268
views
0
recommends
+1 Recommend
1 collections
    0
    shares

      Publish your conference poster on ScienceOpen Posters to carry on the conversation.

      All posters are assigned an Open Access CC BY 4.0 license, a Crossref DOI and are integrated with ORCID, ROR, FunderID and more for best discoverability.

      scite_
       
      • Record: found
      • Abstract: found
      • Poster: found
      Is Open Access

      A review of Modelling approaches for Ecological Risk Assessment of Pesticides

      Published
      research-article
      Bookmark

            Abstract

            A wide diversity of plant protection products (PPP) is used for crop protection leading to the contamination of soil, water, and air, which can have ecotoxicological impacts on living organisms. It is inconceivable to study the effects of each compound on each species from each compartment, experimental studies being time consuming and cost prohibitive, and animal testing having to be avoided. Therefore, numerous models are developed to assess PPP ecotoxicological effects. Our objective was to provide an overview of the modeling approaches enabling the assessment of PPP effects (including biopesticides) on the biota. Six categories ofmodels were inventoried: (Q)SAR, DR and TKTD, population, multi-species, landscape, and mixture models. They were developed for various species (terrestrial and aquatic vertebrates and invertebrates, primary producers, micro-organisms) belonging to diverse environmental compartments, to address different goals (e.g., species sensitivity or PPP bioaccumulation assessment, ecosystem services protection). Among them, mechanistic models are increasingly recognized by EFSA for PPP regulatory risk assessment but, to date, remain not considered in notified guidance documents. The strengths and limits of the reviewed models are discussed together with improvement avenues (multigenerational effects, multiple biotic and abiotic stressors). This review also underlines a lack of model testing by means of field data and of sensitivity and uncertainty analyses. Accurate and robust modeling of PPP effects and other stressors on living organisms, from their application in the field to their functional consequences on the ecosystems at different scales of time and space, would help going toward a more sustainable management of the environment.

            Content

            Author and article information

            Journal
            ScienceOpen Posters
            ScienceOpen
            31 May 2022
            Affiliations
            [1 ] INRAE, Directorate for Collective Scientific Assessment, Paris
            [2 ] Univ Lyon 1, CNRS 5558, Villeurbanne
            [3 ] INRAE, UR RiverLy, Ecotoxicology laboratory, Villeurbanne
            [4 ] Avignon Univ, INRAE, UMR EMMAH, Avignon
            [5 ] IST Ifremer - Appuidoc, Bibliothèque La Pérouse, Plouzan
            [6 ] Univ Paris-Saclay, INRAE, AgroParisTech, UMR ECOSYS, Thiverval-Grignon
            [7 ] Ineris, Experimental Toxicology and Modelling Unit, UMR-I 02 Verneuil en Halatte
            Author notes
            Author information
            https://orcid.org/0000-0003-4604-0166
            Article
            10.14293/S2199-1006.1.SOR-.PPN7GQU.v1
            64a96eb4-b257-41ee-89e2-1c13ca7069ef

            This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com .

            History
            : 31 May 2022

            Ecology,General environmental science,Mathematical modeling & Computation

            References

            1. Larras Floriane, Charles Sandrine, Chaumot Arnaud, Pelosi Céline, Le Gall Morgane, Mamy Laure, Beaudouin Rémy. A critical review of effect modeling for ecological risk assessment of plant protection products. Environmental Science and Pollution Research. 2022. Springer Science and Business Media LLC. [Cross Ref]

            Comments

            Comment on this article