Covariation in abscission force and terminal velocity of windborne sibling seeds alters long-distance dispersal projections

Brittany J. Teller, James H. Marden, Katriona Shea

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


Summary: Despite the fact that seeds are unlikely to be identical - even among siblings within a maternal individual - dispersal models typically use one mean trait value to represent the ability of an entire species to disperse. Previous work has shown that the environmental conditions under which individuals leave the maternal site strongly affect how far seeds will travel. However, less is known about how trait variation within individuals contributes to dispersal or how such variation might interact with abiotic factors. Here, we develop the use of an ergometer in a novel application to investigate variation in seed traits, specifically the force required for seed abscission and seed terminal velocity, exhibited by seeds from different locations within maternal capitula of the invasive species Carduus nutans (Asteraceae). We find that seeds from the centre of capitula are significantly easier to liberate and have slower falling velocities than siblings found near the edge of capitula. When abscission force is positively correlated with terminal velocity, slowly falling, easily abscised, central seeds are projected to travel much further than edge seeds on slow winds. Our experimental and theoretical results, which together show that within-individual variation can strongly affect model projections of species dispersal, have important implications for our broader understanding of population spread rates, the spatial structure of populations, metapopulation connectivity and gene flow in the landscape.

Original languageEnglish (US)
Pages (from-to)593-599
Number of pages7
JournalMethods in Ecology and Evolution
Issue number5
StatePublished - May 1 2015

All Science Journal Classification (ASJC) codes

  • Ecology, Evolution, Behavior and Systematics
  • Ecological Modeling


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