McLeod Anne M, Arnot Jon A, Borgå Katrine, Selck Henriette, Kashian Donna R, Krause Ann, Paterson Gord, Haffner G Doug, Drouillard Ken G
Great Lakes Institute for Environmental Research, University of Windsor, Windsor, Ontario, Canada.
Integr Environ Assess Manag. 2015 Apr;11(2):306-18. doi: 10.1002/ieam.1599. Epub 2015 Jan 6.
Trophic magnification factors (TMFs) provide a method of assessing chemical biomagnification in food webs and are increasingly being used by policy makers to screen emerging chemicals. Recent reviews have encouraged the use of bioaccumulation models as screening tools for assessing TMFs for emerging chemicals of concern. The present study used a food web bioaccumulation model to estimate TMFs for polychlorinated biphenyls (PCBs) in a riverine system. The uncertainty associated with model predicted TMFs was evaluated against realistic ranges for model inputs (water and sediment PCB contamination) and variation in environmental, physiological, and ecological parameters included within the model. Finally, the model was used to explore interactions between spatial heterogeneity in water and sediment contaminant concentrations and theoretical movement profiles of different fish species included in the model. The model predictions of magnitude of TMFs conformed to empirical studies. There were differences in the relationship between the TMF and the octanol-water partitioning coefficient (KOW ) depending on the modeling approach used; a parabolic relationship was predicted under deterministic scenarios, whereas a linear TMF-KOW relationship was predicted when the model was run stochastically. Incorporating spatial movements by fish had a major influence on the magnitude and variation of TMFs. Under conditions where organisms are collected exclusively from clean locations in highly heterogeneous systems, the results showed bias toward higher TMF estimates, for example the TMF for PCB 153 increased from 2.7 to 5.6 when fish movement was included. Small underestimations of TMFs were found where organisms were exclusively sampled in contaminated regions, although the model was found to be more robust to this sampling condition than the former for this system.
营养放大因子(TMFs)提供了一种评估食物网中化学物质生物放大作用的方法,并且越来越多地被政策制定者用于筛选新兴化学物质。最近的综述鼓励使用生物累积模型作为筛选工具,以评估关注的新兴化学物质的TMFs。本研究使用食物网生物累积模型来估算河流系统中多氯联苯(PCBs)的TMFs。针对模型输入(水和沉积物中PCB污染)的实际范围以及模型中包含的环境、生理和生态参数的变化,评估了与模型预测的TMFs相关的不确定性。最后,该模型被用于探索水和沉积物污染物浓度的空间异质性与模型中包含的不同鱼类理论移动剖面之间的相互作用。TMFs大小的模型预测符合实证研究。根据所使用的建模方法,TMF与正辛醇 - 水分配系数(KOW)之间的关系存在差异;在确定性情景下预测为抛物线关系,而当模型随机运行时预测为线性TMF - KOW关系。纳入鱼类的空间移动对TMFs的大小和变化有重大影响。在从高度异质系统中的清洁位置专门收集生物体的条件下,结果显示偏向于更高的TMF估计值,例如,当包括鱼类移动时,PCB 153的TMF从2.7增加到5.6。在仅在受污染区域对生物体进行采样的情况下,发现TMFs有小幅度的低估,尽管对于该系统,发现模型对这种采样条件比前一种情况更稳健。