Data for: The role of temperature in the start of seasonal infectious disease epidemics
Abstract
Many infectious diseases display strong seasonal dynamics. When both hosts and parasites are influenced by seasonal variables, it is unclear if the start of an epidemic is limited by host or parasite factors or both. The Daphnia-Pasteuria host-parasite system exhibits seasonal epidemics. We aimed to ascertain how temperature contributes to the timing of P. ramosa epidemics in early spring. To this aim, we experimentally disentangled this effect from the effects of temperature on host development and phenology and from that of host traits on parasite time to visible infection. We hypothesized that the parasite is additionally directly limited by low temperatures beyond its need for available hosts. We found that parasite time to visible infection decreased with increasing temperature at a faster rate than host time to hatching and maturity did, consistent with this hypothesis. We also found that hosts hatched from sexual resting stages are less likely to become infected than those produced clonally and that hosts resistant to many known parasite strains are slower to show signs of visible infection compared to those susceptible to many. Together, these results imply that climate change could lead to earlier seasonal epidemics for this host-parasite system, which may also impact longer-term population dynamics.
Methods
Data were collected from experimental epidemics of the bacterial endoparasite Pasteuria ramosa in the waterflea Daphnia magna at different temperatures. Briefly, five different temperature treatments were applied to jars of Daphnia juveniles (of either a largely resistant phenotype or a largely susceptible phenotype) and jars of Daphnia ephippia. Each sampling day the number of juveniles, adults and infected individuals were counted. To calculate the main outcome variables (time to hatch for ephippia, time to maturation, time to infection), the number of newly hatched juveniles, number of new adults (with eggs) and number of new infections were calculated on each sampling day and multiplied by the day of the experiment. These were then divided by the total number hatched, matured or infected, respectively, to obtain an average time to hatch, maturation or infection for each experimental jar. For prevalence, the total number ever infected over the course of the experiment was divided by the maxiumum number of individuals ever present in the jar.
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