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Larras F, Charles S, Chaumot A, Pelosi C, Le Gall M, Mamy L, Beaudouin R. A critical review of effect modeling for ecological risk assessment of plant protection products. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:43448-43500. [PMID: 35391640 DOI: 10.1007/s11356-022-19111-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 02/03/2022] [Indexed: 06/14/2023]
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 of models 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. Graphical Abstract Combination of the keyword lists composing the first bibliographic query. Columns were joined together with the logical operator AND. All keyword lists are available in Supplementary Information at https://doi.org/10.5281/zenodo.5775038 (Larras et al. 2021).
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Affiliation(s)
- Floriane Larras
- INRAE, Directorate for Collective Scientific Assessment, Foresight and Advanced Studies, Paris, 75338, France
| | - Sandrine Charles
- University of Lyon, University Lyon 1, CNRS UMR 5558, Laboratory of Biometry and Evolutionary Biology, Villeurbanne Cedex, 69622, France
| | - Arnaud Chaumot
- INRAE, UR RiverLy, Ecotoxicology laboratory, Villeurbanne, F-69625, France
| | - Céline Pelosi
- Avignon University, INRAE, UMR EMMAH, Avignon, 84000, France
| | - Morgane Le Gall
- Ifremer, Information Scientifique et Technique, Bibliothèque La Pérouse, Plouzané, 29280, France
| | - Laure Mamy
- Université Paris-Saclay, INRAE, AgroParisTech, UMR ECOSYS, Thiverval-Grignon, 78850, France
| | - Rémy Beaudouin
- Ineris, Experimental Toxicology and Modelling Unit, UMR-I 02 SEBIO, Verneuil en Halatte, 65550, France.
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Vighi M, Barsi A, Focks A, Grisoni F. Predictive models in ecotoxicology: Bridging the gap between scientific progress and regulatory applicability-Remarks and research needs. INTEGRATED ENVIRONMENTAL ASSESSMENT AND MANAGEMENT 2019; 15:345-351. [PMID: 30821044 DOI: 10.1002/ieam.4136] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2018] [Accepted: 02/18/2019] [Indexed: 06/09/2023]
Abstract
This paper concludes a special series of 7 articles (4 on toxicokinetic-toxicodynamic [TK-TD] models and 3 on quantitative structure-activity relationship [QSAR] models) published in previous issues of Integrated Environmental Assessment and Management (IEAM). The present paper summarizes the special series articles and highlights their contribution to the topic of increasing the regulatory applicability of effect models. For both TK-TD and QSAR approaches, we then describe the main research needs. The use of TK-TD models for describing sublethal effects must be better developed, particularly through the improvement of the dynamic energy budget (DEBtox) approach. The potential of TK-TD models for moving from lower (molecular) to higher (population) hierarchical levels is highlighted as a promising research line. Some relevant issues to improve the acceptance of QSAR models at the regulatory level are also described, such as increased transparency of the performance assessment and of the modeling algorithms, model documentation, relevance of the chosen target for regulatory needs, and improved mechanistic interpretability. Integr Environ Assess Manag 2019;00:000-000. © 2019 SETAC.
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Affiliation(s)
- Marco Vighi
- IMDEA Water Institute, Alcalà de Henares (Madrid), Spain
| | - Alpar Barsi
- Dutch Board for the Authorisation of Plant Protection Products and Biocides (Ctgb), Ede, Netherlands
| | - Andreas Focks
- Wageningen University & Research, Wageningen, Netherlands
| | - Francesca Grisoni
- University of Milano-Bicocca, Department of Earth and Environmental Sciences, Milano, Italy
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Thursby G, Sappington K, Etterson M. Coupling toxicokinetic-toxicodynamic and population models for assessing aquatic ecological risks to time-varying pesticide exposures. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 2018; 37:2633-2644. [PMID: 29978497 PMCID: PMC6238213 DOI: 10.1002/etc.4224] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2017] [Revised: 02/12/2018] [Accepted: 07/03/2018] [Indexed: 05/05/2023]
Abstract
Population modeling evaluations of pesticide exposure time series were compared with aspects of a currently used risk assessment process. The US Environmental Protection Agency's Office of Pesticide Programs models daily aquatic 30-yr pesticide exposure distributions in its risk assessments, but does not routinely make full use of the information in such time series. We used mysid shrimp Americamysis bahia toxicity and demographic data to demonstrate the value of a toxicokinetic-toxicodynamic model coupled with a series of matrix population models in risk assessment refinements. This species is a small epibenthic marine crustacean routinely used in regulatory toxicity tests. We demonstrate how the model coupling can refine current risk assessments using only existing standard regulatory toxicity test results. Several exposure scenarios (each with the same initial risk characterization as determined by a more traditional organism-based approach) were created within which population modeling documented risks different from those of assessments based on the traditional approach. We also present different acute and chronic toxicity data scenarios by which toxicokinetic-toxicodynamic coupled with population modeling can distinguish responses that traditional risk evaluations are not designed to detect. Our results reinforce the benefits of this type of modeling in risk evaluations, especially related to time-varying exposure concentrations. Environ Toxicol Chem 2018;37:2633-2644. Published 2018 Wiley Periodicals Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America.
