The footprint of pesticide stress in communities—Species traits reveal community effects of toxicants

Liess, Matthias; Schäfer, Ralf B.; Schriever, Carola A.

doi:10.1016/j.scitotenv.2008.05.054

Cited by 176 publications

(143 citation statements)

References 28 publications

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“…non-chemical agricultural management). For aquatic biotopes several field investigations have identified the values for abiotic parameters (Liess and von der Ohe, 2005;Liess et al, 2008). For example, long-living K-strategists thrive only if ecosystem disturbance is limited, and may need, for example, continuous water flow.…”

Section: Abiotic Parametersmentioning

confidence: 99%

Scientific Opinion on good modelling practice in the context of mechanistic effect models for risk assessment of plant protection products

2014

EFS2

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The Panel has interpreted the Terms of Reference as a stepwise analysis of issues relevant to both the development and the evaluation of models to assess ecological effects of pesticides. The regulatory model should be selected or developed to address the relevant specific protection goal. The basis of good modelling practice must be the knowledge of relevant processes and the availability of data of sufficient quality. The opinion identifies several critical steps in order to set models within risk assessment, namely: problem formulation, considering the specific protection goals for the taxa or functional groups of concern; model domain of applicability, which drives the species and scenarios to model; species (and life stage) selection, considering relevant life history traits and toxicological/toxicokinetics characteristics of the pesticide; selection of the environmental scenario, which is defined by a combination of abiotic, biotic and agronomic parameters to provide a realistic worst-case situation. Model development should follow the modelling cycle, in which every step has to be fully documented: (i) problem definition; (ii) model formulation, i.e. design of a conceptual model; (iii) model formalisation, in which variables and parameters are linked together into mathematical equations or algorithms; (iv) model implementation, in which a computer code is produced and verified; (v) model setup, including sensitivity analysis, uncertainty analysis and comparison with observed data, that delivers the regulatory model; (vi) prior to actual use in risk assessment, the regulatory model should be evaluated for relevance to the specific protection goals; (vii) feedback from risk assessor with possible recommendations for model improvement. Model evaluation by regulatory authorities should consider each step of the modelling cycle: the opinion identifies points of particular attention for the use of mechanistic effect models in pesticide risk assessment. It is recommended that models be documented in a complete and transparent way, that a feedback platform be established involving risk assessors and model developers, and that a set of agreed models be made available. The Panel has interpreted the Terms of Reference to mean a provision of a stepwise analysis of issues relevant to both the development and the assessment of models to assess ecological effects of pesticides. In accordance with the Terms of Reference, the Panel has pointed out mainly those general issues shared by several types of models and/or application fields, but some specific issues have been considered if highly relevant to a given model type and/or application field.The PPR Panel emphasises that the availability and quality of data are of the utmost importance at all stages of modelling. If the data are not sufficient, the regulatory model may not be considered acceptable for risk assessment.Clear and accurate problem formulation is the first critical step to implement the use of any model within risk assessment: the risk assessment ar...

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Section: Abiotic Parametersmentioning

confidence: 99%

Scientific Opinion on good modelling practice in the context of mechanistic effect models for risk assessment of plant protection products

2014

EFS2

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“…Apesar dos efeitos biológicos e bioquímicos poderem vincular a biodisponibilidade dos compostos de interesse com a sua concentração em órgãos-alvo e toxicidade intrínseca, as limitações do biomonitoramento, como os fatores que não estão relacionados com a poluição; devem ser cuidadosamente considerados na interpretação dos dados ( VAN DER OOST et al, 2003) já que algumas características biológicas geralmente respondem a diferentes estressores e, portanto não são susceptíveis de discriminar os efeitos de múltiplos estressores (LIESS et al, 2008). Para tanto, é necessário conhecer as condições de exposição no ambiente e melhorar a compreensão da toxicocinética da mistura total e seus componentes, além de características das espécies em estudo RICE et al, 2008;GOMEZ-EYLES et al, 2009).…”

Section: Indicadores Biológicosunclassified

Proposta conceitual de estudo para a integração e gerenciamento do uso de marcadores bioquímicos de contaminação ambiental

