OCS Study

BOEM 2016-020

An Analysis of the Impacts of the 

Deepwater Horizon Oil Spill on the

Gulf of Mexico Seafood Industry

U.S. Department of the Interior

Bureau of Ocean Energy Management

Gulf of Mexico OCS Region

OCS Study

BOEM 2016-020

An Analysis of the Impacts of the

Deepwater Horizon Oil Spill on the

Gulf of Mexico Seafood Industry

Authors

Michael Carroll

Brad Gentner

Sherry Larkin

Kate Quigley

Nicole Perlot

Lisa Dehner

Andrea Kroetz

Prepared under BOEM Contract

M14PC00002

by

The Vertex Companies, Inc.

One Congress St, 10th Floor

Boston, MA 02114

Published by

U.S. Department of the Interior

Bureau of Ocean Energy Management

Gulf of Mexico OCS Region

New Orleans, LA

March 2016

DISCLAIMER

This report was prepared under contract between the Bureau of Ocean Energy Management

(BOEM) and The Vertex Companies. Study concept, oversight, and funding were provided by the 

U.S. Department of the Interior, Bureau of Ocean Energy Management, Environmental Studies Program, 

Washington, DC, under Contract Number M14PC00002. This report has been technically reviewed by 

BOEM and it has been approved for publication. The views and conclusions contained in this document 

are those of the authors and should not be interpreted as representing the opinions or policies of the U.S.

Government, nor does mention of trade names or commercial products constitute endorsement or 

recommendation for use. 

REPORT AVAILABILITY

To download a PDF file of this Gulf of Mexico OCS Region report, go to the U.S. Department

of the Interior, Bureau of Ocean Energy Management, Environmental Studies Program 

Information System website and search on OCS Study BOEM 2016-020.

This report can be viewed at select Federal Depository Libraries. It can also be obtained

from the National Technical Information Service; the contact information is below.

U.S. Department of Commerce

National Technical Information Service

5301 Shawnee Rd.

Alexandria, Virginia 22312

Phone: (703) 605-6040

Fax: (703) 605-6900

Email: bookstore@ntis.gov

CITATION

Carroll, Michael; Gentner, Brad; Larkin, Sherry; Quigley, Kate; Perlot, Nicole, et al. 2016. An 

analysis of the impacts of the Deepwater Horizon oil spill on the Gulf of Mexico seafood 

industry. U.S. Dept. of the Interior, Bureau of Ocean Energy Management, Gulf of

Mexico OCS Region, New Orleans, LA. OCS Study BOEM 2016-020. 202 p.

i

CONTENTS

List of Tables ................................................................................................................. v

List of Figures .............................................................................................................. vi

List of Acronyms.......................................................................................................... ix

Summary........................................................................................................................ 1

Chapter One: Introduction............................................................................................ 5

1.1 Timeline of Events................................................................................................ 5

1.2 Study Objectives................................................................................................... 8

1.3 Building the Input/Output (I/O) Model ................................................................... 9

1.4 Overview of Study .............................................................................................. 13

Chapter Two: Factors Affecting Gulf Seafood Following the Deepwater Horizon

Oil Spill......................................................................................................................... 15

2.1 Overview of Factors............................................................................................ 15

2.2 Geographical Distribution of Impacts.................................................................. 15

2.3 Ecosystem Effects.............................................................................................. 18

2.3.1 Oysters .................................................................................................................19

2.3.2 Fishes...................................................................................................................20

2.3.3 Crustaceans: Crabs and Shrimp ...........................................................................21

2.4 Consumer Demand ............................................................................................ 22

2.5 Imports and Lost Market Share .......................................................................... 23

2.6 Temporary Fishery Closures .............................................................................. 24

2.7 Implications for Assessing Impacts..................................................................... 26

Chapter Three: Fishing and Seafood Industry Background.................................... 28

3.1 Overview of All Species...................................................................................... 28

3.1.1 Commercial Fishing Regulations ..........................................................................28

3.1.2 Fisheries Characteristics and Trends....................................................................29

3.1.3 Supply Chain and Market Factors.........................................................................31

3.2 Shrimp ................................................................................................................ 32

3.2.1 Shrimp Commercial Fishing Regulations ..............................................................32

3.2.2 Shrimp Fisheries Characteristics and Trends........................................................34

3.2.3 Shrimp Supply Chain and Market Factors.............................................................38

3.3 Blue Crab ........................................................................................................... 42
ii

3.3.1 Blue Crab Commercial Fishing Regulations..........................................................42

3.3.2 Blue Crab Fisheries Characteristics and Trends ...................................................42

3.3.3 Blue Crab Supply Chain and Market Factors ........................................................47

3.4 Oysters ............................................................................................................... 50

3.4.1 Oysters Commercial Fishing Regulations .............................................................50

3.4.2 Oysters Fisheries Characteristics and Trends.......................................................50

3.4.3 Oysters Supply Chain and Market Factors............................................................54

3.5 Menhaden .......................................................................................................... 56

3.5.1 Menhaden Commercial Fishing Regulations.........................................................56

3.5.2 Menhaden Fisheries Characteristics and Trends ..................................................56

3.5.3 Menhaden Supply Chain and Market Factors .......................................................60

3.6 Reef Fish ............................................................................................................ 63

3.6.1 Reef Fish Commercial Fishing Regulations ..........................................................63

3.6.2 Reef Fish Fisheries Characteristics and Trends....................................................66

3.6.3 Reef Fish Supply Chain and Market Factors.........................................................71

3.7 Pelagic Finfish .................................................................................................... 73

3.7.1 Pelagic Finfish Commercial Fishing Regulations...................................................73

3.7.2 Pelagic Finfish Fisheries Characteristics and Trends............................................74

3.7.3 Pelagic Finfish Supply Chain and Market Factors .................................................79

3.8 Other Crustaceans ............................................................................................. 81

3.8.1 Other Crustaceans Commercial Fishing Regulations............................................81

3.8.2 Other Crustaceans Fisheries Characteristics and Trends .....................................82

3.8.3 Other Crustaceans Supply chain and Market Factors ...........................................87

3.9 Summary of Seafood Industry Trends ................................................................ 88

3.10Seafood Compensation Program ....................................................................... 88

Chapter Four: Economic Impact Model..................................................................... 92

4.1 Selection of Base Model..................................................................................... 92

4.1.1 Types of Economic Models...................................................................................92

4.1.2 The I/O Platform and Alternative Models...............................................................95

4.2 I/O Model Development...................................................................................... 97

4.2.1 U.S. National Impact Model ..................................................................................99

4.2.2 IMPLAN Modeling: Dealer, Processor and Retail Multipliers ...............................103

4.3 Construction of Overall Impact Model Structure ............................................... 103

4.3.1 Avoiding Double Counting ..................................................................................104
iii

4.3.2 Creating Dealer, Processor, Distributor and Retail Sectors.................................104

4.3.3 Product Flows.....................................................................................................105

4.3.4 Margins...............................................................................................................109

4.3.5 General Model Assumptions...............................................................................110

4.4 Derivation of Input Data.................................................................................... 111

4.4.1 Scenario 1: Market Dynamic: Change in Reported Dockside Value....................112

4.4.2 Scenario 2: Market Constant: Change in Reported Landings Valued at Pre-Spill 

Price 113

Chapter Five: Model Results .................................................................................... 115

5.1 Overall model results by scenario..................................................................... 115

5.1.1 Scenario 1: Market Dynamic: Change in Reported Dockside Value....................115

5.1.2 Scenario 2: Market Constant: Change in Reported Landings Valued at Pre-Spill 

Price 117

5.2 Shrimp .............................................................................................................. 118

5.3 Blue Crab ......................................................................................................... 122

5.4 Oysters ............................................................................................................. 125

5.5 Menhaden ........................................................................................................ 128

5.6 Reef Fish .......................................................................................................... 131

5.7 Pelagic Finfish .................................................................................................. 134

5.8 Other Crustaceans ........................................................................................... 137

5.9 Bait ................................................................................................................... 139

5.10Other Shellfish.................................................................................................. 142

5.11Miscellaneous Finfish ....................................................................................... 145

Chapter Six: Summary and Discussion .................................................................. 148

6.1 Summary of Study Approach and Results........................................................ 148

6.2 Comparison of Results with Previous Studies .................................................. 152

6.3 General Caveats............................................................................................... 153

6.4 General Uses.................................................................................................... 156

References................................................................................................................. 157

Appendix I. Tables of Supply Chain Multipliers by Species and State, Inclusive of 

Trade Flows and Margins ......................................................................................... 170

Alabama .................................................................................................................. 170

Florida (West Coast)................................................................................................ 171

Louisiana ................................................................................................................. 173
iv

Mississippi ............................................................................................................... 175

Texas....................................................................................................................... 176

Total Gulf................................................................................................................. 178
v

List of Tables

Table 1. Calculated Short-Run Economic Impacts of the DWH Oil Spill on the Gulf of 

Mexico Seafood Industry by Scenario and Sector.................................................. 3

Table 2. A Chronological Summary of the Deepwater Horizon Oil Spill and Response by 

BP and Management Authorities............................................................................ 5

Table 3. Composition of Species Categories for the Economic Impact Model.................. 12

Table 4. Vessel Permits of Shrimp by State, Dec. 20, 2013. .............................................. 33

Table 5. Federal Regulations for Commercial Reef Fish Harvests (Snappers, Groupers, & 

other Reef Fish), 2013........................................................................................... 64

Table 6. Vessel and Dealer Permit Requirements by state for Commercial Reef Fish 

Harvests (Snappers, Groupers, & other Reef Fish), 2013..................................... 65

Table 7. Federal Vessel and Dealer Permits by State in the Gulf of Mexico, 12/20/2013 . 73

Table 8. Federal Vessel and Dealer Permits by State in the Gulf of Mexico, 12/20/2013 . 81

Table 9. Impact Model Types, Strengths and Weaknesses................................................. 94

Table 10. Species Groups and Gear Types......................................................................... 101

Table 11. Supply Chain Margins by Value Chain Sector and Source ................................ 110

Table 12. Change in Dockside Revenue of Baseline Options ............................................ 112

Table 13. Scenario 1: Market Dynamic Input Data ............................................................ 113

Table 14. Scenario 2: Market Constant Input Data............................................................. 114

Table 15. Scenario 1 Results............................................................................................... 116

Table 16. Scenario 2 Results............................................................................................... 118

Table 17. Shrimp Economic Model Results....................................................................... 120

Table 18. Blue Crab Economic Model Results................................................................... 123

Table 19. Oysters Economic Model Results....................................................................... 126

Table 20. Menhaden Economic Model Results.................................................................. 129

Table 21. Reef Fish Economic Model Results.................................................................... 132

Table 22. Pelagic Finfish Economic Model Results........................................................... 135

Table 23. Other Crustaceans Economic Model Results...................................................... 138

Table 24. Bait Economic Model Results ............................................................................ 140

Table 25. Other Shellfish Economic Model Results........................................................... 143

Table 26. Miscellaneous Finfish Economic Model Results................................................ 146

Table 27. Impact Model Summary ..................................................................................... 149
vi

List of Figures 

Figure 1. Comparison of State Level Landings from 2009 to 2010..................................... 16

Figure 2. Comparison of State Level Dockside Revenue from 2009 to 2010...................... 17

Figure 3. Monthly Average of Gulf of Mexico Federal Fishing Closures (%EEZ) in 2010 26

Figure 4. Composition of Commercial Gulf Landings (lbs) by Core Species Group from 

2007 to 2009 ......................................................................................................... 30

Figure 5. Composition of Dockside Revenue (Nominal USD) of Commercial Gulf 

Landings by Core Species Group from 2007 to 2009........................................... 30

Figure 6. General Seafood Supply Chain Diagram.............................................................. 32

Figure 7. Gulf of Mexico Shrimp Landings and Dockside Revenue from 2002 to2013 ..... 34

Figure 8. Commercial Shrimp Landings Before and During the DWH Oil Spill Relative to 

Fisheries Closures................................................................................................. 35

Figure 9. Commercial Shrimp Dockside Revenue Before and During the DWH Oil Spill 

Relative to Fisheries Closures............................................................................... 35

Figure 10. Comparison of State Level Shrimp Landings from 2009 to 2010........................ 37

Figure 11. Comparison of State Level Shrimp Dockside Revenue from 2009 to 2010......... 37

Figure 12. Overview of the Gulf of Mexico Shrimp Supply Chain....................................... 39

Figure 13. Annual Shrimp Imports into the US and Gulf of Mexico Region from 2007–2013

............................................................................................................................... 41

Figure 14. Gulf of Mexico Blue Crab Landings and Dockside Revenue from 2002-2013 ... 43

Figure 15. Commercial Blue Crab Landings Before and During the DWH Oil Spill Relative 

to Fisheries Closures............................................................................................. 44

Figure 16. Commercial Blue Crab Dockside Revenue Before and During the DWH Oil Spill 

Relative to Fisheries Closures............................................................................... 44

Figure 17. Comparison of Blue Crab Landings by State from 2009 to 2010......................... 46

Figure 18. Comparison of Blue Crab Dockside Revenue by State from 2009 to 2010 ......... 46

Figure 19. Overview of the Gulf of Mexico Blue Crab Supply Chain .................................. 48

Figure 20. Annual Crab Imports into the US and Gulf of Mexico Region from 2004–2013 49

Figure 21. Gulf of Mexico Eastern Oyster Landings and Dockside Revenue from 2002–2013

............................................................................................................................... 51

Figure 22. Commercial Oyster Landings Before and During the DWH Oil Spill Relative to 

Fisheries Closures................................................................................................. 52

Figure 23. Commercial Oyster Dockside Revenue Before and During the DWH Oil Spill 

Relative to Fisheries Closures............................................................................... 52

Figure 24. Comparison of State Level Oyster Landings from 2009 to 2010 ......................... 54
vii

Figure 25. Comparison of State Level Oyster Dockside Revenue from 2009 to 2010.......... 54

Figure 26. Overview of the Gulf of Mexico Oyster Supply Chain ........................................ 55

Figure 27. Gulf of Mexico Menhaden Landings and Dockside Revenue from 2002–2013 .. 57

Figure 28. Commercial Menhaden Landings Before and During the DWH Oil Spill Relative 

to Fisheries Closures............................................................................................. 58

Figure 29. Commercial Menhaden Dockside Revenue Before and During the DWH Oil Spill 

Relative to Fisheries Closures............................................................................... 58

Figure 30. Comparison of State Level Menhaden Landings from 2009 to 2010................... 60

Figure 31. Comparison of State Level Menhaden Dockside Revenue from 2009 to 2010.... 60

Figure 32. Overview of the Gulf of Mexico Menhaden Supply Chain.................................. 62

Figure 33. Annual Fish Meal and Fish Oil Imports into the US and Gulf of Mexico Region 

from 2007–2012.................................................................................................... 63

Figure 34. Gulf of Mexico Reef Fish Landings and Dockside Revenue from 2002–2013.... 66

Figure 35. Commercial Reef Fish Landings Before and During the DWH Oil Spill Relative 

to Fisheries Closures............................................................................................. 68

Figure 36. Commercial Reef Fish Dockside Revenue Before and During the DWH Oil Spill 

Relative to Fisheries Closures............................................................................... 68

Figure 37. Comparison of State Level Reef Fish Landings from 2009 to 2010 .................... 70

Figure 38. Comparison of State Level Reef Fish Dockside Revenue from 2009 to 2010 ..... 70

Figure 39. Overview of the Gulf of Mexico Reef Fish Supply Chain ................................... 72

Figure 40. Gulf of Mexico Pelagic Finfish Landings and Dockside Revenue from 2002–2013

............................................................................................................................... 74

Figure 41. Commercial Pelagic Finfish Landings Before and During the DWH Oil Spill 

Relative to Fisheries Closures............................................................................... 76

Figure 42. Commercial Pelagic Finfish Dockside Revenue Before and During the DWH Oil 

Spill Relative to Fisheries Closures...................................................................... 76

Figure 43. Comparison of State Level Pelagic Finfish Landings from 2009 to 2010............ 78

Figure 44. Comparison of State Level Pelagic Finfish Dockside Revenue from 2009 to 2010

............................................................................................................................... 78

Figure 45. Overview of the Gulf of Mexico Pelagic Finfish Supply Chain........................... 80

Figure 46. Gulf of Mexico Other Crustaceans Landings and Dockside Revenue from 2002–

2013....................................................................................................................... 82

Figure 47. Commercial Other Crustacean Landings Before and During the DWH Oil Spill, 

Relative to Fisheries Closures............................................................................... 84

Figure 48. Commercial Other Crustacean Dockside Revenue Before and During the DWH 

Oil Spill, Relative to Fisheries Closures............................................................... 84
viii

Figure 49. Comparison of State Level Other Crustaceans Landings from 2009 to 2010 ...... 86

Figure 50. Comparison of State Level Other Crustaceans Dockside Revenue from 2009 to 

2010....................................................................................................................... 86

Figure 51. General Schematic of I/O Model Components, Product Flows, and Data Sources..

............................................................................................................................... 99

Figure 52. Overview of National I/O Model (Kirkley 2011)............................................... 100

Figure 53. Harvester Sales to These Sectors by Percent of Value. ...................................... 106

Figure 54. Dealer Sales to These Sectors by Percent of Value ............................................ 107

Figure 55. Destination of Seafood When it Leaves Dealer.................................................. 107

Figure 56. Processor Sales to These Sectors by Percent of Value ....................................... 108

Figure 57. Destination of Seafood When it Leaves Processor............................................. 108

Figure 58. Wholesale Sales to These Sectors by Percent of Value...................................... 109

Figure 59. Destination of Seafood When it Leaves Wholesale............................................ 109
ix

List of Acronyms

BOEM U.S. Department of the Interior, Bureau of Ocean Energy Management

CGE Computable General Equilibrium

DWH Deepwater Horizon

EEZ Exclusive Economic Zone

FDA U.S. Food and Drug Administration

FEAM Fishery Economic Assessment Model

FEUS Fisheries Economics of the United States

GCCF Gulf Coast Claims Facility

IFQ Individual Fishing Quota

IMPLAN IMpact analysis for PLANning

I/O Input/Output

IQF Individually Quick Frozen

ITC International Trade Commission 

NEFSC Northeast Fisheries Science Center

NMFS National Oceanic and Atmospheric Administration, National Marine Fisheries 

Service

NOAA National Oceanic and Atmospheric Administration

PAHs Polycyclic Aromatic Hydrocarbons

REMI Regional Economic Modeling, Inc.

RIMS Regional Input-Output Modeling System

SAM Social Accounting Matrix

USNM U.S. National Impact Model

VOO Vessels of Opportunity

1

Summary

This study gathered various economic data to determine the structure of the seafood industry in 

the Gulf of Mexico, factors that affect the industry, and to estimate the economic impacts of the 

Deepwater Horizon (DWH) oil spill on the seafood industry. The research focuses on the 

structure of the seafood industry’s supply chain, and how that structure may have changed as a 

result of the spill. The research in this study consists of two key components: a comprehensive 

examination of the factors that have affected the gross revenues of domestic commercial 

fishermen operating in the Gulf during and after the oil spill, and an economic impact model for 

the seafood supply chain in the five Gulf States (Alabama, West Florida, Louisiana, Mississippi, 

and Texas).

The study begins with a descriptive analysis of how the oil spill may have affected the seafood 

industry in the Gulf in both the short and long term. The geographic distributions of impacts are

discussed in order to improve understanding of differences in economic effects across fisheries, 

states, and associated coastal communities. Potential longer-term effects of the oil spill on the 

Gulf ecosystem are reviewed at a more aggregate level, as are potential implications on the

ecosystem at a fishery level. Concerns with seafood safety and implications for consumer 

perception and demand of seafood from the Gulf that have been raised in the literature are 

summarized. Initial adjustments in markets due to product shortages and food safety concerns are 

also summarized, and challenges faced by Gulf seafood producers trying to regain market share 

from import products and non-Gulf domestic producers are discussed. The temporary fisheries 

closures implemented by the federal government due to safety concerns are summarized spatially 

and temporally to allow direct comparison to changes in harvest patterns. Changes in the overall 

U.S. economy during the pre- and post-spill period are also noted and discussed, including the 

likelihood of positive exogenous effects on seafood demand during the damage period. This

section of this report concludes with a summary of how these impacts were or were not able to 

be factored into the subsequent economic impact model developed for this study.

Background information on the fishing and seafood industries in the Gulf was presented by

grouping species into the following categories: shrimp, blue crab, oysters, menhaden, reef fish, 

pelagic finfish, other crustaceans, bait, other shellfish, and miscellaneous finfish. Various 

secondary data sets were collected and merged to accomplish this task for the time period 

surrounding the oil spill, namely 2002–2013, and the data sets were examined for trends. The 

analysis used the same the eight-month “damage period” of May 2010 through December 2010 

as defined by the Seafood Compensation Program Settlement Agreement (see Section 3.10) and 

is the period over which economic impacts to the Gulf seafood industry were estimated in this 

study. In addition, this study also used one of the “benchmark time periods” in the Seafood 

Compensation Program Settlement Agreement, that is, May to December of 2009. In addition to 

monthly landings by fishery and state during the damage and benchmark time periods,

qualitative information was gathered outside of the damage period in order to explain some of 

the observed results. Types of additional information and data collected included product prices, 

sales, trade (i.e., imports and export information), financial information, employment/wage data, 

and regulatory information (e.g., permit data and fishing closures). 
2

The fishing and seafood industry background sections of this report include a general overview 

of the fishing industry and the associated supply chain in the Gulf. The summaries by fishery 

include a review of the regulatory structure, harvest trends, and a discussion of typical trade 

routes and practices, as well as some general insights into how each species category was 

individually affected by the oil spill. The final section of the background chapter discusses the

Seafood Compensation Program including how the program was designed to reach settlement 

amounts at the firm level. 

The economic impact modeling section of this report begins with a literature review that was 

used to justify model selection and helped determine the model structure and design. As a result, 

a custom input-output model was selected and constructed for the analyses. The model traces the 

regional economic consequences of a change in product flows, such as occurred during and 

following the oil spill. The change in landed value (industry revenues) is assumed to be the 

initial impact of the spill and the loss is initially incurred by the harvest sector, one of five 

industry sectors explicitly modeled in the value chain: harvesters, dealers, processors, 

wholesale/distribution, and retail (includes both restaurants and markets). Model outputs for each 

sector included changes in the following four metrics of economic activity: (1) total sales, (2) 

value added (labor income, property income and indirect business taxes), (3) income (personal 

income from salaries and wages, and proprietors’ income if self-employed), and (4) employment 

(number of full-time jobs). The changes are described and summarized below (following a 

discussion of the species) by looking specifically at the “total effects”; however, four types of 

impacts are estimated using multipliers (a means of extrapolation), namely: direct (change in 

expenditures by commercial fishermen), indirect (change in output of suppliers to commercial 

fishermen), induced (change in expenditures of employees affected), and total (sum of direct, 

indirect and induced effects). In summary, the total effects are used to quantify impacts incurred 

during the damage period because they are a measurement of short-term economic impacts. Any

longer-term impacts are not captured in this modeling exercise.

An economic impact model developed for this project combined ten harvester sectors (ten 

commercial fisheries) taken from the U.S. National Economic Impact Model with custom supply 

chain sectors constructed using 2012 Impact Analysis for Planning (IMPLAN) data and recent 

cost and earnings data collected by the Gulf States Marine Fisheries Commission. The custom 

multipliers were combined with trade flow and margin data to create a backward-linked seafood 

supply chain model for each state and the entire Gulf region. The custom model was then used to 

examine the economic activity lost to the entire seafood supply chain from the oil spill under two

scenarios. Those scenarios were the “market dynamic” scenario, in which 2009 landings data 

were compared to 2010 landings data (including the oil spill damage period) and reported prices

were used, and the “market constant” scenario, in which landings in 2010 (including the oil spill 

damage period) were modeled by keeping prices fixed at 2009 levels. The estimated reduction in 

revenues to harvesters across the Gulf (i.e., the “loss” estimates) for the market dynamic scenario 

was $7.5 million, and the loss from the market constant scenario was $141.1 million; these are 

the figures that are inputted into the IMPLAN model in order to derive the estimated impacts 

across the value chain.

Table 1 summarizes the results of this impact modeling exercise by scenario at the Gulf wide 

level. Overall, the DWH oil spill was calculated to have reduced “total sales” between $51.7 and 
3

$952.9 million. This reduction, in turn, reduced “value added” by $21.4 to $392.7 million, 

reduced “income” by $21.6 to $309.8 million, and reduced “jobs” by 740 to 9,315 jobs. The 

harvesting sector bore the brunt of those losses, losing $20.1 to $354.5 million in total sales, $7.9

to $137.8 million in value added, $11.9 to $126.3 million in income, and 449 to 3,809 jobs. The 

sector that experienced the lowest economic impacts was the dealer sector, losing $4.3 to $80.6 

million in total sales, $887,000 to $16.8 million in value added, $652,000 to $12.3 million in 

income, and 28 to 527 jobs. 

Table 1. Calculated Short-Run Economic Impacts of the DWH Oil Spill on the 

Gulf of Mexico Seafood Industry by Scenario and Sector

Sector Impact Type Market Dynamic 

(Total Impact)

Market Constant

(Total Impact)

Harvester

Sales -$20,114 -$354,512

Value Added -$7,932 -$137,782

Income -$11,858 -$126,268

Employment -449 -3,809

Dealer

Sales -$4,261 -$80,644

Value Added -$887 -$16,792

Income -$652 -$12,338

Employment -28 -527

Processor

Sales -$6,348 -$120,156

Value Added -$1,503 -$28,454

Income -$1,053 -$19,938

Employment -42 -798

Distributor

Sales -$9,714 -$183,874

Value Added -$4,143 -$78,421

Income -$3,580 -$67,766

Employment -82 -1,543

Market

Sales -$5,630 -$106,572

Value Added -$3,838 -$72,648

Income -$2,503 -$47,374

Employment -74 -1,391

Restaurant

Sales -$5,662 -$107,171

Value Added -$3,095 -$58,581

Income -$1,908 -$36,106

Employment -66 -1,246

Total

Sales -$51,729 -$952,929

Value Added -$21,399 -$392,678

Income -$21,554 -$309,791

Employment -740 -9,315

Note: Dollar Values are in Thousands of $US, Employment is in number of full time jobs

This modeling exercise demonstrated that the harvest sector had the least ability to adjust or 

adapt to the oil spill and was most impacted by the fishery closures. The market dynamic 

scenario incorporates the various external factors that occurred during the modeling horizon 

(most notably changes in prices). In particular, prices for most species were higher in the post-
4

spill period. These higher prices were due to both spill-related and non-spill-related factors. 

This implies that the market dynamic scenario likely underestimates the negative economic 

impacts of the oil spill, while the market constant scenario likely overestimates the negative 

economic impacts of the oil spill. Consideration and use of these impact estimates requires a 

thorough understanding of what these results represent, especially to each sector in the value 

chain, and the limitations of the input data.

Although the aggregate economic impact estimates are informative, results by species and state 

provide a more robust and intuitive set of results. At the state level, losses were highest in 

Louisiana, Mississippi, and Alabama. In Texas and West Florida, losses were lower, and some 

species categories even saw positive economic effects as a result of the oil spill. Shrimp, oysters 

and menhaden (in that order) were the most impacted species categories. Blue crab, reef fish, and 

pelagic finfish were roughly tied for fourth. Although species-level impacts were apparent in 

most of the species categories, positive impacts were noted in various West Florida and Texas 

species categories. Certain impacts that presented counterintuitive results were investigated 

further, and in most cases, market events external to the oil spill were driving these results. 

Overall, this study offers a robust range of impact estimates. However, definitive impact 

estimates derived solely by the oil spill will remain conjecture without further empirical 

examination of the complex cause and effect relationships that have influenced the revenues in 

these fisheries. We believe the results can be used to bookend impacts that have occurred in the 

short term, and should be a strong framework for any further studies that attempt to define 

impacts of the oil spill on the Gulf seafood industry. The model developed in this study can also 

be used to estimate the economic impacts to the Gulf seafood industry from various potential 

future events.
5

Chapter One: Introduction

1.1 Timeline of Events

The Deepwater Horizon oil spill in the Gulf of Mexico began on April 20, 2010 with a blowout 

and uncontrolled release of oil at the seafloor. It is now considered the largest marine oil spill in 

U.S. history. With respect to seafood, the effects of the spill began with fishery closures (i.e., 

harvest bans) and grew to concerns about seafood safety. This included concerns about 

bioaccumulation of oil in marine fishes and about public health being affected by the chemical 

dispersants that were used in response to the spill. 

The short-term social and economic effects that occurred in the first 20 months after the oil spill

were studied by others conducting research and interviews in the coastal communities of 

Louisiana, Mississippi, and Alabama (Austin et al. 2014). A priority in that project was recording 

impacts on the lives and businesses of participants in the commercial fishing industry. 

Information from interviews was put in context with existing historical and geographical 

socioeconomic data. A summary of the history of fishing methods, processing of various 

products, and government regulations was presented for shrimp, oysters, crabs, and finfish. 

External historical effects on the fishing industry were summarized, including changing fishing 

regulations, rising fuel prices, local hurricanes, and import competition. Impacts that occurred in 

the summer and fall months directly after the spill were described, including fisheries closures, 

the claims compensation process, the Vessels of Opportunity (VOO) program, and consumer 

perception issues. This information supplements this report and is referenced in the appropriate 

sections.

Table 2 shows a timeline of events during the spill (Austin et al. 2014). The timeline includes 

actions taken by several management authorities that occurred between April 20, 2010 and April 

20, 2012. This timeline covers events specifically related to the seafood industry and events

related to impacts of the oil spill.

Table 2. A Chronological Summary of the Deepwater Horizon Oil Spill and 

Response by BP and Management Authorities

Date DWH Related Event

4/20/10

Approx. 9:50 p.m. CDT. An unexpected influx of hydrocarbons (a “kick”) escalated to 

a blowout on the Deepwater Horizon platform, just after the crew finished drilling the 

exploratory Macondo well. Gas that flowed onto the rig floor through a mud-gas vent 

line ignited in two separate explosions, eventually sinking the platform. The 

explosions killed 11 platform workers and injured 17 others; another 98 people 

survived without serious physical injury.

4/29/10

The U.S. Coast Guard designates the DWH spill a Spill of National Significance, 

establishing a National Incident Commander to coordinate nationwide response. 

Louisiana Governor Jindal declares State of Emergency in Louisiana. 

Louisiana Governor announces creation of VOO Program which will hire local 
6

Date DWH Related Event

fishermen to help in oil clean up and landfall prevention.

4/30/10

Louisiana Department of Wildlife and Fisheries begins closing state waters and 

oyster grounds to fisheries. Governor Jindal orders the opening of Mississippi River 

fresh water diversions to try to prevent oil from penetrating into coastal marshes.

The fresh water causes 80% mortality in nearby oyster beds by July. 

5/2/10

First VOO task forces from Terrebonne and St. Bernard parishes, Louisiana

reported working. 

The National Oceanic and Atmospheric Administration (NOAA) begins closing 

federal waters to fisheries, initially totaling 6,817 square miles (3% of Federal Gulf 

waters).

5/25/10 Federal Fishery Resource Disaster declared. NOAA Fisheries expands fishing 

closed area in Gulf to 22% of Federal Gulf waters.

6/1/10 Closure of portions of Mississippi state waters to commercial and recreational 

fishing.

6/2/10 Federal fisheries closure area reaches peak at 37% of federal Gulf waters normally 

open to fisheries.

6/4/10 NOAA reopens 16,000 square miles of the Gulf formerly closed to fishing.

6/13/10 The Florida Fish and Wildlife Conservation Commission announce partial closures 

of state waters to commercial and recreational fishing.

6/21/10 NOAA re-expands closed fishing areas, which now approach 36% of Gulf federal 

waters.

7/12/10 Commercial and recreational fisheries closures amount to 35% of the Gulf normally 

open to fishing.

7/15/10

Leaking well is successfully shut in for the first time, stopping flow of oil into the Gulf; 

BP begins well integrity test to determine how well leak is capped before permanent 

sealing is attempted.

7/29/10 Reopening of some Louisiana state waters to commercial fishing from the 

Mississippi River Delta to the Mississippi state line.

8/3/10 BP succeeds in sealing the well with concrete through the “static kill” procedure 

before the relief well’s completion.

8/4/10 Federal government issues report on DWH oil budget and environmental fates.

8/6/10 Mississippi Department of Marine Resources and Mississippi Department of 

Environmental Quality reopen state waters to finfish and shrimp fisheries. 
7

Date DWH Related Event

8/16/10

Alabama Department of Conservation and Natural Resources Marine Resources 

Division announce re-opening of all state waters closed to commercial and 

recreational fishing.

Florida Fish and Wildlife Conservation Commission announce re-opening of closed 

state waters to fishing.

8/23/10 Gulf Coast Claims Facility (GCCF) officially takes over claims process from BP.

9/7/10 NOAA and U.S. Environmental Protection Agency announce that no dead zones 

have been observed or are expected as part of DWH oil spill.

9/15/10 BP officially halts VOO program in Florida, Alabama, and Mississippi. In these three 

states, the program spent $500 million and hired 3,500 vessels.

9/19/10 Admiral Allen announces oil spill is over after completion of relief well. 

10/1/10 NOAA reopens 5,628 square miles of Gulf waters off Louisiana to fishing.

10/22/10 NOAA reopens 7,037 square miles of Gulf waters south of the Florida panhandle to 

commercial and recreational fishing.

10/23/10 BP announces $20 million in funding for seafood inspection and marketing to Florida 

state government.

11/1/10

BP announces $218 million grant to Louisiana state government for seafood testing 

and promotion ($48 million), tourism promotion ($30 million), and coastal restoration 

($140 million).

11/8/10 Mississippi Department of Marine Resources opens some public oyster beds to 

tonging, and sets a 10 sack per vessel per day limit.

11/10/10 Louisiana Department of Wildlife and Fisheries reopens 98% of state waters to 

commercial fisheries by this date.

11/15/10

After harvesting on public oyster beds opened in October in Western Louisiana, 

harvesting reopens in Terrebonne and Lafourche parishes and most of Barataria 

Bay. Public oyster beds east of the Mississippi River in Louisiana remain closed.

11/24/10 NOAA temporarily re-closes 4,000 square miles of deep Gulf waters to shrimping for 

royal red shrimp after oil is brought up by some trawls.

1/31/11 GCCF releases Dr. John W. Tunnell’s report, prepared for the Facility, on oil spill 

effects on fisheries and recovery timelines.

2/2/11 NOAA reopens the waters closed to royal red shrimping the previous November. 

3/24/11 Louisiana Department of Wildlife and Fisheries holds meeting on crab mortalities 

reported in coastal Louisiana in recent months.
8

Date DWH Related Event

4/11/11

Louisiana Department of Wildlife and Fisheries orders reopening of commercial 

fishing in portions of state inside waters within the Mississippi River Delta that were 

previously closed due to spill impacts. Over 99% of state waters now open for 

fishing. 

BP awards $30 million tourism grant to Florida.

4/18-

23/11

Louisiana Department of Wildlife and Fisheries opens some state inshore waters for 

special early shrimp season.

4/19/11 NOAA re-opens last federal Gulf Waters to fishing, those nearest to DWH site.

6/2/11

Oceana and other national environmental groups file notice to sue NOAA Fisheries 

for immediate closure of Gulf shrimp fishery because of concerns over large 

increases in sea turtle mortalities observed in the Gulf and claims of rising violations 

of turtle excluder devices requirements on shrimp trawls.

6/22/11

Louisiana Shrimp Association hosts rally at Louisiana State Capitol over GCCF 

compensation issues and environmentalist threat to sue over turtle excluder devices 

regulations, claiming the spill, not shrimpers, is at fault.

8/3/11

NOAA denies last of three separate petitions from environmental groups requesting 

emergency closures or restrictions on shrimping because of the large number of sea 

turtle deaths in the Gulf.

8/22/11 Louisiana Department of Wildlife and Fisheries opens Fall inshore shrimp season 

after a May inshore shrimp season of historically below-average total landings. 

9/26/11

Study published in the Proceedings of the National Academy of Sciences reports 

biological changes found in juvenile killifish exposed to BP spill oil could signify 

trouble for the reproduction of coastal fish populations.

10/11 Gulf shrimpers report very poor white shrimp catches in Fall inshore season.

4/19/12

Institute for Southern Studies publishes two-year oil spill anniversary report detailing 

community non-profit initiatives, ongoing coastal land loss and lack of restoration 

funding, environmental health concerns following the spill including cleanup worker 

health issues, commercial fishers’ experiences, and criticism of the proposed 

BP/PSC settlement (Sturgis 2012).

Source: Austin et al. (2014)

1.2 Study Objectives

The most immediate economic losses caused by the oil spill (other than to the oil industry) were 

to fisheries and the associated value chain. Though all aspects of fisheries and the value they 

generate should be examined, and some have–such as economic losses suffered by recreational

fishermen (e.g., Alvarez et al. 2014)–this study focuses solely on commercial fisheries. 

Specifically, the broad objectives of this study were to:
9

• Improve understanding of the varied impacts of the oil spill on the individuals and firms 

that comprise the Gulf’s seafood industry.

• Improve understanding of the structure of the Gulf’s seafood industry and how this 

structure may have been altered as a result of the oil spill.

• Provide information that will be used to improve the nation’s response to future oil spills 

as it relates to the Gulf’s seafood industry.

To accomplish these objectives, this study conducted an economic impact analysis of changes in 

the value of harvested seafood across the Gulf. The intent of the analysis and of the methods 

selected to complete the analysis was to develop a model with broader application outside this 

study. Key considerations and criteria with respect to selecting the methods used included that it 

would: 

• Capture the effects of the oil spill across the value chain (i.e., from the harvest sector 

through retail).

• Include the species and/or fisheries important to each of the five Gulf States.

• Use species/fisheries distinctions commonly used in the literature, available data, and 

definitions of the damage period from previous analysis.

• Develop a model that would have subsequent uses.

• Provide substantive discussion regarding nuances in the data (and estimated economic 

impacts) with respect to spatial, temporal and marketing differences across 

species/fisheries.

1.3 Building the Input/Output (I/O) Model

Economic impact metrics trace the flow of expenditures in a community or region. A change in 

final demand or, as in this case, a reduction in the domestic supply of seafood, changes those 

economic flows and reduces employment, incomes, and total sales in the region. In this study, 

the model assessed these changes in economic flows across multiple supply chain segments, 

numerous species categories, and the five Gulf States. After the model was built, estimates of the 

initial changes in domestic seafood supply (i.e., flow of expenditures) induced by the spill were 

needed to calculate the economic impacts to the Gulf States. 

To estimate representative changes in seafood supply (in dollars), we examined the various 

factors (regulatory, biological, etc.) that affect supply of commercially important species and 

determined key species and groupings to be included in the impact analysis. To estimate 

representative changes in associated seafood revenues, we had to understand factors that affect 

price and, ultimately, fishery revenue (e.g., changes in import quantities and values, changes in 

consumer preferences reflected in a shift in demand, etc.) Although the scope of this research did 

not include an econometric analysis of these factors, a comprehensive qualitative analysis of 
10

these factors was completed to ground truth estimated changes in domestic dock-side landings 

and value with respect to the relative contribution of the oil spill.

The closures of fishing areas following the oil spill are summarized in Section 2.6, especially 

large-scale closures that should be directly observable by comparing landings with previous 

seasons. The basic premise of the model is that a change in landings (in volume and value) can

be an adequate proxy to initiate the calculation of economic impacts. The landings data was 

obtained from National Oceanic and Atmospheric Administration’s National Marine Fisheries 

Service (NMFS) to use official estimates that have been used in previous analyses of impacts, 

and likely will be used in the future analyses of impacts (NOAA 2013). The reduction in 

economic activity (change in value of reduced landings) is used to calculate the associated 

economic impacts that ripple through the supply chain. 

The change in landed value (industry revenues) represents the initial impact on the harvest 

sector, one of five industry sectors explicitly modeled in the value chain. The five industry 

sectors are harvesters, dealers, processors, wholesale/distribution, and retail (includes both 

restaurants and markets). Model outputs for each link in the supply chain included the following 

four metrics of economic activity (Kirkley 2011):

• Total Sales is the gross sales by businesses within the economic region affected by an 

activity. 

• Value Added includes labor income plus rental and other property income and indirect 

business taxes.

• Income includes personal income (wages and salaries) and proprietors’ income (income 

from self-employment).

• Employment is specified on the basis of full-time and part-time jobs. There is 

significant part-time and seasonal employment in commercial fishing and many other 

industries.

