Future Work- Food Web AlterationHypothesis: Trophic position has a significant affect on PCB contamination in top predator fish.

Results- Lake Source AnalysisPCA (based on congener concentrations in fish) clearly distinguished locally-impacted lakes from those that are only atmospherically contaminated by PCBs (Figures 5 and 6).

Polychlorinated Biphenyl (PCB) Fish Contamination: A Look at Michigan’s Upper Peninsula Inland LakesEMILY C SOKOL1, NOEL R URBAN1, JUDITH A PERLINGER1, TANVIR KHAN1, CAREY FRIEDMAN2

1Department of Civil and Environmental Engineering, Michigan Technological University, 2Massachusetts Institute of Technology

BackgroundPolychlorinated biphenyls (PCBs) are a group of chemicals produced anthropogenically, primarily as flame retardants. PCBs are comprised of two phenyl rings attached by a carbon-carbon bond, with each ring containing up to five chlorines bonded to the carbon atoms (Figure 1). There are a total of 209 possible PCBs, or congeners, due to the possible combinations of number and positions of chlorine atoms on the biphenyl skeleton. Only 12 congeners are considered “dioxin-like” by the US EPA.

PCBs were banned from production in the late 1970s when cancer and negative effects on mammalian reproductive and nervous systems were observed following accidental exposure (Thomas, 2008). PCBs can be volatilized, transported in the atmosphere, and deposited to and reemitted from both aquatic and terrestrial ecosystems (Gouin et al., 2003). In Michigan, fish consumption advisories exist as a result of PCB bioaccumulation. Figure 2 shows the lakes in Michigan’s upper peninsula from which fish samples were analyzed for PCBs by the Michigan Department of Environmental Quality (MDEQ).

Objective

The objective of this study is to develop quantitative relationships between PCB concentrations in fish and the environmental factors influencing that contamination. These factors include:

•source of contamination- while all lakes are atmospherically impacted, some lakes also have local (industrial) sources.

•ecosystem characteristics• food web structure

The quantitative relationships may then be used to predict fish PCB contamination in lakes that have not been monitored. In addition, predictions may be made as to when it could be safe to consume a desired amount of fish based on scenarios of future PCB emissions to the environment.

Methods

Results- Calibration of BioaccumulationEPA’s BASS predicted most species PCB contamination adequately to proceed with food web manipulation (Figure 8).

Results- Contamination Complexity RevealedA two box model was developed to predict steady-state PCB congener concentrations in any given lake, assuming equilibrium with air and sediment (figure 3). The model was implemented for two lakes, but equilibrium partitioning between water and fish under-predicted measured PCB concentrations in fish (Figure 4).

ReferencesBecker, George C. Fishes of Wisconsin. Madison: U of Wisconsin, 1983. Print.

