Development of a Novel BP Oil Spill / Food Web Interaction Model for Coastal Waters in the Northern Gulf of Mexico (NGI BP-GRI Phase II): A New Task in Support of Task 3 (Phase I/II) Investigator: Dr. Scott P. Milroy (community ecology; coupled biophysical models) – PI Task 3 (Phase I/II) Synergy: 1) Time series data for a multitude of critical physical and chemical oceanographic measures have been acquired from stations within the Mississippi Sound (MsS), Mississippi Bight (MsB), and Chandeleur Sound (ChS) as part of NGI BP-GRI Task 3. These, coupled with the CODAR stations (NGI BPGRI Task 2) within the Central Gulf of Mexico Ocean Observing System (CenGOOS) will provide critical initialization/validation information for oil spill trajectory forecasting. 2) Task 3 collections/analyses of polycyclic aromatic hydrocarbon (PAH) contamination within surface/bottom waters, surficial sediments, suspended particulates (including phytoplankton and zooplankton assemblages within the 20-53 m and 53+ m size-fractions), and the commerciallyand ecologically-valuable macrobiota (incl. Menhaden, Pink Shrimp, Oyster) will provide key boundary conditions and calibration/validation data for food web model parameters of toxicant bioaccumulation, transfer efficiencies, and other insights into oil impacts on ecosystem function. Oil Spill / Food Web Interaction Model – Action Items: 1) Utilize Task 3 (Phase I/II) PAH in situ and bioaccumulation data to inform the development of a novel oil spill / food web interaction model. 2) Synthesize the pertinent elements of the Thomann et al. (1992), Chapra (1997), and Gin et al. (2001) food web models for a best-fit amalgam which most faithfully represents the coastal food web of the MsS, MsB, and ChS. 3) Engage in original Fortran 95 code development, testing, calibration, and hindcast/forecast model validation on the USM High Performance Computing Cluster (HPCC). 4) Test the forecast capabilities of the new oil spill / food web interaction model, using Milroy’s Task 3 (Phase I) PAH bioaccumulation data from 2010, to predict Milroy’s “current” Task 3 (Phase II) PAH bioaccumulation and/or depuration data from 2011. Oil Spill / Food Web Interaction Model – Background: The lethal and sub-lethal effects of PAH exposure on marine organisms (particularly the more sensitive juvenile forms) are expected to drive significant shifts in primary and secondary production, larval recruitment, and community structure within the lower tiers of the marine food web (Gin et al. 2001). While the acute toxic effects of spilled oil can be as devastating to marine ecosystems as they are immediate, it is also critical to understand the more subtle, long-term ecological perturbations which arise from chronic, sub-lethal perfusions of oil and oil products into the various compartments within complex marine/coastal food webs. Indeed, the chronic exposure to petroleum hydrocarbons, in concentrations as low as 0.05 ppm, has been shown to progressively depress photosynthetic activity in algal cultures (Clark 1997). Beyond 0.25 ppm, feeding efficiencies in the copepod Acartia spp. are decreased and food selection is altered (Gin et al. 2001). While the robust nekton are generally able to avoid areas most grievously affected by oil, the phytoplankton, holoplankton, and meroplankton are incapable of avoiding oiled water masses and are typically more sensitive to exposures than are the larger and/or adult forms (Reed and Spaulding 1978). Hatching success of fertilized capelin (smelt) eggs is significantly reduced in crude oil concentrations as low as 0.01 ppm, while development abnormalities within the surviving ichthyoplankton were observed where crude oil concentrations exceeded 250 ppm (Clark 1997). Of course, the ecological repercussions of these chronic effects would not be constrained to a single compartment within the coastal/marine food webs of the northern Gulf of Mexico; rather, the intimate connectivity between these compartments would necessarily transfer oil-related toxicants (e.g. PAHs) to several key groups of marine organisms within the affected food web. The potential incorporation of PAH-related carcinogens into local fisheries (Baker 1983) and shellfish (e.g. oysters, shrimp, crab) is also a major cause of concern. Hence, the ability to forecast the impacts of PAH-contamination within ecologically- and commercially-important species would not only serve to define the extent of ecosystem impairment as a result of the Deepwater Horizon (DwH) spill, but such information could also be used by resource managers to forecast production, mortality, and the bioaccumulation of PAH-toxins among endmembers within the larger marine food web. Oil Spill / Food Web Interaction Model – Model Development: Using measures of PAH chemical species and relative concentrations within bulk