Back to monitoring outcomes


  • Biodiversity

  • Function


Biotic interactions structure ecosystems and underpin many ecosystem functions (Kaiser-Bunbury et al. 2015). Interactions related to specific ecosystem functions include pollination, seed dispersal and predation, of these pollination is one of the most tractable to measure (Kaiser-Bunbury 2015).

It is relevant to measure pollination where this is a key functional goal of a project (Kaiser-Bunbury et al. 2015), for example grassland restoration in an agricultural landscape. However, it is possible to assess pollination in other ecosystem types, and pollination is key to maintaining plant richness, particularly rare species, underpinning overall biodiversity (Wei et al. 2021, Kral-O’Brien et al. 2021). In some systems a small number of species maintain pollination functionality but as more sites are assessed, more species are required to provide the threshold level of pollination (Kremen et al. 2018). Different pollinator groups have different sensitivities and high land-use intensity reduces overall pollinator abundance (Millard et al. 2021).

Methodology summary

A standardised methodology is available from the UK Pollinator Monitoring Scheme (UKPoMS):

  • Site visits 4 times a year (mid-April to mid-May, June, July, Aug to mid-Sept) during suitable weather conditions
  • Pan traps are set for 6 hours during 0900-1700
  • 3 traps (UV blue, yellow, white) are set up in 5 locations per km square – where possible these should be allocated in alignment with Species diversity data collection and in large sites with multiple habitats, stratified by habitat type
  • In short vegetation traps are placed on the ground, in vegetation >10 cm traps are supported on a stake
  • Traps are filled with water with a few drops of washing up liquid added
  • Local flower abundance is also recorded in the area surrounding the pan traps
  • Flower visitation in 50 x 50 cm plots is also recorded, targeting specific flowering plants at specific times of years

Derived metrics include total abundance and diversity (see Species diversity).

More advanced measures of network statistics are possible (Kaiser-Bunbury et al. 2015) e.g.:

  • Interaction diversity – higher interaction diversity = higher community stability
  • Interaction evenness – if a few species dominate and others are rare then interaction evenness will be low, but loss of rare species can increase evenness even as diversity declines
  • Partner diversity – diversity of interaction partners per species (pollinator species associated with each plant or plant species associated with each pollinator); high partner diversity increases overall resilience
  • Vulnerability and generality – mean diversity of interaction partners across species; high partner diversity increases overall resilience
  • Specialisation – dependency of species on few partners, implications for competition for resources and vulnerability to loss of partners
  • Modularity – identifying groups of species that share interactions more frequently within modules

Metric threshold or direction of change

Generally, higher pollinator diversity is desirable. See notes on advanced measures of network statistics in Methodology summary.

Technological innovations

• Radio frequency ID (insects tagged and tracked) and radar (insects tagged and tracked, large-scale weather radars) for detecting and tracking insects (Barlow and O’Neill 2020).
• Automated visual and audio monitoring and classification by machine learning for invertebrate ID (Barlow and O’Neill 2020).
• Vision motion software for monitoring fine-scale pollinator behaviours (Barlow and O’Neill 2020).


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


  • Community


  • Medium


  • Tier 2

Technical expertise

  • Low

Standardised methodology

  • Yes