The CERCLA Type A Natural Resource Damage Assessment Model for Coastal and Marine Environments (NRDAM/CME)

Technical Documentation Volume I - Part 1 Model Description

for

Office of Environmental Policy and Compliance U.S. Department of the Interior Washington, DC 20240

by

Deborah P. French, Mark Reed, Kathy Jayko, Shih-shing Feng, Henry Rines, Sharon Pavignano, Tatsu Isaji, Suzanna Puckett, Aimee Keller, Fred W. French III, Dian Gifford, John McCue, and Thomas Opishinski Applied Science Associates, Inc. 70 Dean Knauss Drive Narragansett, RI 02882

and

Garry Brown, Emily MacDonald, Jacqueline Quirk, Stefan Natzke, and Bradly S. Ingram A.T. Kearney, Inc. Kearney Centaur Division 225 Reinekers Lane Alexandria, VA 22313

Richard Bishop, Michael Welsh, and Marty Phillips

Hagler Bailly Consulting, Inc. 4513 Vernon Boulevard Madison, WI 53705

April 1996

Revision I, dated October 1997

Contract No. 14-01-0001-91-C-11

ASA 90-53The CERCLA Type A Natural Resource Damage Assessment Model for Coastal and Marine Environments (NRDAM/CME)

Technical Documentation Volume I - Part 2 Model Description

for

Office of Environmental Policy and Compliance U.S. Department of the Interior Washington, DC 20240

by

Deborah P. French, Mark Reed, Kathy Jayko, Shih-shing Feng, Henry Rines, Sharon Pavignano, Tatsu Isaji, Suzanna Puckett, Aimee Keller, Fred W. French III, Dian Gifford, John McCue, and Thomas Opishinski Applied Science Associates, Inc. 70 Dean Knauss Drive Narragansett, RI 02882

and

Garry Brown, Emily MacDonald, Jacqueline Quirk, Stefan Natzke, and Bradly S. Ingram A.T. Kearney, Inc. Kearney Centaur Division 225 Reinekers Lane Alexandria, VA 22313

Richard Bishop, Michael Welsh, and Marty Phillips

Hagler Bailly Consulting, Inc. 4513 Vernon Boulevard Madison, WI 53705

April 1996

Revision I, dated October 1997

Contract No. 14-01-0001-91-C-11

ASA 90-53TABLE OF CONTENTS

Page

List of Acronyms x

Acknowledgments xi

List of Figuresxii

List of Tables xiv

1. INTRODUCTION AND OVERVIEW I.1-1 1.1 Overview of the Model I.1-2 1.2 Major Simplifying Assumptions I.1-5 1.3 Organization of the Documentation I.1-9 1.4 References I.1-10

2. NRDAM/CME GRID SYSTEM AND GEOGRAPHICAL INFORMATION I.2-1 2.1 Grid System I.2-1 2.2 Geographic Information System and Database I.2-2 2.2.1 Coastline I.2-4 2.2.2 Bathymetry I.2-4 2.2.3 Shoreline and Habitat Type I.2-4 2.2.4 Air and Water Temperatures I.2-7 2.2.5 Salinity, Density and Mixed Depth Layer I.2-7 2.2.6 Ice I.2-8 2.2.7 Winds I.2-8 2.2.8 Currents I.2-8 2.3 References I.2-10

3. PHYSICAL FATES SUBMODEL I.3-1 3.1 Overview I.3-1 3.2 Assumptions in the Physical Fates Submodel I.3-3 3.3 Fates Submodel Grid Systems I.3-4 3.4 Surface Spreading I.3-5 3.5 Volatilization from a Surface Slick I.3-5 3.6 Entrainment/Dissolution from Surface Slick to Water Column I.3-6 3.7 Sinking I.3-11 3.8 Volatilization from the Water Column I.3-13 3.9 Horizontal and Vertical Transport I.3-14 3.10 Bottom Contamination I.3-15 3.11 Ice Effects I.3-17 3.12 Shoreline Effects I.3-20 3.13 Fates Model Timestep I.3-22 3.14 Particle Arrays I.3-23 3.15 Output to the Biological Effects Submodel I.3-23 3.16 List of Symbols I.3-24ii

3.17 References I.3-26

4. BIOLOGICAL EFFECTS SUBMODEL I.4-1 4.1 Overview I.4-1 4.1.1 Summary of the Biological Effects Submodel I.4-1 4.1.2 Assumptions in the Biological Effects Submodel I.4-6 4.2 Toxicity Model I.4-8 4.2.1 Algorithms I.4-8 4.2.2 Toxicity Data Requirements I.4-14 4.2.3 Oils and Petroleum Products I.4-18 4.3 Exposure Model I.4-22 4.3.1 Fishery Species I.4-24 4.3.2 Young-of-the-Year (Eggs and Larvae) I.4-28 4.3.3. Lower Trophic Level Production Losses I.4-30 4.3.3.1 Sublethal Effects on Primary and Secondary Producers I.4-30 4.3.3.2 Lethal Effects and Habitat Recovery I.4-32 4.3.3.3 Secondary Consumers I.4-39 4.3.4 Wildlife I.4-39 4.4 Food Web Model I.4-45 4.5 Population Model I.4-51 4.5.1 Catch Losses of Fish I.4-51 4.5.2 Hunting Losses of Wildlife I.4-55 4.5.3 Population Losses of Wildlife I.4-57 4.6 Measurement of Natural Resource Injuries I.4-58 4.7 List of Symbols I.4-59 4.8 References I.4-61

5. RESTORATION SUBMODEL I.5-1 5.1 Overview I.5-1 5.2 Assumptions of the Restoration Submodel I.5-2 5.3 Literature Review of Strategies and Actions I.5-2 5.3.1 Restoration of Habitats I.5-2 5.3.1.1 Restoration of Open Water Habitats I.5-3 5.3.1.2 Restoration of Wetlands I.5-5 5.3.1.3 Restoration of Macroalgal Beds I.5-8 5.3.1.4 Restoration of Seagrass Beds I.5-10 5.3.1.5 Restoration of Mollusk Reefs I.5-11 5.3.1.6 Restoration of Coral Reefs I.5-13 5.3.1.7 Restoration of Shorelines I.5-15 5.4 Model Conceptualization and Assumptions I.5-17 5.4.1 Identification of Potential Habitat Restoration Actions I.5-17 5.4.1.1 Open Water Habitat I.5-17 5.4.1.2 Saltmarshes and Tidal Wetlands I.5-18 5.4.1.3 Mangrove Swamps, Macroalgal Beds, and Seagrass Beds I.5-18 5.4.1.4 Invertebrate Reefs I.5-18 5.4.1.5 Unconsolidated Shorelines I.5-19 5.4.1.6 Hard Shorelines I.5-19 5.4.2 Deciding Whether to Invoke Habitat Restoration Actions I.5-19iii 5.4.2.1 Timing of Habitat Restoration Actions I.5-20 5.4.2.2 Recovery I.5-23 5.4.3 Restocking I.5-24 5.4.4 Restoration of Assimilative Capacity I.5-25 5.5 Net Injury and Damages I.5-27 5.6 List of Symbols I.5-27 5.7 References I.5-27

