The relationship between elevation and seed-plant species richness in the Mt. Namjagbarwa region (Eastern Himalayas) and its underlying determinants

Understanding how species richness changes along altitudinal gradients and what mechanisms answer for those patterns has intrigued increasing attention from numerous researchers, however, there is still no consistent agreement on these questions. Here, based on available distribution records, we explored the elevational pattern of species richness for seed plants in the Mt. Namjagbarwa region (Eastern Himalayas, China), a previously unexplored region. Species richness in each 100 m elevation band was estimated by spatial interpolation method according to their recorded elevation range over a large altitudinal gradient from 700 to 5000 m. In each elevation band, species richness was related to several explanatory factors, including temperature, humidity, spatially related variables and biogeographical distributions. Regression analyses were performed to obtain a quantitative assessment of the relative contribution of each predictor to the empirical richness pattern. Overall, species richness along elevation showed a hump-shaped pattern, with a peak at 1600–2000 m. In all sub-groups (life form, biogeographical affinity, and range-size category), species richness showed unimodal patterns with increasing elevation generally, but with different peak positions. Regression models indicated species richness patterns are highly correlated with energy-related factor in most data sets, explaining the observed richness patterns, but also more or less associated with other variables (climatic variation, area, precipitation, and mid-domain effect). The water-energy dynamics model was found to explain the elevational species richness patterns. Meantime, there was an elevational coincidence between maximum species richness and floristic overlap index, which proving the role of the biotic process in shaping the species richness gradient. Our findings reconfirmed that the elevational richness gradient is influenced by many processes, including ecological factors and evolutionary history, and suggested the need to consider more factors in order to determine key mechanisms in future studies.