Progress 09/15/07 to 09/14/11
Outputs
OUTPUTS: Activities: Data collection has been completed as described in our proposal. Specifically, we have Russian wheat aphid (RWA) density data collected over two years at two winter wheat sites and multiple barley sites (3 barley sites in 2008 and 2 barley sites in 2009). Spatiotemporal covariate matrixes (inclusive of topography, Landsat satellite imagery and weather variables) are being developed in association with spatially and temporally explicit RWA density data. Specific data collected between Sept 08 and Nov 09: 72 plots were developed in winter wheat in SE Colorado (near Lamar, CO). Half of the plots were artificially infested with RWA, while the remaining half relied upon natural infestation. Plots were sampled three times (i.e., sample dates: March 5, April 7, May 19) for RWA density. 72 plots were developed in winter wheat in NE Colorado (near Briggsdale, CO). Once again, half of the plots were artificially infested with RWA, leaving 36 plots to be naturally infested. Plots were sampled 3 times (sample dates: March 3, April 8, May 5) for RWA density. Winter wheat tillers were obtained from each plot from which yield estimates are currently being calculated. Barley fields used to obtain data for validation of the spatiotemporal RWA model in 2009 were relatively small. 30 plots of barley were developed (half of which were artificially infested) in eastern Colorado (near Akron, CO) and sampled three times each (May 18, June 15, and June 30). 30 plots in barely were developed (half of which were artificially infested) in NE Colorado (near Fort Collins, CO) and sampled three times (May 29, Jun 17, Jul 2). Barley tillers were obtained from each plot from which yield estimates are currently being calculated. With granted funds, ancillary data were obtained at each plot, during each sampling period for other pests of wheat and barley. Specifically, density data were obtained for thrips, greenbug, bird cherry oat aphid, and brown wheat mites. These data may provide insight into pest community composition effects on yield. Our modeling efforts have resulted in some exciting and positive results. These results are currently in preparation for submission or in the revision process. We expect two Russian wheat aphid centric publications plus other publications using ancillary data collected as noted. Events: Merrill, S. C. (2011) A Series of Surprises: Modelling the Pest Agroecosystem Landscape. Commonwealth Scientific and Industrial Research Organization (CSIRO) Brisbane. June 2011. Brisbane, Australia; Merrill, S. C. (2011) Revisiting our assumptions about the pest agroecosystem landscape. NCEAS (National Center for Ecological Analysis and Synthesis) Ecolunch Seminar Series. June 2011. Santa Barbara, CA. Publication in revision: Merrill, S. C., T. O. Holtzer, F. B. Peairs, and P. J. Lester (In revision) Prediction of Spatially Explicit Russian Wheat Aphid Densities in Winter Wheat Agroecosystems. Pest Management Sciences PARTICIPANTS: Dr. Scott Merrill worked extensively in the field to develop sample design, infest plots, sample plots and educate field personnel regarding project specific goals as well as integrated pest management philosophy. Dr. Frank Peairs has provided extensive oversight and direction throughout the project. Research associates Jeff Rudolph and Terri Randolph have provided help with logistics and have aided in data development (e.g., educating and directing technicians). Field technicians (Steve Rauth, Tyler Keck, Marie Stiles, Dylan Walker, Anthony Longo-Peairs and Lukas Rael) have assisted in sampling and infesting of plots, as well as data development such as counting pest abundances and measuring yields. Extension agent Bruce Bosley and entomology research associates Cynthia Walker and Mike Koch were instrumental in establishing contacts with the farming community, including contact with Todd and Cary Wickstrom, as well as John and Jeremy Stulp who provided wheat / fallow agroecosystem acreage for this study. TARGET AUDIENCES: Further work will include development of a website with links dedicated to Russian wheat aphid management suggestions. Additionally fact sheets will be distributed to educate stakeholders about this online resource. Fact sheet will be disseminated in several ways: (1) it will be added to the small grains section of the High Plains Integrated Pest Management Guide (highplainsipm.org); (2) it will be published electronically as one of Colorado State University's insect management fact sheets (http://www.ext.colostate.edu/pubs/insect/pubins.html), (3) it will be distributed at Colorado State University Wheat Field Days; and (4) it will be distributed as part of one of the Colorado Wheat Grower newsletters, which is sent to every grower of more than 25 acres of wheat. PROJECT MODIFICATIONS: We requested and received a no-cost extension to provide additional time for modeling and publication.
Impacts
Change in Knowledge: Our results show that our spatiotemporal Russian wheat aphid prediction model has strong but conditional success in predicting the density of this aphid pest solely using remotely sensed data.
