Aim To investigate how species richness and similarity of non-native plants varies along gradients of elevation and human disturbance.
Location Eight mountain regions on four continents and two oceanic islands.
Methods We compared the distribution of non-native plant species along roads in eight mountainous regions. Within each region, abundance of plant species was recorded at 41–84 sites along elevational gradients using 100-m2 plots located 0, 25 and 75 m from roadsides. We used mixed-effects models to examine how local variation in species richness and similarity were affected by processes at three scales: among regions (global), along elevational gradients (regional) and with distance from the road (local). We used model selection and information criteria to choose best-fit models of species richness along elevational gradients. We performed a hierarchical clustering of similarity to investigate human-related factors and environmental filtering as potential drivers at the global scale.
Results Species richness and similarity of non-native plant species along elevational gradients were strongly influenced by factors operating at scales ranging from 100 m to 1000s of km. Non-native species richness was highest in the New World regions, reflecting the effects of colonization from Europe. Similarity among regions was low and due mainly to certain Eurasian species, mostly native to temperate Europe, occurring in all New World regions. Elevation and distance from the road explained little of the variation in similarity. The elevational distribution of non-native species richness varied, but was always greatest in the lower third of the range. In all regions, non-native species richness declined away from roadsides. In three regions, this decline was steeper at higher elevations, and there was an interaction between distance and elevation.
Main conclusions Because non-native plant species are affected by processes operating at global, regional and local scales, a multi-scale perspective is needed to understand their patterns of distribution. The processes involved include global dispersal, filtering along elevational gradients and differential establishment with distance from roadsides.