A Trophodynamic Model of Methylmecury Bioaccumulation following a First-Flush Anomaly in a Constructed Wetland in. Part 1. Model Development Using

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1 A Trophodynamic Model of Methylmecury Bioaccumulation following a First-Flush Flush Anomaly in a Constructed Wetland in South Florida: Part 1. Model Development Using Structural t Sensitivity Analysis Waterwise Consulting, LLC Hollywood, FL Larry E. Fink, M.S.,

2 Disclaimer This presentation was prepared by author Larry E. Fink as a private consultant. All information expressed herein, including but not limited to analysis, methods, findings, conclusions, recommendations and opinions are solely l those of the author and do not state or reflect those of the author s employer. The author s employer does not make any warranty, expressed or implied, or assume any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, product or process disclosed.

3 Abstract Stormwater Treatment Area (STA) 2 is one of six constructed wetlands complexes in South Florida for nutrient removal to support Everglades restoration. The first, second, and third floodings of Cell 1, an unfarmed parcel used as a hunting preserve, resulted in unprecedented first-flush methylmercury (MeHg) anomalies peaking at 4.8, 7.2, and 20 ng/l in unfiltered surface water in 2000, 2001, and 2002, respectively. The anticipation of progressively worsening first-flush events following successive dry-out and rewetting cycles prompted an intensive study of the third, involving inflow, interior, and outflow surface waters and interior marsh soil, pore water, periphyton, plants, and fish. The results were used to develop, calibrate, and apply a time-dependent, multi-trophic level mathematical model of methylmercury bioaccumulation consisting of a series of one-compartment uptake and depuration models linked to simulate predator-prey relationships. The time-dependent forcing functions were surface water, wet soil, periphyton, and macrophytes using observed MeHg concentrations with linear interpolation between measurements. The largemouth bass forage consisted of macroinvertebrates, mosquitofish, sunfish, and incidental ingestion of hydric soils; sunfish consisted of the same less sunfish, and mosquitofish that of a periphyton grazer with incidental ingestion of periphyton and a benthic macroinvertebrate with incidental ingestion of soil. The model differential equations were solved using a 0.1-day time step and a 4 th -order Runge-Kutta integration scheme. Following the pioneering work of Nordstrom and co-workers, the fish growth rate was an allometeric function of species and size, the fish forage rate was proportional to bioenergetic demand, which was proportional to growth rate plus active metabolic rate, the dissolved oxygen (DO) demand was proportional to the active metabolic rate, and the gill uptake efficiency of the truly dissolved fraction of MeHg was proportional to that of DO. To initialize the model, the MeHg bioaccumulation kinetics of the benthic macroinvertebrate were based on the freshwater mudworm, Lumbriculus variegatus and the periphyton grazer was assumed to have a depuration rate coefficient equal to ½ that of the mudworm. The mosquitofish feeding and DO consumption rate functions were adapted from literature values. The fish gill and gut uptake efficiencies were initially set at 20% of DO and 50% of theoretical, respectively. When the model would not calibrate to the observed mosquitofish data, the gill uptake efficiencies were reduced to 2% and the depuration rate coefficients of macroinvertebrate and grazer varied. The mosquitofish fit improved substantially but still overestimated the first-flush peak, then underestimated the declining profile therafter. The best fit was achieved only when mosquitofish prey-switching was invoked, assuming the macroinvertebrate population developed first and the grazer later. The experience from this exercise suggests several areas for subsequent research, including the assumption that all mosquitofish THg was MeHg and the influences of dissolved and forage organic carbon on the efficiencies of MeHg uptake via gill and gut, respectively. Also of interest are the effects of time-dependent MeHg recycling and prey switching on ecotoxicological risk assessment.

4 Goal To develop, calibrate and validate a bioenergetically self-consistent dynamic, multi- trophic mechanistic mathematical ti model of methylmercury (MeHg) bioaccumulation in wetland ecosystems to support ecosystem restoration and protection decision-making

5 Objectives Part 1: Model Development via Structural Sensitivity Analysis Part 2: Model Application to First-Flush Methylmercury Ecotoxicological Risks

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7 Stormwater Treatment Area 2 G 328 (STA-2) circa Cell 3 Cell 2 Cell 1 G acres acres acres C1X G-330A Not to Scale G-335

8 Background Treatment Cells 2 and 3 of Stormwater Treatment Area 2 (STA-2) met mercury start-up t criteria i (interior < inflow) in 9/00 and 11/00, respectively; but Cell 1 experienced progressively worsening MeHg anomalies after (re)flooding in 9/00 (4.8 ng/l), 10/01 (7.2 ng/l), & 8/02 (20 ng/l). Concern Cell 1 would never stabilize and have to be shut down prompted p intensive treatment cell monitoring, research, and modeling of 3 rd anomaly. This modeling gproject simulates mosquitofish THg bioaccumulation data collected at Cell 1 Site C1CC.

