The evolution of spermatophytes (seed plants) is relatively well known in their evolutionary relationships over temporal changes, but their spatial evolution is another critical yet often neglected lens, especially using a taxon-based approach. Here, by integrating geographic distributions and origin locations across 429 spermatophyte families worldwide with unsupervised machine learning approaches, we constructed a Spermatophyte Spatial Evolutionary System that classifies global spermatophytes into 18 distribution types and six distribution supertypes within three primary floristic elements: cosmopolitan, tropical, and temperate. We found that the three elements all primarily originated from Gondwana, with the cosmopolitan element being the youngest and the temperate element being the oldest in terms of origin. They primarily formed during the Tertiary, particularly between the Eocene and Miocene, driven mainly by climate, long-distance dispersal, and tectonic movement, while each exhibited distinct migration routes and formation models. Our results provide novel insights into the spatial evolution of global spermatophytes and highlight that similar distribution patterns of spermatophytes were driven by their comparable formation processes and mechanisms at the levels of floristic element, distribution supertype, and type.

Understanding plant adaptive strategies that determine species distributions and ecological optima is crucial for predicting responses to global change drivers. While functional traits provide mechanistic insights into distribution patterns, the specific trait syndromes that best predict elevational optima, particularly in less-studied regions such as the Himalayas, remain unclear. This study employs a novel hierarchical framework integrating morphological, anatomical, and physiological traits to explain elevational distributions among 310 plant species across a 3,500-m gradient (2,650–6,150 m). We analyzed 95,000 floristic records collected from 4,062 localities spanning 80,000 km² in Ladakh, NW Himalayas, India, to define elevational optima and link them with 17 functional traits from over 7,800 individuals. We assessed the roles of moisture and cold limitations on trait–optima relationships by comparing two contrasting habitats (dry steppe and wetter, colder alpine). The predictive power of functional traits was more pronounced in the alpine species facing more extreme abiotic stress than the steppe species. Our results indicate that conservative life history strategies strongly predict elevational optima in alpine areas, while drought avoidance and competitive dominance are key in steppe habitats. Trait syndromes combining short stature, compact growth forms, enhanced storage tissues, and features promoting water-use efficiency (δ¹³C), freezing resistance (fructan levels), and nutrient retention (high root nitrogen and leaf phosphorus) explained 61% of the variation in alpine species' optima. Conversely, lifespan and clonal propagation determined the optima of steppe species at lower elevations. The study emphasizes the importance of functional trait combinations in determining elevational optima, highlighting that alpine species prioritize resource conservation and stress tolerance, while steppe species focus on competitive growth strategies. This multi-trait approach contrasts with previous research focusing on single trait–elevation relationships, providing novel insights into the diverse mechanisms shaping elevational distributions and offering valuable predictive power for assessing vegetation responses to future climate change.