Aim Understanding large scale patterns in trait variation in climbing plants (lianas, vines, scramblers, twiners) is important for the development of a stronger theoretical understanding of climbing plant ecology and for more applied issues such as prediction of community assembly under changing climatic conditions. We compared values of five key functional traits for 388 species of climbing plant from tropical and temperate regions of Australia to quantify variation between these two biogeographic regions.
Methods Data on dispersal mode, growth habit, leaf form, leaf size and seed mass were compiled from field measurements and published sources. Comparative analyses were performed in three ways: (1) across species where each species was treated as an independent data point, (2) using evolutionary divergence analyses for each trait, and (3) in multidimensional space using a matrix of similarities between species.
Results Tropical climbing plants had 22-fold greater seed mass and four times greater leaf size than did temperate species. Tropical climbers were more likely to be woody (63%) than were temperate species (40%). Surprisingly we found a similar proportion of animal-dispersed seeds in the two regions, although we expected animal-dispersed seeds to be more prevalent in the tropics. We also found similar proportions of simple- and compound-leaved species between the two regions. All of our findings were consistent between cross-species and phylogenetic analyses indicating that patterns in present-day species are reflected in the evolutionary history of Australian climbers. Multivariate analyses suggested that there is a spectrum of variation among climbing plants, with tropical species having greater seed mass, leaf size and woody growth compared with temperate climbing plant species.
Main conclusions Tropical and temperate climbers of Australia exhibit a mixture of similar and contrasting traits and ecological strategies. Understanding strategy variation along latitudinal gradients will be particularly informative for predicting ecosystem and community structure with climate change.