Publications
- No publications reported this period
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Progress 09/15/09 to 09/14/10
Outputs
OUTPUTS: Activities: We have collected data as described in our proposal. Specifically, we have RWA density data collected over two years at two winter wheat sites and multiple barley sites (3 barley sites in 2008 and 2 barley sites in 2009). Spatiotemporal covariate matrixes (inclusive of topography, Landsat satellite imagery and weather variables) are being developed in association with spatially and temporally explicit RWA density data. Specific data collected between Sept 08 and Nov 09: 72 plots were developed in winter wheat in SE Colorado (near Lamar, CO). Half of the plots were artificially infested with RWA, while the remaining half relied upon natural infestation. Plots were sampled three times (i.e., sample dates: March 5, April 7, May 19) for RWA density. 72 plots were developed in winter wheat in NE Colorado (near Briggsdale, CO). Once again, half of the plots were artificially infested with RWA, leaving 36 plots to be naturally infested. Plots were sampled 3 times (sample dates: March 3, April 8, May 5) for RWA density. Winter wheat tillers were obtained from each plot from which yield estimates are currently being calculated. Barley fields used for to obtain data for validation of the spatiotemporal RWA model in 2009 were relatively small. 30 plots of barley were developed (half of which were artificially infested) in eastern Colorado (near Akron, CO) and sampled three times each (May 18, June 15, and June 30). 30 plots in barely were developed (half of which were artificially infested) in NE Colorado (near Fort Collins, CO) and sampled three times (May 29, Jun 17, Jul 2). Barley tillers were obtained from each plot from which yield estimates are currently being calculated. With granted funds, ancillary data were obtained at each plot, during each sampling period for other pests of wheat and barley. Specifically, density data were obtained for thrips, greenbug, bird cherry oat aphid, and brown wheat mites. These data may provide insight into pest community composition effects on yield. Modeling efforts are ongoing. Given our successful data collection efforts we expect to be able to develop quality validation prediction errors and recalibration of model parameters. However, because Landsat 7 ETM+ data sensors (used as independent data layers in the original project) have been corrupted, the original data set is being reanalyzed using Landsat 5 satellite imagery. With completion of modeling efforts to reparameterize original data using Landsat 5 imagery, we expect to be able to continue validation of modeling efforts. More specifically, we expect little change to occur with reparameterization because Landsat 7 ETM+ band 8 (the primary difference between the two satellite imagery acquisitions, and not included in Landsat 5 imagery) had a small effect size in the original modeling efforts. Events: Merrill, S. C. (2010) Understanding the link between Precision Agriculture and Landscape Ecology. NCEAS (National Center for Ecological Analysis and Synthesis) Ecolunch Seminar Series. April 2010. Santa Barbara, CA PARTICIPANTS: Dr Scott Merrill has worked extensively in the field to develop sample design, infest plots, sample plots and educate field personal regarding project specific goals as well as integrated pest management philosophy. Dr Frank Peairs has provided extensive oversight and direction throughout the project. Research associates Jeff Rudolph and Terri Randolph have provided help with logistics and have aided in data development (e.g., educating and directing technicians). Field technicians (Steve Rauth, Tyler Keck, Marie Stiles, Dylan Walker, Anthony Longo-Peairs and Lukas Rael) have assisted in sampling and infesting of plots, as well as data development such as counting pest abundances and measuring yields. Work has been completed in establishing farming collaborators for access to small grain plots. Todd and Cary Wickstrom, as well as John and Jeremy Stulp have offered wheat / fallow agroecosystem acreage for our use. Extension agent Bruce Bosley and entomology research associates Cynthia Walker and Mike Koch were instrumental in establishing contacts with the farming community, including contact with the aforementioned collaborators. TARGET AUDIENCES: Nothing significant to report during this reporting period. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.
Impacts
Modeling efforts are ongoing. Given our successful data collection efforts we expect to be able to develop quality validation prediction errors and recalibration of model parameters. Change in Knowledge: Because Landsat 7 ETM+ data sensors (used as independent data layers in the original project) have been corrupted, the original data set is being reanalyzed using Landsat 5 satellite imagery. With completion of modeling efforts to reparameterize original data using Landsat 5 imagery, we expect to be able to continue validation of modeling efforts. More specifically, we expect little change to occur with reparameterization because Landsat 7 ETM+ band 8 (the primary difference between the two satellite imagery acquisitions, and not included in Landsat 5 imagery) had a small effect size in the original modeling efforts.
