Location: Emerging Pests and Pathogens
Project Number: 8062-22000-021-29
Start Date: Nov 01, 2013
End Date: Jul 31, 2016
Five pairs of study areas in central Wisconsin will be analyzed with ArcGIS software to determine the percent area covered by row crops, grasslands, and forests. Study areas will be paired to control for physical factors such as climate, slope and soil type, with one study area having a high percentage of non-crop habitat and one having a low percentage. Nested within each study area will be five study plots in potato fields. The field perimeter and the landscape in a 1km diameter circle surrounding each plot will be analyzed for landscape complexity using the same metrics as above, allowing for comparisons across three spatial scales. The landscape composition at the perimeter and 1km diameter scales will be ground-truthed. Vector abundance and diversity will be measured on each plot weekly throughout the season using water traps, and plants next to the traps will be censused visually for aphids to ascertain which species are colonizing the field. To determine initial inoculum size, a random sample of seed tubers will be collected from each participating grower and assayed for PVY with ELISA and RT-PCR. In order to minimize confounding environmental variables and management practices, one plot in each 10km study area will include 50 short-term sentinel plants (out-plants), grown virus-free in a greenhouse. Sentinel plants will be placed randomly within the plot rows next to field plants and will be removed, sampled for aphids and PVY, and replaced with virus-free plants weekly. This will allow for uniformity of cultivar and soil characteristics. We will combine sequential sampling of field plants with sentinel plants to produce high-resolution temporal infection data. By comparing the cumulative epidemic curves of the resident plants and sentinel plants, we can detect the sequence of coinfections and detect ontogenetic effects such as mature plant resistance. At the end of the season, yield and tuber infection will also be sampled. Wisconsin suction trap data will be used to estimate flight onset for PVY vectors. A generalized additive mixed model (GAMM) will be used to describe the annual and seasonal trends in aphid abundance using trap data. From these models, the seasonal predictions in aphid abundance will be used to deduce or better define the interval in which elevated risk for crop exposure to virus-carrying aphids will be greatest. In the proposed project, we will compare aphid flight data with field collected data on colonizing and transient aphids in order to quantify the relationship between migratory flights and virus transmission in the field. Since PVY is transmitted very quickly, it can be challenging to correlate aphid species with the spread of PVY based on trapped specimens alone. We will test correlations between aphid flight data, field-level aphid surveys, and data on PVY in sentinel plants to better understand the relationship between migrating aphids and PVY.