Jan. 1, 2012 - Mar. 31, 2014Award Number
Martin Wiedmann, Ph.D
Riparian buffer zones have been implicated in the transmission of foodborne pathogens to produce fields and fresh fruits and vegetables, but no one currently understands how the growth of produce in close proximity to riparian zones influences the risk of contamination. The proposed work will measure the movement of fecal bacteria through riparian zones and onto produce fields by detecting the movement of genes from those bacteria. The measured movement of genes from field sampling will be compared to models that represent competing ideas about how the bacteria move. These models produce maps for farms and surrounding lands. They tell us how bacteria move across the land in a manner similar to what roadmaps tell us about the movement of cars. The maps that agree best with the movement patterns of fecal bacteria will be used to advise growers about when, where and how riparian zones increase risk of foodborne pathogen dispersal onto produce. Ultimately, a web-based tool can be developed to apply the best model to new lands and help the produce industry evaluate crop planting decisions, pre-harvest surveillance practices and harvest practices to prevent product contamination.
Riparian buffer zones in agricultural landscapes provide essential ecosystem services while increasing species diversity and habitat connectivity for wildlife and plants. Unfortunately, improved wildlife habitat adjacent to crop production areas may increase risk for contamination of fruits and vegetables. Therefore, buffer zones could serve as transport pathways across landscapes for foodborne pathogens. Accurate information about the role of buffer zones in dispersing foodborne pathogens is essential for the produce industry to strike a balance between the use of buffer zones to enhance soil and water quality while controlling the risks associated with infiltration of produce by wildlife. In this proposal, we will apply an innovative approach, using techniques that have been pioneered in the emerging field of landscape genetics, to systematically answer questions about pathogen movement, sources, and sinks within agricultural landscapes. We propose to conduct causal modeling of the effect of riparian zone and produce field qualities on the movement of fecal bacteria across agricultural landscapes. Competing models will be formulated using remotely-sensed and field-collected data, e.g. vegetation density and type, buffer width, soil habitat quality, produce type, and infiltration rate of host animal feces. These models will provide data to predict produce contamination risk in the landscape context. The data will produce maps of the most efficient paths for fecal bacteria across the landscape. The predictions from these maps will then be compared to genetic data from fecal bacteria isolates collected in the field. The set of models producing good fits to the genetic data will define landscape attributes that promote pathogen dispersal. A key advantage of analyzing fecal bacteria directly, as opposed to tracking host animals, is that this analysis can account for unmeasurable events such as transmission of bacteria among host individuals or even among host animal species during dispersal. These models can also account for persistence across extrahost environments. The product of this research will be: i) a set of landscape attributes that effect dispersal, and ii) a set of characteristic dispersal patterns of fecal bacteria within buffer zones and from buffer zones to crop production areas. These results will inform spatial modeling of food contamination risk associated with buffer zones. This quantitative assessment of the role of riparian buffer zones in the movement of pathogens can be used to modify pre-harvest product sampling strategies and produce harvest methods to account for the spatial structure in contamination risk in a produce field. For example, our project may define a certain proximity to a buffer that carries an increased risk of pathogen presence and thus may not be suitable to grow crops that are susceptible to contamination from the soil. This project directly addresses three specific questions under priority 1.3-Co-management of Food Safety and the Environment and questions about movement efficiency of foodborne pathogens between domestic animal and produce operations. This project will specifically support the produce industry by providing scientific data and tools to predict the risk of produce contamination on lands impacted by riparian zones.