The availability of water influences the evolution of life as well as the evolution of the Earth's land surface. Until recently, role of geomorphological and biological (geo-bio) processes including their interactions and inferred coevolution have been poorly understood for extremely water-limited (hyper-arid) environments. This emerging field lies at the nexus of weathering, soil (crust) formation and erosion but also involves landform evolution, which creates barriers or corridors for life across varied geological time scales. To address the complex issues that arise from this field, the German Research Foundation (DFG) has funded Collaborative Research Centre CRC1211 (Earth-Evolution at the Dry Limit) through interdisciplinary research. The natural laboratories used for this work are the hyper-arid cores of the Atacama and Namib deserts, and the main objective has been to gain improved understanding of the evolution of the geosphere and biosphere in hyper-arid environments and to evaluate interactions between these spheres. We hypothesize that phases or events of higher water-availability (by fog, dew or rain) are the key drivers of geo-bio co-evolution. Furthermore, we hypothesize that barriers of geological, geomorphological, and climatic origin are the main controls on present-day biodiversity at various heirarchies including ecosystem dynamics. To test these hypotheses, the studies reported in this virtual special issue (VSI) combine expertise from the fields of population and (phylo-) genetics, molecular biology, biogeography, ecology, soil sciences, geomorphology, meteorology, (palaeo-) climatology, (isotope-) geochemistry and geochronology to shed new light on the trajectories and thresholds of the evolution and isolation of life. This article collection reports recent progress in the hope of motivating and inspiring scientists from all over the world to collaborate on a more comprehensive and quantitative understanding of dry-limited systems, with a view to implementing this understanding into overarching Earth system models.