Diversity metrics
Species diversity
We measured community richness using: (1) species richness (SR), (2) the
Shannon-Wiener diversity index (H’) (Shannon and Weaver 1949), and (3)
Smith and Wilson’s (1996) index of evenness (Evar).
Species presence/absence data was collected for all sub-plots, so to
avoid pseudo-replication we calculated a single species richness measure
for each plot by averaging the species richness of the nine sub-plots.
In addition to calculating the overall species richness of each plot, we
calculated the species richness of shrubs (25 species total), herbs (102
species total), and graminoids (52 species total) separately. Our other
two measures of community richness required species abundance data,
which was only collected for one sub-plot in each plot, so H’ and
Evar measurements at the plot-level were taken from a
single sub-plot.
Phylogenetic diversity
Phylogeny construction
To study the effect of reindeer grazing on phylogenetic diversity, we
constructed a regional vascular plant phylogeny. After reducing all
taxonomy assignments to the species-level, which involved re-assigning
subspecies, hybrids, and synonymous species, we identified 145 unique
species from our samples to include in the regional phylogeny. DNA
sequences for these species for the genes matK and rbcL were collected
from GenBank (Supplementary material Appendix 1, Table A1). If sequence
information was not available for one or both of matK and rbcL for a
species, we used the closest-relative within the same genus with
available matK and/or rbcL sequence information. Sequences for the
identified species or close relative were available for 138/145 species
for rbcL and 140/145 for matK (Supplementary material Appendix 1, Table
A1). Two species did not have available sequence information for either
gene and did not have a close relative that could be substituted:Cerastium cerastoides and Carex parallela . C.
cerastoides was manually inserted at the base of the Cerastiumclade (Scheen et al. 2004) and C. parallela was manually inserted
into a clade with Carex dioica (Lipnerová et al. 2013).
To ensure the correct reading frame prior to sequence alignment, all
sequences were translated to amino acids in ExPASy (Gasteiger et al.
2003). Alignments were completed in MEGA7 (Kumar et al. 2016) using
MUSCLE with the nucleotides for the coding regions of plant plastids and
default settings. Non-informative gaps were manually removed from the
matK alignments and excess lengths were trimmed from the ends of both
genes. We identified GTR+G+I as the best model for rbcL and GTR+G as the
best model for matK using the Model Selection tool in MEGA7.
Bayesian inference of trees was performed using MrBayes (Huelsenbeck and
Ronquist 2001) with two partitions: one for matK and one for rbcL. We
ran our model for 100 000 000 generations with 4 chains at a temperature
of 0.2 and a stop value of 0.01 for convergence. The sample frequency
was set to every 1000 generations with a burn-in fraction of 0.25 and
the trees were dated by constraining seven nodes (Table 1; Bell et al.
2010). The analysis converged at 10 304 000 generations. We illustrate
the posterior with the majority rule consensus tree, created by
collapsing clades with posterior probabilities less than 50% to
polytomies (Supplementary material Appendix 1, Figure A1).
Phylogenetic structure
We used mean pairwise distance (MPD) as our measure of phylogenetic
structure. MPD is more sensitive to changes in distantly related taxa
than is the mean nearest taxon distance (Webb et al. 2002). To prevent
bias resulting from calculations due to distantly related species (e.g.Lycopodium species), we used only the angiosperms (133/145
sampled species) to calculate MPD. We calculated a standardized measure
of MPD with the aid of the function ses.mpd , in the R package
“picante” by comparing the observed phylogenetic community structure
to a specified null model with a randomized community structure (Kembel
et al. 2010, R Core Team 2019). Using taxa that were identified to the
species-level, we calculated both (1) a presence/absence-based measure
of MPD (calculated at the sub-plot level and then averaged within each
plot) and (2) an abundance-based measure (calculated for a single
sub-plot in each plot), by weighting the pairwise distances by the
product of the relative abundance of each species in each pair. Both MPD
metrics were calculated for every tree in the posterior sample (created
by merging the two runs and removing the 25% burn-in: final n =
15,458 trees) and averaged to produce a single measure for each plot.
For our null model we used the independentswap algorithm (with
1000 iterations per run and 999 runs), which randomizes the community
data matrix while maintaining species occurrence frequency and sample
species richness (Gotelli 2000). We used the p-value, or quantile, of
observed MPD vs. the MPD of null communities as our standardized
response variable, as this metric is less biased than the more common
Net-Relatedness Index (Vamosi et al. 2014). Our measure describes the
rank of the observed phylogenetic dispersion relative to the
distribution produced by the null model. A value of 0 corresponds to a
community that is more clumped than any of the null communities, a value
of 0.5 corresponds to a community that has a median dispersion relative
to the null communities, and a value of 1 corresponds to a community
that is more dispersed than any of the null communities. We refer to
these metrics as phylogenetic dispersion (from the species
presence/absence data) and abundance-weighted phylogenetic dispersion
(from the relative species abundance data).