Impact multipliers can be separated into four types of impacts. The impact types from this model 

are presented as direct, indirect, induced, and total impacts (Kirkley 2011):

• Direct effects express the economic impacts in the sector in which the expenditure was 

initially made. For example, the direct income impact for the harvester sector would 

show the total income generated among harvesting employees and proprietors by demand 

for services from the harvesting sector. This direct impact would result from expenditures

made by commercial fishermen.

• Indirect effects measure the economic impacts in the specific sectors providing goods 

and services to the directly affected sector. Indirect effects include the purchases of 

products by directly-affected harvesters from manufacturers and purchases of accounting 

services. These indirect impacts extend throughout the economy since each supplier 

purchases from other suppliers in turn. For example, the accounting firms who provide 
11

services to the directly-affected harvesters would need to purchase office supplies and 

business equipment. Thus, the indirect output multiplier would represent the total output 

generated in the various supplier sectors resulting from demand for goods or services 

from the direct sector.

• Induced effects are the economic activity generated by personal consumption 

expenditures by employees in the directly and indirectly affected sectors, as harvesters, 

accountants, and other directly and indirectly affected employees spend their paychecks. 

These household purchases also have additional “indirect” and “induced” effects, all of 

which are defined as induced effects.

• Total effects are the sum of the direct, indirect and induced economic impacts. Total 

effects quantify the total impact (i.e., for total sales, value added, income or employment) 

throughout the economy created by demand for goods and services by the direct sector.

In summary, the economic impact analyses are based on measures of changes in economic 

activity, which, in this case, is a change in the dockside value (i.e., fishery revenue generated 

through catch landings) of commercially-landed marine fish and shellfish species in the Gulf 

following the oil spill. For consistency, changes in dockside value were measured using the 

reference periods set forth in the lawsuit settlement. According to the settlement, the “damage 

period” is defined as the period between May and December of 2010. This definition is 

important because it determines the period during which businesses (including fishermen and 

other supply chain participants) could claim compensation. Businesses could use any of the 

following three baseline reference periods, across the same months, in order to estimate a loss in 

dockside value or revenues loss: 2009, the average of 2008 and 2009, or the average of 2007, 

2008, and 2009 (Settlement Agreement, 2012). Quantifying impacts during the damage period is 

a measurement of short-term economic impacts. Any longer-term impacts are not captured in this

modeling exercise.

An alternative to using the official reported landings data over time collected by NMFS is to use 

the actual claims submitted and paid to firms that experienced losses. However, the data 

available in the public domain are aggregated in such a way that the extent to which they 

included all members of the industry is unknown (although they could be extrapolated based on 

average losses). In addition, the claims data has evolved over the post-spill period. For example, 

claims by commercial fishermen were calculated differently for shrimp, oyster, finfish, and blue 

crab/other seafood, as outlined in Exhibit 10: Seafood Compensation Program of the Settlement 

Agreement (2012). Seafood processors, dealers, and wholesalers were compensated under 

Exhibit 4: Business Economic Loss Claims of the Settlement Agreement (2012). Claims for 

these types of businesses were calculated based on revenue for a benchmark period in the years 

leading up to the oil spill, and a compensation period of three or more consecutive months 

between May and December 2010 (Settlement Agreement 2012). Though the eligibility 

requirements differed among commercial fishermen and other industry sectors, both business 

types had similar compensation frameworks. The difference in revenue between these periods 

was the first step in the compensation calculation. Claimants could also seek compensation for 

profits the claimant might have been expected to generate in 2010 in the absence of the spill 

based on the claimant’s growth in revenue in January-April of 2010 relative to the benchmark 

period (Settlement Agreement 2012). 
12

Another complication with using the claims data was that the settlement included only formulas 

for calculating the claims; the actual claims cannot be calculated from those formulas without 

confidential data, which is not available because of NMFS confidentiality rules and denial by the 

claims administrator. Therefore, claims data are not available by species category and state, as 

would be needed.

The settlement agreement divided all seafood landings into four categories: shrimp, oysters, 

finfish, and blue crab/other seafood. For this study, commercial fisheries in the Gulf were further 

disaggregated, given the availability of landings data and previous groupings created for an 

economic impact analysis by species/gear types (Kirkley 2011). The composition of the 

categories used in this study is summarized in Table 3.

Table 3. Composition of Species Categories for the Economic Impact Model

Fishery Groupings Species Included

Shrimp mantis shrimp, brown shrimp, tiger shrimp, pink shrimp, rock shrimp, 

royal shrimp, seabob shrimp, white shrimp

Blue Crab blue crab

Oysters eastern oyster

Menhaden Gulf menhaden

Reef Fish amberjack, grouper, hind, hogfish, rudderfish, scamp, snapper

Pelagic Finfish barrelfish, driftfish, oilfish, swordfish, tuna, wahoo

Bait ballyhoo, butterfish, herring, mullet, shad

Other Shellfish quahog, octopus, squid

Other Crustaceans Florida crab, crawfish, lobsters

Miscellaneous Finfish barracudas, bass, bluefish, brotula, cobia, croaker, grunts, hake, 

jacks, kingfish, ladyfish, leatherjacket, lionfish, lookdown, mackerels, 

margate, mojarras, parrotfishes, permit, pigfish pinfish, pomfrets, 

pompanos, porgy, puffers, stingrays, rosefish, runner, sardine, 

scads, scorpionfish, scup, sea bass, sea catfishes, seatrout, sharks, 

sheepshead, spadefishes, spot, squirrelfishes, tilefish, triggerfish, 

tripletail, wenchman

Estimates of changes in dockside value have been examined for each of the fishery categories 

and the five Gulf states across the three baseline periods allowed in the Settlement Agreement

(2012). Trying to determine changes in revenue streams is not an exact science. Based on the 

settlement documents, there were compelling reasons to allow fishermen to select from several 

baseline options for fairness or equity concerns. Estimates of revenue changes across all the three 

potential baselines from the settlement are detailed in Section 4.4.

One way to deal with different baselines is to examine upper and lower bounds on a series of 

different baselines. That is the strategy used here. Using 2009 as the baseline produces the 

lowest loss of revenues in aggregate across the Gulf. After review of the revenue data and 

consideration of the various factors external to the spill that may have influenced this revenue 

data, we determined that an additional scenario that holds external market effects constant would 

be advantageous. In doing this, we created an additional scenario where prices were held 

constant at 2009 levels to examine only the impact in reduced landings. After estimating revenue 
13

changes when holding prices constant, we found that holding 2009 prices constant presented the 

largest losses in harvester revenues relative to the spill year. As a result, 2009 was used for both 

the upper, holding prices constant, and the lower, allowing prices to change, bound estimates on 

the economic impacts of the spill. The scenario using 2009 as a baseline allowing prices to 

change will be called the Market Dynamic scenario and the scenario using 2009 data holding 

prices constant will be called the Market Constant scenario. 

1.4 Overview of Study

Chapter Two provides a descriptive analysis of how the oil spill may have affected the Gulf 

seafood industry. It begins with the geographic distribution of impacts to improve understanding 

of spatial effects across fisheries, states and associated coastal communities. Potential longerterm effects of the oil spill on the Gulf ecosystem are reviewed at a higher aggregate level, as are

potential implications at the fishery level. Concerns with seafood safety and implications on 

consumer perception and demand for Gulf seafood are reviewed through various sources of 

literature. Larger changes in the U.S. economy during the pre- and post-spill period are also 

noted and discussed with respect to likely positive exogenous effects on seafood demand during 

the damage period. Initial adjustments in markets due to product shortages and food safety 

concerns are summarized, and challenges faced by Gulf seafood producers trying to regain 

market share from import products and non-Gulf domestic producers are discussed. The 

temporary fisheries closures implemented by the federal government due to safety concerns are 

summarized spatially and temporally to allow direct comparison to changes in harvest patterns. 

Chapter Two concludes with a summary of how these impacts were or were not able to be 

factored into the subsequent economic impact model developed for this study.

Chapter Three outlines the fishing industry, the associated supply chain in the Gulf, and presents 

background data and detailed qualitative information on each species category. The fishery 

industry summaries include a review of the regulatory structure, harvest trends, and a discussion 

of typical trade routes and practices, and some general insights into how they were affected 

during the spill. Each species category is described in sub-chapters about the species and species 

groupings in the study. The final subchapter of the fishery industry background presents the 

Seafood Compensation Program and details how the program was applied to reach settlement 

amounts for the seafood industry participants. 

Chapter Four introduces the modeling portion of the study. A review of the relevant impact 

modeling literature is outlined and a solid rationale for model choice and design is presented. 

Chapter Four also contains a discussion of model construction and an overview of the 

multipliers, trade flows, margins, and assumptions for the custom input-output impact model.

The methodology behind the model, the model’s assumptions and the source of the data behind 

the customization of the model for this project are presented. Options for input data are reviewed 

and established based on the time periods established by the settlement. Two different market 

scenarios are developed (market dynamic and market constant) that estimate impacts based on 

the dockside value changes.

Chapter Five presents the overall results of the model scenarios by supply chain segment and 

gives a summary of which segments in the Gulf as whole were most impacted. It also presents
14

species-level results by state for employment, sales, value added, and income for the two 

scenarios (Market Constant and Market Dynamic) used in the impact model. A summary of the 

results is presented and discussed relative to what could be drawn from earlier qualitative 

research in the study. 

Chapter Six is a summary of the study and study conclusions. The study results are compared to 

previous studies, caveats are noted, and the intended uses and limitations of this study are 

reviewed.

The Appendix presents the custom multipliers that were developed based on the previous models 

and sources of literature referenced. These multipliers can serve as a basis for future analysis and 

impact model development.
15

Chapter Two: Factors Affecting Gulf Seafood Following the 

Deepwater Horizon Oil Spill

2.1 Overview of Factors

This chapter provides an overview of the likely impacts of the Deepwater Horizon oil spill on 

industry sectors within the Gulf of Mexico seafood supply chain. First, the geographic 

distribution of impacts relative to initial changes in landings as a result of the oil spill and

historical accounts of community impacts provided by local publications are discussed. Then,

potential longer-term impacts on the ecosystem and studies that begin to measure these impacts 

are presented. Examining these studies tells us that biological evidence is accruing, but 

attempting to measure the effects of uncertain long-run changes in stocks is beyond the scope of 

this study, as it falls outside the damage period. The effects of the oil spill on seafood safety and 

on consumer demand is discussed, including the results of studies that examined consumer 

perceptions following the oil spill. Changes in the overall U.S. economy during the key periods 

of this study are noted, and their relationship to seafood demand is discussed, including the 

effects of competition from imports and other domestic suppliers. The fishery closures 

implemented by the government to prevent harvesting in areas contaminated with oil are 

examined, since they correlate to changes in harvests during the spill. 

Landings for a given geographical area can be examined for a quick assessment of economic 

impacts. Though some impacts can be examined temporally and spatially in this analysis, various 

exogenous variables (both long term and short term) cannot be separated at this time and may not 

be measureable for years to come. The specific contribution of each potential cause of a change 

in landings is unknown and could have come from multiple sources, including the oil spill, use of 

dispersants, ecological changes, decrease in demand, etc. Also, the extent to which each of the 

potential causes is directly attributable to (or was caused by) the spill is debatable. Assessing 

economic impacts is further complicated by the fact that prices for Gulf seafood increased in 

2011 (Burdeau and Reeves 2012). This section identifies the potential suite of confounding 

market factors, and to what extent they are captured in the resulting estimates of economic 

impacts modeled in this study.

2.2 Geographical Distribution of Impacts

The geographical distribution of impacts is important to recognize because of the spatial and 

temporal differences in several Gulf fisheries. Communities near the oil spill saw the highest 

impacts, because these communities included home ports to fishermen who traditionally 

participate in fisheries that are open from April through December (the damage period in 2010). 

Because of the complexity of the biological ecosystems and fishery management systems that 

encompass these fisheries across the five Gulf states, it is prudent to examine geographical 

differences in landings during the damage period compared to historical landings. In addition, 

documented impacts on local communities in the Gulf region add considerable qualitative 

evidence of key impacts by region. 

Figure 1 shows the difference in landings of all commercial fisheries by state in 2010 compared 

to the landings during the 2009 baseline period used for this study. Though West Florida and 
16

Texas appear to have had minimal changes in landings between 2009 and 2010, Alabama, 

Mississippi, and Louisiana experienced significant declines. The less apparent impacts in Texas 

and West Florida are believed to be partially because West Florida and Texas were farther from 

the spill than the other states.

Source: NMFS Commercial Landings Statistics

Figure 1. Comparison of State Level Landings from 2009 to 

2010 

Though a change in landings is helpful in terms of assessing changes in product flows, the value 

of those landings is equally important. Any changes in product value will directly affect the 

profitability of the harvest sector and other components of the value chain. Figure 2 shows 

another comparison of state-level data, but in dollar terms as opposed to pounds. This figure 

shows that Alabama, Louisiana, and Mississippi had lower dockside revenues in 2010 than they 

did in 2009. Even though West Florida and Texas may have landed nearly the same quantity of 

product as the previous year (Figure 1), their dockside revenue increased (Figure 2) because of 

the overall increases in market prices for seafood.

0

200,000

400,000

600,000

800,000

1,000,000

Alabama Florida Louisiana Mississippi Texas

Landings 

(Thousands of lbs)

2009 2010
17

Source: NMFS Commercial Landings Statistics

Figure 2. Comparison of State Level Dockside Revenue from 

2009 to 2010

Newspaper articles reported the possibility of greater long-term impacts in specific areas and 

described hard-hit areas struggling to recover, especially those specializing in the harvest of 

shrimp, crabs, and oysters. Louisiana was the focus because of the relatively high importance of 

seafood to the state’s economy. Smith (2013), Burdeau and Reeves (2012), Johnson, Calkins and 

Fisk (2012), and Jamall (2012) all noted regional impacts two to three years after the oil spill, 

and described the impacts to fishermen and processors specifically. The results focus on 

declining shrimp, crab, and oyster landings, which are all important species to Louisiana’s 

seafood industry. 

Austin et al. (2014) focused on impacts in the coastal areas of Louisiana, Mississippi, and 

Alabama, stating that these areas were most directly affected by the spill. There was a particular 

focus on those in the shrimping industry, because shrimp is the largest contributor to seafood 

revenue in the Gulf (see Figure 5). Gill et al. (2011) compared the social and mental health 

impacts of the 1989 Exxon Valdez and the 2010 Deepwater Horizon oil spills, and described the 

implications for Gulf coast residents.

The U.S. Small Business Administration contracted a report (U.S. Small Business 

Administration 2013) that examined the effects of the spill on communities and small business 

sectors, including the commercial fishing industry, likely to have been impacted by the oil spill.

Louisiana and, to a lesser extent, Mississippi, were the most affected. The effects were 

compounded because the Gulf was facing other challenges, including recovering from the 

damage of several severe hurricanes throughout the 2000s, environmental challenges, frequentlychanging fishing regulations, increasing fuel costs, and declining seafood prices. The report 

hypothesized that geographically isolated portions of the region would be disproportionately 

affected, but instead found that impacts were related to proximity to oiled areas and fishing 

closures and that economic benefits were most significant in the response staging areas. 

$0

$50,000

$100,000

$150,000

$200,000

$250,000

$300,000

Alabama Florida Louisiana Mississippi Texas

Dockside Revenue 

(Thousands of Nominal $US)

2009 2010
18

Other efforts to track and record the social impact of the oil spill include an oral history project 

during which fishermen in the Gulf region were interviewed to document their experience in the 

fishing industry and with the oil spill (Kyriakoudes 2010–2012).

There is strong reason to believe that these impacts were attributed to the spill event. However, 

for this study it was difficult to focus spatially beyond the state level, given the limited 

availability of regional harvest data. It is clear though through the harvest data presented above 

that spill impacts were focused in particular in the states of Louisiana, Mississippi, and Alabama,

and had much less influence, if any, in Texas and West Florida from a statewide perspective.

2.3 Ecosystem Effects

The DWH oil spill was the largest marine oil spill in U.S. history (Camilli et al. 2010). More 

than four million barrels (636 million liters) of oil were released into the Gulf (Deepwater 

Horizon Unified Command 2010, Levy and Gopalakrishnan 2010, Urriza and Duran 2010). The 

light crude oil was released at a depth of 1500 m, where it emulsified because of turbulent 

mixing, reduced buoyancy, and the addition of Corexit 9500 dispersant (Fodrie and Heck 2011). 

Although a significant portion of the released oil did not rise to the surface, oil emulsified 

throughout the water column can have detrimental impacts on marine life (Fodrie and Heck 

2011). An oil spill can affect marine ecosystems for extended periods of time through direct 

destruction of habitats, mortality, and pollution of flora and fauna, and shifts in food web 

structure and function (Sumaila et al., 2012).

For example, long-term environmental and economic impacts from the 1989 Exxon Valdez oil 

spill in Prince William Sound, Alaska were still being felt in 2000 (Graham 2003). Similarly, the 

substantial release of oil into the Gulf and subsequent cleaning activities may have caused severe 

impacts on the ecosystem that may persist in the future (Love et al., 2013). In terms of landings, 

many fisheries have been impacted by post-spill closures. Spatial databases of annual reported 

commercial catch in the Gulf were analyzed, and data indicate that more than 20% of annual 

U.S. commercial fisheries catch in the Gulf was negatively affected by the oil spill (McCreaStrub et al. 2011). The fisheries at the greatest risk of economic losses include shrimp, blue crab, 

menhaden, and oyster fisheries (McCrea-Strub et al. 2011). It is essential to gather as much 

information as possible regarding the biological consequences of the oil spill on commercial 

species, because the Gulf is one of the most productive fishery regions in the U.S. 

Many habitats and associated biota within the Gulf are vulnerable to natural and anthropogenic 

stressors, such as destruction and alteration by oiling events (Zacharias and Gregr 2005, National 

Research Council of the National Academies 2005). Habitats that may be affected by the oil spill 

include oyster reefs, salt marshes, seagrasses, mangroves, pelagic sargassum, coral reefs, and 

estuaries (Getter et al. 1981, Jackson et al. 1989, Freeman et al. 2010, White et al. 2011). 

Commercial fish and shellfish depend on many of these habitats for some part of their life cycle 

and damage to these habitats, notably biologically rich marshes and estuaries, will affect many 

species (Corn and Copeland 2010). 

Commercial Gulf species that are vulnerable to oil exposure and may be at risk for economic loss 

include Eastern oyster, blue crab, brown shrimp, Gulf menhaden, and other finfishes, such as 
19

snappers (Lutjanus spp.) and groupers (Epinephelus spp. and Mycteroperca spp) (McCrea-Strub

et al. 2011). NOAA has documented direct impacts of past Gulf oil spills on blue crabs, shrimp, 

and finfishes, and these species are known to be susceptible to an oiling event (NOAA 2010). 

Of all the world’s native oyster reefs, those in the Gulf were the most productive (Beck et al. 

2011). The offshore oil industry is responsible for considerable damage to the Gulf’s oyster reefs 

(DNR 2012). The effects of an oil spill on marine fishes may not be evident until several years

have passed. Crustaceans (shrimp and crab) have also likely been harmed through higher 

mortality and the harmful compounds released during and after the oil spill, which can be 

transferred to predators that consume the toxic crustaceans. 

These past and future socioeconomic effects on commercially-important species (and the seafood 

industry) are somewhat unquantifiable until biological studies on the effects of the oil spill are 

complete. Even then, the lengths of time over which the biological (and therefore 

socioeconomic) impacts may be felt are uncertain. 

In general, marine organisms can be affected by oil through surface exposure, ingestion,

absorption, and fouling of important habitats that can create long-term alterations to an 

ecosystem (Jackson et al. 1989, Peterson et al. 2003). Eggs, larvae, and juveniles of many 

species are killed or suffer from genetic damage, physical deformities, and altered developmental 

timing after being exposed to oil (Kocan et al. 1996, Tuvikene 1995). Individuals that survive 

exposure can have potentially depressed immune functions that leave them susceptible to viral 

disease or mortality (Carls et al.1998). Large mortality events of eggs and larvae due to oil 

exposure can impact the population of inflicted organisms (Hjermann et al. 2007). In addition to 

physical effects of oil exposure, the life cycles of many marine organisms, particularly those of 

economic importance, can be disrupted through decreases in habitat use, altered migration 

patterns, and food availability (NOAA 2010). The subsections below describe potential effects 

that can be observed in oysters, fishes, crabs, and shrimp with observed examples of each type of 

organism.

2.3.1 Oysters

Oysters have an integral ecological role in marine environments with the numerous beneficial 

goods and services they provide (Cruz-Rodrígues and Chu 2002, Grabowski and Peterson 2007).

Oysters are sessile invertebrates that feed by filtering large volumes of seawater to extract 

suspended particulate matter (e.g., algae and sediment particles) from the water (Cruz-Rodrígues 

and Chu 2002, Newell 2004). They form reefs by clumping together; these reefs form habitat and 

shelter for transient and resident fish and invertebrates (Kilgen and Dugas 1989, Grabowski and 

Peterson 2007). By attenuating wave energy, oyster reefs also help stabilize sediment and 

mitigate shoreline erosion of other valuable habitats, such as salt marshes and seagrasses 

(Henderson and O'Neil 2003, Meyer et al. 1997). Oysters aid in water quality by reducing 

phytoplankton biomass, microbial biomass, and contaminants associated with suspended matter 

during the filtration process (Björk and Gilek 1996, Dame and Dankers 1988, Grabowski and 

Peterson 2007). Due to the high volume of water that they can filter, oysters are considered an 

important biofilter that helps maintain ecosystem functioning (Baird and Ulanowicz 1989, 

Grizzle et al. 2006, Newell 1988). An event such as the oil spill, which exposed oysters to oil and
20

also dispersants, could pose long-lasting impacts on the ecosystem and the various species it 

supports.

Due to their sessile nature, oysters are vulnerable to environmental conditions and stressors, such 

as an oiling event (Culbertson et al. 2007, 2008). When oil and dispersants are present in water, 

oysters can filter and accumulate harmful pollutants, such as polycyclic aromatic hydrocarbons 

(PAHs) present in oil, into their tissues as they feed (Fisher et al. 2000). Oysters have been 

documented to bioaccumulate contaminants within their tissues (Obana et al. 1981, Landrum et 

al. 1991). Contaminants absorbed in the tissues of organisms can be transferred to organisms that 

feed on them, which can have adverse effects for the consumers, including humans (Suedel et al. 

1994). Because of potential carcinogenic effects in humans, after an oyster is contaminated with 

PAHs, it should not be consumed (Lubchenco et al. 2012, Bolger 1999). Fry and Anderson 

(2014) investigated the transfer of oil from the spill into estuarine food webs and found that oil 

was minimally assimilated in the diets of mussels and barnacles. Although this study did not test 

oysters, mussels and barnacles are also filter feeders and function similarly to oysters. Larval 

oysters are free-living until they find suitable substrate to attach to (Kilgen and Dugas 1989);

oily substrate can prevent attachment or cause mortality (Freeman et al. 2010). Adult oysters can 

be suffocated if they are submerged in oil or if they close their shells to protect themselves in 

response to oil and chemicals in the water (Freeman et al. 2010). In cold water, oysters can close 

their shells for up to two weeks without direct adverse effects, but in warm water they can die 

within two days of closing their shells. The oil spill occurred in April, when water temperatures 

are variable; oysters may have suffered mortality due to closure of their shells in warm water. To 

date, there is little evidence of adverse effects on oyster recruitment post-oil spill. More data is 

needed to conclusively say whether oyster recruitment has been negatively affected after the oil 

spill. 

2.3.2 Fishes 

The effects of oil on marine fishes can often be difficult to detect. Visual signs of an oiling event 

are not as apparent with fishes as they are with birds or marine mammals. Determining if fishes 

are impacted by an oiling event may be difficult, particularly in the short-term after an oil spill 

(Sumaila et al. 2012). However, effects of oil on fishes have been well studied. In Prince William 

Sound, Alaska, the Exxon Valdez spill in 1989 provided a base for such studies (Sumaila et al. 

2012). Important fish species, such as Pacific herring (Clupea pallasii) and pink salmon 

(Oncorhynchus gorbuscha), were negatively affected by that spill. Effects on these fishes 

included premature hatching, reduced growth rates, morphological and genetic abnormalities, 

and increased mortality (Bue et al. 1998; Rice et al. 2001). Liver lesions and increased disease 

due to depressed immune systems were also seen in adult Pacific herring (Moles et al. 1993; 

Carls et al. 2001); over a five-year period, these effects contributed to increased natural mortality 

for adult herring (Thorne and Thomas 2008).

As oil spreads through the marine ecosystem, it can damage coastal areas that are important 

nursery areas for juvenile fish and shrimp (Sumaila et al. 2012). PAHs can cause direct mortality 

in fishes and can induce sublethal effects such as DNA damage, liver disease, fin erosion, 

increased heart rates, and reproductive, developmental, and immune system impairment (NOAA 

2010, National Wildlife Federation 2014). A recent study investigating the effects of crude oil on 

the developing hearts of embryos of large predatory pelagic fish reported abnormalities in 
21

cardiac function of bluefin and yellowfin tunas and amberjack (Incardona et al. 2014). In the 

Gulf, developmental crude oil toxicity of these fishes likely caused population declines of early 

life stages of tunas, amberjack, billfish, and other large predators that spawn near oiled locations 

(Incardona et al. 2014). Gulf killifish collected from an oiled location after the spill were also 

observed to undergo developmental abnormalities due to crude oil exposure (Dubansky et al. 

2013). Fishes can also be affected on a trophic level through consumption of contaminated prey. 

For example, oil and associated hydrocarbons are taken up by plankton and other surfacedwelling species that link to aquatic food webs (Sumaila et al. 2012). Fishes can consume 

contaminated prey, bioaccumulate pollutants into their own tissues, and potentially pass the 

harmful contaminants to larger predators, including humans (Suedel et al. 1994, Sumaila et al. 

2012). The effect of the oil spill on fish recruitment is still largely unknown. One study reported 

lower biomass of larval fishes of several important commercial species, including tuna, marlin, 

and dolphinfish, after the oil spill (Rooker et al. 2013). Other studies have reported the potential 

loss of recruitment due to crude oil exposure to larval stages of commercially important fish 

species (Incardona et al. 2014, Dubansky et al. 2013). In contrast, one study reported no 

significant differences in recruitment of marsh-associated fishes in coastal Alabama after the

spill (Moody et al. 2013). Because the effects of an oil spill on marine fishes may not be fully 

apparent until several years after an oiling event (Thorne and Thomas 2008), it is unclear 

whether the spill has affected the recruitment of commercially-important fishes. 

2.3.3 Crustaceans: Crabs and Shrimp 

The impact of oil exposure on the benthic community, which includes crustaceans, such as crab 

and shrimp, and other invertebrates, can be variable and often difficult to predict (Mendelssohn 

et al. 2012). For example, Sanders et al. (1980) reported that oil can cause acute reduction in 

benthic invertebrate abundance due to mortality or avoidance. Other studies have documented 

minor or subtle changes in invertebrate abundance (Lee et al. 1981, DeLaune et al. 1984). In 

general, it is recognized that benthic organisms are more vulnerable to oil exposure because of

their close association with contaminated habitats, food sources, and nutrients (Rozas et al. 2000; 

Chapman and Wang 2001, Culbertson et al. 2007, 2008). Benthic invertebrates are susceptible to 

mortality when initially in contact with oil and extreme fluctuations in populations and 

community diversity are not uncommon (Suchanek 1993). Oxygen availability, which is crucial 

to benthic organisms, can be greatly reduced due to oil (Mendelssohn et al. 2012). Oil exposure 

to crabs and shrimps can result in declines in abundance, growth rate, and condition (Culbertson 

et al. 2007, 2008). For example, juvenile shrimp exposed to oil from the spill experienced 

reduced growth rates when held in field mesocosms exposed to high levels of oil (Rozas et al. 

2014). The PAHs that are present in oil can result in direct mortality to benthic crustaceans by 

smothering the organisms or by physically and chemically inducing toxicity (NOAA 2010). In 

laboratory experiments, adult Alaskan shrimp and juvenile crabs experienced mortality when 

exposed to crude oil for 96 hours (Brodersen et al. 1977). Oil that enters an estuary can cover 

crab burrows, deplete available oxygen in the water, induce toxicity in crabs that swim through 

the oil, and induce early molting, which leaves crabs more sensitive to oil pollution (Malan 

1990). Both crabs and shrimp can accumulate PAHs in their tissues and may be unable to 

metabolize the compounds (NOAA 2010). If the animals are unable to process or dispel toxic 

compounds from tissues, these harmful compounds can be transferred to higher trophic levels 

through predators that consume the toxic crustaceans (NOAA 2010). There is little evidence of 

the effect of the oil spill on crab and shrimp recruitment. One study conducted along coastal 
22

Alabama concluded that there were no significant differences in recruitment of marsh-associated 

nekton, including crabs and shrimps (Moody et al. 2013). This one study addressing recruitment 

of marsh associated fish was restricted to one location affected by the oil spill. Beyond this one 

study, little is known about shrimp and crab recruitment successes after the oil spill. The impact 

of the oil spill on crustacean recruitment is still largely unknown.

2.4 Consumer Demand

The effects on the marketability of species suspected to have been harmed by the oil spill are 

generally negative, at least in the short-term. Early on, concerns were expressed regarding 

seafood safety, often oysters specifically (Robbins 2010; Kirkham 2010). To address these 

concerns, NOAA and the U.S. Food and Drug Administration (FDA) immediately enacted a 

seafood testing program. After thousands of samples were tested, none tested above the FDA 

safety standards (Alexander-Bloch and Anderson 2011, Louisiana Seafood News 2011).

However, the unknown nature of the extent of harm to various species was particularly 

concerning (Wittenberg 2010; Fowler 2012; Goldenberg 2010). Interviews with fishermen found 

that some continued to eat the seafood they caught throughout the period after the spill, and 

others stopped eating any of their catch (Austin et al. 2014). Some fishermen in Louisiana 

reported difficulty selling seafood to their usual customers due to food safety concerns (Austin et 

al. 2014). Even three years after the oil spill, though seafood safety may no longer be a primary 

concern, consternation persists about genetic mutations and cell damage in prey fish for food fish 

resulting from oil in bottom sediments with potential impacts to reproductive capability (Mohan 

2013; Kaufman 2011; Pittman 2013; Fowler 2012). 

One year after the oil spill, the Times-Picayune reported that some dealers were unable to sell the 

same volume they had sold in the previous years (in this case, oysters) due to decreases in 

consumer confidence, chef confidence, and brand damage (Alexander-Bloch and Anderson 

2011). This and similar reports express concerns that though landings may return to pre-spill 

levels, the markets may not. It was reported in the media that BP gave the Louisiana Seafood 

Promotion and Marketing Board $30 million to help repair the Gulf’s poor seafood brand image

(Alexander-Bloch and Anderson 2011). Friedrick (2011) noted that BP issued an upfront 

payment of $2 million to fund a crisis communications and public relations campaign to combat 

misinformation and negative press about seafood consumption and tourism in the region.

Although the program was considered to have fast-acting and deep-reaching positive benefits,

consumer concerns still remained (Friedrick 2011). The Gulf Seafood Marketing Coalition 

reported that at the time of the spill, 70% of consumers were not comfortable with eating Gulf 

seafood; results were from a survey commissioned through Big Communications and New South 

Research and were reported at the 2012 International Boston Seafood Show (Telesca 2012).

Joanne McNeely, a representative from the Gulf Seafood Marketing Coalition, stated “And now 

it’s basically flipped. We have 70% that are comfortable with it, and we have about ... 20% to 

30% who are not comfortable or they’re eating less” (Telesca 2012). From this study and others,

it is believed that initial impacts due to food safety concerns and negative consumer perception 

were prevalent in most U.S. consumer markets but quickly subsided.

Similar studies show that due to health concerns, consumers were less willing to purchase Gulf 

shrimp, crabs, and oysters immediately after the oil spill, but consumer concerns declined 
23

notably during the post-spill period. A survey conducted in 2010 by the University of Minnesota 

concluded that greater than half of U.S. consumers say they would change their seafood 

consumption due to the safety concerns caused by the oil spill (Wittenburg 2011). The research 

also noted that, although consumers indicated they would change consumption, there was no 

proof that people actually changed consumption habits. The level of concern was at its highest in 

July of 2010 and appears to have reduced dramatically toward the end of 2010. From this 

research, it is apparent there were large short-term concerns with perception during the damage 

period in 2010, but longer-term concerns were much less apparent just months after the damage 

period. 

A study by Michigan State University (McKendree et al. 2013) reported that 29% of U.S.

consumers sought to reduce their seafood consumption due to the oil spill. Others, albeit 

seemingly fewer, surmise that the Gulf seafood brand may have been bolstered through publicity 

surrounding the oil spill (Alexander-Bloch and Anderson 2011).

Another factor affecting consumer demand for seafood and dockside values of landings is the 

change in the overall condition of the general economy that occurred from 2007 to 2010. From

2007 to 2009, the U.S. economy experienced the worst recession since the 1930s (Chandra 

2010). During this period, the fourth quarter of 2007 to the second quarter of 2009 specifically,

GDP shrank a reported 5.1% and then expanded at a 3.9% annual rate for the first three months

of 2010 (Kowalski 2011, Chandra 2010). During the period of 2007 and 2009, seafood markets 

adjusted to compensate for the weak consumer markets. In times of recession, it is common for 

consumers to eat less often at restaurants and to buy more at retail markets. Wright noted that 

during 2009 restaurant sales of seafood declined notably, but retail sales did not compensate as 

expected due to price competition from other proteins (Wright 2010). The fact that a much 

higher percentage of seafood was consumed in the mid- to higher-end restaurants (Decker 2012),

which were believed to be highly affected by this recession, complicates these economic 

adjustments. In 2010, it was reported that restaurant visits and sales dramatically increased

(Decker 2012), and it was anticipated this increase was largest in the higher-end restaurants that 

tend to sell more local products. Many of the species harvested from the Gulf are sold as fresh or 

local products, which tend to be segmented for these higher-end markets and would have been 

highly impacted by these shifts in demand. The landings data and industry interviews indicated 

that prices and harvester revenues in various Gulf fisheries increased because of this general 

economic turnaround, and that the short supply in these markets added to price increases.

Another confounding market factor during this period was the fluctuation in supply of imported 

products, which is discussed in the following section. Impact estimates based on fishery revenue 

changes from 2009 to 2010 will not be solely representative of impacts due to the spill. 

2.5 Imports and Lost Market Share

The shortages of domestic Gulf seafood and perceived food safety risks forced distributors, 

retailers/restaurants, and some processors to find alternative sources of supply (both domestic 

and imported). For larger-volume frozen and shelf-stable products, as supply from the Gulf 

decreased, the number imported products increased to help meet demand. For smaller-volume 

fresh and live items, as supply from the Gulf decreased, there was an increase in non-Gulf 

domestic sources to help meet demand. The import data and industry reports suggest that import 
24

penetration has been significant in the U.S. seafood market before, during, and after the oil spill. 

The competition of imports, combined with the rising expenses of commercial fishing, such as 

increased fuel prices, has decreased profit margins for domestic seafood (Austin et al. 2014). 

Looking at import and landings data, it is difficult to attribute increases in imports in 2010 

directly to shortages caused by the oil spill. However, numerous personal communications 

conducted in conjunction with this study revealed that after the spill in 2010, many key markets 

switched to imported product to cover supply shortages and appease consumer concerns. In 

many cases, this increase in imported products continued into the proceeding period of 2011 and 

potentially 2012. In addition to imports taking over many of these markets, certain species (blue 

crab and oysters) that are sourced in other regions of the U.S. were also substituted in place of 

local Gulf products. Changing sourcing is not trivial; adjustments back to Gulf resources can 

take considerable time and consultation on price on behalf of the seller. In some cases, buyers 

may have permanently switched because of consistency of supply and more competitive prices.

In most cases, though, it was noted that buyers did resume purchases from Gulf sources 

sometime in 2011 or 2012. 

Another important trend related to market fluctuations is shortages of global supply during the 

post-spill period. Both shrimp and crab supply from various Asian countries were experiencing 

rapid slowing in supply beginning in late 2010. The decline in shrimp and crab imports into the 

U.S. after the spill are illustrated in Figures 13 and 20. The supply of imports compared to 

domestic landings for shrimp and swimming crab or blue crab amounted to an estimated 80% 

and 18% respectively in 2010 (NMFS 2014); these decreases in imported supply are believed to 

have had compounded positive effects on prices both during and beyond the 2010 period. 

It will be very difficult to discern, in this study, the effects of these import shortages in relation to 

the effects of the domestic shortages that resulted from the oil spill. Comparing the relative 

volume of imports to domestic production for key markets, such as shrimp, we can conclude that 

the domestic producer would, in many cases, be a price taker, and the importing producer would 

represent the price maker in most major seafood markets. In effect, this reduction of overall 

domestic and imported supply of particular species, such as shrimp and swimming crab or blue 

crab, would have driven market prices up for these products and increased dockside revenues 

paid in the Gulf region for these species. These market effects influencing price cannot be solely 

attributed to the oil spill; it is challenging to use only dockside revenue as a proxy for impacts 

created by the spill. 

2.6 Temporary Fishery Closures

This section discusses state-level closures and outlines the size and scope of federal closures 

which occurred during the damage period. After the oil spill, several states and the federal 

government closed their respective areas to fishing. The harvest of commercial seafood products 

from those areas was prohibited and domestically-sourced product was prevented from entering 

the supply chain. Fishery closures in the Gulf during the damage period represent cause and 

effect impacts that occurred in the various fisheries during the official damage period defined for 

the settlement (May to December 2010). Randy Pausina, who oversees fisheries programs at the 

Louisiana Department of Wildlife and Fisheries, was quoted as saying, “I can say with complete 

certainty that any lowered numbers we had with shrimp, crab and finfish last year was absolutely 
25

100 percent unrelated to anything other than the fisheries closures” (Alexander-Bloch 2011). At 

the time of the spill this claim seemed reasonable, but after further examination it is understood 

that various other biological and economic factors could have influenced, and to a certain extent 

have influenced, harvests of the noted Gulf species groupings. Examining the timing and extent 

of closures compared to historical landings can help us describe specific states and species that 

incurred impacts. 

The first commercial fisheries closures began at the state level on April 30, 2010, when the 

Louisiana Department of Wildlife and Fisheries began to close oyster grounds. Also, the 

Mississippi River fresh water diversions were opened in an attempt to prevent oil from entering

coastal marshes. At the height of fisheries closures, 55% of Louisiana state waters were closed to 

fishing (Upton 2011). On July 29, Louisiana state waters from the Mississippi River Delta to the 

Mississippi state line were reopened, and by November 10, 98% of state waters were reopened to 

commercial fishing. Public oyster beds in Western Louisiana opened in October 2010, and by 

mid-November all oyster beds west of the Mississippi River had reopened. 

Portions of Mississippi state waters were first closed to fishing on June 1, 2010. Eventually 95% 

of Mississippi state waters were closed to fishing (Upton 2011). On August 6, state waters were 

reopened to finfish and shrimp fisheries, but not until November 8, 2010 were some public 

oyster beds were reopened. 

Florida closed 2% of its state waters to commercial fishing on June 13, 2010 and reopened them 

August 16, 2010. 

Beginning in June 2010, Alabama slowly closed its state waters to fishing; at its peak amounted 

to 40% of the state waters were closed (Upton 2011). During August, Alabama began to reopen 

sections to different types of fishing. By September 6, 2010, all state waters were reopened for 

commercial fishing with the exception of public oyster reefs, which remained closed for 

rehabilitation purposes. 

Texas did not report any specific closures in state waters.

NOAA began to close federal waters to fishing on May 2, 2010. Figure 3 shows the monthly 

average of the percentage of Gulf waters in the U.S. exclusive economic zone (EEZ) that were 

closed during the damage period, May to December 2010. The largest closure at any given time 

was from June 2 to June 4, 2010, when 36.6% of Gulf waters were closed. On April 19, 2011, 

the last of the federal waters, those closest to the site of the spill, were reopened. NMFS records 

of daily Gulf closure percentages were aggregated into monthly averages so the date and 

magnitude of fisheries closures could be compared to monthly landings and dockside value. 
26

Source: NMFS Deepwater Horizon/BP Oil Spill: Size and Percent Coverage of Fishing Area 

Closures Due to BP Oil Spill

Figure 3. Monthly Average of Gulf of Mexico Federal Fishing Closures 

(%EEZ) in 2010 

2.7 Implications for Assessing Impacts

The oil spill can be expected to decrease commercial seafood landings, revenues, and exports, 

while increasing imports. For some species, this may have occurred immediately after the oil 

spill, be occurring now, and continue into the future. However, the complete effects of the oil 

spill on dockside landings and value (i.e., harvester and fishery revenues) and, ultimately, the 

profitability of the seafood industry are difficult to determine with the available data. Decreases 

in landings are visible in 2010 and subsequent annual landings data, due to temporary fisheries 

closures. There is also potential harm to habitat, fish health, and reproduction. Decreases in exvessel prices may also occur due to consumer safety and quality concerns, and a loss of available 

markets for Gulf seafood due to initial closures. 