6. BIOLOGICAL DATABASE I.6-1 6.1 Delineation of Province and Habitat I.6-1 6.2 Lower Trophic Level ProductionI.6-17 6.3 Fishery Species Biomass I.6-17 6.4 Fisheries Life History Parameters I.6-43 6.5 Fishery Young-of-the-Year (YOY) I.6-43 6.6 Wildlife Abundances I.6-50 6.7 Wildlife Population Parameters I.6-50 6.8 List of Symbols I.6-66 6.9 References I.6-66

7. CHEMICAL AND TOXICOLOGICAL DATABASE I.7-1 7.1 Introduction I.7-1 7.2 Density I.7-12 7.3 Vapor Pressure I.7-16 7.4 Solubility I.7-16 7.5 Partition Coefficient I.7-17 7.6 Degradation Rate I.7-21 7.7 Viscosity I.7-25 7.8 Oil and Oil Products I.7-26 7.9 Biological Toxicity I.7-28 7.10 List of Symbols I.7-31 7.11 References I.7-36

8. COMPENSABLE VALUE SUBMODEL: WILDLIFE VALUES I.8-1 8.1 Overview I.8-1 8.1.1 Introduction I.8-1 8.1.2 Assumptions in the Compensable Value Submodel I.8-1 8.2 Economic Rent I.8-2 8.3 Lost Harvest by Recreational Hunters I.8-4 8.3.1 Wildlife Recreational Waterfowl Hunting Values I.8-4 8.3.2 Recreational Hunting of Mammals I.8-4 8.4 Wildlife Viewing I.8-5 8.4.1 Number of Affected Trips I.8-6 8.4.2 Value Per Trip I.8-6 8.5 Discounting and Price Levels I.8-17 8.6 References I.8-18

9. COMPENSABLE VALUE SUBMODEL: FISHERIES VALUES I.9-1 9.1 Overview I.9-1iv 9.1.1 Introduction I.9-1 9.1.2 Assumptions in the Compensable Value Submodel I.9-2 9.1.3 Conceptual Approach to Estimating Fishery Use Values I.9-2 9.2 Economic Rent I.9-7 9.2.1 Magnitude of Commercial Fisheries I.9-7 9.2.2 Measure of Damages I.9-8 9.3 Lost Harvests by Recreational Anglers I.9-13 9.3.1 Recreation Fisheries Catch I.9-18 9.3.2 Primary Mode of Recreational Fishing I.9-25 9.3.3 Total Value of Recreational Fish I.9-25 9.3.4 Relationship Between Marginal and Total Value of Recreational Fish I.9-33 9.3.5 Recreational Fishing Use Values for Marginal Changes in Catch I.9-43 9.4 Summary of Fishery Lost Use Values I.9-45 9.5 References and Literature Cited I.9-58

10. COMPENSABLE VALUE SUBMODEL: BEACH RECREATION VALUES I.10-1 10.1 Overview I.10-1 10.1.1 IntroductionI.10-1 10.1.2 Assumptions in the Compensable Value Submodel I.10-1 10.1.3 Conceptual Approach I.10-2 10.2 Visitation to Coastal Beaches I.10-3 10.2.1 Baseline Information on National Seashores I.10-6 10.2.2 Baseline Information on Public Beaches I.10-17 10.3 Valuation of Coastal Beach Activities I.10-34 10.3.1 Conceptual Valuation Issues I.10-34 10.3.2 Review of Beach Value Studies I.10-36 10.3.3 Average Saltwater Beach Recreational Value Estimate for National and Other Public Beaches I.10-39 10.4 Derivation of Coastal Beach Losses I.10-39

11. COMPENSABLE VALUE SUBMODEL: BOATING VALUES I.11-1 11.1 Introduction I.11-1 11.2 Boating Literature I.11-1 11.2.1 Information Sources Consulted I.11-1 11.2.2 Literature Review I.11-3 11.3 Conclusion I.11-10 11.4 References I.11-11

12. HABITAT RESTORATION AND RESTOCKING COSTS I.12-1 12.1 Summary of Habitat Restoration Activities I.12-2 12.1.1 Natural Recovery I.12-2 12.1.2 In Situ Treatment I.12-4 12.1.3 Material Removal I.12-4 12.1.4 Upland Disposal I.12-5 12.1.5 Open Water Disposal and Capping I.12-7 12.1.6 Habitat Reconstruction I.12-7v

12.2 Habitat Restoration Activities and Estimated Costs by NRDAM/CME Habitat I.12-9 12.2.1 Intertidal Rocky ShoreI.12-9 12.2.1.1 Technical Feasibility of Habitat Restoration Alternatives I.12-10 12.2.1.2 Selected Habitat Restoration Candidate I.12-11 12.2.1.3 Cost of Habitat Restoration I.12-12 12.2.2 Intertidal Gravel Beach I.12-12 12.2.2.1 Technical Feasibility of Habitat Restoration Alternatives I.12-12 12.2.2.2 Selected Habitat Restoration Candidate I.12-14 12.2.2.3 Cost of Habitat Restoration I.12-15 12.2.3 Intertidal Sand Beach I.12-16 12.2.3.1 Technical Feasibility of Habitat Restoration Alternatives I.12-16 12.2.3.2 Selected Habitat Restoration Candidate I.12-19 12.2.3.3 Cost of Habitat Restoration I.12-19 12.2.4 Intertidal Mud Flat I.12-20 12.2.4.1 Technical Feasibility of Habitat Restoration Alternatives I.12-20 12.2.4.2 Selected Habitat Restoration Candidate I.12-21 12.2.4.3 Cost of Habitat Restoration I.12-21 12.2.5 Intertidal Saltmarsh I.12-23 12.2.5.1 Technical Feasibility of Habitat Restoration Alternatives I.12-24 12.2.5.2 Selected Habitat Restoration Candidate I.12-24 12.2.5.3 Cost of Habitat Restoration I.12-24 12.2.6 Intertidal Mangrove I.12-26 12.2.6.1 Technical Feasibility of Habitat Restoration Alternatives I.12-27 12.2.6.2 Selected Habitat Restoration Candidate I.12-28 12.2.6.3 Cost of Habitat Restoration I.12-28 12.2.7 Intertidal Macrophyte Beds I.12-29 12.2.7.1 Intertidal Macroalgal Beds I.12-29

