Ordination and statistics
We prepared NMDS plots of all three datasets (“Pilot”, “Pilot full” and “Full”, see explanation below) with abundance and presence-absence based dissimilarity metrics to investigate the importance of depth and transformation for determining the composition of prey (Fig. 2). Depending on the dataset being used, ordination required 4 or 5 dimensions to reach a conservative and low stress-level of 0.1. The pilot prey reads required fewer dimensions (k = 4) than the full dataset and the dataset consisting of the full subset (k = 5). Regardless of dataset or metric, prey composition differed significantly between copepods from different seasons and stations (PERMANOVA, p < 0.001, Fig. 2). The most visually distinct clusters were found when using the season sampled for profiling prey compositions, and samples acquired during the pilot (“Pilot”, Fig. 2a and d) formed less distinct clusters than those from the full sequencing. The same physical samples subset from the full dataset (“Pilot full”, Fig. 2b and e) formed more divergent clusters. Ordination of the complete set of samples (”Full”, Fig. 2c and f) returned a pattern typical of a seasonal transition, with prey compositions from successive seasons overlapping, and samples from disparate seasons (e.g. August and April/May) forming separate clusters. Successive Betadisper tests (Table S3) indicated however that the clusters observed may be influenced by heterogenous dispersion (e.g. Fig. 2f). The copepod species sampled was a less significant predictor of pilot and pilot full diets (Fig. 2a and b) when using Bray-Curtis as dissimilarity metric (p = 0.003 and p = 0.03, respectively), than with Jaccard. For both datasets with greater depth (“Pilot full”, and “Full”), Jaccard dissimilarities led to visually greater separation of clusters.