Dillon, C. O. Mysis Shrimp on the Blue - 52 Rivers. 52 Rivers. 15 Jan. 2013. Web. 20 May 2014. <http://52rivers.com/mysis-shrimp-on-the-blue/>.Gouin, T.; Mackay, D.; Jones, K. C.; Harner, T.; Meijer, S. N., Evidence for the "grasshopper" effect and fractionation during long-range atmospheric transport of organic contaminants. Environmental Pollution 2004, 128 (1-2), 139-148.Hanchin, P. A. 201X. The Fish Community of the Portage-Torch Lake System, Houghton County, Michigan in 2007-2008. State of Michigan Department of Natural Resources, Fisheries Special Report XX, Lansing.Michigan Lake Polygons. Michigan Department of Technology, Management and Budget. State of Michigan. 2002, http://www.mcgi.state.mi.us/mgdl/Newell, Bob. "Heptagenia Solitaria (Ginger Quill) Mayfly Nymph Pictures." Heptagenia Solitaria (Ginger Quill) Mayfly Nymph Pictures. 28 June 2011. Web. 20 May 2014.Phytoplankton. Michigan Environmental Education Curriculum, The Great Lakes Ecosystem. Michigan Technological University. Web. 21 May 2014. http://techalive.mtu.edu/meec/module08/Phytoplankton.htm.Thomas, G. O., Polychlorinated Biphenyls. In Encyclopedia of Ecology, Editors-in-Chief: Sven Erik, J., Eds. Academic Press: Oxford, 2008; pp 2872-2881USGS The National Map. National Elevation Data. National Atlas of the United States, May 29, 2013, http://viewer.nationalmap.gov/viewer/WI Fish ID. University of Wisconsin Sea Grant Institute. University of Wisconsin Center for Limnology, Wisconsin Department of Natural Resources, and the University of Wisconsin Sea Grant Institute, 2013. Web. 20 May 2014. <http://www.seagrant.wisc.edu/home/Default.aspx?tabid=604>.State of Michigan image. Volunteer @ NOAA. NOAA, 05 Oct. 2007. Web. 08 Dec. 2014. <http://www.volunteer.noaa.gov/michigan.html>.Zanden, M. J. V. and J. B. Rasmussen (1996). "A Trophic Position Model of Pelagic Food Webs: Impact on Contaminant Bioaccumulation in Lake Trout." Ecological Monographs 66(4): 451-477.White Sucker. New York Department of Natural Conservation, Web. 26 Feb. 2015. <http://www.dec.ny.gov/animals/94491.html>."Wisconsin Department of Natural Resources." Fishes of Wisconsin. Wisconsin Department of Natural Resources, 31 Aug. 2012. Web. 26 Feb. 2015. <http://dnr.wi.gov/topic/fishing/species/npike.html>."Wisconsin Department of Natural Resources." Fishes of Wisconsin. Wisconsin Department of Natural Resources, 31 Aug. 2012. Web. 26 Feb. 2015. <http://dnr.wi.gov/topic/fishing/species/yperch.html>.Kurtz, John, Victor Poretti, Thomas Miller, and Dean Bryson. "AMBIENT BIOMONITORING NETWORK Benthic Macroinvertebrate Data Executive Summary." AMBIENT BIOMONITORING NETWORK Benthic Macroinvertebrate Data Executive Summary. New Jersey Bureau of Freshwater and Biological Monitoring, 5 Feb. 2008. Web. 26 Feb. 2015. <http://www.state.nj.us/dep/wms/bfbm/GenExecSum.html>."Pix For Daphnia Diagram." Pix For Daphnia Diagram. N.p., Web. 26 Feb. 2015. <http://pixgood.com/daphnia-diagram.html>."Introduction: The Fathead Minnow." Aquatic Pathobiology Laboratory: Atlas of Fathead Minnow Normal Histology. University of Florida, Web. 26 Feb. 2015. <http://aquaticpath.phhp.ufl.edu/fhm/intro.html>.Scharff, R. F. "The History of European Fauna." Project Gutenberg. Project Gutenberg, 23 July 2010. Web. 26 Feb. 2015. <http://www.gutenberg.org/files/33236/33236-h/33236-h.htm>.

Figure 1: PCB chemical structure (Thomas, 2008)

Acknowledgements Funding provided by NSF (Project ICER-1313755) Fish sample measurements provided by Mr. Joseph Bohr, Water Resources Division, Michigan Department of Environmental Quality. EPA’s BASS model files and assistance from Mr. M. Craig Barber, research ecologistState of Michigan fish survey documents and expertise from Mr. Patrick Hanchin, Fisheries Biologist, Michigan Department of Natural Resources

Siskiwit Lake

Deer Lake

Lake LeVasseur

Manistique Lake

Muskallonge LakeOtter Lake

Boston Lake

Portage Lake

Torch Lake

Runkle Lake

Chicagon Lake

Emily Lake

Little Lake

Shag LakeSilver Lake

Sporley LakeGoose Lake

Engman Lake

ConclusionsResults show a statistically significant difference between congener distributions in fish from lakes with different sources of PCB contamination. This distinction allows us to assess PCB sources in all lakes. Mean depth was the parameter found to best predict PCB concentrations in fish. Ongoing analysis of biomagnification will reveal the effects of food web structure on PCB contamination in fish.

Figure 2: MDEQ sampled lakes from 2000 through 2010. An additional 13 lakes were sampled prior to 2000 where the fish were analyzed by an earlier method.

-0.1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

-0.4

-0.2

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0.2

0.4

0.6

0.8

1Emily Lake

Goose Lake

Little Lake

Manistique Lake

Otter LakePortage Lake

Silver Lake

Torch Lake

Shag LakeDeer Lake

Engman Lake

Goose Lake

Lake LeVasseur

Muskallonge Lake

Runkle Lake

Shakey Lakes

Torch Lake

Northern Pike Walleye

Component A

Com

pon

ent

B

only atmospherically impacted lakes

locally impacted lakes

Figure 5: PCA results. Species were analyzed separately. Component A consists of the first component for Walleye-sampled lakes and the second component for Northern Pike-sampled lakes (vice versa for component B). The component axes were altered so that the lakes sampled for both species (Goose Lake and Torch Lake) fell on the same axis. Only Manistique Lake significantly correlated with both components (p<0.05).

0 150 300 450 600 750 9000

50

100

150

200

250

300

350

400

450Northern Pike (Esox lucius)

length (mm)

Tot

al P

CB

Con

cent

ratio

n (p

pb)

Figure 8: BASS outputs compared to measured fish contamination in Torch Lake. The concentrations are the sum of all PCB congeners run in BASS.

Results- Ecosystem Characteristics Predictor(s)Multiple Linear Regression Analysis indicated that a single variable related to lake size (mean depth) could best predict total PCB concentrations in fish (Figure 7).

