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      Paleoneurology of Amniotes : New Directions in the Study of Fossil Endocasts 

      A Look in to the Neurocranium of Living and Extinct Lepidosauria

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          Assembling the Squamate Tree of Life: Perspectives from the Phenotype and the Fossil Record

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            Phylogeny And Systematics Of Squamata (Reptilia) Based On Morphology

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              Combining phylogenomic and supermatrix approaches, and a time-calibrated phylogeny for squamate reptiles (lizards and snakes) based on 52 genes and 4162 species.

              Two common approaches for estimating phylogenies in species-rich groups are to: (i) sample many loci for few species (e.g. phylogenomic approach), or (ii) sample many species for fewer loci (e.g. supermatrix approach). In theory, these approaches can be combined to simultaneously resolve both higher-level relationships (with many genes) and species-level relationships (with many taxa). However, fundamental questions remain unanswered about this combined approach. First, will higher-level relationships more closely resemble those estimated from many genes or those from many taxa? Second, will branch support increase for higher-level relationships (relative to the estimate from many taxa)? Here, we address these questions in squamate reptiles. We combined two recently published datasets, one based on 44 genes for 161 species, and one based on 12 genes for 4161 species. The likelihood-based tree from the combined matrix (52 genes, 4162 species) shared more higher-level clades with the 44-gene tree (90% vs. 77% shared). Branch support for higher level-relationships was marginally higher than in the 12-gene tree, but lower than in the 44-gene tree. Relationships were apparently not obscured by the abundant missing data (92% overall). We provide a time-calibrated phylogeny based on extensive sampling of genes and taxa as a resource for comparative studies.
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                Book Chapter
                2023
                November 22 2022
                : 123-177
                10.1007/978-3-031-13983-3_5
                fe98fb91-5336-434e-b073-28490cfc1ba3
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