Quantifying persistent chemical accumulation in fish as a function of bioenergetic demands and growth rates

这项研究是基于“剂量会产生毒性”这句格言。 剂量不是通过测量环境中化学品的平均浓度来准确量化的，而是通过预测“热”暴露的概率来量化的。 对于与鱼类等食物相关的化学品暴露，我们需要知道哪些因素和过程使某些鱼类比其他鱼类受到更严重的污染。 污染物浓度在鱼类物种内部和之间的这种变异性也具有生态重要性，因为这种变异性可以提供对食物网功能和结构的深入了解。 因此，这项研究对生态毒理学和水生态学都至关重要。 我们的目标是将毒物动力学模型与食物网模型相结合，以产生非稳态食物网模型，解释和预测污染物浓度在水生食物网的时间变异性。

This research is based on the adage that 'dose makes the poison'. Dose is not accurately quantified by measuring average concentrations of a chemical in the environment, but by predicting the probability of a 'hot' exposure. For chemical exposures associated with food such as fish, we need to know what factors and processes that make some fish more contaminated than others. This variability of contaminant concentrations within and among fish species is also of ecological importance for this variability can provide insight into food web function and structure. Therefore this research is critical to both ecotoxicology and aquatic ecology. We aim to integrate toxicokinetic modeling with food web models in order to produce non-steady state food web models that explain and predict the temporal variability of contaminant concentrations in aquatic food webs.