Nicholas C. Everall
Comparability of macroinvertebrate biomonitoring indices of river health derived from semi-quantitative and quantitative methodologies
Everall, Nicholas C.; Johnson, Matthew F.; Wood, Paul; Farmer, Andrew; Wilby, Robert L.; Measham, Nick
Authors
Dr MATTHEW JOHNSON M.JOHNSON@NOTTINGHAM.AC.UK
Associate Professor
Paul Wood
Andrew Farmer
Robert L. Wilby
Nick Measham
Abstract
Aquatic macroinvertebrates have been the basis for one of the primary indicators and a cornerstone of lotic biomonitoring for over 40 years. Despite the widespread use of lotic invertebrates in statutory biomonitoring networks, scientific research and citizen science projects, the sampling methodologies employed frequently vary between studies. Routine statutory biomonitoring has historically relied on semi-quantitative sampling methods (timed kick sampling), while much academic research has favoured fully quantitative methods (e.g. Surber sampling). There is an untested assumption that data derived using quantitative and semi-quantitative samples are not comparable for biomonitoring purposes. As a result, data derived from the same site, but using different sampling techniques, have typically not been analysed together or directly compared. Here, we test this assumption by comparing a range of biomonitoring metrics derived from data collected using timed semi-quantitative kick samples and quantitative Surber samples from the same sites simultaneously. In total, 39 pairs of samples from 7 rivers in the UK were compared for two seasons (spring and autumn). We found a strong positive correlation (rs = +0.84) between estimates of taxa richness based on ten Surber sub-samples and a single kick sample. The majority of biomonitoring metrics were comparable between techniques, although only fully quantitative sampling allows the density of the community (individual m−2) to be determined. However, this advantage needs to be balanced alongside the greater total sampling time and effort associated with the fully quantitative methodology used here. Kick samples did not provide a good estimate of relative abundance of a number of species/taxa and, therefore, the quantitative method has the potential to provide important additional information which may support the interpretation of the biological metrics.
Citation
Everall, N. C., Johnson, M. F., Wood, P., Farmer, A., Wilby, R. L., & Measham, N. (2017). Comparability of macroinvertebrate biomonitoring indices of river health derived from semi-quantitative and quantitative methodologies. Ecological Indicators, 78, 437-448. https://doi.org/10.1016/j.ecolind.2017.03.040
Journal Article Type | Article |
---|---|
Acceptance Date | Mar 19, 2017 |
Online Publication Date | Mar 31, 2017 |
Publication Date | Jul 1, 2017 |
Deposit Date | Apr 3, 2017 |
Publicly Available Date | Apr 3, 2017 |
Journal | Ecological Indicators |
Print ISSN | 1470-160X |
Electronic ISSN | 1872-7034 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 78 |
Pages | 437-448 |
DOI | https://doi.org/10.1016/j.ecolind.2017.03.040 |
Keywords | Macroinvertebrate; Species richness; Biological monitoring; Biotic index; River |
Public URL | https://nottingham-repository.worktribe.com/output/853080 |
Publisher URL | http://www.sciencedirect.com/science/article/pii/S1470160X17301589 |
Contract Date | Apr 3, 2017 |
Files
Everall et al. 2017.pdf
(1.4 Mb)
PDF
Copyright Statement
Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by-nc-nd/4.0
You might also like
Material flow analysis of chemical additives in plastics: A critical review
(2024)
Journal Article
Downloadable Citations
About Repository@Nottingham
Administrator e-mail: discovery-access-systems@nottingham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search