Abstract
Seed dispersal by wind is one of the most important dispersal mechanisms in plants. The key seed trait affecting seed dispersal by wind is the effective terminal velocity (hereafter "terminal velocity", V (t) ), the maximum falling speed of a seed in still air. Accurate estimates of V (t) are crucial for predicting intra- and interspecific variation in seed dispersal ability. However, existing methods produce biased estimates of V (t) for slow- or fast-falling seeds, fragile seeds, and seeds with complex falling trajectories. We present a new video-based method that estimates the falling trajectory and V (t) of wind-dispersed seeds. The design involves a mirror that enables a camera to simultaneously record a falling seed from two perspectives. Automated image analysis then determines three-dimensional seed trajectories at high temporal resolution. To these trajectories, we fit a physical model of free fall with air resistance to estimate V (t) . We validated this method by comparing the estimated V (t) of spheres of different diameters and materials to theoretical expectations and by comparing the estimated V (t) of seeds to measurements in a vertical wind tunnel. V (t) estimates closely match theoretical expectations for spheres and vertical wind tunnel measurements for seeds. However, our V (t) estimates for fast-falling seeds are markedly higher than those in an existing trait database. This discrepancy seems to arise because previous estimates inadequately accounted for seed acceleration. The presented method yields accurate, efficient, and affordable estimates of the three-dimensional falling trajectory and terminal velocity for a wide range of seed types. The method should thus advance the understanding and prediction of wind-driven seed dispersal.