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Affiliation(s)
- Glen Thursby
- USEPA, Office of Research and Development, National Health and Environmental Effects Research Laboratory, Atlantic Ecology Division, Narragansett, RI USA 02882
| | - Keith Sappington
- USEPA, Office of Pesticide Programs, Environmental Fate and Effect Division, Washington, DC USA 20460
| | - Mathew Etterson
- USEPA, Office of Research and Development, National Health and Environmental Effects Research Laboratory, Mid-Continental Ecology Division, Duluth, MN USA 55804
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Mintram KS, Brown AR, Maynard SK, Thorbek P, Tyler CR. Capturing ecology in modeling approaches applied to environmental risk assessment of endocrine active chemicals in fish. Crit Rev Toxicol 2017; 48:109-120. [PMID: 28929839 DOI: 10.1080/10408444.2017.1367756] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Endocrine active chemicals (EACs) are widespread in freshwater environments and both laboratory and field based studies have shown reproductive effects in fish at environmentally relevant exposures. Environmental risk assessment (ERA) seeks to protect wildlife populations and prospective assessments rely on extrapolation from individual-level effects established for laboratory fish species to populations of wild fish using arbitrary safety factors. Population susceptibility to chemical effects, however, depends on exposure risk, physiological susceptibility, and population resilience, each of which can differ widely between fish species. Population models have significant potential to address these shortfalls and to include individual variability relating to life-history traits, demographic and density-dependent vital rates, and behaviors which arise from inter-organism and organism-environment interactions. Confidence in population models has recently resulted in the EU Commission stating that results derived from reliable models may be considered when assessing the relevance of adverse effects of EACs at the population level. This review critically assesses the potential risks posed by EACs for fish populations, considers the ecological factors influencing these risks and explores the benefits and challenges of applying population modeling (including individual-based modeling) in ERA for EACs in fish. We conclude that population modeling offers a way forward for incorporating greater environmental relevance in assessing the risks of EACs for fishes and for identifying key risk factors through sensitivity analysis. Individual-based models (IBMs) allow for the incorporation of physiological and behavioral endpoints relevant to EAC exposure effects, thus capturing both direct and indirect population-level effects.
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Affiliation(s)
- Kate S Mintram
- a College of Life and Environmental Sciences , University of Exeter , Exeter , UK
| | - A Ross Brown
- a College of Life and Environmental Sciences , University of Exeter , Exeter , UK
| | - Samuel K Maynard
- b Syngenta, Jealott's Hill International Research Centre , Bracknell , Berkshire , UK
| | - Pernille Thorbek
- b Syngenta, Jealott's Hill International Research Centre , Bracknell , Berkshire , UK
| | - Charles R Tyler
- a College of Life and Environmental Sciences , University of Exeter , Exeter , UK
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Simultaneous determination of multiclass pesticide residues in human plasma using a mini QuEChERS method. Anal Bioanal Chem 2017; 409:3757-3765. [DOI: 10.1007/s00216-017-0317-7] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2017] [Revised: 03/01/2017] [Accepted: 03/14/2017] [Indexed: 11/26/2022]
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Perez-Gonzalez E, Osuna-Martinez UG, Herrera-Moreno MN, Rodriguez-Meza GD, Gonzalez-Ocampo HA, Bucio-Pacheco M. Organochlorine Pesticides in Gonad, Brain, and Blood of Mice in Two Agricultural Areas of Sinaloa. BULLETIN OF ENVIRONMENTAL CONTAMINATION AND TOXICOLOGY 2017; 98:454-459. [PMID: 28110349 DOI: 10.1007/s00128-016-2028-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2016] [Accepted: 12/30/2016] [Indexed: 05/19/2023]
Abstract
The adverse effect of pesticides on non-target wildlife and human health is a primary concern in the world, but in Mexico, we do not know which wildlife species are at the greatest risk. The aim of this study was to determine organochlorine pesticides in mice of two agricultural fields in Sinaloa, Culiacan and Guasave. Procedures of extraction, analysis, and quantification were followed according to the modified EPA 8081b method. In three mouse tissues (gonad, brain, and blood), γBHC and decachlorobiphenyl with a frequency higher than 50% and endosulfan sulfate with 43% were observed. The wildlife fauna living in agricultural areas are at great risk due to: (1) diversity of the chemicals used for pest control, like mice, and (2) variety of organochlorine pesticides in direct or indirect contact with non-target organisms, affecting the health of animals and humans (toxic effects and accumulation).
