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Comparison of predicted aquatic risks of pesticides used under different rice-farming strategies in the Mekong Delta, Vietnam
This study evaluates the risks of pesticides applied in rice-fish and rice farming, with and without integrated pest management (IPM) strategies, to non-target aquatic organisms in two provinces of the Mekong Delta, Vietnam. Pesticide inventories and application patterns were collected from 120 Viet...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5978820/ https://www.ncbi.nlm.nih.gov/pubmed/27854060 http://dx.doi.org/10.1007/s11356-016-7991-4 |
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author | Stadlinger, Nadja Berg, Håkan Van den Brink, Paul J. Tam, Nguyen. T. Gunnarsson, Jonas S. |
author_facet | Stadlinger, Nadja Berg, Håkan Van den Brink, Paul J. Tam, Nguyen. T. Gunnarsson, Jonas S. |
author_sort | Stadlinger, Nadja |
collection | PubMed |
description | This study evaluates the risks of pesticides applied in rice-fish and rice farming, with and without integrated pest management (IPM) strategies, to non-target aquatic organisms in two provinces of the Mekong Delta, Vietnam. Pesticide inventories and application patterns were collected from 120 Vietnamese farmers through interviews. Risks were assessed using (1) Pesticide RIsks in the Tropics to Man, Environment, and Trade (PRIMET), a first-tier model, which calculates predicted environmental concentrations (PECs) of pesticides in the rice field, based on the compound’s physico-chemical properties and the application pattern, and then compares the PECs to safe concentrations based on literature data, and (2) species sensitivity distribution (SSD), a second-tier assessment model using species sensitivity distributions to calculate potentially affected fraction (PAF) of species based on the PECs from PRIMET. Our results show that several of the used insecticides pose a high risk to fish and arthropods and that the risks are higher among rice farmers than among rice-fish farmers. This study indicates that the PRIMET model in combination with SSDs offer suitable approaches to help farmers and plant protection staff to identify pesticides that may cause high risk to the environment and therefore should be substituted with safer alternatives. |
format | Online Article Text |
id | pubmed-5978820 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-59788202018-06-21 Comparison of predicted aquatic risks of pesticides used under different rice-farming strategies in the Mekong Delta, Vietnam Stadlinger, Nadja Berg, Håkan Van den Brink, Paul J. Tam, Nguyen. T. Gunnarsson, Jonas S. Environ Sci Pollut Res Int Ecotoxicology in Tropical Regions This study evaluates the risks of pesticides applied in rice-fish and rice farming, with and without integrated pest management (IPM) strategies, to non-target aquatic organisms in two provinces of the Mekong Delta, Vietnam. Pesticide inventories and application patterns were collected from 120 Vietnamese farmers through interviews. Risks were assessed using (1) Pesticide RIsks in the Tropics to Man, Environment, and Trade (PRIMET), a first-tier model, which calculates predicted environmental concentrations (PECs) of pesticides in the rice field, based on the compound’s physico-chemical properties and the application pattern, and then compares the PECs to safe concentrations based on literature data, and (2) species sensitivity distribution (SSD), a second-tier assessment model using species sensitivity distributions to calculate potentially affected fraction (PAF) of species based on the PECs from PRIMET. Our results show that several of the used insecticides pose a high risk to fish and arthropods and that the risks are higher among rice farmers than among rice-fish farmers. This study indicates that the PRIMET model in combination with SSDs offer suitable approaches to help farmers and plant protection staff to identify pesticides that may cause high risk to the environment and therefore should be substituted with safer alternatives. Springer Berlin Heidelberg 2016-11-16 2018 /pmc/articles/PMC5978820/ /pubmed/27854060 http://dx.doi.org/10.1007/s11356-016-7991-4 Text en © The Author(s) 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Ecotoxicology in Tropical Regions Stadlinger, Nadja Berg, Håkan Van den Brink, Paul J. Tam, Nguyen. T. Gunnarsson, Jonas S. Comparison of predicted aquatic risks of pesticides used under different rice-farming strategies in the Mekong Delta, Vietnam |
title | Comparison of predicted aquatic risks of pesticides used under different rice-farming strategies in the Mekong Delta, Vietnam |
title_full | Comparison of predicted aquatic risks of pesticides used under different rice-farming strategies in the Mekong Delta, Vietnam |
title_fullStr | Comparison of predicted aquatic risks of pesticides used under different rice-farming strategies in the Mekong Delta, Vietnam |
title_full_unstemmed | Comparison of predicted aquatic risks of pesticides used under different rice-farming strategies in the Mekong Delta, Vietnam |
title_short | Comparison of predicted aquatic risks of pesticides used under different rice-farming strategies in the Mekong Delta, Vietnam |
title_sort | comparison of predicted aquatic risks of pesticides used under different rice-farming strategies in the mekong delta, vietnam |
topic | Ecotoxicology in Tropical Regions |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5978820/ https://www.ncbi.nlm.nih.gov/pubmed/27854060 http://dx.doi.org/10.1007/s11356-016-7991-4 |
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