Influence of climate change and pesticide use practices on the ecological risks of pesticides in a protected Mediterranean wetland: A Bayesian network approach
| dc.contributor.author | Martínez Megías, Claudia | |
| dc.contributor.author | Mentzel, Sophie | |
| dc.contributor.author | Fuentes Edfuf, Yasser | |
| dc.contributor.author | Moe, Jannicke | |
| dc.contributor.author | Rico, Andreu | |
| dc.contributor.funder | Ministerio de Ciencia, Innovación y Universidades | |
| dc.contributor.funder | Generalitat Valenciana | |
| dc.contributor.ror | https://ror.org/02jjdwm75 | |
| dc.date.accessioned | 2024-07-08T13:14:13Z | |
| dc.date.available | 2024-07-08T13:14:13Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | Pollution by agricultural pesticides is one of the most important pressures affecting Mediterranean coastal wetlands. Pesticide risks are expected to be influenced by climate change,which will result in an increase of temperatures and a decrease in annual precipitation. On the other hand,pesticide dosages are expected to change given the increase in pest resistance and the implementation of environmental policies like the European ´Farm-to-Fork` strategy,which aims for a 50 % reduction in pesticide usage by 2030. The influence of climate change and pesticide use practices on the ecological risks of pesticides needs to be evaluated making use of realistic environmental scenarios. This study investigates how different climate change and pesticide use practices affect the ecological risks of pesticides in the Albufera Natural Park (Valencia,Spain),a protected Mediterranean coastal wetland. We performed a probabilistic risk assessment for nine pesticides applied in rice production using three climatic scenarios (for the years 2008,2050 and 2100),three pesticide dosage regimes (the recommended dose,and 50 % increase and 50 % decrease),and their combinations. The scenarios were used to simulate pesticide exposure concentrations in the water column of the rice paddies using the RICEWQ model. Pesticide effects were characterized using acute and chronic Species Sensitivity Distributions built with toxicity data for aquatic organisms. Risk quotients were calculated as probability distributions making use of Bayesian networks. Our results show that future climate projections will influence exposure concentrations for some of the studied pesticides,yielding higher dissipation and lower exposure in scenarios dominated by an increase of temperatures,and higher exposure peaks in scenarios where heavy precipitation events occur right after pesticide application. Our case study shows that pesticides such as azoxystrobin,difenoconazole and MCPA are posing unacceptable ecological risks for aquatic organisms,and that the implementation of the ´Farm-to-Fork` strategy is crucial to reduce them. © 2023 The Authors | |
| dc.description.fundingtype | This study was funded by the CICLIC project (Smart tools and technologies to assess the environmental fate and risks of Contaminants under Climate Change) funded by the Spanish Ministry of Science, Innovation and Universities ( RTI 2018_097158_A_C32 ); the H2020-MSCA-ITN ECORISK2050 project, funded by the European Union's Horizon 2020 research and innovation program (grant agreement No. 813124 ); and the Talented Researcher Support Programme - PlanGenT ( CIDEGENT/2020/043 ) of the Generalitat Valenciana . We would like to thank J. Soria for the 2008 water flow data and L. Blanch for the information on rice production and pesticide management practices. | |
| dc.description.peerreviewed | yes | |
| dc.description.status | Published | |
| dc.format | application/pdf | |
| dc.identifier.citation | Martínez-Megías, C., Mentzel, S., Fuentes-Edfuf, Y., Moe, S. J., & Rico, A. (2023). Influence of climate change and pesticide use practices on the ecological risks of pesticides in a protected Mediterranean wetland: A Bayesian network approach. Science of the Total Environment, 878, 163018. | |
| dc.identifier.doi | https://doi.org/10.1016/j.scitotenv.2023.163018 | |
| dc.identifier.issn | 489697 | |
| dc.identifier.officialurl | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150919792&doi=10.1016%2fj.scitotenv.2023.163018&partnerID=40&md5=5882d5245adbbfa447fa732d69a2dee7 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14417/3022 | |
| dc.journal.title | Science of the Total Environment | |
| dc.language.iso | en | |
| dc.publisher | Elsevier B.V. | |
| dc.relation.department | Strategy | |
| dc.relation.entity | IE University | |
| dc.relation.projectID | MCIU: H2020-MSCA-ITN ECORISK2050 | |
| dc.relation.projectID | RTI 2018_097158_A_C32 | |
| dc.relation.projectID | Horizon 2020: 813124 | |
| dc.relation.school | IE Business School | |
| dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject.other | Aquatic organisms | |
| dc.subject.other | Bayesian networks | |
| dc.subject.other | Ecology | |
| dc.subject.other | Environmental protection | |
| dc.subject.other | Farms | |
| dc.subject.other | Pesticides | |
| dc.subject.other | Probability distributions | |
| dc.subject.other | Risk assessment | |
| dc.subject.other | Risk perception | |
| dc.subject.other | Wetlands | |
| dc.subject.other | Agricultural pesticides | |
| dc.subject.other | Bayesia n networks | |
| dc.subject.other | Coastal wetlands | |
| dc.subject.other | Ecological risks | |
| dc.subject.other | Exposure concentration | |
| dc.subject.other | Farm-to-fork strategy | |
| dc.subject.other | Pesticide use | |
| dc.subject.other | Plant protection products | |
| dc.subject.other | Probabilistic Risk Assessment | |
| dc.subject.other | Rice farming | |
| dc.subject.other | Climate change | |
| dc.subject.other | 2 (4 chloro 2 methylphenoxy)acetic acid | |
| dc.subject.other | Pesticide | |
| dc.subject.other | Bayesian analysis | |
| dc.subject.other | Climate change | |
| dc.subject.other | Coastal wetland | |
| dc.subject.other | Crop production | |
| dc.subject.other | Ecological impact | |
| dc.subject.other | Environmental impact | |
| dc.subject.other | Mediterranean environment | |
| dc.subject.other | Albufera Natural Park | |
| dc.subject.other | Comunidad Valencia | |
| dc.subject.other | Spain | |
| dc.subject.other | Valencia [Comunidad Valencia] | |
| dc.subject.other | Agriculture | |
| dc.subject.other | Aquatic Organisms | |
| dc.subject.other | Bayes Theorem | |
| dc.subject.other | Climate Change | |
| dc.subject.other | Pesticides | |
| dc.subject.other | Water Pollutants | |
| dc.subject.other | Chemical | |
| dc.subject.other | Wetlands | |
| dc.title | Influence of climate change and pesticide use practices on the ecological risks of pesticides in a protected Mediterranean wetland: A Bayesian network approach | |
| dc.type | info:eu-repo/semantics/article | |
| dc.version.type | info:eu-repo/semantics/publishedVersion | |
| dc.volume.number | 878 | |
| dspace.entity.type | Publication | |
| person.identifier.scopus-author-id | 57204592021 | |
| person.identifier.scopus-author-id | 57224919474 | |
| person.identifier.scopus-author-id | 57191627008 | |
| person.identifier.scopus-author-id | 57210861272 | |
| person.identifier.scopus-author-id | 35096511800 |
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