However, some of the decreases in landings and ex-vessel prices may have been offset by factors 

unrelated to the oil spill, such as shifts in fishing effort to other areas or other species, favorable 

market conditions (including a decrease in supply), population increases, and/or increases in 

beneficial fishing conditions (weather, water temperature). Isolating the distinct contribution of 

each confounding factor affecting the seafood industry supply chain (across space, time, and 

species) in the Gulf, though a laudable goal, is not achievable because data constraints and

subjectivity about the extent to which secondary spill effects continue to be attributable to the oil 

spill. However, by examining the historical harvest data against 2010 harvest data from the 

period of fishery closures, we have noted fluctuations due, at least in part, and in some cases 

mostly, to the oil spill. 

13%

33%

31%

22%

16%

7%

2%

0.4% 0

5

10

15

20

25

30

35

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

% of Federal Gulf Waters Closed to 

Fishing
27

This study focuses on using landings and dockside value (harvester/fishery revenue) fluctuations

that occurred during the damage period (i.e., May to December 2010) to estimate regional 

economic impacts which are surmised to be caused by the spill closure. The changes in landings 

and dockside value for the designated fishery categories are used as input data to calculate 

impacts. As a result, two scenarios will anchor this analysis:

• Scenario 1, Market Dynamic or change in reported dockside value, and

• Scenario 2, Market Constant or change in reported landings valued at pre-spill prices.

The derivation of these two input data scenarios are further defined in Chapter Four of this 

report. Because of the issues regarding the cause and effect relationship of these data and the oil 

spill, these two scenarios are assumed to bookend actual effects. 
28

Chapter Three: Fishing and Seafood Industry Background

3.1 Overview of All Species

This chapter provides an overview of the species, fisheries, and supply chains that will be 

captured in the economic impact analysis of the Deepwater Horizon oil spill in the Gulf of 

Mexico. We review the regulatory structure of the Gulf fisheries, show historical landings data 

and landings data for the relevant 2009 and 2010 period, and offer insight on the supply chain 

and market factors that may have affected each species category. Each species category is 

discussed. The final section describes the Seafood Compensation Program and details how it was 

applied to estimate settlements for seafood industry participants who filed claims.

3.1.1 Commercial Fishing Regulations

Federal and state commercial fishing regulations affect the volume of seafood harvested from the 

Gulf. These regulations apply to stocks affected by the oil spill. Each species (or group of 

species) managed by federal and or state governments is regulated differently. Typical tools used 

for regulation include permitting, size limits, closed areas and seasons, trip limits, aggregate and 

individual quotas, gear restrictions, and vessel monitoring system requirements. Federal 

regulations apply to waters 3 to 200 nautical miles offshore; regulations by states apply to waters 

within three nautical miles of shore, with a few exceptions (e.g., Florida’s west coast and Texas, 

where state governance extends to three marine leagues or approximately nine nautical miles 

offshore).

Federal fisheries management is governed by NOAA. In the Gulf region, NOAA is advised by 

the Gulf of Mexico Fishery Management Council (GMFMC), one of eight regional Fishery 

Management councils established by the Fishery Conservation and Management Act of 1976. 

Each state that borders the Gulf manages their fisheries within their 3–9 nautical miles from 

shore through a state department. Each state has its own administrative process for developing 

and implementing regulations.

The numbers of federal dealer and vessel permits by species and state indicate the maximum 

number of operations operating in each species and state in the Gulf. In most cases, the number 

of active permits is likely to be less than the total number of permits. In some cases, a fishery 

permit may be retained for insurance purposes, in case other work is not available or hurricane 

damage or regulations limit the ability to participate in an alternative fishery. In general, 

fishermen own portfolios of permits and participate in those fisheries that are most profitable in 

any given season, which may change from year to year. In most cases, however, the number of 

permits gives the best indication of fishery participation, short of matching permits to logbook 

information, which is a lengthy process that is possible only under a specified grant from NOAA 

and the applicable science center.

Alabama: Alabama requires gear and species/species group specific commercial fishing licenses 

for oysters, mussels, mullet/mackerel, live bait, use of a gill net, shrimp boat (by vessel size 

category), purse seine, oyster dredge, oyster catcher, hook and line, and crab. A Seafood Dealer 

Permit is required for the sale of seafood. 
29

Florida: Florida requires commercial fishermen to have a Saltwater Products License to fish in 

state waters and sell saltwater products. Endorsements must be obtained to harvest/sell blue crab, 

stone crab, lobster, and “restricted species.” If a trap is used to commercially harvest stone crab 

or lobster, the fisherman must own trap certificates and obtain annual tags for each trap. The total 

number of traps is limited to the number of certificates a fishermen owns. Divers must obtain a 

commercial dive permit. Dealers must obtain either a Wholesale Saltwater Products Dealer 

License (for sales to any customer except the consumer) or a Retail Saltwater Products Dealer 

License (for sales to end consumer).

Louisiana: Louisiana requires gear and species/species group specific commercial fishing 

licenses for individuals participating in fishing (captains, apprentices), vessels, and numerous 

gear and species-specific gear. Dealer licenses are also required for wholesale, retail, and 

transport. Some are species-specific. In many cases, licenses must be obtained for boats, 

vehicles and individuals.

Mississippi: Mississippi requires gear and species/species-group specific commercial fishing 

licenses for captains, shrimp (by vessel size category), crab (by gear type), finfish hook and line 

(by gig per vessel and person), menhaden boat/net, oyster (by gear), and live bait (shrimp dealer, 

shrimp boat, minnow). Business licenses include an Interstate Commerce License, Seafood 

Dealer/Processor License, Menhaden Processor License, and Seafood Transport License. In

many cases, licenses must be obtained for boats, vehicles, and individuals.

Texas: In Texas, commercial fishing licenses are required for fishermen and boats targeting 

finfish, oyster, mussel and clam, shrimp, crab, and menhaden. Business licenses include licenses 

for dealers, wholesalers, retailers, and those importing seafood. In most cases, licenses must be 

obtained for boats, vehicles, and individuals. Other licenses are gear-specific for a particular 

species. 

3.1.2 Fisheries Characteristics and Trends

Figure 4 and Figure 5 list the composition of total landings by weight and dockside value, 

respectively. The relative contributions from each species group are helpful in understanding the 

relative size of potential impacts that may have occurred in each fishery. Menhaden accounts for 

the highest volume of landings, but only 9% of dockside value, whereas shrimp accounts for 

12% of landings by weight, but generates an estimated 52% of the total dockside value. During 

the period from 2007 to 2009, the relative percentages by species group remained fairly constant 

from year to year.
30

Source: NMFS Commercial Landings Statistics

Figure 4. Composition of Commercial Gulf Landings (lbs) by Core Species 

Group from 2007 to 2009

Source: NMFS Commercial Landings Statistics

Figure 5. Composition of Dockside Revenue (Nominal $US) of Commercial 

Gulf Landings by Core Species Group from 2007 to 2009

Shrimp

12.39%

Blue Crab

3.47%

Oysters

1.23%

Misc Finfish

1.48%

Menhaden

54.72%

Reef Fish

24.26%

Pelagic Finfish

0.19%

Bait

0.75%

Other Crustaceans

1.47%

Other Shellfish

0.05%

Shrimp

52.02%

Blue Crab

9.53%

Oysters

9.97%

Misc Finfish

3.65%

Menhaden

9.17%

Reef Fish

5.51%

Pelagic Finfish

1.43%

Bait

1.02%

Other Crustaceans

7.50% Other Shellfish

0.20%
31

After reviewing the relative size and breakdown of these species categories, we determined that 

certain categories (other shellfish, miscellaneous finfish, and bait) were so small and fragmented 

that detailed examination of the historical harvest numbers would not yield much value to this

study. See Chapter Five for a summary of the impact results for these smaller categories, but 

with fewer contexts to species-specific changes and market influences.

3.1.3 Supply Chain and Market Factors

Typically, seafood harvesters in the Gulf sell their catch to a dealer/aggregator or processor who

has a dealer’s license. In some cases, the harvester has a dealer’s license and can sell directly to 

restaurants, the public, and/or at farmer’s markets. Wholesalers/distributors purchase seafood 

from dealers and/or processors and sell the seafood to restaurants and retailers. Some dealers and 

processors have their own retail stores. That is, many entities’ supply chains are vertically 

integrated; other supply chains rely on largely informal contracts between harvesters, dealers, 

and others to bring seafood to market. It appears that the seafood supply chain in the Gulf can 

vary greatly in level of integration, but most species sold for human consumption have supply 

chains with three to five basic components (harvester, dealer/aggregator, processor, 

wholesaler/distributor, and retail/restaurant outlet). Each species and/or product supply chain can 

follow a slightly different path. 

Though some harvesters may have been able to switch to other fisheries or areas for fishing 

during the oil spill, others could not, due to longer and more costly travel distances, or lack of 

permits. In some fishing sectors, temporary and seasonal employment are common 

arrangements. Many employees, such as deckhands, are typically paid based on the volume of 

seafood (U.S. Small Business Association 2012) and were greatly affected by this disruption in 

fishing operations. Some docks were forced to shut down because they were diverted to spill 

cleanup efforts. At the processor level, there were not as many boats selling product because they

were unable to fish or were participating in the VOO program (Austin et al. 2014). After supplies 

increased in 2011, labor recruitment problems arose because the previous lack of work had 

caused workers to move out of the region. To make up for decreased supply during 2010, 

wholesalers, distributors, retail stores/restaurants, and some processors relied on imports, 

freshwater fish, and seafood from other domestic regions. This substitution helped these entities 

retain their markets through diversification. When Gulf seafood became available, however, 

some buyers were no longer interested in purchasing domestic seafood, due to either the cost (as 

reduced domestic supplies could have increased prices) or commitments to remain with current 

suppliers. Many processors were forced to sell at lower profit margins in order to remain 

competitive, with the goal of maintaining their current customer base (Austin et al. 2014).

To provide a better understanding of the dynamics associated with the supply chain and how the 

interrelationship of these market segments may or may not have been impacted due to the spill, a 

typical supply chain is depicted in Figure 6. Based on literature gathered and input from supply 

chain participants, the diagram shows general relationships and market dynamics. Typically, a 

vessel sells to a dealer or aggregator at the dock, who then sells the product to a processor. After 

the product has been processed into its final form, it is sold to distributors. Specialty distributors 

are often vertically integrated with processors and tend to deal in specialty seafood products,

such as fresh or live seafood, which requires time-sensitive distribution. Specialty distributors 

may sell direct to retail and restaurant outlets, or sell indirect to these outlets through a 
32

foodservice or retail distributor. Retail distributors are often subcontracted to transport the 

product to a location, such as a grocery store, where it can be purchased by a consumer. 

Foodservice distributors focus more on shelf-stable or frozen products that sell to restaurants and 

are then sold to a consumer.

Figure 6. General Seafood Supply Chain Diagram

3.2 Shrimp

3.2.1 Shrimp Commercial Fishing Regulations

The Gulf commercial shrimp industry primarily harvests two different species: white 

(Litopenaeus setiferus), and brown (Farfantepenaeus aztecus). From 2007–2009, approximately 

48% of shrimp landings and 50% of shrimp revenue in the Gulf were attributed to white shrimp, 

47% of shrimp landings and 43% of shrimp revenue were attributed to brown shrimp, and the 

remaining 5% of landings and 7% of revenue were attributed to a combination of all other
33

shrimp species (NOAA 2013). Shrimp (except royal red shrimp) are co-managed by federal and 

state entities. Some states make their regulations consistent with federal regulations to simplify 

management and rules for commercial fishermen. Offshore shrimping is not subject to seasonal 

closures, and fishing continues throughout most of the year. These vessels are typically around 

100 feet in length, and are able to travel from Texas to Florida, often on trips lasting for weeks 

(U.S. Small Business Administration 2013). Inshore shrimping is state-regulated and has

seasonal closures to protect juvenile shrimp. These vessels are typically less than 25 feet in 

length, and fish day trips or for a few days at most (U.S. Small Business Administration 2013). 

Brown shrimp are fished inshore from May to July; white shrimp are fished from August to 

December (BOEM 2014). 

Shrimp harvest is usually managed by gear restrictions, minimum size requirements, seasonal 

closures, and area closures. Shrimping in federal waters does not have a trip limit or minimum 

size limit. However, when white shrimp taken in the EEZ are transported to Louisiana, they must 

be large enough to meet with the minimum size limit of that state in order to be landed there. 

Royal red shrimp is managed separately from the other shrimp species, with a quota of 392,000 

lbs tail weight in 2013. Royal red season opens January 1 and closes when the quota is reached 

or projected to be reached.

Table 4 shows the number of federal dealer and vessel permits by state for shrimp at the end of 

2013. Royal red shrimp is shown separately from other shrimp species because it is the only 

species that is fished exclusively in federal waters and therefore requires a separate permit. These 

numbers indicate the maximum number of shrimp operations operating in each state in the Gulf.

The number of active permits is likely to be less than the official permits issued. In most cases,

there is latent fishing effort represented in these permit figures because fishermen shift efforts 

between fisheries.

Table 4. Vessel Permits of Shrimp by State, Dec. 20, 2013

State Royal Red 

Shrimp

Other 

Shrimp

Species

AL 35 97

FL 52 204

LA 49 394

MS 17 104

TX 90 532

Total 243 1,331

Note: Florida permit numbers include permits for the entire state. That is, the numbers are for 

both the South Atlantic and Gulf of Mexico management regions of Florida. This is an over 

representation of fishing operations in the Gulf.

Source: Gulf of Mexico Fishery Management Council 
34

3.2.2 Shrimp Fisheries Characteristics and Trends

Gulf shrimp landings fluctuated from 2002 to 2009; there was a peak in 2006 of approximately 

288 million pounds (Figure 7). In 2010, total shrimp landings declined to 179 million pounds, 

and then increased to 220 million pounds in 2011 and 2012. It declined to 205 million pounds in 

2013. Shrimp landings in 2010 were down by 29% compared to the landings in 2009, whereas 

dockside revenues increased 3% in 2010 compared to 2009. This is because the average price of 

shrimp increased in 2010, perhaps in response to supply shortages caused by the fishery closures. 

With respect to volume of landings, it appears that shrimp harvests rebounded in the two years 

immediately following the oil spill. Such a recovery is not unexpected, because shrimp are 

highly resilient. Shrimp grow quickly, and have a typical lifespan of less than two years; near the 

ocean floor, each female releases up to a million eggs, which enter into estuaries as juveniles to 

grow to adulthood (NOAA Fish Watch 2014). However, oil contamination has been documented 

in the coastal marshes that are critical habitat for juvenile shrimp; this could have long-term 

negative effects on the stock and landings (Tunnell 2011). 

Source: NMFS Commercial Landings Statistics 

Figure 7. Gulf of Mexico Shrimp Landings and Dockside Revenue from 

2002 to2013

Shrimping is driven by seasonal stock dynamics. Monthly commercial shrimp landings (Figure

8) and monthly dockside values (Figure 9) across all Gulf States in 2010 are shown in 

comparison to 2009. To facilitate evaluating landings with the oil spill event, the average share 

of Gulf U.S. EEZ waters that were closed to fishing each month is also shown as a relative proxy 

(see Figures 8 and 9). Though there was a notable decline in landings from 2009 to 2010 (Figure

8), the effect on revenue was not as significant (Figure 9). 

$0

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200220032004200520062007200820092010201120122013

Shrimp Dockside Revenue

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Shrimp Landings

(Thousands of lbs)

Shrimp Landings

Shrimp Revenue
35

Source: NMFS Commercial Landings Statistics

Figure 8. Commercial Shrimp Landings Before and During the DWH Oil 

Spill Relative to Fisheries Closures 

Source: NMFS Commercial Landings Statistics

Figure 9. Commercial Shrimp Dockside Revenue Before and During the 

DWH Oil Spill Relative to Fisheries Closures 

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Fisheries Closures

2009

2010
36

Shrimp is landed primarily in Louisiana and Texas (Austin et al. 2014). White and brown shrimp 

are caught throughout the entire Gulf region, and pink shrimp are caught off the coast of Florida. 

On average, Texas lands more brown shrimp and larger shrimp that fetch higher prices. 

Comparatively, on average, Louisiana lands more white shrimp and smaller shrimp which yield 

lower prices.

State level harvests from the 2010 period compared to the baseline period in 2009 show that

landing volumes decreased in all states except West Florida; the largest decline occurred in 

Louisiana (Figure 10). In 2010, dockside revenue was less than it was in 2009 in each state 

except West Florida and Texas (Figure 11). Even though landings in Texas decreased, dockside 

revenues increased. 
37

Source: NMFS Commercial Landings Statistics 

Figure 10. Comparison of State Level Shrimp Landings from 2009 to 

2010 

Source: NMFS Commercial Landings Statistics

Figure 11. Comparison of State Level Shrimp Dockside Revenue 

from 2009 to 2010

In Louisiana, the peak month for shrimp is May. In May of 2010, 65% less shrimp were landed 

than in May of 2009 (NOAA 2013). May 2010 revenues in Louisiana were 44% less than they 

had been in May of 2009 (NOAA 2013). In Texas, the peak month for shrimp is August. In 

August of 2010, 26% less shrimp were landed than in May of 2009 (NOAA 2013). However, in 

0

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2009 2010

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Shrimp Dockside Revenue

(Thousands of Nominal $US)

2009 2010
38

August of 2010, Texas shrimp revenues were 22% higher than they were in August of 2009 

(NOAA 2013). 

3.2.3 Shrimp Supply Chain and Market Factors

Typically, the first step in shrimp processing is done at the dock by the dealer/aggregator (Figure 

12). It includes washing, sizing, and grading the shrimp. The shrimp can then be frozen whole or 

sent on to a processor. Processors produce primarily raw shrimp (peeled & deveined, peeled 

undeveined, green headless, easy peel, or shell on tail on). A small portion of production goes 

into cooked, cut, and breaded shrimp and other value-added items. Cooked, peeled shrimp can be 

canned, but, according to the International Trade Commission (ITC), most often shrimp is frozen 

(ITC 2011). The average size range of Texas product tends to be larger than product caught in 

Louisiana because of the species landed, differences in fishing area size, topography, and 

environmental conditions. This size difference has effects on price and can influence revenues 

realized in the fishery. Though most processors are separate from distributors and produce 

product to be sold on the spot market, a few processors distribute and sell. High volume 

processors sometimes purchase and freeze large quantities of shrimp and distribute it over 

several months (U.S. Small Business Administration 2013). The number of processors 

participating in the shrimp industry had been consolidating before the spill. Between 1991 and 

2001, the Gulf region lost nearly a third of its processors (Keithly 2005).
39

Photo of white, brown, and pink shrimp: (Fishwatch 2014)

Figure 12. Overview of the Gulf of Mexico Shrimp Supply Chain
40

The majority of shrimp products in the Gulf go to the food service trade. Government 

institutional sales, such as the military, comprise about 15% of the food service trade. The 

remaining volume goes to the retail trade (Michael Stephens, General Manager and Chief 

Counsel of Bama Sea Products Inc., personal communication, 2014). An industry source believes

that much of the market lost during the damage period has been gained back, but also that much 

of this returning volume was bought back by dropping price (David Veal, Executive Director of 

American Shrimp Processors Association, personal communication, 2014).

It is well established that shrimp imports are important in determining domestic shrimp prices in 

the Gulf region. As a result of an ITC investigation into foreign producer dumping, tariffs were

levied for various producing countries (ITC 2011). This ITC report noted the relationship 

between domestic shrimp and imported shrimp as “sometimes interchangeable” and “comparable 

on many factors”; a “reasonable overlap of competition” exists (ITC 2011). 

Additional research has estimated price elasticity relationships between imported shrimp and 

domestic dock price. Poudel (2008) found that when there is a 10% increase in Asian production 

of cultured shrimp, Gulf dockside price is expected to decline by approximately 3.5%. Similarly, 

when South American cultured shrimp production increases by 10%, dockside prices in the Gulf 

decline by approximately 2.2%. More recently, Tabarestani (2013) found that the quantity of

shrimp imports into the U.S. and the dockside price of shrimp in the Gulf are related; however, 

they are two separate markets that do not follow the same price/quantity relationship. Although 

the quantity of shrimp landed in the Gulf has remained relatively stable, prices from the mid1980s to the mid-2000s continued to decline (Poudel 2008). Also, as the quantity of imported 

shrimp available has risen, prices for imported shrimp have declined (Poudel 2008).

The trend of increasing shrimp imports into the Gulf region continued from the mid-1980s until 

2012 (NMFS Trade Query 2014). After reviewing shrimp imports from 2007–2013 in Figure 13, 

we note that total U.S. imports and Gulf region imports both dropped during 2013, in effect,

putting upward pressure on shrimp prices. Imports into the Gulf region actually continued to 

increase in 2012, but total U.S. imports were dropping precipitously during 2012 and 2013. This 

could indicate that the shrimp trade was actively substituting imported product up until 2012, at 

which point the shortage of imported product became too difficult to source from, but the 

concrete data to substantiate this may not be available. 
41

Source: NMFS Annual Trade Data by Product through U.S. Customs Districts 

Figure 13. Annual Shrimp Imports into the U.S. and Gulf of Mexico Region

from 2007–2013

Early Mortality Syndrome is the primary factor that has negatively impacted U.S. shrimp imports 

over the past couple of years (2012 and 2013). This disease can kill 50% of shrimp on a farm. 

The full impact of Early Mortality Syndrome on global shrimp production was felt in the 2012 

and 2013 markets, when global farm production decreased by 15%. Considering that global 

farmed production of shrimp from 2006 to 2011 had been increasing at a rate of 4.8% per year, 

the full effect of Early Mortality Syndrome in 2013 was based on a 23% reduction in expected 

global market volume (Chamberlain, 2013). In addition, in December 2012 a countervailing duty 

case filed against imports from China, Ecuador, India, Indonesia, Malaysia, Thailand, and 

Vietnam added pressure to reduce import volumes during the post-spill period (ITC 2011). 

Gulf shrimp production recovered to historical levels and imports declined dramatically in 2013.

The shrimp trade reported that domestic Gulf shrimp has been able to regain most of its lost 

market share (David Veal, Executive Director of American Shrimp Processors Association, 

personal communication 2014). These complex and dynamic relationships in the shrimp trade

make it difficult to draw out all the factors that have influenced the trade of Gulf shrimp. We can 

deduce that these key issues post-spill have influenced the price of Gulf shrimp sold, and made it 

difficult to isolate the impacts of the oil spill.

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2007 2008 2009 2010 2011 2012 2013

Shrimp Imports into Gulf Region

(Thousands of Kg)

Shrimp Imports into Total US

(Thousands of Kg)

Total US

Gulf Region
42

3.3 Blue Crab

3.3.1 Blue Crab Commercial Fishing Regulations

Management of the commercial blue crab (Callinectes sapidus) is conducted primarily by the 

states, because this species is found primarily in waters less than three nautical miles from shore. 

Sometimes blue crab is co-managed by federal and state entities. Some states make their 

regulations consistent with federal regulations to simplify management and rules for commercial 

fishermen. Crab management relies largely on gear requirements, rules regarding take of female 

crabs, and minimum size requirements. Crabbing vessels smaller than 35 feet often set 25–100 

traps, and vessels larger than 35 feet set hundreds of traps (U.S. Small Business Administration 

2013). The blue crab fishery is not subject to seasonal closures, so crab fishing continues yearround.

3.3.2 Blue Crab Fisheries Characteristics and Trends

Figure 14 shows Gulf blue crab landings and dockside revenue from 2002–2013. Landings from 

2002–2009 fluctuate, and reach an all-time low of 41 million pounds in 2010. Landings exhibited

a downward trend from 2011–2013, dropping about five million pounds each year. However, 

dockside revenue increased from 2011–2013, from $49 million in 2011 to $61 million in 2013. 

In total, Gulf blue crab landings for 2010 were down by 33% compared to 2009, whereas 

dockside revenues in the blue crab fishery during 2010 were down by only 9% compared to 2009 

(Figure 14). The market for blue crab, especially blue crab meat, is complex. This market is 

influenced by external factors, such as imports. Like shrimp, crabs are fast-growing and shortlived, which explains their quick recovery (Tunnell 2011). However, long-term effects could 

result from oil contamination in the nursery habitat of the coastal marshes. Though Moody 

(2013) observed a significant decline in 2010 blue crab populations, he also noted that in 2011, 

populations returned to pre-spill abundance. Overall, as blue crab landings in the Gulf have 

fluctuated but showed a general decline from 2002 to 2010, it is difficult to differentiate the 

long-term effects of the oil spill.
43

Source: NMFS Commercial Landings Statistics 

Figure 14. Gulf of Mexico Blue Crab Landings and Dockside Revenue 

from 2002–2013

Monthly landings (Figure 15) and dockside value (Figure 16) for commercial blue crab in 2010 

are compared to the baseline year of 2009 and the federal fishery closures. Although blue crab 

fishing primarily occurs in state waters, this closure can be a relative proxy for when the inshore 

closures occurred. For details on temporary state level fishery closures, see Section 2.6. The 

period of May to October 2010 shows low landings in comparison to the previous year, but 

demonstrates a relatively small decrease in dockside value.

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200220032004200520062007200820092010201120122013

Blue Crab Revenue

(Thousands of Nominal $US)

Blue Crab Landings

(Thousands of lbs)

Blue Crab Landings

Blue Crab Revenue
44

Source: NMFS Commercial Landings Statistics 

Figure 15. Commercial Blue Crab Landings Before and During the DWH Oil 

Spill Relative to Fisheries Closures

Source: NMFS Commercial Landings Statistics 

Figure 16. Commercial Blue Crab Dockside Revenue Before and During the 

DWH Oil Spill Relative to Fisheries Closures

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Blue Crab Dockside Revenue

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Fisheries

Closures

2009

2010
45

Figure 17 shows that Alabama, Louisiana, and Mississippi experienced declines in crab landings 

from 2009 to 2010, but West Florida and Texas saw increases. Louisiana landings declined by 

42% to approximately 31 million pounds from 2009 to 2010 (NOAA 2013). Mississippi and 

Alabama crab landings also declined in 2010 by 38% and 36%, respectively, although 

comparatively in size they were significantly smaller than in Louisiana (NOAA 2013). 

Corresponding dockside revenues were similar, with all states decreasing in revenue in 2010 

except West Florida and Texas, although revenues did not decline as much as landing volume, 

potentially due to market adjustments that occurred in 2010 (Figure 18). 
46

Source: NMFS Commercial Landings Statistics 

Figure 17. Comparison of Blue Crab Landings by State from 2009 to 

2010 

Source: NMFS Commercial Landings Statistics 

Figure 18. Comparison of Blue Crab Dockside Revenue by State 

from 2009 to 2010

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2009 2010

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2009 2010
47

3.3.3 Blue Crab Supply Chain and Market Factors

The blue crab supply chain begins with vessels selling to dealers/aggregators, who then sell to 

processors (Figure 19). On occasion, vessels sell directly to processors. Five basic product forms 

are produced from blue crab: whole live, soft shell, meat, whole cooked, and value added. 

Product aggregators cull out premium grade crabs, such as live males, for the whole live market 

and sell to shedding operations and specialty distributors, then sell remaining lower grade 

product to processors for meat, whole cooked and value added (Austin et al. 2014). Although all 

these product forms are imported, the meat product form has the most import competition. There 

are three basic product forms for meat: fresh, pasteurized, and frozen. The closest substitute for 

domestic blue crab is fresh blue crab meat from Venezuela and Mexico. The next-closest 

substitute is pasteurized blue crab meat from Thailand, Indonesia, and various other Asian 

countries. The third, but weaker, substitute is frozen meat from China and other countries.
48

Photo of blue crab: (Monterey Bay Aquarium Seafood Watch 2015)

Figure 19. Overview of the Gulf of Mexico Blue Crab Supply Chain

Over the past 20 years, there has been a rapid reduction in blue crab processors in the Gulf 

region. A 2000 ITC report noted an increase in the number of crabs sold to the live market and a 

decrease in sales to the processor market. This report also noted a decrease in the average size of 

harvested crabs, which resulted in less meat (ITC 2000). In recent years, competition for supply 

at this level of the chain has increased progressively each year since the spill. An industry source 
49

indicated that lack of supply from 2011 through 2013 has created a difficult market for 

processors, and required daily break-even volumes are not always being met (Bauer 2014). In 

addition, larger, higher quality crab can yield around 18% meat, whereas the smaller, lower 

quality crab only yield around 13% meat, compounding the effects of this shift in use in recent 

years. The combination of these effects, and a reduction in both domestic landings and imported 

meat, created a volatile and difficult market for crab processors from 2011 to 2014.

Supply from import markets also competes with domestic blue crab. As was noted with frozen 

shrimp, blue crab meat has a distinct imported substitute product. The 2000 ITC report 

determined that domestic blue crab meat (Callinectes sapidus) is a “like” item to imported crab 

meat products of both blue crab (Callinectes sapidus) and flower crab (Portunus pelagicus). 

However, the report noted that because there were no significant idling of productive facilities 

and that firms were operating at a reasonable level of profit, no countervailing duties were 

instituted. 

Figure 20 shows that imports of swimming crab meat (both blue crab and flower crab) peaked in 

2008 and have trended downward since, except for a slight increase in crab meat imported into 

the Gulf region in 2012. It has been indicated by crab meat importers that lower harvest levels 

from importing countries has created a shortage in global supply of crab products, driving prices 

up over the past few years (Bauer 2014).

Source: NMFS Annual Trade Data by Product through U.S. Customs Districts 

Figure 20. Annual Crab Imports into the U.S. and Gulf of Mexico Region

from 2004–2013

The complexity of product use and global imports, combined with downward trend in supply and 

rapidly rising prices, has created a difficult business climate for processors (Bauer 2014). The 

crab market tends to be more volatile than the shrimp market, and it is a challenge to predict 

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Swimming Crab Imports into Gulf Region

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(Thousands of Kg)

Total US

Gulf Region
50

future crab volumes and prices. With the shrimp market, industry experts and retailers were well 

aware of the global supply shortage at least a year before it happened. The crab industry was 

aware of the general trends, but did not have the foresight or sophistication to predict future 

volumes or prices, which left the processors in a difficult price position on all forward contracts. 

The results are seen in the supply chain. The increased competition for whole crab off the boat 

has created increasing prices paid to fisherman and has forced the prices of finished product to 

increase. Processors are a pass-through service provider and are paid on the pounds they 

produce, not the value of landed crab. In a rising market like this, it is critical that volumes are 

high and consistent, but it is also critical that processors are able to increase prices with their 

clients (distributors and retail/restaurant outlets) as soon as vessel price increases. In today’s 

commodity seafood trade, almost all large distributors and retail/restaurant outlets have forward 

contracted prices that are difficult to adjust due to predetermined consumer promotions and 

preprinted advertising and pricing material. Due to the current climate of lower and less 

consistent volumes and rapidly increasing prices, the processors have struggled to remain 

profitable.

Another factor that was noted by the crab processors, but that may not have been as influential as 

it was with the shrimp processors or oyster processors, was the loss in market share and the 

transitional period to regain this market share (Bauer 2014). With frozen shrimp and Individually 

Quick Frozen (IQF) oysters, imported supply was abundant during the damage period, enabling 

substitution and a large shift in market share. Because of the rapidly declining supply of 

imported crab meat during the past five years, specifically the shortage during the damage period 

in 2010, it would be more challenging for the market to simply shift to imports.

3.4 Oysters

3.4.1 Oysters Commercial Fishing Regulations

The eastern oyster (Crassostrea virginica) lives attached to structures in the shallow saltwater 

bays along the Gulf coast. Management of oysters is conducted by the states because these 

species are found in waters less than three nautical miles from shore. Oyster management is 

usually subject to a minimum size requirement, gear restrictions, handling requirements, daylight 

harvesting only, and day and area closures determined by the state. Many oyster beds are 

privately owned and the owners may harvest any time of the year, though peak harvest season is 

considered to be in the late fall. In Louisiana, there are many large privately owned oyster beds 

(U.S. Small Business Administration 2013). Public oyster beds are state-regulated: there is a 

limit on the amount that can be taken and time closures can also be implemented. Public beds 

account for the majority of Alabama and Mississippi’s oyster harvests (U.S. Small Business 

Administration 2013).

3.4.2 Oysters Fisheries Characteristics and Trends

Gulf oyster landings have fluctuated from a high of 27 million pounds in 2003 to a low of 15 

million pounds in 2010 (Figure 21). Post-spill landings from 2011–2013 have fluctuated between 

19 million and 21 million pounds; they have not recovered to pre-spill levels of 23 million 
51

pounds landed during the baseline period of 2009. Though landings from 2012 to 2013 dropped 

from 21 million pounds to 19 million pounds, revenues increased from $74 million to $77 

million, showing an increase in price in 2013. Total Gulf oyster landings for 2010 were down by 

31% compared to landings in 2009 and revenues (nominal) in the oyster fishery during 2010 

were down by 25% compared to 2009. 

Source: NMFS Commercial Landings Statistics

Figure 21. Gulf of Mexico Eastern Oyster Landings and Dockside 

Revenue from 2002–2013

Monthly landings (Figure 22) and dockside values (Figure 23) for oysters in 2010 are compared

to 2009. However, federal fisheries closures are not shown, because oysters are subject to 

fishing regulations by state, rather than federal fishing regulations. Instead, oyster landings and 

revenue in Figures 22 and 23 are shown relative to when the freshwater diversions from the 

Mississippi River were opened at the end of April 2010 (see Section 1.1). Though this was 

intended to keep oil from flowing into bays and estuaries, the large influx of freshwater had the 

unintended side effect of decreasing the salinity in the oysters’ habitat and causing greater than 

80% mortality in some areas (Buskey 2010). For oysters this is a more relevant spill-related 

event than federal fisheries closures.

Figures 22 and 23 show a steep declines in oyster landings and revenues in the Gulf after the 

opening of the Mississippi River diversions. Though landings were still higher October to 

December of 2010 than they were from May to September of 2010, total oyster landings during 

the peak harvesting month of November were 35% less in 2010 than they were in 2009.

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$50,000

$60,000

$70,000

$80,000

$90,000

0

5,000

10,000

15,000

20,000

25,000

30,000

200220032004200520062007200820092010201120122013

Oyster Revenue

(Thousands of Nominal $US)

Oyster Landings

(Thousands of lbs)

Oyster Landings

Oyster Revenue
52

Source: NMFS Commercial Landings Statistics 

Figure 22. Commercial Oyster Landings Before and During the DWH Oil 

Spill Relative to Fisheries Closures

Source: NMFS Commercial Landings Statistics 

Figure 23. Commercial Oyster Dockside Revenue Before and During the 

DWH Oil Spill Relative to Fisheries Closures

0

500

1,000

1,500

2,000

2,500

3,000

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Oysters Landings

(Thousands of lbs)

Release of Mississippi River 4/30/2010

2009

2010

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Oyster Dockside Revenue

(Thousands of Nominal $US)

Release of Mississippi River 4/30/2010

2009

2010
53

Louisiana and Texas generate the highest landings and dockside revenue from the oyster 

fisheries (see Figures 24 and 25). Louisiana and Mississippi had the greatest declines in oyster 

landings from 2009 to 2010 (54% and 34%, respectively) and revenue (51% and 30%, 

respectively) and do not appear to have fully recovered (NOAA 2013). In contrast, Texas oyster 

landings actually increased by 93% and revenues increased by 104% from 2009 to 2010. This 

would suggest that when Louisiana and Mississippi landings were low due to the oil spill and 

release of the Mississippi River freshwater diversions, Texas may have decided to harvest more 

oysters, to fill in for this shortage of supply. Though oyster landings in Texas then decreased in 

2011, they increased again in 2012 and 2013, when the average price was higher. 
54

Source: NMFS Commercial Landings Statistics 

Figure 24. Comparison of State Level Oyster Landings from 2009 to 

2010 

Source: NMFS Commercial Landings Statistics 

Figure 25. Comparison of State Level Oyster Dockside Revenue 

from 2009 to 2010

3.4.3 Oysters Supply Chain and Market Factors

Gulf oyster production produces four primary products (whole live, shucked, IQF and postharvest process), which are sold predominantly in the U.S. market (Figure 26). During the period 

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

Alabama Florida Louisiana Mississippi Texas

Oyster Landings

(Thousands of lbs)

2009 2010

$0

$10,000

$20,000

$30,000

$40,000

$50,000

$60,000

Alabama Florida Louisiana Mississippi Texas

Oyster Dockside Revenue

(Thousands of Nominal $US)

2009 2010
55

after the spill, product substitution occurred in various markets in which Gulf oysters were 

dominant (Nelson 2014). Whole, live production out of the Gulf is the highest-value product and 

competes predominantly with live oyster from both the Chesapeake region and the West Coast. 

Whole, live oyster in most cases goes straight from an aggregator to a specialty distributor who 

sells into high-end restaurant and retail markets. 

Photo of eastern oyster: (Fishwatch 2014)

Figure 26. Overview of the Gulf of Mexico Oyster Supply Chain
56

During the period following the spill, product substitution for live Gulf oysters occurred for 

many major markets. An industry source indicated that, in some cases, end retail and restaurant 

customers did not return to purchase of live Gulf oyster products. It was reported that many large 

retailers shifted to companies like Coast Seafood Company, a large vertically-integrated oyster 

grower and specialty distributor on the West Coast of the U.S. Due to the consistency of product 

that Coast Seafood offered, these retail clients may have permanently shifted sourcing away from 

the Gulf oyster industry (Nelson 2014). 

IQF product from the Gulf is the lowest-value product and competes predominantly with 

imported frozen product from Korea. IQF product is sold for secondary processing/breading 

operations, such as King and Prince Seafood and Tampa Maid Foods. These secondary 

processors have traditionally used excess domestic Gulf oyster production that is over-abundant 

in the spring months of the year to supply IQF raw material for their breading operations. As 

early as the late 1980s, these secondary processors started buying supplemental IQF oysters to be 

used as raw material in their breading operations here in the U.S. When the supply of low-value 

Gulf oysters is affected by external impacts, such as hurricanes, these secondary processors rely 

heavily on IQF oyster imports from Korea. During and after the oil spill, it was reported that the 

secondary processors switched, for the long-term, almost all raw material purchases over to 

imports, and dramatically limited Gulf oyster purchases. This fact was validated when an 

outbreak of Norovirus in 2012 required the FDA to recall various oyster products produced from 

frozen oysters imported from Korea (FDA 2012). Because imports of IQF products are blended 

with various other product forms in the import figures, it is difficult to show these effects or 

determine whether these breaded processors have shifted back to Gulf oyster product. An 

industry source indicated that if the recall had not occurred, the supply chain relationship most 

likely would have been permanently altered (Nelson 2014).

Another notable change in the supply chain was that dealers or product aggregators to become 

more vertically integrated into processing and distribution. Due to the current supply constraints, 

many dealers have shifted their operations vertically up the supply chain to capture more market 

share (Nelson 2014).

3.5 Menhaden

3.5.1 Menhaden Commercial Fishing Regulations

The fishing season for Gulf menhaden (Brevoortia patronus) opens in late April and runs until 

November. In 2010, the oil spill occurred one day after the menhaden season had opened. 

Menhaden are captured offshore by large purse seine vessels and smaller net running boats that 

are guided by spotter planes (Austin et al. 2014). Menhaden is landed primarily in Louisiana. 

3.5.2 Menhaden Fisheries Characteristics and Trends

In 2010, aggregate menhaden landings hit an all-time low for the Gulf of 750 million pounds

(Figure 27). Compared to 2009, total Gulf menhaden landings for 2010 were down by 25%; 

compared to 2009, revenues (nominal) in the menhaden fishery during 2010 were down by 15%. 

From 2010 to 2011, total Gulf landings nearly doubled, from 753 million to 1.4 billion pounds, 
57

and revenue increased 80%, to $93 million. In 2012, landings and revenue declined to pre-spill 

numbers.

Source: NMFS Commercial Landings Statistics 

Figure 27. Gulf of Mexico Menhaden Landings and Dockside Revenue from 

2002–2013

Monthly menhaden landings and dockside values in the Gulf States in 2010 are compared to 

2009 in Figures 28 and 29, respectively. The figures also include the percentage of the Gulf EEZ 

that was closed to fishing in the months following the spill. Total landings and revenue of Gulf 

menhaden were negatively impacted during the fishery closures, although toward the end of the 

closures (October 2010) the fishery appeared to rebound above both revenue and landings from 

the previous year. 

