EPA 910-R-14-001C | January 2014 

An Assessment of Potential Mining Impacts 

on Salmon Ecosystems of Bristol Bay, Alaska 

Volume 3 – Appendices E-J 

Region 10, Seattle, WA

www.epa.gov/bristolbay
EPA 910-R-14-001C 

January 2014

AN ASSESSMENT OF POTENTIAL MINING IMPACTS ON 

SALMON ECOSYSTEMS OF BRISTOL BAY, ALASKA 

VOLUME 3—APPENDICES E-J

U.S. Environmental Protection Agency

Region 10

Seattle, WA
CONTENTS 

VOLUME 1 

An Assessment of Potential Mining Impacts on Salmon Ecosystems of Bristol Bay, Alaska

VOLUME 2

APPENDIX A: Fishery Resources of the Bristol Bay Region

APPENDIX B: Non-Salmon Freshwater Fishes of the Nushagak and Kvichak River Drainages

APPENDIX C: Wildlife Resources of the Nushagak and Kvichak River Watersheds, Alaska 

APPENDIX D: Traditional Ecological Knowledge and Characterization of the Indigenous 

Cultures of the Nushagak and Kvichak Watersheds, Alaska

VOLUME 3

APPENDIX E: Bristol Bay Wild Salmon Ecosystem: Baseline Levels of Economic Activity and 

Values

APPENDIX F: Biological Characterization: Bristol Bay Marine Estuarine Processes, Fish, and 

Marine Mammal Assemblages 

APPENDIX G: Foreseeable Environmental Impact of Potential Road and Pipeline 

Development on Water Quality and Freshwater Fishery Resources of Bristol Bay, Alaska 

APPENDIX H: Geologic and Environmental Characteristics of Porphyry Copper Deposits 

with Emphasis on Potential Future Development in the Bristol Bay Watershed, Alaska

APPENDIX I: Conventional Water Quality Mitigation Practices for Mine Design, 

Construction, Operation, and Closure

APPENDIX J: Compensatory Mitigation and Large-Scale Hardrock Mining in the Bristol Bay 

Watershed
AN ASSESSMENT OF POTENTIAL MINING IMPACTS ON 

SALMON ECOSYSTEMS OF BRISTOL BAY, ALASKA 

VOLUME 3—APPENDICES E-J

Appendix E: Bristol Bay Wild Salmon Ecosystem: Baseline 

Levels of Economic Activity and Values 
Bristol Bay Wild Salmon Ecosystem

Baseline Levels of Economic Activity and Values 

John Duffield

Chris Neher 

David Patterson

Bioeconomics, Inc. Missoula, MT

Gunnar Knapp 

Institute of Social and Economic Research—University of Alaska 

Anchorage

Tobias Schwörer

Ginny Fay

Oliver Scott Goldsmith

Institute of Social and Economic Research

University of Alaska Anchorage

December 2013

For: 

NatureServe

Conservation Services Division

 
Contents 

..................................................................................................................................................... 1

Contents .......................................................................................................................................... 2

List of Tables .................................................................................................................................. 4

List of Figures ................................................................................................................................. 7

Executive Summary ........................................................................................................................ 9

Subsistence and Village Economies ......................................................................................... 11

Commercial Fisheries ............................................................................................................... 14

Recreation ................................................................................................................................. 17

Summary of Economic Significance ........................................................................................ 17

Net Economic Values ............................................................................................................... 22

1.0 Introduction and Setting .......................................................................................................... 28

1.1 Study Objectives and Report Organization ......................................................................... 28

1.2 Definition of Study Area ..................................................................................................... 29

1.3 Focus of Study-Economic Uses .......................................................................................... 32

2.0 Bristol Bay Recreation and Subsistence Economics .............................................................. 35

2.1 Bristol Bay Sportfishing Economics ................................................................................... 35

2.1.1 Bristol Bay Area Trip Characteristics and Angler Attitudes ........................................... 35

2.1.2 Bristol Bay Angler Expenditures ..................................................................................... 38

2.1.3 Aggregate Direct Sport fishing Expenditures in Bristol Bay........................................... 40

2.2 Bristol Bay Subsistence Harvest Economics .......................................................................... 42

2.3 Bristol Bay Sport Hunting and Non-consumptive Economics ............................................... 47

2.3.1 Sport Hunting ................................................................................................................... 47

2.3.2 Non-consumptive Wildlife Viewing / Tourism Economics ............................................ 48

3.0 Bristol Bay Commercial Fisheries .......................................................................................... 51

3.1 Introduction ......................................................................................................................... 51

3.2 Overview of the Bristol Bay Salmon Industry .................................................................... 52

3.3 Bristol Bay Salmon Harvests .............................................................................................. 57

3.4 Bristol Bay Salmon Products and Markets ......................................................................... 71

3.5 Bristol Bay Salmon Prices .................................................................................................. 80

3.6 Bristol Bay Salmon Ex-Vessel and Wholesale Value ........................................................ 92

3.7 Bristol Bay Salmon Fishermen ........................................................................................... 96

3.8 Bristol Bay Salmon Processors ......................................................................................... 105

3.9 Bristol Bay Salmon Industry Employment ....................................................................... 109

3.10 Bristol Bay Salmon Industry Taxes ................................................................................ 117

3.11 Regional Distribution of Bristol Bay Permit Holders, Fishery Earnings, and Processing 

Employment ............................................................................................................................ 119

3.12 Distribution of Salmon Permits and Earnings within The Bristol Bay Region .............. 129

3.13 Economic Measures of the Bristol Bay Salmon Industry ............................................... 137

3.14 Bristol Bay Commercial Fisheries: Summary ................................................................ 144

3.15 Appendix: Data Sources ................................................................................................ 153

4.0 Economic Significance of Healthy Salmon Ecosystems in the Bristol Bay Region: Summary 

Findings....................................................................................................................................... 171

4.1 Introduction ....................................................................................................................... 173

4.2 Methods............................................................................................................................. 174

2 
4.3 Regional Economic Overview .......................................................................................... 178

4.4 Commercial Salmon Fisheries .......................................................................................... 182

4.5 Recreation ......................................................................................................................... 184

4.5.1 Non-Consumptive Use ............................................................................................... 187

4.5.2 Sport Fishing .............................................................................................................. 188

4.5.3 Sport Hunting ............................................................................................................. 189

4.6 Subsistence ........................................................................................................................ 190

4.7 Conclusions ....................................................................................................................... 191

4.8 Key Assumptions and Uncertainties ................................................................................. 193

4.9 Data Sources .................................................................................................................... 196

5.0 Bristol Bay Net Economic Values ........................................................................................ 199

5.1 Commercial Fisheries ....................................................................................................... 199

5.2 Subsistence Harvest .......................................................................................................... 202

5.3 Sport Fishing Net Economic Value .................................................................................. 208

5.4 Sport Hunting Net Economic Value ................................................................................. 210

5.5 Wildlife Viewing and Tourism Net Economic Value ....................................................... 211

5.6 Total Net Economic Value and Present Value and Inter-temporal Issues ........................ 211

References ................................................................................................................................... 217

3 
List of Tables

Table 1. Bristol Bay Area Communities, Populations, and Subsistence Harvest ......................... 12

Table 2. Selected Economic Measures of the Bristol Bay Commercial Salmon Industry, 2000-

2010............................................................................................................................................... 16

