Quantifying Uncertainty in the Trophic Magnification Factor Related to Spatial Movements of Organisms in a Food Web

Anne McLeod, Jon Arnot, Katrine Borgå, Henriette Selck, Donna Kashian, Ann Krause, Gord Paterson, D Doug Haffner, Ken Drouillard

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review


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
TidsskriftIntegrated Environmental Assessment and Management
Udgave nummer2
Sider (fra-til)306-318
StatusUdgivet - 2015

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