The definition of ‘long-term’ requires reference to the generation time and the scale over which environmental variation of interest operates. A long-term (large temporal scale) population study of an annually reproducing insect would be expected to include annual population estimates over at least ten years. An equivalent study of an amoeba, which can reproduce daily, might be completed in a few weeks. However, if the focus of a long-term study is the role of seasonal variation in determining population number, then it is likely that a study will need at least twenty-five years of data, irrespective of the size of the organism and the generation time. This chapter reviews a range of time series analytical techniques and presents R code listings for measuring synchrony and species associations, detecting break-points in time series and measuring community stability. Statistical methods to assess if a species has gone extinct are described. Techniques for detecting density dependence in time series are reviewed. Temporal β-diversity is defined as the shift in the identities and/or the abundances of named taxa in a specified assemblage over two or more time points. The measurement of temporal β-diversity is discussed. Numerous R code listings are presented.