12.2.7.1.1 Technical Feasibility of Habitat Restoration Actions I.12-29 12.2.7.1.2 Selected Habitat Restoration Candidate I.12-30 12.2.7.1.3 Cost of Habitat Restoration I.12-30 12.2.7.2 Intertidal Seagrass Beds I.12-30

12.2.7.2.1 Technical Feasibility of Habitat Restoration Actions I.12-30 12.2.7.2.2 Selected Habitat Restoration Candidate I.12-31 12.2.7.2.3 Cost of Habitat Restoration I.12-31 12.2.8 Intertidal Coral Reef I.12-31 12.2.8.1 Technical Feasibility of Habitat Restoration Actions I.12-32 12.2.8.2 Selected Habitat Restoration Candidate I.12-32 12.2.8.3 Cost of Habitat Restoration I.12-32 12.2.9 Intertidal Mollusk (Oyster) Reef I.12-32 12.2.9.1 Technical Feasibility of Habitat Restoration Alternatives I.12-34

12.2.9.1.1 Reconstruction of Reef Substrate I.12-35 12.2.9.1.2 Reestablish Habitat with Seed Oysters I.12-37 12.2.9.2 Selected Habitat Restoration Candidate I.12-37 12.2.9.3 Cost of Habitat Restoration I.12-39 12.2.10 Intertidal Artificial (Man-made) Structures I.12-41vi 12.2.11 Subtidal Benthic Environments (Rock, Gravel, Sand,

and Mud Bottoms) I.12-41 12.2.11.1 Characteristics of Subtidal Benthic Environments I.12-42 12.2.11.2 Technical Feasibility of Habitat Restoration

Alternatives I.12-43 12.2.11.2.1 In Situ Restoration I.12-43 12.2.11.2.2 Material Removal I.12-44 12.2.11.3 Selected Habitat Restoration Candidate I.12-50 12.2.11.4 Cost of Habitat Restoration I.12-51 12.2.12 Subtidal Saltmarsh I.12-54 12.2.12.1 Technical Feasibility of Habitat Restoration

Alternatives I.12-55 12.2.12.2 Selected Habitat Restoration Candidate I.12-56 12.2.12.3 Cost of Habitat Restoration I.12-57 12.2.13 Subtidal Mangrove I.12-58 12.2.14 Subtidal Macroalgal Bed I.12-59 12.2.14.1 Injury to Macroalgal BedsI.12-59 12.2.14.2 Technical Feasibility of Habitat Restoration Actions I.12-60 12.2.14.3 Selected Habitat Restoration Candidate I.12-63 12.2.14.4 Cost of Habitat Restoration I.12-63 12.2.15 Subtidal Coral Reef I.12-65 12.2.15.1 Functional Characteristics of Coral ReefsI.12-65 12.2.15.2 Injury to Coral Reefs I.12-65 12.2.15.3 Technical Feasibility of Habitat Restoration Actions I.12-66 12.2.15.4 Selected Habitat Restoration Candidate I.12-67 12.2.15.5 Cost of Habitat Restoration I.12-68 12.2.16 Subtidal Mollusk (Oyster) Reef I.12-70 12.2.17 Subtidal Seagrass Bed I.12-70 12.2.17.1 Injury to Seagrass Habitats I.12-70 12.2.17.2 Technical Feasibility of Habitat Restoration Actions I.12-71 12.2.17.3 Selected Habitat Restoration Candidate I.12-73 12.2.17.4 Cost of Habitat Restoration I.12-74 12.3 Restocking I.12-75 12.4 References I.12-91

13. ASSIMILATIVE CAPACITY RESTORATION COSTS I.13-1 13.1 Restoring Assimilative Capacity I.13-1 13.2 List of Symbols I.13-5

14. SUMMARY: FINAL DAMAGES TOTAL 14-1vii

LIST OF ACRONYMS

ADF&G Alaska Department of Fish and Game API American Petroleum Institute CDF&G California Department of Fish and Game HDLNR Hawaii Department of Land and Natural Resources MMS Minerals Management Service, U.S. Department of the Interior NMFSNational Marine Fisheries Service, U.S. Department of Commerce, NOAA NMML National Marine Mammals Laboratory, U.S. Department of Commerce,

NOAA NOAA National Oceanic and Atmospheric Administration, U.S. Department of

Commerce NS&T NOAA National Status and Trends Program ODF&G Oregon Department of Fish and Game PFMC Pacific Fishery Management Council PSMFC Pacific States Marine Fisheries Commission USCOE United States Army Corps of Engineers USDOI United States Department of the Interior USEPA United States Environmental Protection Agency USDOC United States Department of Commerce USFWS United States Fish and Wildlife Service WDF&G Washington Department of Fish and Gameviii

ACKNOWLEDGMENTS

Development of the CERCLA type A Natural Resource Damage Assessment Model for Coastal and Marine Environments (NRDAM/CME) has been based on the cumulative efforts of hundreds of scientists over the past several decades. These contributions, both direct and indirect, are too numerous and diverse to acknowledge individually, but the density of references within this technical documentation demonstrates the extent to which we have relied on work performed by previous researchers.

Mr. David Rosenberger, U.S. Department of the Interior, Office of Environmental Policy and Compliance, Contracting Officer's Technical Representative, has contributed significantly to the success of this project by establishing contacts, facilitating data transfers, and providing undaunted moral support.

Randall Luthi, Linda Burlington, and Eli Reinharz of NOAA's Damage Assessment Regulations Team (DART); Doug Helton and Carol Jones of NOAA's Damage Assessment Center (DAC); Pierre duVair, Paul Reilly, Dave Parker and other of California Department of Fish and Game; and Michael Mohr (Humboldt State University) have provided valuable comments and advice in the development of this model. Pamela Bergman (USDOI Anchorage) and Douglas Mutter, Beverly Agler, David McGillivary, and Michael Jacobson of USFWS (Anchorage) provided valuable input on data sources for Alaska. R.Glenn Ford (Ecological Consulting, Portland, OR) provided data and advice on model algorithms.

Numerous individuals at ASA, some of whom are university students working part time, have provided support in the preparation of this model and the documentation: Chris Galagan, Heather Creel, Marcy Smith, Susan Watts, Sarah Watts, Jennifer Amaral, and Ellen Field.

