The concepts of similarity and difference have been intrinsic to community ecology since its early origins. Many ecological questions can only be expressed in terms of distances: spatial structure, but also community similarity/dissimilarity. The clearest and most direct approach to these kinds of questions requires working with these symmetrical dissimilarity matrices directly. This chapter presents a general workflow within the dissimilarity-based analysis framework. The key analyses—correlation, ordination, and spatial correlation—are demonstrated with R code using the ecodist package for a sample dataset from the Rocky Mountains. The likely driving variables in this region are geographic distance and elevation. Do changes in these variables relate to changes in plant community composition? Do sites that are farther apart in space have less similar vegetation? What about sites that differ in elevation? Key decision points within the workflow are highlighted, making it possible to adapt this framework for other systems and other research questions.