Table 3. Summary of Regional Economic Expenditures Based on Wild Salmon Ecosystem 

Services (Million 2009 $) ............................................................................................................. 18

Table 4. Total Estimated Recreational Direct Spending in Alaska Attributable to Bristol Bay 

Wild Salmon Ecosystems, 2009 ................................................................................................... 19

Table 5. Cash Economy Full-time Equivalent Employment Count by Place of Work in the 

Bristol Bay Region, 2009 .............................................................................................................. 20

Table 6. Cash Economy Estimated Economic Significance of Bristol Bay Ecosystems ............. 21

Table 7. Summary of Bristol Bay Wild Salmon Ecosystem Services, Net Economic Value per 

Year (Million 2009 $) ................................................................................................................... 27

Table 8. Estimated Net Present Value of Bristol Bay Ecosystem Net Economic Use Values and 

Alternative Assumed Perpetual Discount Rates ........................................................................... 27

Table 9. Demographic and Socioeconomic Characteristics of the Bristol Bay Region ............... 29

Table 10. Bristol Bay Area Communities and Populations .......................................................... 30

Table 11: Types of Ecosystem Services ...................................................................................... 33

Table 12. Bristol Bay Angler Distribution across Trip Types, by Residency .............................. 36

Table 13: Bristol Bay Angler Trip Characteristics. ..................................................................... 37

Table 14: Bristol Bay Angler Survey, Targeted Species. ............................................................ 37

Table 15: Bristol Bay Angler Rating of Selected Attributes of Fishing Trip .............................. 38

Table 16. Nonresident Trips to Bristol Bay Waters, Mean Expenditure Per Trip Estimates By 

Trip Type ...................................................................................................................................... 39

Table 17: Distribution of Trip Expenditures across Spending Categories, by Residency and Area

....................................................................................................................................................... 39

Table 18. Estimated 2009 Bristol Bay area angler trips, by Angler Residency ............................ 40

Table 19. Estimated Aggregate Spending Associated with Sportfishing in the Bristol Bay Region 

(2009 dollars) ................................................................................................................................ 41

Table 20. Bristol Bay Sportfishing: Aggregate in and out of Region and State Spending (2009) 41

Table 21. ADF&G Division of Subsistence Average Per Capita Subsistence Harvest for Bristol 

Bay Communities.......................................................................................................................... 43

Table 22. Historical Subsistence Salmon Harvest for Bristol Bay, Alaska: 1975-2007 (ADF&G 

Division of Subsistence ASFDB) ................................................................................................. 45

Table 23. Bristol Bay Subsistence Salmon Harvests by District and Location Fished, 2007. .... 46

Table 24. Estimated Total Annual Bristol Bay Area Subsistence-Related Expenditures (2009 $)

....................................................................................................................................................... 47

Table 25. ADF&G Reported Big Game Hunting in Bristol Bay and Alaska Peninsula Game 

Management Units ........................................................................................................................ 48

Table 26. Estimated annual big game hunting expenditures for Bristol Bay region .................... 48

Table 27. Comparison of Bristol Bay Drift Gillnet and Set Gillnet Fisheries (2006-10 Average)

....................................................................................................................................................... 64

Table 28. Sales of Selected Sockeye Salmon Products. ............................................................... 73

Table 29. Selected Indicators of Participation in 2009 Drift Gillnet Fishery ............................... 98

4 
Table 30. Estimated Number of 2009 Drift Gillnet Permit Holders who Fished Alone, With 

another Permit Holder, or Did Not Fish........................................................................................ 99

Table 31. Estimates of Bristol Bay Processor Costs, Prices and Profits ..................................... 107

Table 32. Indicators and Estimates of Bristol Bay Salmon Industry Fishing Processing 

Employment ................................................................................................................................ 112

Table 33. Monthly Employment in Food Manufacturing, by Borough or Census Area. ........... 116

Table 34. Selected Data and Estimates for Bristol Bay Salmon Taxes ...................................... 118

Table 35. Comparison of Vessels Used in the Bristol Bay Drift Gillnet Fishery, by Residency of 

Permit Holder .............................................................................................................................. 123

Table 36. Participation and Gross Earnings in Bristol Bay Salmon Fisheries............................ 128

Table 37. Population, Permit Holders, and Salmon Earnings, by Community: 2000 & 2010 ... 130

Table 38. Salmon Permit Holders per 100 Residents, by Community ....................................... 134

Table 39. Bristol Bay Salmon Fishery Earnings, by Community............................................... 136

Table 40. Economic Measures of Bristol Bay Salmon Industry: Sockeye Salmon Harvests ..... 138

Table 41. Economic Measures of Bristol Bay Salmon Industry: Sockeye Value ...................... 139

Table 42. Economic Measures of the Bristol Bay Salmon Industry: Export Value. .................. 141

Table 43. Economic Measures of the Bristol Bay Salmon Industry: Employment .................... 142

Table 44. Economic Measures of the Bristol Bay Salmon Industry: Permit Prices and Values. 

(Source: www.cfec.state.ak.us/bit/MNUSALM.htm ) ................................................................ 143

Table 45. Distribution of Harvests for Bristol Bay Fishing Districts, 1986-2010 ...................... 146

Table 46. Geographic Distribution of Bristol Bay Salmon Industry Employment and Earnings.

..................................................................................................................................................... 150

Table 47. Relative Indicators of 2010 Salmon Fishery Participation and Earnings. .................. 151

Table 48. Selected Economic Measures of the Bristol Bay Salmon Industry, 2000-2010. ........ 152

Table 49. Distribution of Selected Economic Measures for the Bristol Bay Commercial Salmon 

Fishing Industry, 1980-2010 ....................................................................................................... 153

Table 50. Estimated Economic Significance of Bristol Bay Ecosystems ................................... 172

Table 51. Annual average jobs associated with $1 million in spending in each sector in 

Southwest Alaska, 2009 .............................................................................................................. 176

Table 52. Annual payroll associated with $1 million in spending in each sector in Southwest 

Alaska, 2009 ............................................................................................................................... 177

Table 53. Employment Count by Place of Work in the Bristol Bay Region, 2009 .................... 179

Table 54. Federal Spending in the Bristol Bay Region, 2009 ($000) ......................................... 179

Table 55. Estimated Residence of Workers in the Bristol Bay Region 2009 ............................. 180

Table 56. Estimated Personal Income in the Bristol Bay Region, 2009 (000$) ....................... 181

Table 57. Estimated Economic Significance of Commercial Fishing ........................................ 183

Table 58. Estimated Recreational Visitors and Expenditures in the Bristol Bay Region, 2009 . 185

Table 59. Estimated Economic Significance of All Recreation ................................................. 186

Table 60. Estimated Economic Significance of Non-Consumptive Use .................................... 187

Table 61. Estimated Economic Significance of Sport Fishing ................................................... 188

Table 62. Estimated Economic Significance of Sport Hunting .................................................. 189

Table 63. Estimated Economic Significance of Subsistence ...................................................... 190

Table 64. Estimated Economic Significance of Bristol Bay Ecosystems ................................... 192

Table 65. Current Bristol Bay Salmon Fishing Permit Numbers and sale prices, 2011 ............. 200

Table 66. Estimation of Total 2011 Net Income for the Bristol Bay Salmon Harvest and 

Processing Sectors based on Reported 1990-2001 Net Income (Link et al. 2003). .................... 202

