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Functional trait diversity

  • Biodiversity

  • Compostion
  • Function


Different species have different functional contributions to an ecosystem (Chiarucci et al. 2011, Botta-Dukát 2005). However, metrics such as taxonomic alpha and beta diversity often don’t detect changes in the underlying functional roles of species in a community (Lelli et al. 2019). Functional diversity, rather than species numbers, strongly determines ecosystem functioning (Diaz and Cabido 2001, McGill et al. 2006, Botta-Dukát 2005, Flynn et al. 2011, Reiss et al. 2009). Turnover of species identity will have the greatest functional consequences for an ecosystem (Hillebrand et al. 2018, Buckland et al. 2005).

Changes in functional diversity are assessed by linking functional traits to species data. Selection of functional traits for analysis will depend on the project and outcomes of interest. Assessing functional traits linked to ecosystem services is a useful approach (Walden et al. 2023).

Methodology summary

Data gathered during Species diversity surveys can be linked to functional traits.

Common approaches for classifying functional traits include:

  • Plant traits: max height, habitat, flowering start, flowering duration, pollen vector (wind vs animal), seed dispersal agent (wind vs animal), seed weight, CSR (competitor, stress tolerant, ruderal) strategy, leaf persistence, life history, life form, sprout insulation, lateral spread, reproductive strategy, woodiness, light indication (Ellenberg values – shade vs light preference on a scale of 1-9)
  • Animal traits: body size, life form, trophic level, dispersal ability, habitat requirement, habitat specificity, temperature needs
  • Aboveground insects: trophic level, diet breadth, dispersal ability, voltinism (number of broods per year), body size
  • Birds: body size, trophic guild (granivore, insectivore, carnivore), dispersal ability, feeding strategy, nesting strategy, migration behaviour, dietary specialisation
  • Fungi: fruit body size, fruit body type, fruit volume, fruit thickness, tree host preference, dispersal vector (asexual spores, mycelial cores)
  • See Lelli et al. 2019, Moretti and Legg 2009 and Vandewalle et al. 2010 for more info

Plant functional traits can be linked to ecosystem services. For examples, a study looking at functional traits in grassland ecosystems in Sweden assessed the following traits (Walden et al. 2023):

  • Livestock production: leaf dry mass, specific leaf area, foraging value
  • Pollination: pollination syndrome (insect pollinated or not), flowering duration, nectar quantity, pollen quantity
  • Temperature regulation: height, specific leaf area, root architecture type (tap root, adventitious, fibrous), lifespan (longer-lived plants better for temp. reg.)
  • Water retention: specific leaf area, height, clonal lateral spread rate (non-clonal, <0.01 m/year, 0.01-0.25 m/year, >0.25 m/year), root architecture type
  • Cultural heritage: grassland specialist, mentions in traditional music
  • See Walden et al. 2023 for more info

Multiple online resources define functional traits for different species groups:

The fundiversity package can aid calculation of functional diversity indices in R (Grenié and Gruson 2023). Commonly used metrics include:

  • Mean trait value per community (average of trait values for a community, weighted by relative abundance) – dominant species have a disproportionate effect on ecosystem function (Roscher et al. 2022)
  • Rao’s quadratic diversity (functional trait diversity)

Metric threshold or direction of change

Functional trait objectives will depend on the project aims, for example see summary on linking plant functional traits to ecosystem services in Methodology summary.

Technological innovations

Plant spectral data has shown potential to be used as a proxy for plant functional diversity (Frye et al. 2021, Lausch et al. 2016, Schweiger et al. 2018).


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


  • Community
  • Landscape


  • Medium


  • Tier 1

Technical expertise

  • High

Standardised methodology

  • Partial