Evidence map›Paper›PMID 32745120›Full record

ArticlePloS one2020

Microbial communities can predict the ecological condition of headwater streams.

Robert H Hilderbrand, Stephen R Keller, Sarah M Laperriere, Alyson E Santoro, Jason Cessna, Regina Trott

Abstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Robert H HilderbrandAppalachian Laboratory, University of Maryland Center for Environmental Science, Frostburg, MD, United States of America.ORCID 0000-0003-0923-7699
Stephen R KellerAppalachian Laboratory, University of Maryland Center for Environmental Science, Frostburg, MD, United States of America.
Sarah M LaperriereHorn Point Laboratory, University of Maryland Center for Environmental Science, Cambridge, MD, United States of America.
Alyson E SantoroHorn Point Laboratory, University of Maryland Center for Environmental Science, Cambridge, MD, United States of America.
Jason CessnaAppalachian Laboratory, University of Maryland Center for Environmental Science, Frostburg, MD, United States of America.
Regina TrottAppalachian Laboratory, University of Maryland Center for Environmental Science, Frostburg, MD, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

ArchaeaBacteriaEcological Parameter MonitoringEcosystemEnvironmental MonitoringGeologic SedimentsHigh-Throughput Nucleotide SequencingMetagenomicsMicrobiotaRiversRNA, Ribosomal, 16SRNA, Ribosomal, 16S

Identifiers

PMID32745120
PMCPMC7398514

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.