ena-STUDY-Universidad de la Republica, Centro Universitario Regional Este-27-11-2018-15:36:39:728-1217
Bacterioplankton composition as indicator of environmental status: proof of principle using indicator value analysis of estuarine communities
Increasing awareness of environmental impacts caused by anthropogenic activities highlights the need of finding indicators of environmental status that can be routinely assessed at large spatial and temporal scales. Microbial communities comprise the greatest share of biological diversity on Earth and can rapidly reflect recent environmental change while keeping records of past events. However, they have been rarely targeted in the search of ecological indicators for habitat types, environmental conditions, or environmental changes. Here, as a proof of principle, we analysed the bacterioplankton community composition of four estuaries in North and South America, Europe, and Asia, and looked for indicators of groups of samples defined using partition techniques, according to primary physicochemical variables typically monitored to infer water quality. Indicator value analysis (IndVal) was conducted to identify indicator OTUs (Operational Taxonomic Units, analogous to species in other fields of ecology) of each group. These bacterioplankton-based indicators exhibited a high capacity to predict the group membership of the samples within each estuary, and to correctly assign the samples to their right estuary in a combined dataset, employing different machine learning techniques. The indicators were composed of OTUs belonging to several bacterial phyla, which responded significantly and differentially to the environmental variables used to define the groups of samples. Moreover, the predictive values of these bacterial indicators were generally higher than those of other biological assemblages commonly used for environmental monitoring. Therefore, this approach appears as apromising tool to complement existing strategies for monitoring and conservation of aquatic systems worldwide.
Increasing awareness of environmental impacts caused by anthropogenic activities highlights the need of finding indicators of environmental status that can be routinely assessed at large spatial and temporal scales. Microbial communities comprise the greatest share of biological diversity on Earth and can rapidly reflect recent environmental change while keeping records of past events. However, they have been rarely targeted in the search of ecological indicators for habitat types, environmental conditions, or environmental changes. Here, as a proof of principle, we analysed the bacterioplankton community composition of four estuaries in North and South America, Europe, and Asia, and looked for indicators of groups of samples defined using partition techniques, according to primary physicochemical variables typically monitored to infer water quality. Indicator value analysis (IndVal) was conducted to identify indicator OTUs (Operational Taxonomic Units, analogous to species in other fields of ecology) of each group. These bacterioplankton-based indicators exhibited a high capacity to predict the group membership of the samples within each estuary, and to correctly assign the samples to their right estuary in a combined dataset, employing different machine learning techniques. The indicators were composed of OTUs belonging to several bacterial phyla, which responded significantly and differentially to the environmental variables used to define the groups of samples. Moreover, the predictive values of these bacterial indicators were generally higher than those of other biological assemblages commonly used for environmental monitoring. Therefore, this approach appears as apromising tool to complement existing strategies for monitoring and conservation of aquatic systems worldwide.