Article pubs.acs.org/est
Modeling PCB-Bioaccumulation in the Bottlenose Dolphin (Tursiops truncatus): Estimating a Dietary Threshold Concentration Brendan E. Hickie,*,† Marc A. Cadieux,†,‡ Kimberly N. Riehl,† Gregory D. Bossart,§ Juan José Alava,∥ and Patricia A. Fair⊥ †
Environmental and Resource Studies Program and Environmental and Life Sciences Graduate Program, Trent University, Peterborough, Ontario K9J7B8,Canada ‡ Clayton H. Riddell Faculty of Environment, Earth, and Resources, University of Manitoba, Winnipeg, Manitoba, R3T 2N2, Canada § Georgia Aquarium, NW Atlanta, Georgia 30313 United States ∥ School of Resource and Environmental Management, Faculty of Environment, Simon Fraser University, 8888 University Drive, Burnaby, British Columbia V5A 1S6, Canada ⊥ Center for Coastal Environmental Health & Biomolecular Research, National Oceanic and Atmospheric Administration, National Ocean Service, 219 Fort Johnson Road, Charleston, South Carolina 29412-9110 United States S Supporting Information *
ABSTRACT: An individually based (IB) model to predict PCB concentrations in the bottlenose dolphin population of Charleston, SC, USA, was developed with the aim to gain a better understanding of the bioaccumulation behavior and health risk of dietary PCBs across the population and their prey. PCB concentrations predicted in male and female bottlenose dolphin were in good agreement with observed tissue concentrations corroborating the reliability of the model performance and its utility in gaining a more complete view of risk. The modeled cumulative distribution of ΣPCB concentrations for the population with a breakdown into juvenile, adult male, and female subclasses ranged from 3600 to 144,400 ng/g lipid with 66% to >80% of the population exceeding the established threshold for adverse health effects of 17,000 ng/g lipid. The model estimated that a dietary PCB concentration not exceeding 5.1 ng/g wet wt would be required to reach a condition where 95% of the population would have tissue levels below the health effect threshold. The IB model for PCBs in bottlenose dolphins provides a novel approach to estimating the maximum acceptable dietary concentration for PCBs, a central and important factor to protect these apex predators. The model also enables effective prediction of concentrations in dolphins from fish contaminant surveys which are logistically easier and less costly to collect.
■
INTRODUCTION In 2004, the Stockholm Convention of Persistent Organic Pollutants (POPs) was endorsed by 131 nations to eliminate the world’s most persistent, bioaccumulative, and toxic substances (UNEP, 2001). Such substances include polychlorinated biphenyls (PCBs), which are ubiquitous in the environment and can cause adverse health effects in wildlife and humans.1,2 These bioaccumulative substances are of great concern because of their potential to reach toxicologically significant tissue concentrations in high-trophic level species. Marine mammals accumulate high levels of POPs, reflecting their long life spans, large lipid reserves, and high trophic position in the aquatic food web as well as their reduced capacity to eliminate these compounds.3,4 Individual POP burdens are influenced by many life history factors including body size, body condition, nutritive condition, disease, metabolism, age, and sex, along with variability in prey selection. 5 Exposure to lipophilic POPs has been linked to immune dysfunction, increased susceptibility to infectious © 2013 American Chemical Society
disease, and disruption of endocrine and reproductive systems in marine mammals.6−11 Species or populations of marine mammals residing in more contaminated coastal areas are the most likely to accumulate high concentrations of many pollutants, thus increasing their risk of suffering adverse health effects.12,13 In recent years, species-specific contaminant bioaccumulation models have been developed for several marine mammal species. Individual and population-based models developed for beluga whales (Delphinapterus leucas) and Arctic ringed seals (Phoca hispida) were used to construct their history of exposure to PCBs and to predict possible future trends.14,15 More recently, models for killer whales (Orcinus orca) were reported characterizing the history of PCB contamination and the Received: Revised: Accepted: Published: 12314
July 17, 2013 September 23, 2013 September 27, 2013 September 27, 2013 dx.doi.org/10.1021/es403166b | Environ. Sci. Technol. 2013, 47, 12314−12324
Environmental Science & Technology
Article
two internal compartments (i.e., blubber and core), and elimination via feces and biotransformation in individual male and female dolphins on a daily basis from weaning until death (approximately 45 years for bottlenose dolphins). Equilibrium distribution of contaminants is assumed between the blubber (i.e., about 22% of total mass and 38% lipid) and the remaining “core” of the animal (i.e., about 5% lipid on average) which includes skin, bone, blood, muscle, and organs. The set of equations and calculations performed for each day for a male or nonreproductive female are reported in Hickie et al.4 The model also also accounts for contaminant accumulation and losses in reproductively active females (gestation, birth, and nursing) and their progeny until they are weaned. In this application, the model was run to pseudo steady-state by using a constant diet concentration throughout each model simulation and by running the model recursively until predicted concentrations for all ages stabilized with respect to time. For the IB model, this required three to four recursions or dolphin generations to reach stability ( males (F: 43% SD = 10.6 vs. M: 35% SD = 9.0; p = 0.0016). HERA: Dolphin Health and Risk Assessment Project (Fair et al.30). bNursing can extend over 3.5 years; reliance on milk is assumed to diminish linearly after 320 days.46,52 cMean of samples from 72 animals (SD = 10.4%).
dolphins has been estimated to range from 5.0 to 6.5 kg/day/ dolphin,32 which is similar to the rate estimated by the model. Data characterizing contaminant levels in whole fish were from analysis conducted by the NOAA/NOS Charleston Laboratory, both as unpublished data as well as those reported by the South Carolina Estuarine and Coastal Assessment Program (SCE12316
dx.doi.org/10.1021/es403166b | Environ. Sci. Technol. 2013, 47, 12314−12324
Environmental Science & Technology
Article
Figure 1. Map of the study area where bottlenose dolphins and fish were sampled.
Figure 2. Mean RRel values (using PCB 180 as the reference; eq 1) for 21 PCB congeners or coeluting congener groups for CHS bottlenose dolphins. Chemicals with an RRel approaching or exceeding unity are considered to be resistant to biotransformation. RRel values less than 0.3 are considered to be readily eliminated by enzyme-mediated biotransformation pathways.
concentration (or range) that provided the best overall fit to the dolphin data for each selected chemical and for ΣPCB. We did this by manually changing the diet concentration of each chemical to get the best agreement between the model and the empirical data for PCBs reported for the CHS dolphin population for the summer periods 2003−2005.26 Biotransformation Rate Constants of Selected PCBs. To estimate biotransformation rate constants for the modeling work, PCB-metabolic indices (i.e., relative retention (RRel) values) were first calculated according to the equation devised by Boon et al.:35 RRel PCBi =
[PCBi]/[PCBR ]predator [PCBi]/[PCBR ]prey
where RRel is the index of susceptibility to biotransformation relative to a reference chemical in the predator−prey relationship; PCBi is the PCB congener for which RRel is being calculated; and PCBR the reference chemical known to be resistant to biotransformation. In effect, this equation calculates the biomagnification factor for PCBi as a proportion of the biomagnification factor for a reference chemical that is considered to be resistant to biotransformation processes (e.g., PCB 153 or 180). PCB 180 was used here as the more commonly used PCB 153 coeluted with PCBs 132 and 168. An RRel value of 1.0 shows that PCBi is also resistant to biotransformation, while a lower RRel value (i.e.,