$0

$20,000

$40,000

$60,000

$80,000

$100,000

$120,000

0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

1,600,000

200220032004200520062007200820092010201120122013

Menhaden Revenue

(Thousands of Nominal $USD)

Menhaden Landings 

(Thousands of lbs)

Menhaden Landings

Menhaden Revenue
58

Source: NMFS Commercial Landings Statistics

Figure 28. Commercial Menhaden Landings Before and During the DWH 

Oil Spill Relative to Fisheries Closures

Source: NMFS Commercial Landings Statistics

Figure 29. Commercial Menhaden Dockside Revenue Before and During 

the DWH Oil Spill Relative to Fisheries Closures

0

5

10

15

20

25

30

35

0

50,000

100,000

150,000

200,000

250,000

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

% of Federal Gulf Waters Closed to Fishing

Menhaden Landings

(Thousands of lbs)

Fisheries Closures

2009

2010

0

5

10

15

20

25

30

35

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

% of Federal Gulf Waters Closed to Fishing

Menhaden Dockside Revenue

(Thousands of Nominal $US)

Fisheries Closures

2009

2010
59

Louisiana menhaden landings are approximately six times larger than the next highest landings 

state (Mississippi) (see Figure 30). Alabama and West Florida total less than 1% of the Gulf’s 

menhaden landings (NOAA 2013). Louisiana’s menhaden landings in July of 2010 were 40

million pounds, 79% less than 2009 landings (NOAA 2013). In July 2010, revenues in Louisiana

were 91% less than revenues in July of 2009 (Figure 29). Though landings and revenue were 

severely impacted in July of 2010 in Louisiana, in August they rebounded to 2009 levels and 

were higher than 2009 levels in October, likely in an effort to make up for the reduced harvest 

volumes which had occurred in July.
60

Source: NMFS Commercial Landings Statistics

Figure 30. Comparison of State Level Menhaden Landings from 2009 

to 2010 

Source: NMFS Commercial Landings Statistics

Figure 31. Comparison of State Level Menhaden Dockside Revenue 

from 2009 to 2010

3.5.3 Menhaden Supply Chain and Market Factors

Two companies account for nearly all menhaden processing in the Gulf: Daybrook Fisheries and 

Omega Protein. The supply chain for menhaden is vertically integrated within these two 

0

100,000

200,000

300,000

400,000

500,000

600,000

700,000

800,000

Alabama Florida Louisiana Mississippi Texas

Menhaden Landings 

(Thousands of lbs)

2009 2010

$0

$5,000

$10,000

$15,000

$20,000

$25,000

$30,000

$35,000

$40,000

$45,000

Alabama Florida Louisiana Mississippi Texas

Menhaden Dockside Revenue

(Thousands of Nominal $US)

2009 2010
61

companies, meaning that they own the vessels, docks, processing plants, and distribution (Figure 

32). The products they produce for human consumption include fish oil supplements and fish oil 

as a food ingredient. They also produce fish meal and fish oil as an ingredient for agriculture, 

aquaculture, and pet food products. According to Daybrook (2014), their processing includes the 

fish being steamed, and pressed. It is then run through decanters and oil separators. After the oil 

is removed and used, the rest of the product goes through an evaporator and multiple drying 

processes before it is cooled and stored as fishmeal. The main competitor of fishmeal is soybean 

meal (International Fish Meal and Fish Oil Organization 2009), but some other competitors 

include animal feed made from algae, poultry by-product, and yeast extract. Substitutes for fish 

oil made for human consumption include flaxseed oil and supplements made from algae. 
62

Photo of Gulf menhaden source: (Monterey Bay Aquarium Seafood Watch 2015)

Figure 32. Overview of the Gulf of Mexico Menhaden Supply Chain

In 2010 and 2011, demand for fish oil was high, which lead to a 40% increase in prices (La 

Monica 2011). Although fisheries closures delayed the menhaden fishing season, fishing was 

still able to occur successfully around the closures; Omega Protein stated that in 2010 it caught 

90% of the fish it had planned to catch that year (La Monica 2011). Omega Protein Inc.’s 2011 

annual report states that 
63

In September and October 2010, Omega Protein received its first 

and second emergency payments from the GCCF of $7.3 million 

and $11.4 million, respectively. These payments were utilized in 

the following manner: 1) $0.6 million of the payments to offset 

recognized losses as of June 30, 2010 related to costs that were not 

able to be allocated to production as a result of intermittent plant 

closures, 2) to offset costs Omega Protein incurred to purchase 

6,315 tons of fish meal to partially offset lost production, and 3) to 

offset the high costs per unit of production Omega Protein incurred 

during the 2010 fishing season in the Gulf of Mexico as a result of 

the closure of its fishing grounds. (Omega Protein 2011)

It concludes by stating “In total, the Company received payments of $44.8 million, net of fees 

and expenses, from the GCCF in 2010 and 2011” (Omega Protein 2011). Comparative U.S.

Import statistics (see Figure 3) confirm this large increase in both Total U.S. and Gulf region 

imports of menhaden fish oil and meal during 2010 and further confirm changes in business 

practice in the menhaden industry due to the oil spill and its associated closures. 

Source: NMFS Annual Trade Data by Product through U.S. Customs Districts 

Figure 33. Annual Fish Meal and Fish Oil Imports into the U.S. and 

Gulf of Mexico Region from 2007–2012

3.6 Reef Fish

3.6.1 Reef Fish Commercial Fishing Regulations

In general, reef fish species in inshore waters are managed with size limits, gear restrictions, and 

aggregate quotas or bag limits. Seasonal closures are also common. Table 5 below gives an 

overview of fishing regulations of reef fish species. 

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

2007 2008 2009 2010 2011 2012

Fish Meal and Fish Oil Imports into 

Gulf Region

(Thousands of Kg)

Fish Meal and Fish Oil Imports into 

Total US

(Thousands of Kg)

Total US

Gulf Region
64

Table 5. Federal Regulations for Commercial Reef Fish Harvests (Snappers, 

Groupers, & other Reef Fish), 2013

Species Minimum Size 

Limited Trip Limited Quota / Closed Seasons

Red Snapper 13” total length Red snapper is 

managed under an 

Individual Fishing 

Quota (IFQ) program.

Anyone commercially 

fishing for red 

snapper must 

possess

IFQ allocation and 

follow established 

protocols.

5.61 mp gutted weight

Vermilion

Lane

Gray (Mangrove)

Mutton

Yellowtail

Cubera

Blackfin

Queen

Silk

Wenchman

10” total length

8” total length

12” total length

16” total length

12” total length

12” total length

None

None

None

None

None

None

None

None

None

None

None

None

None

None

NOTE: The Gulf Council 

has set a control date of

December 31, 2008, for 

the commercial reef fish 

fishery.

Shallow-Water 

Groupers (SWG)

Gag

Red

Black

Yellowfin

Scamp

Yellowmouth

22” total length

18” total length

24” total length

20” total length

16” total length

None

Grouper are 

managed under an 

IFQ program. Anyone 

commercially fishing 

for grouper or tilefish 

must possess IFQ 

allocation and follow 

established protocols.

Gag: 0.567 mp gutted 

weight

Red Grouper: 5.37 mp 

gutted weight

Other shallow water 

grouper: 0.510 mp 

gutted weight

Deep-Water Groupers 

(DWG)

Yellowedge

Snowy

None

None

DWG quota 1.127 mp 

gutted Weight

Speckled Hind

Warsaw

For purposes of the 

IFQ, these species are 

also included as SWG.

Goliath Harvest and possession is prohibited.

Red Drum It is illegal to harvest or possess in federal waters.
65

Species Minimum Size 

Limited Trip Limited Quota / Closed Seasons

Tilefish (Golden)

Blueline Tilefish

Goldface Tilefish

None

None

None

Tilefish is managed 

under an IFQ 

program.

Anyone commercially 

fishing for tilefish 

must possess IFQ 

allocation and follow 

established protocols.

Overall tilefish Quota:

582,000 lbs gutted 

weight

Hogfish 12” fork length None Closed Dec 2 – Dec 31, 

2013

Gray Triggerfish 14” fork length 12 fish 60,900 lbs whole weight

Closed June 1 through 

July 31

Greater Amberjack 36” fork length 2,000 lbs 409,000 lbs round 

weight

Closed March 1 through 

May 31

Lesser Amberjack

Banded Rudderfish

14” – 22” fork 

length

14” – 22” fork 

length

None

None

None

None

Source: Gulf of Mexico Fishery Management Council 

Table 6 shows the number of federal dealer and vessel permits by state for reef fish at the end of

2013. These numbers give an indication of the maximum number of reef fish operations 

operating in each state in the Gulf. The number of active permits is likely to be less than the 

official permits issued. In most cases, latent fishing effort is represented in these permit figures 

because fisherman shift efforts between fisheries.

Table 6. Vessel and Dealer Permit Requirements by state for Commercial Reef 

Fish Harvests (Snappers, Groupers, & other Reef Fish), 2013

State

Vessel Permits 

Reef Fish 

Longline 

Endorsement

Vessel Permits 

Reef Fish

Vessel Permits 

Reef Fish 

IFQ Account

Dealer Permits 

Reef Fish

AL 0 39 35 7

FL 59 642 592 145

LA 0 38 42 16

MS 0 9 12 3

TX 2 67 58 22

Total 61 795 739 193

Note: Florida permit numbers include permits for the entire state. That is, the numbers are for 

both the South Atlantic and Gulf of Mexico management regions of Florida. This is an over 

representation of fishing operations in the Gulf.

Source: Gulf of Mexico Fishery Management Council 
66

3.6.2 Reef Fish Fisheries Characteristics and Trends

Reef fish landings hit a low in 2010 at 12 million pounds; revenues were lowest in 2005, at $17 

million. Total Gulf reef fish landings for 2010 were down by 21% compared to the 2009 

landings, and dockside revenues in the reef fish fisheries during 2010 were down by 15% 

compared to 2009 (Figure 34). Although reef fish landings increased slightly from 16 million 

pounds in 2011 to 17 million pounds in 2013, revenues jumped from $44 million in 2011 to $55 

million in 2013. This shows an increased price for reef fish from 2011–2013.

Source: NMFS Commercial Landings Statistics 

Figure 34. Gulf of Mexico Reef Fish Landings and Dockside Revenue from 

2002–2013

The full list of species categorized under reef fish for this study is displayed in Table 3. The reef 

fish category includes all species of grouper and snapper, which accounted for 90% of the total

landings in 2009 (NOAA 2013). These species are most often harvested by larger ocean-going 

vessels (U.S. Small Business Administration 2013). Grouper landings were down 27% in 2010 

compared to 2009, and revenue was down 22% in 2010 compared to revenue for 2009 (NOAA 

2013). Snapper landings were down by 18% in 2010 compared to 2009, and revenue was down 

only 10% in 2010 compared to 2009 (NOAA 2013). The 2005–2006 red snapper trawl survey 

indicated strong recruitment, which is believed to have supported landings from 2007–2013, 

except the year of the spill, 2010 (SEDAR 2009).

Fishery closures after the oil spill appear to have impacted reef fish landings during the damage 

period. The monthly landings and dockside value of reef fish in 2010 are shown in Figures 35 

and 36, relative to the baseline period of 2009 and the fishery closures. This shows a slight 

reduction in landings from March to October 2010 in comparison to 2009, and also demonstrates 

$0

$10,000

$20,000

$30,000

$40,000

$50,000

$60,000

0

5,000

10,000

15,000

20,000

25,000

200220032004200520062007200820092010201120122013

Reef Fish Revenue 

(Thousands of Nominal $US)

Reef Fish Landings 

(Thousands of lbs)

Reef Fish Landings

Reef Fish Revenue
67

a relatively similar decrease in dockside value. Reef fish landings in the months of 2010 before

the spill date were not as high as the previous year, but it should also be noted that landings in 

the months following the spill decreased notably. It appears that, as the closures were lifted, 

landings made an unseasonable increase from September to December.
68

Source: NMFS Monthly Commercial Landings Statistics 

Figure 35. Commercial Reef Fish Landings Before and During the DWH Oil 

Spill Relative to Fisheries Closures

Source: NMFS Monthly Commercial Landings Statistics 

Figure 36. Commercial Reef Fish Dockside Revenue Before and During the 

DWH Oil Spill Relative to Fisheries Closures

0

5

10

15

20

25

30

35

0

200

400

600

800

1,000

1,200

1,400

1,600

1,800

2,000

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

% of Federal Gulf Waters Closed to Fishing

Reef Fish Landings

(Thousands of lbs)

Fisheries Closures

2009

2010

0

5

10

15

20

25

30

35

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

4,500

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

% of Federal Gulf Waters Closed to Fishing

Reef Fish Dockside Revenue

(Thousands of Nominal $US)

Fisheries Closures

2009

2010
69

Figures 37 and 38 show that reef fish harvests are by far largest in West Florida, followed by 

Texas and Louisiana, and minimal landings in Mississippi and Alabama. The geographic focus 

of the reef fish category is in West Florida and Texas, the two states that had minimal, if any,

closures due the oil spill. Although this geographic focus may have insulated this species 

category, there were apparent reductions in both landings and dockside value in West Florida, 

Louisiana, and Alabama, but steady increases in Texas.
70

Source: NMFS Commercial Landings Statistics 

Figure 37. Comparison of State Level Reef Fish Landings from 2009 

to 2010 

Source: NMFS Commercial Landings Statistics 

Figure 38. Comparison of State Level Reef Fish Dockside Revenue 

from 2009 to 2010

An industry source indicated that the majority of fisherman in Alabama, Mississippi, and 

Louisiana stopped fishing during the damage period; some fisherman in northwest Florida 

shifted their fishing locations away from the spill, and Texas did not have to alter its fishing 

practices (Krebs 2014). It was indicated that depressed prices and fear of oil in the fish 

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

Alabama Florida Louisiana Mississippi Texas

Reef Fish Landings 

(Thousands of lbs)

2009 2010

$0

$5,000

$10,000

$15,000

$20,000

$25,000

$30,000

Alabama Florida Louisiana Mississippi Texas

Reef Fish Dockside Revenue

(Thousands of Nominal $US)

2009 2010
71

encouraged many fisherman not to fish during the damage period. After the DWH well was 

capped in July, a series of fishing areas were reopened over the next few months, and reef fish 

fishing effort resumed well above average levels. An industry source noted that this flooded the 

snapper market with product in November and December of 2010, driving prices down (David 

Krebs 2014). 

3.6.3 Reef Fish Supply Chain and Market Factors

Although many of the primary reef fish species are caught by different vessels and in different 

geographic areas, the product market and supply chain for snapper and grouper species are very 

similar (see Figure 39). Both the snapper and grouper fisheries in the Gulf region are relatively 

fragmented because there are various participants. On the dockside, the supply chain becomes 

more consolidated with fewer companies processing and shipping fish into market. These reef 

fish species are sold primarily into fresh domestic markets in a fillet and whole product form and 

can compete in lower-end markets with imported reef fish shipped from around the world. Due 

to the premium paid for fresh product, a smaller portion of this product goes to frozen markets. 

As with most of the finfish species, reef fish can directly compete with both fresh and frozen 

imported product in some lower-end markets because from a presentation standpoint, the product 

is completely indistinguishable to the consumer. The nature of the product and strong availability 

of imports would have made it easy for seafood wholesalers and distributors to substitute product 

during the oil spill. Evidence does support that substitution occurred; there was also strong 

evidence that unique local markets do occur for species like red snapper. As was noted in the 

harvest data in Section 3.6.2, reef fisherman, specifically red snapper fisherman, were able to 

resume harvests and effectively flooded the market, driving prices down.
72

Photo of grouper and snapper source: (Fishwatch 2014)

Figure 39. Overview of the Gulf of Mexico Reef Fish Supply Chain

The red snapper fishery has been undergoing a rebuilding strategy since the 1990s. On January 1, 

2007 NOAA instituted an IFQ system. The effects of this and some focused marketing projects 

in the Gulf region created many positive effects on the snapper fishery before and after the 

damage period. Marketing efforts, established in 2010, have helped the snapper industry

establish new business relationships with companies like HEB Grocery Company in Texas. An 
73

industry source indicated that the transferable nature of the IFQ system, combined with these 

new business relationships, have enabled fishing effort to shift geographic focus away from the 

DWH fishing areas in Louisiana and Alabama and focus more in the Texas region, where there 

are strong historical harvests and newly established markets (Krebs 2014). 

Although import competition for reef fish does exist, including imports of snapper, there is 

limited evidence of direct substitution in premium markets. In case of red snapper and many 

other higher value reef fish, there is a defined market and premium paid for fresh domestic 

product which limits the opportunity for substitution of imported products. Although we know 

substitution did occur in some markets, gaining back market share for the domestic producers 

seems to have happened relatively easily according to an industry source (Krebs 2014).

3.7 Pelagic Finfish

3.7.1 Pelagic Finfish Commercial Fishing Regulations

Table 7 shows the number of federal dealer and vessel permits by state for different pelagic 

finfish fisheries at the end of 2013. These numbers give an indication of the maximum number 

of operations operating in each fishery in the Gulf. However, ownership of a permit does not 

necessarily indicate that the permit is being used. 

The number of active permits is likely to be less than the official permits issued. In most cases 

there is latent fishing effort represented in these permit figures due to fisherman shifting efforts 

between fisheries. Still, the values below provide the best indication of fishery participation 

available short of matching permits to logbook information to determine the number of active 

permits.

Table 7. Federal Vessel and Dealer Permits by State in the Gulf of Mexico, 

12/20/2013

State Vessel Permits 

Dolphin Wahoo

Vessel Permits

Swordfish 

(Handgear)

Vessel Permits 

Swordfish 

(Directed)

Vessel Permits 

Swordfish 

(Incidental)

AL 19 0 0 0

FL 1403 50 74 33

LA 20 0 30 5

MS 1 0 0 0

TX 20 1 2 6

Total 1,463 51 106 44

 
74

State Dealer Permits 

Dolphin Wahoo

Int’l Trade Permits 

Pelagic Finfish 

Species

Dealer Permits 

Swordfish

AL 3 0 4

FL 108 54 81

LA 5 0 8

MS 0 0 0

SC 18 1 7

TX 2 4 3

Total 136 59 103

Note: Florida permit numbers include permits for the entire state. That is, the numbers are for 

both the South Atlantic and Gulf of Mexico management regions of Florida. This is an over 

representation of fishing operations in the Gulf.

Source: Gulf of Mexico Fishery Management Council 

3.7.2 Pelagic Finfish Fisheries Characteristics and Trends

Figure 40 shows that pounds of pelagic finfish landed in Gulf States plummeted from 3.6 million 

in 2009 to 1.5 million in 2010, but by 2012 were back up to 2009 landings. Pelagic finfish 

revenue hit an all-time low in 2010 at $3 million, but increased back up to $13 million in 2012. 

Pelagic finfish in 2010 were down by 57% in landings and 67% in revenue compared to the 

baseline period of 2009. (See Table 3 for a list of the species categorized under pelagic fish.)

Source: NMFS Commercial Landings Statistics 

Figure 40. Gulf of Mexico Pelagic Finfish Landings and Dockside 

Revenue from 2002–2013

$0

$2,000

$4,000

$6,000

$8,000

$10,000

$12,000

$14,000

$16,000

$18,000

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

200220032004200520062007200820092010201120122013

Pelagic Finfish Revenue 

(Thousands of Nominal $USD)

Pelagic Finfish Landings 

(Thousands of lbs)

Pelagic Finfish Landings

Pelagic Finfish Revenue
75

Yellowfin tuna (Thunnus albacores), bluefin tuna (Thunnus thynnus), and bigeye tuna (Thunnus 

obesus) together account for approximately 75% of 2009 pelagic finfish landings, and therefore 

tuna harvests are the primary factor affecting pelagic finfish landings. 

Although the 2011 rebound in landings could indicate a minimal long-term effect from the oil 

spill on these species, recent studies indicate larvae could have been harmed due to the spill, 

which would not yet be reflected in landing data. A study of the larvae of Southern bluefin tuna, 

yellowfin tuna, and yellowtail amberjack by Incardona (2014) showed that crude oil exposure 

compromised the function of the larvae’s heart development; exposure to oil even at very low 

concentrations can have an effect, and the larvae that survive the initial exposure can have 

reduced swimming performance later in life due to heart development issues. Because the oil 

spill occurred during tuna spawning season in the Gulf, there is concern that the 2010 year class 

was affected in this way, but this could be very difficult to confirm because of the longer life 

cycle of these species and the highly migratory and trans-boundary nature of these stocks 

(Incardona 2014).

Monthly landings (Figure 41) and monthly dockside values (Figure 42) for pelagic finfish in 

2010 are represented in comparison to the baseline period of 2009 and the fishery closures. This 

shows a clear reduction in landings and dockside value during the damage period in comparison 

to the 2009 baseline year. This landings data seems to suggest that the vessels stopped fishing 

almost entirely from shortly after the spill until the end of the year. Austin et al. (2014)

interviewed a tuna processor in Louisiana who stated no tuna was sold to his company for a year 

after the date of the spill. He stated that most tuna boats in the area did not fish at all after the 

spill in 2010. Instead, they participated in the VOO program, and then went back to their homes 

in Vietnam. 
76

Source: NMFS Commercial Landings Statistics 

Figure 41. Commercial Pelagic Finfish Landings Before and During the 

DWH Oil Spill Relative to Fisheries Closures

Source: NMFS Commercial Landings Statistics 

Figure 42. Commercial Pelagic Finfish Dockside Revenue Before and 

During the DWH Oil Spill Relative to Fisheries Closures

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Fisheries Closures

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Fisheries Closures

2009

2010
77

Based on Figures 43 and 44 below, it can be noted that nearly all Gulf landings of pelagic finfish 

occur in Louisiana and West Florida. Louisiana landings decreased 90% and revenues decreased 

93% from 2009 to 2010 (NOAA 2013). The primary driver in the reduction of Gulf-wide landing 

was due to Louisiana having little to no landings from June to December of 2010 (NOAA 2013). 

West Florida tuna landings decreased 11% and revenues decreased 47% from 2009 to 2010 

(NOAA 2013). Though West Florida saw some sporadic tuna landings during the damage period 

(May–December 2010), these levels were much less consistent than in 2009.
78

Source: NMFS Commercial Landings Statistics 

Figure 43. Comparison of State Level Pelagic Finfish Landings from 

2009 to 2010 

Source: NMFS Commercial Landings Statistics 

Figure 44. Comparison of State Level Pelagic Finfish Dockside 

Revenue from 2009 to 2010

0

500

1,000

1,500

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Pelagic Finfish Landings 

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2009 2010

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Pelagic Finfish Dockside Revenue

(Thousands of Nominal $US)

2009 2010
79

3.7.3 Pelagic Finfish Supply Chain and Market Factors

Although many of the primary pelagic finfish species are caught by different vessels and in 

different geographic areas, the product market and supply chain for yellowfin, bigeye, and 

bluefin tuna are very similar. Though not completely integrated like the menhaden fishery, the 

commercial Gulf tuna fleet is relatively vertically integrated compared to that of other species 

categories like reef fish, oyster, blue crab, and even shrimp. 

These tuna species are sold primarily into fresh domestic markets in a loin product form and 

compete directly with imported tuna shipped from around the world. A smaller portion of this 

product is sold into frozen product markets. Domestic tuna competes directly with both fresh and 

frozen imported tuna and is almost completely indistinguishable to the consumer. The nature of 

the product and strong availability of imports would have made it very easy for the seafood 

wholesalers and distributors to substitute product during the oil spill. It appears this was the case,

because harvest data indicates that the Gulf tuna fisherman stopped fishing almost altogether 

during the damage period. 
80

Photo of bigeye, bluefin, and yellowfin tuna source: (Fishwatch 2014)

Figure 45. Overview of the Gulf of Mexico Pelagic Finfish Supply Chain

Although other external factors may have affected the Gulf tuna market in 2010, it appears from 

the harvest data that fisherman did not fish during the latter part of the damage period. It can be 
81

surmised that this decision was made based on the fishery closures, but there were most likely 

other associated factors that weighed into this decision, such as the high cost of operating and 

strong competition from imports and other domestic markets in light of a tarnished product 

image. 

3.8 Other Crustaceans

3.8.1 Other Crustaceans Commercial Fishing Regulations

The “other crustaceans” category is comprised of three primary species: crawfish, Florida crab 

(also known as stone crab), and spiny lobster. In 2010, both the commercial spiny lobster and 

stone crab fisheries were managed with tradable effort permits, and fishermen were allocated a 

number of traps they could use to fish each year. The programs were intended to reduce 

commercial fishing effort and have largely been successful in that regard. The spiny lobster 

fishery is managed by a federal regional council, the stone crab fishery is managed by the State 

of Florida, and the crawfish fishery is managed by the state of Louisiana. Under these 

management systems, permits are required, the number of legal commercial traps is fixed, and 

the traps are regulated to be of the same dimensions and construction. 

Currently the spiny lobster fishery is regulated with an additional total allowable catch 

(“aggregate catch limit” or ACL) and associated measures, but this regulation was implemented 

after the spill. Spiny lobster harvests are also regulated by a minimum size limit (i.e., carapace 

must be more than 3”). The commercial fishing season is closed from April 1 to August 5. Other 

regulations for spiny lobster include prohibition on landing females that are carrying eggs

(“berried” animals), and prohibition on the use of casitas (small structures that attract lobsters).

Table 8 below shows the number of vessel permits held in 2013 for spiny lobster.

Table 8. Federal Vessel and Dealer Permits by State in the Gulf of Mexico, 

12/20/2013

State Vessel Permits 

Lobster Tailing

Vessel Permits 

Spiny Lobster

AL 4 9

FL 211 166

LA 1 2

MS 0 1

TX 4 5

Total 220 183

Note: Florida permit numbers include permits for the entire state. That is, the numbers are for 

both the South Atlantic and Gulf of Mexico management regions of Florida. This is, therefore, an 

over representation of fishing operations in the Gulf.

Source: Gulf of Mexico Fishery Management Council 

The stone crab fishery is unique: typically only one claw from each animal is harvested, and 

larger claws receive significantly higher prices. The stone crab fishery also has a limited harvest 
82

season (15 October through 15 May) and a minimum harvest claw (propodus) size of 2–3/4 in 

(70 mm). Peak landings were 3.5 million pounds of claws statewide in the 2000–01 fishing year. 

Statewide landings in 2009–2010 were 2.4 million pounds of claws.

The crawfish fishery is highly seasonal, and most of the harvest occurs between March and June. 

Crawfish are primarily harvested and sold live to consumers local to the Louisiana area due to 

the short shelf life of the live product (UL 2010).

3.8.2 Other Crustaceans Fisheries Characteristics and Trends

In 2006 landings of other crustaceans hit an all-time low: 11 million pounds, though revenues 

fluctuate but show a general upward trend (Figure 46). Landings of other crustaceans in 2010 

were down by 13% from 2009, and revenues increased by 54%. This trend shows that the price 

of other crustaceans was much higher in 2010 than it was in 2009.

Source: NMFS Commercial Landings Statistics 

Figure 46. Gulf of Mexico Other Crustaceans Landings and Dockside 

Revenue from 2002–2013

The species categorized under other crustaceans for this study are listed in Table 3. During

2009, landings in the “other crustaceans” fishery category included 67% crawfish, 19% Florida 

crab, 13% spiny lobster, and 1% slipper lobster. However, the species composition of this group 

fluctuates from year to year more than the other species categories. From 2009 to 2010, crawfish

landings decreased 25%, but spiny lobster landings increased 33%. Additionally, there was a 

31% increase in Florida crab revenue and a 168% increase in spiny lobster revenues, suggesting

that the price of spiny lobster increased rapidly and drove the overall increase in revenues of the 

other crustacean category during 2010. Further decreases in other crustacean landings in 2011 

and 2012 were primarily due to decreases in crawfish landings, but 2012 also saw a decrease in

$0

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200220032004200520062007200820092010201120122013

Other Crustacean Landings 

Other Crustaceans Revenue 

(Thousands of Nominal $US)

(Thousands of lbs)

Other Crustaceans Landings

Other Crustaceans Revenue
83

spiny lobster landings. In 2013, other crustacean landings were back up to pre-spill levels, 

primarily due to a 195% increase in crawfish landings between 2012 and 2013.

Figures 47 and 48 present other crustacean landings and dockside revenue in 2010 by month, 

relative to the baseline period of 2009, and the federal fishing closures. Landings and dockside

revenue in 2010 were notably lower than 2009 from May to July. After July, both landings and 

revenues surpassed 2009 harvests, but with revenues increasing dramatically toward the end of 

2010. This would suggest that some sort of market event drove prices in West Florida on spiny 

lobster during the latter part of 2010.
84

Source: NMFS Commercial Landings Statistics

Figure 47. Commercial Other Crustacean Landings Before and During the 

DWH Oil Spill, Relative to Fisheries Closures

Source: NMFS Commercial Landings Statistics 

Figure 48. Commercial Other Crustacean Dockside Revenue Before and 

During the DWH Oil Spill, Relative to Fisheries Closures

0

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% of Federal Gulf Waters Closed to Fishing

Other Crustaceans Landings 

(Thousands of lbs)

Fisheries Closures

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Fisheries

Closures

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2010
85

In reviewing Figures 49 and 50 below, it is important to note that all crawfish was landed in 

Louisiana, all lobster (spiny and slipper) was landed in West Florida, and over 99% of Florida 

crab was landed in West Florida. The large drop in landings in Louisiana can be attributed to a 

large reduction in crawfish harvest with a much smaller decrease in Louisiana dockside value of 

crawfish, indicating some market adjustments in price due to the supply shortage. In West 

Florida, the increase in landings can be attributed to spiny lobster, and the large dockside

revenue increase is believed to be driven by a dramatic increase in spiny lobster price in the latter 

part of 2010.
86

Source: NMFS Commercial Landings Statistics 

Figure 49. Comparison of State Level Other Crustaceans Landings 

from 2009 to 2010 

Source: NMFS Commercial Landings Statistics 

Figure 50. Comparison of State Level Other Crustaceans Dockside 

Revenue from 2009 to 2010

0

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Other Crustaceans Landings

(Thousands of lbs)

2009 2010

$0

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$50,000

$60,000

Alabama Florida Louisiana Mississippi Texas

Other Crustaceans Dockside Revenue

(Thousands of Nominal $US)

2009 2010
87

The primary harvest region for spiny lobster and Florida crab is geographically located far 

enough from the spill and federal closures that they appear to have had minimal effects on 

harvests (GOM FMC 2011). In addition, it is important to note the seasonal harvest of these 

West Florida fisheries occurred at the latter part and somewhat outside the damage period. To 

date, there has been no indication the oil spill has had any effects on the spiny lobster stock or 

fishery. For example, there was no mention of the DWH oil spill during the Spiny Lobster 

Review Panel meeting (which was convened in February 2015) to discuss the validity of the 

most recent stock assessment and recommended ACLs; in fact, the Panel noted that landings 

increased in 2010 and 2011 compared the previous decade (Spiny Lobster Review Panel 

Summary 2015).

3.8.3 Other Crustaceans Supply chain and Market Factors

The other crustaceans category includes three primary species: crawfish, Florida crab (also 

known as stone crab), and spiny lobster. Although these are three distinctly different species, we 

will summarize their relative differences and similarities in the supply chain and markets. 

Crawfish are harvested (farmed and wild) almost exclusively in Louisiana and are sold mostly 

live to local markets within a one-day driving distance. The supply of crawfish can be volatile, 

and when supplies are abundant, crawfish are frozen and sold whole. Abdominal or “tail meat” is 

processed and sold both fresh and frozen. Due to the extended shelf life of this product, it can be 

sold in markets outside of the direct Louisiana region (UL 2010).

Spiny lobster and Florida crab are both harvested almost exclusively in West Florida, and both 

are featured in high-end product markets. Spiny lobsters are sold both live and as frozen tails.

Florida crabs are harvested only for their claws, and the live carapace is returned to the sea. Both 

these species are sold into local West Florida markets, but there are also lucrative export markets 

in Asia that have been growing in recent years and driving up product values. 

Crawfish harvests tend to fluctuate largely from year to year and tend to be highly influenced by 

weather events such as Hurricane Katrina. Landings of crawfish decreased by 25% from 2009 to 

2010. Overall landings in the other crustaceans category show a decline from 2010 to 2012, 

which can be attributed to crawfish harvest declines. Because of the historical volatility of 

landings and sensitivity to weather events, it is difficult to separate these effects and definitively 

say this reduction was solely due to the oil spill. Another factor that has not been thoroughly 

examined, but may have influence on crawfish revenue, is the large increase of imported 

crawfish products from China in the past decade. 

In the 2010, there was a large increase in dockside revenue compared to 2009 in the other 

crustaceans category. The state and species level harvest data in Chapter 3.8.2 indicate that this 

large increase is based primarily on price increases in spiny lobster and somewhat based on price 

increases in Florida crab. In general, a suite of factors can contribute to fluctuations in revenue,

but in this particular case it appeared to be mostly driven by favorable market factors. The 

primary factor that influenced revenue in the spiny lobster industry in recent years has been the 

transformation of its production capacity from processed lobster to live lobster, to meet the 

demand of the high-priced live Asian markets. This transformation in markets is believed to have 
88

had a large impact on price received by the fisherman and driven up the revenues in the other 

crustaceans category. Note, however, that large price and revenue increases were in return for 

healthy live lobsters that are more costly to harvest, such that revenue increases may have been 

offset by higher cost of handling, masking any potential increases in net returns or profits (Spiny 

Lobster Review Panel Summary 2015). The magnitude of the 2010 increase in revenue was 

complicated by the fact that spiny lobster prices were at their lowest since 1970 in the 2009 

harvest year, due to unprecedented weak global market demand (Vondruska 2010). In addition to 

these market factors, a lack of recent hurricanes, and potentially a reduction in recreational 

fishing effort during the early part of the 2010 summer due to concerns of the spill, could have

contributed to the increase in commercial landings during the latter part of the damage period

(Spiny Lobster Review Panel Summary 2015). 

3.9 Summary of Seafood Industry Trends

After reviewing the regulations, harvest trends, supply chain, and market factors by key species 

category and state, we can identify some relative trends. Although it appears that landings 

decreased in most major fisheries due to the spill closures, based on the spatial and temporal 

nature of these fisheries we see that certain species and states appear to have been unaffected by 

the spill. When reviewing changes in dockside revenue of the species categories, we see that the 

situation is more complex due to the dynamic nature of markets and moving prices, and the same 

conclusions cannot be clearly drawn from the data. In general, it can be noted that a series of 

events external to the oil spill increased prices and overall revenues in 2010 and minimized 

potential damages that could have occurred if favorable market conditions had not existed during 

the damage period. 

Distinct trends show the effects of the spill were focused in the geographic region closest to the

spill and the areas that incurred sizable closures, primarily Louisiana, Mississippi, and Alabama

(see section 2.2 for more details). In states further away from the spill that incurred minimal if 

any closures, like West Florida and Texas, effects on landings and dockside revenue seem to be 

relatively muted. 

3.10 Seafood Compensation Program

Another approach considered in estimating losses to the seafood industry of the oil spill is to 

look at the amount paid through legitimate claims made to BP funds. This approach requires 

examination of the Seafood Compensation Program. A substantial amount of effort and funding 

went into the methodology and development of this program. This program is a concrete 

representation of how these impacts were quantified and paid out. 

A $20 billion initial estimate of the potential damage of the spill was made and allocated to the 

Deepwater Horizon Oil Spill Trust. The trust was established by BP to settle claims resulting 

from the oil spill. The fund was established to compensate for natural resource damages, and to 

compensate state and local response costs, and individuals. The funds were distributed by the 

GCCF, established in June 2010 after a meeting of BP executives with U.S. President Barack 

Obama. In June 2012, the settlement of claims through the GCCF was replaced by the courtsupervised settlement program.
89

The Seafood Compensation Program is a separate $2.3 billion fund established under the 

Economic and Property Damages Settlement. Its sole function is to compensate for economic 

damages suffered by seafood vessel owners, commercial fishermen, or seafood crew that owned, 

operated, leased, or worked on a vessel that was home ported in a Gulf coast community, or 

landed seafood in the Gulf coast area. The Program also specifically covers economic damages 

suffered by oyster leaseholders and IFQ owners, which includes participants in the reef fish 

programs in the Gulf.

Eligible claims were awarded to entities in the following categories:

• Oyster Leaseholders: Person or business holding one or more private oyster leases.

• Seafood Vessel Owners: Person or business who owns a vessel and earns income from 

leasing or renting that vessel to a commercial fisherman and/or oyster leaseholder; also 

may be a commercial fisherman if also a boat captain.

• Commercial Fishermen: Boat captains, including businesses who hold a commercial fishing 

license and make income from catching/harvesting and selling shrimp, oysters, finfish or 

blue crab/other seafood caught in certain Gulf waters.

• Seafood Crew: First Mate, Second Mate, or Boatswain working for a commercial fisherman; 

Deckhand whose primary responsibilities occur off-shore in certain waters (Deepwater 

Horizon Settlements 2012).

According to the settlement, the damage period is defined as the time between May and 

December of 2010. The definition of the damage period is important, because it determined the 

period over which businesses, including fishermen and fisheries and other supply chain 

participants, could claim compensation. Businesses could use any of the following three baseline 

reference periods, across the same months, to estimate a loss in dockside value or revenues loss: 

2009; the average of 2008 and 2009; or the average of 2007, 2008, and 2009 (Settlement 

Agreement 2012).

The verification of earnings was based on tax records or other documentation sufficient to 

identify gross revenues. Though some commercial fishing fleets had improved their 

documentation practices due to missed opportunities to receive aid after Hurricane Katrina, many 

had not (U.S. Small Business Administration 2013). As an alternative, individuals were able to 

complete a Sworn Written Statement for Sufficient Documentation of Benchmark Revenue that 

includes the information required to identify revenue by vessel, catch types, and landing 

locations. Documentation showing revenue by vessel and catch types is evident in trip tickets if 

these are submitted. However, fishermen and dealers have noted that some individuals’ trip 

tickets do not always accurately reflect revenue earned due to illegal landings for species out of 

season or brought in by unpermitted individuals. The extent to which this occurs is unknown.

Crew needed to submit tax records or pay period documentation to receive compensation. This 

can also be problematic, because crew arrangements with vessel owners are sometimes informal 

and crew are often paid in cash or in catch that they can sell, so there would not be an automatic 
90

paper trail. However, this often cannot be documented. The extent to which this occurs is also 

unknown. For these reasons, the claims distributed are very possibly an underrepresentation of 

actual seafood revenue effects.

Seafood processors are compensated separately under the Economic and Property Damages 

Settlement. The Seafood Compensation Program does not apply to claims relating to fishing, 

processing, selling, catching or harvesting of menhaden.

The Seafood Compensation Program has five separate plans to provide compensation, each of 

which has its own eligibility requirements, documentation requirements, and compensation 

method. The five categories are Shrimp, Oysters, Finfish, Blue Crab/Other Seafood, and Seafood 

Crew (excluding Boat Captains) for all seafood industries. Each claim category is divided into 

different claim classes. The class an individual is in depends upon the claims made, with the 

types of compensable claims determined by the relationship the individual has with the vessels 

used in the claims. These distinctions are important because each class may give an individual 

the chance to file a new/additional claim. They may fall within more than one seafood-type 

category if they distribute different types of seafood (Settlement Agreement 2012). 

The deadline to file a claim under the Seafood Compensation Program was January 22, 2013.

After the Seafood Compensation Program initial funds distribution, any additional money left in 

the Fund will be distributed to those claimants who already received compensation. In other 

words, those who make claims now may later receive an additional share of this final distribution 

amount, which will be systematically distributed as lump sums. However, this process is being 

challenged due to accusation of fraud by plaintiffs (BP 2013).

If an individual made a claim and/or received compensation under the Seafood Compensation 

Program, they may still be eligible to separately receive compensation under other sections of the 

Deepwater Horizon Economic and Property Damages Settlement, or the Medical Benefits 

Settlement, depending on the nature of their loss.

In this way, the full amount of the Seafood Compensation Fund is the lower limit of the amount 

of compensation going to the seafood industry. Specifically, it is distributed only to those 

directly impacted by the oil spill. Processors, dealers, wholesalers, and fishing supply industries 

would be compensated through other fund sources.

