Species richness has dominated our view of global biodiversity patterns for centuries. The dominance of this paradigm is reflected in the focus by ecologists and conservation managers on richness and associated occurrence-based measures for understanding drivers of broad-scale diversity patterns and as a biological basis for management. However, this is changing rapidly, as it is now recognized that not only the number of species but the species present, their phenotypes and the number of individuals of each species are critical in determining the nature and strength of the relationships between species diversity and a range of ecological functions (such as biomass production and nutrient cycling). Integrating these measures should provide a more relevant representation of global biodiversity patterns in terms of ecological functions than that provided by simple species counts. Here we provide comparisons of a traditional global biodiversity distribution measure based on richness with metrics that incorporate species abundances and functional traits. We use data from standardized quantitative surveys of 2,473 marine reef fish species at 1,844 sites, spanning 133 degrees of latitude from all ocean basins, to identify new diversity hotspots in some temperate regions and the tropical eastern Pacific Ocean. These relate to high diversity of functional traits amongst individuals in the community (calculated using Rao's Q), and differ from previously reported patterns in functional diversity and richness for terrestrial animals, which emphasize species-rich tropical regions only. There is a global trend for greater evenness in the number of individuals of each species, across the reef fish species observed at sites ('community evenness'), at higher latitudes. This contributes to the distribution of functional diversity hotspots and contrasts with well-known latitudinal gradients in richness. Our findings suggest that the contribution of species diversity to a range of ecosystem functions varies over large scales, and imply that in tropical regions, which have higher numbers of species, each species contributes proportionally less to community-level ecological processes on average than species in temperate regions. Metrics of ecological function usefully complement metrics of species diversity in conservation management, including when identifying planning priorities and when tracking changes to biodiversity values.

Networks of citizen scientists (CS) have the potential to observe biodiversity and species distributions at global scales. Yet the adoption of such datasets in conservation science may be hindered by a perception that the data are of low quality. This perception likely stems from the propensity of data generated by CS to contain greater levels of variability (e.g., measurement error) or bias (e.g., spatio-temporal clustering) in comparison to data collected by scientists or instruments. Modern analytical approaches can account for many types of error and bias typical of CS datasets. It is now possible to (1) describe how the sampling process influences the overall variability in response data using mixed-effects modeling, (2) integrate data to explicitly model the sampling process and account for bias using a hierarchical modeling framework, and (3) examine the relative influence of many different or related explanatory factors using machine learning tools. Information from these modeling approaches can further be incorporated into predictions of species distributions and estimates of biodiversity. By detailing how CS data are generated, patterns can be discerned from complex datasets that are unevenly distributed and collected by many observers with varying skill levels. Even so, gaining the full potential from even the best designed CS projects requires meta-data describing the sampling process, reference data to allow for standardization, and insightful modeling suitable to the type of response data of interest.

MotivationThe BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community‐led open‐source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.Main types of variables includedThe database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.Spatial location and grainBioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2).Time period and grainBioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.Major taxa and level of measurementBioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.Software format.csv and .SQL.

The worldwide decline of coral reefs necessitates targeting management solutions that can sustain reefs and the livelihoods of the people who depend on them. However, little is known about the context in which different reef management tools can help to achieve multiple social and ecological goals. Because of nonlinearities in the likelihood of achieving combined fisheries, ecological function, and biodiversity goals along a gradient of human pressure, relatively small changes in the context in which management is implemented could have substantial impacts on whether these goals are likely to be met. Critically, management can provide substantial conservation benefits to most reefs for fisheries and ecological function, but not biodiversity goals, given their degraded state and the levels of human pressure they face.

Ectotherms generally shrink under experimental warming, but whether this pattern extends to wild populations is uncertain. We analysed ten million visual survey records, spanning the Australian continent, multiple decades and comprising all common coastal reef fish (335 species). We found that temperature indeed drives spatial and temporal changes in fish body size, but not consistently in the negative fashion expected. Around 55% of species were smaller in warmer waters (especially among small-bodied species) while 45% were bigger. The direction of a species' response to temperature through space was generally consistent with its response to temperature increase at any given location, suggesting that spatial trends could help forecast fish responses to warming. However, temporal changes were ~10x faster than spatial trends (~4% versus ~40% body size change per 1°C change through space and time respectively). The rapid and variable responses of