Evidence map›Paper›PMID 38978138›Full record

ArticleEnvironmental microbiome2024

Exploring freshwater stream bacterial communities as indicators of land use intensity.

Syrie Hermans, Anju Gautam, Gillian D Lewis, Martin Neale, Hannah L Buckley, Bradley S Case, Gavin Lear

Abstract read
In one paragraph

Article in Environmental microbiome, 2024. 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.

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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

7 authors.

Syrie HermansSchool of Science, Auckland University of Technology, 34 St Paul Street, Auckland, 1142, New Zealand.
Anju GautamSchool of Biological Sciences, The University of Auckland, 3a Symonds Street, Auckland, 1010, New Zealand.
Gillian D LewisSchool of Biological Sciences, The University of Auckland, 3a Symonds Street, Auckland, 1010, New Zealand.
Martin NealePuhoi Stour, 15 Taipari Road, Te Atatu, Auckland, 0610, New Zealand.
Hannah L BuckleySchool of Science, Auckland University of Technology, 34 St Paul Street, Auckland, 1142, New Zealand.
Bradley S CaseSchool of Science, Auckland University of Technology, 34 St Paul Street, Auckland, 1142, New Zealand.
Gavin LearSchool of Biological Sciences, The University of Auckland, 3a Symonds Street, Auckland, 1010, New Zealand. g.lear@auckland.ac.nz.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundStream ecosystems comprise complex interactions among biological communities and their physicochemical surroundings, contributing to their overall ecological health. Despite this, many monitoring programs ignore changes in the bacterial communities that are the base of food webs in streams, often focusing on stream physicochemical assessments or macroinvertebrate community diversity instead. We used 16S rRNA gene sequencing to assess bacterial community compositions within 600 New Zealand stream biofilm samples from 204 sites within a 6-week period (February-March 2010). Sites were either dominated by indigenous forests, exotic plantation forests, horticulture, or pastoral grasslands in the upstream catchment. We sought to predict each site's catchment land use and environmental conditions based on the composition of the stream bacterial communities.

resultsRandom forest modelling allowed us to use bacterial community composition to predict upstream catchment land use with 65% accuracy; urban sites were correctly assigned 90% of the time. Despite the variation inherent when sampling across a ~ 1000-km distance, bacterial community data could correctly differentiate undisturbed sites, grouped by their dominant environmental properties, with 75% accuracy. The positive correlations between actual values and those predicted by the models built using the stream biofilm bacterial data ranged from weak (average log N concentration in the stream water, R

conclusionsFreshwater bacterial community data provide useful insights into land use impacts on stream ecosystems; they may be used as an additional measure to screen stream catchment attributes.

Identifiers

PMID38978138
PMCPMC11232138

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Registered trials

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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.