Finally, we wish to thank Liz Carpentieri, Donna Kelly, Teri Woodbine, Eileen Hughes and Kathy Gordon for their capable, steadfast support and timely response through the many incarnations of this documentation.ix LIST OF FIGURES

Page

Figure 1.1 Schematic overview of the NRDAM/CME 1-3

Figure 2.1 Example set of grids used in the NRDAM/CME. Shown are the

boundaries of habitat grids, each containing 100x100 cells 2-3

Figure 4.1 Schematic of the biological effects submodel for calculation of

injuries 4-3

Figure 4.2 Mortality as a function of concentration (ppb) and temperature

following 96 hours of exposure. The LC50 at 25  14 ppb for this (hypothetical) example of a chemical 4-15

Figure 4.3 Mortality as a function of concentration (ppb) and time of exposure

at 25  assuming the LC50 is 14 ppb 4-16

Figure 4.4 Generalized food web structure for the marine environment 4-47

Figure 5.1 Schematics showing cases where restoration will or will not reduce

compensable value. Area A is the net additional loss and area B is the net gain resulting from performing the restoration action. The times of events are: t 1 = time work on site begins, t2 = time work on site is completed, t 3 = time recovery is 99% complete assuming restoration action performed, t4 = time habitat is no longer toxic assuming no restoration action is performed (i.e., assuming natural recovery). Restoration will not reduce losses if the additional Loss imposed by the action is greater than the gain (upper graph, area A > area B). Restoration will reduce the injury if the gains outweigh the losses (lower graph, area A < B) 5-21

Figure 5.2 Case of complete destruction of a wetland habitat by toxicity or

oiling. Restoration (replanting) will always lessen compensable value. (Ordinate is percent loss of compensable value.) 5-22

Figure 6.1 New England provinces 6-8

Figure 6.2 Mid-Atlantic provinces 6-9

Figure 6.3 Southeast provinces 6-10

Figure 6.4 Gulf of Mexico provinces 6-11

Figure 6.5 California provinces 6-12

Figure 6.6 Pacific northwest provinces 6-13x

Figure 6.7 Alaska provinces 6-14

Figure 6.8 Caribbean provinces 6-15

Figure 6.9 Pacific Island provinces 6-16

Figure 7.1 Variation of viscosity with temperature 7-30

Figure 9.1 Methodology for Measuring Consumptive Use Values for Fisheries 9-4

Figure 9.2 Consumer's Surplus and Small Fish Kills 9-37

Figure 9.3 Net Benefits and Small Reductions in Catch Rates 9-42

Figure 10.1 Methodology Used to Derive Compensable Values for National Seashores 10-4

Figure 10.2 Methodology Used to Derive Compensable Values for State and Local Public

Beaches 10-5

Figure 10.3 Index of Representative Beach Areas Used to Construct Estimates of Visitation

Densities of State and Local Public Beaches 10-19

Figure 10.4 Conceptual Framework for Estimating Comparable Release-Induced Recreation

Losses 10-35

Figure 12.1 Commercial Hazardous Waste Treatment and Disposal Facilities in Coastal States

(Except Alaska) 12-6

Figure 12.2 Waste Disposal Facilities used in calculations of restoration actions in

Alaska 12-8xi LIST OF TABLES

Table 2.1 Beach slopes (m/m) assumed in three regions of the U.S. coastline

I.2-5

Table 2.2 Mean tidal range and swash width (m) by biological province, with

beach width (m) at sample beach slopes. I.2-5

Table 3.1 Values of the entrainment coefficient C * and the associated viscosity for

three oils (Delvigne and Sweeney, 1988). I.3-8

Table 3.2 Characteristic parameters for oil droplets entrained in the water column,

assuming a wave height of 1.3 m, a specific gravity for oil of 0.9, a turbulent dispersion coefficient D v of 10 -3 , and an initial mixing depth of

z m of 2 m. I.3-10

Table 3.3 Maximum holding capacity (mm, calculated from volume/unit area) for

three classes of oils and various shoreline types. I.3-21

Table 3.4 Shoreline widths (m), oil removal rates (per day), and implied half lives

(days) for various shoreline types. I.3-21

Table 4.1 U.S. EPA freshwater acute water quality criteria formulations as a function

of water hardness (H, mg CaCO 3 /1) in u g/l conforming to the formula: exp ( h 1 1nH + h 2 ). I.4-13

Table 4.2 Fishery species behavior groups. I.4-25

Table 4.3 Lower trophic level production categories for which exposure and

production losses are calculated in the toxicity model. I.4-30

Table 4.4 Description of trophic habitat types and number of years required

for recover to 99% of full functionality, starting from zero functionality (i.e., lethal condition). I.4-35

Table 4.5 Classification of wildlife behavioral groups and assumed

probability of being oiled and dying given that a surface slick is encountered. I.4-42

Table 4.6 Trophic compartments in the food web model (Figure 4.4). Those

directly valued are noted. Other compartments are valued only via the food web I.4-46

Table 4.7 Measurement of natural resource injuries and required compensable

values (*-user provides measure of total injury due to closures). I.4-58xii

Table 6.1 Biological provinces (National Estuarine Atlas = NOAA, 1985)

I.6-2

Table 6.2 Explanation of systems for landward and seaward portions of a

province, by type of province. Fishery species abundances vary by landward open water, seaward open water, and structured (wetland, bed or reef) habitat. Seaward area is always the major portion of the province I.6-6

Table 6.3 Classification of ecological habitats. Seaward (Sw) and landward

(Lw) system codes are listed. (Fringing types indicated by (F) are only as wide as intertidal zone in that province. Others (W = water) are a full grid cell wide and must have a fringing type to Landward.) I.6-7

Table 6.4 Areas assumed for provinces - km2 . Seaward (Swd) and landward

(Lwd) areas includes all subtidal seaward or landward ecological habitats, respectively (Table 6.3) Wetlands and flats (Wetl) area includes all intertidal wetlands and mud flats. Data from (A) digitized areas, (B) Estuaries of the United States (Basta et al., 1990), (C) Coastal Wetlands of the United States, sum of saltmarsh + tidal flats (Field et al., 1991), (D) Caribbean Fishery Management Council (1990), or (G) grid area. I.6-18

Table 6.5 Lower trophic level production rate (gC/m 2/day) and biomass

(kg/km2 ) data contained in the biological database by province, habitat and season I.6-20

Table 6.6 Categorization of fishery species. I.6-21

Table 6.7 Categories of fishery species and their province and trophic

compartment assignments. (A category need not exist in all provinces for which the category applies.) I.6-44

Table 6.8 Habitats where benthic fishery species are assumed to exist. I.6-48

Table 6.9 Fisheries parameters required by the biological effects submodel.

