Progress 03/15/12 to 03/14/16
Outputs
Target Audience:Our target audience for the work completed in this project includes farmers, custom retail applicators, industry representatives and other scientists. During the life of this project, we reached out to and shared information with all of these stakeholders. We reached farmers and custom retail applicators through small group winter meetings during model parameterization, and shared progress updates with them while learning about their interest in the project. The publications and scientific presentations from this project reached industry representatives and other scientists at annual professional society meetings (e.g. Weed Science Society of America). Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?We have trained one Ph.D. student, one postdoctoral research associate, and several undergraduate research assistants over the life of this project. How have the results been disseminated to communities of interest?We havereached out directly to growers and custom retail applicators to spread management insights gained from this project through small-group winter meetings (3) and large-scale events such as University of Illinois' Agronomy Day (2)and Pest Management Conference (2). The management insights gained from the epidemiological analysis have also been incorporated into the integrated weed management extension publications of the University of Illinois Weed Science Extension Team. We have disseminated technical results to academic, industry and government scientists through presentations at professional society meetings, including the International Weed Science Society (1), North Central Weed Science Society (2), and Weed Science Society of America (3). We have published the information from these presentations as abstracts. Finally, we have published one journal article, and have three more in preparation, communicating the research findings of this project. What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
The proposed work in this project has proceeded according to plan. Our greenhouse study of fitness costs associated with maintenance of herbicide resistance alleles over six-generations in Amaranthus tuberculatus was completed in summer of 2015. The genotypes that competed in each generation of the study represent five accessions of A. tuberculatus seed with different alleles present in a common genetic background. Differential success among the different genotypes resulted in varying proportions of mature seed harvested at the end of each generation. After the sixth generation was completed, we assayed the final proportion of resistance alleles present in the population of mature seed, and calculated fitness penalties for each trait based on these data. We discovered that fitness costs of resistance to PSII inhibitors, ALS inhibitors, PPO inhibitors and HPPD inhibitors were all low. Two types of resistance to glyphosate, affecting the shikimate pathway, were identified in our populations: 1) increased copy number of EPSPS, and 2) a mutation to the EPSPS gene. The former resistance mechanism showed a strong fitness cost, whereas the latter mechanism did not show a fitness cost. These results indicate that fitness costs for herbicide resistance alleles may be less common than previously thought, suggesting that rotation herbicide modes of action over time may not be an effective way of combatting resistance, since standing frequencies of resistant alleles in the population should remain relatively constant when fitness costs are low. Data mining of epidemiological data for glyphosate resistance in A. tuberculatus is complete. The dataframe contains proportion of seeds expressing glyphosate resistance in A. tuberculatus for 141 farms, landscape characteristics for those farms, and 8 years of management history. We have found strong links between herbicide management characteristics of farming operations and resistance profiles of waterhemp populations on those farms, but did not see strong signals from landscape features or weed community composition. Classification and regression tree (CART) analysis indicated that 44% of the variation in A. tuberculatus glyphosate resistance could be explained by a CART model featuring diversity of herbicide modes of action and glyphosate application rate. Those farms which used an average of more than three herbicide MOA during the study period (2004-2011) had lower proportions of glyphosate resistant seeds (Presist= 0.016), compared to those with less than 3 MOA over that period (Presist= 0.089). Farms which used between 1.1 and 1.6 times the 0.75 kg a.i. ha-1 rate of glyphosate had the greatest proportion of resistant seeds (Presist= 0.24). Farms using very low or very high rates of glyphosate tended to have lower resistance levels (Presist= 0.04 and 0.09, respectively). We also found no signal of spatial contagion in the rate of glyphosate resistance evolution, compared to a strong management signal: what farmers did on their own farms mattered, in terms of resistance evolution. These results support long-standing recommendations from the UIUC Weed Science Extension team to use multiple modes of herbicide action as part of an integrated weed management strategy. We have finished incorporating management risk factors for herbicide resistance evolution into cellular automata model of glyphosate resistance evolution and spread in A. tuberculatus. The model simulates the spatial demography and population genetics of this weed from field to regional scales, and enables the user to aggregate weed management decisions at different spatial scales as well, from field to region. Model output indicates that aggregating recommended management practices (such as diverse mixtures of herbicide representing multiple modes of action) at larger spatial scales both increases the time needed for resistance traits to spread through an area and results in lower population densities of weeds over time. The model also shows that this pest management problem has elements of the tragedy of the commons: when weed management is not spatially coordinated, growers that do not use recommended practices (e.g. just use the same herbicide, by itself, year after year) benefit from weed management diversity among their neighbors while contributing resistance alleles to the surrounding landscape.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2016
Citation:
Evans, J. A., P. J. Tranel, A. G. Hager, B. R. Schutte, C. Wu, L. Chatham and A. S Davis. 2016. Managing the evolution of herbicide resistance. Pest Management Science. 72: 74-80.
