Evidence map›Paper›PMID 26335524›Full record

ArticleEnvironmental science and pollution research international2016

Experiments in water-macrophyte systems to uncover the dynamics of pesticide mitigation processes in vegetated surface waters/streams.

Christoph Stang, Nikita Bakanov, Ralf Schulz

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Article in Environmental science and pollution research international, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

3 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

3 authors.

Christoph StangInstitute for Environmental Sciences, University Koblenz-Landau, Fortstraße 7, 76829, Landau, Germany. stang@uni-landau.de.
Nikita BakanovInstitute for Environmental Sciences, University Koblenz-Landau, Fortstraße 7, 76829, Landau, Germany.
Ralf SchulzInstitute for Environmental Sciences, University Koblenz-Landau, Fortstraße 7, 76829, Landau, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Knowledge on the dynamics and the durability of the processes governing the mitigation of pesticide loads by aquatic vegetation in vegetated streams, which are characterized by dynamic discharge regimes and short chemical residence times, is scarce. In a static long-term experiment (48 h), the dissipation of five pesticides from the aqueous phase followed a biphasic pattern in the presence of aquatic macrophytes. A dynamic concentration decrease driven by sorption to the macrophytes ranged from 8.3 to 60.4% for isoproturon and bifenox, respectively, within the first 2 h of exposure. While the aqueous concentrations of imidacloprid, isoproturon, and tebufenozide remained constant thereafter, the continuous but decelerated concentration decrease of difenoconazole and bifenox in the water-macrophyte systems used here was assumed to be attributed to macrophyte-induced degradation processes. In addition, a semi-static short-term experiment was conducted, where macrophytes were transferred to uncontaminated medium after 2 h of exposure to simulate a transient pesticide peak. In the first part of the experiment, adsorption to macrophytes resulted in partitioning coefficients (logK D_Adsorp) ranging from 0.2 for imidacloprid to 2.2 for bifenox. One hour after the macrophytes were transferred to the uncontaminated medium, desorption of the compounds from the macrophytes resulted in a new phase equilibrium and K D_Desorp values of 1.46 for difenoconazole and 1.95 for bifenox were determined. A correlation analysis revealed the best match between the compound affinity to adsorb to macrophytes (expressed as K D_Adsorp) and their soil organic carbon-water partitioning coefficient (K OC) compared to their octanol-water partitioning coefficient (K OW) or a mathematically derived partitioning coefficient.

Indexed as

Biodegradation, EnvironmentalAdsorptionEmbryophytaHydrocharitaceaePesticidesPotamogetonaceaeRiversSoilSoil PollutantsWaterWater Pollutants, ChemicalPesticidesSoilSoil PollutantsWaterWater Pollutants, ChemicalAquatic vegetationBest management practicePesticidesRisk mitigationSorptionUHPLC-MSVegetated streams

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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.