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).