5 
Table 67. Estimated Two-Stage Least Squares Wage Compensating Differential Model of 

Subsistence Harvest in 90 Alaska Communities (Duffield 1997). ............................................. 205

Table 68. Estimated Total Annual Bristol Bay Subsistence Harvest (usable pounds of harvest)

..................................................................................................................................................... 207

Table 69. Estimated Net Economic Annual Value of Bristol Bay Area Subsistence Harvest ... 208

Table 71: Estimated Mean Willingness to Pay for Anglers’ Recent Trip to Bristol Bay .......... 209

Table 72. Estimated Willingness to Pay for Sportfishing Fishing in the Bristol Bay Region .... 210

Table 73. Estimated annual big game hunting net economic value for Bristol Bay region ....... 210

Table 74. Summary of Bristol Bay Wild Salmon Ecosystem Services, Net Economic Value per 

Year (Million 2009 $) ................................................................................................................. 214

Table 75. Estimated Net Present Value of Bristol Bay Ecosystem Net Economic Use Values and 

Alternative Assumed Perpetual Discount Rates ......................................................................... 216

6 
List of Figures

Figure 1. Map of Bristol Bay Study Area ..................................................................................... 11

Figure 2. Bristol Bay Area Location and Major Communities .................................................... 13

Figure 3. Bristol Bay Area Commercial Salmon Fishery Management Districts ........................ 14

Figure 4. Selected Bristol Bay Salmon Processor Costs: 2001-2009 ........................................... 24

Figure 5. Flows of Ecosystem Services (adapted from (National Research Council 2005)) ....... 25

Figure 6. Bristol Bay Area Location and Major Communities .................................................... 30

Figure 7. Map of Bristol Bay Study Area .................................................................................... 32

Figure 8. Comparison of Resident and Nonresident Bristol Bay Angler Trip Types .................. 36

Figure 9. Distribution of Bristol Bay Subsistence Harvest .......................................................... 43

Figure 10. Major Bristol Bay River Systems ................................................................................ 53

Figure 11. Bristol Bay Commercial Salmon Harvests. ................................................................. 57

Figure 12. Bristol Bay Fishing Districts. Source: ADFG map posted at: .................................... 58

Figure 13. Bristol Bay Commercial Sockeye Salmon Harvests, by District. ............................... 59

Figure 14. Share of Bristol Bay Commercial Sockeye Salmon Harvest, by District. .................. 60

Figure 15. Naknek-Kvichak District Sockeye Salmon Harvests, by River of Origin. ................. 61

Figure 16. Bristol Bay Salmon Harvests, by Fishery.................................................................... 65

Figure 17. World Sockeye Supply ................................................................................................ 66

Figure 18. Alaska Salmon Supply ................................................................................................ 67

Figure 19. World Salmon and Trout Supply ................................................................................. 68

Figure 20. Bristol Bay Sockeye Preseason Projection and Actual Commercial Catch ................ 69

Figure 21. Bristol Bay Salmon Harvests, 1985-2009 ................................................................... 70

Figure 22. Bristol Bay Sockeye Salmon Production .................................................................... 72

Figure 23. Share of Sockeye Salmon Production in Bristol Bay .................................................. 72

Figure 24. Bristol Bay Sockeye Salmon Harvests and Production ............................................... 74

Figure 25. Monthly Sales Volume of Bristol Bay Salmon Products ............................................ 75

Figure 26. Alaska Frozen Sockeye Production and U.S. Frozen Sockeye Exports. ..................... 77

Figure 27. Estimated End-Markets for Alaska Frozen Sockeye Salmon ...................................... 78

Figure 28. Alaska Canned Sockeye Production and U.S. Canned Sockeye Exports .................... 79

Figure 29. Average Ex-Vessel Price of Bristol Bay Sockeye Salmon, 1975-2010 ...................... 80

Figure 30. Average Wholesale and Ex-Vessel Prices of Bristol Bay Sockeye Salmon ............... 81

Figure 31. Average Monthly First Wholesale Prices. ................................................................... 83

Figure 32. Average Wholesale and Ex-Vessel Prices, Bristol Bay and Rest of Alaska ............... 84

Figure 33. Average Ex-Vessel Prices of Sockeye Salmon, Selected Alaska Areas. .................... 84

Figure 34. Japanese Red-Fleshed Salmon Imports, May-April .................................................... 85

Figure 35. Japanese Red-Fleshed Frozen Salmon Imports & Wild Sockeye Wholesale Price .... 86

Figure 36. Japanese Wholesale Prices and Bristol Bay Prices for Sockeye Salmon .................... 87

Figure 37. Average United States Import Prices of Selected Farmed Salmon Products .............. 88

Figure 38. U.S. Wholesale Prices for Selected Wild and Farmed Salmon Products .................... 88

Figure 39. Monthly Average Wholesale Case Prices for Alaska Canned Sockeye Salmon. ........ 89

Figure 41. Ex-Vessel and First Wholesale Value: 1984-2010 ...................................................... 93

Figure 42. Distribution of Nominal Value of Bristol Bay Sockeye Salmon ................................ 94

Figure 43. Distribution of Value of Bristol Bay Sockeye Salmon ............................................... 95

Figure 44. Number of Limited Entry Permits Issued and Fished in Bristol Bay .......................... 97

Figure 45. Average Gross Earnings of Bristol Bay Drift Gillnet Permit Holders ...................... 100

7 
Figure 46. Average Gross Earnings of Bristol Bay Set Gillnet Permit Holders ......................... 101

Figure 47. Average Prices Paid for Bristol Bay Limited Entry Permits ..................................... 102

Figure 48. Average Permit Prices and Total Earnings: Bristol Bay Drift Gillnet Fishery ......... 103

Figure 49. Average Prices and Earnings: Bristol Bay Set Gillnet Fishery ................................. 103

Figure 50. Northern Economics’ Estimates of the Breakdown of Operating Costs ................... 104

Figure 51. Number of Companies Reporting Salmon Production in Bristol Bay, by Product ... 106

Figure 52. Selected Bristol Bay Salmon Processor Costs, 2001-2009 ....................................... 108

Figure 53. Selected Estimates of Bristol Bay Salmon Fishing and Processing Workers ........... 113

Figure 54. Monthly Employment in Food Manufacturing, Bristol Bay Region ......................... 115

Figure 55. Bristol Bay Region Local Communities Source: 

www.visitbristolbay.org/bbvc/images/bb_map_large.jpg .......................................................... 120

Figure 56. Number of Bristol Bay Permit Holders by Residency .............................................. 121

Figure 57. Permit Holders Average Earnings, by Residency ..................................................... 122

Figure 58. Share of Total Earnings of Bristol Bay Drift Gillnet Permit Holders, by Residency 124

Figure 59. Share of Total Earnings of Bristol Bay Set Gillnet Permit Holders, by Residency .. 125

Figure 60. Share of Bristol Bay Seafood Processing Employment, by Residency ..................... 126

Figure 61. Local Bristol Bay Resident Share of Salmon Fisheries: Selected Measures ............. 127

Figure 62. Estimated Bristol Bay Area Population, by Area ...................................................... 131

Figure 63. Estimated Population by Region ............................................................................... 131

Figure 64. Number of Drift Gillnet Holders, by Region............................................................. 132

Figure 65. Number of Drift Gillnet Holders per 100 Residents, by Region ............................... 132