I.6-49

Table 6.10 Categorization of wildlife species. Model categories are codes

1-46. Species included are listed below the category with species code >99. I.6-51

Table 6.11 Classification of wildlife species into behavior groups and trophic

compartments. I.6-62

Table 6.12 Usage of habitats by wildlife behavioral groups. I.6-64xiii

Table 6.13 Population parameters for wildlife required by the biological effects

submodel. I.6-65

Table 7.1 Chemicals contained in the NRDAM/CME. I.7-2

Table 7.2a Classification of chemicals in PHYSCHEM data base I.7-13

Table 7.2b Classification of chemicals in PHYSCHEM data base I.7-14

Table 7.2c Classification of chemicals in PHYSCHEM data base I.7-15

Table 7.3 Regression equations for estimation of parameters Kow and K oc .

I.7-19

Table 7.4 Description of degradation rate classes I.7-23

Table 7.5 Biodegradation rate class and half life of 26 chemicals. I.7-24

Table 7.6 Oils and oil products for physical fates model I.7-27

Table 7.7 Derivation of toxicity data set for the PHYSCHEM data base

I.7-32

Table 8.1 Compensable commercial values (1991 dollars) for furbearers, by

biological province numbers and groupings into economic provinces see Table 6.1) 8-3

Table 8.2 Recreational hunting values (1991 dollars) for waterfowl, by flyway

and biological provinces assigned 8-5

Table 8.3 Percent allocation of primary non-residential non-consumptive days

to species groups for respondents having visited oceansides 8-10

Table 8.4 Assignment of species to species groups and assumed marginal relationship 8-12

Table 8.5 Assignment of states and biological provinces to wildlife economic

provinces 8-13

Table 8.6 Procedures for calculating compensable non-consumptive use values 8-14

Table 8.7 Compensable values for lost wildlife viewing (1991 dollars per

year), by wildlife economic province groupings and wildlife species groups, for a one percent reduction in wildlife 8-16

Table 9.1 Categorization of biological provinces into fisheries economic

provinces and NMFS regions used for fisheries management and statistics. I.9-5xiv

Table 9.2 1984-1988 average commercial catch (in kg) by economic

province. I.9-9
Table 9.3 1984-1988 average commercial price (in mid-1991$/kg) by

economic province.I.9-14

Table 9.4 1984-1988 average recreational catch (in kg) by economic

province. I.9-21

Table 9.5 Primary mode of recreational fishing by economic province.I.9-26

Table 9.6 Data on Visits, Marginal Bids, and Number of Fish Caught per

Outing * I.9-35

Table 9.7 Total and Net Benefits Associated per Unit Reduction in Catch

I.9-39

Table 9.8 Comparison of Changes in Total and Net Benefits I.9-41
Table 9.9 Estimated recreational value (in mid-1991$/kg) by economic

province. I.9-46

Table 9.10 Relative proportion of weight of commercial and recreational catch by

economic province and species category. I.9-50
Table 9.11 Net use value for fisheries (in mid-1991$kg) by economic province. I.9-54

Table 10.1 Acadian province visitation statistics for national beaches. I.10-8

Table 10.2 Virginian province visitation statistics for national beaches. I.10-9

Table 10.3 Carolinian province visitation statistics for national beaches.

I.10-11

Table 10.4 NRDAM/CME wildlife species available for replenishment

activities. I.10-13

Table 10.5 Louisianian province visitation statistics for national beaches.

I.10-14

Table 10.6 Californian province visitation statistics for national beaches.

I.10-15

Table 10.7 Columbian province visitation statistics for national beaches.

I.10-16

Table 10.8 Acadian province visitation statistics for public beaches. I.10-20xv

Table 10.9 Virginian province visitation statistics for public beaches. I.10-21

Table 10.10 Carolinian Province Visitation Statistics for Public Beaches I.10-24 Table 10.11 West Indian province visitation statistics for public beaches. I.10-26

Table 10.12 Louisianian province visitation statistics for public beaches. I.10-28

Table 10.13 Californian province visitation statistics for public beaches. I.10-30

Table 10.14 Columbian province visitation statistics for public beaches. I.10-32

Table 10.15 Summary of recreation value estimates from recent empirical

studies of saltwater beaches. I.10-40

Table 10.16 Derivation of estimated compensable recreation losses at national

beaches in the acadian province, per linear meter of shoreline. I.10-42

Table 10.17 Derivation of estimated compensable recreation losses at national

beaches in the Virginian province, per linear meter of shoreline. I.10-43

Table 10.18 Derivation of estimated compensable recreation losses at national

beaches in the Carolinian province, per linear meter of shoreline. I.10-44

Table 10.19 Derivation of estimated compensable recreation losses at national

beaches in the west indian province, per linear meter of shoreline I.10-45

Table 10.20 Derivation of estimated compensable recreation losses at national

beaches in the Louisianian province, per linear meter of shoreline. I.10-46

Table 10.21 Derivation of estimated compensable recreation losses at national

beaches in the Californian province, per linear meter of shoreline. I.10-47

Table 10.22 Derivation of estimated compensable recreation losses at national

beaches in the Columbian province, per linear meter of shoreline I.10-48

Table 10.23 Derivation of estimated compensable recreation losses at public

beaches in the Acadian province, per linear meter of shoreline I.10-49

Table 10.24 Derivation of estimated compensable recreation losses at public beaches in

the Virginian province, per linear meter of shoreline.I.10-50xvi

Table 10.25 Derivation of estimated compensable recreation losses at public beaches in

the Carolinian province, per linear meter of shoreline I.10-51

Table 10.26 Derivation of estimated compensable recreation losses at public

beaches and Pacific Insular provinces, per linear meter of shoreline I.10-52

Table 10.27 Derivation of estimated compensable recreation losses at public

beaches in the Louisianian province, per linear meter of shoreline I.10-53

Table 10.28 Derivation of estimated compensable recreation losses at public

beaches in the Californian province, per linear meter of shoreline I.10-54

Table 10.29 Derivation of estimated compensable recreation losses at public

beaches in the Columbian province, per linear meter of shoreline.

Table 11.1 Journals Reviewed in the Literature Search for Recreational

Boating Values I.11-2

Table 11.2 Individuals Consulted for Information on Marine Recreational

Boating Valuation Studies. I.11-4

Table 11.3 Boating value estimates. I.11-6

Table 12.1 Summary of Actions for Habitat Restoration - NRDAM/CME.

