Evidence map›Paper›PMID 25703619›Full record

ArticleEnvironmental science and pollution research international2015

Depth, soil type, water table, and site effects on microbial community composition in sediments of pesticide-contaminated aquifer.

Marja K Mattsson, Xinxin Liu, Dan Yu, Merja H Kontro

Abstract read
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In one paragraph

Article in Environmental science and pollution research international, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.5field-weighted citation impact, top 19% of its field
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

2 citing papers in PubMed, 20 citations in OpenAlex.

  1. Review
  2. 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

4 authors at 1 institution in 1 country.

Marja K MattssonDepartment of Environmental Sciences, University of Helsinki, Niemenkatu 73, 15140, Lahti, Finland, marja.mattsson@helsinki.fi.
Xinxin Liu
Dan Yu
Merja H Kontro
University of Helsinki · FI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microbial community compositions in pesticide-contaminated aquifers have not been studied, although such information is important for remediation and maintaining freshwater sources clean under changing climate. Therefore, phospholipid (PLFAs), glycolipid (GLFAs), and neutral lipid (NLFAs) fatty acids were determined from sand and clay sediments at depths of 0.3-24.8 m, all contaminated with triazines and dichlobenil/2,6-dichlorobenzamide. The portion of fungi and Gram-negative bacteria at 0.3 m was greater than at 0.8 m, where the percentage of Gram-positive bacteria, actinobacteria, and sulfate-reducing bacteria (SRB) increased. In deeper sediments, microbial biomass, activity, and diversity decreased. Clay sediments seemed to serve as a reservoir for slow pesticide elution to groundwater, and their biomarker portion for all bacteria except actinobacteria was greater than in sand sediments. The slow pesticide dissipation seemed to occur in the main groundwater flow zone, resulting in nitrogen release simultaneously with organic matter elution from gardening and bank filtration. As a result, microbial biomass, activity, and diversity were increased. This shift in conditions towards that in surface soil may be appropriate for enhanced natural attenuation of pesticides in groundwater sources.

Indexed as

Environmental MonitoringWater MicrobiologyBacteriaBenzamidesBiomassFresh WaterGeologic SedimentsGroundwaterNitrogenPesticidesSoilWater Pollutants, Chemical2,6-dichlorobenzamideBenzamidesNitrogenPesticidesSoilWater Pollutants, Chemical

Identifiers

PMID25703619
OpenAlexW2005270836

What OpenQuestion holds

Textmetadata
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.