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Genetic variation and cryptic lineage diversity of the Nigerian red-headed rock agama Agama agama associate with eco-geographic zones.

ABSTRACT: AbstractNigeria is an Afrotropical region with considerable ecological heterogeneity and levels of biotic endemism. Among its vertebrate fauna, reptiles have broad distributions, thus, they constitute a compelling system for assessing the impact of ecological variation and geographic isolation on species diversification. The red-headed rock agama, Agama agama, lives in a wide range of habitats and, thus, it may show genetic structuring and diversification. Herein, we tested the hypothesis that ecology affects its genetic structure and population divergence. Bayesian inference phylogenetic analysis of a mitochondrial DNA (mtDNA) gene recovered four well-supported matrilines with strong evidence of genetic structuring consistent with eco-geographic regions. Genetic differences among populations based on the mtDNA also correlated with geographic distance. The ecological niche model for the matrilines had a good fit and robust performance. Population divergence along the environmental axes was associated with climatic conditions, and temperature ranked highest among all environmental variables for forest specialists, while precipitation ranked highest for the forest/derived savanna, and savanna specialists. Our results cannot reject the hypothesis that niche conservatism promotes geographic isolation of the western populations of Nigerian A. agama. Thus, ecological gradients and geographic isolation impact the genetic structure and population divergence of the lizards. This species might be facing threats due to recent habitat fragmentation, especially in western Nigeria. Conservation actions appear necessary.

SUBMITTER: Nneji LM

PROVIDER: S-EPMC6911843 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Project description:While traditionally species recognition has been based solely on morphological differences either typological or quantitative, several newly developed methods can be used for a more objective and integrative approach on species delimitation. This may be especially relevant when dealing with cryptic species or species complexes, where high overall resemblance between species is coupled with comparatively high morphological variation within populations. Rock lizards, genus Darevskia, are such an example, as many of its members offer few diagnostic morphological features. Herein, we use a combination of genetic, morphological and ecological criteria to delimit cryptic species within two species complexes, D. chlorogaster and D. defilippii, both distributed in northern Iran. Our analyses are based on molecular information from two nuclear and two mitochondrial genes, morphological data (15 morphometric, 16 meristic and four categorical characters) and eleven newly calculated spatial environmental predictors. The phylogeny inferred for Darevskia confirmed monophyly of each species complex, with each of them comprising several highly divergent clades, especially when compared to other congeners. We identified seven candidate species within each complex, of which three and four species were supported by Bayesian species delimitation within D. chlorogaster and D. defilippii, respectively. Trained with genetically determined clades, Ecological Niche Modeling provided additional support for these cryptic species. Especially those within the D. defilippii-complex exhibit well-differentiated niches. Due to overall morphological resemblance, in a first approach PCA with mixed variables only showed the separation between the two complexes. However, MANCOVA and subsequent Discriminant Analysis performed separately for both complexes allowed for distinction of the species when sample size was large enough, namely within the D. chlorogaster-complex. In conclusion, the results support four new species, which are described herein.

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Genetic variation and cryptic lineage diversity of the Nigerian red-headed rock agama Agama agama associate with eco-geographic zones.

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