EBV class EBV candidate
Genetic composition Co-ancestry
Allelic diversity
Population genetic differentiation
Breed and variety diversity
Species populations Species distribution
Population abundance
Population structure by age/size class
Species traits Phenology
Morphology
Reproduction
Physiology
Movement
Community composition Taxonomic diversity
Species interactions
Ecosystem function Net primary productivity
Secondary productivity
Nutrient retention
Disturbance regime
Ecosystem structure Habitat structure
Ecosystem extent and fragmentation
Ecosystem composition by functional type

EBV class - Genetic composition


Co-ancestry

Measurement and scalability Temporal sensitivity Feasibility Relevance and related CBD 2020 targets
Pairwise relatedness among individuals or inbreeding coefficient of selected species, within and among populations of each species Generation time Available for many species but few populations, and little systematic sampling over time This variable provides a good measure of the genetic independence of allele frequencies among individuals and about their susceptibility to lowered fitness. Aichi Target: 12

Allelic diversity

Measurement and scalability Temporal sensitivity Feasibility Relevance and related CBD 2020 targets
Allelic richness from genotypes of selected species (e.g. endangered species and domesticated species) at multiple locations (statistically representative of the species distribution) Generation time Data avalailable for several species and for several locations, but little global systematic sampling It is one the most used variables to measure genetic diversity, and can support the estimation of indicators such as “Trends in genetic diversity of selected species” and the “Red List Index”. Aichi Targets: 12, 13

Population genetic differentiation

Measurement and scalability Temporal sensitivity Feasibility Relevance and related CBD 2020 targets
Gene frequency differentiation (Fst and other measures) among populations or of a subpopulation compared to the metapopulation of selected species Generation time Data available for many species but often for a limited number of populations. Easy to augment datasets It is one the most used variables to measure genetic diversity, and can support the estimation of indicators such as “Trends in genetic diversity of selected species” and the “Red List Index”. Aichi Targets: 12, 13

Breed and variety diversity

Measurement and scalability Temporal sensitivity Feasibility Relevance and related CBD 2020 targets
Number of animals of each livestock breed and proportion of farmed area under each local crop variety, at multiple locations 5 to 10 years Large datasets have been compiled by national organizations and FAO for livestock breeds, but there is insufficient systematic sampling for coverage of local crop varieties It is an essential variable to estimate the indicator “Trends in genetic diversity of domesticated animals and cultivated plants”. Aichi Target: 13

EBV class - Species populations


Species distribution

Measurement and scalability Temporal sensitivity Feasibility

Relevance and
related CBD 2020
targets

Presence surveys for groups of species easy to monitor, over an extensive network of sites with geographic representativeness. Potential role for incidental data from any spatial location 1 to >10 years Presence surveys are available for a larger number of species than population counts and can make use of existing distribution atlas. Some efforts for data compilation and integration exist (GBIF, IUCN, Map of Life). There is an increasing trend for data contributed by citizen scientists (Observado, iNaturalist) Abundance & distribution of populations/taxon per se is an intuitive biodiversity metric with public resonance. Abundance & distribution contributes to extinction risk indicators & indicators of supply of ES associated with particular spp. Range shifts expected under climate change. Aichi Targets: 4,5,6,7,8,9,10,11,12,14,15

Population abundance

Measurement and scalability Temporal sensitivity Feasibility Relevance and
related CBD 2020
targets
Population counts for groups of species easy to monitor and/or important for ecosystem services, over an extensive network of sites with geographic representativeness 1 year Population counts underway for a significant number of species in each of the following groups: birds, butterflies, mammals, plankton, important fisheries, coral reef fishes. Most of these extensive networks are geographically restricted. Much of the data are currently being collected by citizen science networks Abundance & distribution of populations/taxon per se is an intuitive biodiversity metric with public resonance. Abundance & distribution contributes to extinction risk indicators & indicators of supply of ES associated with particular spp. Range shifts expected under climate change. Aichi Targets: 4,5,6,7,8,9,10,11,12,14,15