As of January 21, 2015, approximately $1.104 billion has been offered and accepted by 

claimants to the Seafood Compensation Program. This amount was distributed to 4,747 unique 

claimants. This amount is the second largest portion of the total $4.399 billion dollars 

distributed, as of the date above, for all funds allocated to reimburse people and businesses 

harmed by the oil spill. The largest category was in Business Economic Loss, payments in this 

category totaled about $2.416 billion (Deepwater Horizon Economic Settlement 2015).

It should be noted that payments for cleanup operations in the VOO program and payments made 

through the Seafood Compensation Program were anticipated to increase the amount of money 

in the economy. It is believed that this helped to offset some of the losses to the seafood industry. 
91

However, there were many other precursors, including rising fuel costs and hurricane damage 

(BOEM 2014 and U.S. Small Business Administration 2013), and the many other factors 

mentioned in this report, that determine the impact on an individual from the Seafood 

Compensation Program.

The Seafood Compensation Program was examined in this study, but claims estimates were not 

directly used in the model. Instead, examination of the program allowed for understanding and 

recognizing the nature of impacts, and the framework of the program assisted in structuring 

species categories and establishing the temporal period for the study.
92

Chapter Four: Economic Impact Model

This chapter begins with a review of the associated impact model literature that was used to 

determine the model structure and present a solid rationale for model choice and design. The 

chapter details the development and construction of the custom I/O impact model, and gives an 

overview of the multiplier construction, trade flows, margins, model structure, and assumptions. 

The methodology behind the model is presented, along with the model’s assumptions and the 

source of the data behind the customization of the model. Options for input data are reviewed 

and set based on the time periods established by the settlement, and two different market 

scenarios are developed (market dynamic and market constant) that estimate impacts based on 

the dockside value changes.

4.1 Selection of Base Model 

In an attempt to estimate the economic losses to the Gulf of Mexico seafood industry caused by 

the Deepwater Horizon oil spill, it is first necessary to identify whether to estimate the loss in 

economic value or the economic impact of the oil spill. Clarifying the difference between the 

terms “economic value” and “economic impact” is necessary, because they refer to different 

concepts that are uniquely suited for evaluating different types of changes in economies.

If a reduction in economic value were used to capture the effects of the oil spill on the Gulf coast 

region, the losses would be measured as the change in market value of seafood, less the value of 

fishermen wages, fuel, supplies, boat depreciation, and other resources that were not used to 

catch the seafood. This net change reflects the social welfare loss from the seafood industry (that 

could be added to recreational losses and non-market values), which is useful to policy makers 

who are considering how much future spending is justified to restore stocks (to regain the losses) 

or to prevent potential losses from future spills. Economic values are the basis of cost-benefit 

analysis of alternative projects or policies. 

On the other hand, an economic impact analysis of the oil spill would capture the reduction in 

total economic activity (measured in jobs, personal income, sales volume, etc.) within a region 

and the distributional effects across sectors in the economy. The total economic impact of a 

contraction in seafood harvesting, including the secondary impacts on local employees and 

companies, is a measure of economic activity levels (as distinct from social or economic value). 

Economic impact analysis includes direct impacts on basic industries, secondary impacts on 

support industries, and finally the impacts on spending by labor employed in these industries. 

Because one of the major objectives of this study was to capture supply chain effects, we 

determined that calculating the economic impact of the oil spill to the Gulf region economy is the 

appropriate methodology for this assessment.

4.1.1 Types of Economic Models

Economic impact models are a representation of all the transactions in an economy, and allow 

analysts to outline the relationships between the production of goods and their final consumers. 

There are several approaches that can be employed to examine the economic impacts to the 

fisheries supply chain from exogenous shocks such as the oil spill. These approaches include 
93

models of the following four types: (1) Input-output (I/O), (2) Social Accounting Matrix (SAM), 

(3) Computable General Equilibrium (CGE), and (4) Econometric. Each is discussed briefly 

below to explain the strengths and weaknesses of each with respect to the overall selection 

criteria for this study.

The first type of impact models are I/O models; these models have been in use the longest of all 

types of economic impact models. As a result, they are used most frequently. These models take 

an accounting representation of the economy and translate exogenous demand shocks (such as a 

sudden drop in sales of seafood) into economic impacts (Kraybill 1994). The demand shocks 

must be estimated outside the I/O model and the estimated shocks are translated into economic 

impacts using multipliers generated in the I/O model to capture effects throughout the supply 

chain (Seung and Waters 2006).

I/O models (at the county, state, or national level) can estimate impacts for any type of demand 

shock, because they are based on a set of economic accounts that are updated every year; that is, 

the software is available for purchase each year. Because they are based on readily available 

data, they are simple and quick to use. On the other hand, commodity prices within the I/O

model are fixed. Additionally, factor substitution in production is not allowed, nor is commodity 

substitution in demand. Because none of these items are allowed to vary within the model as a 

result of the demand change, I/O models can overestimate impacts. This is because the model 

cannot account for the behavioral changes of individuals and firms to compensate (and hence 

partially offset) the demand shock.

SAMs are an extension of I/O models that are expanded to include more details on income 

distributions. As a result, SAMs have the same drawbacks as I/O models, but also require more 

data (West 1995). The IMPLAN software package, however, includes a SAM, and the user can 

specify whether to use multipliers that incorporate the SAM data (MIG 2013). Because IMPLAN 

includes a SAM, most IMPLAN-based I/O analyses incorporate the SAM information. 

Generally, SAMs are also the starting point for the creation of CGE models. 

CGE models overcome the fixed price model limitations of both I/O and SAM approaches. The 

CGE model uses basic economic accounts in a simulation model that allows prices and quantities 

to equilibrate after a demand shock (Rey 2000). Therefore, factor and commodity substitutions 

are captured. As a result, they can also estimate welfare impacts (i.e., changes in distribution of 

income effects across industries). On the negative side, CGE models require massive amounts of 

economic data, including demand and supply elasticities (i.e., the responsiveness of individuals 

and firms to changes in prices). CGE models also require complex and time consuming modeling 

and calibration. They also could underestimate impacts. The development of CGE models for 

fisheries would be extremely complicated because of the lack of available detailed data on 

fisheries supply chain sectors, and the responsiveness of each following the oil spill. Building 

such a model is beyond the scope of this project.

Finally, econometric models use regression-based approaches to estimate economic impacts. 

They are statistically rigorous, stochastic, and can forecast changes into the future. They require 

both time series and cross section data, and they require the most data of all the model types 

discussed here. Finally, when econometric approaches are used to estimate economic impacts, 
94

they can only estimate total impacts and have no ability to examine inter-industry linkages. 

Econometric models were not considered appropriate for this project. 

Table 9 summarizes the strengths and weaknesses of these approaches. Though a couple of the 

approaches were ruled out due to complexity or unsuitability based on the objectives of the 

study, the table provides a mechanism to help with final model selection discussed below.

Table 9. Impact Model Types, Strengths and Weaknesses.

Methodology Strengths Weaknesses

Input Output (I/O)

Detailed inter-industry 

linkages

Simple structure

Flexible/adaptable

Easily integrated with other 

approaches

Starting point for CGE

Linear structure

Static

No supply constraint

No price response

Social Accounting 

Matrix (SAM)

Same as above

More details on 

interdependency, particularly 

for households

Same as I/O

Large data requirements

Overestimates impacts

Computable General 

Equilibrium (CGE)

Non-linear

Can be stochastic

Includes price effect

Includes supply constraint

Includes supply and demand 

substitution

Too flexible

Even larger data needs

Calibration challenging

Huge analytical lift

Underestimates impacts

Econometric

Statistically rigorous

Stochastic

Ability to forecast 

Largest data requirements 

(time series and cross 

section)

Total impacts only

No ability to examine interindustry linkages

Source: (Kraybill 1994, West 1995, Rey 2000)

After considering the modeling criteria established earlier, and the general strengths and 

weakness summarized in Table 9, we decided to use the I/O approach augmented with SAM data 

through the use of IMPLAN multipliers. 

Though there are other choices for analyzing economic impacts, such as the ratio between total 

regional employment and fishing employment (Hartman 2002), the impacts are restricted in 

terms of metrics of economic activity generated, metrics that are available using the I/O output. 

In addition, assessing the economic impacts of commercial and recreational fisheries has also 

involved models that join economic and biological and/or ecological considerations. The 

underlying premise is that understanding natural resource public policy implications requires an 

understanding not only of economic effects and impacts on ecosystems, but also the interaction 
95

between these disciplines. These models represent a substantial departure from those that deal 

exclusively with economic impacts suffered by industries (the focus of this study).

4.1.2 The I/O Platform and Alternative Models

The general use of methodologies based on I/O to estimate economic impacts is made possible 

by the commercial availability of I/O models that can be adapted to the needs of many different 

kinds of analyses. A number of models are available, but Regional Input-Output Modeling 

System (RIMS) II, IMPLAN, and Regional Economic Modeling, Inc. (REMI) appear to be the 

most widely used in the estimation and analysis of economic impacts (Kirkley 2011). 

These models offer broadly similar capabilities but have distinct characteristics. The U.S. 

Department of Commerce developed and offers RIMS II. IMPLAN was originally developed for 

the U.S. Forest Service and is now maintained by IMPLAN Group, LLC. Developed by Regional 

Economic Modeling, Inc., REMI combines an I/O model with econometric models that provide 

added capabilities, particularly a dynamic component that allows components of the model (e.g., 

population, factor prices) to change as the regional economy responds to new final demands. 

RIMS II and IMPLAN may be purchased by the user; REMI can only be leased (Lynch 2000).

IMPLAN is currently used almost exclusively for economic impact studies (Murdock et al. 

2002). IMPLAN represents a middle ground between the simplicity and inflexibility of RIMS II 

and the complexity, cost, and substantial data requirements of REMI. IMPLAN is purchased as a 

set of software and datasets that allows the user to define regions and customize the I/O model. 

More recent versions of IMPLAN, particularly Version 3.0, allow the modeler even more 

flexibility to change the model and add sectors (MIG 2013). This flexibility and costeffectiveness has helped IMPLAN become the industry standard for the estimation of economic 

impacts not only for commercial and recreational fishing, but also many other economic 

activities.

Economic impact models use final consumer purchases to track industry activity in the supply 

chain backwards from the consumer (Miller and Blair 1985). Unfortunately, retail data on 

consumer purchases of seafood is difficult to obtain, particularly from restaurants (Kirkley 

2011). Instead, analysts often have access only to purchases made at various places in the supply 

chain before the product reaches the consumer. As a result, a special economic impact model has 

to be constructed to examine the typical economic linkages down the supply chain from the 

fisherman and the linkages forward in the supply chain to the consumers. 

To examine economic impact forward of fishermen, price mark-ups or margins for the sectors 

forward in the supply chain need to be specified in order to determine the value entering the next 

industry link forward. For instance, the nationwide average processor mark-up is used to increase 

the landed price to the value the wholesaler would pay the processor. This procedure is repeated 

until the value paid by the consumer is estimated. Steinback (2004) has shown that this is 

mathematically equivalent to modeling the demand shock backwards.

Commercial fisheries sectors are not well described in the standard IMPLAN industry because of

the relative small size of the fishing industry and the lack of standardized cost and earnings data 
96

on fisheries sectors. As a result, most fishery economic impact analysis first relies on modifying 

existing economic impact models or creating new economic impact models. The model 

developed by Kirkley (2011) can be adapted for use across the fisheries wholesale sector 

backwards and is one of the models discussed below. 

In general, fishery impact models can be classified into three categories: coefficient models, 

spreadsheet models, or fully integrated models. The Fishery Economic Assessment Model 

(FEAM) is a coefficient model (Carter and Radtke 1986). The NMFS national model is a 

spreadsheet model (Kirkley 2011) and the Northeast Fisheries Science Center (NEFSC) model is 

a fully integrated model (Woods Hole Oceanographic Institute 2000). 

The FEAM is based on IMPLAN and was developed for the West Coast Fisheries Development 

Foundation (Carter and Radtke 1986). FEAM was constructed to estimate regional impacts of 

fishery management changes by combining IMPLAN data with landings and other industry data 

focusing specifically on income impacts (Research Group 2000). As mentioned above, IMPLAN 

lacks detail on commercial fishing and processing sectors. FEAM addresses this shortcoming by 

constructing expenditure coefficients for these sectors. The model apportions fishery 

expenditures to existing IMPLAN sectors, such as fuel, labor, and other supplies. 

Landings data drives the FEAM, and the model uses the Pacific Coast Fisheries Information 

Network standardized landings databases that include information on landing port, fleet 

characteristics, and onshore businesses. FEAM has a graphical user interface and the user can 

use menu selection to conduct analyses. These menus allow for some customization by changing 

model assumptions. 

The model then estimates personal income associated with the volume and value of landings (or

predicted change in landings). Because of its structure, FEAM calculates income estimates by 

geographic location. IMPLAN is organized around counties as a geographic delimiter, so FEAM 

impacts are also associated with the county of landing based on the location of the port of 

landing. 

This, however, leads to one of the major criticisms of FEAM. The model does not track the flow 

of income in and out of counties, and assumes all activities accrue to the county. Therefore, 

FEAM may overestimate the impacts within the landing county and underestimate the impacts 

outside the landing county (Pacific Fishery Management Council 2004). Additionally, very little 

is known about how FEAM generates the commercial fishery-specific coefficients that interface 

with IMPLAN (Seung and Waters 2006). Regardless of these drawbacks, FEAM has been used 

numerous times for fishery economic impact estimation, mainly because of its ease of use and its 

linkage to readily available and standardized landings data (Leeworthy and Wiley 2000).

The NEFSC model is one of the most detailed disaggregated IMPLAN based models ever 

created for any sector. Instead of incorporating the commercial fisheries sector into coefficients 

as in FEAM, or building production functions that interface with IMPLAN multipliers as in the 

U.S. National Impact Model (USNM), the NEFSC model creates a series of additional sectors by 

region within the existing IMPLAN data, and thereby retains the full functionality of IMPLAN.
97

At the time of the NEFSC model’s creation, base IMPLAN contained 528 sectors (Woods Hole 

Oceanographic Institute 2000). The NEFSC model included an additional 24 sectors across 11 

coastal sub-regions, bringing the total sector count to 793 sectors (Woods Hole Oceanographic 

Institute 2000). In each region, 17 gear type-based seafood harvesting, dealer, processing, water 

transportation, shipbuilding and repair, and warehousing sectors were defined. The harvesting 

sectors were created using detailed industry cost and earnings surveys. The other sectors were 

constructed using survey data, published data, and informal industry interviews. These sectors 

were created in the IMPLAN format and the base IMPLAN data tables were edited to include 

these additional sectors. The model can be created within IMPLAN and the multipliers generated 

using the full functionality of IMPLAN.

The biggest strength of building these sorts of models is that the model retains all the 

functionality of IMPLAN, including the ability to trace all the inter-sector relationships. No other 

method described here allows this level of impact result disaggregation. However, this level of 

detail comes at a great cost in terms of data needs and model construction time. Creating such a 

model is beyond the scope of this project, and indeed, is usually beyond the scope of any 

economic impact project. 

The review of I/O models shows that modifying IMPLAN and/or relying on base IMPLAN data 

and multipliers is the most flexible, most adaptable method, and the method best suited for this 

project. Within those approaches, adding new sectors to the base IMPLAN data is the best 

method retaining all the IMPLAN functionality, but is cost prohibitive and requires data that 

simply does not exist in the Gulf. Instead, spreadsheet models require less data and can be 

constructed more quickly. Though built external to IMPLAN, they are constructed using 

IMPLAN data and retain the ability to examine the impacts in the supply chain across the entities 

of concern to this project. However, they do not allow the disaggregation of those impacts to the 

ancillary industries. 

In addition, BOEM already uses spreadsheet-type impact models like the U.S. National Model.

MAG-PLAN is a large, multi-region model that calculates the economic impact of oil and gas 

exploration, drilling and production operations in the Gulf. Its construction is very similar to the 

U.S. National Model. One benefit of these types of models is their scalability. New sectors can 

be added easily. As product flow data improves or changes, the model can be quickly modified 

to take advantage of the new or better information.

4.2 I/O Model Development 

Traditional I/O modeling relies on input of final demand that then trickles through the supply 

chain back to the product’s origin. Typically, economic impact models begin an impact analysis 

by introducing a shock to a final demand sector. In the case of seafood, it would be ideal to 

present the change in consumer demand that resulted from the spill, but that information is 

impossible to obtain. Steinback (2004) showed that a backward linked model that begins with a 

shock to the harvesting sector produces the same results as starting with a final demand shock. 

Backward linked models start with landings and “push” those landings through each link of the 

supply chain. In fisheries, because almost no data exists on final demand or, more importantly in 

this case, final demand impacts resulting from the oil spill, the analysis must start with changes 
98

in the value of landings. For each link in the chain backward, only the value added, or margin, 

for that sector is included in the flow. Additionally, only the portion of the value added that 

accrues within the region is included.

In summary, the economic impact model will be a backward-linked model, which means impacts 

are calculated with losses from the harvest sector. This section details the multiplier construction, 

trade flows, and margins for this model. The harvesting sector and distribution sector multipliers 

will be obtained from the U.S. National Impact Model. Figure 51 shows the general structure of 

the impact model used for this project. The six sectors include: (1) Harvesters, (2) Dealers, (3) 

Processors, (4) Distributors, (5) Markets, and (6) Restaurants. Figure 51 shows the directional 

flow of seafood products and indicates where the multipliers for each link in the supply chain are 

sourced or constructed. Harvester and Distribution multipliers are obtained from the U.S. 

National Model (Kirkley 2011). Market and Restaurant multipliers are obtained from the 

IMPLAN model. The multipliers for the dealer, processor, market, and restaurant sectors will be 

obtained from the data contained in the 2012 IMPLAN model, but modified with data collected 

by the Gulf States Marine Fisheries Commission (Gulf Commission) data for the dealer and 

processor sectors. IMPLAN contains only a single processing sector. This processing sector will 

be heavily modified to create two new sectors: one for the dealer function and one for the 

processing function. The links in this chain are tied together using product flow and margin data 

from those same reports (Miller 2014a; Miller 2014b). Not shown in Figure 51 are exports; 

however, the model includes the leakages in the supply chain due to exports, and exports leave 

the supply chain at each sector downstream of the consumer. The trade component of the model 

is detailed below and referenced in the “Trade Flows” in Figure 51.
99

Figure 51. General Schematic of I/O Model Components, Product 

Flows, and Data Sources

4.2.1 U.S. National Impact Model

USNM was developed in response to a lack of basic data on fishery supply chain sectors in the 

basic input output accounts for the country maintained by the Department of Commerce. 

Because of this basic lack of data, NMFS developed a backward-linked model of the U.S.

seafood supply chain by species group/gear type harvesting sectors. This model disaggregated

harvesting into ten species groupings based on gear type, similar production technologies, and 

similar cost structures across these groupings (see Table 10 below). 

That lack of data regarding fishery supply chain sectors exists today, although is it slightly better. 

IMPLAN now contains seafood harvesting and seafood processing sectors, but the cost and 

earnings data used to construct the gear type/species production functions from the NMFS model 

are superior, because they were created by those with more knowledge of seafood value chains.
100

(IMPLAN was originally created for land-based applications.) For this project, the shrimp sector, 

reef fish sector, crab, reef fish, and menhaden gear type/species production functions were based 

on cost and earnings data collected directly from those harvesters (Kirkley 2011). 

The USNM is a true spreadsheet model; it was created in Microsoft© Excel©. The majority of 

the models examined for this study are of this type. This report will not discuss each model 

examined, because the USNM is the best example of the type. Additionally, the USNM is the 

best-documented model of this type. The USNM also provides the basic structure and much of 

the data used in the creation of the model used for this project.

The USNM contains a series of six linked worksheets, and general model operation is 

diagrammed in Figure 52. The model contains macros that download current NMFS online 

landings data and allocate the landed value into species/gear type sectors. The model then uses a 

backward linking or margining process to allocate demand to processor/dealer, wholesaler, and 

retail sectors. The model then outputs total sales, value-added, income and employment by 

harvesting, processing, wholesaling and retailing sectors. The retail sector is divided into grocery 

stores and restaurants. 

Figure 52. Overview of National I/O Model (Kirkley 2011)

The model creates 18 gear-based sectors; shrimp, crab, lobster, East Coast groundfish, highly 

migratory species, reef fish, West Coast groundfish, halibut, menhaden/industrial, salmon, sea 

scallop, surf clam/ocean quahog, other trawl, all other finfish, all other shellfish, freshwater, 

inshore and miscellaneous and bait. Those sectors include the following gears: butterfly nets, 

dredges and scrapes, gill and trammel nets, hoes, tongs, picks, rakes and hooks, hand lines, 

longlines and trolling, pots and traps, pound, fyke, hoop nets, haul or purse seines, trawls, and 

miscellaneous not-otherwise-specified gears. Cost and earnings data from NMFS surveys, 

published sources, and key informant interviews were used to build spreadsheet-based 
101

“production functions” for each of these gear types. These production functions are a linear 

spending of landed revenue into IMPLAN sectors. 

Summarized from Kirkley (2011), NMFS provides landings data and these species were 

aggregated to increase modeling tractability. The landings scenarios analyzed here were first 

grouped into similar groupings for the same reasons. The USNM is designed to take these 

aggregated landings and estimate the economic impacts from the harvester to the consumer. 

Landed revenue is allocated to these gear types by species group aggregations listed in Table 10. 

Landings from NMFS are first aggregated into these groups. Then the landed value (revenue) in 

each of these 18 groups is allocated across the ten gear type production functions pertinent to 

Gulf species aggregated for this analysis. The species/gear groupings were designed to reflect a 

general understanding of fish and seafood products. In some cases, a given species (e.g., shrimp) 

is sufficiently important to warrant its own category, particularly in the Gulf. On the other hand, 

many species are either byproducts in another species’ production process, or belong to a fishery 

that is so small that cost and earning data will likely never be collected. In those cases, those 

species have been included in the “all other finfish” category. Because the NMFS landings data 

report gear used to harvest fish and there are many gear types used, a similar aggregating 

strategy was used to condense gear types, and then species groups were combined with gear 

types used most frequently to target those species.

For this spreadsheet model, the harvester multipliers by species/gear type were taken directly 

from the USNM. The multipliers for the seafood distribution sector were also taken from the 

USNM. There is no seafood distribution sector in IMPLAN, so Kirkley (2011) aggregated 

several IMPLAN distribution sectors.

Table 10. Species Groups and Gear Types

Species group Major species in group

Shrimp All shrimp

Crab All crab except blue crab

Lobster American lobster

East Coast Groundfish Cod, flounder, goosefish, haddock, hake, plaice, pollock, 

shark (dogfish)

HMS Shark (other than dogfish), swordfish, tuna

Reef Fish Gag, grouper, mackerel (king & Spanish), snapper, tilefish

West Coast Groundfish Cod, hake, pollock, rockfish, sablefish, sole, whiting

Halibut All halibut

Menhaden/Industrial Alewife, ladyfish, menhaden

Salmon All salmon

Sea Scallop All scallop

Surf Clam/Ocean Quahog Surf clam, ocean quahog, quahog

Other Trawl Anchovies, croaker, herring, mackerel (other than king & 

Spanish), mullet, sardine, shad, squid

All Other Finfish Amberjack, drum, hind, pompano, porgy, scad, sea bass, 

tautog
102

All Other Shellfish Clam, spiny lobster, mussel, oyster, sea urchin, snail (conch)

Freshwater Catfish, crawfish, perch, tilapia, trout

Inshore and Miscellaneous Bass, blue crab, seaweed, sponge

Bait Worms, bait fish

Source: (Kirkley 2011)

From the harvester forward, industry margins, also called mark-ups or value added, are applied 

to the revenues entering in the previous link in the supply chain. The marked up value is then 

applied to the appropriate IMPLAN sector. For instance, a dealer/processor buys product from a 

harvester. That dealer/processor adds value to that product at an estimated 65%. That is, if the 

dealer/processor purchased that fish for $1, she sells it to the next link in the supply chain for 

$1.65. It is only the value added, or $0.65, that is then applied to the dealer/processor sector in 

IMPLAN. The original $1 is applied to the harvesting sector described above. This process 

continues until that $1 of seafood has been carried through the supply chain all the way to the 

consumer. The total impact is therefore the sum of the impacts across all of these seafood supply 

chain sectors. As long as only the margined amounts, or value added amounts, are used in the 

analysis, no double counting occurs. 

After exhausting all harvester cost data, production functions could not be constructed for all 

gear types in the USNM (Kirkley 2011). In addition, as much as 33% of reported landings do not 

list a gear type, and 6% list “combined, unspecified” in 2001. To handle the unallocated landings 

within the USNM, the model distributes these unspecified landings using the proportions of the 

total across all other gear types from the specified gears. 

Finally, the USNM did not construct Gulf regional multipliers for either the harvester sectors or 

the wholesale sector. The USNM constructed state level and U.S. level multipliers. Because this 

project requires a Gulf regional multiplier, the U.S.-level multipliers were used as proxies for 

Gulf regional multipliers. It is likely that this substitution overstates the actual impact for the 

harvesting and distribution sectors at the Gulf region level. However, it is likely the 

overstatement is slight, considering the data from the Gulf Commission reports detailed below 

(Miller et al. 2014a and 2014b). Those reports indicate that majority of the seafood that is not 

exported out of the U.S. stays within the region for dealing and processing. Because the Gulf 

region has a well-developed fisheries equipment supply industry, it is likely that leakages out of 

the Gulf region in the indirect phase are small. Both of these facts indicate that the difference 

between a Gulf region multiplier would not be very much smaller than the U.S. Region 

multipliers used for both the harvester and distribution sectors. 

The model has the limitations listed above, but these limitations have very little impact on the 

use of this model for Gulf fisheries for several reasons. First, gear type will be specified for all 

landings and so the proration of unspecified gears will not be necessary. Second, only butterfly 

nets and hand oyster gear, gears proxied in the model, are used in the Gulf. Both of these gears 

are used on a very limited basis. Third, the cost and earnings data and the product flow data for 

shrimp in this model come from Gulf studies. 
103

4.2.2 IMPLAN Modeling: Dealer, Processor and Retail Multipliers

IMPLAN is a commercially-available software tool that takes government labor and business 

transaction data and creates a series of national input/output structural matrices. The software is a 

user-friendly interface to these structural matrices that allows the analysis of regional economic 

impacts by state, and those underlying data matrices are updated annually, usually lagging two 

years behind the current year. This project will use 2012 IMPLAN data because it was the most 

recent data available when this project began. This software is widely accepted as the industry 

standard for regional economic impact modeling and is widely used in the private sector and 

across many government agencies. 

IMPLAN is a software tool that takes their proprietary input-output tables and allows the user to 

edit those tables, define the analysis region and construct multipliers based on those changes. For 

this analysis, an IMPLAN model was created for each state and for the Gulf region as a whole. 

IMPLAN has also added the flexibility to heavily edit nearly all the data within their model 

including creating new sectors. Since the USNM was created, IMPLAN has added a seafood 

processing sector to the sectoring scheme used. As a result, this model uses the 2012 IMPLAN 

seafood processing sector as the template for both dealers and seafood processing sectors using 

the Gulf Commission reports (Alexander et al. 2014a, 2014b). 

Though the harvesting sectors were created by state and species, the other sectors in the supply 

chain are disaggregated only by state. That is, each state model contains ten harvester sectors by 

species that interface with a single dealer, processor, wholesale and retail sector. The 

Commission survey did not achieve a high enough response rate to disaggregate the dealer, 

processor, wholesale, and retail sectors by species. This is assumed to have very little impact on 

the multipliers produced in the model as, typically, the farther up the supply chain from the 

harvester one goes, the less species-specific their production process. For instance, shrimp-only 

processing facilities exist, but there are no shrimp-only restaurants or shrimp-only seafood

counters in the grocery store. Even if there were a shrimp-only restaurant, it is unlikely that its 

cost structure would be any different than any other restaurant with similar costs for the main 

dish. However, a shrimp processing plant is likely to have different cost structures and 

potentially different multipliers than a processor that handled all seafood products. It is assumed 

that the impact of having a single processing sector in each state and for each species is small. 

4.3 Construction of Overall Impact Model Structure 

This section details how the completed multipliers for each species harvesting sector are 

assembled after creating the other sector multipliers using trade flows and margins to create the 

total model of the Gulf seafood supply chain. This section will address the pitfalls and 

assumptions found in putting together these types of complex impact models. Sections below 

detail avoiding double counting, creating the remaining supply chain sector multipliers, 

developing trade flows, developing sector margins and detailing the assumptions necessary to 

use this modeling framework. 
104

4.3.1 Avoiding Double Counting

To correctly estimate a backward linked model, the multipliers must be modified for each link in 

the chain to prevent purchases from the previous link in the chain in order to prevent double 

counting. For instance, to create the dealer multiplier, the harvesting sector must be shut off 

because the harvesting impacts have already been accounted for in the harvesting multiplier. 

Again, for the processor, both the dealer sector and the harvesting sector would need to be shut 

off when creating the processor multiplier to avoid double counting for those fish that moved 

from the harvester to the dealer to the processor. To avoid double counting, the regional purchase 

coefficient for each sector already accounted for is set to zero. The model for each state and the 

region is re-inverted and the multipliers are re-created. This creates a complicated matrix of 

multipliers, because this model allows product to skip various links in the chain, as reported in 

the product flow data from the Gulf Commission reports.

4.3.2 Creating Dealer, Processor, Distributor and Retail Sectors

The market and restaurant multipliers were created first. To create the restaurant multipliers, any 

seafood purchasing was turned off in the base model, as described above, and the multipliers 

reconstructed. This process was repeated for dealers and processors. The multipliers for each 

state and the entire Gulf across the three impact types (direct, indirect and induced) and the four 

impact metrics (total sales, value added, income and employment) were exported to the 

multiplier database created above for harvesters and distributors. 

Next, the processing and dealer sectors were created by modifying the IMPLAN processing 

sector using the Gulf Commission reports for each sector. IMPLAN uses sector “production 

functions” to represent the spending pattern for each sector. These production functions are the 

heart of economic impact modeling. They are not production functions in the traditional 

econometric sense, but are a proportional representation of spending patterns for that sector. That 

is, an IMPLAN production function describes what a sector is required to purchase from all other 

sectors to produce $1 worth of total sales. The data from the Gulf Commission reports on input 

purchasing behavior was converted from average dollars spent to percent of total expenditures as 

in Kirkley (2011), because the IMPLAN production functions are built in percentage form. Once 

these percentage production functions were created for each state and the entire region, the 

IMPLAN processing sector’s production function was modified to account for the more accurate 

data. 

The most striking finding in comparing the base IMPLAN data to the Commission data is that 

the Commission report found that processors and dealers spent a higher percentage of their input 

expenditures on purchasing seafood inputs than the IMPLAN data indicated. Because the 

Regional Purchase Coefficients for harvesters were zeroed to avoid double counting, this had the 

effect of pulling those multipliers down from the IMPLAN estimates in the model. 

After the production functions had been modified, employment information, also supplied in the 

Commission reports, was also modified in IMPLAN. Using total output for each sector and total 

employment in each state, output value per worker was modified to reflect the Commission data.

Output value per worker is a major driver of employment and induced impact multipliers. The 

total number of employees was also modified in IMPLAN based on the data in the Commission 
105

reports. Once these two modifications to production functions and employment were made, the 

multipliers were re-created for each state and the region as a whole.

Though the Commission data was not reported at the state level, updating the production 

functions for each state in IMPLAN based on Gulf-wide production functions generates different 

multipliers in each state, because each state has a different industry structure and because the 

output per worker and total employees was different for each state. The Commission reports did 

not report balance sheets at the state level due to low sample sizes and potential confidentiality 

issues. 

The same process was used to construct the dealer sector using the IMPLAN processing sector.

Using the processing sector as a proxy for the dealer sector was necessary because the 

commission reports did not contain enough data to construct a completely new sector and the 

dealer and processing sectors are typically quite similar, with some dealers acting as 

dealer/processors. The Kirkley (2011) model used only one sector, a combined dealer/processor 

sector. 

Again, after these modifications were made to each sector and in each state, the matrices were reinverted, re-creating the model and social accounting matrices, and the multipliers were then recreated. This was done for each state and the region as a whole. The multipliers, three for each 

impact type and four for each impact metric, were exported and added to the matrix of 

multipliers referred to above. 

4.3.3 Product Flows

After the multipliers have been created, trade flows are used to direct the flow of seafood to each 

link in the chain as shown in Figure 51. The trade flows are used as a road map to direct the 

margined values from the previous sector into the next sector in the chain. The Commission 

reports were very helpful: they illustrate the complex patterns seafood takes from the harvester to 

the consumer. All Dealer and Processor trade flows come from the Commission report, and the 

harvester and wholesale trade flows were sourced from the USNM. The model constructed for 

this study takes full advantage of that information, allowing for a complicated flow that skips 

certain links in the chain at certain times. All direct-to-public sales are applied to the markets 

multiplier using the markets margin. This assumes that the harvester, dealer, processor, or 

wholesaler that sells directly to the public has a similar cost structure as the market sector in

IMPLAN. The impact of this assumption is unknown; however, it is likely very small. 

USNM product flows were averaged at the U.S. level and used for harvester and wholesale 

sectors, because this information was not available from the Commission reports. The flows for 

the processor and dealer sectors were taken from the Commission reports. The flows were not 

published at the state level due to small sample sizes and potential issues with confidentiality in 

the Commission reports. Across all states, the Gulf region average trade flows were used for 

processors and dealers. In all cases it was assumed that “Other” in the Commission report was a 

direct to consumer sale. This likely biased the multipliers upwards, because some of this “Other” 

category was probably business or family gifts or barter in the community generating no 

additional economic activity. Figure 53 displays who the harvester sells to and by what 
106

percentage of the landed seafood. It was assumed, as in the USNM, that 100% of harvester to 

dealer transactions stays in the state of harvest. The USNM did not separate the dealer and 

processor sectors, as this model has done. As a result, the flow of seafood going to the 

dealer/processor sector in the USNM was assumed to be divided equally between the two 

separated dealer and processing sectors in this model. This model used the harvester trade flows 

in the USNM for the Gulf region, where 90% of all landed seafood is assumed sold to a 

dealer/processor, with 45% being a dealer sector and 45% flowing to the processing sector. Only 

5% goes directly to wholesale, only 2.5% is sold directly to restaurants, and 2.5% is sold directly 

to markets.

Source: (Kirkley 2011)

Figure 53. Harvester Sales to These Sectors by Percent 

of Value

Figure 54 details the sectors the dealer sells to and the percentage of sales going to each sector. 

In the Gulf, 40.9% of seafood by value is sold directly to the wholesale sector and 37.1% is sold 

to processors. Of the approximately 20% remaining, 10.7% is sold to markets, 5.3% directly to 

restaurants, and 4.2% to consumers. Figure 55 details the flow of the seafood products from the 

dealer regionally. The majority, 58.7%, of the seafood leaving the dealers stays in the state where 

it was landed, 22.8% leaves the state but stays in the Gulf region, and 18.5% leaves the Gulf 

region entirely and is considered a “leakage” from the model (i.e., no further economic activity is 

included in the model calculations).

90.0%

5.0%

2.5% 2.5%

Dealer/Processor

Wholesale

Market

Restaurant
107

Source: (Kirkley 2011)

Figure 54. Dealer Sales to These Sectors by Percent of 

Value

Source: (Kirkley 2011)

Figure 55. Destination of Seafood When it Leaves 

Dealer

The next link in the supply chain, processing, is detailed in Figure 56. The majority, 60.3%, of 

processed product flows into the wholesale sector, as one would expect. The next largest amount, 

21.5%, flows to the market sector and 10.7% flows to the restaurant sector. Only 0.4% and 0.2% 

flow directly to the consumer and other, respectively. Figure 57 details where, regionally, 

37.1%

40.9%

10.7%

5.3%

4.2%

0.1%

Processor

Wholesale

Market

Restaurant

Public

Other

22.8% 58.7%

18.5%

In State

In Gulf

Out of Gulf
108

processed product goes: 36.4% stays in the state it was landed, an additional 24.0% stays in the 

Gulf region, and 38.8% leaves the Gulf region. 

Source: (Kirkley 2011)

Figure 56. Processor Sales to These Sectors by Percent 

of Value

Source: (Kirkley 2011)

Figure 57. Destination of Seafood When it Leaves 

Processor

Figure 58 shows that 60% of the product entering the distribution sector passes to markets, 30% 

goes to the restaurant sector, 2% goes directly to the public, and 8% goes to export. These figures 

are taken from the USNM and are fixed for every state in the U.S. Figure 59 details the trade 

flows within the region from wholesale to the two retail sectors. Wholesale trade flow was taken 

from the USNM. Because that model did not construct a Gulf subregion, as discussed above, it is 

unknown how much product stays within the Gulf region during wholesale distribution. Figure 

60.3%

21.5%

10.7%

0.4% 0.2%

Wholesale

Market

Restaurant

Public

Other

36.4%

24.0%

38.8% In State

In Gulf
109

59 indicates that 43.8% of 60% of seafood product entering the distribution sector goes to 

markets in the state where that seafood was caught. Figure 59 also indicates that 45.2% of the 

30% of the seafood entering the distribution sector passes through to the restaurant sector in the 

state where the seafood was caught. For the purposes of this model, it is assumed that 100% of 

the portion that stays in the U.S. also stays in the Gulf region. This assumption will produce a 

multiplier for these sectors that is larger than the true multiplier if any of that seafood is sold 

outside the Gulf region. 

Source: (Kirkley 2011)

Figure 58. Wholesale Sales to These Sectors by Percent 

of Value

Source: (Kirkley 2011)

Figure 59. Destination of Seafood When It Leaves Wholesale

4.3.4 Margins

Margins are the next link in the creation of the model. For a backward-linked model, only the 

margin is passed forward to the next link in the chain. The margin is the amount of value added 

60.0%

30.0%

2.0%

8.0%

Market

Restaurant

Public

Export

0.00% 20.00% 40.00% 60.00% 80.00% 100.00%

Markets

Restaurants

51.4%

50.8%

43.8%

45.2%

4.7%

4.1%

US

In state

Export
110

to the product in the current link in the supply chain. It is often called mark-up at the retail level. 

Margin information can be very difficult to obtain quantitatively, because businesses view their 

margins as proprietary. In this effort, the margins for the distribution, restaurant, and market 

participants are taken from the USNM. Margins for the dealer and processor sectors come from 

the Gulf Commission reports and are averaged across the Gulf region. Table 11 contains the 

margins used for this model. Blanks in the table means the data is not included in that particular 

source.

Table 11. Supply Chain Margins by Value Chain Sector and Source

Sector

Markup 

Commission 

Report

U.S.

National 

Model

Dealer 16.4% 128.9%

Processor 27.7%

Distribution 62.7%

Restaurant 182.4%

Markets 33.4%

Because of globalization, increases in imports, and increasing prices for high-quality domestic 

seafood, it is widely held that margins in the retail sectors have been trending downward 

(Kirkley 2011). It is likely that the margins in the USNM overstate current industry margins, 

which have the effect of increasing the impacts from this model over what they would be with 

more up to date margins. This difference can be seen in Table 11. The dealer margin from the 

Gulf Commission is nearly eight times smaller than the dealer/processor margin from the 

USNM. Even if the margins for the dealers and processors from the Commission Reports are 

combined, they are still nearly three times lower than the USNM margins. 

4.3.5 General Model Assumptions

Beyond the assumptions listed above in each individual section, there are some general 

assumptions for all I/O models that also apply. All I/O models are linear representations of 

complex systems. Therefore, many simplifications and generalizations were made to construct 

this model. Additionally, all I/O models are static. They are created using data from a period in 

time that do not allow prices to change or production functions to adjust to change in product 

volume or product price. 

All I/O models assume constant returns to scale. That is, the same quantity of inputs is needed 

for each unit of output. This holds for all productions levels. All I/O models assume there are no 

supply constraints. That is, there are limitless raw materials, and there is no demand change large 

enough to consume all the supply of any input. This is less of a concern for examining reductions 

in supply, as were examined here.

All I/O models assume that supply and demand are fixed. Because supply and demand changes 

may precipitate changes in an industry’s cost structure and product flows, I/O models based on 

static data cannot capture these changes. A sector’s production function is a weighted average of 
111

the inputs required for the production of the primary product and all of the sector’s by-products. 

This is a common limitation of I/O modeling, and has little impact if supply and demand are not 

changing. However, this spill and the subsequent closures and marketing campaigns likely had 

some impact. This assumption means that no industry in the supply chain will adjust their 

production technology. That is, for example, dealers and processors may have changed the types 

of things they produced based on changes in availability of inputs post-spill or changes in prices 

of inputs post-spill.

