A recent increase in studies of b diversity has yielded a confusing array of concepts, measures and methods. Here, we provide a roadmap of the most widely used and ecologically relevant approaches for analysis through a series of mission statements. We distinguish two types of b diversity: directional turnover along a gradient vs. non-directional variation. Different measures emphasize different properties of ecological data. Such properties include the degree of emphasis on presence ⁄ absence vs. relative abundance information and the inclusion vs. exclusion of joint absences. Judicious use of multiple measures in concert can uncover the underlying nature of patterns in b diversity for a given dataset. A case study of Indonesian coral assemblages shows the utility of a multi-faceted approach. We advocate careful consideration of relevant questions, matched by appropriate analyses. The rigorous application of null models will also help to reveal potential processes driving observed patterns in b diversity.

Understanding the ecological consequences of biodiversity is a fundamental challenge. Research on a key component of biodiversity, genetic diversity, has traditionally focused on its importance in evolutionary processes, but classical studies in evolutionary biology, agronomy and conservation biology indicate that genetic diversity might also have important ecological effects. Our review of the literature reveals significant effects of genetic diversity on ecological processes such as primary productivity, population recovery from disturbance, interspecific competition, community structure, and fluxes of energy and nutrients. Thus, genetic diversity can have important ecological consequences at the population, community and ecosystem levels, and in some cases the effects are comparable in magnitude to the effects of species diversity. However, it is not clear how widely these results apply in nature, as studies to date have been biased towards manipulations of plant clonal diversity, and little is known about the relative importance of genetic diversity vs. other factors that influence ecological processes of interest. Future studies should focus not only on documenting the presence of genetic diversity effects but also on identifying underlying mechanisms and predicting when such effects are likely to occur in nature.

Understanding spatial variation in biodiversity along environmental gradients is a central theme in ecology. Differences in species compositional turnover among sites (β diversity) occurring along gradients are often used to infer variation in the processes structuring communities. Here, we show that sampling alone predicts changes in β diversity caused simply by changes in the sizes of species pools. For example, forest inventories sampled along latitudinal and elevational gradients show the well-documented pattern that β diversity is higher in the tropics and at low elevations. However, after correcting for variation in pooled species richness (γ diversity), these differences in β diversity disappear. Therefore, there is no need to invoke differences in the mechanisms of community assembly in temperate versus tropical systems to explain these global-scale patterns of β diversity.

Abstract. b-diversity represents the compositional variation among communities from site-to-site, linking local (a-diversity) and regional (c-diversity). Researchers often desire to compare values of bdiversity across localities or experimental treatments, and to use this comparison to infer possible mechanisms of community assembly. However, the majority of metrics used to estimate b-diversity, including most dissimilarity metrics (e.g., Jaccard's and Sørenson's dissimilarity index), can vary simply because of changes in the other two diversity components (a or c-diversity). Here, we overview the utility of taking a null model approach that allows one to discern whether variation in the measured dissimilarity among communities results more from changes in the underlying structure by which communities vary, or instead simply due to difference in a-diversity among localities or experimental treatments. We illustrate one particular approach, originally developed by Raup and Crick (1979) in the paleontological literature, which creates a re-scaled probability metric ranging from À1 to 1, indicating whether local communities are more dissimilar (approaching 1), as dissimilar (approaching 0), or less dissimilar (approaching À1), than expected by random chance. The value of this metric provides some indication of the possible underlying mechanisms of community assembly, in particular the degree to which deterministic processes create communities that deviate from those based on stochastic (null) expectations. We demonstrate the utility of this metric when compared to analyses of Jaccard's dissimilarity index with case studies from disparate empirical systems (coral reefs and freshwater ponds) that differ in the degree to which disturbance altered a-diversity, as well as the selectivity by which disturbance acted on members of the community.

While small‐scale studies show that more diverse native communities are less invasible by exotics, studies at large spatial scales often find positive correlations between native and exotic diversity. This large‐scale pattern is thought to arise because landscapes with favorable conditions for native species also have favorable conditions for exotic species. From theory, we proposed an alternative hypothesis: the positive relationship at large scales is driven by spatial heterogeneity in species composition, which is driven by spatial heterogeneity in the environment. Landscapes with more spatial heterogeneity in the environment can sustain more native and more exotic species, leading to a positive correlation of native and exotic diversity at large scales. In a nested data set for grassland plants, we detected negative relationships between native and exotic diversity at small spatial scales and positive relationships at large spatial scales. Supporting our hypothesis, the positive relationships between native and exotic diversity at large scales were driven by positive relationships between native and exotic beta diversity. Further, both native and exotic diversity were positively correlated with spatial heterogeneity in abiotic conditions (variance of soil depth, soil nitrogen, and aspect) but were uncorrelated with average abiotic conditions, supporting the spatial‐heterogeneity hypothesis but not the favorable‐conditions hypothesis.