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Global warming may force montane species to shift upward to keep pace with their shifting climate niche. How species differences in such distribution shifts depend on their elevational positions, elevation-dependent warming rates, and other environmental constraints, or plant functional traits is poorly understood. Here, we analyzed for 137 Himalayan tree species how distribution shifts vary with elevational niche positions, environmental constraints, and their functional traits. We developed ecological niche models using MaxEnt by combining species survey and botanical collections data with 19 environmental predictors. Species distributions were projected to 1985 and 2050 conditions, and elevational range parameters and distribution areas were derived. Under the worst-case RCP 8.5 scenario, species are predicted to shift, on average, 3 m/year in optimum elevation, and have 33% increase in distribution area. Highland species showed faster predicted elevational shifts than lowland species. Lowland and highland species are predicted to expand in distribution area in contrast to mid-elevation species. Tree species for which species distribution models are driven by responses to temperature, aridity, or soil clay content showed the strongest predicted upslope shifts. Tree species with conservative trait values that enable them to survive resource poor conditions (i.e., narrow conduits) showed larger predicted upslope shifts than species with wide conduits. The predicted average upslope shift in maximum elevation (8 m/year) is >2 times faster than the current observations indicating that many species will not be able to track climate change and potentially go extinct, unless they are supported by active conservation measures, such as assisted migration. Abstract in Nepali is available with online material.

Tropical montane systems are characterized by a high plant species diversity and complex environmental gradients. Climate warming may force species to track suitable climatic conditions and shift their distribution upward, which may be particularly problematic for species with narrow elevational ranges. To better understand the fate of montane plant species in the face of climate change, we evaluated a) which environmental factors best predict the distribution of 277 plant species along the Himalayan elevational gradient in Nepal, and b) whether species elevational ranges increase with increasing elevation. To this end, we developed ecological niche models using MaxEnt by combining species survey and presence data with 19 environmental predictors. Key environmental factors that best predicted the distribution of Himalayan plant species were mean annual temperature (for 54.5% of the species) followed by soil clay content (10.2%) and slope (9.4%). Although temperature is the best predictor, it is associated with many other covariates that may explain species distribution, such as irradiance and potential evapotranspiration. Species at both ends of the Himalayan elevational gradient had narrower elevational ranges than species in the middle. Our results suggest that with further global warming, most Himalayan plant species have to migrate upward, which is especially critical for upland species with narrow distribution ranges.

Plant functional traits determine plant performance and have therefore the potential to shape and predict species distributions along environmental gradients. This study analyses how traits affect tree species distribution along an elevational gradient in the Himalayas, Nepal. We addressed three questions: (a) what plant strategies can be distinguished among tree species? (b) how are plant traits and strategies associated with elevation? and (c) what plant traits are the best predictors of species positions along elevational gradient? We quantified for 31 tree species a set of 39 plant traits related to resource uptake, use and conservation. We analysed how traits cluster into separate functions using a cluster analysis, and how traits and clusters associate into distinct plant strategies using a principal component analysis. The cluster analysis showed five clusters of traits, reflecting (a) efficiency in vertical expansion, (b) efficiency in horizontal expansion, (c) efficiency in metabolism, (d) physical defence and (e) tree functional groups (conifers vs. broadleaf species). The first PCA axis reflects trade-offs in traits and clusters linked to elevation: highland species had trait values that increase safety against freezing induced cavitation, high solar radiation and strong wind, and that increase resource conservation. In contrast, lowland species had trait values that increase efficiency of resource acquisition, metabolism and expansion. Additionally, a bivariate analysis showed that the first PCA axis is more strongly related to elevation than the individual traits, indicating that the combination of traits is more important than the individual traits. An all subsets regression analysis showed that a small set of traits best explain species distribution: highland species had smaller size (low basal area), safer hydraulics (low conduit diameter) and lower leaf and branch display efficiency (low leaf area per xylem area, specific branch length) that increase persistence under harsh conditions. Remarkably, leaf traits were poor predictors of species' elevational positions. Synthesis. Multiple trade-offs in plant size, hydraulics and light competitiveness shape species distribution along the elevational gradient. Along this extreme environmental gradient, stem and branch traits that integrate multiple plant organs and functions are better predictors of species' elevational distributions than leaf traits.