Integrative assessment of genetic, landscape, and climatic data in Aspidosperma quebracho-blanco across the Argentinian Gran Chaco

Background and aims – Integrating landscape information with genetic data offers critical insights for biodiversity conservation and management. The Gran Chaco region, one of the most biodiverse and threatened subtropical woodlands, features a highly heterogeneous landscape largely shaped by river dynamics. This study focuses on Aspidosperma quebracho-blanco , a dominant tree species in this region with ecological, commercial, medical, and conservation significance, to investigate the interactions among population genetics, landscape features, and climatic factors. Material and methods – To assess if watersheds influence the spatial distribution of genetic variability in A. quebracho-blanco , we conducted analyses of genetic variability and structure among watersheds. Based on AFLP data, we applied horizontal interpolation analysis, Mantel test, and Barrier software to identify potential barriers to gene flow among populations and compared these with topographic and hydrographic features across the Argentinian Chaco. Finally, we used Principal Component Analysis (PCA) to evaluate the influence of environmental variables on genetic diversity. Key results – Our results reveal that genetic variability is spatially structured at the regional scale. Eight potential barriers to gene flow were identified, primarily corresponding to major river systems and orographic features. PCA indicated that elevation and climate likely influence population genetic patterns. Conclusion – The observed associations among genetic structure, landscape heterogeneity, and climate provide essential insights for the management, conservation, and ecological restoration of A. quebracho-blanco in the Gran Chaco region. For in situ conservation, it is recommended that each sampled population be managed independently. In contrast, for restoration actions and ex situ conservation, management is recommended from a watershed-based perspective.