Wind speed is one of the most important factors for seed wind dispersal. A wind speed reduction region, which could be influenced by vegetation arrangement, will form in the lee of vegetation and therefore affects the seed dispersal. Here, by taking shrub as an example, quantitative differences in seed dispersals of low vegetation between single element and windbreak‐like clumps are numerically investigated. The local variation of stream‐wise wind speed is focused. Empirically parameterized functions of leeward wind distributions are employed. It reveals that the accumulative probability of dispersed seeds from a point source with considering leeward wind reduction could be well fitted by a logistic function. For a fixed release height or vegetation porosity, accumulative probabilities for single element and those for windbreak‐like clumps would intersect at a leeward location. This intersection location decreases linearly with release height but exponentially with porosity. The fitting parameter r
0 (the center of logistic function) for single element increases as the same manner for windbreak‐like clumps, with regard to the increase of release height, porosity, and height. But, the increasing rates for single element are higher than those for windbreak‐like clumps. The fitting parameter p (the power index of logistic function) for single element is generally larger than that for windbreak‐like clumps. With the increase of release height, p decreases at first but increases then for single element, while it shows opposite trend for windbreak‐like clumps. p decreases with porosity for both single element and windbreak‐like clumps. But, the decreasing rate for single element is lower than that for windbreak‐like clumps. p increases exponentially with height for windbreak‐like clumps, while it almost keeps constant for single element. These results suggest the potential importance of vegetation arrangement on seed dispersal and therefore possibly provide additional reason for the disagreement among observed dispersal kernels.