Abstract Seed or samara terminal velocity is a key trait affecting the dispersal potential of wind‐dispersed plants. However, this trait is often represented in dispersal models by a single mean value per species. This is despite considerable variation in dispersal traits within species and individuals that may have implications for both phenotypic selection and rates of spread. Methodological constraints may have acted as a barrier for robust assessments of intraspecific variation in seed terminal velocity. To quantify intraspecific variation in wind dispersal traits, we develop a low‐cost, time‐efficient method to measure the terminal velocity of a large number of samaras. We made three separate terminal velocity measurements for each of 750 Pinus radiata samaras, allowing partitioning of variation among individual cones, trees and source populations. We use the mechanistic WALD model to assess the potential influence of observed variation in samara terminal velocity on predicted dispersal kernels under a variety of realistic conditions. We demonstrate a twofold range in samara terminal velocity within P. radiata, with the highest variation occurring within individual cones, and the lowest among cones within individual trees. We identify a potential influence of source population on terminal velocity. Our modelling results demonstrate that this within‐species variation is sufficient to affect the shape of the predicted dispersal kernels, particularly the kernel tails and therefore the likelihood of long‐distance dispersal events. The effect of samara terminal velocity on dispersal is especially pronounced under environmental conditions that enhance seed dispersal. Our findings illustrate the scale of within‐species variation in a key dispersal trait, and the likely effect of this variation on dispersal distance. We suggest that the high level of variation observed within individual cones of P. radiata is likely to reduce the potential for phenotypic selection, and may either be indicative of a “bet‐hedging” strategy, or simply the result of the constraints of cone morphology on samara development. To obtain accurate dispersal models for wind‐dispersed species we highlight the necessity of capturing this variation for inclusion in future modelling approaches, and describe a device that can achieve such measurements easily and at low cost.