Studies using tree-rings to reconstruct forest disturbance dynamics are common and their number has been increasing in the recent years. Despite the evident need for a common set of tools for verification, replication and comparison across studies, only a few DOS programmes for disturbance detection exist and they are for limited purposes only. Currently, the ideal statistical environment for the task is R, which is becoming the primary tool for various types of tree-ring analyses. This has led to the development of TRADER (Tree Ring Analysis of Disturbance Events in R), an open-source software package for R that provides an analysis of tree growth history for disturbance reconstructions. We have implemented four methods, which are commonly used for the detection of disturbance events: radial-growth averaging criteria developed by Nowacki and Abrams (1997), the boundary-line method (Black and Abrams, 2003), the absolute-increase method (Fraver and White, 2005), and the combination of radial-growth averaging and boundary-line techniques (Splechtna et al., 2005). TRADER, however, enables the analysis of disturbance history by a total of 24 published methods. Furthermore, functions for the detection of tree recruitment and growth trends were also included. The main features of the presented package are described and their application is shown on a real tree-ring datasets. The package requires little knowledge of the R environment giving straightforward analyses with suitable parameters, but at the same time it is easily modifiable by the more experienced user. The package improves research efficiency and facilitates replication of previous studies. One of its major advantages is that it offers the possibility for comparison between different methods of disturbance history reconstruction.