Figure 66. Number of Set Gillnet Holders, by Region ............................................................... 133

Figure 67. Number of Set Gillnet Permit Holders per 100 Residents, by Region ...................... 133

Figure 68. Total Salmon Fishery Earnings, by Region ............................................................... 135

Figure 69. Per Capita Salmon Fisheries Earnings, by Region .................................................... 135

Figure 70. Bristol Bay Commercial Salmon Harvests ................................................................ 138

Figure 71. Ex-Vessel and Wholesale Value of Bristol Bay Sockeye Salmon ............................ 140

Figure 72. Estimated Value of US Exports of Bristol Bay Salmon Products ............................. 141

Figure 73. Estimated Total Value of Bristol Bay Limited Entry Permits ................................... 144

Figure 74. Bristol Bay Commercial Salmon Harvests ................................................................ 145

Figure 75. Estimated Shares of Bristol Bay Sockeye Salmon Production, 2010 ....................... 147

Figure 76. Average Ex-Vessel and Wholesale Prices of Bristol Bay Sockeye Salmon ............. 148

Figure 77. Ex-Vessel and First Wholesale Value 1980-2010 ..................................................... 149

Figure 78. Local Bristol Bay Resident Share of Bristol Bay Salmon Fisheries. ........................ 150

Figure 79. Selected Bristol Bay Salmon Processor Costs: 2001-2009 ....................................... 212

Figure 80. Flows of Ecosystem Services (adapted from (National Research Council 2005)) ... 213

8 
Executive Summary

The objective of this report is to characterize the baseline levels of economic activity and related 

ecosystem services values for the Bristol Bay wild salmon ecosystem. The overarching purpose 

of this report is to provide baseline economic information to the Environmental Protection 

Agency in order to inform review of mining proposals in the Nushugak and Kvichak drainages. 

Both regional economic significance and social net economic accounting frameworks are 

described in this report. This study reviews and summarizes existing economic research on the 

key sectors in this area and reports findings based on original survey data on expenditures and 

net benefits. This report combines efforts on the part of Bioeconomics, Inc. and the University 

of Alaska Institute of Social and Economic Research. John Duffield and Chris Neher compiled 

the report and authored the executive summary, Sections 1, 2, and 5. Gunnar Knapp wrote 

Section 3 (commercial fisheries), and Tobias Schwörer, Ginny Fey and Scott Goldsmith wrote 

Section 4. 

The major components of the total value of the Bristol Bay area watersheds include subsistence 

use, commercial fishing, sport fishing and other recreation, and the preservation values (or 

indirect values) held by users and the U.S. resident population. The overall objectives of this 

study is to estimate the share of the total regional economy (expenditures, income, and jobs) that 

is dependent on these essentially pristine wild salmon ecosystems and to provide a preliminary 

but relatively comprehensive estimate of the total economic value (from an applied welfare 

economics perspective) that relies on a healthy ecosystem. 

It is important to note that while the geographic scope of this economic characterization report is 

targeted to the Bristol Bay wild salmon ecosystem, the scope of the proposed mining activity is 

somewhat narrower, including the Nushugak and Kvichak drainages. Values tied to, and specific 

to, the proposed mining activity (and discharges) in the Nushugak and Kvichak Drainages would 

be a subset of those reported here, and have not been identified in this general characterization 

analysis. This report uses existing information and data to target this economic characterization 

report to ecosystem services and associated economic activity and values, specific to the Bristol 

Bay Region. However, data on different economic sectors vary in quality, and available data on 

some economic activities (such as non-consumptive tourism) make it more difficult to identify 

activities and associated economic values narrowly targeted to the Bristol Bay area. The overall 

intent of this report is to provide a general picture of the full range of economic values associated 

with ecosystem services supplied by the entire Bristol Bay region. 

Following this executive summary, the report is organized into five main sections. Section 1 

provides a brief introduction to the report. Section 2 addresses economic visitation and 

expenditures related to sport fishing, subsistence harvests, hunting, and non-consumptive 

recreation. Section 3 focuses on commercial fishing. Section 4 combines the regional economic 

activity associated with recreation and commercial fishing into an analysis of regional economic 

significance of these activities. Finally, Section 5 focuses on the net economic values associated 

with recreation and commercial fisheries in the Bristol Bay ecosystem.

9 
For purposes of a baseline year, the most recent generally available data year is used (2009). 

Where available, (primarily in the commercial fisheries discussion) data on 2010 is also shown. 

Summary values are presented for 2009 data and in 2009 dollars. 

 

The rivers that flow into the Bristol Bay comprise some of the last great wild salmon ecosystems 

in North America (Figure 1). The Kvichak River system supports the world’s largest run of 

sockeye salmon. While these are primarily sockeye systems, all five species of Pacific salmon 

are abundant, and the rich salmon-based ecology also supports many other species, including 

Alaska brown bears and healthy populations of rainbow trout. The Naknek, Nushugak, Kvichak, 

Igushik, Egegik, Ugashik, and Togiak watersheds are all relatively pristine with very few roads 

or extractive resource development. Additionally, these watersheds include several very large 

and pristine lakes, including Lake Iliamna and Lake Becherof. Lake Iliamna is one of only two 

lakes in the world that supports a resident population of freshwater seals (the other is Lake 

Baikal in Russia). Additionally, there are nationally-important public lands in the headwaters, 

including Lake Clark National Park and Preserve, Katmai National Park and Preserve, Togiak 

National Wildlife Refuge, and Wood-Tikchick State Park (the largest state park in the U.S.). 

The existing mainstays of the economy in this region are all wilderness-compatible and 

sustainable in the long run: subsistence use, commercial fishing, and wilderness sport fishing, 

hunting, and wildlife viewing and other non-consumptive recreation. Commercial fishing is 

largely in the salt water outside of the rivers themselves and is closely managed for 

sustainability. The subsistence, sport fish and other recreation sectors are primarily personal use 

and catch and release fishing, respectively. The limited harvest from these activities is relatively 

low impact when compared to the commercial fishery harvest. 

10 
Figure 1. Map of Bristol Bay Study Area 

This report focuses on an overview of values based on existing data and previous studies, and 

estimation of both the regional economic significance (focusing on jobs and income) of these 

ecosystems using an existing regional economic model. Total value in a social benefit-cost 

framework is also considered. This report provides a preliminary but relatively comprehensive 

estimate of the range of fishery-related values in this region (Figure 1). 

This summary provides a brief characterization of each of the major sectors, followed by the 

primary economic findings. 

Subsistence and Village Economies

The Bristol Bay economy is a mixed cash-subsistence economy. The primary features of these 

socio-economic systems include use of a relatively large number of wild resources (on the order 

of 70 to 80 specific resources in this area), a community-wide seasonal round of activities based 

on the availability of wild resources, a domestic mode of production (households and close kin), 

frequent and large scale non-commercial distribution and exchange of wild resources, traditional 

systems of land use and occupancy based on customary use by kin groups and communities, and 

a mixed economy relying on cash and subsistence activities (Wolfe and Ellanna, 1983; Wolfe et 

al. 1984). The heart of the cash-subsistence economy in Bristol Bay is the resident population of 

7,475 individuals located in 25 communities (Table 1) spread across this primarily un-roaded 

area (Figure 2). Archeological evidence indicates that Bristol Bay has been continuously 

inhabited by humans at least since the end of the last major glacial period about 10,000 years 

11 
ago. Three primary indigenous cultures are represented here: Aleuts, Yupik Eskimos, and the 

Dena’ina Athapaskan Indians. The share of the population that is Alaska Native is relatively high 

at 70 percent, compared to Alaska as a whole, with 16 percent. 

