There is considerable interest in understanding patterns of β‐diversity that measure the amount of change in species composition through space or time. Most hypotheses for β‐diversity evoke nonrandom processes that generate spatial and temporal within‐species aggregation; however, β‐diversity can also be driven by random sampling processes. Here, we describe a framework based on rarefaction curves that quantifies the nonrandom contribution of species compositional differences across samples to β‐diversity. We isolate the effect of within‐species spatial or temporal aggregation on beta‐diversity using a coverage standardized metric of β‐diversity (βC). We demonstrate the utility of our framework using simulations and an empirical case study examining variation in avian species composition through space and time in engineered versus natural riparian areas. The primary strengths of our approach are that it provides an intuitive visual null model for expected patterns of biodiversity under random sampling that allows integrating analyses across α‐, γ‐, and β‐scales. Importantly, the method can accommodate comparisons between communities with different species pool sizes, and it can be used to examine species turnover both within and between meta‐communities.

Aim: Many insect species are facing existential crises, primarily due to diverse human activities. Most insect assessments, however, are based on relatively short time series or some iconic species. Here, we assess how the occupancy of ground beetles has changed in Germany over the last 36 years. Location: Germany. Methods: In close collaboration with taxonomic experts from natural history societies, we compiled the best available occurrence data for ground beetles in Germany, estimated the changes in species occupancy over time, and related these changes to species traits and characteristics. Results: We obtained trends for 383 species and found that 52% of species significantly declined, and 22% significantly increased in site occupancy over the last 36 years. The remainder of the species (26%) all showed a mean negative trend, albeit nonsignificant. Species classified as non-threatened in the German red list declined at a similar rate as threatened species, with 64% of the Near Threatened species experiencing significant declines (highest among all red list categories). Across all traits, we found that large (compared to medium-sized) and omnivore (compared to predator) species declined less. Conclusions: Since ground beetles are key predators in many natural and agricultural ecosystems that play an important role in pest control and the food chain, their decline should raise concerns. Thus, we urgently plead for more harmonised and systematic monitoring of this insect group.

It is commonly thought that the biodiversity crisis includes widespread declines in the spatial variation of species composition, called biotic homogenization. Using a typology relating homogenization and differentiation to local and regional diversity changes, we synthesize patterns across 461 metacommunities surveyed for 10 to 91 years, and 64 species checklists (13 to 500+ years). Across all datasets, we found that no change was the most common outcome, but with many instances of homogenization and differentiation. A weak homogenizing trend of a 0.3% increase in species shared among communities/year on average was driven by increased numbers of widespread (high occupancy) species and strongly associated with checklist data that have longer durations and large spatial scales. At smaller spatial and temporal scales, we show that homogenization and differentiation can be driven by changes in the number and spatial distributions of both rare and common species. The multiscale perspective introduced here can help identify scale-dependent drivers underpinning biotic differentiation and homogenization.

Emerging technologies are increasingly employed in environmental citizen science projects. This integration offers benefits and opportunities for scientists and participants alike. Citizen science can support large-scale, long-term monitoring of species occurrences, behaviour and interactions. At the same time, technologies can foster participant engagement, regardless of pre-existing taxonomic expertise or experience, and permit new types of data to be collected. Yet, technologies may also create challenges by potentially increasing financial costs, necessitating technological expertise or demanding training of participants. Technology could also reduce people's direct involvement and engagement with nature. In this perspective, we discuss how current technologies have spurred an increase in citizen science projects and how the implementation of emerging technologies in citizen science may enhance scientific impact and public engagement. We show how technology can act as (i) a facilitator of current citizen science and monitoring efforts, (ii) an enabler of new research opportunities, and (iii) a transformer of science, policy and public participation, but could also become (iv) an inhibitor of participation, equity and scientific rigour. Technology is developing fast and promises to provide many exciting opportunities for citizen science and insect monitoring, but while we seize these opportunities, we must remain vigilant against potential risks. This article is part of the theme issue ‘Towards a toolkit for global insect biodiversity monitoring’.

