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Keywords:

  • abscission;
  • dispersal;
  • long-distance dispersal;
  • mechanistic modelling;
  • meteorology;
  • seed trap;
  • tropical forest;
  • updraft;
  • wind dispersal

Summary

  1. Seed dispersal is a short-term phenomenon with long-term consequences for population survival and spread. Physiological mechanisms that target the release of seeds to particular sets of environmental conditions that maximize the probability of long-distance dispersal should evolve if long dispersal distance enhances fitness.
  2. In this study, we use high-frequency censuses of seeds actually dispersed, high-frequency within-canopy meteorological observations and long-term measurements of above-canopy wind to investigate the environmental conditions that control the timing of seed abscission at different time-scales for a wind-dispersed tropical tree, Luehea seemannii.
  3. We show that seed abscission follows a typical seasonal pattern, is rare at night and is most prevalent during periods of prolonged updrafts, higher temperature, with negative feedback when the heat canopy flux is relatively high.
  4. We use phenomenological (super-WALD) and mechanistic (coupled Eulerian–Lagrangian closure) models to estimate the relative effects of the timing of seed release at different subannual temporal scales (seconds–hours) on the resulting long-term (season–decade) dispersal kernels. We find that periods of high wind speed increase the probability of long-distance dispersal between 100–1000 m, but decrease the probability at distances further than 1000 m relative to unbiased environmental conditions. We also find abscission during updrafts to increase the probability of long-distance dispersal at distances greater than 100 m.
  5. Synthesis: We observe preferential abscission during updrafts in a tropical wind-dispersed tree. We use mechanistic models and long-term wind statistics to estimate the dispersal consequences of preferential seed release in specific environmental conditions. We find that the timing of the dispersal season may be influenced by wind conditions that maximize long-distance dispersal; however, there are likely other environmental factors essential for their determination. Our approach provides a method to bridge between small turbulence scales and large ecosystem scales to predict dispersal kernels. These findings shed light on the evolutionary processes that drive optimization of the timing of seed abscission and may be incorporated into plant population movement models to increase their accuracy and predictive power.