The infection of maize by Fusarium verticillioides can result in highly variable disease symptoms ranging from asymptomatic plants to severe rotting and wilting. We produced F. verticillioides green fluorescent proteinexpressing transgenic isolates and used them to characterize early events in the F. verticillioides-maize interaction that may affect later symptom appearance. Plants grown in F. verticillioides-infested soil were smaller and chlorotic. The fungus colonized all of the underground parts of a plant but was found primarily in lateral roots and mesocotyl tissue. In some mesocotyl cells, conidia were produced within 14 to 21 days after infection. Intercellular mycelium was detected, but additional cells were not infected until 21 days after planting. At 25 to 30 days after planting, the mesocotyl and main roots were heavily infected, and rotting developed in these tissues. Other tissues, including the adventitious roots and the stem, appeared to be healthy and contained only a small number of hyphae. These results imply that asymptomatic systemic infection is characterized by a mode of fungal development that includes infection of certain tissues, intercellular growth of a limited number of fungal hyphae, and reproduction of the fungus in a few cells without invasion of other cells. Development of visibly rotted tissue is associated with massive production of fungal mycelium and much less organized growth.

Each species had a unique environmental niche though there were multiple niche overlapping areas for the diploids across time, suggesting the potential existence of several hybrid zones during the Pleistocene and the Holocene. No evidence of niche divergence was found, suggesting that species diversification was not driven by ecological speciation but by evolutionary history, though it could be associated to distinct environmental adaptations.

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Summary Endophytic fungi compose a significant part of plant microbiomes. However, while a small number of fungal taxa have proven beneficial impact, the vast majority of fungal endophytes remain uncharacterized, and the drivers of fungal endophyte community (FEC) assembly are not well understood. Here, we analysed FECs in three cereal crops‐related wild grasses – Avena sterilis, Hordeum spontaneum and Aegilops peregrina – that grow in mixed populations in natural habitats. Taxa in Ascomycota class Dothideomycetes, particularly the genera Alternaria and Cladosporium, were the most abundant and prevalent across all populations, but there was also high incidence of basidiomyceteous yeasts of the class Tremellomycetes. The fungal community was shaped to large extent by stochastic processes, as indicated by high level of variation even between individuals from local populations of the same plant species, and confirmed by the neutral community model and Raup‐Crick index. Nevertheless, we still found strong determinism in FEC assembly with both incidence and abundance data sets. Substantial differences in community composition across host species and locations were revealed. Our research demonstrated that assembly of FECs is affected by stochastic as well as deterministic processes and suggests strong effects of environment heterogeneity and plant species on community composition. In addition, a small number of taxa had high incidence and abundance in all of the 15 populations. These taxa represent an important part of the core FEC and might be of general functional importance.

1 We review the problems concerned with describing ecological variability and explain why nonlinear systems theory and chaos may be of relevance for understanding pattern and change in ecosystems. 2 The basic concepts of chaos are considered briefly, where possible in the context of plant ecology. We outline the period doubling route to chaos and associated concepts of bifurcation, universality, sensitivity to initial conditions, dimensionality, attractors and Lyapunov exponents. 3 Examples are selected from the literature to illustrate how nonlinear models and time series analysis have already contributed to research in plant ecology. 4 Key methods used to detect the presence of chaos in ecological time series, including determination of the 'return map,' the Lyapunov exponent, the technique of nonlinear prediction and the method of surrogate data, are surveyed. We discuss how small sample-size, as typically acquired in field-studies, can act as a formidable limitation in such approaches. 5 Models of plant communities, which emphasize the importance of spatiotemporal dynamics, are outlined. The concept of deterministic chaos is shown to be useful in this setting also.