Testing the effect of sequencing depth on prey composition
Non-metric multidimensional scaling (NMDS) plots were used to visualize
how depth of sequencing and data transformation may influence prey
composition resolution. Multiple variants were made to explore
beta-diversity using both occurrence, and presence/absence-based
dissimilarity metrics. All ordinations were computed from sample-wise
dissimilarities from compositional data at zOTU-level. Relative
abundances were used to compute Bray-Curtis dissimilarities (Bray &
Curtis, 1957), whereas a presence/absence-table enforcing a 0.01%
relative abundance threshold was used for Jaccard dissimilarities
(Jaccard, 1901). We used Scree-plots to find the appropriate dimensions
for a conservative acceptance threshold of ≤0.1 stress. Final NMDS plots
were calculated iteratively (trymax = 100) with adequate dimensions (k =
4 or 5) using the metaMDS function of vegan (Oksanen et al., 2019).
PERMANOVA (nperm = 10000) analyses were used to test if three
explanatory variables (season, station and species) accounted for the
observed variance in prey composition. We subsequently tested if the
grouped samples had homogenous and comparable dispersions (p ≥ 0.05), or
if compositional differences in prey could be due to heterogenous
dispersion among groups (p < 0.05, Betadisper).