Similarly, I/O models are not dynamic from a price standpoint. This is part of the reason two 

scenarios are presented in the results in the next chapter. The first scenario looks at what 

happened a year on, and the second scenario tries to hold price effects constant. Reductions in 

supply drive prices upward. Exogenous shocks, like those in the import shrimp market discussed 

previously, can also drive domestic prices up. Seafood safety concerns likely decreased demand, 

pushing prices downward. Seafood marketing campaigns likely partially offset (to an unknown 

degree) seafood safety concerns, having a positive price effect. I/O models cannot capture these 

effects internally, and this effort focuses on using scenarios that help illustrate the impact of the 

dynamism of prices. 

4.4 Derivation of Input Data

The periods used in the Settlement Agreement (2012) were reviewed to determine the baseline 

periods for this study. The scenarios presented below were developed in line with the three 

baseline periods: 2009; the average of 2008 and 2009; and the average of 2007, 2008, and 2009. 

The use of these baseline time periods is discussed in Section 3.10 of this report relative to the 

Seafood Compensation Program. 

Based on the examination of the baseline periods compared to 2010, we determined that the 2009 

period appeared to be the most representative period for this study. Using 2009 as the baseline 

year allows for comparison to the closest time period and enables basic calculations of the two 

scenarios that have been chosen. For this research, the established baseline periods were further 

developed by creating two scenarios using 2009 as the baseline, one based on the change in 

dockside revenue, Market Dynamic, and the other based on the change in dockside revenue but 

holding price constant at 2009 levels, Market Constant. This second scenario was developed to 

capture the change in landings with the intent to rule out all other market changes, all other 

things being held the same. 

Table 12 presents the harvester revenue changes relative to the 2010 period across the scenarios 

considered for this study. It is apparent that the least negative harvester revenue scenario is the 

Market Dynamic scenario, with a $7.5 million dollar loss, and the Market Constant scenario is 

the largest, with a $141.1 million dollar loss. These two scenarios best represent a low estimate 

and high estimate of the dockside revenue impacts, and so were used in the model as input data 

to simulate impacts down the supply chain.
112

Table 12. Change in Dockside Revenue of Baseline Options

Species

Market 

Constant 

(2009)

Market 

Dynamic 

(2009)

2008–2009 

Average

2007–2009 

Average

Shrimp -$79,875,900 $15,622,579 -$10,868,692 -$16,075,751

Blue crab -$8,774,918 -$2,408,376 -$943,814 -$1,741,477

Oysters -$21,855,409 -$18,909,982 -$14,624,461 -$11,071,846

Menhaden -$18,006,707 -$10,654,667 -$11,146,529 -$8,475,872

Reef fish -$5,901,930 -$4,131,149 -$3,798,319 -$2,764,298

Pelagic finfish -$5,562,246 -$6,502,469 -$5,573,132 -$4,809,847

Other 

crustaceans $1,150,730 $21,189,942 $20,300,920 $12,732,634

Bait -$758,340 -$325,910 -$427,051 -$130,682

Other shellfish $207,530 $62,652 $76,349 $41,135

Miscellaneous 

finfish -$1,696,938 -$1,395,770 -$2,570,569 -$2,299,290

Totals -$141,074,128 -$7,453,150 -$29,575,298 -$34,595,294

Source: NMFS Commercial Landings Statistics

4.4.1 Scenario 1: Market Dynamic: Change in Reported Dockside Value

The first scenario relied on the reference periods established in the lawsuit. The lawsuit 

established the period from May 2010 to December 2010 as the damage period. Earlier in the 

report, the three baseline periods were detailed, comparing the 2007–2009 average landings, 

2008–2009 average landings, and 2009 landings during the same months. It was found that the 

difference in landings was smallest when comparing May–December 2009 with May–December 

2010. This was chosen as the lower bound estimate of economic impacts.

This scenario (Table 13) examines what happened immediately following the spill. Note that 

negative values are decreases in revenue, and positive values are increases in revenue. This 

scenario takes into account, but does not control for, the dynamics that occurred across most 

fisheries due to both the short-term reduction in seafood supply and the price increases due to 

exogenous changes in imports. Several markets experienced price shifts due to global seafood 

market changes that are captured in this scenario. Overall, summing across all the cells in Table 

13, the Gulf experiences a loss of $7.5 million. Under this scenario, the largest loss was across 

Oysters in Louisiana ($21.5 million). The largest gain was shrimp in Texas ($37.7 million).
113

Table 13. Scenario 1: Market Dynamic Input Data 

Scenario 1 

Input Data Alabama

Florida 

(West 

Coast)

Louisiana Mississippi Texas

Species 

Group 

Total

Shrimp -$12,637 $3,967 -$9,477 -$3,918 $37,689 $15,623

Blue crab -$201 $2,277 -$5,472 -$91 $1,078 -$2,408

Oysters $0 -$7 -$21,545 -$2,724 $5,367 -$18,910

Menhaden -$30 $4 -$878 -$9,751 $0 -$10,655

Reef fish -$725 -$2,789 -$1,523 $0 $905 -$4,131

Pelagic finfish -$4 -$1,359 -$5,139 $0 $0 -$6,502

Other 

crustaceans $0 $24,380 -$3,139 $0 -$51 $21,190

Bait -$90 -$500 $187 $12 $65 -$326

Other shellfish -$48 $131 -$21 -$9 $9 $63

Miscellaneous 

finfish -$120 -$1,200 -$43 -$146 $112 -$1,396

State Total -$13,856 $24,904 -$47,050 -$16,626 $45,175 -$7,453

(Dollar Values are in Thousands of $US)

4.4.2 Scenario 2: Market Constant: Change in Reported Landings Valued at PreSpill Price

The second scenario attempts to examine the change in the industry holding prices constant and 

focusing simply on the reduction in landings. The scenario was constructed by taking the percent 

reduction by species in landed volume between the reference periods in 2009 and 2010 and 

applying that percent reduction to 2009 landed value. The percent reduction was calculated for 

each species group and was run through the model by species. This, in effect, holds prices 

constant and looks at the loss only in landings terms. As a result, this scenario represents an 

upper bound on the impact of the spill on local fishing communities, whereas the previous 

scenario examines the impact of what happened, including the impact that increased prices, both 

from the reduction in supply from the spill and from other exogenous market factors.

As can be seen in Table 14, under this scenario, the biggest loss was across shrimp in Louisiana 

($36.2 million). The largest gain was other crustaceans in West Florida ($4.8 million). In West 

Florida there were some large increases in revenue attributed to spiny lobster which appeared to 

have created this gain. Across this entire scenario, the loss to the Gulf seafood supply chain is 

$141.0 million.
114

Table 14. Scenario 2: Market Constant Input Data

Scenario 2 

Input Data Alabama

Florida 

(West 

Coast)

Louisiana Mississippi Texas

Species 

Group 

Total

Shrimp -$19,483 $2,332 -$36,159 -$6,983 -$19,583 -$79,876

Blue crab -$279 $2,697 -$11,964 -$98 $870 -$8,775

Oysters $0 -$779 -$22,397 -$2,814 $4,134 -$21,855

Menhaden -$27 -$8 -$8,517 -$9,455 $0 -$18,007

Reef fish -$719 -$4,440 -$1,512 $0 $769 -$5,902

Pelagic finfish -$4 -$416 -$5,142 $0 -$1 -$5,562

Other 

crustaceans $0 $4,779 -$3,577 $0 -$51 $1,151

Bait -$203 -$790 $181 $5 $49 -$758

Other shellfish -$60 $281 -$18 -$10 $14 $208

Miscellaneous 

finfish -$203 -$165 -$1,111 -$229 $11 -$1,697

State Total -$20,979 $3,491 -$90,216 -$19,583 -$13,789 -$141,076

(Dollar Values are in Thousands of $US)

It is difficult to compare the multipliers used in this analysis to those in USNM for a number of 

reasons. First, Fisheries Economics of the United States (FEUS) does not publish speciesspecific estimates in their impact estimates, and so only aggregate totals can be compared. As the 

size of the impacted region increases, more goods and services can be supplied within the region,

increasing the multipliers as more transactions take place in-region. As a result, the U.S. level 

multipliers will simply be higher. Looking at the latest FEUS, the aggregate multiplier for the 

U.S. across all sectors is roughly 9.9, whereas the Gulf region multiplier implied in Table 14

above is 6.8 (NMFS 2014). Because the harvester sectors are taken from the FEUS model, the 

difference lies in the other sectors, trade flows and margins. As shown above in Table 11, the 

dealer margin from the Gulf Commission reports (Miller et al. 2014b) is nearly eight times lower 

than the margin used in the FEUS model. Also, the Gulf Commission report shows more product 

skipping over sectors in the supply chain, at every link, and delivering the goods directly to the 

consumer. This acts to reduce the overall impact, but it does enhance impacts in lower links of 

the chain. Finally, the restaurant sector multipliers in FEUS represent about 67.7% of the total 

impact in the USNM supply chain, which is widely recognized as too high. Within this model the 

total impact attributable to the restaurant sector is 11.1% of the total impact across all sectors, 

which is in line with estimates for the restaurant sector in the economy.
115

Chapter Five: Model Results 

5.1 Overall model results by scenario

The total results by impact type are first reported for each scenario and then results are discussed 

by impact type (direct, indirect, and induced). Direct impacts describe the economic activity 

generated by the initial purchase of the good or service. Indirect impacts describe the activity 

generated as businesses purchase the goods and services necessary to provide the purchased 

seafood. Induced impacts describe the spending of incomes by employees and owners generated 

by the purchase of seafood. Results are also discussed by the measure of economic activity 

(sales, value added, income and employment) and sector (harvester, dealer, processor, 

distributer, market, and restaurant).

5.1.1 Scenario 1: Market Dynamic: Change in Reported Dockside Value

The lower bound estimates of the economic impact of the DWH oil spill to the Gulf seafood 

industry the impact of the spill are summarized in Table 15 by sector, impact measure and 

impact type. Overall, the entire seafood supply chain lost 740 jobs, $51.7 million in sales, $21.4

million in value added, and $21.6 million in income during the 8-month damage period. The 

harvesting sector was estimated to have experienced the largest losses, losing 449 jobs, $20.1

million in sales, $7.9 million in value added, and $11.9 million in income under this conservative 

scenario.
116

Table 15. Scenario 1 Results

Sector

Economic 

Activity 

Measure

Impact Type

Total

Direct Indirect Induced

Harvester

Sales -$5,063 $1,020 -$16,070 -$20,114

Value Added -$3,572 $1,113 -$5,473 -$7,932

Income -$8,049 -$2,256 -$1,553 -$11,858

Employment -335 4 -118 -449

Dealer

Sales -$3,557 -$249 -$454 -$4,261

Value Added -$477 -$131 -$279 -$887

Income -$417 -$82 -$153 -$652

Employment -21 -3 -3 -28

Processor

Sales -$4,877 -$737 -$734 -$6,348

Value Added -$654 -$398 -$451 -$1,503

Income -$572 -$234 -$247 -$1,053

Employment -29 -7 -6 -42

Distributor

Sales -$3,533 -$1,225 -$4,956 -$9,714

Value Added -$2,234 -$375 -$1,535 -$4,143

Income -$1,483 -$1,018 -$1,079 -$3,580

Employment -38 -7 -36 -82

Market

Sales -$3,178 -$861 -$1,591 -$5,630

Value Added -$2,275 -$551 -$1,012 -$3,838

Income -$1,659 -$295 -$549 -$2,503

Employment -55 -6 -13 -74

Restaurant

Sales -$2,877 -$1,135 -$1,650 -$5,662

Value Added -$1,661 -$618 -$816 -$3,095

Income -$1,117 -$343 -$448 -$1,908

Employment -49 -7 -10 -66

Total

Sales -$23,087 -$3,187 -$25,455 -$51,729

Value Added -$10,873 -$960 -$9,566 -$21,399

Income -$13,297 -$4,229 -$4,029 -$21,554

Employment -527 -26 -187 -740

(Dollar Values are in Thousands of $US, Employment is in Number of full time jobs)

Overall and across all sectors, the harvesting sector generates most of the change in economic 

activity. The harvesting sector’s value added loss highlights the confounding market responses 

after the spill. Typically, value added exceeds income, by definition. But because there were 

revenue increases across species groups with relatively low value added multipliers (supply 

chain multipliers for each state and the Gulf region are provided in the Appendix), and revenue 

declined for species with relatively high value added multipliers, value added losses for 

harvesters were lower than income for the harvesters when summed across all species.
117

5.1.2 Scenario 2: Market Constant: Change in Reported Landings Valued at PreSpill Price

As evidenced in Table 16, when focusing only on landings reductions and holding prices 

constant at 2009 levels (the higher bound estimates), the estimated economic losses are much 

larger. Overall, under this price-constant scenario, the spill cost Gulf communities $952.9 million 

in sales, $392.7 million in value added, $309.8 million in income, and 9,315 jobs. The majority 

of this impact is absorbed by the harvesters, who lost $354.5 million in sales, $137.8 million in 

value added, $126.3 million in income, and 3,809 jobs. Though USNM combines dealers and 

processers into one sector, they were split for this modeling exercise. Together, they would 

comprise the second most impacted group, with the dealers and processors losing $80.6 million 

and $120.1 million in sales, respectively, for a combined loss of $200.7 million in sales and 

1,325 jobs during the 8-month damage period. By separating those two sectors, distributors are 

the second hardest hit with a $183.8 million loss in sales.
118

Table 16. Scenario 2 Results 

Sector

Economic 

Activity 

Measure

Impact Type

Total

Direct Indirect Induced

Harvester

Sales -$128,258 -$74,110 -$152,144 -$354,512

Value Added -$69,985 -$24,023 -$43,774 -$137,782

Income -$59,860 -$24,552 -$41,857 -$126,268

Employment -2,338 -355 -1,116 -3,809

Dealer

Sales -$67,326 -$4,720 -$8,597 -$80,644

Value Added -$9,032 -$2,482 -$5,278 -$16,792

Income -$7,893 -$1,550 -$2,895 -$12,338

Employment -404 -56 -66 -527

Processor

Sales -$92,319 -$13,944 -$13,893 -$120,156

Value Added -$12,385 -$7,540 -$8,529 -$28,454

Income -$10,823 -$4,437 -$4,679 -$19,938

Employment -554 -137 -107 -798

Distributor

Sales -$66,882 -$23,178 -$93,814 -$183,874

Value Added -$42,277 -$7,097 -$29,047 -$78,421

Income -$28,073 -$19,271 -$20,422 -$67,766

Employment -715 -140 -688 -1,543

Market

Sales -$60,161 -$16,288 -$30,122 -$106,572

Value Added -$43,054 -$10,430 -$19,165 -$72,648

Income -$31,408 -$5,578 -$10,387 -$47,374

Employment -1,036 -116 -240 -1,391

Restaurant

Sales -$54,460 -$21,487 -$31,224 -$107,171

Value Added -$31,442 -$11,695 -$15,444 -$58,581

Income -$21,137 -$6,499 -$8,470 -$36,106

Employment -925 -128 -193 -1,246

Total

Sales -$469,406 -$153,728 -$329,794 -$952,929

Value Added -$208,174 -$63,267 -$121,236 -$392,678

Income -$159,193 -$61,888 -$88,709 -$309,791

Employment -5,972 -933 -2,411 -9,315

(Dollar Values are in Thousands of $US, Employment is in Number of full time jobs)

5.2 Shrimp

Changes in the shrimp markets throughout the post-spill Gulf are displayed in Table 17. In

Scenario 1, the Market Dynamic Scenario that allows prices to adjust, some states experienced 

large losses in response to activities occurring in the import market. For instance, sales dropped 

in Alabama ($62.6 million), Louisiana ($47.7 million), and Mississippi ($20.2 million). 

However, in areas less affected by the spill and spill closures, Texas and West Florida, total sales 

from shrimp harvests increased. Shrimp landings drove total sales in West Florida to increase
119

$21.7 million and total sales in Texas to increase $209.8 million under the Market Dynamic 

Scenario. Overall, then, the Gulf experienced a net increase in economic activity from shrimp 

harvests in the period immediately following the spill under the Market Dynamic Scenario. Gulfwide economic activity rose, supporting $105.2 million in total sales, $43.3 million in value 

added, $33.4 million in income and 990 jobs. 

Under Scenario 2, the Market Constant Scenario, Gulf-wide economic activity generated by 

shrimp declined. If prices are held constant at 2009 levels, total sales dropped $538.1 million, 

value added dropped $221.6 million, income dropped $171.0 million, and 5,062 jobs were lost 

Gulf-wide. This makes the shrimp market the loss leader under the Market Constant Scenario 

across all species modeled individually in this analysis. Under this scenario, all states but West 

Florida lost economic activity; Louisiana lost $181.8 million, Texas lost $109.0 million, 

Alabama lost $96.6 million, and Mississippi lost $36.0 million. West Florida increased $12.8 

million in total sales. 

Comparing these two results demonstrates that two things happened post spill. First, harvest 

effort shifted to areas less affected or not affected by the spill, as evidenced by West Florida, 

showing positive impacts under both scenarios, and Texas, showing more positive impacts under 

the Market Dynamic Scenario than negative impacts under the Market Constant Scenario. 

Second, the fact that Texas showed negative results under the Market Constant Scenario also 

demonstrates there was a significant price effect. That is, as post-spill shrimp volumes fell 

domestically and imports began to fall, the drop in supply pushed prices upward. Some of this 

price effect may also be due to aggressive post-spill marketing of Gulf shrimp.
120

Table 17. Shrimp Economic Model Results 

Shrimp Scenario 1 Scenario 2

State Sector Employment Total 

Sales

Value 

Added Income Employment Total Sales Value Added Income

AL Harvester -486 -$19,493 -$9,011 -$7,272 -749 -$30,051 -$13,893 -$11,211

AL Dealer -26 -$6,801 -$974 -$750 -41 -$10,485 -$1,501 -$1,156

AL Processor -45 -$10,046 -$1,721 -$1,230 -69 -$15,487 -$2,653 -$1,896

AL Distributor -100 -$10,171 -$6,071 -$5,020 -154 -$15,680 -$9,359 -$7,739

AL Market -125 -$8,363 -$5,642 -$3,656 -192 -$12,892 -$8,698 -$5,637

AL Restaurant -114 -$7,772 -$4,193 -$3,366 -176 -$11,981 -$6,464 -$5,189

AL Total -896 -$62,646 -$27,612 -$21,294 -1,381 -$96,576 -$42,568 -$32,828

W FL Harvester 109 $6,753 $3,447 $2,489 64 $3,970 $2,026 $1,463

W FL Dealer 15 $2,233 $301 $175 9 $1,313 $177 $103

W FL Processor 22 $3,368 $582 $335 13 $1,980 $342 $197

W FL Distributor 33 $3,409 $1,905 $1,692 20 $2,004 $1,120 $994

W FL Market 41 $3,187 $2,162 $1,423 24 $1,874 $1,271 $836

W FL Restaurant 34 $2,779 $1,672 $1,045 20 $1,634 $983 $614

W FL Total 254 $21,729 $10,069 $7,159 150 $12,775 $5,919 $4,207

LA Harvester -284 -$14,864 -$8,049 -$5,509 -1083 -$56,710 -$30,709 -$21,019

LA Dealer -39 -$5,436 -$1,376 -$1,000 -151 -$20,739 -$5,248 -$3,815

LA Processor -53 -$7,707 -$2,039 -$1,427 -201 -$29,404 -$7,779 -$5,445

LA Distributor -78 -$7,405 -$4,553 -$3,813 -296 -$28,251 -$17,369 -$14,548

LA Market -92 -$6,323 -$4,275 -$2,767 -352 -$24,123 -$16,309 -$10,557

LA Restaurant -83 -$5,928 -$3,355 -$2,148 -316 -$22,616 -$12,802 -$8,195

LA Total -629 -$47,663 -$23,647 -$16,664 -2,399 -$181,843 -$90,216 -$63,579

MS Harvester -96 -$6,839 -$3,025 -$2,197 -171 -$12,188 -$5,391 -$3,916

MS Dealer -15 -$2,148 -$350 -$262 -27 -$3,828 -$623 -$467

MS Processor -23 -$3,242 -$635 -$430 -41 -$5,777 -$1,132 -$766

MS Distributor -31 -$3,140 -$1,882 -$1,550 -56 -$5,595 -$3,354 -$2,762

MS Market -36 -$2,503 -$1,707 -$1,088 -65 -$4,461 -$3,042 -$1,939

MS Restaurant -35 -$2,325 -$1,260 -$785 -63 -$4,144 -$2,245 -$1,399

MS Total -236 -$20,197 -$8,859 -$6,312 -423 -$35,993 -$15,787 -$11,249
121

Shrimp Scenario 1 Scenario 2

State Sector Employment Total 

Sales

Value 

Added Income Employment Total Sales Value Added Income

TX Harvester 764 $69,903 $32,751 $24,683 -397 -$36,321 -$17,017 -$12,825

TX Dealer 126 $20,397 $3,578 $2,712 -66 -$10,598 -$1,859 -$1,409

TX Processor 193 $30,697 $6,542 $4,659 -101 -$15,950 -$3,399 -$2,421

TX Distributor 305 $33,232 $18,104 $15,852 -159 -$17,267 -$9,407 -$8,237

TX Market 367 $29,274 $19,977 $13,053 -191 -$15,210 -$10,380 -$6,782

TX Restaurant 323 $26,247 $15,301 $9,383 -168 -$13,638 -$7,950 -$4,875

TX Total 2,078 $209,750 $96,253 $70,342 -1,082 -$108,984 -$50,012 -$36,549

Gulf Harvester 380 $38,968 $15,121 $13,124 -1945 -$199,237 -$77,311 -$67,103

Gulf Dealer 58 $8,930 $1,860 $1,366 -298 -$45,660 -$9,507 -$6,986

Gulf Processor 88 $13,306 $3,151 $2,208 -452 -$68,032 -$16,111 -$11,289

Gulf Distributor 171 $20,362 $8,684 $7,504 -874 -$104,109 -$44,402 -$38,369

Gulf Market 154 $11,802 $8,045 $5,246 -788 -$60,341 -$41,133 -$26,823

Gulf Restaurant 138 $11,868 $6,487 $3,998 -706 -$60,680 -$33,168 -$20,443

Gulf Total 989 $105,236 $43,348 $33,446 -5,063 -$538,059 -$221,632 -$171,013

(Dollar Values are in Thousands of $US, Employment is in Number of full time jobs)
122

5.3 Blue Crab

Overall, blue crab is a much smaller industry than shrimp. Table 18 demonstrates the complex 

dynamics occurring in the blue crab market region-wide post spill. In Scenario 1, the Market 

Dynamic Scenario that allows prices to adjust, some states took large losses, even though prices 

were allowed to change in response to activities occurring in the import market. For instance, 

sales dropped in Alabama ($1.0 million), Louisiana ($28.4 million), and Mississippi ($465,000). 

However, in areas less affected by the spill and spill closures, Texas and West Florida, total sales 

from blue crab harvests increased. Blue crab landings drove total sales in West Florida to

increase $12.5 million and total sales in Texas to increase $5.9 million under the Market 

Dynamic Scenario. Overall, then, the Gulf experienced a net decrease in economic activity from 

blue crab harvests in the period immediately following the spill under the Market Dynamic 

Scenario. Gulf-wide economic activity fell, losing $16.3 million in total sales, $6.8 million in 

value added, $5.5 million in income, and 165 jobs. 

In Scenario 2, the Market Constant Scenario, Gulf-wide economic activity generated by blue 

crab is markedly down. If prices are held constant at 2009 levels, total sales dropped $59.5 

million, value added dropped $24.8 million, income dropped $19.9 million, and 602 jobs were

lost Gulf-wide. Under this scenario, all states but West Florida and Texas lost economic activity. 

Louisiana lost $62.1 million, Alabama lost $1.4 million, and Mississippi lost $505,000. West 

Florida gained $14.8 million in total sales, which is more than the Market Dynamic scenario, 

suggesting that West Florida volumes rose post-spill while prices fell. Texas gained $4.7 million, 

suggesting that volumes increased in Texas but prices were only up slightly. 
123

Table 18. Blue Crab Economic Model Results

Blue Crab Scenario 1 Scenario 2

State Sector Employment Total 

Sales

Value 

Added Income Employment Total Sales

Value 

Added Income

AL Harvester -4 -$348 -$140 -$133 -6 -$483 -$195 -$184

AL Dealer 0 -$108 -$15 -$12 -1 -$150 -$22 -$17

AL Processor -1 -$160 -$27 -$20 -1 -$222 -$38 -$27

AL Distributor -2 -$162 -$97 -$80 -2 -$225 -$134 -$111

AL Market -2 -$133 -$90 -$58 -3 -$185 -$125 -$81

AL Restaurant -2 -$124 -$67 -$54 -3 -$172 -$93 -$74

AL Total -11 -$1,035 -$436 -$357 -16 -$1,437 -$607 -$494

W FL Harvester 46 $3,939 $1,588 $1,504 54 $4,665 $1,881 $1,782

W FL Dealer 8 $1,282 $173 $100 10 $1,518 $205 $119

W FL Processor 13 $1,933 $334 $192 15 $2,290 $396 $228

W FL Distributor 19 $1,957 $1,094 $971 23 $2,318 $1,295 $1,150

W FL Market 24 $1,830 $1,241 $817 28 $2,167 $1,470 $967

W FL Restaurant 20 $1,596 $960 $600 23 $1,890 $1,137 $711

W FL Total 130 $12,537 $5,390 $4,184 153 $14,848 $6,384 $4,957

LA Harvester -110 -$9,466 -$3,816 -$3,615 -240 -$20,696 -$8,344 -$7,904

LA Dealer -23 -$3,138 -$794 -$577 -50 -$6,862 -$1,736 -$1,262

LA Processor -30 -$4,450 -$1,177 -$824 -66 -$9,729 -$2,574 -$1,802

LA Distributor -45 -$4,275 -$2,629 -$2,202 -98 -$9,348 -$5,747 -$4,814

LA Market -53 -$3,651 -$2,468 -$1,598 -116 -$7,982 -$5,396 -$3,493

LA Restaurant -48 -$3,423 -$1,937 -$1,240 -105 -$7,483 -$4,236 -$2,712

LA Total -309 -$28,403 -$12,821 -$10,056 -675 -$62,100 -$28,033 -$21,987

MS Harvester -2 -$157 -$63 -$60 -2 -$170 -$68 -$65

MS Dealer 0 -$50 -$8 -$6 0 -$54 -$9 -$7

MS Processor -1 -$75 -$15 -$10 -1 -$81 -$16 -$11

MS Distributor -1 -$73 -$43 -$36 -1 -$79 -$47 -$39

MS Market -1 -$58 -$39 -$25 -1 -$63 -$43 -$27

MS Restaurant -1 -$54 -$29 -$18 -1 -$58 -$32 -$20
124

Blue Crab Scenario 1 Scenario 2

State Sector Employment Total 

Sales

Value 

Added Income Employment Total Sales

Value 

Added Income

MS Total -6 -$467 -$197 -$155 -6 -$505 -$215 -$169

TX Harvester 22 $1,866 $752 $712 17 $1,504 $607 $575

TX Dealer 4 $584 $102 $78 3 $471 $83 $63

TX Processor 6 $878 $187 $133 4 $708 $151 $108

TX Distributor 9 $951 $518 $454 7 $767 $418 $366

TX Market 11 $838 $572 $373 8 $676 $461 $301

TX Restaurant 9 $751 $438 $268 7 $606 $353 $217

TX Total 61 $5,868 $2,569 $2,018 46 $4,732 $2,073 $1,630

Gulf Harvester -71 -$6,104 -$2,461 -$2,331 -258 -$22,240 -$8,966 -$8,493

Gulf Dealer -9 -$1,377 -$287 -$211 -33 -$5,016 -$1,044 -$767

Gulf Processor -14 -$2,051 -$486 -$340 -50 -$7,474 -$1,770 -$1,240

Gulf Distributor -26 -$3,139 -$1,339 -$1,157 -96 -$11,437 -$4,878 -$4,215

Gulf Market -24 -$1,819 -$1,240 -$809 -87 -$6,629 -$4,519 -$2,947

Gulf Restaurant -21 -$1,830 -$1,000 -$616 -78 -$6,666 -$3,644 -$2,246

Gulf Total -165 -$16,320 -$6,813 -$5,464 -602 -$59,462 -$24,821 -$19,908

(Dollar Values are in Thousands of $US, Employment is in Number of full time jobs)
125

5.4 Oysters

Table 19 demonstrates the complex dynamics occurring in the post-spill oyster market regionwide. Alabama does not harvest or process oysters, so it has been omitted. In Scenario 1, the 

Market Dynamic Scenario that allows prices to adjust, all states except Texas took large losses, 

even though prices were allowed to change in response to activities occurring in the import 

market. For instance, sales dropped in West Florida ($40,000), Louisiana ($111.5 million), and 

Mississippi ($14.0 million). 

However, in Texas, an area less affected by the spill and spill closures, and unaffected by the 

Mississippi River releases, total sales from oyster harvests increased. Oyster landings drove total 

sales to increase $29.1 million in Texas under the Market Dynamic Scenario. Overall, then, the 

Gulf experienced a net decrease in economic activity from oyster harvests in the period 

immediately following the spill under the Market Dynamic Scenario. Gulf-wide economic 

activity fell, losing $127.7 million in total sales, $52.9 million in value added, $42.9 million in 

income and 1,277 jobs. Across all the species comparisons, this is the largest Gulf-wide loss 

under the Market Dynamic Scenario.

In Scenario 2, the Market Constant Scenario, Gulf-wide economic activity generated by oyster 

harvests dropped, but by less than would be expected given the results across other species. If 

prices are held constant at 2009 levels, total sales dropped $147.6 million, value added dropped 

$61.1 million, income dropped $49.6 million, and 1,476 jobs were lost Gulf-wide. Under this 

scenario, all states but Texas lost economic activity. Louisiana lost $115.9 million, West Florida 

lost $4.3 million, and Mississippi lost $14.4 million. Texas gained $22.4 million in total sales. 

This suggests that Texas received much higher prices for oysters with slightly increased volumes 

harvested. Overall, it appears that prices increased very slightly in Mississippi and Louisiana 

post-spill, possibly driven by dramatically reduced harvests. In West Florida, however, it appears 

prices increased dramatically post-spill, nearly eliminating a $4.3 million dollar loss had prices 

remained constant at 2009 levels. 
126

Table 19. Oysters Economic Model Results 

Oysters Scenario 1 Scenario 2

State Sector Employment Total 

Sales

Value 

Added Income Employment Total Sales

Value 

Added Income

W FL Harvester 0 -$12 -$5 -$5 -15 -$1,336 -$527 -$515

W FL Dealer 0 -$4 -$1 $0 -3 -$439 -$59 -$34

W FL Processor 0 -$6 -$1 -$1 -4 -$662 -$114 -$66

W FL Distributor 0 -$6 -$3 -$3 -7 -$670 -$374 -$332

W FL Market 0 -$6 -$4 -$3 -8 -$626 -$425 -$280

W FL Restaurant 0 -$5 -$3 -$2 -7 -$546 -$329 -$205

W FL Total 0 -$39 -$17 -$14 -44 -$4,279 -$1,828 -$1,432

LA Harvester -419 -$36,940 -$14,558 -$14,233 -435 -$38,400 -$15,133 -$14,796

LA Dealer -90 -$12,357 -$3,127 -$2,273 -93 -$12,845 -$3,251 -$2,363

LA Processor -120 -$17,520 -$4,635 -$3,244 -124 -$18,213 -$4,818 -$3,373

LA Distributor -177 -$16,833 -$10,349 -$8,668 -184 -$17,499 -$10,759 -$9,011

LA Market -209 -$14,373 -$9,717 -$6,290 -218 -$14,941 -$10,101 -$6,539

LA Restaurant -188 -$13,476 -$7,628 -$4,883 -196 -$14,008 -$7,929 -$5,076

LA Total -1,203 -$111,499 -$50,014 -$39,591 -1,250 -$115,906 -$51,991 -$41,158

MS Harvester -53 -$4,671 -$1,841 -$1,800 -55 -$4,824 -$1,901 -$1,859

MS Dealer -11 -$1,493 -$243 -$182 -11 -$1,543 -$251 -$188

MS Processor -16 -$2,254 -$441 -$299 -17 -$2,328 -$456 -$309

MS Distributor -22 -$2,183 -$1,309 -$1,078 -23 -$2,255 -$1,352 -$1,113

MS Market -25 -$1,740 -$1,187 -$756 -26 -$1,798 -$1,226 -$781

MS Restaurant -25 -$1,617 -$876 -$546 -25 -$1,670 -$905 -$564

MS Total -152 -$13,958 -$5,897 -$4,661 -157 -$14,418 -$6,091 -$4,814

TX Harvester 104 $9,201 $3,626 $3,545 80 $7,088 $2,793 $2,731

TX Dealer 18 $2,904 $509 $386 14 $2,237 $392 $298

TX Processor 28 $4,371 $932 $663 21 $3,367 $718 $511

TX Distributor 43 $4,732 $2,578 $2,257 33 $3,645 $1,986 $1,739

TX Market 52 $4,168 $2,845 $1,859 40 $3,211 $2,191 $1,432

TX Restaurant 46 $3,737 $2,179 $1,336 35 $2,879 $1,678 $1,029
127

Oysters Scenario 1 Scenario 2

State Sector Employment Total 

Sales

Value 

Added Income Employment Total Sales

Value 

Added Income

TX Total 291 $29,113 $12,669 $10,046 223 $22,427 $9,758 $7,740

Gulf Harvester -538 -$47,502 -$18,720 -$18,303 -622 -$54,900 -$21,636 -$21,154

Gulf Dealer -71 -$10,810 -$2,251 -$1,654 -82 -$12,493 -$2,601 -$1,911

Gulf Processor -107 -$16,106 -$3,814 -$2,673 -124 -$18,615 -$4,408 -$3,089

Gulf Distributor -207 -$24,647 -$10,512 -$9,084 -239 -$28,486 -$12,149 -$10,498

Gulf Market -187 -$14,285 -$9,738 -$6,350 -216 -$16,510 -$11,255 -$7,339

Gulf Restaurant -167 -$14,366 -$7,852 -$4,840 -193 -$16,603 -$9,075 -$5,594

Gulf Total -1,277 -$127,716 -$52,887 -$42,904 -1,476 -$147,607 -$61,124 -$49,585

(Dollar Values are in Thousands of $US, Employment is in Number of full time jobs)
128

5.5 Menhaden

Because of the vertical integration of only two companies in the menhaden market, the dynamics 

are less complicated. Table 20 examines those dynamics region wide by state. In Scenario 1, the 

Market Dynamic Scenario that allows prices to adjust, all states except Florida and Texas took 

losses, even though prices were allowed to change. Sales dropped in Alabama ($156,000), 

Louisiana ($4.6 million), and Mississippi ($50.4 million). West Florida total sales increased 

$20,000. The majority of the directed harvest for this species occurs in Mississippi and 

Louisiana. Texas landed no menhaden across the periods examined.

In no state did sales from menhaden increase. Overall, the Gulf experienced a net loss in 

economic activity from menhaden harvests in the period immediately following the spill under 

the Market Dynamic Scenario. Gulf-wide economic activity fell losing $72.7 million in total 

sales, $29.7 million in value added, $24.2 million in income and 786 jobs. 

In Scenario 2, the Market Constant Scenario, Gulf-wide economic activity generated by 

menhaden was markedly down. With prices held constant at 2009 levels, total sales dropped 

$122.8 million, value added dropped $50.2 million, income dropped $40.9 million and 1,329

jobs were lost Gulf-wide. Under this scenario, all states lost economic activity; Louisiana lost

$44.5 million, West Florida lost $41,000, Alabama lost $140,000, and Mississippi lost $48.9

million. Comparing these two scenarios demonstrates that prices definitely rose in West Florida 

and Mississippi and fell in Louisiana. 

Because they are vertically integrated, impacts in supply chain beyond harvester were likely 

much less than estimated here, because they simply imported product to make up the difference 

directly into their processing sector.
129

Table 20. Menhaden Economic Model Results 

Menhaden Scenario 1 Scenario 2

State Sector Employment Total 

Sales

Value 

Added Income Employment Total Sales Value Added Income

AL Harvester -1 -$53 -$20 -$20 -1 -$48 -$18 -$18

AL Dealer 0 -$16 -$2 -$2 0 -$15 -$2 -$2

AL Processor 0 -$24 -$4 -$3 0 -$21 -$4 -$3

AL Distributor 0 -$24 -$14 -$12 0 -$22 -$13 -$11

AL Market 0 -$20 -$13 -$9 0 -$18 -$12 -$8

AL Restaurant 0 -$19 -$10 -$8 0 -$17 -$9 -$7

AL Total -1 -$156 -$63 -$54 -1 -$141 -$58 -$49

W FL Harvester 0 $6 $2 $2 0 -$13 -$5 -$5

W FL Dealer 0 $2 $0 $0 0 -$4 -$1 $0

W FL Processor 0 $3 $1 $0 0 -$6 -$1 -$1

W FL Distributor 0 $3 $2 $2 0 -$7 -$4 -$3

W FL Market 0 $3 $2 $1 0 -$6 -$4 -$3

W FL Restaurant 0 $3 $2 $1 0 -$5 -$3 -$2

W FL Total 0 $20 $9 $6 0 -$41 -$18 -$14

LA Harvester -21 -$1,545 -$589 -$580 -202 -$14,991 -$5,711 -$5,626

LA Dealer -4 -$503 -$127 -$93 -35 -$4,885 -$1,236 -$899

LA Processor -5 -$714 -$189 -$132 -47 -$6,926 -$1,832 -$1,282

LA Distributor -7 -$686 -$422 -$353 -70 -$6,654 -$4,091 -$3,426

LA Market -9 -$585 -$396 -$256 -83 -$5,682 -$3,841 -$2,486

LA Restaurant -8 -$549 -$311 -$199 -74 -$5,327 -$3,015 -$1,930

LA Total -54 -$4,582 -$2,034 -$1,613 -511 -$44,465 -$19,726 -$15,649

MS Harvester -231 -$17,163 -$6,539 -$6,441 -224 -$16,644 -$6,341 -$6,246

MS Dealer -38 -$5,346 -$870 -$653 -37 -$5,184 -$844 -$633

MS Processor -58 -$8,067 -$1,580 -$1,070 -56 -$7,823 -$1,532 -$1,038

MS Distributor -78 -$7,813 -$4,684 -$3,857 -76 -$7,577 -$4,542 -$3,740

MS Market -91 -$6,229 -$4,248 -$2,708 -88 -$6,041 -$4,119 -$2,626

MS Restaurant -88 -$5,787 -$3,135 -$1,953 -85 -$5,611 -$3,040 -$1,894
130

Menhaden Scenario 1 Scenario 2

State Sector Employment Total 

Sales

Value 

Added Income Employment Total Sales Value Added Income

MS Total -584 -$50,405 -$21,056 -$16,682 -566 -$48,880 -$20,418 -$16,177

Gulf Harvester -370 -$27,478 -$10,468 -$10,312 -626 -$46,438 -$17,692 -$17,428

Gulf Dealer -40 -$6,091 -$1,268 -$932 -67 -$10,293 -$2,143 -$1,575

Gulf Processor -60 -$9,075 -$2,149 -$1,506 -102 -$15,337 -$3,632 -$2,545

Gulf Distributor -117 -$13,887 -$5,923 -$5,118 -197 -$23,470 -$10,010 -$8,650

Gulf Market -105 -$8,049 -$5,487 -$3,578 -178 -$13,603 -$9,273 -$6,047

Gulf Restaurant -94 -$8,094 -$4,424 -$2,727 -159 -$13,679 -$7,477 -$4,609

Gulf Total -786 -$72,674 -$29,719 -$24,173 -1,329 -$122,820 -$50,227 -$40,854

(Dollar Values are in Thousands of $US, Employment is in Number of full time jobs)
131

5.6 Reef Fish 

Table 21 shows the changes in economic activity to the reef fish industry in the Gulf post-spill. 

In Scenario 1, the Market Dynamic Scenario that allows prices to adjust, some states took large 

losses, even though prices were allowed to change. For instance, sales dropped in Alabama ($3.7 

million), Louisiana ($7.9 million) and West Florida ($15.3 million). 

However, in Texas, an area less affected by the spill and fishing closures, total sales from reef 

fish harvests increased. Reef fish landings drove total sales in Texas to $4.9 million under the 

Market Dynamic Scenario. Overall, then, the Gulf experienced a net decrease in economic 

activity from reef fish harvests in the period immediately following the spill, under the Market 

Dynamic Scenario. Gulf-wide economic activity fell, losing $28.0 million in total sales, $11.5

million in value added, $9.4 million in income and 273 jobs. 

