Species diversity may be additively partitioned within and among samples (alpha and beta diversity) from hierarchically scaled studies to assess the proportion of the total diversity (gamma) found in different habitats, landscapes, or regions. We developed a statistical approach for testing null hypotheses that observed partitions of species richness or diversity indices differed from those expected by chance, and we illustrate these tests using data from a hierarchical study of forest-canopy beetles. Two null hypotheses were implemented using individual- and sample-based randomization tests to generate null distributions for alpha and beta components of diversity at multiple sampling scales. The two tests differed in their null distributions and power to detect statistically significant diversity components. Individual-based randomization was more powerful at all hierarchical levels and was sensitive to departures between observed and null partitions due to intraspecific aggregation of individuals. Sample-based randomization had less power but still may be useful for determining whether different habitats show a higher degree of differentiation in species diversity compared with random samples from the landscape. Null hypothesis tests provide a basis for inferences on partitions of species richness or diversity indices at multiple sampling levels, thereby increasing our understanding of how alpha and beta diversity change across spatial scales.

Ecologists have traditionally viewed the total species diversity within a set of communities as the product of the average diversity within a community (alpha) and the diversity among the communities (beta). This multiplicative concept of species diversity contrasts with the lesser known idea that α‐ and β‐diversities sum to give the total diversity. This additive partitioning of species diversity is nearly as old as the multiplicative concept, yet ecologists are just now beginning to use additive partitioning to examine patterns of species diversity. In this review we discuss why additive partitioning remained “hidden” until just a few years ago. The rediscovery of additive partitioning has expanded the way in which ecologists define and measure β‐diversity. Beta diversity is no longer relegated to describing change only along an environmental gradient. Through additive partitioning, β‐diversity is explicitly an average amount of diversity just as is α‐diversity. We believe that the additive partitioning of diversity into α and β components will continue to become more widely used because it allows for a direct comparison of α‐ and β‐diversities. It also has particular relevance for testing ecological theory concerned with the determinants of species diversity at multiple spatial scales and potential applications in conservation biology.

There is a lack of quantitative syntheses of fragmentation effects across species and biogeographic regions, especially with respect to species life-history traits. We used data from 24 independent studies of butterflies and moths from a wide range of habitats and landscapes in Europe and North America to test whether traits associated with dispersal capacity, niche breadth and reproductive rate modify the effect of habitat fragmentation on species richness. Overall, species richness increased with habitat patch area and connectivity. Life-history traits improved the explanatory power of the statistical models considerably and modified the butterfly species-area relationship. Species with low mobility, a narrow feeding niche and low reproduction were most strongly affected by habitat loss. This demonstrates the importance of considering life-history traits in fragmentation studies and implies that both species richness and composition change in a predictable manner with habitat loss and fragmentation.

The PREDICTS project—Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)—has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of human impacts relating to land use. We have used this evidence base to develop global and regional statistical models of how local biodiversity responds to these measures. We describe and make freely available this 2016 release of the database, containing more than 3.2 million records sampled at over 26,000 locations and representing over 47,000 species. We outline how the database can help in answering a range of questions in ecology and conservation biology. To our knowledge, this is the largest and most geographically and taxonomically representative database of spatial comparisons of biodiversity that has been collated to date; it will be useful to researchers and international efforts wishing to model and understand the global status of biodiversity.

The primary emphasis of conservation biology has moved away from attempting to manage single species within a given habitat to the preservation of entire communities within ecoregions, requiring that greater attention be paid to how biodiversity and species composition vary across spatial scales. Using a nested sampling design, we examined spatial variation in the biodiversity of forest Lepidoptera across three hierarchical levels: 20 forest stands, five sites, and three ecoregions. We used blacklight traps to sample the moth communities of each forest stand every week in June and August of 2000. Lepidopteran community composition was most significantly influenced by ecoregional differences, whereas patterns of α and β diversity across scales differed depending on how diversity was measured. Diversity partitioning models demonstrated that turnover in species richness occurred equally across all spatial scales because numerically rare species were continually encountered. In contrast, within‐stand effects disproportionately influenced Simpson and Shannon diversity ( relative to outcomes from randomization tests ), suggesting that local factors determined species dominance. Because most Lepidoptera in forests appear to be rare ( >50% ), it will be impossible for conservation biologists to design management plans to account for every species. We suggest that a more meaningful strategy would be to identify species that attain a reasonable abundance within a community ( 5–10% of all the individuals in a sample ) and that are unique to particular spatial levels. This strategy should produce two desirable outcomes: the conservation of species that render ecoregions distinct and the maintenance of functionally dominant species within forests.