Essential Biodiversity Variables (EBVs) are a set of standardized biological measurements that help scientists study, report and manage changes in biodiversity across time, space, and biological level. They bridge the gap between raw biodiversity data and derived policy-relevant indicators, and have the potential to serve as a foundation for biodiversity monitoring programs around the world (Pereira et al. 2013).
Biodiversity is defined to include genes, species, traits, community composition, and ecosystems. Data on one or more of these dimensions over time and space support biodiversity assessments in marine, terrestrial, and freshwater areas. Information on how biodiversity changes in these environments is necessary for policy-making. In order to detect change, systematic biodiversity observations are collected using standard formats and methods, together with environmental monitoring. These observational data are moved to open databases. Ensuring that data are interoperable across databases will make efficient use of biodiversity information for guiding conservation and sustainable development strategies.
Essential variables to understand climate, biodiversity, and other environmental changes have already been developed (e.g. Essential Climate Variables, Essential Ocean Variables). The concept of Essential Biodiversity Variables (EBVs) was introduced to advance the collection, sharing, and use of biodiversity information (Pereira et al. 2013; Navarro et al. 2017), providing a way to aggregate the many biodiversity observations collected through different methods such as in situ monitoring or remote sensing. EBVs can be visualised as biodiversity observations at one location over time, or in many locations, aggregated in a time series of maps.
The process towards operationalising EBVs is shown in the accompanying figure. Filling the EBV cube requires collecting biodiversity observations by people and groups, depositing raw data into databases using standard formats and metadata, and processing the data (upper box). The information in the EBV cube helps to detect and model biodiversity change for science, policy, and sustainable development applications (lower box). The underlying drivers and pressures of biodiversity change can then be identified (Mace and Baillie 2007) and modelled (Oliver et al. 2015). Validation of modelling can then feed into global and regional policy processes to explain observations, to improve forecasting of biodiversity change, and to produce global assessment reports.
EBVs are scalable, meaning the underlying observations can be used to represent different spatial or temporal resolutions required for the analysis of trends. For example, ecological community data collected at a location from different sampling events or methods can be combined into a single time series. The aggregated data may indicate the change in ecological communities across the region.
When combined with social or economic information from human or environmental pressures, EBVs can be used to identify indicators for biodiversity that reflect responses, for example change in the proportion of habitat in PAs and ecosystem service benefits to humans.
Developing and applying EBVs requires local, national, and international adoption of standard approaches to collect, store, and share biodiversity and environmental observations. This is fundamental to address the pressing societal and economic needs of today and in the future.
EBV classes and names
There are 6 EBV classes and 21 EBV names. By clicking on the icon you will get more detailed information.
| EBV class | EBV name |
|---|---|
|
Genetic composition
|
Genetic diversity (richness and heterozygosity) |
| Genetic differentiation (number of genetic units and genetic distance) | |
| Effective population size | |
| Inbreeding | |
|
Species populations
|
Species distributions |
| Species abundances | |
|
Species traits
|
Morphology |
| Physiology | |
| Phenology | |
| Movement | |
| Reproduction | |
|
Community composition
|
Community abundance |
| Taxonomic/phylogenetic diversity | |
| Trait diversity | |
| Interaction diversity | |
|
Ecosystem functioning
|
Primary productivity |
| Ecosystem phenology | |
| Ecosystem disturbances | |
|
Ecosystem structure
|
Live cover fraction |
| Ecosystem distribution | |
| Ecosystem Vertical Profile |
Genetic populations
The spatial and temporal variability in the distribution and abundance of species populations.
| EBV name | EBV description |
|---|---|
| Intraspecific genetic diversity | The variation in DNA sequences among individuals of the same species. |
| Genetic differentiation | Divergence in genetic composition (identity and frequencies of alleles) among multiple populations. |
| Effective population size | The number of individuals in an idealized population that will exhibit the same amount of genetic diversity loss as the population under consideration. |
| Inbreeding | Mating between related individuals. |
Species populations
The spatial and temporal variability in the distribution and abundance of species populations.