seawater, surficial sediments, suspended particulates (of both the 20-53 m and 53+ m size fractions), as well as the standard biometrics, lipid fraction, and PAH concentrations from the macrobiota from Milroy’s NGI BP-GRI Task 3 (Phase I/II) complimentary research, a coastal food web interaction model (Fig. 1) shall be developed to assess probable impacts of the DwH spill on several key marine organisms within northern Gulf of Mexico coastal waters. In the proposed model, the organism-oil toxicant (PAH) interaction may take place either through the passive uptake of dissolved PAHs in the water column or from the sediments, or through the consumption of oil-contaminated prey (similar to the food web interaction model utilized by Gin et al. 2001). Uptake shall depend upon the organism’s respiration rate and the PAH transfer efficiency across the (idealized) organism membrane. Disparate PAH assimilation efficiencies for a specific oil compound, such as naphthalene or benzo(a)pyrene shall be estimated from available ecotoxicology resources and calibrated for the proposed model using the kinetics suggested by Chapra (1997) and adjusted for the representative species chosen for each food web compartment, as: Phytoplankton: C phy t Zooplankton: Planktivorous Fishes: C pf C ff t Benthic Invertebrates: (1) C zoo K zoo BCFzooCd C zoo zoo phy I L ( zoo) C phy t t Foraging/Predatory Fishes: K phy BCFphyCd C phy K pf BCF pf C d C pf (2) (3) Ppf phy pf phy I L ( pf ) C phy Ppf zoo pf zoo I L ( pf ) C zoo K ff BCF ff Cd C ff (4) Pff inv ff inv I L ( ff ) Cinv Pff pf ff pf I L ( ff ) C pf Cinv Kinv BCFinv Esed Cd ( sed ) Ed Cd Cinv t Pinv phyinv phy I L ( inv)C phy Pinv zooinv zoo I L ( inv)Czoo Pinvsedinvsed I L ( oc)Csed (5) Water Phytoplankton and 20-53 m Particulate PAHs Zooplankton and 53+ m Particulate PAHs Planktivorous Fishes (PAHs) Foraging and Predatory Fishes (PAHs) Suspensionfeeding Benthic Inverts (PAHs) Depositfeeding Benthic Inverts (PAHs) Dissolved PAHs Dissolved PAHs Detritus/ Particulate PAHs Sediment Figure 1. Schematic of the proposed oil spill / food web interaction model, adapted from Gin et al. 2001. where Ci is the PAH concentration in the ith group on a lipid basis (g PAH kg-1 lipid), Cd is the dissolved concentration of a specific PAH in the water column (g m-3), BCFi is the bioconcentration factor for the ith group (m3 kg-1), i→j is the PAH assimilation efficiency (g PAH absorbed g-1 PAH ingested) for the ith group feeding on the jth prey, ILi is the lipid-specific consumption rate (kg lipid in prey kg-1 lipid in predator s-1) of the ith group, ILoc is the rate of organic carbon ingestion relative to lipid ingestion (kg organic carbon ingested kg-1 lipid ingested s-1), Pi→j is the proportional preference factor (unitless) for the ith group feeding on the jth prey, and Ei is the fractional PAH uptake (unitless) from either the water column or from the surficial sediments. Oil Spill / Food Web Interaction Model – Timeline/Milestones: Jan – Apr 2011: Core Fortran 95 code development Apr – Jun 2011: Test individual subroutines; benchmark processing speeds on the USM HPCC Jun – Aug 2011: Consolidate Fortran 95 code; test integrity/fidelity of the full model Aug – Sep 2011: Adjust core Fortran 95 code (bug-testing and code revision) Sep – Dec 2011: Calibrate/Validate model with Milroy’s Task 3 (Phase I) data; compare model performance (forecast fidelity) relative to Milroy’s Task 3 (Phase II) data Jan – Feb 2012: Draft final project report 15 Feb 2012: Final project report due Oil Spill / Food Web Interaction Model – Summary Budget: Total salaries & benefits $ 51,827 Total Rents/Travel $ 3,609 Total Commodities/Software Licenses $ 8,080 Equipment (Dell Workstation) $ 7,098 Total Indirect Costs (46.5% of TDC) $ 27,857 Total Costs $ 94,861 References: Baker, JM (1983) Impact of oil pollution on living resources. Commission on Ecology Papers 4: 218-230. Clark, RB (1997) Marine Pollution. Gookcraft Ltd., Great Britain, UK, pp. 23-59. Chapra, SC (1997) Surface Water Quality Modeling. McGraw-Hill, New York, USA, pp. 784-794. Collins, JF et al. (1998) Potency equivalency factors for some polycyclic aromatic hydrocarbons and polycyclic aromatic derivatives. Regul. Toxicol. Pharmacol. 28: 45-54 Gin, KYH, et al. (2001) An oil spill-food chain interaction model. Marine Pollution Bulletin 42(7): 590-597. Reed, M & ML Spaulding (1978) An oil spill-fishery interaction model: comparison of treated and untreated spill impacts. Environmental Assessment of Treated versus Untreated Oil Spills: Second Interim Progress Report, No. E(11-1)4047. U.S. Department of Energy, Washington DC, USA. Thomann, RV, JP Connolly, and TF Parkerton (1992) An equilibrium model of organic chemical accumulation in aquatic food webs with sediment interaction. Environmental Toxicology and Chemistry 11: 615-629.