Table 1. Bristol Bay Area Communities, Populations, and Subsistence Harvest 

Bristol Bay Area 

Community /year of 

AKF&G survey

Population 

(2010 census)

Per Capita Harvest 

(AKF&G Surveys)

Total Annual 

Harvest (lbs)

% Native Population 

(2000 census)

Aleknagik 2008 219 296 64,824 81.9%

Clark's Point 2008 62 1210 75,020 90.7%

Dillingham 1984 2,329 242 563,618 52.6%

Egegik 1984 109 384 41,856 57.8%

Ekwok 1987 115 797 91,655 91.5%

Igiugig 2005 50 542 27,100 71.7%

Iliamna 2004 109 469 51,121 50.0%

King Salmon 2008 374 313 117,062 29.0%

Kokhanok 2005 170 680 115,600 86.8%

Koliganek 2005 209 899 187,891 87.4%

Levelock 2005 69 527 36,363 89.3%

Manokotak 2008 442 298 131,716 94.7%

Naknek 2008 544 264 143,616 45.3%

New Stuyahok 2005 510 389 198,390 92.8%

Newhalen 2004 190 692 131,480 85.0%

Nondalton 2004 164 358 58,712 89.1%

Pedro Bay 2004 42 306 12,852 40.0%

Pilot Point 1987 68 384 26,112 86.0%

Port Alsworth 2004 159 133 21,147 4.8%

Port Heiden 1987 102 408 41,616 65.6%

South Naknek 2008 79 268 21,172 83.9%

Ugashik 1987 12 814 9,768 72.7%

Togiak City 2000 817 246 200,982 86.3%

Twin Hills 2000 74 499 36,926 84.1%

Un-surveyed communities 457 --

Total 7,475 343 2,563,313

Sources: US Census Bureau (2010 census statistics), and ADF&G Division of Subsistence Community Profile Data Base; Personal Comm. David 

Holen, ADF&G Oct 25, 2011.

Wild renewable resources are important to the people of this region and many residents rely on 

wild fish, game, and plants for food and other products for subsistence use. Total harvest for 

these 25 communities is on the order of 2.6 million pounds based largely on surveys undertaken 

from the late 1980s through 2008, as summarized in the Alaska Division of Subsistence 

community profile data base. A new round of surveys is now underway to update this data. 

Estimates for the 2004-2008 study years (Fall et al. 2006; 2008; 2009) are included in the data 

presented in Table 1. Additionally, as yet unpublished data from 2009 for Alegnagik, Clarks 

Point and Manokotak are included in the table (Per. Com. David Holen, ADF&G, Oct. 25, 2011). 

Per capita harvests average about 343 pounds. Primary resources harvested include salmon, other 

freshwater fish, caribou, and moose. Based on recent surveys, subsistence use continues to be 

very important for communities of this region and participation in subsistence activity, including 

12 
harvesting, processing, giving and receiving is quite high. Compared to other regions of Alaska, 

the Bristol Bay area has many features characteristic of an unique subsistence economy, 

including the great time depth of its cultural traditions, its high reliance on fish and game, the 

domination of the region’s market economy by the commercial salmon fishery, and the extensive 

land areas used by the region’s population for fishing, hunting, trapping and gathering. (Wright, 

Morris, and Schroeder, 1985; Fall, Krieg, and Holen, 2009). 

13 

Figure 2. Bristol Bay Area Location and Major Communities 

The primary private source of cash employment for participants in Bristol Bay’s mixed cashsubsistence economy is the commercial salmon fishery. The compressed timing of this fishery’s 

harvesting activity makes it a good fit with subsistence in the overall Bristol Bay cashsubsistence economy. Participation in the Bristol Bay salmon fishery is limited to holders of 

limited entry permits and their crew. There are approximately 1,860 drift gillnet permits for 

fishing from boats and approximately 1,000 set net permits for fishing from the shore. The 

driftnet fishery accounts for about 80% of the harvest. Most of the harvest is processed by about 

ten large processing companies in both land-based and floating processing operations which 

employ mostly non-resident seasonal workers.

Many commercial fishing permit holders and crew members, as well as some employees in the 

processing sector, are residents of Bristol Bay’s dominantly-native Alaskan villages. An 

ADF&G summary of subsistence activity in Bristol Bay (Wright, Morris, and Schroeder 1985) 
noted that as of the mid-1980’s traditional patterns of hunting, fishing, and gathering activities 

had for the most part been retained, along with accommodations to participate in the commercial 

fishery and other cash-generating activities. In the abstract to this 1985 paper, the authors 

characterize the commercial salmon fishery as “a preferred source of cash income because of its 

many similarities to traditional hunting and fishing, and because it is a short, intense venture that 

causes little disruption in the traditional round of seasonal activities while offering the potential 

for earning sufficient income for an entire year.” Commercial fishing is a form of selfemployment requiring many of the same skills, and allowing nearly the same freedom of choice 

as traditional subsistence hunting and fishing (Wright, Morris, Schroeder 1985; p. 89). 

Figure 3. Bristol Bay Area Commercial Salmon Fishery Management Districts

Commercial Fisheries 

The Bristol Bay commercial salmon fishery harvests salmon which spawn in and return to 

numerous rivers over a broad area. The Bristol Bay commercial fishery management area 

encompasses all coastal and inland waters east of a line from Cape Menshikof to Cape 

Newhenham (Figure 3). This area includes eight major river systems: Naknek, Kvichak, Egegik, 

Ugashik, Wood, Nushagak, Igushik and Togiak. Collectively these rivers support the largest 

commercial sockeye salmon fishery in the world (ADF&G, 2005). This is an interesting and 

unique fishery, both because of its scale and significance to the local economy, but also because 

it is one of the very few major commercial fisheries in the world that has been managed on a 

14 
sustainable basis. The substantial diversity in this system, both across species and within species 

(population diversity or the “portfolio effect”), leads to relatively stable populations. Schindler 

(2010) estimated that variability in annual Bristol Bay salmon runs is 2.2 times lower than if the 

system consisted of a single population, and that a single homogeneous population of salmon 

would lead to 10 times more frequent fisheries closures. These findings indicate the importance 

of maintaining population diversity in order to protect the ecosystem and the economy that 

depends on it. 

