Data analyses: variation in the light environment
We quantified light penetration in our grassland community to determine
how much light variation exists and to identify sources of that
variation. We examined light penetration across plots to assess
variation across the site (‘interplot light variation’), within plots to
quantify heterogeneity in light penetration (‘intraplot light
variation’), and across months to determine how light penetration
changed throughout the growing season (‘temporal light variation’). To
quantify interplot light variation, we calculated mean light penetration
(%) within a plot during one sampling event, and further calculated
variance (σ2) between these means for each month
(N=3). For intraplot light variation, we calculated the variance in
light penetration within each plot for each month (N=147). Finally, to
quantify temporal variation, we calculated variance in mean light
penetration for each plot across months (June, July, August; N=49).
Additionally, to assess how light penetration levels differ across June,
July, and August, we performed a one-way repeated measures ANOVA using
mean light penetration as the response variable and plot as the
within-subject factor, followed by a Bonferroni post hoc test to
determine significant differences between months. We visually assessed
normality and checked for equal variances among months using a Mauchly’s
test for sphericity. For these analyses, we used the ‘anova_test’ and
‘pairwise_t_test’ functions from the package ‘rstatix’ v0.6.0
(Kassambara 2020).