Dataset Information

Microbial communities can predict the ecological condition of headwater streams.

ABSTRACT: Humanity's reliance on clean water and the ecosystem services provided makes identifying efficient and effective ways to assess the ecological condition of streams ever more important. We used high throughput sequencing of the 16S rRNA region to explore relationships between stream microbial communities, environmental attributes, and assessments of stream ecological condition. Bacteria and archaea in microbial community samples collected from the water column and from stream sediments during spring and summer were used to replicate standard assessments of ecological condition performed with benthic macroinvertebrate collections via the Benthic Index of Biotic Integrity (BIBI). Microbe-based condition assessments were generated at different levels of taxonomic resolution from phylum to OTU (Operational Taxonomic Units) in order to understand appropriate levels of taxonomic aggregation. Stream sediment microbial communities from both spring and summer were much better than the water column at replicating BIBI condition assessment results. Accuracies were as high as 100% on training data used to build the models and up to 80% on validation data used to assess predictions. Assessments using all OTUs usually had the highest accuracy on training data, but were lower on validation data due to overfitting. In contrast, assessments at the order-level had similar performance accuracy for validation data, and a reduced subset of orders also performed well, suggesting the method could be generalized to other watersheds. Subsets of the important orders responded similarly to environmental gradients compared to the entire community, where strong shifts in community structure occurred for known aquatic stressors such as pH, dissolved organic carbon, and nitrate nitrogen. The results suggest the stream microbes may be useful for assessing the ecological condition of streams and especially useful for stream restorations where many eukaryotic taxa have been eliminated due to prior degradation and are unable to recolonize.

SUBMITTER: Hilderbrand RH

PROVIDER: S-EPMC7398514 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Microbial communities can predict the ecological condition of headwater streams.

Hilderbrand Robert H RH Keller Stephen R SR Laperriere Sarah M SM Santoro Alyson E AE Cessna Jason J Trott Regina R

PloS one 20200803 8

Humanity's reliance on clean water and the ecosystem services provided makes identifying efficient and effective ways to assess the ecological condition of streams ever more important. We used high throughput sequencing of the 16S rRNA region to explore relationships between stream microbial communities, environmental attributes, and assessments of stream ecological condition. Bacteria and archaea in microbial community samples collected from the water column and from stream sediments during spr ...[more]

PMID: 32745120

Similar Datasets

Project description:Microbial communities are responsible for the bulk of biogeochemical processing in temporary headwater streams, yet there is still relatively little known about how community structure and function respond to periodic drying. Moreover, the ability to sample temporary habitats can be a logistical challenge due to the limited capability to measure and predict the timing, intensity and frequency of wet-dry events. Unsurprisingly, published datasets on microbial community structure and function are limited in scope and temporal resolution and vary widely in the molecular methods applied. We compared environmental and microbial community datasets for permanent and temporary tributaries of two different North American headwater stream systems: Speed River (Ontario, Canada) and Parkers Creek (Maryland, USA). We explored whether taxonomic diversity and community composition were altered as a result of flow permanence and compared community composition amongst streams using different 16S microbial community methods (i.e., T-RFLP and Illumina MiSeq). Contrary to our hypotheses, and irrespective of method, community composition did not respond strongly to drying. In both systems, community composition was related to site rather than drying condition. Additional network analysis on the Parkers Creek dataset indicated a shift in the central microbial relationships between temporary and permanent streams. In the permanent stream at Parkers Creek, associations of methanotrophic taxa were most dominant, whereas associations with taxa from the order Nitrospirales were more dominant in the temporary stream, particularly during dry conditions. We compared these results with existing published studies from around the world and found a wide range in community responses to drying. We conclude by proposing three hypotheses that may address contradictory results and, when tested across systems, may expand understanding of the responses of microbial communities in temporary streams to natural and human-induced fluctuations in flow-status and permanence.

Project description:Streamflow-duration assessment methods (SDAMs) are rapid, indicator-based tools for classifying streamflow duration (e.g., intermittent vs perennial flow) at the reach scale. Indicators are easily assessed stream properties used as surrogates of flow duration, which is too resource intensive to measure directly for many reaches. Invertebrates are commonly used as SDAM indicators because many are not highly mobile, and different species have life stages that require flow for different durations and times of the year. The objectives of this study were to 1) identify invertebrate taxa that can be used as SDAM indicators to distinguish between stream reaches having intermittent and perennial flow, 2) to compare indicator strength across different taxonomic and numeric resolutions, and 3) to assess the relative importance of season and habitat type on the ability of invertebrates to predict streamflow-duration class. We used 2 methods, random forest models and indicator species analysis, to analyze aquatic and terrestrial invertebrate data (presence/absence, density, and biomass) at the family and genus levels from 370 samples collected from both erosional and depositional habitats during both wet and dry seasons. In total, 36 intermittent and 53 perennial reaches were sampled along 31 forested headwater streams in 4 level II ecoregions across the United States. Random forest models for family- and genus-level datasets had stream classification accuracy ranging from 88.9 to 93.2%, with slightly higher accuracy for density than for presence/absence and biomass datasets. Season (wet/dry) tended to be a stronger predictor of streamflow-duration class than habitat (erosional/depositional). Many taxa at the family (58.8%) and genus level (61.6%) were collected from both intermittent and perennial reaches, and most taxa that were exclusive to 1 streamflow-duration class were rarely collected. However, 23 family-level or higher taxa (20 aquatic and 3 terrestrial) and 44 aquatic genera were identified as potential indicators of streamflow-duration class for forested headwater streams. The utility of the potential indicators varied across level II ecoregions in part because of representation of intermittent and perennial reaches in the dataset but also because of variable ecological responses to drying among species. Aquatic invertebrates have been an important field indicator of perennial reaches in existing SDAMs, but our findings highlight how including aquatic and terrestrial invertebrates as indicators of intermittent reaches can further maximize the data collected for streamflow-duration classifications.

Dataset Information

Microbial communities can predict the ecological condition of headwater streams.

Publications

Microbial communities can predict the ecological condition of headwater streams.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets