Using the expert model PERPEST to translate measured and predicted pesticide exposure data into ecological risks

An important topic in the registration of pesticides and the interpretation of monitoring data is the estimation of the consequences of a certain concentration of a pesticide for the ecology of aquatic ecosystems. Solving these problems requires predictions of the expected response of the ecosystem to chemical stress. Up until now, a dominant approach to come up with such a prediction is the use of simulation models or safety factors. The disadvantage of the use of safety factors is a crude method that does not provide any insight into the concentration–response relationships at the ecosystem level. On the other hand, simulation models also have serious drawbacks like that they are often very complex, lack transparency, their implementation is expensive and there may be a compilation of errors, due to uncertainties in parameters and processes. In this paper, we present the expert model prediction of the ecological risks of pesticides (PERPEST) that overcomes these problems. It predicts the effects of a given concentration of a pesticide based on the outcome of already performed experiments using experimental ecosystems. This has the great advantage that the outcome is more realistic. The paper especially discusses how this model can be used to translate measured and predicted concentrations of pesticides into ecological risks, by taking data on measured and predicted concentrations of atrazine as an example. It is argued that this model can be of great use to evaluate the outcome of chemical monitoring programmes (e.g. performed in the light of the Water Framework Directive) and can even be used to evaluate the effects of mixtures.     

A multi-scale approach to modelling spatial and dynamic ecological patterns for reservoir's water quality management

With growing levels of urbanization and agriculture throughout the world, it is increasingly important that both research and management efforts take into account the effects of this widespread landscape alteration and its consequences for natural systems. Freshwater ecosystems, namely reservoirs, are particularly sensitive to land use changes. In this context, modelling can be very useful, for decision support, as an investigative tool to forecast the outcome of various scenarios, to guide current management in order to meet future targets and to develop integrated frameworks for management accordingly to the Water Framework Directive (WFD). The present paper examined the applicability of a holistic Stochastic-Dynamic Methodology (StDM), coupled with a Cellular Automata (CA) model, in capturing how expected changes at land use level will alter the ecological status of lentic ecosystems, namely at physicochemical and biological levels. The methodology was applied to Portuguese reservoirs located in the Douro's basin and illustrated with a series of stochastic-dynamic and spatial outputs taking into account expected scenarios regarding land use changes. Overall, the simulation results are encouraging since they seem to demonstrate the tool reliability in capturing the stochastic environmental dynamics of the selected metrics facing spatial explicit scenarios. The ultimate goal was to couple monitoring assessment and the described modelling techniques to ease management and decision making regarding the practical implementation of the WFD, both at the scale of the reservoir body and at the scale of the respective river watershed dynamics.     

依据(代)生物体对化学品的反应预测对生态系统服务功能的影响

保护生态系统服务功能越来越多地被作为风险评估的目标,但是目前生态风险评估的终点和评估生态系统服务功能受到的潜在影响之间有很大的差距。作者提出了一个框架,将常用的生态毒理学终点与对种群和群落的影响以及生态系统的服务功能联系起来。这个框架建立在机制效应模型的长足进步上,这些模型旨在跨越多种生物组织,并解释各种生物相互作用和反馈。为了说明这一点,作者引入了2个研究案例,它们采用了已完善和已验证的机制效应模型：鱼种群的inSTREAM个体模型和AQUATOX生态系统模型。他们还展示了动态能量平衡理论可以为解释组织级毒性提供一种通用货币。他们认为,一个基于机制模型的框架,可以预测化学品暴露对生态系统服务的影响,再结合经济估值,可以为环境管理提供一种有用的方法。作者强调了使用这个框架的潜在好处以及未来工作中需要解决的挑战。
精选自Forbes, V. E., Salice, C. J., Birnir, B., Bruins, R. J.F., Calow, P., Ducrot, V., Galic, N., Garber, K., Harvey, B. C., Jager, H., Kanarek, A., Pastorok, R., Railsback, S. F., Rebarber, R. and Thorbek, P. (2017), A framework for predicting impacts on ecosystem services from (sub)organismal responses to chemicals. Environmental Toxicology and Chemistry, 36: 845–859. doi: 10.1002/etc.3720
详情请见http://onlinelibrary.wiley.com/doi/10.1002/etc.3720/full