The five species of pacific salmon found in Bristol Bay are the focus of the major commercial 

fisheries. Sockeye salmon account for about 94% of the volume of Bristol Bay salmon harvests 

and an even greater share of the value. The fishery is organized into five major districts (Figure 

3) including Togiak, Nushagak, Naknek-Kvichak, Egegik, and Ugashik. Catches in each district 

vary widely from year to year and over longer time periods of time, reflecting wide variation in 

returns to river systems within each district. Currently there is particular interest in the 

significance of fisheries resources of river systems in the Nushagak and Kvichak districts, 

because of potential future resource development in these watersheds. Over the period 1986-

2010, the Naknek-Kvichak catches ranged from as low as 5% to as high as 52% of total Bristol 

Bay catches; Nushagak district catches ranged from as low as 9% to as high as 45% of total 

Bristol Bay catches. For most of the past decade, the combined Nushagak and Naknek-Kvichak 

districts have accounted for about 60% of the total Bristol Bay commercial sockeye harvest.1

Management is focused on discrete stocks with harvests directed at terminal areas at the mouths 

of the major river systems (ADF&G, 2005). The stocks are managed to achieve an escapement 

goal based on maximum sustained yield. The returning salmon are closely monitored and 

counted and the openings are adjusted on a daily basis to achieve desired escapement. Having the 

fisheries near the mouths of the rivers controls the harvest on each stock, which is a good 

strategy for protection of the discrete stocks and their genetic resources. The trade-off is that the 

fishery is more congested and less orderly, and the harvest is necessarily more of a short pulse 

fishery, with most activity in June and early July. This has implications for the economic value 

of the fish harvest, both through effects on the timing of supply, but also on the quality of the 

fish. Most fish are canned or frozen, rather than sold fresh. Total catches vary widely from year 

to year. Between 1980 and 2010, Bristol Bay sockeye salmon harvests ranged from as low as 10 

million fish to as high as 44 million fish. Harvests can vary widely from year to year and annual 

pre-season forecasts are subject to a wide margin of error. 

Strong Japanese demand for frozen sockeye salmon drove a sharp rise in Bristol Bay salmon 

prices during the 1980s. Competition from rapidly increasing farmed salmon production drove a 

protracted and dramatic decline in prices between 1988 and 2001, which led to an economic 

crisis in the industry. However, growing world salmon demand, a slowing of farmed salmon 

production growth, diversification of Bristol Bay salmon products and markets, and 

improvements in quality have driven a strong recovery in prices over the past decade. The real 

ex-vessel value paid to fishermen fell from $359 million in 1988 to $39 million in 2002, and rose 

1

 Bristol Bay salmon harvest statistics can be found at 

http://www.adfg.alaska.gov/index.cfm?adfg=commercialbyareabristolbay.salmon

15 

 
to $181 million in 2010 (values in 2010 dollars).2

 The real first wholesale value of Bristol Bay 

salmon production fell from $616 million in 1988 to $124 million in 2002, and then rose to $390 

million in 2010. In 2009, the ex-vessel value of Bristol Bay salmon harvest was approximately 

$300 million. Many other factors, such as changes in wild salmon harvests, exchange rates, 

diseases in Chilean farmed salmon, and global economic conditions have also affected prices. In 

general, changes in ex-vessel prices paid to fishermen have reflected changes in first wholesale 

prices paid to processors.

There are many potential economic measures of the Bristol Bay salmon industry (Table 2). 

Which measure is most useful depends upon the question being asked. For example, if we want 

to know how the Bristol Bay salmon fishery compares in scale with other fisheries, we should 

look at total harvests or ex-vessel or wholesale value. If we want to know how it affects the 

United States balance of payments, we should look at estimated net exports attributable to the 

fishery. If we want to know how much employment the industry provides for residents of the 

local Bristol Bay region, Alaska or the United States, we should look at estimated employment in 

fishing and processing for residents of these regions. If we want to know the net economic value 

attributable to the fishery, we should look at estimated profits of Bristol Bay fishermen and 

processors. These different measures (Table 2) vary widely in units, in scale, and in the measure 

of how economically “important” the fishery is. For example, for the period 2000-2010, Bristol 

Bay harvests were 62% of all Alaska sockeye salmon harvests and 45% of total world production 

for the species.

Table 2. Selected Economic Measures of the Bristol Bay Commercial Salmon Industry, 

2000-2010. 

Measure 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Avg.

Sockeye Salmon Havests

Millions of fish 21 14 11 15 26 25 28 30 28 31 29 23 11 - 31

Millions of pounds 125 96 65 93 152 155 165 173 160 183 170 140 65 - 183

Bristol Bay harvest

volume as a share of:

Alaska sockeye salmon 61% 56% 48% 50% 59% 58% 69% 62% 71% 71% 74% 62% 48% - 74%

World sockeye salmon 45% 40% 28% 38% 47% 47% 49% 47% 52% 55% 45% 28% - 55%

Alaska wild salmon (all species) 18% 12% 10% 13% 19% 16% 22% 18% 23% 25% 18% 10% - 25%

World wild salmon (all species) 7% 5% 4% 5% 8% 7% 8% 7% 9% 7% 7% 4% - 9%

World wild & farmed salmon

 (all species) 3% 2% 1% 2% 3% 3% 3% 3% 3% 3% 2% 1% - 3%

Gross Value ($ mllions)

Ex-vessel value 80 40 32 48 76 95 109 116 117 144 181 94 32 - 181

First wholesale value 175 115 100 114 176 220 237 249 262 293 390 212 100 - 390

Total value of US exports of 

Bristol Bay salmon products 150 137 97 111 172 193 173 183 206 230 254 173 97 - 254

 

 

 

 

Selected Economic Measures of the Bristol Bay Salmon Industry, 2000 2010

Range

2 The ex-vessel value is the total post-season adjusted price paid to fishermen for the first purchase of commercial 

harvest.

16 

 
Recreation 

Next to commercial fishing and processing, recreation is the most important private economic 

sector in the Bristol Bay region. This recreational use includes sport fishing, sport hunting, and 

other tourism/wildlife viewing recreational trips to the Bristol Bay Region. The 2005 Bristol 

Bay Angler Survey (Duffield et al. 2007) confirmed that the fresh water rivers, streams, and 

lakes of the region are a recreational resource equal or superior in quality to other world 

renowned sport fisheries. 

In survey responses Bristol Bay anglers consistently emphasize the importance of Bristol Bay’s 

un-crowded, remote, wild setting in their decisions to fish the area. Additionally, a significant 

proportion of these anglers specifically traveled to the region to fish the world-class rainbow 

trout fisheries. These findings indicate that Bristol Bay sport fishing is a relatively unique 

market segment, paralleling the findings of Romberg (1999) and Duffield, Merritt and Neher 

(2002) that angler motivation, characteristics, and values vary significantly across Alaska sport 

fisheries.

Recreational fishing use of the Bristol Bay region is roughly divided between 58% trips to the 

area by Alaska residents and 42% trips by non-residents. These non-residents (approximately 

12,500 trips in 2009 (personal communication, ADF&G, 2011)) account for the large majority of 

total recreational fishing spending in the region. It is estimated that in 2009 approximately $50 

million was spent in Alaska by nonresidents specifically for the purpose of fishing in the Bristol 

Bay region. In total, it is estimated that $60 million was spent in Alaska in 2009 on Bristol Bay 

fishing trips. 

While sport fishing within the Bristol Bay region comprises a large and well-recognized share of 

recreational use and associated visitor expenditures, thousands of trips to the region each year are 

also made for the primary purpose of sport hunting and wildlife viewing. Lake Clark and Katmai 

National Parks are nationally significant protected lands and are important visitor destinations 

attracting around 65,000 recreational visitors in 2010 (NPS public visitation statistics). 

Additionally, rivers within Katmai NP provide the best locations in North America to view wild 

brown bears. 