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Affiliation(s)
- Ernestina Perez-Gonzalez
- Centro de Estudios Justo Sierra, Higher Education level, Surutato, Badiraguato, Sinaloa, Mexico.
- Departamento de Medio Ambiente, Instituto Politecnico Nacional-CIIDIR-Sinaloa, Bulevar Juan De Dios Batiz Paredes #250, Colonia San Joachin, C.P. 81101, Guasave, Sinaloa, Mexico.
| | | | - Maria-Nancy Herrera-Moreno
- Departamento de Medio Ambiente, Instituto Politecnico Nacional-CIIDIR-Sinaloa, Bulevar Juan De Dios Batiz Paredes #250, Colonia San Joachin, C.P. 81101, Guasave, Sinaloa, Mexico
| | - Guadalupe-Durga Rodriguez-Meza
- Departamento de Medio Ambiente, Instituto Politecnico Nacional-CIIDIR-Sinaloa, Bulevar Juan De Dios Batiz Paredes #250, Colonia San Joachin, C.P. 81101, Guasave, Sinaloa, Mexico
| | - Hector-A Gonzalez-Ocampo
- Departamento de Medio Ambiente, Instituto Politecnico Nacional-CIIDIR-Sinaloa, Bulevar Juan De Dios Batiz Paredes #250, Colonia San Joachin, C.P. 81101, Guasave, Sinaloa, Mexico
| | - Marcos Bucio-Pacheco
- Centro de Estudios Justo Sierra, Higher Education level, Surutato, Badiraguato, Sinaloa, Mexico
- Departamento de Información y Bibliografia Especializada, Escuela de Biologia, Universidad Autonoma de Sinaloa, Culiacan, Sinaloa, Mexico
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KAUR GURPREET, JAIN AK, SINGH SANDEEP. CYP/PON genetic variations as determinant of organophosphate pesticides toxicity. J Genet 2017; 96:187-201. [DOI: 10.1007/s12041-017-0741-7] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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Forbes VE, Galic N. Next-generation ecological risk assessment: Predicting risk from molecular initiation to ecosystem service delivery. ENVIRONMENT INTERNATIONAL 2016; 91:215-219. [PMID: 26985654 DOI: 10.1016/j.envint.2016.03.002] [Citation(s) in RCA: 44] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2016] [Revised: 03/04/2016] [Accepted: 03/05/2016] [Indexed: 06/05/2023]
Abstract
Ecological risk assessment is the process of evaluating how likely it is that the environment may be impacted as the result of exposure to one or more chemicals and/or other stressors. It is not playing as large a role in environmental management decisions as it should be. A core challenge is that risk assessments often do not relate directly or transparently to protection goals. There have been exciting developments in in vitro testing and high-throughput systems that measure responses to chemicals at molecular and biochemical levels of organization, but the linkage between such responses and impacts of regulatory significance - whole organisms, populations, communities, and ecosystems - are not easily predictable. This article describes some recent developments that are directed at bridging this gap and providing more predictive models that can make robust links between what we typically measure in risk assessments and what we aim to protect.
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Affiliation(s)
- Valery E Forbes
- Department of Ecology, Evolution, and Behavior, College of Biological Sciences, 123 Snyder Hall, 1475 Gortner Ave, St. Paul, MN 55018, USA.
| | - Nika Galic
- Department of Ecology, Evolution, and Behavior, College of Biological Sciences, 123 Snyder Hall, 1475 Gortner Ave, St. Paul, MN 55018, USA.
