A model-based approach to studying changes in compositional heterogeneity.

Non-random species loss and gain in local communities change the compositional heterogeneity between communities over time, which is traditionally quantified with dissimilarity-based approaches. Yet, dissimilarities summarize the multivariate species data into a univariate index and obscure the species-level patterns of change, which are central to understand the causes and consequences of the community changes., Here, we propose a model-based approach that looks for species-level effects of time period and construct a multiple-site metric as a sum across species to test the consistency of the individual species responses. Species fall into different response types, showing how they influence the changes in community heterogeneity., In a comparison with other multiple-site metrics, we illustrate the properties of our method and the differences and similarities with other approaches. For instance, our metric estimates the total variation in a community data set based on species-level contributions, not the compositional dissimilarities between particular sites. Similar to some other approaches, we can distinguish between heterogeneity derived from turnover or richness differences., Our approach was applied to a set of 23 forest understorey resurvey studies spread across Europe. We show the species gains and losses may as well decrease or increase levels of community heterogeneity. Although species occurrences and communities have not changed in a consistent way along continental-scale environmental gradients such as climatic conditions, several species shifted in a similar way across the different data sets., Testing the significance of shifts in species prevalence over time to infer corresponding changes in the compositional heterogeneity among sites provides a very intuitive tool for community resurvey studies. The main strengths of our framework are the explicit consideration of the relative roles of species gains and losses and the straightforward generalization to different sets of hypotheses related to community changes. [ABSTRACT FROM AUTHOR]