In:
Environmental Systems Research, Springer Science and Business Media LLC, Vol. 3, No. 1 ( 2014-12)
Kurzfassung:
The integrative assessment of responses to environmental disturbance simultaneously considering multiple taxonomic groups or guilds has become increasingly important in ecological monitoring. The most common solution to combine data of different taxonomic groups is the calculation of compound indices comprising several individual indicators. However, these indices run the risk of cancelling out underlying trends when single components change in different directions. In contrast, multivariate community analyses are supposed to be more sensitive to detect environmental responses, since information on the abundance of multiple species is not reduced to a single dimension. Results We propose a new standardised approach for multivariate community analyses on ecosystem scale, based on a combined data matrix from different taxonomic groups. The power of these multivariate analyses is compared with two single score indices integrating data from all involved taxonomic groups (Ecological Quality Class according to the European Water Framework Directive and Shannon diversity). The multivariate indication of ecosystem change was much more sensitive and powerful in detecting and monitoring environmental impacts and restoration effects than single numeric score indices. Conclusions Compared to common monitoring systems based on compound indices, the multivariate analysis of multiple taxonomic groups is feasible with the same sampling effort, and independent of the investigation scale and the occurrence of certain indicator taxa. Since ecological community data are structured similarly throughout freshwater, marine and terrestrial ecosystems, the presented methods for data combination and multivariate indication can be analogously applied in any other habitats and can improve data integration across ecosystem borders.
Materialart:
Online-Ressource
ISSN:
2193-2697
DOI:
10.1186/2193-2697-3-12
Sprache:
Englisch
Verlag:
Springer Science and Business Media LLC
Publikationsdatum:
2014
ZDB Id:
2705690-9
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