A new tool for assessment and monitoring of community and ecosystem change based on multivariate abundance data integration from different taxonomic groups

Abstract

Background: 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.

Unravelling the drivers of aquatic communities using disparate organismal groups and different taxonomic levels

“…Our results also show that the use of multivariate data of several biological groups provides broad information about the ecosystem state. Thus, bioassessment should utilise multivariate data (see also Mueller et al, 2014). Furthermore, the reduction of complex community data of various organismal groups to single numeric scores, as is commonly applied in bioassessment, bears a risk of losing important information (Caroni et al, 2013;Dahm et al, 2013).…”

Assessment of the impact of Atlantic bluefin tuna farming on Adriatic benthic habitats by analysing macroinvertebrate assemblage structure at family level

“…Other authors also propose the use of non-metric multivariate approaches for monitoring aquatic environments. However, they recommend the combination of several taxonomic groups, since this is feasible with the same sampling effort and independent of the scale of research and the occurrence of certain indicator taxa (Mueller et al, 2014). Furthermore, we have already discussed the univariate information provided by some benthic biotic indicators vs. the multivariate information from the whole assemblage data set.…”

Taxonomic Level Needed to Detect Significant Changes in Polychaete Communities Over Different Macrophyte Assemblages on Rocky Intertidal Shores

“…species composition) is more sensitive than univariate analysis (e.g. species richness and abundance) in detecting the significant effect of environmental changes because the relative abundance of each taxon is not compiled into a single dimension (Mueller et al, 2014).…”