resistance. Producers could potentially manage area-wide herbicide resistance by coordinating the timing, placement, and use of herbicide-resistant cultivars, but also establishing protocol for ensuring that equipment is weed-free before use elsewhere. The strategies producers use to manage the spatial variability of weed resistance on their operations could supplement this line of research, potentially contributing to the coordination of location-based strategies to manage the spread of herbicide-resistant weeds. Finally, this analysis only considered costs. Future analyses could focus more explicitly on changes in profitability if reliable before- and after resistance yield records and production costs were collected. Expanding the analysis to include other crops might increase respondent participation and provide additional variability important for making broader generalizations across farms, regions, and technologies adopted to minimize the cost impact of herbicide-resistant weeds on production agriculture.