Statistical analyses
All statistical analyses associated with microbial community richness
and composition in roots and shoots of A. speciosa were conducted
in R (R Core Team 2018, v. 3.5.1) using the vegan package (Oksanenet al . 2017) except where otherwise noted. All analyses were
based on rarefied data (160, 7820, 634 and 1400 sequences for bacteria,
AMF, non-AM root fungi and FFE, respectively) using the ‘rrarefy’
function. Samples with few sequences were removed from further analyses
to allow for greater sequencing depth, which resulted in 36, 36, 34 and
36 samples for bacteria, AMF, non-AM root fungi and FFE, respectively.
Analyses of plant ITS2 data when extracting DNA from all remaining
foliar tissue was based on a rarefaction level of 8475 sequences. These
sampling depths were chosen based on saturation of sequencing effort
curves (Figure 2) and in effort to retain the most samples (n = 18 per
sampling strategy for bacteria, AMF and foliar fungi and 17 for non-AM
root fungi). Sequencing effort curves were produced using the iNext
package (Hsieh and Chao 2016). To test how sampling strategy influenced
microbial alpha diversity metrics, we calculated richness as the number
of SVs in each sample as well as Pielou’s ‘J’ evenness, which describes
the similarity of species frequencies. To compare diversity metrics
(based on SVs) between the two sampling strategies we performed a
Wilcoxon signed-rank test on all paired values. To ensure that potential
differences in sampling strategies were not due to artifactual SVs, we
also compared results when implementing LULU, an algorithm for
post-clustering curation that clustered SVs at 98.5% similarity and a
minimum relative co-occurrence of 0.9 (Frøslev et al .,
2017) .
We performed non-metric multidimensional scaling (NMDS) to evaluate
community structures for each sampling strategy and target region,
individually. Each NMDS analysis was performed using the ‘metaMDS’
function and stress for all plots was between 0.04 and 0.16. These
analyses were performed on Bray-Curtis distances of Hellinger
transformed sequence abundances as well as Raup-Crick distances of
presence/absence data. The ‘Procrustes’ function in vegan was used to
assess similarity of patterns produced in the NMDS analyses for the
paired sampling strategies and congruency was visualized in Procrustes
plots. The ‘protest’ function was used with 1000 permutations to
estimate the significance of the Procrustes statistic. We performed
analyses on both presence/absence and abundance data to determine how
low-abundant SVs influenced the differences between sampling strategies.
To determine variation in microbial communities among individual plants
when we extracted from multiple subsamples, we performed NMDS analyses
as well as a PERMANOVA using the ‘adonis’ function. We also performed a
PERMANOVA to detect seasonal differences between May and September
leaf-disc collections. Figures were generated using ggplot2 (Wickham
2016).