Today, at the international level, powerful data portals are available to biodiversity researchers and policymakers, offering increasingly robust computing and network capacities and capable data services for internationally agreed-on standards. These accelerate individual and complex workflows to map data-driven research processes or even to make them possible for the first time. At the national level, however, and alongside these international developments, national infrastructures are needed to take on tasks that cannot be easily funded or addressed internationally. To avoid gaps, as well as redundancies in the research landscape, national tasks and responsibilities must be clearly defined to align efforts with core priorities. In the present article, we outline 10 essential functions of national biodiversity data infrastructures. They serve as key providers, facilitators, mediators, and platforms for effective biodiversity data management, integration, and analysis that require national efforts to foster biodiversity science, policy, and practice.

Aim: Theoretical, experimental and observational studies have shown that biodiversity-ecosystem functioning (BEF) relationships are influenced by functional community structure through two mutually non-exclusive mechanisms: (1) the dominance effect (which relates to the traits of the dominant species); and (2) the niche partitioning effect [which relates to functional diversity (FD)]. Although both mechanisms have been studied in plant communities and experiments at small spatial extents, it remains unclear whether evidence from small-extent case studies translates into a generalizable macroecological pattern. Here, we evaluate dominance and niche partitioning effects simultaneously in grassland systems world-wide.Location: Two thousand nine hundred and forty-one grassland plots globally.Time period: 2000-2014.Major taxa studied: Vascular plants.Methods: We obtained plot-based data on functional community structure from the global vegetation plot database "sPlot ", which combines species composition with plant trait data from the "TRY " database. We used data on the community-weighted mean (CWM) and FD for 18 ecologically relevant plant traits. As an indicator of primary productivity, we extracted the satellite-derived normalized difference vegetation index (NDVI) from MODIS. Using generalized additive models and deviation partitioning, we estimated the contributions of trait CWM and FD to the variation in annual maximum NDVI, while controlling for climatic variables and spatial structure.Results: Grassland communities dominated by relatively tall species with acquisitive traits had higher NDVI values, suggesting the prevalence of dominance effects for BEF relationships. We found no support for niche partitioning for the functional traits analysed, because NDVI remained unaffected by FD. Most of the predictive power of traits was shared by climatic predictors and spatial coordinates. This highlights the importance of community assembly processes for BEF relationships in natural communities.Main conclusions: Our analysis provides empirical evidence that plant functional community structure and global patterns in primary productivity are linked through the resource economics and size traits of the dominant species. This is an important test of the hypotheses underlying BEF relationships at the global scale.

It is commonly thought that the biodiversity crisis includes widespread decreases in the uniqueness of different sites in a landscape (biotic homogenization). Using a typology relating homogenization and differentiation to local and regional diversity changes, we synthesize patterns across 283 metacommunities surveyed for 10-91 years, and 54 species checklists (13-500+ years). On average, there is a 0.2% increase in species shared among communities/year (i.e., weak homogenization), but across data sets, differentiation frequently occurs, with no statistically significant change being most common. Local (not regional) diversity frequently underlies composition change, and homogenization is strongly associated with checklist data that have longer durations and large spatial scales. Conservation and management can benefit from the multiscale perspective used here as it disentangles the implications of both the differentiation and homogenization currently unfolding. One-Sentence Summary Biotic homogenization is most prevalent at large temporal and spatial scales.

Patterns of biodiversity provide insights into the processes that shape biological communities around the world. Variation in species diversity along biogeographical or ecological gradients, such as latitude or precipitation, can be attributed to variation in different components of biodiversity: changes in the total abundance (i.e. more-individual effects) and changes in the regional species abundance distribution (SAD). Rarefaction curves can provide a tool to partition these sources of variation on diversity, but first must be converted to a common unit of measurement. Here, we partition species diversity gradients into components of the SAD and abundance using the effective number of species (ENS) transformation of the individual-based rarefaction curve. Because the ENS curve is unconstrained by sample size, it can act as a standardized unit of measurement when comparing effect sizes among different components of biodiversity change. We illustrate the utility of the approach using two datasets spanning latitudinal diversity gradients in trees and marine reef fish, and find contrasting results. Whereas the diversity gradient of fish was mostly associated with variation in abundance (86%), the tree diversity gradient was mostly associated with variation in the SAD (59%). These results suggest that local fish diversity may be limited by energy through the more-individuals effect, while species pool effects are the larger determinant of tree diversity. We suggest that the framework of the ENS-curve has the potential to quantify the underlying factors influencing most aspects of diversity change.