Within Scenario 2, the Market Constant Scenario, Gulf-wide economic activity generated by reef 

fish was markedly down. With prices held constant at 2009 levels, total sales dropped $39.9 

million, value added dropped $16.4 million, income dropped $13.4 million and 391 jobs were

lost Gulf-wide. Under this scenario, all states but Texas lost economic activity; Louisiana lost

$7.8 million, Alabama lost $3.7 million and West Florida lost $24.4 million. Texas gained by 

$4.2 million in totals sales. This result was driven by slightly higher prices but also slightly 

higher volumes landed in Texas.
132

Table 21. Reef Fish Economic Model Results 

Reef Fish Scenario 1 Scenario 2

State Sector Employment Total 

Sales

Value 

Added Income Employment Total Sales ValueAdded Income

AL Harvester -14 -$1,250 -$481 -$479 -13 -$1,240 -$477 -$475

AL Dealer -2 -$390 -$56 -$43 -1 -$387 -$55 -$43

AL Processor -3 -$576 -$99 -$71 -3 -$572 -$98 -$70

AL Distributor -6 -$583 -$348 -$288 -6 -$579 -$345 -$286

AL Market -7 -$480 -$324 -$210 -7 -$476 -$321 -$208

AL Restaurant -7 -$446 -$241 -$193 -6 -$442 -$239 -$192

AL Total -39 -$3,725 -$1,549 -$1,284 -36 -$3,696 -$1,535 -$1,274

W FL Harvester -52 -$4,809 -$1,850 -$1,842 -83 -$7,656 -$2,946 -$2,933

W FL Dealer -10 -$1,570 -$212 -$123 -16 -$2,500 -$337 -$196

W FL Processor -16 -$2,368 -$409 -$235 -25 -$3,769 -$651 -$375

W FL Distributor -23 -$2,397 -$1,340 -$1,189 -37 -$3,816 -$2,133 -$1,893

W FL Market -29 -$2,241 -$1,520 -$1,000 -46 -$3,567 -$2,420 -$1,593

W FL Restaurant -24 -$1,954 -$1,176 -$735 -38 -$3,111 -$1,872 -$1,170

W FL Total -154 -$15,339 -$6,507 -$5,124 -245 -$24,419 -$10,359 -$8,160

LA Harvester -28 -$2,626 -$1,010 -$1,006 -28 -$2,607 -$1,003 -$999

LA Dealer -6 -$873 -$221 -$161 -6 -$867 -$219 -$159

LA Processor -8 -$1,238 -$328 -$229 -8 -$1,229 -$325 -$228

LA Distributor -12 -$1,190 -$731 -$613 -12 -$1,181 -$726 -$608

LA Market -15 -$1,016 -$687 -$445 -15 -$1,008 -$682 -$441

LA Restaurant -13 -$952 -$539 -$345 -13 -$945 -$535 -$343

LA Total -82 -$7,895 -$3,516 -$2,799 -82 -$7,837 -$3,490 -$2,778

TX Harvester 17 $1,561 $601 $598 14 $1,325 $510 $508

TX Dealer 3 $490 $86 $65 3 $416 $73 $55

TX Processor 5 $737 $157 $112 4 $626 $133 $95

TX Distributor 7 $798 $435 $381 6 $678 $369 $323

TX Market 9 $703 $480 $313 7 $597 $407 $266

TX Restaurant 8 $630 $367 $225 7 $535 $312 $191

TX Total 49 $4,919 $2,126 $1,694 41 $4,177 $1,804 $1,438
133

Reef Fish Scenario 1 Scenario 2

State Sector Employment Total 

Sales

Value 

Added Income Employment Total Sales ValueAdded Income

Gulf Harvester -113 -$10,438 -$4,016 -$3,998 -161 -$14,912 -$5,737 -$5,712

Gulf Dealer -15 -$2,362 -$492 -$361 -22 -$3,374 -$702 -$516

Gulf Processor -23 -$3,519 -$833 -$584 -33 -$5,027 -$1,190 -$834

Gulf Distributor -45 -$5,384 -$2,296 -$1,984 -65 -$7,692 -$3,281 -$2,835

Gulf Market -41 -$3,121 -$2,127 -$1,387 -58 -$4,458 -$3,039 -$1,982

Gulf Restaurant -36 -$3,138 -$1,715 -$1,057 -52 -$4,484 -$2,451 -$1,511

Gulf Total -273 -$27,962 -$11,479 -$9,371 -391 -$39,947 -$16,400 -$13,390

(Dollar Values are in Thousands of $US, Employment is in Number of full time jobs)
134

5.7 Pelagic Finfish 

Table 22 lists the economic changes occurring in the post-spill pelagic finfish markets regionwide. In Scenario 1, the Market Dynamic Scenario that allows prices to adjust, all states took 

large losses, even though prices were allowed to change. For instance, sales dropped in Alabama 

($21,000), Louisiana ($26.6 million), Texas ($1,000) and West Florida ($7.5 million). Overall, 

then, the Gulf experienced a net decrease in economic activity from pelagic finfish harvests in 

the period immediately following the spill under the Market Dynamic Scenario. Gulf-wide 

economic activity fell losing $44.0 million in total sales, $18.0 million in value added, $14.7

million in income and 450 jobs. 

In Scenario 2, the Market Constant Scenario, Gulf-wide economic activity generated by pelagic 

finfishes was markedly down. With prices held constant at 2009 levels, total sales dropped $37.6 

million, value added dropped $15.4 million, income dropped $12.6 million and 385 jobs were

lost Gulf-wide. Under this scenario, all states lost economic activity; Louisiana lost $26.6 

million, Alabama lost $23,000, Texas lost $4,000, and West Florida lost $2.3 million. There is 

very little difference between the two scenarios in the market for pelagic finfish. Prices and 

volumes harvested were down in West Florida, though prices were up in Louisiana but volumes 

were relatively low. 
135

Table 22. Pelagic Finfish Economic Model Results 

Pelagic Finfish Scenario 1 Scenario 2

State Sector Employment Total 

Sales

Value 

Added Income Employment Total Sales

Value 

Added Income

AL Harvester 0 -$7 -$3 -$3 0 -$8 -$3 -$3

AL Dealer 0 -$2 $0 $0 0 -$2 $0 $0

AL Processor 0 -$3 -$1 $0 0 -$4 -$1 $0

AL Distributor 0 -$3 -$2 -$2 0 -$4 -$2 -$2

AL Market 0 -$3 -$2 -$1 0 -$3 -$2 -$1

AL Restaurant 0 -$3 -$1 -$1 0 -$3 -$1 -$1

AL Total 0 -$21 -$9 -$7 0 -$24 -$9 -$7

W FL Harvester -28 -$2,336 -$898 -$890 -9 -$715 -$275 -$272

W FL Dealer -5 -$765 -$103 -$60 -2 -$234 -$32 -$18

W FL Processor -8 -$1,153 -$199 -$115 -2 -$353 -$61 -$35

W FL Distributor -11 -$1,168 -$653 -$579 -3 -$357 -$200 -$177

W FL Market -14 -$1,092 -$740 -$487 -4 -$334 -$227 -$149

W FL Restaurant -12 -$952 -$573 -$358 -4 -$291 -$175 -$110

W FL Total -78 -$7,466 -$3,166 -$2,489 -24 -$2,284 -$970 -$761

LA Harvester -106 -$8,836 -$3,395 -$3,365 -106 -$8,839 -$3,397 -$3,367

LA Dealer -21 -$2,948 -$746 -$542 -21 -$2,949 -$746 -$542

LA Processor -29 -$4,179 -$1,106 -$774 -29 -$4,181 -$1,106 -$774

LA Distributor -42 -$4,015 -$2,469 -$2,068 -42 -$4,017 -$2,470 -$2,069

LA Market -50 -$3,429 -$2,318 -$1,500 -50 -$3,430 -$2,319 -$1,501

LA Restaurant -45 -$3,214 -$1,820 -$1,165 -45 -$3,216 -$1,820 -$1,165

LA Total -293 -$26,621 -$11,854 -$9,414 -293 -$26,632 -$11,858 -$9,418

TX Harvester 0 -$1 $0 $0 0 -$1 $0 $0

TX Dealer 0 $0 $0 $0 0 $0 $0 $0

TX Processor 0 $0 $0 $0 0 -$1 $0 $0

TX Distributor 0 $0 $0 $0 0 -$1 $0 $0

TX Market 0 $0 $0 $0 0 -$1 $0 $0

TX Restaurant 0 $0 $0 $0 0 $0 $0 $0
136

Pelagic Finfish Scenario 1 Scenario 2

State Sector Employment Total 

Sales

Value 

Added Income Employment Total Sales

Value 

Added Income

TX Total 0 -$1 $0 $0 0 -$4 $0 $0

Gulf Harvester -197 -$16,379 -$6,294 -$6,238 -168 -$14,011 -$5,384 -$5,336

Gulf Dealer -24 -$3,717 -$774 -$569 -21 -$3,180 -$662 -$486

Gulf Processor -37 -$5,538 -$1,312 -$919 -31 -$4,737 -$1,122 -$786

Gulf Distributor -71 -$8,475 -$3,615 -$3,124 -61 -$7,250 -$3,092 -$2,672

Gulf Market -64 -$4,912 -$3,349 -$2,184 -55 -$4,202 -$2,864 -$1,868

Gulf Restaurant -57 -$4,940 -$2,700 -$1,664 -49 -$4,226 -$2,310 -$1,424

Gulf Total -450 -$43,961 -$18,044 -$14,698 -385 -$37,606 -$15,434 -$12,572

(Dollar Values are in Thousands of $US, Employment is in Number of full time jobs)
137

5.8 Other Crustaceans 

Table 23 demonstrates increases and decreases in the post-spill other crustaceans markets regionwide. This species category contains only four species: crawfish, Florida crab, and slipper and 

spiny lobster. The crawfish landings come 100% out of Louisiana; 100% of the lobster and 

99.5% of all the West Florida crab is harvested in West Florida. In Scenario 1, the Market 

Dynamic Scenario that allows prices to adjust, Louisiana took large losses, even though prices 

were allowed to change. For instance, crawfish sales in Louisiana dropped ($16.2 million).

However, in West Florida, an area less affected by the spill and spill closures, total sales from 

spiny lobster and Florida crab increased dramatically. Other crustaceans landings drove total 

sales in West Florida to $133.7 million under the Market Dynamic Scenario. Overall, then, the 

Gulf experienced a net increase in economic activity from other crustaceans harvests in the 

period immediately following the spill under the Market Dynamic Scenario. Gulf-wide economic 

activity rose, supporting $142.9 million in total sales, $58.8 million in value added, $45.3 million 

in income, and 1,329 jobs were gained. This makes other crustaceans the largest positive market 

in this analysis.

In Scenario 2, the Market Constant Scenario, Gulf-wide economic activity generated by other 

crustaceans was markedly up. With prices held constant at 2009 levels, total sales rose $7.8 

million, value added rose $3.2 million, income rose $2.5 million and 72 jobs were gained Gulfwide. However, under this scenario, all states but West Florida lost economic activity; Louisiana 

lost $18.5 million and Texas lost $279,000. West Florida would have been up by $26.2 million in 

totals sales. West Florida’s increases are attributable to slightly higher volumes and much higher 

dockside prices.
138

Table 23. Other Crustaceans Economic Model Results 

Other Crustaceans Scenario 1 Scenario 2

State Sector Employment Total 

Sales

Value 

Added Income Employment Total Sales

Value 

Added Income

W FL Harvester 394 $41,614 $16,106 $13,897 77 $8,158 $3,157 $2,724

W FL Dealer 90 $13,727 $1,851 $1,075 18 $2,691 $363 $211

W FL Processor 137 $20,698 $3,576 $2,058 27 $4,058 $701 $403

W FL Distributor 204 $20,955 $11,711 $10,397 40 $4,108 $2,296 $2,038

W FL Market 254 $19,589 $13,286 $8,745 50 $3,840 $2,605 $1,714

W FL Restaurant 211 $17,084 $10,279 $6,425 41 $3,349 $2,015 $1,260

W FL Total 1,290 $133,667 $56,809 $42,597 253 $26,204 $11,137 $8,350

LA Harvester -51 -$5,358 -$2,074 -$1,789 -58 -$6,106 -$2,363 -$2,039

LA Dealer -13 -$1,800 -$456 -$331 -15 -$2,052 -$519 -$377

LA Processor -17 -$2,552 -$675 -$473 -20 -$2,909 -$770 -$539

LA Distributor -26 -$2,452 -$1,508 -$1,263 -29 -$2,795 -$1,718 -$1,439

LA Market -31 -$2,094 -$1,416 -$916 -35 -$2,387 -$1,613 -$1,044

LA Restaurant -27 -$1,963 -$1,111 -$711 -31 -$2,238 -$1,267 -$811

LA Total -165 -$16,219 -$7,240 -$5,483 -188 -$18,487 -$8,250 -$6,249

TX Harvester -1 -$87 -$34 -$29 -1 -$88 -$34 -$29

TX Dealer 0 -$27 -$5 -$4 0 -$28 -$5 -$4

TX Processor 0 -$41 -$9 -$6 0 -$42 -$9 -$6

TX Distributor 0 -$45 -$24 -$21 0 -$45 -$25 -$22

TX Market 0 -$39 -$27 -$18 -1 -$40 -$27 -$18

TX Restaurant 0 -$35 -$21 -$13 0 -$36 -$21 -$13

TX Total -1 -$274 -$120 -$91 -2 -$279 -$121 -$92

Gulf Harvester 502 $52,993 $20,509 $17,697 27 $2,878 $1,114 $961

Gulf Dealer 79 $12,113 $2,522 $1,853 4 $658 $137 $101

Gulf Processor 120 $18,048 $4,274 $2,995 7 $980 $232 $163

Gulf Distributor 232 $27,619 $11,779 $10,179 13 $1,500 $640 $553

Gulf Market 209 $16,008 $10,912 $7,116 11 $869 $593 $386

Gulf Restaurant 187 $16,098 $8,799 $5,423 10 $874 $478 $295

Gulf Total 1,329 $142,879 $58,795 $45,263 72 $7,759 $3,194 $2,459

(Dollar Values are in Thousands of $US, Employment is in Number of full time jobs)
139

5.9 Bait

Table 24 shows the changes in the post-spill bait industry region-wide. In Scenario 1, the Market 

Dynamic Scenario that allows prices to adjust, some states took large losses, even though prices 

were allowed to change. For instance, sales dropped in Alabama ($461,198) and West Florida 

($2.7 million). 

However, in areas less affected by the spill and spill closures, Louisiana, Mississippi, and Texas, 

total sales from bait harvests increased. Bait landings drove total sales in Louisiana to $967,943, 

Mississippi to $59,915, and Texas to $352,754 under the Market Dynamic Scenario. Overall, 

then, the Gulf experienced a net decrease in economic activity from bait harvests in the year 

immediately following the spill under the Market Dynamic Scenario. Gulf-wide economic 

activity fell, losing $2.2 million in total sales, $904,000 in value added, $703,000 in income and 

21 jobs. 

In Scenario 2, the Market Constant Scenario, Gulf-wide economic activity generated by bait 

decreased. With prices held constant at 2009 levels, total sales dropped $5.1 million, value added 

dropped $2.1 million, income dropped $1.6 million, and 47 jobs were lost Gulf-wide. The Gulf’s 

decrease in total sales can be attributed to West Florida ($4.3 million) and Alabama ($1 million). 

However, it should be noted that under this scenario, total sales in Louisiana, Mississippi, and 

Texas all increased slightly; Louisiana increased $936,826, Mississippi increased $27,006, and 

Texas increased $263,474. Increases in Louisiana were driven by higher harvest volumes, in 

Mississippi both prices and volumes were both up slightly, and in Texas increased harvest 

volumes drove the increase.
140

Table 24. Bait Economic Model Results 

Bait Scenario 1 Scenario 2

State Sector Employment Total 

Sales

Value 

Added Income Employment Total Sales

Value 

Added Income

AL Harvester -1 -$154 -$59 -$53 -3 -$348 -$134 -$119

AL Dealer 0 -$48 -$7 -$5 0 -$109 -$16 -$12

AL Processor 0 -$72 -$12 -$9 -1 -$162 -$28 -$20

AL Distributor -1 -$72 -$43 -$36 -2 -$164 -$98 -$81

AL Market -1 -$60 -$40 -$26 -2 -$135 -$91 -$59

AL Restaurant -1 -$55 -$30 -$24 -2 -$125 -$67 -$54

AL Total -4 -$461 -$191 -$153 -10 -$1,043 -$434 -$345

W FL Harvester -8 -$855 -$330 -$292 -13 -$1,351 -$522 -$462

W FL Dealer -2 -$281 -$38 -$22 -3 -$445 -$60 -$35

W FL Processor -3 -$424 -$73 -$42 -4 -$671 -$116 -$67

W FL Distributor -4 -$430 -$240 -$213 -7 -$679 -$379 -$337

W FL Market -5 -$402 -$272 -$179 -8 -$635 -$431 -$283

W FL Restaurant -4 -$350 -$211 -$132 -7 -$554 -$333 -$208

W FL Total -26 -$2,742 -$1,164 -$880 -42 -$4,335 -$1,841 -$1,392

LA Harvester 3 $320 $124 $109 3 $310 $120 $106

LA Dealer 1 $107 $27 $20 1 $104 $26 $19

LA Processor 1 $152 $40 $28 1 $147 $39 $27

LA Distributor 2 $146 $90 $75 1 $142 $87 $73

LA Market 2 $125 $84 $55 2 $121 $82 $53

LA Restaurant 2 $117 $66 $42 2 $113 $64 $41

LA Total 11 $967 $431 $329 10 $937 $418 $319

MS Harvester 0 $20 $8 $7 0 $9 $3 $3

MS Dealer 0 $6 $1 $1 0 $3 $0 $0

MS Processor 0 $10 $2 $1 0 $4 $1 $1

MS Distributor 0 $9 $6 $5 0 $4 $3 $2

MS Market 0 $7 $5 $3 0 $3 $2 $1

MS Restaurant 0 $7 $4 $2 0 $3 $2 $1
141

Bait Scenario 1 Scenario 2

State Sector Employment Total 

Sales

Value 

Added Income Employment Total Sales

Value 

Added Income

MS Total 0 $59 $26 $19 0 $26 $11 $8

TX Harvester 1 $111 $43 $38 1 $83 $32 $28

TX Dealer 0 $35 $6 $5 0 $26 $5 $3

TX Processor 0 $53 $11 $8 0 $40 $8 $6

TX Distributor 1 $57 $31 $27 0 $43 $23 $20

TX Market 1 $51 $34 $23 0 $38 $26 $17

TX Restaurant 1 $45 $26 $16 0 $34 $20 $12

TX Total 4 $352 $151 $117 1 $264 $114 $86

Gulf Harvester -8 -$816 -$315 -$279 -18 -$1,900 -$734 -$650

Gulf Dealer -1 -$186 -$39 -$29 -3 -$433 -$90 -$66

Gulf Processor -2 -$278 -$66 -$46 -4 -$646 -$153 -$107

Gulf Distributor -4 -$425 -$181 -$157 -8 -$988 -$422 -$364

Gulf Market -3 -$246 -$168 -$109 -7 -$573 -$391 -$255

Gulf Restaurant -3 -$248 -$135 -$83 -7 -$576 -$315 -$194

Gulf Total -21 -$2,199 -$904 -$703 -47 -$5,116 -$2,105 -$1,636

(Dollar Values are in Thousands of $US, Employment is in Number of full time jobs)
142

5.10 Other Shellfish

Table 25 shows the complex dynamics occurring in the other shellfish market region wide post 

spill. In Scenario 1, the Market Dynamic Scenario that allows prices to adjust, some states took 

losses, even though prices were allowed to change in response to activities occurring in the 

market. For instance, sales dropped in Alabama ($248,000), Louisiana ($108,000), and 

Mississippi ($45,000). Overall, this is a very small fishery.

However, in areas less affected by the spill and spill closures, Texas and West Florida, total sales 

from other shellfish harvests increased. Other shellfish landings drove total sales in West Florida 

to $720,000 and $51,000 in Texas under the Market Dynamic Scenario. Overall, then, the Gulf 

experienced a net increase in economic activity from other shellfish harvests in the period 

immediately following the spill under the Market Dynamic Scenario. Gulf-wide economic 

activity rose, supporting $423,000 in total sales, $175,000 in value added, $142,000 in income, 

and five additional jobs. 

In Scenario 2, the Market Constant Scenario, Gulf-wide economic activity generated by other 

shellfish was markedly up. If prices were held constant at 2009 levels, total sales rose $1.4 

million, value added rose $580,000, income rose $471,000, and 14 jobs were gained Gulf-wide. 

Under this scenario, all but West Florida and Texas lost economic activity; in total sales 

Louisiana lost $94,000, Alabama lost $308,000, and Mississippi lost $49,000. West Florida 

gained $1.5 million in totals sales and Texas gained $76,000. This uncharacteristic result, at least 

as far as all other species markets analyzed here, would have been driven by prices that dropped 

significantly and harvest volumes that increased dramatically.
143

Table 25. Other Shellfish Economic Model Results 

Other Shellfish Scenario 1 Scenario 2

State Sector Employment Total 

Sales

Value 

Added Income Employment Total Sales

Value 

Added Income

AL Harvester -1 -$83 -$33 -$32 -1 -$103 -$41 -$40

AL Dealer 0 -$26 -$4 -$3 0 -$32 -$5 -$4

AL Processor 0 -$38 -$7 -$5 0 -$48 -$8 -$6

AL Distributor 0 -$39 -$23 -$19 0 -$48 -$29 -$24

AL Market 0 -$32 -$22 -$14 -1 -$40 -$27 -$17

AL Restaurant 0 -$30 -$16 -$13 -1 -$37 -$20 -$16

AL Total -1 -$248 -$105 -$86 -3 -$308 -$130 -$107

W FL Harvester 3 $225 $89 $87 5 $482 $190 $186

W FL Dealer 0 $74 $10 $6 1 $158 $21 $12

W FL Processor 1 $111 $19 $11 2 $239 $41 $24

W FL Distributor 1 $113 $63 $56 2 $242 $135 $120

W FL Market 1 $105 $72 $47 3 $226 $153 $101

W FL Restaurant 1 $92 $55 $35 2 $197 $119 $74

W FL Total 7 $720 $308 $242 15 $1,544 $659 $517

LA Harvester 0 -$36 -$14 -$14 0 -$31 -$12 -$12

LA Dealer 0 -$12 -$3 -$2 0 -$10 -$3 -$2

LA Processor 0 -$17 -$5 -$3 0 -$15 -$4 -$3

LA Distributor 0 -$16 -$10 -$8 0 -$14 -$9 -$7

LA Market 0 -$14 -$9 -$6 0 -$12 -$8 -$5

LA Restaurant 0 -$13 -$7 -$5 0 -$11 -$6 -$4

LA Total 0 -$108 -$48 -$38 0 -$93 -$42 -$33

MS Harvester 0 -$15 -$6 -$6 0 -$17 -$7 -$6

MS Dealer 0 -$5 -$1 -$1 0 -$5 -$1 -$1

MS Processor 0 -$7 -$1 -$1 0 -$8 -$2 -$1

MS Distributor 0 -$7 -$4 -$4 0 -$8 -$5 -$4

MS Market 0 -$6 -$4 -$2 0 -$6 -$4 -$3

MS Restaurant 0 -$5 -$3 -$2 0 -$6 -$3 -$2
144

Other Shellfish Scenario 1 Scenario 2

State Sector Employment Total 

Sales

Value 

Added Income Employment Total Sales

Value 

Added Income

MS Total 0 -$45 -$19 -$16 0 -$50 -$22 -$17

TX Harvester 0 $16 $6 $6 0 $24 $9 $9

TX Dealer 0 $5 $1 $1 0 $8 $1 $1

TX Processor 0 $8 $2 $1 0 $11 $2 $2

TX Distributor 0 $8 $5 $4 0 $12 $7 $6

TX Market 0 $7 $5 $3 0 $11 $7 $5

TX Restaurant 0 $7 $4 $2 0 $10 $6 $3

TX Total 0 $51 $23 $17 0 $76 $32 $26

Gulf Harvester 2 $157 $62 $61 6 $521 $205 $201

Gulf Dealer 0 $36 $7 $5 1 $119 $25 $18

Gulf Processor 0 $53 $13 $9 1 $177 $42 $29

Gulf Distributor 1 $82 $35 $30 2 $270 $115 $100

Gulf Market 1 $47 $32 $21 2 $157 $107 $70

Gulf Restaurant 1 $48 $26 $16 2 $158 $86 $53

Gulf Total 5 $423 $175 $142 14 $1,402 $580 $471

(Dollar Values are in Thousands of $US, Employment is in Number of full time jobs)
145

5.11 Miscellaneous Finfish

Table 26 shows the complex dynamics occurring in the post-spill miscellaneous finfish market 

region-wide. In Scenario 1, the Market Dynamic Scenario that allows prices to adjust, all states 

except Texas took large losses, even though prices were allowed to change in response to 

activities occurring in the market. For instance, sales dropped in Alabama ($616,000), West 

Florida ($6.6 million), Louisiana ($224,000), and Mississippi ($749,000). 

However, in Texas, an area less affected by the spill and spill closures, total sales from 

miscellaneous finfish harvests increased. Miscellaneous finfish landings drove total sales to 

$610,490 million in Texas under the Market Dynamic Scenario. Overall, then, the Gulf 

experienced a net decrease in economic activity from miscellaneous finfish harvests in the period 

immediately following the spill under the Market Dynamic Scenario. Gulf-wide economic 

activity fell losing $9.4 million in total sales, $3.9 million in value added, $3.1 million in income, 

and 89 lost jobs. 

In Scenario 2, the Market Constant Scenario, Gulf-wide economic activity generated by 

miscellaneous finfish decreased, but by less than would have been expected given the results 

across other species. With prices held constant at 2009 levels, total sales dropped $11.4 million, 

value added dropped $4.7 million, income dropped $3.8 million, and 110 jobs were lost Gulfwide. Under this scenario, all states but Texas lost economic activity; Louisiana lost $5.8 million, 

West Florida lost $905,000 million, Alabama lost $1.0 million, and Mississippi lost $1.2 million. 

Texas gained $57,000 in total sales. This suggests that Texas would have received higher prices 

for miscellaneous finfish post spill. Overall, it appears that in the other states, prices would have 

increased dramatically post spill. 
146

Table 26. Miscellaneous Finfish Economic Model Results 

Miscellaneous 

Finfish Scenario 1 Scenario 2

State Sector Employment Total 

Sales

Value 

Added Income Employment Total Sales

Value 

Added Income

AL Harvester -2 -$206 -$79 -$75 -4 -$349 -$134 -$127

AL Dealer 0 -$65 -$9 -$7 0 -$109 -$16 -$12

AL Processor 0 -$95 -$16 -$12 -1 -$161 -$28 -$20

AL Distributor -1 -$97 -$58 -$48 -2 -$163 -$97 -$81

AL Market -1 -$79 -$54 -$35 -2 -$134 -$91 -$59

AL Restaurant -1 -$74 -$40 -$32 -2 -$125 -$67 -$54

Total -5 -$616 -$256 -$209 -11 -$1,041 -$433 -$353

W FL Harvester -21 -$2,062 -$792 -$750 -3 -$283 -$109 -$103

W FL Dealer -4 -$675 -$91 -$53 -1 -$93 -$13 -$7

W FL Processor -7 -$1,018 -$176 -$101 -1 -$140 -$24 -$14

W FL Distributor -10 -$1,031 -$576 -$512 -1 -$142 -$79 -$70

W FL Market -12 -$964 -$654 -$430 -2 -$132 -$90 -$59

W FL Restaurant -10 -$841 -$506 -$316 -1 -$115 -$69 -$43

W FL Total -64 -$6,591 -$2,795 -$2,162 -9 -$905 -$384 -$296

LA Harvester -1 -$74 -$28 -$27 -19 -$1,910 -$734 -$695

LA Dealer 0 -$25 -$6 -$5 -5 -$637 -$161 -$117

LA Processor 0 -$35 -$9 -$6 -6 -$904 -$239 -$167

LA Distributor 0 -$34 -$21 -$17 -9 -$868 -$534 -$447

LA Market 0 -$29 -$19 -$13 -11 -$741 -$501 -$324

LA Restaurant 0 -$27 -$15 -$10 -10 -$695 -$393 -$252

LA Total -1 -$224 -$98 -$78 -60 -$5,755 -$2,562 -$2,002

MS Harvester -3 -$251 -$96 -$91 -4 -$393 -$151 -$143

MS Dealer -1 -$80 -$13 -$10 -1 -$125 -$20 -$15

MS Processor -1 -$121 -$24 -$16 -1 -$189 -$37 -$25

MS Distributor -1 -$117 -$70 -$58 -2 -$183 -$110 -$90

MS Market -1 -$93 -$64 -$40 -2 -$146 -$100 -$64

MS Restaurant -1 -$87 -$47 -$29 -2 -$136 -$74 -$46
147

Miscellaneous 

Finfish Scenario 1 Scenario 2

State Sector Employment Total 

Sales

Value 

Added Income Employment Total Sales

Value 

Added Income

MS Total -8 -$749 -$314 -$244 -12 -$1,172 -$492 -$383

TX Harvester 2 $193 $74 $70 0 $18 $7 $7

TX Dealer 0 $61 $11 $8 0 $6 $1 $1

TX Processor 1 $92 $20 $14 0 $9 $2 $1

TX Distributor 1 $99 $54 $47 0 $9 $5 $4

TX Market 1 $87 $60 $39 0 $8 $6 $4

TX Restaurant 1 $78 $46 $28 0 $7 $4 $3

TX Total 6 $610 $265 $206 0 $57 $25 $20

Gulf Harvester -35 -$3,515 -$1,351 -$1,278 -43 -$4,273 -$1,642 -$1,554

Gulf Dealer -5 -$798 -$166 -$122 -6 -$970 -$202 -$148

Gulf Processor -8 -$1,189 -$282 -$197 -10 -$1,445 -$342 -$240

Gulf Distributor -15 -$1,819 -$776 -$670 -19 -$2,212 -$943 -$815

Gulf Market -14 -$1,054 -$719 -$469 -17 -$1,282 -$874 -$570

Gulf Restaurant -12 -$1,060 -$580 -$357 -15 -$1,289 -$705 -$434

Gulf Total -89 -$9,435 -$3,874 -$3,093 -110 -$11,471 -$4,708 -$3,761

(Dollar Values are in Thousands of $US, Employment is in Number of full time jobs)
148

Chapter Six: Summary and Discussion

6.1 Summary of Study Approach and Results

This study gathered various types of economic data in order to analyze the structure of the 

seafood industry in the Gulf of Mexico and to estimate the impacts of the Deepwater Horizon oil 

spill on the Gulf seafood industry. The study focuses in on the five Gulf states (Alabama, West 

Florida, Louisiana, Mississippi, and Texas) and segmented the species into ten like category 

groupings (shrimp, oysters, menhaden, blue crab, reef fish, pelagic finfish, other crustaceans, 

bait, other shellfish, and miscellaneous finfish). A key goal of the study was to examine the 

structure of the seafood industry’s supply chain and look at how that structure may have changed 

as a result of the oil spill. Various data sets were collected and merged to provide background 

information for the time period surrounding the spill, namely 2002–2013, and the data sets were 

examined for trends. The analysis focused in on the same time periods as in the Settlement 

Agreement, that is, May to December of 2007; 2008; 2009; and 2010. The eight-month period of 

May to December of 2010, known as the damage period, was the period over which this study 

estimated damages. Additional data outside of the damage period and qualitative information 

relative to long-term impacts were gathered and contributed to the analysis and enhanced our 

understanding of the model results. 

The analysis was conducted using a custom impact model to quantify the economic impacts of 

the oil spill on the Gulf seafood industry. This model used the change in dockside seafood

landings and value to estimate impacts based on the settlement periods and defined spill closure 

periods as defined in this report. A backward-linking custom impact model was developed using

the best available model structure in the literature and enhanced by recent financial and 

economic reports published by the Gulf Commission. The custom model was then used to 

examine the economic activity lost to the entire seafood supply chain by calculating impacts 

based on the change in dockside landings and value from 2009 to 2010 during the damage 

period. Results were presented by the defined species categories and states and interpreted in 

context to qualitative research gathered in the study. 

Two sets of input data were specified for the empirical calculation of economic impacts in the 

short-run: Market Dynamic, the change in dockside revenue from 2009 to 2010 for the damage 

period; and Market Constant, the change in dockside revenue from 2009 to 2010 for the damage 

period based on 2010 landings and holding 2010 prices constant at 2009 levels. These scenarios 

were intended to generate a range of viable impact estimates to address market uncertainty and 

offer an examination of the upper and lower bound revenue loss estimates.

Table 27 summarizes the results of this impact modeling exercise by scenario at the Gulf-wide 

level. Overall, the oil spill generated between $51.7 and $952.9 million loss in total sales. This 

loss cost the region $21.4–$392.7 million in value added, $21.6–$309.8 million in income, and 

740–9,315 jobs. The harvesting sector bore the brunt of those losses, losing between $20.1–

$354.5 million in total sales, $7.9–$137.8 million in value added, $11.9–$126.3 million in 

income, and 449–3,809 jobs. The dealer sector fared the best, losing $4.3–$80.6 million in total 

sales, $887,000–$16.8 million in value added, $652,000–$12.3 million in income, 28–527 jobs.
149

Table 27. Impact Model Summary

Sector Impact Type Market Dynamic 

(Total Impact)

Market Constant 

(Total Impact)

Harvester

Sales -$20,114 -$354,512

Value Added -$7,932 -$137,782

Income -$11,858 -$126,268

Employment -$449 -$3,809

Dealer

Sales -$4,261 -$80,644

Value Added -$887 -$16,792

Income -$652 -$12,338

Employment -$28 -$527

Processor

Sales -$6,348 -$120,156

Value Added -$1,503 -$28,454

Income -$1,053 -$19,938

Employment -$42 -$798

Distributor

Sales -$9,714 -$183,874

Value Added -$4,143 -$78,421

Income -$3,580 -$67,766

Employment -$82 -$1,543

Market

Sales -$5,630 -$106,572

Value Added -$3,838 -$72,648

Income -$2,503 -$47,374

Employment -$74 -$1,391

Restaurant

Sales -$5,662 -$107,171

Value Added -$3,095 -$58,581

Income -$1,908 -$36,106

Employment -$66 -$1,246

Total

Sales -$51,729 -$952,929

Value Added -$21,399 -$392,678

Income -$21,554 -$309,791

Employment -$740 -$9,315

(Dollar Values are in Thousands of $US, Employment is in Number of full time jobs)

Although an overall picture of impacts in the Gulf is informative, impacts broken down by 

species and state proved to be much more explanatory because of the impacts and dynamics 

reported at the fisheries level. In general, it can be noted that impacts were highest in Louisiana, 

Mississippi, and Alabama, and dramatically lower, and in some cases nonexistent, in Texas and 

West Florida. Although each species category has a slightly different outcome depending on the 

nature of the species location and market, it can be noted that shrimp, followed by oysters and 

then menhaden, were the top three most impacted species. Blue crab, reef fish, and pelagic 

finfish are roughly tied for fourth given the results of the two scenarios. 
150

Due to the sheer size and value of the shrimp category, our model revealed the largest impacts 

across shrimp relative to the other species due to the oil spill closures. Although Louisiana had 

by far the largest impacts, Mississippi and Alabama also had substantial impacts relative to the 

size of their fisheries. Results in Texas were interesting because the Market Dynamic scenario 

indicated positive impacts, whereas the Market Constant scenario showed negative impacts.

Through further investigation and research (see Chapter Three), it appears that strong price 

increases have had a strong positive influence in the Market Dynamic results for Texas.

Although much of these price influences can be attributed to supply shortages caused by the 

spill, it appears some of this price increase can be attributed to exogenous factors, such as the

restriction of import supply and a general improvement in the economy during the damage 

period.

The next-largest impacts have been noted in the oyster category; all states except Texas have 

been impacted. Louisiana again saw the largest impacts due to the spill, with Mississippi next 

and smaller impacts in Florida. Because of the historical harvests and the effects of the release of 

the Mississippi River freshwater diversions in April of 2010, these results are intuitive from a 

geographical standpoint (see Chapter Three). The difference in impacts between the two 

scenarios was much less than noted in other species categories due to a much smaller increase in 

price from 2009 to 2010. Although these impacts are relatively large, longer-term impacts in 

2011, 2012, and 2013 are not captured by these results and are presumed to be present given the 

lower historical harvests (noted in Figure 21).

The third-heaviest impact was felt by the menhaden industry. The menhaden industry is located 

primarily in Mississippi and Louisiana, and those two states were impacted the most. Because

the industry is owned by two vertically-integrated fishing companies and a larger portion of the 

product produced is not for human consumption, the effects of these impacts and the way the 

market reacts tend to be slightly different. Although it was indicated in Omega Proteins’ annual 

report that they took a loss as of June 30, 2010, they later indicated that they caught 90 % of the 

fish they planned on catching for that year. Because of the consolidated nature of this industry, it 

appears competition for raw material is less competitive than in the other species categories, and 

this enables processors to simply buy raw material with less risk of losing their customer base to 

competitive markets. This was one species category that has shown a slight decrease in price 

across all states that landed product. 

Other species categories with negative impacts that could be attributed to specific product 

markets were blue crab, reef fish, pelagic finfish, and other crustaceans. Although these 

categories were much smaller in volume and value, in some cases, the relative impact on these 

categories was significant. 

Impacts on blue crab were greatest in Louisiana, followed by Mississippi and Alabama. As 

indicated with shrimp, it is believed that stronger blue crab prices in 2010 counteracted impacts 

of the spill in the Market Dynamic scenario. Although some of these price influences can be 

attributed to supply shortages caused by the spill, it appears that a portion of this price increase 

could be attributed to exogenous factors, such as a slowing of imported supply and a general 

improvement in the economy during the damage period. Though harvest volumes were reduced 

in areas impacted by the spill closures, Florida and Texas had an increase in harvest volume. 
151

Prices seem to increase in all states except Florida. In addition to the impacts captured in this 

model, some concerns with longer-term ecological effects have been noted in Chapters 2 and 3. 

However, given the historical downward trend in harvest, it is difficult to differentiate 

preexisting biological effects from the effects of the oil spill.

Negative impacts on reef fish were largest in West Florida, but also occurred in Louisiana and

Alabama. There were positive impacts in Texas, where both landings and revenue increased 

during the damage period. There was indication from the industry that a notable shift in fishing 

effort did occur away from the spill area and into Texas, which was bolstered by a successful 

contract with a major Texas retail chain (Krebs 2014). Although impacts were negative in West 

Florida, it appears that prices increased in both West Florida and Texas; results in these states 

show lower impacts with the Market Dynamic scenario and higher relative impacts with the 

Market Constant scenario. As indicated by an industry source, many of the reef fish fisheries 

have seen improvement since the spill, showing a notable increase in post-spill landings and 

revenue (Krebs 2014). An industry source indicated this is due to a combination of factors, such 

as changes in the management strategy and improved markets (Krebs 2014).

As indicated by harvest data, much of the fishing effort for tuna, the primary species in the 

pelagic finfish category, decreased during the damage period; this resulted in large impacts 

relative to the size of the fishery. Pelagic finfish are caught primarily in Louisiana, where 

impacts to the fishery were relatively dramatic. Smaller negative impacts did exist in West 

Florida, Alabama, and Texas. Because there was a relatively small difference between the two 

modeling scenarios, we conclude that prices on the whole did not change much in 2010, although 

we have noted a notable decrease in prices in West Florida during the damage period. Although 

overall impacts on this species category were not large in comparison to other categories like 

shrimp, oyster, and menhaden, the percent decline in economic activity for this category appears 

to be the largest. Another long-term concern that was noted in Chapter Two, but was not 

captured in this model, was evidence that the emerging 2010 year class of certain pelagic finfish 

species may have compromised cardiac function due to exposure to oil and so may demonstrate 

greater impacts in future harvests.