- Type:
Journal Articles
Status:
Other
Year Published:
2016
Citation:
Evans, J. A., P. J. Tranel, A. G. Hager, C. Wu, and A. S Davis. in prep. Aggregating management decisions at larger spatial scales slows evolution of herbicide resistance. Pest Management Science.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2016
Citation:
Evans J, A. S. Davis, P. J. Tranel, A. Hager. 2016. Coordinating weed management decisions across landscapes: impacts on the spread of herbicide resistance traits. Weed Science Society of America Abstracts. 465.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2016
Citation:
Wu, C., P. J. Tranel and A. S. Davis. 2016. Ecological fitness of herbicide resistance traits in waterhemp as determined by a multi-generational greenhouse study. Weed Science Society of America Abstracts. 425.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2015
Citation:
Tranel, P., C. Wu and A. S. Davis. 2015. New empirical data for modeling evolution of herbicide resistance. International Weed Science Society Abstracts.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2015
Citation:
Wu, C, P. Tranel and A. S. Davis. 2015. Evolution of glyphosate resistance: tangling of EPSPS amplification, mutation and translocation based Non-targetsite Resistance? North Central Weed Science Society Abstracts. 60.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2015
Citation:
Wu, C, P. Tranel and A. S. Davis. 2015. Fitness costs of herbicide resistance traits in waterhemp. North Central Weed Science Society Abstracts. 141.
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Progress 03/15/14 to 03/14/15
Outputs
Target Audience: Because the evolution of herbicide resistance in weeds is a process that includes many actors, our target audience for this project includes farmers in the northern U.S. corn belt, custom retail agrichemical applicators, agrichemical and seed industry representatives, other weed scientists and policy makers. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided? We have trained one Ph.D. Crop Science student at the University of Illinois, and one postdoctoral research associate.We have also trained over 200 agricultural professionals in the very practical herbicide resistance management results from this project at the January 2015 UIUC ExtensionCrop Management Conference. How have the results been disseminated to communities of interest? Results have been disseminated to five main audiences for this work: growers, retail applicators, industry representatives, other scientists and policy makers. We have made presentations to the first two groups through UIUC-hosted extension meetings (four in January 2014, plus individual presentations in May 2014, August 2014 and one in January 2015) as well as through guest lectures in 'train the trainer' short courses. We have also made several presentations at regional and national weed science meetings to industry reps and other scientists, and through individual meetings with both of these groups as well. Finally, we have shared results slides from our work with policy makers in support of their public speaking on how U.S. agriculture can move forward in the face of herbicide resistance. What do you plan to do during the next reporting period to accomplish the goals? We will continue the greenhouse evaluation of fitness costs of herbicide resistance evolution and the modeling work looking at potential benefits of spatial aggregation of management decisions. We will continue to write up and submit results of the work for publication in scientific journals. Finally, we will continue our outreach efforts to educate farmers, retail applicators, industry representatives, other scientists and policy makers on the practical tips that have come from this project for managing and hindering the evolution of herbicide resistance.
Impacts
What was accomplished under these goals?
The proposed work in this project is proceeding according to plan. Our greenhouse study of fitness costs associated with maintenance of herbicide resistance alleles in Amaranthus tuberculatus is nearing completion of the fifth of six generations of competitive grow-outs. The genotypes competing in each generation of the study represent five of A. tuberculatus seed with different alleles present in a common genetic background. Differential success among the different genotypes will result in arying proportions of mature seed harvested at the end of each generation. After the sixth generation, we will assay the final proportions of resistance alleles present in the population of mature seed, and calculate fitness penalties for each trait based on these data. Data mining of epidemiological data for glyphosate resistance in A. tuberculatus is complete. The dataframe contains proportion of seeds expressing glyphosate resistance in A. tuberculatus for 141 farms, landscape characteristics for those farms, and 8 years of management history. We have found strong links between herbicide management characteristics of farming operations and resistance profiles of waterhemp populations on those farms, but did not see strong signals from landscape features or weed community composition. Classification and regression tree (CART) analysis indicated that 44% of the variation in A. tuberculatus glyphosate resistance could be explained by a CART model featuring diversity of herbicide modes of action and glyphosate application rate. Those farms which used an average of more than three herbicide MOA during the study period (2004-2011) had lower proportions of glyphosate resistant seeds (Presist= 0.016), compared to those with less than 3 MOA over that period (Presist= 0.089). Farms which used between 1.1 and 1.6 times the 0.75 kg a.i. ha-1 rate of glyphosate had the greatest proportion of resistant seeds (Presist= 0.24). Farms using very low or very high rates of glyphosate tended to have lower resistance levels (Presist= 0.04 and 0.09, respectively). We also found no signal of spatial contagion in the rate of glyphosate resistance evolution, compared to a strong management signal: what farmers did on their own farms mattered, in terms of resistance evolution. These results support long-standing recommendations from the UIUC Weed Science Extension team to use multiple modes of herbicide action as part of an integrated weed management strategy. We have begun to incorporate management risk factors for herbicide resistance evolution into a landscape-scale cellular automata model of glyphosate resistance evolution and spread in A. tuberculatus.