| EBV name | EBV description |
|---|---|
| Species distributions | The species occurrence probability over contiguous spatial and temporal units addressing the global extent of a species group. |
| Species abundances | Predicted count of individuals over contiguous spatial and temporal units addressing the global extent of a species group. |
Species traits
Within-species variation in trait measurements along the axis of taxonomic diversity.
| EBV name | EBV description |
|---|---|
| Morphology | The variation in physical attributes of organisms of the same species. |
| Physiology | Chemical or physical functions promoting organism fitness and responses to environment. |
| Phenology | Presence, absence, abundance or duration of seasonal activities of organisms. |
| Movement | Behaviors related to the spatial mobility of organisms such as dispersal and migration routes. |
| Reproduction | Sexual or asexual production of new individual organisms (‘offspring’) from parents. Examples: Age at maturity, number of offspring, lifetime reproductive output. |
Community composition
The abundance and diversity of organisms making up ecosystems.
| EBV name | EBV description |
|---|---|
| Community abundance | The abundance of organisms in ecological assemblages. |
| Taxonomic/phylogenetic diversity | The diversity of species identities, and/or phylogenetic positions, of organisms in ecological assemblages. |
| Trait diversity | The diversity of functional traits of organisms in ecological assemblages. |
| Interaction diversity | The diversity and structure of multi-trophic interactions between organisms in ecological assemblages. |
Ecosystem functioning
Attributes related to the performance of ecosystems that result from the collective activities of its organisms.
| EBV name | EBV description |
|---|---|
| Primary productivity | The rate at which energy is transformed into organic matter primarily through photosynthesis. |
| Ecosystem phenology | Duration and magnitude of cyclic processes observed at the ecosystem level, such as in vegetation activity, phytoplankton blooms, etc. |
| Ecosystem disturbances | Abrupt deviances in the functioning of the ecosystem from its regular dynamics. |
Ecosystem structure
The spatial arrangement of ecosystem units collectively defined by organisms forming these units.
| EBV name | EBV description |
|---|---|
| Live cover fraction | The horizontal (or projected) fraction of area covered by living organisms, such as vegetation, macroalgae or live hard coral. |
| Ecosystem distribution | The horizontal distribution of discrete ecosystem units. |
| Ecosystem Vertical Profile | The vertical distribution of biomass in ecosystems, above and below the land surface. |
References
Balvanera, P., Brauman, K.A., Cord, A.F., Drakou, E.G., Geijzendorffer, I.R., Karp, D.S., et al. (2022). Essential ecosystem service variables for monitoring progress towards sustainability. Curr. Opin. Environ. Sustain., 54, 101152. Mace, G.M. & Baillie, J.E.M. (2007). The 2010 biodiversity indicators: challenges for science and policy. Conserv. Biol., 21, 1406–1413. Navarro, L.M., Fernández, N., Guerra, C., Guralnick, R., Kissling, W.D., Londoño, M.C., et al. (2017). Monitoring biodiversity change through effective global coordination. Curr. Opin. Environ. Sustain., 29, 158–169. Oliver, T.H., Heard, M.S., Isaac, N.J.B., Roy, D.B., Procter, D., Eigenbrod, F., et al. (2015). Biodiversity and resilience of ecosystem functions. Trends Ecol. Evol., 30, 673–684. Pereira, H.M., Ferrier, S., Walters, M., Geller, G.N., Jongman, R.H.G., Scholes, R.J., et al. (2013). Essential biodiversity variables. Science, 339, 277–278. Schmeller, D.S., Mihoub, J.-B., Bowser, A., Arvanitidis, C., Costello, M.J., Fernandez, M., et al. (2017). An operational definition of essential biodiversity variables. Biodivers Conserv, 26, 2967–2972.