I.12-3

Table 12.2 Unit cost estimates for the upland disposal of oil-contaminated soil

(mid-1991 dollars). I.12-23

Table 12.3 NRDAM/CME fishery species available for restocking activities.

I.12-77

Table 12.4 NRDAM/CME wildlife species available for restocking activities.

I.12-79

Table 12.5 Individual species included in NRDAM/CME fishery species

restocking categories. I.12-81

Table 12.6 Individual species included in NRDAM/CME wildlife species

restocking categories. I.12-82

Table 12.7 NRDAM/CME Fishery Species Restocking Costs and Applicability

(by NRDAM/CME Province).I.12-83xvii

Table 12.8 Wildlife species restocking costs and availability for species captive

raised and relocated from the wild, based on report from leading animal supplier. I.12-84

Table 12.9 NRDAM/CME wildlife species restocking costs and availability.

I.12-90

Table 13.1 Chemicals and LC50s used in the analysis of the assimilative

capacity restoration cost. The CAS # for values obtained from the NRDAM/CME chemical database are listed under source. Other sources are by assuming values for the listed chemical or by review of data in AQUIRE. The PAH value is the mean of the four aromatics where data are available. I.13-2

Table 13.2 Cost for removing and disposing of subtidal sediments (C eq , 1991 $

US/m 3 ) by biological province I.13-3
Table 13.3 Cost per equivalent toxic mass ($/EqTM, 1991 $ US) by biological

province. PS = biological province where the assumed dredge site is located. I.13-4

Table 14.1 Price index used to adjust past year economic values to 1991

dollars. Note that the base year for this series is 1982 I.14-2

Table 14.2 Gross National Product Implicit Price Deflators for years prior to

1996, from Survey of Current Business, Volume 76, No. 1/2, Jan./Feb. 1996. I.14-31

1. INTRODUCTION AND OVERVIEW The Natural Resource Damage Assessment Model for Coastal and Marine Environments (NRDAM/CME), Version 2.5, is a tool for assessing natural resource damages resulting from minor spills of hazardous substances or oils in coastal and marine environments. The NRDAM/CME is designed for use under the Comprehensive Environmental Response, Compensation, and Liability Act of 1980, as amended (CERCLA) and the Oil Pollution Act of 1990 (OPA). This document describes the content and workings of the NRDAM/CME. CERCLA authorizes Federal, State, and Indian tribal natural resource trustees to assess and obtain compensation from parties responsible for hazardous substance releases that cause natural resource injuries. OPA provides trustees with similar authority in cases of oil discharges into navigable waters. The Department of the Interior has issued regulations for conducting natural resource damage assessments under CERCLA that are codified at 43 Code of Federal Regulations Part 11. The National Oceanic and Atmospheric Administration has issued regulations for assessments under OPA that are codified at 15 Code of Federal Regulations Part
990. Federal and State trustees who conduct hazardous substance assessments in accordance with the CERCLA regulations receive a rebuttable presumption if they proceed to litigation. Federal, State, and Indian tribal trustees receive a rebuttable presumption for oil assessments conducted in accordance with the OPA regulations. The NRDAM/CME is one of the simplified "type A" procedures incorporated into the CERCLA regulations. The OPA regulations allow any type A procedure incorporated in the CERCLA regulations to be used for assessments under OPA as well, so long as certain criteria are met. This document is solely intended to provide users with a better understanding of how the NRDAM/CME was developed and how it operates. Trustees who wish to use the NRDAM/CME and obtain a rebuttable presumption for hazardous substance assessments must consult the CERCLA regulations on the applicability of the model, the necessary and permissible user-supplied information, the required administrative process, and the conditions under which the model results can be supplemented with site-specific "type B" studies. Trustees who wish to obtain a rebuttable presumption for oil assessments, must consult the OPA regulations.2

1.1 Overview of the Model The NRDAM/CME is comprised of a series of linked submodels and databases (Figure 1.1) which calculates a damage claim based on the cost to restore injured natural resources plus certain economic values lost by the public pending recovery. The NRDAM/CME is supported by a geographical information system (GIS) which supplies spatially gridded environmental and biotic information to the physical fates, biological effects, and restoration submodels. The user is required to supply the following information to the model: (1) identification number of spilled substance, (2) amount spilled, (3) date and time of release start, (4) duration of release, (5) latitude and longitude of release point, (6) a wind time series, (7) background and tidal currents (8) to what extent cleanup of the spill was carried out, (9) a reference year and price index for the dollar damages, (10) information on closures to fishing, hunting, and shoreline recreation.

The wind time series is supplied by the user as a data file external to the model. Upon reaching the end of this user-supplied file, the model uses stochastic winds based on the climatological values contained in the database. Currents are entered as two components. Background currents are assumed constant in time, but may vary spatially as a series of vectors at different latitude-longitude points. The user enters flood tide vectors in a similar manner. The model calculates one or two tidal cycles per day, as chosen by the user. The physical fates submodel computes the dynamic distribution of the spilled substance in the environment. Computations continue until all environmental exposure levels are below minimum thresholds. The physical fates submodel creates a time series file of surface slick coverage and concentrations of the spilled substance, in the water column, on the bottom, and along the shoreline. When the physical fates submodel computations cease, this time series file is used as input to the biological effects and restoration submodels.3

Figure 1.14

The biological effects submodel computes (1) direct lethal effects on eggs, larvae, juvenile and adult fish and shellfish, birds, mammals, reptiles and lower trophic level biota; (2) indirect and long term effects involving the eventual loss of fish and shellfish as a result of lost eggs, larvae and juveniles, and wildlife (birds, mammals, reptiles) as a result of lost broods; and (3) indirect effects of lost lower trophic level biota and other species without direct use values through the food web. These effects are computed by dynamic juxtaposition of biotic distributions with the distributions of the spilled substance on the water surface, in the water column, in the sediments, and along the shoreline. In the NRDAM/CME, the biological effects submodel quantifies the injury to natural resources in terms of lost or disrupted services. Then the restoration submodel evaluates and selects among a range of restoration actions. The compensable value submodel calculates damages associated with injuries based on lost use values. Compensable values and restoration costs are then summed to produce a final measure of damages in U.S. dollars. The strategy of using linked numerical submodels to calculate biological effects due to anthropogenic activities is relatively recent. Published applications of this approach are: (1) Effects of power plants on fish populations (Hess et al., 1975, Van Winkle, 1977)

(2) Effects of oil spills on fish populations and fisheries (Reed, 1980; Spaulding et al., 1985; Reed et al., 1984; Laevastu and Fukuhara, 1984; French et al., 1989);

(3) Effects of oil spills on marine mammals (Ford, 1985; Brody, 1988; Reed et al., 1990; French et al., 1990; Jayko et al., 1990)

(4) Effects of oil spills on bird populations (Ford et al., 1982; Samuels and Lanfear, 1982; Ford, 1985; Ford et al., 1987); and

(5) Effects of net entanglement on marine mammals (French and Reed, 1989).

The first inclusion of a relatively comprehensive economics component in such an impact model appears to have been in the original version of the NRDAM/CME issued in 1987 (Grigalunas et al., 1988; Reed et al., 1989). The methodology of linked numerical submodels has been in use for over a decade, and represents the most objective, internally consistent, comprehensive approach to environmental impact assessment available. However, its application generally requires an integrated team of professionals, trained in specific classical areas (e.g. physics, biology, chemistry, economics) as well as numerical modeling, which explains the limited use of this approach to date. The NRDAM/CME is actually an expert system, in that it allows relatively untrained individuals to apply complex analytical procedures usually requiring the presence of expert personnel.5

1.2 Major Simplifying Assumptions Development of a model capable of calculating a specific natural resource damage figure for spills of any of 462 substances anywhere along the United States coast requires certain simplifications. The NRDAM/CME incorporates averaged data that may or may not fully correspond with actual conditions at the precise time and location of a real spill. Also, the model is based on a number of assumptions that may or may not hold true in a particular case. The databases used by the NRDAM/CME are listed in Volumes III, IV, and V. The major assumptions in the NRDAM/CME, which are discussed in greater detail in Sections 3 through 11, are summarized below.
1. Winds The model accepts as input a single wind time series which is assumed invariant in space. For discharges which cover very large areas, traverse great distances, or occur in mountainous areas where topographic effects are important, spatial variability in the wind may have a significant effect. To compensate for this effect, the wind time series can be compiled using the recorded wind speeds and directions corresponding to the geographic area in which the major portion of a discharge is found at any given time during a discharge.
2. Currents The currents in the model are two dimensional, vertically averaged values. Three-dimensional complexities such as reverse flows at depth, vertical shear profiles, upwelling, and downwelling are inherently neglected in the Type A model. Thus, both the magnitude and direction of transport vectors in the water column may be inaccurate if these complexities are significant. However, the ultimate effect on the reliability of the final damage figure is usually not significant in offshore and other areas where the biological habitats are homogeneous. 3. Resolution of physical domain The physical fates submodel resolves the physical domain into discrete rectangular grid cells, with attributes being uniform within a cell. Increasing the resolution (i.e., using a greater number of smaller cells), provides a better representation of the real world as long as reliable data at the finer resolution is available. The Type A model has a resolution of 0.2 to 5 km, commensurate with available data for bathymetry, habitat type, shoreline type, and currents. Higher resolution is used in nearshore areas, with broader scales offshore. 4. Resolution of contaminant distributions The model represents the contaminant on the water surface and in the water column by distributions of discrete slicks or particles. The maximum number of slicks and particles allowed by the computational software/hardware affects the ability of the model to resolve these spatial distributions. The model is designed to adequately resolve contaminant releases of up to a few6

days in duration. For longer or more chronic spills, the limited number of available slicks and particles results in less precise resolution. 5. Geographic regions The ecosystems included in the assessment are those aquatic systems in estuarine and marine environments of the United States, including territories and possessions. The seaward bounds are at or are just beyond the Exclusive Economic Zone boundaries. All regions where salinity is brackish or saline (>0.05%) are included. In some regions (i.e., major estuaries and river mouths), tidal freshwater habitats are also included. Intertidal portions of shorelines are habitats considered by the model. Upland, groundwater, and atmosphere are not included in the model domain, nor are injuries suffered by biological organisms in these environments.
6. United States resources Injuries and the resulting damages are quantified only for resource services to U.S. populations (i.e., of people). Thus, injury to a "U.S. fish" (e.g., a fish later caught by a U.S. fisherman) is quantified whether the injury or discharge occurs in U.S. or in nearby international waters. "U.S. fish" are assumed to move freely and randomly in a water body regardless of the border. All injuries to wildlife, because of their mobility and migration through the U.S. for at least a portion of each year, are assumed compensable to the U.S. public to the extent that they provide services to that population. Food-web losses in international habitats within the model domain which result in injury to U.S. fish and wildlife resources are included in the model's calculation of compensable value. 7. Species Biological resources assessed for injury are fish, shellfish, wildlife (i.e., other vertebrates), invertebrates, and plants. Those fish, shellfish, and wildlife species having some measurable consumptive or nonconsumptive use value, and where quantification of their abundance can be documented, are included in direct valuations of injury. These are, for the most part, the larger fish, shellfish, reptiles, and mammals, and all bird species which make primary use of the included aquatic habitats. Plants, invertebrates, and small vertebrates are included as contributors to food webs and habitat value for the individually valued fishery and wildlife species. For a list of the specific species included, see Volume IV.
8. Abundances The environment is represented by aerially and seasonally averaged abundances. Incident-specific and short-duration (i.e., weeks or less) concentrations of biological organisms are not specifically modeled, but are included in the overall average. 9. Acute toxicity. The injury is quantified based on the acute toxicity of a perturbation in toxic contaminant concentration. The model is not designed to address long-term, chronic exposure to pollutants. Toxic responses are averaged over species groups.7

10. Ecosystem-level interactions It is assumed that the mortalities and changes in biological productivity are small enough that ecosystem structure is not significantly changed. The model does not address changes in predator-prey or competitive relationships between populations. The direct, mortality from the contaminant and loss of food resources are assumed the main effects on the populations. The populations affected are not assumed to respond in any compensatory manner (i.e., natural mortality and reproduction rates after the discharge effects dissipate are assumed the same as before the discharge). 11. Closures and mortality If the user specifies a fishing or hunting closure, the model assumes that the closed area encompasses the zone where mortality occurs. If the closed area does not in fact encompass the zone where mortality occurs, then the model may underestimate hunting and fishing losses.
12. Restoration The only restoration actions evaluated by the model are: specific types of on-site restoration actions for open-water, wetland, macroalgal bed, seagrass bed, mollusk reef, coral reef, and shoreline habitats; one-for-one, in-kind restocking; and restoration of assimilative capacity through off-site removal of contaminated sediment. 13. Compensable values The model calculates damages for four specific categories of public loss: Lost economic rent for lost commercial harvests resulting from any user-specified closures and/or from population losses; Lost harvests by recreational anglers and hunters resulting from any user-specified closures and/or from population losses; Lost wildlife viewing, resulting from population losses, by residents of states bordering provincess in which injuries occurred; and
Lost beach visitation due to closure. Other losses, such as reduced quantity or quality of beach attendance in the absence of official closure or reduced quality of fishing, are not addressed. 14. Commercial prices The model assumes that the spill does not change the commercial price of fish and
wildlife. 15. Level of fishing and hunting effort The model assumes that the level of effort expended by commercial and recreational fishermen and hunters is not affected by the spill. 16. Productivity of fishing and hunting effort The model assumes that the marginal productivity of fishing and hunting effort fully recovers after the spill.8