Publications
- Type:
Journal Articles
Status:
Awaiting Publication
Year Published:
2015
Citation:
Evans, J. A., P. J. Tranel, A. G. Hager, B. R. Schutte, C. Wu, L. Chatham and A. S Davis. In review. Complex herbicide mixtures reduce risks of herbicide resistance in an important agricultural weed. Pest Management Science.
- Type:
Conference Papers and Presentations
Status:
Accepted
Year Published:
2015
Citation:
Wu, C., P. Tranel and A. S. Davis. 2015. Ecological fitnesses of multiple herbicide-resistance traits in the absence of herbicide selection determined from a multi-generation greenhouse study of waterhemp (Amaranthus tuberculatus). Weed Science Society of America Abstracts. 55: 79.
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Progress 03/15/13 to 03/14/14
Outputs
Target Audience: Our group made presentationsat the North Central Weed Science Society (poster) and Weed Science Society of America (oral) annual meetings. We also gave presentations to two grower groups on the aims of this project. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided? Thus far, we have trained one PhD student, one postdoctoral research associate and two undergraduate research assistants. How have the results been disseminated to communities of interest? We have given scientific talks at professional society conferences (North Central Weed Science Society, Weed Science Society of America) and to grower groups (UIUC Agronomy Day, private workshop with growers involved in project). As the project is still in its early stages, these talks have been about the goals and progress of the project. What do you plan to do during the next reporting period to accomplish the goals? We will continue our greenhouse study, completing the fourth and fifth generations. We will use the risk factors identified in the data mining portion of the project to create a landscape-scale cellular automata model of the evolution and spread of glyphosate resistance in common waterhemp, with respect to various coordinated management strategies.
Impacts
What was accomplished under these goals?
The proposed work in this project is proceeding according to plan. Our greenhouse study of fitness costs associated with maintenance of herbicide resistance alleles in Amaranthus tuberculatus is nearing completion of the third of six generations of competitive grow-outs. The genotypes competing in each generation of the study represent five of A. tuberculatus seed with different alleles present in a common genetic background. Differential success among the different genotypes will result in arying proportions of mature seed harvested at the end of each generation. After the sixth generation, we will assay the final proportions of resistance alleles present in the population of mature seed, and calculate fitness penalties for each trait based on these data. Data mining of epidemiological data for glyphosate resistance in A. tuberculatus is complete. The dataframe contains proportion of seeds expressing glyphosate resistance in A. tuberculatus for 141 farms, landscape characteristics for those farms, and 8 years of management history. We have found strong links between herbicide management characteristics of farming operations and resistance profiles of waterhemp populations on those farms, but did not see strong signals from landscape features or weed community composition. Classification and regression tree (CART) analysis indicated that 44% of the variation in A. tuberculatus glyphosate resistance could be explained by a CART model featuring diversity of herbicide modes of action and glyphosate application rate. Those farms which used an average of more than three herbicide MOA during the study period (2004-2011) had lower proportions of glyphosate resistant seeds (Presist= 0.016), compared to those with less than 3 MOA over that period (Presist= 0.089). Farms which used between 1.1 and 1.6 times the 0.75 kg a.i. ha-1 rate of glyphosate had the greatest proportion of resistant seeds (Presist= 0.24). Farms using very low or very high rates of glyphosate tended to have lower resistance levels (Presist= 0.04 and 0.09, respectively). These results support long-standing recommendations from the UIUC Weed Science Extension team to use multiple modes of herbicide action as part of an integrated weed management strategy. Our next step will be to incorporate management risk factors for herbicide resistance evolution into a landscape-scale cellular automata model of glyphosate resistance evolution and spread in A. tuberculatus.
Publications
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Progress 03/15/12 to 03/14/13
Outputs
OUTPUTS: As this project is in its early stages, our outputs have focused primarily on informing stakeholders of the structure and goals of the project, with additional emphasis on education of participants, aimed at improving data collection. In April 2012, we hosted an outreach meeting for the farmers involved in this study of landscape and management factors affecting the evolution and spread of herbicide resistance in Amaranthus tuberculatus. During the meeting, we described the rationale and goals for the project. We also used this time to collect 10-year management histories from the farmers for the fields being surveyed in the project. Making sure the management histories are complete is an important factor in the success of the data analysis effort, therefore we worked with individual growers on an ongoing basis to fill knowledge gaps. Also in 2012, we met with interested industry groups to educate them about the aims of the project. PARTICIPANTS: We have enlisted the participation of several dozen commercial farmers and a custom retail agrichemical applicator in central Illinois, securing permission to sample common waterhemp seeds from their fields, and obtaining management histories about their farming operations. As part of the project, we are training a Ph.D. student in Weed Science, and mentoring a postdoctoral research associate in spatial population dynamics modeling. TARGET AUDIENCES: Because the evolution of herbicide resistance in weeds is a process that includes many actors, our target audience for this project includes farmers in the northern U.S. corn belt, custom retail agrichemical applicators, agrichemical and seed industry representatives, and other weed scientists. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.
Impacts
We are still in the process of performing experiments and collecting data. There are no outcomes or impacts to report yet.
Publications
- No publications reported this period
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