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.

Department of Botany Faculty of Science University of South Bohemia České Budějovice 370 05 Czech Republic

Department of Experimental Plant Biology Faculty of Science Charles University Prague 128 43 Czech Republic

Department of Experimental Plant Biology Faculty of Science University of South Bohemia České Budějovice 370 05 Czech Republic

Institute of Botany of the Czech Academy of Sciences Průhonice 252 43 Czech Republic

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