Linking host distributions, parasite specialization, and parasite
distribution
We used generalized linear mixed effects models (GLMMs) to test how
parasite specialization in experiments was related to 1) host community
variation (crop area harvested, Q1), 2) parasite occurrence across hosts
(from recorded natural history collections, Q2), and 3) predicted
specialization from abiotic environment (ENM contrasts, Q3). For each of
the three predictors of host specialization, we modeled relative
emergence of an S. hermonthica population i , on a focal
host as follows:
Emergenceij = β0 +
β1Xi + S0j +
𝜖ij ,
where β0 and β1 are
coefficients, Xi is the value for one of the
predictors of specialization (i.e. crop area harvested, observed
parasite occurrence, or ENM contrast), S0j is the
random effect of host genotype j , and 𝜖ijis the irreducible error. Models were built using the ‘lmer’ function
from the lme4 package (Bates et al. 2015) and
corresponding model summaries and statistical parameters for the fixed
effects were calculated with the lmerTest package using
Satterthwaite’s method (Kuznetsova et al. 2017).