9 Florida Action Level Florida Proposed WQC

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12 Intensive Mercury Monitoring Program: Filtered water every 4 wks. analyzed for THg, MeHg, etc. Cell 3 Cell 2 Cell acres acres acres Site C1CC Not to Scale Mosquitofish s composite every 4 wks; homogenate analyzed for THg Soil 4-cm cores every 12 wks; homogenate THg, MeHg, etc. Plants (emergent, submersed, periphyton) tissue composite homogenate every 26 wks. analyzed for THg, MeHg, ash, moisture

13 Methods Unfiltered and filtered (0.4 micron Meissner) water collected using Geotech peristaltic pump via acid-precleaned teflon tubing at 0.5 m depth with lab, pre- & post-trip blanks; qtrly field dup. 4-cm soil cores by 5-cm dia. pre-cleaned butyrate tubes; blank rinsate analyzed for THg, MeHg mosquitofish collected per site, composited, & homogenized using a Polytron with acid-precleaned rod; blank rinsate analyzed for THg, MeHg qtrly. THg & MeHg in water, soil, and plants and THg in mosquitofish homogenate (n = 3 aliquots) analyzed by Frontier Geosciences in Seattle, WA using USEPA Methods 1631 and 1630.

14 Model Development dco/dt = IR x [FDm x CM x AEm + Sum (FDi x CPi)] + GVR x GAE x CW KD x CO (CO/BW) x dbw/dt Where: CO = conc. toxicant in test organism (mg/kg wet wt.) CW = conc. Toxicant in contact water (ug/l) CM = conc. toxicant in contact media (mg/kg wet wt.) CPi = conc. toxicant in prey item i IR = organism ingestion rate per unit wet body wt. GUEm = gut uptake efficiency from medium m (unitless) GVR = gill ventilation rate (L/day) GAE = gill absorption efficiency (unitless) KD = depuration rate coefficient (day-1) BW = test organism wet body weight (Kg)

15 Model Solution Linear interpolation to approx. daily surface water, wet soil, and wet periphyton MeHg concs. from data every 4, 12, & 26 wks, respectively. Solution to bioaccumulation model differential equation approximated using 4 th -order Runge- Kutta algorithm and 0.1-day time step. Solution algorithm verified against analytic solution for constant ingestion, depuration, and growth rates. Model input, output, and graphics implemented via Microsoft EXCEL spreadsheet.

16 Model Parameterization Mudworm, herbivore, and insect carnivore foraging rates bioenergetically self-consistent with growth rates based on ranges of literature values for organic carbon uptake, utilization and growth allocation efficiencies. Mudworm MeHg t 1/2 of 6-12d and GUEs of 10-25% from sediment are consistent with published data (Leppanen and Kukkonen, 1998). Growth doubling times and depuration t 1/2 s were set equal (herbivore) or multiples (insect = 3x) of the mudworm values. Default temperature dependencies of growth rate for mudworm, herbivore, and insect are mosquitofish values.

17 Model Parameterization Mosquitofish growth, ingestion, and gill ventilation rates from bioenergetics model of Norstrom et al. (1976), calibrated to measurements of Cech et al. (1985) and Mitz and Newman (1989), and size and length data from Hurley et al. (1999) specific to the Everglades Nutrient Removal Project, a prototype constructed wetland. Incremental soil, water, mudorm, herbivore, insect carnivore, and mosquitofish [Hg(II)], [MeHg], [DO], T 0, [DOC] by linear interpolation between obs.

18 every 4 wks. every 4 wks. C1AA C1BB C1CC C1AA C1BB Mosquitofish THg (mg/kg wet wt) Mosquitofish shthgasmehgconc nc. (mg/kgwet wt) C1CC Soil MeHg HgConc. (mg/kgdryw wt) Surface Water Filtered MeHg (ng/l) FilteredMeHg(ng/L) )every 12 wks C1AA C1BB C1CC Soil MeHg (mg/kg dry wt) 0 Aug-02 Nov-02 Feb-03 May-03 Aug-03 Nov-03

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20 Mosquitofish Observed Gut Contents: ENR Project Treatment Cells 3 and 4 (sum. 98)*: 15% 31% animal tissue by volume Diet Item Animal Percent Volume rotifer 2 32% copepod 6 49% ostracod 1 12% chironomid larvae 1 20% Nematode 1 8% dipteran adult 5 47% terrestrial adult insect 5 8% leech 2 18% shrimp hi 3 6% * from Hurley et al., 1999

