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<div>Understanding and predicting how microbes disseminate through the environment requires a nuanced understanding of the factors that influence microbial dispersion beyond data correlations. To this end, we are developing and evaluating the uncertainty in improved modeling tools to predict and examine spatially explicit three-dimensional (3D) canopy microclimate and turbulence. Advances in computational sciences (e.g., ray tracing algorithms, graphics processing unit computing), and biophysical modeling are used to estimate microclimate heterogeneity and its effect on microbial development, while physics-based models are used to estimate in- and above-canopy turbulence and its impacts on dispersion and deposition. These tools are being integrated into a 3D simulation environment that will be used to test hypotheses or to predict temporally evolving dispersion plumes and the probability of infection risk. Our research is showing that the complex architecture of trellised agricultural systems requires an improved understanding of how canopy heterogeneity and local orography interact with meso and microscale events to influence air turbulence and dispersion at field and regional scales.</div>