Castro

Jonsson

2011

Biotemas

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A agricultura sustentável prioriza o uso racional da terra e da biota. Para tanto, é necessária a compreensão da interação entre os insumos agrícolas e os ecossistemas. Porém, há carência de métodos de fácil acesso para a verificação de contaminação ambiental por muitos desses produtos, como os agrotóxicos e de suas misturas. A aplicação de métodos alternativos no monitoramento de áreas degradadas pode gerar vantagens econômicas quando comparados à implementação de protocolos de análise que utilizam métodos de alto custo que demandam maior tempo de análise. Uma vez que a saúde ambiental pode ser avaliada por meio de estudos com indicadores biológicos, a abordagem aqui apresentada objetiva discutir alguns aspectos a respeito do monitoramento de risco ambiental com organismos não-alvo sentinela, focando parâmetros bioquímicos. Tais parâmetros evidenciariam que o agrotóxico penetrou no organismo e ocasionou uma resposta a um efeito de acordo com a dose ou o tempo de exposição. Esses parâmetros poderão ser utilizados como indicadores biológicos bioquímicos em programas de monitoramento ambiental devido à identificação precoce de alterações. Os resultados obtidos de seu uso poderão ser utilizados para subsidiar políticas relacionadas ao gerenciamento de riscos ambientais. Palavras-chave: Agrotóxicos, Árvore de decisão, Enzimas, Indicadores biológicos, Monitoramento ambiental AbstractConceptual study proposal for the integration and management of biochemical markers of environmental contamination use. Sustainable agriculture prioritizes the rational use of land and biota. For this, there is a need for understanding the interaction between the agriculture inputs and the ecosystems. However, there is a lack of easy access methods for verifying environmental contamination due to many of these products, such as pesticides and their mixtures. The application of alternative methods for monitoring degraded areas can generate economic advantages when compared to the implementation of protocols for analysis using high cost methods which demand a longer analysis time. Since environmental health can be accessed through studies using biomarkers, the approach presented here aims to discuss some aspects on the environmental risk monitoring with sentinel non-target organisms, focusing on biochemical parameters. Such parameters showed that the pesticide penetrated into the body and caused a response according to the dose or time of exposition.

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“…The implementation of the CA model, using as toxicological endpoints Predicted Environmental Concentration (PEC) and Predicted No Effect Concentration (PNEC), for non-target representative organisms of aquatic ecosystems (algae, daphnids and fish), made it possible to estimate the volume of grey water of pesticides mixtures. In this regard, Liess et al (2008) concluded that, relating pesticide exposure to species traits in communities enables the identification and prediction of ecotoxicological effects of pesticides on the ecosystem level.…”

Section: Introductionmentioning

confidence: 99%

A mathematical model to estimate the volume of grey water of pesticide mixtures

Paraíba

Pazianotto

Luiz

et al. 2014

Span. j. agric. res.

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The usual method to calculate grey water footprint does not take into account the volume of water required to dilute concentrations of pesticide mixtures in freshwater and it also depends on maximum concentration limit acceptable in water. We propose a model to estimate the grey water footprint of crops by calculating the volume of water necessary to dilute pesticide mixtures reaching freshwaters. The model requires short-term toxicity data from aquatic organisms based on EC50 values, soil pesticide half-life and soil sorption coefficient values, and does not require maximum concentration limit acceptable in water. The lixiviation rate and runoff rate of each pesticide was estimated by attenuation factor and by Soilfug model, respectively. The usefulness of the proposed model was illustrated by estimating the volume of grey water required to dilute the 17 most widely used herbicides in sugarcane crops of Brazil. The grey water footprint corresponding to the recommended agronomic dose for each herbicide varied between 4.20×106 m3 yr-1 and 1.20×1012 m3 yr-1 and the grey water footprint of the mixture of herbicides was 2.36×1012 m3 yr-1 in a cultivated area of 8.4×106 ha. These results establish the ranking position of each herbicide in the composition of the grey water footprint of mixture of herbicides. The rank of each herbicide could be used to create a label to be placed on the package of the pesticide, thus informing farmers about the volume of grey water per hectare due to the use of this herbicide.

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The footprint of pesticide stress in communities—Species traits reveal community effects of toxicants

Cited by 176 publications

References 28 publications

Scientific Opinion on good modelling practice in the context of mechanistic effect models for risk assessment of plant protection products

Scientific Opinion on good modelling practice in the context of mechanistic effect models for risk assessment of plant protection products

Proposta conceitual de estudo para a integração e gerenciamento do uso de marcadores bioquímicos de contaminação ambiental

A mathematical model to estimate the volume of grey water of pesticide mixtures

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