21 Simplified Mosquitofish Diet for Modeling Study periphyton grazer periphyton carnivorous insect? Mosquitofish (Gambusia holbrooki) SAV grazer?? benthic worm? Incidental soil/sediment ingestion dead leaf detritivore

22 Hg(II) GAE = 1 MeHg GAE = 1 Hg(II) KD = LN(2)/1000 d MeHg KD = LN(2)/1000 d Continuously growing chohort from t = 0 vs. average size cohort (ENR = g fr. Hurley et al. 1999) Diet = 0

23 Hg(II) GAE = 0.2 MeHg GAE = 0.2 Hg(II) KD = LN(2)/1000 d MeHg KD = LN(2)/1000 d Continuously growing chohort from t = 0 vs. average size cohort (ENR = g fr. Hurley et al. 1999) Diet = 0

24 Fish Hg(II) KD = LN(2)/32d Fish MeHg KD = LN(2)/32d Worm KD = LN(2)/6d Fish Hg(II) GUE = 0.05 Fish MeHg GUE = 0.45 Worm KD = LN(2)/12d Fish Diet = 100% Worm Worm KD = LN(2)/24d Fish GAE = 0 Worm Diet = 100% Soil Worm KD = LN(2)/48d Worm Hg(II) GUE = 0.05 Worm MeHg GUE = 0.2

25 Fish Hg(II) KD = LN(2)/32d Fish MeHg KD = LN(2)/32d Worm KD = LN(2)/6d Fish Hg(II) GUE = 0.05 Fish MeHg GUE = 0.45 Worm KD = LN(2)/12d Fish Diet = 100% Worm Worm KD = LN(2)/24d Fish GAE = 0 Worm Diet = 100% Soil Worm KD = LN(2)/48d Worm Hg(II) GUE = 0.05 Worm MeHg GUE = 1

26 Fish Hg(II) KD = LN(2)/32d Fish MeHg KD = LN(2)/32d Fish KD = LN(2)/32d Fish Hg(II) GUE = 0.05 Fish MeHg GUE = 0.45 Fish KD = LN(2)/54d Fish Diet = 100% Worm Fish GAE = Worm Diet = 100% Soil Worm KD = LN(2)/81d 0 Worm KD = LN(2)/162d Worm Hg(II) GUE = 0.05 Worm MeHg GUE = 1

27 Fish Hg(II) KD = LN(2)/32d Fish MeHg KD = LN(2)/32d Worm Herbi KD = LN(2)/6d Fish Hg(II) GUE = 0.05 Fish MeHg GUE = 0.55 Worm Herbi KD = LN(2)/12d Fish Diet = 100% Herbivore Herbi KD = LN(2)/24d Fish GAE = 0 Herbi Diet = 100% SAV Herbi KD = LN(2)/48d Herbi Hg(II) GUE = 0.05 Herbi MeHg GUE = 0.2

28 Herbi Hg(II) KD = LN(2)/3d Herbi MeHg KD = LN(2)/6d Worm Fish KD KD = = LN(2)/32d LN(2)/6d Fish Hg(II) GUE = 0.05 Fish MeHg GUE = 0.55 Worm Herbi KD = LN(2)/12d LN(2)/54d Fish Fish Diet = 100% Herbivore GAE = Herbi Diet = 100% SAV 0 Herbi KD = LN(2)/81d Herbi KD = LN(2)/162d Herbi Hg(II) GUE = 0.05 Herbi MeHg GUE = 0.2

29 Herbi Hg(II) KD = LN(2)/3d Herbi MeHg KD = LN(2)/12d Insect Hg(II) KD = LN(2)/3d Insect MeHg KD = LN(2)/24d Fish Hg(II) KD = LN(2)/32d Fish MeHg KD = LN(2)/32d Fish GAE = 0 Fish Hg(II) GUE = 0.05 Fish MeHg GUE = 0.55 Fish Diet = 100% Insect Insect Diet = 100% Herbi Herbi Diet = 100% Peri

30 Mudworm eats periphyton detritus

31 Mudworm eats SAV detritus 100% SAV 100% SAV Worm Hg(II) GUE = 0.05; MeHg GUE: 0.2

32 100% SAV 100% SAV WormHg(II) GUE = 0.05; MeHg GUE: 0.1

33 65% periphyton 35% SAV 65% periphyton 35% SAV Worm Hg(II) GUE = 0.05; MeHg GUE: 0.1

34 Key Inferences The observed first-flush mosquitofish THg spike was not likely l caused by gill uptake of diffusively i available MeHg for mosquitofish more than a few weeks old. and the population age distribution is unlikely to be substantially skewed in that way even upon reflooding. No single, time-independent mosquitofish foraging g strategy is consistent with the observed MeHg bioaccumulation trajectory in STA-2 Cell 1 C1CC.