Publications
- No publications reported this period
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Progress 09/15/08 to 09/14/09
Outputs
OUTPUTS: Effective integrated pest management (IPM) for Russian wheat aphid (RWA), Diuraphis noxia (Kurdjumov), a major pest of wheat and barley, requires quality spatio-temporal prediction models. Damage estimates are in the hundreds of millions of dollars since the introduction of the RWA into the United States. We have built a predictive model with the goal of explaining within-field variation in RWA population structure using weather variables, soil characteristics, topography and Landsat 7 Enhanced Thematic Mapper imagery. This model has the potential to be a key IPM tool (e.g. forecasting, placement of resistant small-grain varieties, precision pesticide application and directed scouting). Cross-validation suggests that this model will predict RWA densities during the early spring on winter wheat as or more precisely than conventional field scouting, relying entirely on remotely sensed data. However, the model has not been validated for other cereals (e.g., barley), or time periods (e.g., late spring or early summer). We completed field work designed to obtain data to validate model predictions under field conditions for high-resolution forecasting of RWA densities using winter wheat and spring barley, from the early spring to harvest (some laboratory work is ongoing). Measured aphid densities will be used to correlate RWA population densities with yield damages. Combining loss functions, temperature variables, and the spatially explicit RWA density model will generate RWA Risk Assessment Maps, which will serve to focus control efforts in areas of greatest need. Four and five site years of spatially and temporally explicit RWA density data have been collected in wheat and barley, respectively. Spatiotemporal covariate matrixes (inclusive of topography, Landsat satellite imagery and weather variables) are being developed. Plots within sites were either artificially or naturally infested and sampled 3 times per growing season. Plot yields were estimated. Wheat and barley data were gathered similarly, except the numbers of barley plots was smaller due to smaller field sizes. Density data also were obtained for thrips, greenbug, bird cherry-oat aphid, and brown wheat mite. This project will use the data collected, as described above to generate an online program, linked to the World Wide Web, designed to produce RWA density maps and Risk Assessment Maps for use by clientele. We expect to be able to develop quality validation prediction errors and recalibration of model parameters. We intend to develop a fact sheet detailing the use of the online program, including the necessary inputs and information on how to understand resulting Russian wheat aphid density surfaces and Risk Assessment Maps. This fact sheet will be disseminated through multiple outlets in order to reach as many wheat growers as possible. PARTICIPANTS: Nothing significant to report during this reporting period. TARGET AUDIENCES: Nothing significant to report during this reporting period. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.
Impacts
RWA Risk Assessment Maps will allow growers to prioritize control efforts on the parts of their operation at greatest risk of economically significant losses to RWA, allowing the most efficient use of scarce production inputs.
Publications
- No publications reported this period
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Progress 09/15/07 to 09/14/08
Outputs
OUTPUTS: Granted funds are addressing a need for the development and testing of quality spatio-temporal prediction models for Russian wheat aphid (RWA), Diuraphis noxia (Kurdjumov), which is a pest of wheat and barley. Damage estimates are in the hundreds of millions of dollars since the introduction of the RWA into the United States. We have built a predictive model with the goal of explaining within-field variation in RWA population structure using weather variables, soil characteristics, topography and Landsat 7 Enhanced Thematic Mapper imagery. This model has the potential to be a key Integrated Pest Management tool (e.g. forecasting, placement of resistant small-grain varieties, precision pesticide application and directed scouting). Cross-validation suggests that this model will predict RWA densities during the early spring on winter wheat as or more precisely than conventional field scouting, relying entirely on remotely sensed data. However, the model has not been validated for other cereals (e.g., barley), or time periods (e.g., late spring or early summer). We have initiated work designed to validate model predictions under field conditions for high-resolution forecasting of RWA densities using winter wheat and spring barley, from the early spring to harvest. Measured aphid densities will be used to correlate RWA population densities with yield damages. Combining loss functions, temperature variables, and the spatially explicit RWA density model will generate RWA Risk Assessment Maps, which will serve to focus control efforts in areas of greatest need. This project will generate an online program, linked to the World Wide Web, designed to produce RWA density maps and Risk Assessment Maps for use by consumers. This study is in its infancy with granted funds allocated, and work started in the fall of 2007. Numerous plots across two wheat field sites in eastern and southern Colorado have been infested with RWA. These sites will be used to test predictions for growing season RWA population dynamics in 2008. PARTICIPANTS: Initial work has been completed in establishing farming collaborators. Todd and Cary Wickstrom, as well as John and Jeremy Stulp have offered wheat / fallow agroecosystem acreage for our use. Extension agent Bruce Bosley and entomology research associates Cynthia Walker and Mike Koch were instrumental in establishing contacts with the farming community, including contact with the aforementioned collaborators. TARGET AUDIENCES: We intend to develop a fact sheet detailing the use of an online program dedicated to generating spatio-temporal Russian wheat aphid density predictions, including the necessary inputs and information on how to understand resulting Russian wheat aphid density surfaces and Risk Assessment Maps. This fact sheet will be disseminated in several ways: (1) it will be added to the small grains section of and the High Plains Integrated Pest Management Guide (highplainsipm.org); (2) it will be published electronically as one of Colorado State University insect management fact sheets (http://www.ext.colostate.edu/pubs/insect/pubins.html), (3) it will be distributed at Colorado State University Wheat Field Days; and (4) it will be distributed as part of one of the Colorado Wheat Grower newsletters, which is sent to every grower of more than 25 acres of wheat. PROJECT MODIFICATIONS: No project modifications have occurred.
Impacts
This project is in its initial phases. Therefore, results are pending.
Publications
- No publications reported this period
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