Over the past century, various mechanistic models have been developed to estimate the magnitude of seed dispersal by wind, and to elucidate the relative importance of physical and biological factors affecting this passive transport process. The conceptual development has progressed from ballistic models, through models incorporating vertically variable mean horizontal windspeed and turbulent excursions, to models accounting for discrepancies between airflow and seed motion. Over hourly timescales, accounting for turbulent fluctuations in the vertical velocity component generally leads to a power-law dispersal kernel that is censored by an exponential cutoff far from the seed source. The parameters of this kernel vary with the flow field inside the canopy and the seed terminal velocity. Over the timescale of a dispersal season, with mean wind statistics derived from an "extreme-value" distribution, these distribution-tail effects are compounded by turbulent diffusion to yield seed dispersal distances that are two to three orders of magnitude longer than the corresponding ballistic models. These findings from analytic models engendered explicit simulations of the effects of turbulence on seed dispersal using computationally intensive fluid dynamics tools. This development marks a bifurcation in the approaches to wind dispersal, seeking either finer resolution of the dispersal mechanism at the scale of a single dispersal event, or mechanistically derived analytical dispersal kernels needed to resolve long-term and large-scale processes such as meta-population dynamics and range expansion. Because seed dispersal by wind is molded by processes operating over multiple scales, new insights will require novel theoretical tactics that blend these two approaches while preserving the key interactions across scales.