35 Key Inferences The after-shock peak that occurred ~300 days after the 1 st flush peak was most likely l caused by the recycling of MeHg taken up by plant leaves that subsequently decomposed as forage for benthic detritivores following winter die-off. It may be necessary to invoke an additional step in the food chain, e.g., and insect carnivore preying on the herbivore or detritivore, depending on the MeHg t 1/2 in mosquitofish.

36 Discussion Preferential foraging of mosquitofish on the rapidly developing detritivorous benthic community hypothesized by the author and others is consistent with the observed MeHg trajectory, but the detritivore must pass through 3 to 7 times more detritus of plant or periphyton p origin than equivalent muck soils to maintain the bioenergetic-equivalent growth rate. An alternative hypothesis is that mosquitofish preferentially foraged on zooplankton grazing algae in equilibrium i with the MeHg spike.

37 Key Conclusions Although bioenergetically constrained, there are still too many degrees of freedom in the model to verify these hypotheses without further study, especially as regards first/reflooding population dynamics and T2, T3, and T4 fish foraging preferences.

38 Key Recommendations Couple the bioenergetically self-consistent, dynamic food chain MeHg bioaccumulation model to a bioenergetically self-consistent wetlands carbon cycling model. Calibrate the model with observed plant and animal standing crop densities and peat bulk density, chemical stoichiometry and accretion rate. Validate the model with the methylmercury y bioaccumulation data. If you get the mercury right, then you ve got everything else right (A. Higer, USGS, retired).

39 Ak Acknowledgements ld Florida DEP The South Florida Water Management District Foster-Wheeler/Tetra Tech Fran Matson Darren Rumbold

40 References Cech, Jr., J.J., M.J. Massingill, B. Vondracek, and A.L. Linden Respiratory Metabolism of Mosquitofish, Gambusia affinis: i Effect of Temperature, Dissolved Oxygen, and Sex Difference. Environ. Biol of Fishes. 13(4): Chipps, S.R and D.H. Wahl Development and Evaluation of a Western Mosquitofish Bioenergetics Model. Trans. Am. Fisheries Soc. 133: Choi, M.H., J.J. Cech, Jr., M.C. Lagunas-Solar Bioavailability of Methylmercury to Scaramento Blackfish (Orthodon Microlepidotus): Dissolved organic Carbon Effects. Environ. Toxicol. Chem. 17(4): Hurley, J.P., L.B. Cleckner, and P. Gorski Everglades Nutrient Removal Project Small Fish Bioaccumulation Study. C University of Wisconsin for South Fl. Water Management District, W. Palm Beach, FL. September.

41 References McCloskey, J.T., I.R. Schultz, and M.C. Newman Estimating the Oral Bioavailability of Methylmercury to Channel Catfish (Ictalurus punctatus). Environ Toxicol. Chem. 17(8): Mitz, S.V. and M.C. Newman Allometric Relationship Between Oxygen Consumption and Body Weight of Mosquitofish, Gambusia affinis. Environ. Biol. Fishes 24(4): Landrum et al., Measuring Abs. Efficiencies: Some Additional Considerations. ETAC: Leppanen and Kukkonen Factors affecting feeding rate, reproduction and growth of an oligochaete Lumbriculus variegatus (Muller). Hydrobiologia. 377:

42 References Norstrom, R.J., A.E. McKinnon, and A.S.W. DeFreitas A Bioenergetics-Based Model for Pollutant Accumulation by Fish. Simulation of PCBs and Methylmercury Residue Levels in Ontario River Yellow Perch (Perca flavescens). J. Fish. Res. Board. Can. 33: Nuutinen, S. and J. Kukkonen The Effect of Se;enium and Organic Material in Lake Sediments on the Bioaccumulation of Methylmercury by Lumbriculus variegatus (oligochaeta). Bioegeochem. 40: Trudel, M. and J.B. Rasmussen Modeling the Elimination of Mercury by Fish. Environ. Sci. Technol. 31(6): Wurtsbaugh, W.A., and J.J. Cech, Jr Growth and Activity of Juvenile Mosquitofish: Temperature and Ration Effects. Trans. Am. Fisheries Soc. 112: