Effect-size and study trait variable extraction
We recorded the following information from each study to allow direct comparison of effect sizes, test the effect of study features (moderators) on this effect, and control for variation between studies: host/prey taxa to test for a phylogenetic trend in our models; parasite type (macroparasite, microparasite, or parasitoid), study design (observational or experimental), predator interaction type (all or non-consumptive), and predator spreader identity (predator spreader or not) for inclusion in mixed effects models (MEMs) testing the effect of these moderators on effect sizes. The majority of studies (45 of 50) were composed of a binary comparison of a parasite response across two levels of predation. Most studies were analyzed using multivariate statistics which makes statistical comparison of effect sizes across studies challenging (Borenstein et al. 2017). For this reason, we extracted the mean parasite response value, sample size, and measure of variation (typically SE, SD, or 95% CI) from the text or figures of each of these studies and calculated the standardized mean difference (Hedges g) using the escalc function in the R package metafor (Viechtbauer 2010). A small minority of studies (5 of 50) reported parasite responses over a range of predation pressures. We converted responses from 3 of these studies to binary effect sizes by using raw data provided to compare the mean parasite response for samples in the first quartile of predator abundance to those in the 4th quartile of predator abundance. We excluded studies from further analysis if sufficient data for this procedure were not provided. Following this protocol we extracted 193 effect sizes from 48 studies.
Not all effect sizes contain the same type of information because of differences in the biology of parasites and in the associated response metric. For our study, we grouped effect sizes into 2 broad categories based on the parasite response that was measured: (i) the number or proportion of hosts infected (quantified as prevalence, number or density of infected individuals, or disease induced mortality rate;n = 89 effect sizes from 22 different studies, Table 1) and (ii) the number of parasites in an average individual (quantified as parasite intensity or parasite load; n = 61 effect sizes from 19 different studies). Because we expected that predators would have different effects on prevalence and intensity measures (for example a small amount of selective predation on a population with highly aggregated parasites may have a large effect on mean intensity but a small effect on prevalence), we analyzed these responses separately. Another distinction we made was to separate parasites from parasitoids. Parasitoids behave like both predators and parasites over the course of their life-cycle. Adult parasitoids are free-living flies and wasps that lay eggs on live hosts, but the juvenile parasitoids that hatch from these eggs are obligately parasitic and typically lethal to the host. Consequently, the effect of predators on parasitoids in prey may result from different processes than the effects on typical parasites. For this reason, we analyzed parasitoids (n = 43 effect sizes from 11 different studies) separately from parasites.