Quantifying spatial and temporal variability of macroinvertebrate metrics

Research output: Contribution to journalArticleAcademicpeer-review

14 Citations (Scopus)


Since the introductions of the Habitat Directive and the European Water Framework Directive, water authorities are now obliged to monitor changes in conservation value/ecological quality on larger spatial scales (opposed to site scale), as well as to indicate the level of confidence and precision of the results provided by the monitoring programs in their river basin management plans (European Commission, 2000). To meet these requirements, analyses of the statistical power of the monitoring programs should be implemented. Currently, the statistical properties associated with aquatic monitoring programs are often unknown. We collected macroinvertebrate samples from 25 meso-eutrophic drainage ditches in the Netherlands and selected 7 taxonomic richness metrics for the evaluation of spatial and temporal variability. Simulations were performed to investigate the effects of changes in (1) the total number of species included in a taxonomic richness metric and (2) the relative number of rare species included in a taxonomic richness metric. Of the 7 metrics evaluated, the number of common species required the smallest number of monitoring sites, followed by the number of Gastropoda species, and the number of species. Also, results showed that metric variability will decrease when the proportion of rare species included in a taxonomic richness metric is reduced or the total number of species included is increased. Irrespective of the metric applied a large effort will be required to detect change within drainage ditches in the Wieden, due to high spatial variability. Therefore, we need to explore the possibilities of applying alternative more cost-effective methods for sampling and sample processing in biomonitoring programs
Original languageEnglish
Pages (from-to)384-393
JournalEcological Indicators
Publication statusPublished - 2012


  • multimetric index
  • statistical power
  • benthic macroinvertebrates
  • multivariate-analysis
  • monitoring programs
  • sampling variation
  • community metrics
  • rare
  • streams
  • lake


Dive into the research topics of 'Quantifying spatial and temporal variability of macroinvertebrate metrics'. Together they form a unique fingerprint.

Cite this