Understanding how species are non-randomly distributed in space, as well as how the resulting spatial structure of diversity responds to ecological, biogeographic and anthropogenic drivers is a critical piece of the biodiversity puzzle. However, most metrics that quantify the spatial structure of diversity (i.e., community differentiation), such as Whittaker’s classical β-diversity metric are influenced by sampling effects. As a result, these measures are influenced by species pool size, species abundance distributions and numbers of individuals. Null models have been proposed to evaluate the degree of differentiation among communities due to spatial structuring relative to that expected from sampling effects. However, to date, these null models do not accommodate the influence of sample completeness (i.e. the proportion of the species pool in the sample). Here, we develop an approach that makes use of individual- and coverage-based rarefaction and extrapolation. Using spatially explicit simulations, we show that our derived metric, βC, captures changes in intraspecific aggregation independently of changes in the species pool size. We then provide two case studies examining spatial structure in forest plots spanning latitudinal gradients: (1) a re-analysis of the “Gentry” plot dataset, and (2) comparing a high diversity plot in Barro Colorado Island, Panama with a low diversity plot in Harvard Forest, Massachusetts, USA. We find no evidence for systematic changes in spatial structure with latitude in these datasets. As it is rooted in biodiversity sampling theory and explicitly controls for sample completeness, our approach represents an important advance over existing null models for spatial aggregation. Potential applications of the approach range from better descriptors of biogeographic diversity patterns to the consolidation of local and regional diversity trends in the current biodiversity crisis. Open research statement The novel code for the calculation of βC can be found in supplementary material S4. Empirical data sets utilized for this research are as follows: Phillips & Miller (2002), Orwig et al. (2015), Condit et al. (2019). Our research repository including the novel code is also available at https://github.com/t-engel/betaC and will be uploaded to Zenodo upon acceptance of this manuscript.

Disentangling the drivers of diversity gradients can be challenging. The Measurement of Biodiversity (MoB) framework decomposes changes in species diversity into three components of community structure: the species abundance distribution (SAD), the total community abundance, and the within-species spatial aggregation. Here we extend MoB from categorical treatment comparisons to quantify variation along continuous geographic or environmental gradients. Our approach requires sites along a gradient, each consisting of georeferenced plots of abundance-based species composition data. We demonstrate our method using a case study of ants sampled along an elevational gradient of 28 sites in mixed deciduous forest of the Great Smoky Mountains National Park, USA. MoB analysis revealed that ant species richness decreased along the elevational gradient because of changes in the SAD and in spatial aggregation, but not because of changes in the number of individuals. Specifically, with increasing elevation, species evenness was lower and species were less aggregated. These results do not support the more-individuals hypothesis; alternative hypotheses are required to explain why evenness and aggregation decrease with elevation. Our extension of MoB has the potential to elucidate the drivers of diversity along environmental gradients and should be useful for a variety of assemblage-level data collected along gradients.

Little consensus has emerged regarding how proximate and ultimate drivers such as productivity, disturbance, and temperature may affect species richness and other aspects of biodiversity. Part of the confusion is that most studies examine species richness at a single spatial scale and ignore how the underlying components of species richness can vary with spatial scale. We provide an approach for the measurement of biodiversity (MoB) that decomposes changes in species rarefaction curves into proximate components attributed to: 1) the species abundance distribution, 2) density of individuals, and 3) the spatial arrangement of individuals. We decompose species richness by comparing spatial and nonspatial sample- and individual-based species rarefaction curves that differentially capture the influence of these components to estimate the relative importance of each in driving patterns of species richness change. We tested the validity of our method on simulated data, and we demonstrate it on empirical data on plant species richness in invaded and uninvaded woodlands. We integrated these methods into a new R package ( mobr ). The metrics that mobr provides will allow ecologists to move beyond comparisons of species richness in response to ecological drivers at a single spatial scale towards a dissection of the proximate components that determine species richness across scales.