The need to prevent and cure emerging diseases often precludes their continuing study in situ. We present studies on the process of disease emergence by host shifts using the model system of anther-smut disease (Microbotryum violaceum) on the plant genus Silene (Caryophyllaceae). This system has little direct social impact, and it is readily amenable to experimental manipulation. Our microevolutionary studies have focused on the host shift of Microbotryum from Silene alba (=latifolia; white campion) onto Silene vulgaris (bladder campion) in a population in Virginia. Karyotypic variation shows that the host shift is recent and originates from the disease on sympatric S. alba. Analysis of the spatial pattern of disease shows that the host shift has been contingent on the co-occurrence of the two species at a local scale. Cross-inoculation studies show that families of the new host differ greatly in their susceptibility to the pathogen, indicating the potential for rapid evolution of resistance. Disease expression on the new host is frequently abnormal, suggesting that the pathogen is imperfectly adapted to its new host. In experimental populations, disease transmission within populations of the old host is greater than within populations of the new host. However, there is also a high transmission rate of the disease from the new host back to the old host, suggesting a feedback effect that increases disease prevalence in the community as a whole. Continuing studies of these populations are designed to determine whether this new host-pathogen system is likely to be self-sustaining and to quantify evolutionary changes in both the host and the pathogen.

Many diseases have both sexual and nonsexual transmission routes, and closely related diseases often differ in their degree of sexual transmission. We investigate the evolution of transmission mode as a function of host social and mating structure using a model in which disease transmission is explicitly dependent on the numbers of sexual and nonsexual contacts (which are themselves a function of population density) and per-contact infection probabilities. Most generally, and in the absence of trade-offs between the degree of sexual transmission and effects on host fecundity and mortality, nonsexual transmission is favored above the social-sexual crossover point (the host density at which the number of nonsexual contacts exceeds the number of sexual contacts), while sexual transmission is favored below this point. When changes in allocation to the two transmission modes are accompanied by changes in mortality or fecundity, both mixed and pure transmission strategies can be favored. If invading genotypes differ substantially from resident genotypes, genetic polymorphism in transmission mode is possible. The evolutionary outcomes are predictable from a knowledge of the equilibrium population sizes in relation to the social-sexual crossover point. Our results also show that predictions about dynamic outcomes, based on rates of invasion for single pathogens into healthy populations, do not adequately describe the resulting disease prevalence nor predict the subsequent evolutionary dynamics; once invasion of a pathogen has occurred, the conditions for spread of a second pathogen are themselves altered. If the host is considered as a single resource, our results show that two pathogens may coexist on a single resource if they use that resource differentially and have differential feedbacks on resource abundance; such resource feedback effects may be present in other biological systems.

Population dynamics across a mortality gradient at an ecological margin are investigated using a novel modeling approach that allows direct comparison of stochastic spatially explicit simulation results with deterministic mean field models. The results show that demographic stochasticity has a large effect at population margins such that density profiles fall off more sharply than predicted by mean field models. Substantial spatial structure emerges at the margin, and spatial correlations (measured parallel to the margin) exhibit a sharp maximum in the tail of the density profile, indicating that spatial substructuring is greatest at an intermediate point across the ecological gradient. Such substructuring may have a substantial impact on Allee effects and evolutionary processes in marginal populations.

Many pathogens of plants are transmitted by arthropod vectors whose movement between individual hosts is influenced by foraging behavior. Insect foraging has been shown to depend on both the quality of hosts and the distances between hosts. Given the spatial distribution of host plants and individual variation in quality, vector foraging patterns may therefore produce predictable variation in exposure to pathogens. We develop a "gravity" model to describe the spatial spread of a vector-borne plant pathogen from underlying models of insect foraging in response to host quality using the pollinator-borne smut fungus Microbotryum violaceum as a case study. We fit the model to spatially explicit time series of M. violaceum transmission in replicate experimental plots of the white campion Silene latifolia. The gravity model provides a better fit than a mean field model or a model with only distance-dependent transmission. The results highlight the importance of active vector foraging in generating spatial patterns of disease incidence and for pathogen-mediated selection for floral traits.

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