Demographic expansion and panmixia in a St. Martin endemic, Anolis pogus, coincides with the decline of a competitor

Understanding patterns of differentiation at microgeographic scales can enhance our understanding of evolutionary dynamics and lead to the development of effective conservation strategies. In particular, high levels of landscape heterogeneity can strongly influence species abundances, genetic structure, and demographic trends. The bearded anole, Anolis pogus, is endemic to the topographically complex island of St. Martin and of conservation concern. Here, we examined genetic diversity and inbreeding, assessed which features of the landscape influence population abundances, tested for population genetic structure across St. Martin, and inferred historical demographic trends. We performed WGS on 54 individuals and conducted abundance surveys of 100 plots throughout the island of St. Martin. Genomic data are hosted elsewhere on NCBI SRA (PRJNA1278788). Hosted here are data from abundance surveys as well as metadata for individuals used to generate WGS libraries. Further, Zenodo provides sc..., , # Demographic expansion and panmixia in a St. Martin endemic, Anolis pogus, coincides with the decline of a competitor

Dataset DOI: [10.5061/dryad.59zw3r2mg](10.5061/dryad.59zw3r2mg)

## Description of the data and file structure

Here, we provide data for a conservation biology study of *Anolis pogus* in Yuan et al. 2025 Journal of Heredity. This study examined the abundance patterns, population structure, inbreeding levels, and demographic history in this species. Data includes both WGS data for 54 individuals as well as abundance survey data from 112 sites. Here, metadata is provided for our WGS libraries. Raw reads are available elsewhere on NCBI SRA (PRJNA1278788). We also provide our abundance survey data. In Zenodo, we provide scripts for processing raw sequencing data, SNP and genotype likelihood calling, and analyses of demographic history, inbreeding, and population structure. We also provide an R script for the fitting of abundance models based on our survey data.

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