Local Causal States and Discrete Coherent Structures

Coherent structures form spontaneously in nonlinear spatiotemporal systems and are found at all spatial scales in natural phenomena from laboratory hydrodynamic flows and chemical reactions to ocean, atmosphere, and planetary climate dynamics. Phenomenologically, they appear as key components that organize the macroscopic behaviors in such systems. Despite a century of effort, they have eluded rigorous analysis and empirical prediction, with progress being made only recently. As a step in this, we present a formal theory of coherent structures in fully-discrete dynamical field theories. It builds on the notion of structure introduced by computational mechanics, generalizing it to a local spatiotemporal setting. The analysis' main tool employs the \localstates, which are used to uncover a system's hidden spatiotemporal symmetries and which identify coherent structures as spatially-localized deviations from those symmetries. The approach is behavior-driven in the sense that it does not rely on directly analyzing spatiotemporal equations of motion, rather it considers only the spatiotemporal fields a system generates. As such, it offers an unsupervised approach to discover and describe coherent structures. We illustrate the approach by analyzing coherent structures generated by elementary cellular automata, comparing the results with an earlier, dynamic-invariant-set approach that decomposes fields into domains, particles, and particle interactions.Comment: 27 pages, 10 figures; http://csc.ucdavis.edu/~cmg/compmech/pubs/dcs.ht

A Coordinated Effort to Manage Soybean Rust in North America: A Success Story in Soybean Disease Monitoring

Existing crop monitoring programs determine the incidence and distribution of plant diseases and pathogens and assess the damage caused within a crop production region. These programs have traditionally used observed or predicted disease and pathogen data and environmental information to prescribe management practices that minimize crop loss (3,69). Monitoring programs are especially important for crops with broad geographic distribution or for diseases that can cause rapid and great economic losses. Successful monitoring programs have been developed for several plant diseases, including downy mildew of cucurbits, Fusarium head blight of wheat, potato late blight, and rusts of cereal crops (13,36,51,80)

A review of the interaction between potassium nutrition and plant disease control

Abstract Potassium (K) is an essential macronutrient involved in many physiological and biochemical functions that affect a plant's susceptibility to disease. These processes include stomatal regulation, enzyme activation, and solute transport, each of which is often discussed through the lens of either plant nutrition or plant disease control. However, the interaction between these stresses and the resulting physiological and agronomic impact is an important consideration when managing a cropping system as a whole and is scarcely addressed in the literature. Therefore, a review of the literature was focused on the interaction of K nutrition and the resulting impact on plant disease control. Nutrient management, especially K, can manipulate these essential plant processes to provide the host plant with either an advantage or disadvantage in disease susceptibility, depending on the pathogen and the situation. Numerous studies have been conducted investigating the individual pathogen and host relationships, concluding that the majority of bacterial and fungal diseases decreased with increasing K nutrition, while viral diseases and nematode infections had inconsistent responses to K nutrition. These differences in the response of disease to K nutrition complicate generalizations across species and environments. Similarly, the impact of K on plant growth is affected by the concentration of each nutrient and its ratio with other nutrients. Therefore, a review of the major physiological processes that depend on plant K nutrition is discussed below with the resulting impact on plant disease control