1. The seed dispersal kernel is a major determinant of spatial population dynamics and spatial distribution of genetic diversity. Among the main methods to estimate it, inverse modelling (IM) and gene shadow model (GSM) rely on seed counts in traps, whereas competing source model (CSM) and spatially explicit mating models (SEMMs) rely on compositions of seed pools. Moreover, GSM, CSM and SEMM exploit genetic information from molecular markers, whereas IM only exploits seed counts ignoring seed origins. These methods were also applied to established seedlings. 2. In the presence of post-dispersal density-dependent mortality (DDM), the effective dispersal kernel, describing the spatial distribution of established seedlings relatively to the seed source, is notoriously different from the basic dispersal kernel, describing the spatial distribution of seed deposition sites relatively to the source. Using simulated data sets, we investigated whether IM, GSM, CSM and SEMM applied to established seedlings estimate the basic or the effective dispersal kernel. In our simulations, DDM resulted in a shift of the mean basic dispersal distance (10m) towards substantially higher effective mean dispersal distances (15m and 208m). 3. We demonstrated that CSM and SEMM estimate the basic seed dispersal kernel, independently from the presence of post-dispersal mortality. By contrast, GSM estimates the effective dispersal kernel. IM failed to provide satisfactory estimates in the presence of DDM in our sampling design. Besides, for all methods, seed migration was inflated in the presence of DDM, due to lower mortality among randomly distributed immigrants relatively to local seedlings. 4. It could seem intuitive that estimates based on seedlings or seeds provide effective or basic dispersal kernels respectively. Our results showed that it is not true for estimates obtained with CSM or SEMM because they rely on the composition of seed/seedling pools and not seed/seedling counts such as IM or GSM. This has important consequences for life stage studies where the discordance of dispersal kernels estimated from different cohorts is used to investigate post-dispersal density-dependent mortality.