Statistical analyses
Community data frames were constructed using individuals as “sites” against ASV, family or order identifications. Incidence and Hellinger-transformed relative read abundances were used as values. Incidence data alone outweighs rare taxa and can significantly alter detected ecological patterns. While read abundances are not directly translatable to taxon abundances in a community, there is utility in transformed abundances to detect otherwise obscured ecological patterns. Hill numbers (Alberdi & Gilbert 2019) were calculated to quantify prey diversity for all three community data frames. Welch’s t-test was used to test the hypothesis of no differences in dietary prey diversity between spiders in ginger and native forest. Additionally, Welch’s t-test was used to test the hypothesis of no differences in read abundances between both groups.
To assess overall compositional differences between the diets of spiders in ginger sites versus native forests, community matrices were constructed using block number combined with transect number as the site, against ASV or order. An order-level food web grid was constructed. Family, genus or species was not used because of overall low BLAST matches; these taxonomic levels provided less compositional information as well as the data was biased towards taxa well-represented in GenBank. Order-level provided the coarsest view of diets while ASV provided the finest grain view. Beta diversity was calculated based on Jaccard distances on both Hellinger-transformed reads and incidence data. Produced values were plotted against distance between sites to assess level of spatial autocorrelation (see S5 in Supplemental Information). Because of very weak correlation between distance and beta diversity and our interest in only a single explanatory variable distinctly split across sites, spatial autocorrelation was not identified as a concern. Non-metric dimensional scaling (NMDS) was performed using beta diversity values, with k = 2 and using a maximum of 1,000 random starts to achieve convergence. Permutational multivariate analysis of variance (PERMANOVA) was performed based on beta diversity values to test the hypothesis that the center and spread of dietary communities across ginger and native forest sites are equivalent.
To assess compositional differences within the two most prevalent orders (Hemiptera and Lepidoptera), 16s sequences were aligned using MUSCLE and a neighbor joining phylogenetic tree using the Jukes-Cantor model of evolution was constructed in Geneious (See S8 and S9 in Supplemental Information). This tree was then used to calculated phylogenetic beta diversity. Phylogenetic beta diversity was used here to allow assessment of relationships between taxa within each order, as family, genus or species identifications were not obtainable using BLAST. Again, NMDS was used to visually assess community similarity in ordination space and differences tested using PERMANOVA.
The lack of confident BLAST identifications resulted in a lower number of identifiable native/non-native sequences; more identifiable sequences were detected in the spiders in ginger because of the higher proportion of introduced taxa. Parasites were identifiable across ginger and native forest sites using BLAST. Parasite frequency was assessed using both the number of ASVs within ginger and native forest sites that were identified as parasitic, and the relative number number of parasitic reads in individual spiders. Welch’s t-test was used to test the hypothesis of no differences in parasitic load between ginger and native forest sites.
BLAST assignment, alignment and phylogenetic reconstruction was completed in Geneious Prime v. 2022.0.2. Analyses were conducted in R version 4.1.2. Analyses and figures were produced using the following packages in R: vegan, BAT, ape, tidyverse, reshape2, ggplot2, ggpubr, ggvenn, formattable, gapminder, bipartite, and ComplexHeatmap. Code for analysis and data is available on GitHub and Dryad (see Data Accessibility).

Results