Similarity analyses in restoration ecology and how to improve their utility

Use of multivariate and nonparametric statistical analyses such as similarity percentages analysis has increased in the past decade within restoration studies. While very useful to compare community composition of restored habitats to reference areas, the ease in which these analyses can be applied, coupled with their power, can result in interpretation errors that could have negative ramifications upon restoration projects. Primarily, similarity measures are often used without stipulating similarity or dissimilarity targets. Despite these drawbacks, the benefits of these methods far outweigh the risks, especially if practitioners take care to specify their community similarity targets a priori and base these targets upon a representative range of reference conditions. However, restoration practitioners should remain focused on fulfilling the objectives of ecological restoration, by ensuring the development of functional habitat that is informed, but not dictated by, statistical analyses. As such, practitioners should take steps to ensure that meaningful univariate trends (e.g. an important species at risk or invasive species) and the overall functionality of the habitat should not be neglected, in favor of these methods of data analysis.