Data Analyses
For all further analyses, we used R Version 4.0.3 (R Development
Core Team; http://www.r-project.org). In general, models were
compared by sequentially deleting terms and comparing model fits using
F-tests or χ2-tests (where appropriate), after which
pairwise contrasts were computed using the ‘ emmeans’ packages ,
with α < 0.05. We checked residual behaviour using the
‘DHARMa’ package . All plots were produced using the ‘ggplot2’ package .
To test for the effect of evolution treatment on temporal changes in gas
production, we used a linear mixed model (LMM) with treatment × time as
fixed explanatory categorical variables, as well as their interaction.
To account for non-independency of observations over time, we fitted
random intercepts for each reactor. Based on the obtained
simulation-based residual plots, we included a dispersion parameter for
levels of treatment and time, using the ‘glmmTMB’ function in the‘glmmTMB’ package . Based on the full model, we calculated
pairwise treatment contrasts for each week, adjusted for multiple
testing using the ‘tukey’ method in the emmeans package.
To look at the impact of the 1% transfer on ecological changes, we
looked at (1) dissimilarity of linked pre-adapted versus adapted
communities (i.e. those that received 1% enrichment from a linked
pre-adapted community, n = 12 samples), (2) dissimilarity of pre-adapted
and adapted communities that were not directly linked through 1%
transfer (n = 132 non-linked samples) and (3) dissimilarity of the
pre-adapted versus control communities (n = 144 samples).
We also simulated potential impact of the 1% enrichment by in silico
adding a 1%-rarefied pre-adaptation samples to the control treatments
and comparing their composition with the original control samples via
PERMANOVA (adonis).
To determine which taxa differed in abundance in the control versus
evolution treatments, we fitted a negative binomial GLM to the
sequencing data using the ‘DESeq’ function in the R package
‘DESeq2 ’ . Focussing on the 100 most common taxa, we calculated
significant differences in the abundance of taxa using Wald tests and
corrected P –values for multiple testing using the ‘frd’ method.