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Schmitt W, Auteri D, Bastiansen F, Ebeling M, Liu C, Luttik R, Mastitsky S, Nacci D, Topping C, Wang M. An example of population-level risk assessments for small mammals using individual-based population models. INTEGRATED ENVIRONMENTAL ASSESSMENT AND MANAGEMENT 2016; 12:46-57. [PMID: 25891765 DOI: 10.1002/ieam.1640] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2014] [Revised: 12/30/2014] [Accepted: 03/05/2015] [Indexed: 06/04/2023]
Abstract
This article presents a case study demonstrating the application of 3 individual-based, spatially explicit population models (IBMs, also known as agent-based models) in ecological risk assessments to predict long-term effects of a pesticide to populations of small mammals. The 3 IBMs each used a hypothetical fungicide (FungicideX) in different scenarios: spraying in cereals (common vole, Microtus arvalis), spraying in orchards (field vole, Microtus agrestis), and cereal seed treatment (wood mouse, Apodemus sylvaticus). Each scenario used existing model landscapes, which differed greatly in size and structural complexity. The toxicological profile of FungicideX was defined so that the deterministic long-term first tier risk assessment would result in high risk to small mammals, thus providing the opportunity to use the IBMs for risk assessment refinement (i.e., higher tier risk assessment). Despite differing internal model design and scenarios, results indicated in all 3 cases low population sensitivity unless FungicideX was applied at very high (×10) rates. Recovery from local population impacts was generally fast. Only when patch extinctions occured in simulations of intentionally high acute toxic effects, recovery periods, then determined by recolonization, were of any concern. Conclusions include recommendations for the most important input considerations, including the selection of exposure levels, duration of simulations, statistically robust number of replicates, and endpoints to report. However, further investigation and agreement are needed to develop recommendations for landscape attributes such as size, structure, and crop rotation to define appropriate regulatory risk assessment scenarios. Overall, the application of IBMs provides multiple advantages to higher tier ecological risk assessments for small mammals, including consistent and transparent direct links to specific protection goals, and the consideration of more realistic scenarios.
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Affiliation(s)
- Walter Schmitt
- Bayer CropScience AG, Environmental Safety, Monheim, Germany
| | - Domenica Auteri
- European Food and Safety Agency, Pesticides Unit, Parma, Italy
| | | | - Markus Ebeling
- Bayer CropScience AG, Environmental Safety, Monheim, Germany
| | - Chun Liu
- Syngenta, Jealott's Hill International Research Centre, Bracknell, Berkshire, United Kingdom
| | | | | | - Diane Nacci
- US Environmental Protection Agency, Atlantic Ecology Division-Population Ecology Branch, Narragansett, Rhode Island
| | - Chris Topping
- Aarhus University, Department of Bioscience, Rønde, Denmark
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Stratonovitch P, Elias J, Denholm I, Slater R, Semenov MA. An individual-based model of the evolution of pesticide resistance in heterogeneous environments: control of Meligethes aeneus population in oilseed rape crops. PLoS One 2014; 9:e115631. [PMID: 25531104 PMCID: PMC4274105 DOI: 10.1371/journal.pone.0115631] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2014] [Accepted: 11/27/2014] [Indexed: 12/02/2022] Open
Abstract
Preventing a pest population from damaging an agricultural crop and, at the same time, preventing the development of pesticide resistance is a major challenge in crop protection. Understanding how farming practices and environmental factors interact with pest characteristics to influence the spread of resistance is a difficult and complex task. It is extremely challenging to investigate such interactions experimentally at realistic spatial and temporal scales. Mathematical modelling and computer simulation have, therefore, been used to analyse resistance evolution and to evaluate potential resistance management tactics. Of the many modelling approaches available, individual-based modelling of a pest population offers most flexibility to include and analyse numerous factors and their interactions. Here, a pollen beetle (Meligethes aeneus) population was modelled as an aggregate of individual insects inhabiting a spatially heterogeneous landscape. The development of the pest and host crop (oilseed rape) was driven by climatic variables. The agricultural land of the landscape was managed by farmers applying a specific rotation and crop protection strategy. The evolution of a single resistance allele to the pyrethroid lambda cyhalothrin was analysed for different combinations of crop management practices and for a recessive, intermediate and dominant resistance allele. While the spread of a recessive resistance allele was severely constrained, intermediate or dominant resistance alleles showed a similar response to the management regime imposed. Calendar treatments applied irrespective of pest density accelerated the development of resistance compared to ones applied in response to prescribed pest density thresholds. A greater proportion of spring-sown oilseed rape was also found to increase the speed of resistance as it increased the period of insecticide exposure. Our study demonstrates the flexibility and power of an individual-based model to simulate how farming practices affect pest population dynamics, and the consequent impact of different control strategies on the risk and speed of resistance development.
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Affiliation(s)
- Pierre Stratonovitch
- Computational and Systems Biology Department, Rothamsted Research, Harpenden, Herts, United Kingdom
| | - Jan Elias
- Syngenta Crop Protection AG, Research Biology, Werk Stein, Schaffhauserstrasse, Stein, Switzerland
| | - Ian Denholm
- Human and Environmental Sciences Department, University of Hertfordshire, Hatfield, Herts, United Kingdom
| | - Russell Slater
- Syngenta Crop Protection AG, Research Biology, Werk Stein, Schaffhauserstrasse, Stein, Switzerland
| | - Mikhail A. Semenov
- Computational and Systems Biology Department, Rothamsted Research, Harpenden, Herts, United Kingdom
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Grimm V, Thorbek P. Population models for ecological risk assessment of chemicals: Short introduction and summary of a special issue. Ecol Modell 2014. [DOI: 10.1016/j.ecolmodel.2014.01.017] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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