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Modeling bioaccumulation in coupled pelagic–benthic food chains: Past insights and future directions

By the 1960s it became recognized that certain organic compounds that had been used in large quantities and dispersed into the environment could persist and accumulate in biota to concentrations that cause adverse impacts. Examples included DDT, toxaphene, and polychlorinated biphenyls (PCBs). This understanding led to efforts to identify substances with high bioaccumulation potential. Early methods relied on laboratory bioconcentration tests that involved uptake and depuration phases in which aquatic organisms (often fish) were exposed to a constant concentration of the substance dissolved in water followed by exposure to clean water. Organisms were periodically sampled over the course of the test and analyzed to determine tissue concentrations of the substance investigated. These data were fitted to a simple model to estimate the uptake and elimination rates and the bioconcentration factor (BCF). The BCF represented the concentration ratio between the aquatic organism and water at steady state. Subsequent efforts led to the development of models to predict BCF from substance properties, most notably the correlations between BCF and log octanol–water partition coefficient (log KOW) [1,2]. While standardized laboratory bioconcentration tests provided a logical, empirical approach to identify substance-specific bioaccumulation concerns, further progress was gained through the introduction of mechanistic mass balance models that systematically described the various uptake and loss processes. One early example involved the prediction of PCB bioaccumulation in a Lake Michigan food chain [3]. This modeling framework incorporated a number of important concepts. First, 4 trophic levels were simulated (phytoplankton, zooplankton, forage fish, piscivorous fish) using a set of coupled, first-order kinetic equations under steady-state conditions. Second, 2 principal routes were considered for each trophic level beyond phytoplankton: uptake fromwater and ingestion of prey from the previous trophic level. Thus, unlike previous food-chain models that required prey concentrations as inputs, this model computed the prey concentrations associated with each trophic level based on the dissolved water concentration. Third, the rate of chemical uptake from water and food and role of growth dilution was linked to the bioenergetics of the organism using allometric scaling equations for each trophic level. Lastly, chemicalspecific toxicokinetic parameters (e.g., gill elimination rate, assimilation efficiency of contaminant from water and food) needed for model calibration were estimated using results from earlier lab studies. An important insight gained from model predictions and confirmed by field data compiled from Lake Michigan was that laboratory derived BCFs could significantly underestimate the extent to which PCBs were accumulated in field biota. This observation had significant management implications for derivation of water quality limits and emission reductions needed to achieve tissue concentrations that met regulatory guidelines. Subsequent field studies from Lake Ontario confirmed that lab BCFs underestimated field bioaccumulation factors (BAFs) for PCBs and a range of other organochlorine compounds even if differences in fish lipid content were taken into account [4]. Further work hypothesized that this discrepancy could be accounted for by dietary exposure in the field and subsequent digestion of prey lipid in the gut resulting in an elevated chemical gradient that caused the observed biomagnification—that is, higher lipid normalized concentration or fugacity in predator to that in prey [5]. In fact, for chemicals with log KOW > 5, the dietary route was shown in subsequent modeling efforts to be dominant route of exposure in pelagic food chains [6]. The hypothesis that lipid digestion in the gut accounted for biomagnification was later confirmed in laboratory and field studies [7]. Concerns posed by chemicals that exhibited biomagnification resulted in restrictions in use and emission in the decades that followed. However, due to their hydrophobic and persistent nature, historical releases, and subsequent distribution to particulates and erosion, deposition and settling to aquatic environments resulted in a legacy of sediments contaminated with these substances. Furthermore, field monitoring and multimedia fate modeling highlighted the role that in-place sediment pollution served in contributing to ongoing bioaccumulation and subsequent impairment of intended water body uses. Food-chain models were extended to include a direct pathway from sediments in addition to the pathway from the water column and to simulate time trends in response to changes in exposure. These models showed that the sediment pathway could be very important for food chains involving demersal fish and shellfish [8,9]. The paper that is the subject of the present essay provided a timely contribution in addressing the interplay of sediment and water column pathways in chemical fate and bioaccumulation [10]. This work expanded on an earlier modeling effort that predicted bioaccumulation of nonmetabolized, nonionic organic chemicals in a linear, pelagic food chain under steady-state conditions using characteristics of the organisms (e.g., weight, All Supplemental Data may be found in the online version of this article. See Table S1 for the number of citations and rank of all the “Top 100” papers, which in this essay is reference [10]. * Address correspondence to thomas.f.parkerton@exxonmobil.com. Published online in Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002/etc.2317 Environmental Toxicology and Chemistry, Vol. 32, No. 9, pp. 1931–1934, 2013 # 2013 SETAC Printed in the USA