The other crustacean category consists of three primary species that come from distinct states,

enabling clear analysis by each key species in the category. Crawfish are harvested exclusively 

in Louisiana, but Florida crab and spiny lobster are harvested almost exclusively in Florida. Our 

model’s ability to break these species down by state allows us to isolate these dramatic 

differences in the individual species. In summary, crawfish in Louisiana, which were in close 

proximity to the spill, incurred relatively large negative impacts, but Florida crab and spiny 

lobster in Florida, which were relatively isolated from the spill, experienced very positive 

impacts. Although this seems intuitive, the magnitude of the increases in West Florida with 

Florida crab and spiny lobster were so large it required further investigation. Although results in 

West Florida for both scenarios showed relatively large positive impacts, the results of the 

Market Dynamic scenario showed impacts around five times greater; this indicates a large price 

increase for these species in 2010. Through further investigation and research, as presented in 

Chapter Three, it appears that extreme price increases and moderate volume increases from 2009 

to 2010 in Florida crab and spiny lobster were the primary driver behind the positive impacts of 

the other crustacean category. Our research, presented in Chapter Three, suggests that much of 
152

this price increase can be attributed to exogenous factors, such as unprecedented weak global 

market demand during the baseline period of 2009, a shift from low-value processed production 

to higher-value live production, and a general increase in the overall economy during the damage 

period. This dramatic transformation in the spiny lobster market is believed to have had a large 

impact on price received by the fisherman and to have driven revenues up notably in the other 

crustaceans category in recent years. It is important to note that, because of the structural 

changes in the industry during this period, revenue increases do not always reflect profit 

increases. Because of the increased cost structure to manage live spiny lobster production, these 

noted revenue changes have likely been eroded in any profits made by the industry. (Spiny 

Lobster Review Panel 2015). Further investigation of the crawfish market showed large 

fluctuations in volume that were highly influenced by external weather events. Although we 

believe the impacts in Louisiana on crawfish in 2010 are related to the oil spill event, because of

the historical volatility of landings and sensitivity to weather events, it could be challenging to 

prove that these impacts were solely due to the spill event. 

6.2 Comparison of Results with Previous Studies

Few analyses have been done to estimate the potential impact of the oil spill on the Gulf seafood 

industry. In October 2010, Greater New Orleans, Inc. published an analysis commissioned to 

project the length of time it would take for commercial catches of shrimp, oysters, blue crab, 

yellowfin tuna, black drum, striped mullet, and menhaden to return to pre-spill levels in 

Louisiana. To predict recovery time, rates of marine life recovery observed in previous oil spills, 

such as the 1989 Exxon Valdez oil spill in Prince William Sound, Alaska, were used. The study 

estimated that projections of revenue losses in the fisheries would likely range from $59 million 

to $89 million in 2011, $38 million to $56 million in 2012, and $18 million to $27 million in 

2013. Using these estimates and projecting out impacts to the larger economy, lost fishing 

revenues resulting from short-term ecological effects experienced 2011 to 2013 were estimated 

to be between $285 million to $428 million, to result in the loss of between 2,700 to 4,000 full 

time employees, and lost employee earnings of between $68 million and $103 million. The 

Bureau of Economic Analysis RIMS II model multipliers were used to estimate impacts. These 

estimates were admittedly initial, and future studies were expected to be more comprehensive 

and could use this analysis as a base. 

However, Greater New Orleans, Inc. (2010) report analyzed economic impacts, moratoria, and 

brand damage. The study surveyed Louisiana fishermen and found that the majority were not 

interested in pursuing other careers in the wake of the oil spill. It also used these interviews to 

recommend ways to increase the success of post-disaster programming. Interviews of the public 

found that five years after Hurricane Katrina tourists still had an interest in visiting Louisiana. 

However, seafood concerns after the oil spill caused interest in visiting Louisiana to decrease, 

because seafood is a significant draw for tourists.

In a study commissioned by the GCCF Administrator, Kenneth Feinberg, Tunnell (2011) 

estimated that most species would experience pre-spill landings levels by 2011. The one 

exception was for oyster beds, which might experience negative effects for a longer period of 

time and would not be harvestable until 2012, 2013, or up to ten years.
153

In 2012, Sumaila et al. published the results of an impact analysis that estimated the potential 

negative economic effects of the oil spill on commercial and recreational fishing and marine 

aquaculture in the Gulf. By computing potential losses throughout the fish value chain, they 

estimated that the commercial fishery would experience present value losses of total revenues, 

total profits, wages, and economic impact of $0.5–2.7 billion, $0.3–1.4 billion, $0.1–0.8 billion, 

and $1.5–8.4 billion, respectively, over the next seven years. They estimated that the shrimp 

fishery would experience the greatest losses of all the commercial fisheries (85% of the total 

economic impact). They used past landings and the value of those landings from 2000–2005 to 

estimate those losses. 

Posadas (2013) compares commercial landings in Mississippi’s fishing sector during the oil spill 

in 2010 with baseline periods covering the five years before (2000–2004) and the five years after 

(2005–2009) Hurricane Katrina. In some cases, there was no significant difference between the 

two baseline periods, and, instead, an average of 2000–2009 landings and revenue was used. The 

study found that total seafood landings in 2010 were 53% of the average annual amount during 

the 2000–2009 baseline period. Total seafood revenue in 2010 was about 44% of what it was 

during the pre-Katrina period, and 56% of what it was during the post-Katrina period. These 

revenue differences showed that Gulf seafood prices were higher in the pre-Katrina period than 

they were in the post-Katrina period. 

These studies indicate that there are other potential economic impacts not covered in these 

analyses, including clean-up costs, value of lost oil, natural and environmental damage beyond 

fisheries impacts, other direct use impacts and non-fish tourism, and non-use existence and 

option values. In addition, price adjustments and impacts at the consumer level due to product 

perception and safety concerns may not have been clearly accounted for due to the various 

exogenous factors mentioned in this report that have influenced markets during this period.

6.3 General Caveats

Specific trends in the harvest data were relevant to the revenue scenarios chosen. The reduction 

in landing volume due to the spill closures was relatively obvious in the harvest data, but 

reduction in revenue was not as apparent in the harvest data. The revenue change scenarios in 

this study were chosen to represent this divergence in the data, and hence the inclusion versus 

exclusion of exogenous market factors. When considering the use of input data for the model, we 

chose to use the Market Dynamic scenario to include market and price fluctuations, and the 

Market Constant scenario to represent a scenario where all market factors except volume were

held constant. It was understood that the smaller impacts would be produced with the Market 

Dynamic scenario because of the notable increase in price which counteracted the fairly 

substantial drops in landed volumes witnessed.

Although there were specific fisheries and states where prices went down during the damage 

period, it was apparent from comparison of the two scenarios’ results that prices in general in the 

Gulf as a whole went up during the damage period. From the research presented in Chapter Two

and Three, it is believed that that three key factors attributed to this positive price trend: 1.) A 

shortage of domestic product due to the spill closures, 2.) An increase in the overall activity in 

the economy, and 3.) A shortage of imported substitute products due various exogenous market 
154

factors. Although the overall trend showed a price increase from 2009 to 2010, which can be 

noted in most key species categories, we did see some price decreases in menhaden and reef fish 

and some isolated decreases, for example in West Florida for blue crab, pelagic finfish, other 

shellfish, and miscellaneous finfish.

There is a philosophical debate that should be considered when reviewing the results of the two 

scenarios that were run through the model. When reviewing the Market Dynamic results, one 

must consider that impacts being presented do not rule out exogenous effects that have in most 

cases increased the revenue of the industry participants. Therefore, in general, the Market 

Dynamic results being presented are believed to underestimate the impacts on the Gulf seafood 

industry. When reviewing the Market Constant results, one must consider that certain market 

factors that would normally help minimize the impacts of the fishery closure have been removed.

Therefore, it is believed that the Market Constant results overestimate the impacts, because net of 

all these exogenous factors, the seafood industry was better off than if the market or price was 

held constant. In the end, it can be debated whether the industry impacts should be based on the 

end result of what they actually lost in revenue verses what they would have lost if all other 

factors were held constant. This is a discussion that we as researchers do not answer in this 

study. However, this is important to consider when interpreting the results of this report.

With any impact model, data processing takes time, and national accounts tend to lag by several 

years. In this case, the most up-to-date data for the IMPLAN multipliers available for this project 

was 2012. Furthermore, the USNM is based on 2000 IMPLAN data and much of the cost data 

used to create the production functions, product flows and margins is from older data sources. 

Without a massive undertaking of time and money to collect and compile that data for the Gulf 

region’s fisheries, the model must rely on these cost structures that are out of date. Many 

improvements have been made, as discussed above, but many more could be made. 

Unfortunately, those enhancements would entail expensive and time-consuming data collection. 

The impact of these older trade flows, margins, and cost structures is unknown. These 

relationships tend to change slowly and, therefore, the impact for the more recent data may be 

slight. Again, the only way to improve the model, to include more up-to-date data, would involve 

a large compilation of data across various sectors that was not feasible in this project.

This model does not examine the economic impact of any large shift in cost structures or trade 

flows induced by the oil spill. All the multipliers for the dealer, processing, market and restaurant 

sectors are from post-spill data. All of the multipliers for the harvesting and wholesale sectors 

were created using pre-spill data. Unlike a hurricane or other disaster that destroys physical 

plants or sinks boats, it is unlikely that this spill caused large shifts in technology. For instance, 

processing underwent significant technological and cost structure change after Hurricanes 

Katrina and Rita. Those types of technology shifts did not occur in response to the spill. 

However, some harvesters may have had to switch target species or travel farther to reach 

unclosed water. This no doubt had an impact on their production functions, but it is unknown 

how this may have impacted the multipliers. If they are substituting one input, say increased 

diesel, for another, perhaps less ice, it is unclear how that would change the multipliers. An 

examination of these changes was beyond the scope of this project and certainly beyond the data 

available. 
155

As with any model, this model is an abstraction. A certain level of aggregation is necessary, but 

that aggregation comes at the cost of granularity. The harvesting sectors used in this model are 

based on representative cost and earnings data for the most important species in the Gulf region. 

However, for the catch-all categories, the multipliers represent average technologies and average 

cost structures across a range of gear types. 

There is also uncertainty in the product flow estimates. They are not specific to each state, 

making the state-level estimates less certain than the Gulf region totals. Many improvements 

have been made over the USNM to represent the seafood supply chain as it exists in the Gulf. 

However, the available data has been exhausted and all previously documented caveats and 

concerns in the USNM remain beyond those improvements. 

Additionally, even though this model adds additional links in the seafood supply chain over the 

USNM, and allows those linkages to be complex, with products from each stage potentially 

jumping links in that chain, better product flow information would likely increase the impact 

estimates. Seafood product flow is complicated, and this model makes a number of simplifying 

assumptions that may skip multiple processing steps or market pathways that may exist. If this 

model is underestimating the number of links in this supply chain, then total impacts are being 

underestimated. Again, improving the trade flow data would require extensive surveys of the 

industry that are broader in scope and better subscribed than the Commission Reports. 

Because of the objectives and scope of this project, the review of I/O models shows that 

modifying IMPLAN and/or relying on base IMPLAN data and multipliers is the most flexible, 

most adaptable way to proceed. Within those approaches, adding new sectors to the base 

IMPLAN data is the best method, retaining all the IMPLAN functionality, but is cost-prohibitive 

and requires data that simply does not exist in the Gulf. Instead, spreadsheet models require less 

data and can be constructed more quickly. Though built external to IMPLAN, they are 

constructed using IMPLAN data and retain the ability to examine the impacts in the supply chain 

across the entities of concern to this project. However, they do not allow the disaggregation of 

those impacts to the ancillary industries. 

BOEM already uses spreadsheet-type impact models like the USNM. MAG-PLAN is a large, 

multi-region model that calculates the economic impact of oil and gas exploration and drilling 

operations in the Gulf. Its construction is very similar to the USNM. One benefit of these types 

of models is their scalability. New sectors can be added easily. As product flow data improves or 

changes, the model can be quickly modified to take advantage of the new or better information. 

CGE models, though not discussed in depth here, may be the ultimate phase for this impact 

modeling effort. They allow the examination of welfare effects and relax price, input, and 

demand substitution restrictions inherent with I/O analysis. However, due to data and budget 

limitations, CGE models are beyond the scope of this effort. It may be advisable for BOEM to 

pursue the construction of these types of models in future developments.
156

6.4 General Uses

Economic impact models produce positive, rather than normative, measures of the change in 

economic activity that results from a perturbation of the demand or production of a good or 

group of goods. A positive model cannot comment on whether these changes are better for 

society or worse for society. Instead, it gives simply a measure of the change in economic 

activity that resulted from changes in revenue from the spill. In much the same way, a 

thermometer measures temperature changes through the course of a storm, but does not itself tell 

the observer if that change in temperature is good or bad.

The focus here should not be on the ultimate numbers produced. This study could have estimated 

impact across a near-infinite number of potential revenue change scenarios. There are any 

numbers of justifications for examining changes using different base periods or looking at the 

present value of a stream of future reductions. The aim was to develop an upper and lower bound 

based on a fairly narrow impact window that included only the damage period. This does not 

mean that these results represent the definitive answer to the question of what was the loss in 

activity stemming from the oil spill. These scenarios were chosen strictly because they used the 

same periods used in the settlement agreement. Instead, it may be helpful to think of the results 

detailed here as measurements of economic “temperatures” as the result of “storm” that was the 

oil spill. The point is that the usefulness of this study is not about the absolute impact 

measurement or which estimate is right or wrong, but rather a demonstration that this work 

represents the creation of a flexible, adaptable model of the seafood supply chain that BOEM and 

others can use to analyze further scenarios related to any oil exploration, development, or 

disaster that BOEM feels might impact the seafood supply chain. 

Going forward, BOEM can use this model to quickly examine any activity under their purview 

that may have an impact on the seafood supply chain in the Gulf. Exploration and drilling 

activities may have impacts on the seafood supply chain and those impacts can now be estimated 

quickly and easily for use in future management of offshore mineral resources. In the event of 

another spill or in examining the risk of future spills, this model can make assessments quickly 

and easily. In the face of a future spill, using similar revenue change scenarios, losses in activity 

could be estimated in near real-time based on closure information. Future extensions would 

include estimating demand and supply relationships to forecast impacts at the early onset of a 

spill. That forecast model could be linked to this impact model to provide impact estimates 

quickly. If BOEM chooses to go further down this path, we recommend using the model 

developed to create a CGE model that would allow price dynamism and the calculation of 

welfare impacts.
157

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Appendix I. Tables of Supply Chain Multipliers by Species and State, 

Inclusive of Trade Flows and Margins

Alabama

Species Sector Economic 

Activity Direct Indirect Induced Total

Shrimp Harvester

Employment 0.0000339 0.0000014 0.0000032 0.0000384

Sales 0.9666627 0.2240365 0.3517429 1.5424421

Value Added 0.4789330 0.0641320 0.1700030 0.7130680

Income 0.4064782 0.0617001 0.1072458 0.5754241

Blue crab Harvester

Employment 0.0000125 0.0000014 0.0000062 0.0000201

Sales 0.6143070 0.2762882 0.8392597 1.7298549

Value Added 0.3576188 0.0798753 0.2598881 0.6973823

Income 0.3391104 0.1350218 0.1864866 0.6606188

Menhaden Harvester

Employment 0.0000162 0.0000016 0.0000059 0.0000237

Sales 0.6054416 0.3497251 0.8050697 1.7602364

Value Added 0.3276854 0.0936000 0.2493102 0.6705955

Income 0.3391104 0.1350218 0.1864866 0.6606188

Reef fish Harvester

Employment 0.0000113 0.0000015 0.0000059 0.0000187

Sales 0.5984202 0.3251572 0.8009360 1.7245134

Value Added 0.3260211 0.0895149 0.2479695 0.6635056

Income 0.3391104 0.1350218 0.1864866 0.6606188

Pelagic 

finfish Harvester

Employment 0.0000132 0.0000017 0.0000058 0.0000206

Sales 0.5960249 0.3358495 0.7873444 1.7192188

Value Added 0.3391104 0.1350218 0.1864866 0.6606188

Income 0.3164522 0.0946016 0.2437235 0.6547773

Bait Harvester

Employment 0.0000097 0.0000019 0.0000050 0.0000166

Sales 0.6289379 0.3942922 0.6866940 1.7099241

Value Added 0.3391104 0.1350218 0.1864866 0.6606188

Income 0.2626752 0.1097102 0.2123601 0.5847455

Other 

shellfish Harvester

Employment 0.0000120 0.0000014 0.0000060 0.0000194

Sales 0.6075021 0.2913910 0.8156346 1.7145277

Value Added 0.3413325 0.0817599 0.2525825 0.6756749

Income 0.3391104 0.1350218 0.1864866 0.6606188

Misc finfish Harvester

Employment 0.0000101 0.0000017 0.0000055 0.0000173

Sales 0.6164447 0.3584126 0.7440150 1.7188723

Value Added 0.3391104 0.1350218 0.1864866 0.6606188

Income 0.2954643 0.0993158 0.2302367 0.6250168

All species Dealer Employment 0.0000014 0.0000004 0.0000003 0.0000021

Sales 0.4772400 0.0291207 0.0317971 0.5381578
171

Species Sector Economic 

Activity Direct Indirect Induced Total

All species

Value Added 0.0424844 0.0148942 0.0196862 0.0770647

Income 0.0405339 0.0084529 0.0103475 0.0593343

Processor

Employment 0.0000019 0.0000011 0.0000005 0.0000035

Sales 0.6543987 0.0883883 0.0521222 0.7949092

Value Added 0.0582552 0.0456319 0.0322697 0.1361568

Income 0.0555807 0.0247853 0.0169640 0.0973300

Distributor

Employment 0.0000050 0.0000005 0.0000024 0.0000079

Sales 0.4740927 0.0620967 0.2686132 0.8048026

Value Added 0.1989961 0.1366047 0.1447595 0.4803603

Income 0.2962584 0.0186946 0.0822784 0.3972314

Market

Employment 0.0000078 0.0000008 0.0000013 0.0000099

Sales 0.4264513 0.0893160 0.1459585 0.6617258

Value Added 0.2982729 0.0551730 0.0930116 0.4464575

Income 0.2109233 0.0300102 0.0483967 0.2893302

Restaurant

Employment 0.0000070 0.0000007 0.0000013 0.0000090

Sales 0.3860405 0.0864955 0.1424235 0.6149595

Value Added 0.2083048 0.0552825 0.0681732 0.3317605

Income 0.1909360 0.0290225 0.0463534 0.2663120

Florida (West Coast)

Species Sector Economic 

Activity Direct Indirect Induced Total

Shrimp Harvester

Employment 0.0000221 0.0000018 0.0000036 0.0000276

Sales 0.9781490 0.3107369 0.4135884 1.7024743

Value Added 0.5122210 0.1042110 0.2525540 0.8689860

Income 0.4088788 0.0823676 0.1363208 0.6275672

Blue crab Harvester

Employment 0.0000125 0.0000014 0.0000062 0.0000201

Sales 0.6143070 0.2762882 0.8392597 1.7298549

Value Added 0.3576188 0.0798753 0.2598881 0.6973823

Income 0.3391104 0.1350218 0.1864866 0.6606188

Oysters Harvester

Employment 0.0000120 0.0000014 0.0000060 0.0000194

Sales 0.6075021 0.2913910 0.8156346 1.7145277

Value Added 0.3413325 0.0817599 0.2525825 0.6756749

Income 0.3391104 0.1350218 0.1864866 0.6606188

Menhaden Harvester

Employment 0.0000162 0.0000016 0.0000059 0.0000237

Sales 0.6054416 0.3497251 0.8050697 1.7602364

Value Added 0.3276854 0.0936000 0.2493102 0.6705955
172

Species Sector Economic 

Activity Direct Indirect Induced Total

Income 0.3391104 0.1350218 0.1864866 0.6606188

Reef fish Harvester

Employment 0.0000113 0.0000015 0.0000059 0.0000187

Sales 0.5984202 0.3251572 0.8009360 1.7245134

Value Added 0.3260211 0.0895149 0.2479695 0.6635056

Income 0.3391104 0.1350218 0.1864866 0.6606188

Pelagic 

finfish Harvester

Employment 0.0000132 0.0000017 0.0000058 0.0000206

Sales 0.5960249 0.3358495 0.7873444 1.7192188

Value Added 0.3391104 0.1350218 0.1864866 0.6606188

Income 0.3164522 0.0946016 0.2437235 0.6547773

Bait Harvester

Employment 0.0000097 0.0000019 0.0000050 0.0000166

Sales 0.6289379 0.3942922 0.6866940 1.7099241

Value Added 0.3391104 0.1350218 0.1864866 0.6606188

Income 0.2626752 0.1097102 0.2123601 0.5847455

Other 

crustaceans Harvester

Employment 0.0000094 0.0000019 0.0000049 0.0000162

Sales 0.6355971 0.4062471 0.6650747 1.7069188

Value Added 0.3391104 0.1350218 0.1864866 0.6606188

Income 0.2511355 0.1132601 0.2056249 0.5700205

Other 

shellfish Harvester

Employment 0.0000120 0.0000014 0.0000060 0.0000194

Sales 0.6075021 0.2913910 0.8156346 1.7145277

Value Added 0.3413325 0.0817599 0.2525825 0.6756749

Income 0.3391104 0.1350218 0.1864866 0.6606188

Misc. finfish Harvester

Employment 0.0000101 0.0000017 0.0000055 0.0000173

Sales 0.6164447 0.3584126 0.7440150 1.7188723

Value Added 0.3391104 0.1350218 0.1864866 0.6606188

Income 0.2954643 0.0993158 0.2302367 0.6250168

All species

Dealer

Employment 0.0000031 0.0000006 0.0000000 0.0000037

Sales 0.4772400 0.0559721 0.0298227 0.5630349

Value Added 0.0243240 0.0327387 0.0188643 0.0759270

Income 0.0133136 0.0203209 0.0104640 0.0440984

Processor

Employment 0.0000039 0.0000012 0.0000005 0.0000056

Sales 0.6543987 0.1373256 0.0572802 0.8490044

Value Added 0.0333534 0.0770770 0.0362308 0.1466612

Income 0.0182558 0.0460500 0.0200913 0.0843971

Distributor

Employment 0.0000051 0.0000006 0.0000027 0.0000084

Sales 0.4740927 0.0773138 0.3081427 0.8595491

Value Added 0.1989961 0.1366047 0.1447595 0.4803603
173

Species Sector Economic 

Activity Direct Indirect Induced Total

All species

Income 0.2988335 0.0259444 0.1016869 0.4264648

Market

Employment 0.0000074 0.0000010 0.0000020 0.0000104

Sales 0.4264513 0.1325479 0.2445101 0.8035094

Value Added 0.3040125 0.0862579 0.1546999 0.5449703

Income 0.2256021 0.0473655 0.0857449 0.3587125

Restaurant

Employment 0.0000063 0.0000009 0.0000015 0.0000087

Sales 0.3860405 0.1350146 0.1796864 0.7007415

Value Added 0.2280392 0.0799150 0.1136874 0.4216416

Income 0.1566927 0.0438299 0.0630115 0.2635340

Louisiana

Species Sector Economic 

Activity Direct Indirect Induced Total

Shrimp Harvester

Employment 0.0000251 0.0000014 0.0000034 0.0000299

Sales 0.9754093 0.2315655 0.3613721 1.5683469

Value Added 0.4538010 0.1960040 0.1994690 0.8492740

Income 0.4089262 0.0597568 0.1126051 0.5812881

Blue crab Harvester

Employment 0.0000125 0.0000014 0.0000062 0.0000201

Sales 0.6143070 0.2762882 0.8392597 1.7298549

Value Added 0.3576188 0.0798753 0.2598881 0.6973823

Income 0.3391104 0.1350218 0.1864866 0.6606188

Oysters Harvester

Employment 0.0000120 0.0000014 0.0000060 0.0000194

Sales 0.6075021 0.2913910 0.8156346 1.7145277

Value Added 0.3413325 0.0817599 0.2525825 0.6756749

Income 0.3391104 0.1350218 0.1864866 0.6606188

Menhaden Harvester

Employment 0.0000162 0.0000016 0.0000059 0.0000237

Sales 0.6054416 0.3497251 0.8050697 1.7602364

Value Added 0.3276854 0.0936000 0.2493102 0.6705955

Income 0.3391104 0.1350218 0.1864866 0.6606188

Reef fish Harvester

Employment 0.0000113 0.0000015 0.0000059 0.0000187

Sales 0.5984202 0.3251572 0.8009360 1.7245134

Value Added 0.3260211 0.0895149 0.2479695 0.6635056

Income 0.3391104 0.1350218 0.1864866 0.6606188

Pelagic 

finfish Harvester

Employment 0.0000132 0.0000017 0.0000058 0.0000206

Sales 0.5960249 0.3358495 0.7873444 1.7192188

Value Added 0.3391104 0.1350218 0.1864866 0.6606188

Income 0.3164522 0.0946016 0.2437235 0.6547773
174

Species Sector Economic 

Activity Direct Indirect Induced Total

Bait Harvester

Employment 0.0000097 0.0000019 0.0000050 0.0000166

Sales 0.6289379 0.3942922 0.6866940 1.7099241

Value Added 0.3391104 0.1350218 0.1864866 0.6606188

Income 0.2626752 0.1097102 0.2123601 0.5847455

Other 

crustaceans Harvester

Employment 0.0000094 0.0000019 0.0000049 0.0000162

Sales 0.6355971 0.4062471 0.6650747 1.7069188

Value Added 0.3391104 0.1350218 0.1864866 0.6606188

Income 0.2511355 0.1132601 0.2056249 0.5700205

Other 

shellfish Harvester

Employment 0.0000120 0.0000014 0.0000060 0.0000194

Sales 0.6075021 0.2913910 0.8156346 1.7145277

Value Added 0.3413325 0.0817599 0.2525825 0.6756749

Income 0.3391104 0.1350218 0.1864866 0.6606188

Misc. finfish Harvester

Employment 0.0000101 0.0000017 0.0000055 0.0000173

Sales 0.6164447 0.3584126 0.7440150 1.7188723

Value Added 0.3391104 0.1350218 0.1864866 0.6606188

Income 0.2954643 0.0993158 0.2302367 0.6250168

All species

Dealer

Employment 0.0000031 0.0000006 0.0000005 0.0000042

Sales 0.4772400 0.0367914 0.0595080 0.5735394

Value Added 0.0906131 0.0177691 0.0367556 0.1451378

Income 0.0737364 0.0118327 0.0199434 0.1055125

Processor

Employment 0.0000039 0.0000008 0.0000008 0.0000056

Sales 0.6543987 0.0738103 0.0849750 0.8131839

Value Added 0.1242533 0.0384040 0.0524782 0.2151355

Income 0.1011079 0.0210003 0.0284729 0.1505811

Distributor

Employment 0.0000050 0.0000005 0.0000026 0.0000082

Sales 0.4606349 0.0532855 0.2673772 0.7812975

Value Added 0.1989961 0.1366047 0.1447595 0.4803603

Income 0.2981619 0.0164221 0.0877405 0.4023245

Market

Employment 0.0000077 0.0000007 0.0000014 0.0000097

Sales 0.4264513 0.0871893 0.1534841 0.6671247

Value Added 0.2998678 0.0538113 0.0973435 0.4510226

Income 0.2108930 0.0286554 0.0524019 0.2919503

Restaurant

Employment 0.0000069 0.0000007 0.0000011 0.0000087

Sales 0.3860405 0.1117695 0.1276439 0.6254540

Value Added 0.2143150 0.0608199 0.0789005 0.3540355

Income 0.1505782 0.0332589 0.0428042 0.2266413
175

Mississippi

Species Sector Economic 

Activity Direct Indirect Induced Total

Shrimp Harvester

Employment 0.0000201 0.0000013 0.0000032 0.0000246

Sales 0.5608192 0.9679633 0.2166960 1.7454785

Value Added 0.5251030 0.0628320 0.1841100 0.7720450

Income 0.4088737 0.0512355 0.1007100 0.5608192

Blue crab Harvester

Employment 0.0000125 0.0000014 0.0000062 0.0000201

Sales 0.6143070 0.2762882 0.8392597 1.7298549

Value Added 0.3576188 0.0798753 0.2598881 0.6973823

Income 0.3391104 0.1350218 0.1864866 0.6606188

Oysters Harvester

Employment 0.0000120 0.0000014 0.0000060 0.0000194

Sales 0.6075021 0.2913910 0.8156346 1.7145277

Value Added 0.3413325 0.0817599 0.2525825 0.6756749

Income 0.3391104 0.1350218 0.1864866 0.6606188

Menhaden Harvester

Employment 0.0000162 0.0000016 0.0000059 0.0000237

Sales 0.6054416 0.3497251 0.8050697 1.7602364

Value Added 0.3276854 0.0936000 0.2493102 0.6705955

Income 0.3391104 0.1350218 0.1864866 0.6606188

Bait Harvester

Employment 0.0000097 0.0000019 0.0000050 0.0000166

Sales 0.6289379 0.3942922 0.6866940 1.7099241

Value Added 0.3391104 0.1350218 0.1864866 0.6606188

Income 0.2626752 0.1097102 0.2123601 0.5847455

Other 

shellfish Harvester

Employment 0.0000120 0.0000014 0.0000060 0.0000194

Sales 0.6075021 0.2913910 0.8156346 1.7145277

Value Added 0.3413325 0.0817599 0.2525825 0.6756749

Income 0.3391104 0.1350218 0.1864866 0.6606188

Misc.

finfish Harvester

Employment 0.0000101 0.0000017 0.0000055 0.0000173

Sales 0.6164447 0.3584126 0.7440150 1.7188723

Value Added 0.3391104 0.1350218 0.1864866 0.6606188

Income 0.2954643 0.0993158 0.2302367 0.6250168

All species

Dealer

Employment 0.0000031 0.0000005 0.0000003 0.0000039

Sales 0.4772400 0.0354551 0.0355448 0.5482399

Value Added 0.0495179 0.0180440 0.0217039 0.0892658

Income 0.0459367 0.0098569 0.0111545 0.0669482

Processor

Employment 0.0000039 0.0000014 0.0000005 0.0000059

Sales 0.6543987 0.1146356 0.0582866 0.8273209

Value Added 0.0678997 0.0585602 0.0355901 0.1620500

Income 0.0629891 0.0284618 0.0182911 0.1097420
176

Species Sector Economic 

Activity Direct Indirect Induced Total

All species

Distributor

Employment 0.0000051 0.0000005 0.0000025 0.0000080

Sales 0.4740927 0.0601765 0.2670535 0.8013227

Value Added 0.1989961 0.1366047 0.1447595 0.4803603

Income 0.2996701 0.0163901 0.0795283 0.3955885

Market

Employment 0.0000074 0.0000006 0.0000013 0.0000093

Sales 0.4264513 0.0744414 0.1379916 0.6388843

Value Added 0.3039767 0.0449305 0.0867172 0.4356243

Income 0.2115826 0.0220505 0.0440503 0.2776834

Restauran

t

Employment 0.0000073 0.0000007 0.0000009 0.0000090

Sales 0.3860405 0.1013874 0.1060341 0.5934620

Value Added 0.2040120 0.0526922 0.0648247 0.3215289

Income 0.1388345 0.0281370 0.0333149 0.2002863

Texas

Species Sector Economic 

Activity Direct Indirect Induced Total

Shrimp Harvester

Employment 0.0000150 0.0000017 0.0000036 0.0000203

Sales 0.9794106 0.4185381 0.4567722 1.8547210

Value Added 0.5122210 0.1042110 0.2525540 0.8689860

Income 0.4022475 0.1142126 0.1384403 0.6549005

Blue crab Harvester

Employment 0.0000125 0.0000014 0.0000062 0.0000201

Sales 0.6143070 0.2762882 0.8392597 1.7298549

Value Added 0.3576188 0.0798753 0.2598881 0.6973823

Income 0.3391104 0.1350218 0.1864866 0.6606188

Oysters Harvester

Employment 0.0000120 0.0000014 0.0000060 0.0000194

Sales 0.6075021 0.2913910 0.8156346 1.7145277

Value Added 0.3413325 0.0817599 0.2525825 0.6756749

Income 0.3391104 0.1350218 0.1864866 0.6606188

Reef fish Harvester

Employment 0.0000113 0.0000015 0.0000059 0.0000187

Sales 0.5984202 0.3251572 0.8009360 1.7245134

Value Added 0.3260211 0.0895149 0.2479695 0.6635056

Income 0.3391104 0.1350218 0.1864866 0.6606188

Pelagic 

finfish Harvester

Employment 0.0000132 0.0000017 0.0000058 0.0000206

Sales 0.5960249 0.3358495 0.7873444 1.7192188

Value Added 0.3391104 0.1350218 0.1864866 0.6606188

Income 0.3164522 0.0946016 0.2437235 0.6547773

Bait Harvester Employment 0.0000097 0.0000019 0.0000050 0.0000166

Sales 0.6289379 0.3942922 0.6866940 1.7099241
177

Species Sector Economic 

Activity Direct Indirect Induced Total

Value Added 0.3391104 0.1350218 0.1864866 0.6606188

Income 0.2626752 0.1097102 0.2123601 0.5847455

Other 

crustaceans Harvester

Employment 0.0000094 0.0000019 0.0000049 0.0000162

Sales 0.6355971 0.4062471 0.6650747 1.7069188

Value Added 0.3391104 0.1350218 0.1864866 0.6606188

Income 0.2511355 0.1132601 0.2056249 0.5700205

Other 

shellfish Harvester

Employment 0.0000120 0.0000014 0.0000060 0.0000194

Sales 0.6075021 0.2913910 0.8156346 1.7145277

Value Added 0.3413325 0.0817599 0.2525825 0.6756749

Income 0.3391104 0.1350218 0.1864866 0.6606188

Misc. finfish Harvester

Employment 0.0000101 0.0000017 0.0000055 0.0000173

Sales 0.6164447 0.3584126 0.7440150 1.7188723

Value Added 0.3391104 0.1350218 0.1864866 0.6606188

Income 0.2954643 0.0993158 0.2302367 0.6250168

All species

Dealer

Employment 0.0000029 0.0000001 0.0000004 0.0000033

Sales 0.4772400 0.0171234 0.0468211 0.5411844

Value Added 0.0555732 0.0101452 0.0292119 0.0949302

Income 0.0498935 0.0058925 0.0161751 0.0719611

Processor

Employment 0.0000039 0.0000006 0.0000006 0.0000051

Sales 0.6543987 0.0796658 0.0804217 0.8144862

Value Added 0.0762028 0.0472064 0.0501754 0.1735845

Income 0.0684148 0.0274206 0.0277831 0.1236185

Distributor

Employment 0.0000050 0.0000006 0.0000025 0.0000081

Sales 0.4740927 0.0893119 0.3183330 0.8817376

Value Added 0.1989961 0.1366047 0.1447595 0.4803603

Income 0.2962891 0.0277689 0.0965431 0.4206011

Market

Employment 0.0000072 0.0000009 0.0000017 0.0000097

Sales 0.4264513 0.1243029 0.2259736 0.7767278

Value Added 0.3081145 0.0809780 0.1409605 0.5300530

Income 0.2246064 0.0448013 0.0769148 0.3463224

Restaurant

Employment 0.0000065 0.0000009 0.0000012 0.0000086

Sales 0.3860405 0.1484021 0.1619733 0.6964160

Value Added 0.2241347 0.0808110 0.1010380 0.4059838

Income 0.1470309 0.0459859 0.0559485 0.2489653
178

Total Gulf

Species Sector Economic 

Activity Direct Indirect Induced Total

Shrimp Harvester

Employment 0.0000143 0.0000028 0.0000073 0.0000243

Sales 0.9255327 0.5746010 0.9941932 2.4943269

Value Added 0.4968370 0.1978230 0.2732250 0.9678850

Income 0.3716233 0.1609359 0.3075290 0.8400882

Blue crab Harvester

Employment 0.0000183 0.0000021 0.0000090 0.0000294

Sales 0.9000327 0.4047951 1.2296150 2.5344428

Value Added 0.5239540 0.1170268 0.3807670 1.0217478

Income 0.4968370 0.1978230 0.2732250 0.9678850

Oysters Harvester

Employment 0.0000176 0.0000021 0.0000088 0.0000285

Sales 0.8900627 0.4269224 1.1950015 2.5119866

Value Added 0.5000926 0.1197880 0.3700633 0.9899439

Income 0.4968370 0.1978230 0.2732250 0.9678850

Menhaden Harvester

Employment 0.0000237 0.0000024 0.0000087 0.0000348

Sales 0.8870438 0.5123888 1.1795227 2.5789553

Value Added 0.4800979 0.1371351 0.3652690 0.9825020

Income 0.4968370 0.1978230 0.2732250 0.9678850

Reef fish Harvester

Employment 0.0000165 0.0000023 0.0000086 0.0000274

Sales 0.8767566 0.4763939 1.1734664 2.5266168

Value Added 0.4776597 0.1311500 0.3633048 0.9721144

Income 0.4968370 0.1978230 0.2732250 0.9678850

Pelagic 

finfish Harvester

Employment 0.0000193 0.0000024 0.0000085 0.0000302

Sales 0.8732472 0.4920594 1.1535530 2.5188595

Value Added 0.4968370 0.1978230 0.2732250 0.9678850

Income 0.4636400 0.1386026 0.3570838 0.9593264

Bait Harvester

Employment 0.0000142 0.0000027 0.0000074 0.0000243

Sales 0.9214687 0.5776849 1.0060881 2.5052418

Value Added 0.4968370 0.1978230 0.2732250 0.9678850

Income 0.3848504 0.1607384 0.3111327 0.8567215

Other 

crustaceans Harvester

Employment 0.0000137 0.0000028 0.0000071 0.0000237

Sales 0.9312252 0.5952001 0.9744133 2.5008387

Value Added 0.4968370 0.1978230 0.2732250 0.9678850

Income 0.3679433 0.1659395 0.3012648 0.8351477

Other 

shellfish Harvester

Employment 0.0000176 0.0000021 0.0000088 0.0000285

Sales 0.8900627 0.4269224 1.1950015 2.5119866

Value Added 0.5000926 0.1197880 0.3700633 0.9899439

Income 0.4968370 0.1978230 0.2732250 0.9678850
179

Misc. finfish Harvester

Employment 0.0000149 0.0000025 0.0000080 0.0000253

Sales 0.9031646 0.5251170 1.0900702 2.5183519

Value Added 0.4968370 0.1978230 0.2732250 0.9678850

Income 0.4328902 0.1455095 0.3373241 0.9157238

All species

Dealer

Employment 0.0000029 0.0000004 0.0000005 0.0000037

Sales 0.4772400 0.0334579 0.0609421 0.5716400

Value Added 0.0640227 0.0175925 0.0374123 0.1190275

Income 0.0559488 0.0109885 0.0205218 0.0874590

Processor

Employment 0.0000039 0.0000010 0.0000008 0.0000057

Sales 0.6543987 0.0988443 0.0984811 0.8517241

Value Added 0.0877889 0.0534493 0.0604566 0.2016948

Income 0.0767178 0.0314511 0.0331636 0.1413324

Distributor

Employment 0.0000051 0.0000010 0.0000049 0.0000109

Sales 0.4740927 0.1642962 0.6649981 1.3033870

Value Added 0.2996763 0.0503103 0.2059001 0.5558867

Income 0.1989961 0.1366047 0.1447595 0.4803603

Market

Employment 0.0000073 0.0000008 0.0000017 0.0000099

Sales 0.4264513 0.1154587 0.2135199 0.7554300

Value Added 0.3051878 0.0739305 0.1358482 0.5149664

Income 0.2226375 0.0395427 0.0736264 0.3358066

Restaurant

Employment 0.0000066 0.0000009 0.0000014 0.0000088

Sales 0.3860405 0.1523119 0.2213294 0.7596818

Value Added 0.2228759 0.0828987 0.1094722 0.4152468

Income 0.1498258 0.0460693 0.0600420 0.2559372
The Department of the Interior Mission

As the Nation's principal conservation agency, the Department of the Interior has

responsibility for most of our nationally owned public lands and natural

resources. This includes fostering sound use of our land and water resources;

protecting our fish, wildlife, and biological diversity; preserving the

environmental and cultural values of our national parks and historical places; and

providing for the enjoyment of life through outdoor recreation. The Department

assesses our energy and mineral resources and works to ensure that their

development is in the best interests of all our people by encouraging stewardship

and citizen participation in their care. The Department also has a major

responsibility for American Indian reservation communities and for people who

live in island territories under U.S. administration.

The Bureau of Ocean Energy Management

As a bureau of the Department of the Interior, the Bureau of Ocean Energy

(BOEM) primary responsibilities are to manage the mineral resources located on

the Nation's Outer Continental Shelf (OCS) in an environmentally sound and safe

manner.

The BOEM Environmental Studies Program

The mission of the Environmental Studies Program (ESP) is to provide the

information needed to predict, assess, and manage impacts from offshore energy

and marine mineral exploration, development, and production activities on

human, marine, and coastal environments.