OTUs related to host performance
OTUs of differential abundance between ranges and temperatures were
identified from the univariate output of the mGLM fitted on
post-disturbance time points. We considered OTUs with p-values
< 0.05 and with coefficients of which the 95% confidence
limits were either both positive or both negative as differentially
abundant. Following a joint modeling approach (Warton et al., 2015), we
used the residuals of the mGLM to calculate Spearman correlations
coefficients between OTUs in the samples of the final timepoint
(t12) and the RGR and observed thallus brittleness
disease symptom, for which 95% confidence intervals were obtained by
bootstrapping with a 1000 iterations.
The univariate GLMMs for host performance traits and diversity measures
were fitted using the R package lme4 (Bates, Mächler, Bolker, & Walker,
2015). nMDS was conducted using the R package vegan (Oksanen et al.,
2017). The mGLMs were ran using the R package mvabund (Y. I. Wang et
al., 2012). To consider time in a flexible way in all post-disturbance
models, we compared different versions of the full model based on the
AICc or AICsum (for the mGLM), where time was specified as
factorial and continuous variable (linear, log transformed, squared root
transformed and as polynomial). Violations of model assumptions were
verified visually with QQ-plots and residual vs fitted-plots for
univariate and multivariate analyses.