Differential abundance analysis
Separately within each of the four plots (2 sites x 2 land cover types), globally differentially abundant ASVs across sampling times were identified using the ANCOM-BC algorithm (Lin & Peddada, 2020) by assessing log-fold-changes in ASV abundances at 06:00, 12:00, and 18:00 sampling times, compared to midnight (00:00) as the intercept/baseline sampling time. We used the ancombc() function in the RANCOMBC package (https://github.com/FrederickHuangLin/ANCOMBC) with settings including alpha = 0.05 significance level, p-value adjustment for multiple comparison using the method of Holm (1979), taxa with fractional prevalence less than 0.1 (= prv_cut) were excluded in the analysis, structural zeros were detected (struc_zero = TRUE) with taxa classified as structural zeros using asymptotic lower bounds (neg_lb = TRUE), and a conservative variance estimator was used for the test statistic (conserve = TRUE). We used the ANCOM-BC global test result which identifies differentially abundant taxa between at least two groups across three or more different groups. To determine whether differentially abundant ASVs were shared across the plots, we constructed Venn diagrams to display the number of overlapping or non-overlapping differentially abundant ASVs across plots and comparison periods (06:00 cf. 00:00, 12:00 cf. 00:00, and 18:00 cf. 00:00).