Predicting species’ maximum dispersal distances from simple plant traits

Many studies have shown plant species' dispersal distances to be strongly related to life-history traits, but how well different traits can predict dispersal distances is not yet known. We used cross-validation techniques and a global data set (576 plant species) to measure the predictive power of simple plant traits to estimate the species' maximum dispersal distance. Including dispersal syndrome (wind, animal, ant, ballistic, and no special syndrome), growth form (tree, shrub, herb), seed mass, plant height, and terminal velocity as explanatory variables in different combinations we constructed models to explain variation in measured maximum dispersal distances and evaluated their ability to predict maximum dispersal distances. Predictions are more accurate, but also limited to a particular set of species, if data on more specific traits, such as terminal velocity, are available. The best model (R2 = 0.60) included dispersal syndrome, growth form and terminal velocity as fixed effects. Reasonable predictions of maximum dispersal distance (R2 = 0.53) are also possible when using only the simplest and most commonly measured traits; dispersal syndrome and growth form together with species taxonomy data. We provide a function dispeRsal to be run in the software package R. This enables researchers to estimate the maximum dispersal distance with confidence intervals for plant species using measured traits as predictors. Easily obtainable trait data, such as dispersal syndrome (inferred from seed morphology) and growth form, enables predictions to be made for a large number of species.