Population structure by age/size class

Measurement and scalability Temporal sensitivity Feasibility Relevance and
related CBD 2020
targets
Quantity of individuals or biomass of a given demographic class of a given taxon or functional group at a given location 1 year Available for some managed species (hunting and fisheries), usually geographically restricted Abundance & distribution of populations/taxon per se is an intuitive biodiversity metric with public resonance. Abundance & distribution contributes to extinction risk indicators & indicators of supply of ES associated with particular spp. Range shifts expected under climate change. Aichi Targets: 4,5,6,7,8,9,10,11,12,14,15

EBV class - Species traits


Phenology

Measurement and scalability Temporal sensitivity Feasibility Relevance and related CBD 2020 targets
Presence, absence, abundance or duration of seasonal activities of organisms. Examples: Timing of breeding, flowering, fruiting, emergence, host infection and so on 1 year Several initiatives to collect plant phenology data at continental scales (e.g. USA, Europe), some making use of citizen science, integration in Global Plant Phenology Data Portal, standardized collection of bird migration phenology Aichi Targets: –
SDG: 13, 15

Morphology

Measurement and scalability Temporal sensitivity Feasibility Relevance and related CBD 2020 targets
Dimensions (for example, volume, mass and height), shape, other physical attributes of organisms. Examples: Body mass, plant height, cell volume, leaf area, wing length, colour and so on 1 - 5 years Animal body size data collected for selected species under harvesting pressure (e.g. marine fish) and for many birds and mammals, plant size data (e.g. stem height and diameter) collected in forest monitoring plots Aichi Targets: 6, 15
SDG: 2, 14

Reproduction

Measurement and scalability Temporal sensitivity Feasibility Relevance and related CBD 2020 targets
Sexual or asexual production of new individual organisms (‘offspring’) from parents. Examples: Age at maturity, number of offspring, lifetime reproductive output 1 to >10 years Limited data collection for selected plant and animal species Aichi Targets: 6, 9, 12
SDG: 14, 15

Physiology

Measurement and scalability Temporal sensitivity Feasibility Relevance and related CBD 2020 targets
Chemical or physical functions promoting organism fitness and responses to environment. Examples: Thermal tolerance, disease resistance, stoichiometry (for example, chlorophyll content) 1 to >10 years Data limited, but some available for corals, lizards, amphibians and insects, some remote sensing data collection with hyperspectral sensors (e.g. plant leaf chlorophyll and water content) Aichi Targets: 8, 10, 15
SDG: –

Movement

Measurement and scalability Temporal sensitivity Feasibility Relevance and related CBD 2020 targets
Behaviours related to the spatial mobility of organisms. Examples: Natal dispersal distance, migration routes, cell sinking of phytoplankton 1 to >10 years Banding/marking and GPS tracking data available for some birds, mammals, turtles, and fish, forthcoming animal tracking from space Aichi Targets: 9
SDG: –

EBV class - Community composition


Taxonomic diversity

Measurement and scalability Temporal sensitivity Feasibility Relevance and related CBD 2020 targets
Multi-taxa surveys (including by morphospecies) and metagenomics at selected in situ locations at consistent sampling scales over time. Hyper-spectral remote sensing over large ecosystems 5-10 years Many intensive long-term research sites have excellent but uncoordinated data, and there are abundant baseline data for many locations in the terrestrial, marine and freshwater realms. Metagenomics and the possibilities of remote sensing are emerging fields This is a basic measure of interaction of species: what species live together. It is the basis of comunity classification and ecosystem health assessments. Functional type composition of the ecosystem is often derived from species composition of observed communities. Aichi Targets: 8, 10, 12, 14

Species interactions

Measurement and scalability Temporal sensitivity Feasibility Relevance and related CBD 2020 targets
Studies of important interactions or interaction networks in selected communities, such as plant-bird seed dispersal systems 5-25 years Some studies have monitored the structure of species interaction networks such as mutualistic networks (pollination and seed dispersal), soil food webs, host-parasite and herbivore-plant interactions. There is a lack of global or regional representativeness of these studies Global change is affecting species interactions, which are determinant in ecosystem functioning and services. Aichi Targets: 7, 9, 14, 15

