Comparative population genetic dataset of nineteen Caribbean tree species

Despite harboring the highest levels of global plant biodiversity, tropical regions remain underrepresented in published genetic research. Genetic data provide a solid foundation for understanding the effects of recent demographic events, such as the legacies of past shifts in forest cover, on genetic structure and diversity. Comparative genetic studies also present a unique opportunity to examine how life-history traits such as dispersal mechanisms, generation time, and reproductive strategies influence genetic variation across landscapes. We used a comparative approach to investigate patterns of genetic diversity in a focal set of 19 tree species in Puerto Rico; the selected species cover a range of life-history traits and climatic preferences. For each species, we used a reference genome-free genotyping by sequencing approach, allowing us to genotyping ~1000 to 200,000 Single Nucleotide Polymorphisms (SNPs). We assessed population genetic structure and compared genetic diversity across populations and species. Additionally, we examined how life-history strategies and climate preferences influence patterns of genetic diversity, particularly in light of recent demographic events such as forest loss and regrowth. Our results illustrate significant patterns of population genetic structure across species, which are related to spatial and climatic gradients across the island. These findings shed light on how long-term geological and climatic conditions on the island have influenced genetic structure of forest trees, and offer insights to likely source populations, corridors, and barriers to gene flow across Puerto Rico in the context of forest regrowth following land-use change. We also report correlations between life-history traits and patterns of genetic diversity, which suggest how growth and reproductive strategies led to variation in species' genetic diversity. Our study by analyzing genetic diversity across different spatial and temporal scales, deepens our understanding of ecosystem resilience and enhances predictions of how tropical forests might respond to ongoing environmental changes.