Summary of Economic Significance

Table 3 through 7 detail the summary results of the analysis of economic values. Table 3 shows 

estimated direct expenditures in Alaska related to harvest or use of Bristol Bay area renewable 

resources. Total estimated direct expenditures (that drive the basic sector of the economy) were 

estimated to be $479 million in 2009. The largest component is commercial fishing harvesting 

and processing. These estimates were obtained from the Alaska Department of Revenue and the 

Commercial Fishing Entry Commission. The next most significant component is wildlife 

viewing/tourism at $104 million in 2009. Sport fishing is estimated to constitute another $60 

million in spending. This estimate is derived from the 2005 Bristol Bay Angler survey data as 

well as AK F&G use estimates. Sport hunting is less important economically. 

17 
The direct economic spending and sales shown in part A of the table supports an estimated 

14,200 direct full and part-time jobs in the Bristol Bay region during peak season. 

Table 3. Summary of Regional Economic Expenditures Based on Wild Salmon Ecosystem 

Services (Million 2009 $)

Ecosystem Service Estimated direct expenditures / sales per year

(A) Direct Expenditures and Sales 

Commercial fish wholesale value3 300.2

Sport fisheries 60.5

Sport hunting 8.2

Wildlife viewing / tourism 104.4

Subsistence harvest expenditures 6.3

Total direct annual economic impact 479.6

(B) Estimated Direct Full & Part-Time Jobs at Peak Season

Commercial fish Sector 11,572

Sport fisheries 854

Sport hunting 132

Wildlife viewing / tourism 1,669

Subsistence harvest expenditures Not Captured by the Market

Total direct annual economic impact 14,227

Table 4 provides additional detail on recreation expenditures, including number of trips and 

spending by residence of the participants. A large share of total recreation expenditures is by 

nonresident anglers ($49.8 million) and nonresident non-consumptive (tourism/wildlife viewing) 

visitors ($92.9 million). This reflects the high quality of this fishery and other recreational 

opportunities in the region, in that the area is able to attract participants from a considerable 

distance in the lower 48 states as well as foreign countries. Subsistence harvest expenditures are 

based on limited data and are likely to be conservative. (Goldsmith, 1998) 

3 Estimates of some year-specific commercial fishery total harvest and total sales vary slightly within this report. 

This is due to differences in how these data are aggregated and reported by the Alaska Fish and Game, and the point 

in time these statistics were accessed during the preparation of this report. 

18 

 
Table 4. Total Estimated Recreational Direct Spending in Alaska Attributable to Bristol 

Bay Wild Salmon Ecosystems, 2009 

Local 

residents

Non-local 

residents

Nonresidents Total 

Visitors

 Non-consumptive - 4,506 36,458 40,964

 Sport fishing 13,076 3,827 12,464 29,367

 Sport hunting - 1,319 1,323 2,642

Total 13,076 9,652 50,245 72,973

Spending per visitor

 Non-consumptive - $2,548 $2,548

 Sport fishing $373 $1,582 $3,995

 Sport hunting - $1,068 $5,170

Spending ($million)

 Non-consumptive - $11.5 $92.9 $104.4

 Sport fishing $4.9 $6.0 $49.8 $60.7

 Sport hunting - $1.4 $6.8 $8.2

Total $4.9 $18.9 $149.5 $173.3

Table 5 summarizes the full time equivalent employment (annual average) for the cash 

component of the economy associated with the major economic sectors of the Bristol Bay 

economy, those dependent on wild salmon ecosystems—recreation, commercial fishing, and 

subsistence, as well as other major employment sectors. The economy of the Bristol Bay Region 

depends on three main activities or sectors—publicly funded services through government and 

non-profits, commercial activity associated with the use of natural resources (mainly commercial 

fishing and recreation), and subsistence. Subsistence is a non-market activity in the sense that 

there is no exchange of money associated with the subsistence harvest. However, local 

participants invest a significant portion of their income to participate in subsistence and the 

harvest has considerable economic value and their expenditures have significant economic 

effects. 

Public services and commercial activities bring money into the economy (basic sectors) and 

provide the basis for a modest support sector. The support sector (non-basic sector) consists of 

local businesses that sell goods and services to the basic sectors including the commercial fishing 

industry, the recreation industry, the government and non-profit sectors. The support sector also 

sells goods and services to participants in subsistence activities. 

 

The relative importance within the regional economy of government as contrasted with 

commercial fishing and recreation can be measured by the annual average employment in each 

sector. In 2009, more than two thousand jobs were directly associated with government spending 

from federal, state, and local sources. Commercial fishing and recreation accounted for 

19 
approximately three thousand or 57 percent of total basic sector jobs. Since much of the 

recreation is using public lands and resources, a share of the government sector; for example 

administration of the federal and state parks and wildlife refuges, is directly related to providing 

jobs and opportunities in the recreation sector. Accordingly, the estimate of recreation-dependent 

jobs is conservative.

The support sector depends on money coming into the regional economy from outside mainly 

through government, commercial fishing, and recreation. The relative dependence of the support 

sector on the three main sectors is difficult to measure. One reason for this is that government 

employment is stable throughout the year, while employment in commercial fisheries and 

recreation vary seasonally. Due to the seasonal stability of government jobs, the payroll spending 

of people employed in government is likely to contribute more to the stability of support sector 

jobs in the region than their share of basic sector jobs indicates. 

Table 5. Cash Economy Full-time Equivalent Employment Count by Place of Work in the 

Bristol Bay Region, 2009 

Annual 

Average Summer Winter Swing

Total jobs count 6,648 16,386 3,792 12,594

Basic 5,490 14,877 2,430 12,447

 Fish harvesting 1,409 6,909 - 6,909

 Fish processing 1,374 4,480 354 4,126

 Recreation 432 1,297 - 1,297

 Government & Health 2,039 1,712 2,056 (344)

 Mineral Exploration 197 450 70 380

Non-basic 1,406 1,509 1,362 147

 Construction 61 92 55 37

 

Trade/Transportation/Leisure

634 717 593 124

 Finance 155 142 162 (20)

 Other wage & salary 239 241 235 6

 Non-basic self employed 317 317 317 -

Resident jobs count 4,675 10,351 3,225 7,126

Note, estimates based on ISER Input-Output modeling described in section below. Fish harvesting and processing 

include other fisheries besides salmon, thus employment numbers cannot be compared with other tables shown in 

this report. Summer and winter employment shown, are point estimates that either show the maximum or minimum 

job count. Swing refers to the difference between maximum and minimum. 

20 
Subsistence users are not the only hunter-gatherers in this economy. Essentially the entire private 

economy is “following the game” (or in this case fish), with many commercial fishermen, 

processors, sport anglers, sport hunters, and wildlife viewers coming from elsewhere in Alaska 

or outside the state to be part of this unique economy at the time that fish and game are available. 

The estimated earnings associated with the salmon ecosystem-dependent jobs are shown in Table 

6. The total of $283 million was divided among $78 million for residents of the Bristol Bay 

region, $104 million to residents of the rest of Alaska, and $100 million to residents of other 

states.

Table 6. Cash Economy Estimated Economic Significance of Bristol Bay Ecosystems

Total Residents NonNon-local Local Total Residents

Direct jobs

 Peak 14,227 4,365 2,273 6,639 7,587

Commercial fish 11,572 3,251 1,089 4,341 7,231

Recreation 2,655 1,114 1,184 2,298 356

Subsistence nonmkt.

non-mkt. non-mkt. nonmkt.non-mkt.

 Annual average 2,811 914 585 1,499 1,313

Commercial fish 1,897 530 177 707 1,190

Recreation 914 384 408 792 123

Subsistence nonmkt.

non-mkt. non-mkt. nonmkt.non-mkt.

