Sampling bias and the robustness of ecological metrics for plant-damage-type association networks: Comment
Schachat, S. R.
Show abstract
Bipartite network metrics, which link taxa at two trophic levels, are notoriously biased when sampling is incomplete or uneven (Bluthgen et al., 2008; Dormann and Bluthgen, 2017; Frund et al., 2016). Yet a new contribution (Swain et al., 2023, henceforth SEA) claims the opposite: that bipartite network metrics are minimally sensitive to incomplete sampling and, in fact, perform better at low sample sizes than traditional richness metrics. Here I show that SEA achieved this extraordinary finding by abandoning accepted practices, including practices from the authors previous papers.
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