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用于生态效应评估和水质标准设定的生态系统模型中不同毒性效应子模型的比较。

Comparison of different toxic effect sub-models in ecosystem modelling used for ecological effect assessments and water quality standard setting.

作者信息

De Laender Frederik, De Schamphelaere Karel A C, Vanrolleghem Peter A, Janssen Colin R

机构信息

Laboratory of Environmental Toxicology and Aquatic Ecology, Ghent University (UGent), Jozef Plateaustraat 22, B-9000 Gent, Belgium.

出版信息

Ecotoxicol Environ Saf. 2008 Jan;69(1):13-23. doi: 10.1016/j.ecoenv.2007.08.020. Epub 2007 Oct 22.

Abstract

Ecosystem models, combining a food web model with a toxic effect sub-model, have been proposed to incorporate ecological interactions in ecological effect assessments. Toxic effect sub-models in different studies tend to differ in (1) the used single-species toxicity data, (2) the effects they consider, (3) the concentration-effect function used. In this paper, we constructed four ecosystem models, each with a different toxic effect sub-model, and tested their capacity to predict biomass changes, and no observed effect concentrations (NOECs) established in an experimental microcosm. For most populations, these predictions depended heavily on the type of ecosystem model. The ecosystem model with a toxic effect sub-model incorporating mortality effects using a logistic concentration-effect function made accurate predictions for most populations. Additional incorporation of sub-lethal effects did not result in better predictions. Ecosystem models using linear concentration-effect functions predict biomass decreases at concentrations that are four times lower than the observed NOECs.

摘要

已提出将食物网模型与毒性效应子模型相结合的生态系统模型,以便在生态效应评估中纳入生态相互作用。不同研究中的毒性效应子模型往往在以下方面存在差异:(1)所使用的单物种毒性数据;(2)它们所考虑的效应;(3)所使用的浓度-效应函数。在本文中,我们构建了四个生态系统模型,每个模型都有不同的毒性效应子模型,并测试了它们预测生物量变化以及在实验微观世界中确定的无观察效应浓度(NOECs)的能力。对于大多数种群而言,这些预测在很大程度上取决于生态系统模型的类型。具有使用逻辑浓度-效应函数纳入死亡率效应的毒性效应子模型的生态系统模型,对大多数种群做出了准确的预测。额外纳入亚致死效应并未带来更好的预测结果。使用线性浓度-效应函数的生态系统模型预测,在浓度比观察到的NOECs低四倍时生物量会下降。

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