Chasing the unknown: predicting seed dispersal mechanisms from plant traits.
The dispersal capabilities of most plant species remain unknown. However, gaining basic dispersal information is a critical step for understanding species' geographical distributions and for predicting the likely impacts of future climate change. Dispersal mechanisms can indicate short- or long-distance dispersers, and highlight important biological interactions. To predict dispersal mechanisms for species where information is limited, we used generalized linear mixed models with basic life-history and ecological traits. Sets of models were created (using Australian species) for six dispersal categories: wind, unassisted, water, ant, vertebrate-ingestion and vertebrate-attachment dispersal mechanisms. We validated our models on the dispersal mechanisms of 50 Australian, 30 Californian, 30 Swiss plant species and a global compilation of 70 species. Growth form, seed mass and vegetation type were the main predictor variables. Our models predicted dispersal mechanisms for Australian and Californian plant species equally well (c. 70% correct) and to a lesser extent for the Swiss flora (c. 50% correct). Our models predicted observed dispersal mechanisms (c. 50% correct) equally well to inferred dispersal mechanisms (based on seed morphology). Synthesis. Our approach of using easily obtainable traits for predicting dispersal mechanisms of species allows dispersal information to be predicted for species where little is known. From here, the application of realistic dispersal curves to the predicted dispersal mechanisms will further understanding on the dispersal capabilities of species.