Disease epidemics and species interactions: A manipulation of seasonal establishment of fungal diseases in an old field.

Many disease epidemics recur seasonally, and such seasonal epidemics can be shaped by species interactions among parasites, pathogens, or other microbes. Field experiments are a classic approach for understanding species interactions but are rarely used to study seasonal epidemics. Our research objective was to help fill this gap by manipulating the seasonal timing of the establishment of infectious diseases while tracking epidemics and other ecological responses. To do this, we conducted a multiyear field experiment in an old field in the Piedmont of North Carolina, USA, dominated by the grass species tall fescue (Lolium arundinaceum (Schreb). Darbysh). In the field, tall fescue experienced seasonal epidemics of multiple foliar fungal diseases: anthracnose in spring, brown patch in mid-summer, and crown rust in late summer to fall. In a fully randomized design, we applied four fungicide treatments to replicate plots of intact vegetation in specific seasons to manipulate the timing of disease epidemics. One treatment was designed to delay the establishment of anthracnose until mid-summer, and another to delay the establishment of both anthracnose and brown patch until fall. In a third treatment, fungicide was applied year-round, and, in a fourth treatment, fungicide was never applied. The experiment comprised 64 plots, each 2 m × 2 m, surveyed from May 2017 to February 2020. Here, we report a dataset documenting responses in the community structure of both plants and foliar fungi. To track disease prevalence in the host population across seasons and years, this dataset includes monthly leaf-level observations of the disease status of over 100,000 leaves. To quantify transmission and investigate within-host pathogen interactions, we longitudinally surveyed disease status in host individuals of known age at least weekly over two growing seasons. Finally, the dataset includes annual data on infection prevalence of the systemic fungal endophyte Epichloë coenophiala, community-level aboveground plant biomass, and plant community cover. These data can be used for meta-analyses, comparisons, and syntheses across systems as ecologists seek to predict and mechanistically understand seasonal disease epidemics. There are no copyrights on the dataset, and we request that users of this dataset cite this paper in all publications resulting from its use.