geoGraph: Connectivity modelling across geographic space with hexagonal discrete global grids

geoGraph enables accurate global-scale connectivity modeling using hexagonal grids, improving correlation between geographic and genetic distances from r = 0.74 to r = 0.84.

• Why it matters: Understanding organism movement across landscapes is vital for ecology and evolutionary biology, but existing tools are limited by distortions or lack of general applicability, especially at large scales.
• What they did: The authors developed geoGraph, an R package that integrates raster and vector GIS data into a hexagonal tessellation, supporting various resolutions and providing a complete analysis pipeline with visualization tools.
• The result: geoGraph demonstrates improved modeling of movement and connectivity at different spatial scales, such as reduced movement across the Himalaya, and is broadly applicable to landscape genetics, conservation, and human dispersal studies.