EBV class - Ecosystem function


Net primary productivity

Measurement and scalability Temporal sensitivity Feasibility Relevance and related CBD 2020 targets
Global mapping with modeling from remote sensing observations (FAPAR, ocean greenness) and selected in-situ locations (eddy covariance) <=1 year A network of regional networks of in-situ measurements exists (FLUXNET), and some global maps based on models and remote sensing are available. GCOS is also addressing this EBV Indicator of the energy flow through ecosystem and a measure of health/degradation; Support biodiveristy at multiple dimensions/trophic levels, regulates climate, impacts on human wellbeing, possible of indicator shifts into alternate ecosystem states; underpins all production-based ecosystem services. Aichi Targets: 5, 8, 14

Secondary productivity

Measurement and scalability Temporal sensitivity Feasibility Relevance and related CBD 2020 targets
Measurement of secondary productivity for selected functional groups, combining in-situ, remote sensing, and models. Example functional groups include: fisheries; livestock; krill; herbivorous birds 1 year FAO and national statistics on fish and livestock production Important to assess ecosystem functioning and ecosystem services. Aichi Targets: 6, 7, 14

Nutrient retention

Measurement and scalability Temporal sensitivity Feasibility Relevance and related CBD 2020 targets
Ratio of nutrient output from the system to nutrient input, measured at selected in situ locations. Can be combined with models and remote sensing to extrapolate regionally 1 year Some intensive monitoring sites have nitrogen saturation monitoring is some acid-deposition areas; phosphorus retention monitoring in some impacted rivers and estuaries Nutrient loss or accumulation affects biodiversity and ecosystems services. Aichi Targets: 5, 8, 14

Disturbance regime

Measurement and scalability Temporal sensitivity Feasibility Relevance and related CBD 2020 targets
Type, seasonal timing, intensity and frequency of event-based external disruptions to ecosystem processes and struture. Examples: sea surface temperature and salinity (RS); scatterometry for winds (RS); trawling pressure (in situ); flood regimes (in situ); fire frequency (in situ, RS); cultivation/ harvest (RS); windthrow; pests (in situ) 1 year Abundant data is avaliable for several perturbations, sometimes at the global scale, although harmonization and integration is needed Key determinant of ecosystem function, structure and composition; changes in the disturbance regime lead to changes in biodiversity. Aichi Targets: 5, 7, 9, 10, 11, 14, 15

EBV class - Ecosystem structure


Habitat structure

Measurement and scalability Temporal sensitivity Feasibility Relevance and related CBD 2020 targets
Remote sensing measurements of cover (or biomass) by height (or depth) classes globally or regionally, to provide a 3-dimensional description of habitats <=1 year Global terrestrial maps available with RS (e.g., LIDAR). Marine and freshwater habitats mapped by combining RS and in situ data Proxy for biomass in ecosystems; key deteminant of habitat suitability for biodiversity; basis for land cover classification. Aichi Targets: 5, 11, 14, 15

Ecosystem extent and fragmentation

Measurement and scalability Temporal sensitivity Feasibility Relevance and related CBD 2020 targets
Local (aerial photo and in-situ monitoring) to global mapping (satellite observations) of natural/semi-natural forests, wetlands, free running rivers, coral reef live cover, benthos cover, etc 1-5 years Global maps of forests, assessment of fragmentation for major river basins, and local to regional maps of coral reefs already exist, but comparable observations over time are limited and distinction between natural and modified ecosystems (e.g. natural forests versus plantations) is often not made This is a key measure of human impacts on ecosystems. It can be used to derive indicators such as extent of forests and forest types, mangrove extent, seagrass extent, coral reef condition. Aichi Targets: 5, 7, 10, 14, 15

Ecosystem composition by functional type

Measurement and scalability Temporal sensitivity Feasibility Relevance and related CBD 2020 targets
Functional types can be directly infered from morphology (in situ) or from remote sensing 5 years Implicitly part of current ecosystem maps. Some models (e.g. DGVMs, marine ecosystem models) are based on functional groups This is a basis for ecosystem classification and lends itself to remote sensing. It can be used to predict ecosystem function and ecosystem services. Aichi Targets: 5, 14, 15