17. Unique activities and locations The model uses average values to compute compensable values. Such values may not be appropriate for unique activities, such as a major fishing tournament, or unique locations. 18. Cumulative effects The model treats each spill as an isolated event. If, for example, more than one spill occurred at the same location, the model would generate damages for each spill as if it were the only one. Any cumulative effects would not be accounted for. 19. Exposure pathways The model calculates exposure to released substances only through water pathways. Therefore, exposure of biological resources through air, groundwater, biological, or geologic pathways, is not accounted for. 20. Response actions The model does not consider any potential injury to natural resource caused by response actions, such as use of chemical dispersants.
21. Mixtures When calculating the effects of mixtures, the model only evaluates one substance within
the mixture. 22. Entry into water
The model assumes that the released substance enters water at or near the surface. 23. Threatened and endangered species The model includes some threatened and endangered species. However, where significant effects on threatened and endangered species is expected, more extensive restoration actions than those considered by the model may be warranted. Also, compensable values may exceed those calculated by the model.

1.3 Organization of the Documentation The documentation is organized as follows. In Volume I all the model algorithms are described, along with the organizational structure and conceptualization of the supporting databases. Contents of the databases, along with sources of information, are detailed in Volume III (chemical and environmental) Volume IV (biological), and Volume V (economic: compensable values, restoration costs). Volume II describes the software and includes a user's manual. The source code listings for the model are in Volume VI. The authorship of the NRDAM/CME may be summarized as follows: Applied Science Associates, Inc. (ASA):

Physical fates, biological effects, and restoration submodels; chemical, environmental, biological and restoration of assimilative capacity cost databases; software coding; user interface.9

A.T. Kearney, Inc.:

Compensable value submodel: fisheries and beach recreation and values; habitat restoration and restocking costs.

Hagler Bailly Consulting, Inc.:

Compensable value submodel: wildlife valuation and boating review.

1.4 References

Brody, A., 1988. A simulation model for assessing the risks of oil spills to the California sea otter population and an analysis of the historical growth of the population. pp. 191-274. In: D.B. Siniff and K. Ralls, (eds), Population Status of California Sea Otters. Rep. Contract No. 14-12-001-30033, U.S. Dept of the Interior, Minerals Manage. Serv., Pacific Outer Continental Shelf Region, Loss Angeles, California.

Ford, R.G., 1985. A risk analysis model for marine mammals and seabirds: a Southern California Bight scenario. Final Report to U.S. Dept of the Interior, Minerals Management Service, Pacific OCS Region, Loss Angeles, CA., Contract No. 14-12-0001-30224, May 1985, MMS-85-0104, 236 p.

Ford, R.G., 1987. Estimating mortality of seabirds from oil spills. p. 547-551. In: Proceedings, 1987 Oil Spill Conference. April 6-9, 1987, Baltimore, Md.

Ford, R.G., Wiens, J.A., Heinemann, D. and Hunt, G.L., 1982. Modeling the sensitivity of colonially breeding marine birds to oil spills: guillemot and kittiwake populations on the Pribilof Islands, Bering Sea. Journal of Applied Ecology 19, 1-31.

French, D.P., S. Hurlbut, E.L. Anderson and M. Reed, 1989. Simulation of effects of potential oil spills on Georges Bank scallop and cod. Final Report prepared for Texaco Canada Resources Ltd., Calgary, Alberta, March 1989, 229 p. plus appendices.

French, D.P. and M. Reed, 1989. Potential impact of entanglement in marine debris on the population dynamics of the northern fur seal, Callorhinus ursinus. Proceedings of the Second International Conference on Marine Debris, Honolulu, Hawaii, April 1989.

French, D.P., M. Reed, J. Calambokidis and J. Cubbage, 1990. A simulation model of seasonal migration and daily movements of the northern fur seal, Callorhinus ursinus. Ecol. Modelling 48:193-219.

Hess, K., M. Sissenwine, and S. Saila, 1975. Simulating the entrainment of winter flounder larvae. In Saila, S. (ed.), Fisheries and Energy Production, A Symposium. D.C. Health and Co. Lexington, MA.

Jayko, K., M. Reed and A. Bowles, 1990. Simulation of interactions between migrating whales and potential oil spills. Environmental Pollution 63:97-127.10

Laevastu, T. and F. Fukuhara (eds), 1984. Quantitative determination of the effects of oil development in the Bristol Bay region on the Commercial fisheries in the Bering Sea. U.S. Dept of Commerce, National Marine Fisheries Service, Northwest and Alaska Fisheries Center, NWAFC Proceedings Report 84-06, March 1984. Reed, M., 1980. An oil spill fishery interaction model formulation and application. Ph.D. Thesis, University of Rhode Island, Department of Ocean Engineering, Kingston, RI 02881.

Reed, M., D.P. French, J. Calambokidis and J. Cubbage, 1990. Simulating the effect of oil spills on the Alaskan fur seal population. Ecol. Modelling 49:49-71.

Reed, M., M.L. Spaulding, S.B. Saila, E. Lorda and H. Walker, 1984. Oil spill fishery impact assessment modeling: The recruitment problem. Estuarine Coastal and Shelf Science, Vol. 19:591-610.

Samuels, W.B. and K.J. Lanfear, 1982. Simulations of seabird damage and recovery from oilspills in the Northern Gulf of Alaska. J. of Environm. Management 15:169-182.

Spaulding, M.L., M. Reed, E. Anderson, T. Isaji, J.C. Swanson, S.B. Saila, E. Lorda and H. Walker, 1985. Oil spill fishery impact assessment model: Sensitivity to spill location and timing. Estuarine Coastal and Shelf Science 20:41-53.

Van Winkle, W. (ed.), 1977. Proceedings of Conference on Assessing the Effects of Power Plants - Induced Mortality on Fish Populations. Pergamon Press, NY. 379 p.11

1. INTRODUCTION AND OVERVIEW I.1-1 1.1 Overview of the Model I.1-2 1.2 Major Simplifying Assumptions I.1-5 1.3 Organization of the Documentation I.1-9 1.4 References I.1-10