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Relative abundance

  • Biodiversity

  • Compostion


Changes in abundance, and identity, of species have greater functional consequences for an ecosystem than changes in simple metrics such as species richness (Hillebrand et al. 2018, Buckland et al. 2005). Trends in mean abundance can detect early signals of species decline and are less sensitive to demographic stochasticity (population fluctuations that occur by random chance as a result of births, deaths and migration) (Santini et al. 2017, van Strien et al. 2012).

It is easier to estimate abundance data at smaller scales (community, population) than at landscape scales (Chiarucci et al. 2011). Abundance data should be collected in a spatially explicit way (e.g. fixed area plots, defined density of sampling points per unit area) (Chase and Knight 2013).

Methodology summary

Species abundance data is collected during some of the species-level surveys to obtain diversity metrics (see Species diversity for methodologies).

Suitable standardised methods are available for trees (collected during woodland plant surveys, Tree diversity and Seedling regeneration surveys), carabid beetles, spiders, butterflies, moths, birds, bats, spittle bugs and crane flies, which all record the number of individuals in each group.

Biomass can also be used to assess the abundance of individuals (see Invertebrate biomass, Mammal biomass, Vegetation biomass).

  • It can be also used to compare abundance between species groups and provides useful information when comparing species where individuals vary appreciably in size
  • Biomass can provide an abundance estimate for herbaceous plants

It can be unfeasible to estimate abundance at large scales, using smaller representative sample units can increase the accuracy of detection, for example plants monitored within standardised quadrats (Buckland et al. 2005).

Calculating metrics (based on Buckland et al. 2005):

  • Species-specific densities are calculated for each species = number of individuals per unit area
  • This can be used to calculate mean density per habitat or site
  • To calculate relative abundance over time, species-specific densities are divided by density at the initial time point, tracking increases or declines in abundance
  • If aggregating relative abundance across species, the geometric mean should be used; this allows overall trends of increases or declines to be detected (Buckland et al. 2005)
  • The geometric mean is calculated by averaging log(relative abundance) across species and taking the exponential

Metric threshold or direction of change

Targets on changes in abundance of specific species will depend on the project aims (e.g. target species that are characteristic of a certain habitat).

Technological innovations

  • Earth Observation sensors generate high resolution imagery, which can be used to identify larger species. (Lausch et al. 2016).
  • Advances in machine learning are increasing the efficiency of classifying and processing camera trap imagery (Tabak et al. 2018).
  • Sequencing methods have shown some promise in detecting invertebrate biomass, with mitogenomic sequencing achieving higher accuracy than metabarcoding. However detection is still poor for low abundance species (Bista et al. 2018).

  • Agricultural
  • Forest
  • Grassland
  • Heathland
  • Other
  • Peatland
  • Saltmarsh
  • Wetland


  • Community
  • Landscape
  • Population


  • Medium


  • Tier 1

Technical expertise

  • High

Standardised methodology

  • Partial