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Abstract Genomic‐scale datasets, sophisticated analytical techniques, and conceptual advances have disproportionately failed to resolve species boundaries in some groups relative to others. To understand the processes that underlie taxonomic intractability, we dissect the speciation history of an Australian lizard clade that arguably represents a “worst‐case” scenario for species delimitation within vertebrates: theCtenotus inornatusspecies group, a clade beset with decoupled genetic and phenotypic breaks, uncertain geographic ranges, and parallelism in purportedly diagnostic morphological characters. We sampled hundreds of localities to generate a genomic perspective on population divergence, structure, and admixture. Our results revealed rampant paraphyly of nominate taxa in the group, with lineages that are either morphologically cryptic or polytypic. Isolation‐by‐distance patterns reflect spatially continuous differentiation among certain pairs of putative species, yet genetic and geographic distances are decoupled in other pairs. Comparisons of mitochondrial and nuclear gene trees, tests of nuclear introgression, and historical demographic modelling identified gene flow between divergent candidate species. Levels of admixture are decoupled from phylogenetic relatedness; gene flow is often higher between sympatric species than between parapatric populations of the same species. Such idiosyncratic patterns of introgression contribute to species boundaries that are fuzzy while also varying in fuzziness. Our results suggest that “taxonomic disaster zones” like theC. inornatusspecies group result from spatial variation in the porosity of species boundaries and the resulting patterns of genetic and phenotypic variation. This study raises questions about the origin and persistence of hybridizing species and highlights the unique insights provided by taxa that have long eluded straightforward taxonomic categorization.
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Genetic structure and landscape effects on gene flow in the Neotropical lizard Norops brasiliensis (Squamata: Dactyloidae)
Abstract One key research goal of evolutionary biology is to understand the origin and maintenance of genetic variation. In the Cerrado, the South American savanna located primarily in the Central Brazilian Plateau, many hypotheses have been proposed to explain how landscape features (e.g., geographic distance, river barriers, topographic compartmentalization, and historical climatic fluctuations) have promoted genetic structure by mediating gene flow. Here, we asked whether these landscape features have influenced the genetic structure and differentiation in the lizard speciesNorops brasiliensis(Squamata: Dactyloidae). To achieve our goal, we used a genetic clustering analysis and estimate an effective migration surface to assess genetic structure in the focal species. Optimized isolation-by-resistance models and a simulation-based approach combined with machine learning (convolutional neural network; CNN) were then used to infer current and historical effects on population genetic structure through 12 unique landscape models. We recovered five geographically distributed populations that are separated by regions of lower-than-expected gene flow. The results of the CNN showed that geographic distance is the sole predictor of genetic variation inN. brasiliensis, and that slope, rivers, and historical climate had no discernible influence on gene flow. Our novel CNN approach was accurate (89.5%) in differentiating each landscape model. CNN and other machine learning approaches are still largely unexplored in landscape genetics studies, representing promising avenues for future research with increasingly accessible genomic datasets.
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- Award ID(s):
- 1831319
- PAR ID:
- 10498986
- Publisher / Repository:
- Nature Publishing Group
- Date Published:
- Journal Name:
- Heredity
- Volume:
- 132
- Issue:
- 6
- ISSN:
- 0018-067X
- Format(s):
- Medium: X Size: p. 284-295
- Size(s):
- p. 284-295
- Sponsoring Org:
- National Science Foundation
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