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Institute
Motivation
The 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 included
The 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 grain
BioTIME 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 grain
BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.
Major taxa and level of measurement
BioTIME 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 research of a generation of ecologists was catalysed by the recognition that the number and identity of species in communities influences the functioning of ecosystems. The relationship between biodiversity and ecosystem functioning (BEF) is most often examined by controlling species richness and randomising community composition. In natural systems, biodiversity changes are often part of a bigger community assembly dynamic. Therefore, focusing on community assembly and the functioning of ecosystems (CAFE), by integrating both species richness and composition through species gains, losses and changes in abundance, will better reveal how community changes affect ecosystem function. We synthesise the BEF and CAFE perspectives using an ecological application of the Price equation, which partitions the contributions of richness and composition to function. Using empirical examples, we show how the CAFE approach reveals important contributions of composition to function. These examples show how changes in species richness and composition driven by environmental perturbations can work in concert or antagonistically to influence ecosystem function. Considering how communities change in an integrative fashion, rather than focusing on one axis of community structure at a time, will improve our ability to anticipate and predict changes in ecosystem function.
Aim
Biodiversity loss is a key component of biodiversity change and can impact ecosystem services. However, estimation of the loss has focused mostly on per-species extinction rates measured over a limited number of spatial scales, with little theory linking small-scale extirpations to global extinctions. Here, we provide such a link by introducing the relationship between area and the number of extinctions (number of extinctions–area relationship; NxAR) and between area and the proportion of extinct species (proportion of extinctions–area relationship; PxAR). Unlike static patterns, such as the species–area relationship, NxAR and PxAR represent spatial scaling of a dynamic process. We show theoretical and empirical forms of these relationships and we discuss their role in perception and estimation of the current extinction crisis.
Location
U.S.A., Europe, Czech Republic and Barro Colorado Island (Panama).
Time period
1500–2009.
Major taxa studied
Vascular plants, birds, butterflies and trees.
Methods
We derived the expected forms of NxAR and PxAR from several theoretical frameworks, including the theory of island biogeography, neutral models and species–area relationships. We constructed NxAR and PxAR from five empirical datasets collected over a range of spatial and temporal scales.
Results
Although increasing PxAR is theoretically possible, empirical data generally support a decreasing PxAR; the proportion of extinct species decreases with area. In contrast, both theory and data revealed complex relationships between numbers of extinctions and area (NxAR), including nonlinear, unimodal and U-shaped relationships, depending on region, taxon and temporal scale.
Main conclusions
The wealth of forms of NxAR and PxAR explains why biodiversity change appears scale dependent. Furthermore, the complex scale dependence of NxAR and PxAR means that global extinctions indicate little about local extirpations, and vice versa. Hence, effort should be made to understand and report extinction rates as a scale-dependent problem. In this effort, estimation of scaling relationships such as NxAR and PxAR should be central.