Goodness-of-fit measures of evenness: a new tool for exploring changes in community structure

Growing concern about the fate of biodiversity, highlighted by the Convention on Biological Diversity's 2010 and 2020 targets for stemming biodiversity loss, has intensified interest in methods of assessing change in ecological communities through time. Biodiversity is a multivariate concept, which cannot be well-represented by a single measure. However, diversity profiles summarize the multivariate nature of multi-species datasets, and allow a more nuanced interpretation of biodiversity trends than unitary metrics. Here we introduce a new approach to diversity profiling. Our method is based on the knowledge that an ecological community is never completely even and uses this departure from perfect evenness as a novel and insightful way of measuring diversity. We plot our measure of departure as a function of a free parameter, to generate evenness profiles. These profiles allow us to separate changes due to dominant species from those due to rare species, and relate these patterns to shifts in overall diversity. This separation of the influence of dominance and rarity on overall diversity enables the user to uncover changes in diversity that would be masked in other methods. We discuss profiling techniques based on this parametric family, and explore its connections with existing diversity indices. Next, we evaluate our approach in terms of predicted community structure (following Tokeshi's niche models) and present an example assessing temporal trends in diversity of British farmland birds. We conclude that this method is an informative and tractable parametric approach for quantifying evenness. It provides novel insights into community structure, revealing the contributions of both rare and common species to biodiversity trends.