Coping with ineffective overlap in multilocus phylogenetics

Missing data is a long-standing issue in phylogenetic inference, which often results in high levels of taxonomic instability, obscuring otherwise well-supported relationships. Multiple approaches have been developed to deal with the negative effects of ineffective overlap on tree resolution, often by identifying taxa for removal. Here we repurpose a heuristic method developed to identify unstable taxa in morphological data matrices, concatabominations, and combine it with a novel gene-tree jackknifing on matrix representation of trees to identify candidates for targeted sequencing. Using a multilocus caecilian dataset, we illustrate the method's capacity to identify candidate taxa and loci for additional sequencing, compare the results to those of the mathematics-based gene sampling sufficiency approach, and explore the terrace space associated with the multilocus dataset. We show that our approach yields tractable numbers of loci/taxa for targeted sequencing that successfully mitigate topological instability due to ineffective overlap, even when modest amounts of data are added.