No abstract

Empirical and mechanistic modeling indicate that pathogens transmitted via aerially dispersed inoculum follow a power law, resulting in dispersive epidemic waves. The spread parameter (b) of the power law model, which is an indicator of the distance of the epidemic wave front from an initial focus per unit time, has been found to be approximately 2 for several animal and plant diseases over a wide range of spatial scales under conditions favorable for disease spread. Although disease spread and epidemic expansion can be influenced by several factors, the stability of the parameter b over multiple epidemic years has not been determined. Additionally, the size of the initial epidemic area is expected to be strongly related to the final epidemic extent for epidemics, but the stability of this relationship is also not well established. Here, empirical data of cucurbit downy mildew epidemics collected from 2008 to 2014 were analyzed using a spatio-temporal model of disease spread that incorporates logistic growth in time with a power law function for dispersal. Final epidemic extent ranged from 4.16 ×108 km2 in 2012 to 6.44 ×108 km2 in 2009. Current epidemic extent became significantly associated (P < 0.0332; 0.56 < R2 < 0.99) with final epidemic area beginning near the end of April, with the association increasing monotonically to 1.0 by the end of the epidemic season in July. The position of the epidemic wave-front became exponentially more distant with time, and epidemic velocity increased linearly with distance. Slopes from the temporal and spatial regression models varied with about a 2.5-fold range across epidemic years. Estimates of b varied substantially ranging from 1.51 to 4.16 across epidemic years. We observed a significant b ×time (or distance) interaction (P < 0.05) for epidemic years where data were well described by the power law model. These results suggest that the spread parameter b may not be stable over multiple epidemic years. However, b ≈ 2 may be considered the lower limit of the distance traveled by epidemic wave-fronts for aerially transmitted pathogens that follow a power law dispersal function.

Wheat blast, caused by the Triticum pathotype of Magnaporthe oryzae, is an emerging disease considered to be a limiting factor to wheat production in various countries. Given the importance of wheat blast as a high-consequence plant disease, weather-based infection models were used to estimate the probabilities of M. oryzae Triticum establishment and wheat blast outbreaks in the United States. The models identified significant disease risk in some areas. With the threshold levels used, the models predicted that the climate was adequate for maintaining M. oryzae Triticum populations in 40% of winter wheat production areas of the United States. Disease outbreak threshold levels were only reached in 25% of the country. In Louisiana, Mississippi, and Florida, the probability of years suitable for outbreaks was greater than 70%. The models generated in this study should provide the foundation for more advanced models in the future, and the results reported could be used to prioritize research efforts regarding the biology of M. oryzae Triticum and the epidemiology of the wheat blast disease.

No abstract

The Lockheed Martin Advanced Technology Center (LM/ATC) is actively investigating alternate applications of coherently phased sparse-aperture optical imaging arrays. Controlling the relative phasing of the apertures enables these arrays to function as imaging interferometers, providing high spectral resolution as well as high spatial resolution imagery. In this paper we will: a) summarize the basic theory of multiple-aperture imaging interferometers; b) illustrate the theory with Fourier transform Imaging Spectrometer (FTIS) simulations, using the Rochester Institute of Technology hyper-spectral scene simulator (DIRSIG) as our source of simulated input data; c) validate the theory with experimental results derived with an LM/ATC optical FTIS tested.