Chasing the unknown: predicting seed dispersal mechanisms from plant traits

Abstract

Summary1. 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 shortor long-distance dispersers, and highlight important biological interactions. 2. 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. 3. 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). 4. 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.

Predicting species' maximum dispersal distances from simple plant traits

“…For plants, it is known that dispersal distance is related to a dispersal syndrome (Willson 1993, Pa¨rtel and Zobel 2007, Vittoz and Engler 2007. Dispersal syndrome may generally be deduced from seed morphology, which is assumed to facilitate dispersal by a specific vector (e.g., animals, wind, water [Hughes et al 1994, Thomson et al 2010). However, a multiplicity of vectors, as well as variation in the behavior of these vectors, makes it difficult to establish a direct association between dispersal syndrome and long-distance dispersal (Nogales et al 2007).…”

Evolution of seed dispersal in the Cerrado biome: ecological and phylogenetic considerations

“…Grouping plants from a community into functional groups according to their dispersal syndromes can help to understand some of these processes, since the morphology of the dispersal units generally reflect different strategies of plants for dispersion by various means, in response to a set of ecological and evolutionary factors (Thomson et al 2010;Fleming & Kress 2013).…”

Dispersal potential of Scaevola crassifolia (Goodeniaceae) is influenced by intraspecific variation in fruit morphology along a latitudinal environmental gradient

“…Often investigations of dispersal ecology aim to predict dispersal ability, potential or distance by using simple plant, fruit or seed traits (Römermann et al 2005;Will et al 2007;Thomson et al 2010). Hydrochory has received less attention than other dispersal modes, with knowledge of hydrochory in the Australian flora particularly lacking (Thomson et al 2010), even though the continent has a large coastal fringe and numerous wetlands.…”

“…Hydrochory has received less attention than other dispersal modes, with knowledge of hydrochory in the Australian flora particularly lacking (Thomson et al 2010), even though the continent has a large coastal fringe and numerous wetlands. Whereas we have previously shown that fruits of S. crassifolia can survive up to 42 days in seawater and are therefore capable of oceanic dispersal (Guja et al 2010) here we have shown that several morphological variables differ significantly between buoyant and sunken fruits.…”