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. 2023 Jul 7;2:15. doi: 10.1038/s44185-023-00020-8

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© The Author(s) 2023

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 3 — a SVDquartet tree. Node support ≥80% from 100 bootstraps is indicated with a black dot. Samples are grouped into three main clades (K1-K3) and two, three, and four subclades, respectively (K1a, K1b, K2a, etc.) based on tree morphology and sNMF analysis with the main clades representing the three secondary species hypotheses (SSHs; annotated). b Principal component analysis (PCA) based on genome-wide SNPs. The relative eigenvalues are shown in the subplots with the displayed eigenvectors shaded in black. c Hierarchical genetic clustering using sNMF across all samples with main clades below and subclades above. Bars in each column represent the contribution of predicted ancestral lineages to each sample. Samples are ordered by cluster and then longitudinally by island.