0.75 1 1.25 1.5 1.75 2

-3.5

-3

-2.5

-2

-1.5

-1f(x) = 2.264 x − 5.29500000000001

log(Mean Depth)

log(

PC

Bt)

Figure 7: Multiple Linear Regression results: Mean depth (ft) was determined to be the best predictor of total PCB concentration (PCBt) in sampled fish. A lipid-normalized PCBt (ppm) was used to account for the multiple species sampled between lakes.

Figure 3: Fractions of PCBs (f) are in the gas (g), particulate (p), dissolved (w), or sorbed (s). A is catchment inputs; B is air-water gas exchange; C is gas/particle partitioning; D is dry deposition (fp); E is wet deposition (fp+fg); F is outlet loss; G is dissolved/particle partitioning; H diffusive exchange; I is settling; J is resuspension; K is particle/pore water partitioning; and L is burial loss.

Contamination Complexity RevealedA model was developed to predict PCB congener concentrations in lake water based on measured

concentrations in air. The modeled-predicted water concentrations were then used to calculate concentrations in fish, assuming equilibrium partitioning. If this simple model could not adequately

predict measured fish PCB concentrations, more analysis was needed.

Lake Source AnalysisPrincipal Component Analysis (PCA) of congener distributions in fish from lakes with known PCB

sources was used to determine if these sources could be distinguished statistically. PCA was then applied to the remaining lakes to determine the sources of PCBs to each lake. IBM SPSS Statistics was used to

perform the analysis.

Calibration of BioaccumulationThe EPA’s Bioaccumulation and Aquatic Systems Simulator (BASS) was used to predict contaminant concentrations in all fish species in a few lakes and results were compared with DEQ measurements.

Fish exposure and processing parameters were tuned to obtain matches between modeled and measured PCB concentrations.

Ecosystem CharacteristicsStepwise multiple linear regression was used to determine which of the following environmental

variables could predict total PCB concentrations in fish from the lakes that had only atmospheric inputs of PCBs. IBM SPSS Statistics was used to perform the analysis.

Future Desired ConsumptionUnder different scenarios of future PCB emissions, the lake mass balance model will be used in

combination with the BASS model to predict how long different categories of lakes will take for PCB concentrations in fish to reach values safe for human consumption.

Food Web AlterationTo determine if food web structure affects PCB bioaccumulation, it was hypothesized that trophic position has an affect on PCB contamination in top predator fish. Concentrations of PCBs will be

predicted using BASS, combined with the model of lake PCB cycling, in lakes with varying food web classes for comparison.

• Watershed Area• Open Water Area within the

Watershed

• Trophic State• Lake Surface

Area

• Mean Depth• Maximum

Depth

• Wetland Area• Catchment Area: Lake

Surface Area Ratios

Future Work- Future Desired ConsumptionProvided future atmospheric PCB congener concentration scenarios from atmospheric modeling, future fish PCB concentrations can be predicted by the coupled lake and food web model to determine when safe fish consumption will occur. GEOS-Chem, a global 3D chemical transport model, is being used by team members to provide future atmospheric concentrations of PCBs.

Figure 6: Summary of lakes divided into categories by means of PCA. Three of the sampled lakes were not categorized due to the unique species sampled.

A B

C

D EF

G

H I J

fg fp

fw fs

fw fsK

L

Figure 4: Comparison of measured fish PCB congener concentrations (lipid normalized) to predicted concentrations assuming equilibrium between water and fish in Manistique Lake. The water concentrations were predicted from the model summarized in Figure 3.

Siskiwit Lake

Deer LakeLake LeVasseur

Manistique Lake

Muskallonge LakeOtter Lake

Boston Lake

Portage Lake

Torch Lake

Runkle LakeChicagon Lake

Emily Lake

Little Lake

Shag LakeSilver Lake

Sporley Lake

Goose Lake

Engman Lake

Locally Impacted Lakes

Undetermined Source Lakes

Only Atmospherically Impacted Lakes

NOAA

Figure 9: Diagram of trophic position of top predator fish caused by diet. The wider the arrow, the greater the dependency of that organism on the corresponding diet. This concept was studied by Zanden and Rasmussen (1996) with lake trout sampling.

1 2 3

Tro

phic

pos

itio

n

Food Web Class

Top Predator

Pelagic Fish

Pelagic Fish

Benthic Fish

Benthos Benthos BenthosZooplankton Zooplankton Zooplankton

Megazooplankton

Larval Fish Larval Fish

Top Predator

Top Predator

99 101 118 128 138+163 153+132+105 170+190 1800

0.5

1

1.5

2Manistique Lake

measuredpredicted

PCB Congener

Conc

etra

tion

(ppb

) 0 150 300 450 600 750 900

Walleye (Sander vitreus)

modeled measured 2007 measured 2000

Length (mm)

0 150 300 450 600 750 900

White Sucker (Catostomus commersonii)

length (mm)