Analyses of coral community change
To estimate the proportion of reef sites containing each coral life
history and species group in each time interval, we utilized binomial
generalized linear mixed effects models that predicted the proportion of
sites containing each life history group as a function of time bin,
coral species group, and their interaction as fixed effects and country
as a random effect. The interaction term was included to allow for
varying temporal trends across individual taxonomic and functional
groups. The random effect of country was included to account for uneven
geographic sampling across time bins. To ensure equal numbers of surveys
were included for each species group within a life history group, only
surveys with presence/absence values for the entire complement of coral
species within a given life history group were included in each model.
Models were fitted using the ‘glmer’ function in the R package
‘lme4’. Mean fitted values and 95% confidence intervals of the
proportion of sites with a coral life history group and its constituent
species groups were plotted for each time bin using the‘plot_model’ function in the R package ‘sjPlot’. Significant
changes in mean fitted values relative to the Pleistocene baseline and
subsequent peak values were assessed via a Tukey post-hoc test using the‘emmeans’ function in the R package ‘emmeans’.
To assess the effects of coral community change on regional diversity
patterns, we tracked temporal changes in community dissimilarity. We
utilized species presence/absence matrices to compute Jaccard’s
dissimilarity index [39]. To account for the higher number of reef
sites and countries added in the latter part of the time series, we
restricted our analysis to change in coral community dissimilarity
within individual countries only. Within each time bin, the
dissimilarity was computed between all possible combinations of reef
sites located within the same country. For each country and time bin
combination, a mean dissimilarity value was computed. To equalize the
influence of each country and to avoid giving undue influence to
countries with a larger number of surveys, mean dissimilarity values
were computed for each country prior to computing the overall mean for a
time bin. Uncertainty estimates were obtained via a bootstrap procedure
that sampled with replacement from the distribution of mean
within-country dissimilarity values for each time bin n times
(with n = number of countries for that bin). This resampling
procedure was performed 1000 times for each time bin; 95% confidence
intervals were determined from the 5th and
95th quantiles of the resampled distributions.
Significant differences in mean within-country coral community
dissimilarity values were determined by pairwise comparisons performed
via permutation tests (with 1000 iterations) using the‘pairwise.perm.t.test’ function in the ‘RVAideMemoire’package in R. All statistical analyses were performed using the program
Rv3.4 [40], and all P-value corrections for multiple testing were
computed using the method outlined in ref 41.