Evidence map›Paper›PMID 30425684›Full record

ArticleFrontiers in microbiology2018

Aquatic Bacterial Communities Associated With Land Use and Environmental Factors in Agricultural Landscapes Using a Metabarcoding Approach.

Wen Chen, Graham Wilkes, Izhar U H Khan, Katarina D M Pintar, Janis L Thomas, C André Lévesque, Julie T Chapados, Edward Topp, David R Lapen

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
–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

26 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

9 authors.

Wen ChenOttawa Research and Development Center, Science and Technology Branch, Agriculture and Agri-Food Canada, Ottawa, ON, Canada.
Graham WilkesOttawa Research and Development Center, Science and Technology Branch, Agriculture and Agri-Food Canada, Ottawa, ON, Canada.
Izhar U H KhanOttawa Research and Development Center, Science and Technology Branch, Agriculture and Agri-Food Canada, Ottawa, ON, Canada.
Katarina D M PintarCanadian Forest Service, Natural Resources Canada, Ottawa, ON, Canada.
Janis L ThomasOntario Ministry of the Environment and Climate Change, Environmental Monitoring and Reporting Branch, Toronto, ON, Canada.
C André LévesqueOttawa Research and Development Center, Science and Technology Branch, Agriculture and Agri-Food Canada, Ottawa, ON, Canada.
Julie T ChapadosOttawa Research and Development Center, Science and Technology Branch, Agriculture and Agri-Food Canada, Ottawa, ON, Canada.
Edward ToppLondon Research and Development Centre, Science and Technology Branch, Agriculture and Agri-Food Canada, London, ON, Canada.
David R LapenOttawa Research and Development Center, Science and Technology Branch, Agriculture and Agri-Food Canada, Ottawa, ON, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study applied a 16S rRNA gene metabarcoding approach to characterize bacterial community compositional and functional attributes for surface water samples collected within, primarily, agriculturally dominated watersheds in Ontario and Québec, Canada. Compositional heterogeneity was best explained by stream order, season, and watercourse discharge. Generally, community diversity was higher at agriculturally dominated lower order streams, compared to larger stream order systems such as small to large rivers. However, during times of lower relative water flow and cumulative 2-day rainfall, modestly higher relative diversity was found in the larger watercourses. Bacterial community assemblages were more sensitive to environmental/land use changes in the smaller watercourses, relative to small-to-large river systems, where the proximity of the sampled water column to bacteria reservoirs in the sediments and adjacent terrestrial environment was greater. Stream discharge was the environmental variable most significantly correlated (all positive) with bacterial functional groups, such as C/N cycling and plant pathogens. Comparison of the community structural similarity via network analyses helped to discriminate sources of bacteria in freshwater derived from, for example, wastewater treatment plant effluent and intensity and type of agricultural land uses (e.g., intensive swine production vs. dairy dominated cash/livestock cropping systems). When using metabarcoding approaches, bacterial community composition and coexisting pattern rather than individual taxonomic lineages, were better indicators of environmental/land use conditions (e.g., upstream land use) and bacterial sources in watershed settings. Overall, monitoring changes and differences in aquatic microbial communities at regional and local watershed scales has promise for enhancing environmental footprinting and for better understanding nutrient cycling and ecological function of aquatic systems impacted by a multitude of stressors and land uses.

Indexed as

agricultural watershedsaquatic bacterial communityland usemetabarcodingstream order

Identifiers

PMID30425684
PMCPMC6218688

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.