Multiplier Jobs 3,455 2,008 1,447 3,455 -

Total jobs

(annual average)

6,266 2,922 2,032 4,954 1,313

Direct wages 

($000)

$166,632 $40,149 $31,048 $66,199 $100,435

Commercial fish $134,539 $22,698 $17,608 $40,307 $94,233

Recreation $32,093 $12,451 $13,440 $25,892 $6,202

Subsistence nonmkt.

non-mkt. non-mkt. nonmkt.non-mkt.

Multiplier wages $115,976 $69,250 $46,724 $115,976 -

Total wages $282,608 $104,399 $77,772 $182,175 $100,435

Note, estimates based on ISER Input-Output modeling described in section below. 

Table 6 provides an accounting of jobs and wages for the cash economy component of the 

Bristol Bay mixed cash-subsistence economy. Kreig et al. (2007) describe the participation in the 

subsistence side of the economy through sharing, bartering, and cash exchange for subsistence 

harvests. An estimate of the number of jobs or livelihoods supported by the subsistence sector 

21 
(besides those associated with expenditures for tools, equipment, and supplies in Table 3) can be 

approximated through either a top-down or bottom-up estimation approach. 

Population levels in Bristol Bay were 7,475 in 2010 (Table 1). Based on 2010 census counts, the 

number of Bristol Bay residents aged 16 and over was 5,448. The cash economy and equivalent 

full-time employment of Alaskans in the Bristol Bay region is estimated at 4,675 (Table 5). The 

estimated cash economy employment for local Bristol Bay residents only is 2,032 (Table 6). By 

not choosing to move elsewhere, Bristol Bay residents reveal their preference for the livelihood 

presented by the mixed cash-subsistence economy. This is supported by the findings in Borass 

(2011). For example, several local interviewees were quoted as saying “But I wouldn’t trade this 

place for anything. This is home; this is where I find clean water to drink.” And “We love this 

place. Moving is not an option to me.” (Boraas (2011) p. 3.) 

Data in Holen et al. (2011) indicate that for Bristol Bay communities participation in subsistence 

activities is very high. In the towns of King Salmon, Naknek and South Naknek 90% or more of 

residents reported participation in subsistence harvest activities (p. 20). One estimate of 

participation (employment) in the subsistence livelihood (full-time equivalent jobs) would be to 

attribute the residual of the adult (16 and over) population less the cash economy jobs (Table 

5)—or around 3,400 jobs to this sector. Therefore, the non-cash economy jobs associated with 

the subsistence sector may be roughly 3,400. 

Another approach would be to examine the effort levels (days in subsistence activities) based on 

subsistence fishing permit data. Fall et al. (2009) indicates that the harvest levels per day are 

actually constrained not by potential daily harvest, but by the processing capacity of the family 

unit (or extended family). 

The total number of full-time equivalent jobs directly dependent on the wild salmon ecosystem is 

the sum of the cash economy jobs (6,266) plus the subsistence sector livelihoods (roughly 

estimated at (3,400 jobs), or about 9,600 jobs. 

Net Economic Values

The preceding discussion has focused on a regional economic accounting framework and job and 

wage-related measures of economic significance. This section introduces the net economic value 

measures for evaluation of the renewable Bristol Bay resources. The framework for this 

accounting perspective is the standard federal guidelines for estimating net economic benefits in 

a system of national accounts (Principles and Standards, U.S. Water Resources Council 1985). 

EPA (2010) is a more recent and complementary set of guidelines. 

The Alaskan subsistence harvest is not traditionally valued in the marketplace. Because the 

subsistence resources are not sold, no price exists to reveal the value placed on these resources 

within the subsistence economy. The prices in external markets, such as Anchorage, are not 

really relevant measures of subsistence harvest value. The supply/demand conditions are unique 

to the villages, many of which are quite isolated. Native preferences for food are strongly held 

22 
and often differ from preferences in mainstream society. Additionally, because these are highly 

vertically integrated economies, substantial value-added may occur before final consumption 

(such as drying, or smoking fish and meats). In their research on estimating the economic value 

of subsistence harvests, Brown and Burch (1992) suggest that these subsistence harvests have 

two components of value, a product value, and what they call an “activity value.” The product 

value is essentially the market value of replacing the raw subsistence harvest. The activity value 

would primarily include the cultural value of participating in a subsistence livelihood. The 

activity value component is also associated with the value of engaging in subsistence harvest and 

food processing activities. This activity value would include maintaining cultural traditions 

associated with a subsistence livelihood. Duffield (1997) estimated a hedonic model of 

subsistence harvest of 90 Alaskan communities. This model was updated to incorporate current 

subsistence harvest data, and education and income data, and estimated a total NEV per pound of 

usable subsistence harvest of between $60.24 and $86.06. 

Based on an estimated 2.6 million pounds of subsistence harvest per year in the Bristol Bay 

region, and valued at an estimated range of $60.24 to $86.06 per pound, this harvest results in an 

estimated net economic value annually of subsistence harvest of between $154.4 and $220.6 

million. 

The net economic value of commercial fisheries is estimated based on data on salmon fishery 

permit sales prices for Bristol Bay. The Commercial Fish Entry Commission reports average 

permit transfer prices annually (and monthly) for the Bristol Bay salmon fishery.4

 Over the 

period from 1991-2011 the average sales price for Bristol Bay drift net permits has been 

$149,000 (in 2011 dollars). The average price for set net permits over the same period has been 

$42,200. The 95% confidence interval on the mean drift net price for this period is from 

$105,500 to $192,700. For the set net permit transfers, the 95% C.I. on the mean sales price was 

between $28,700 and $55,700.5 For both types of permits combined, it is estimated that the total 

market value of the permits ranges from approximately $225 million to $414 million.

In order to be comparable to other annual net economic values in this analysis (such as sport 

fishing or sport hunting) the net present value of commercial fishing permits, as represented by 

the market value, must be converted into an annual value reflecting expected annual permit net 

income The permit total value can be annualized using an appropriate amortization (or discount) 

rate. The decision to sell a commercial fishing permit at a given price is an individual (or 

private) decision. In deciding on an acceptable sales price, a permit holder considers past profits 

from operating the permit, risk associated with future operation of the permit (both physical and 

financial), and many other factors. All these considerations weigh on how heavily a permit seller 

discounts (reduces) potential future profits from fishing the permit in order to arrive at a lumpsum value for the permit. Huppert et al. (1996) specifically looked at Alaska commercial salmon 

permit operations and sales and estimated the individual discount rate on drift net permit sales in 

the Bristol Bay and surrounding fisheries. This discount rate was estimated from both 

profitability and permit sales price data. Huppert et al. estimated the implied discount rate 

4 A long time series of monthly and annual permit transfer prices is continuously updated at, 

http://www.cfec.state.ak.us/pmtvalue/mnusalm.htm 5 Over the period 1991-2011, a total of 3,246 Bristol Bay drift net salmon permits and 1,867 set net salmon permits 

were reported sold by the Commercial Fish Entry Commission.

23 

 
appropriate for annualizing permit sales prices in this setting at 13.52%. This estimate was 

consistent with previous estimates for the fishery.6

 Use of the 13.52% discount rate from 

Huppert results in an estimated average annual permit net income associated with Bristol Bay 

commercial salmon fishing of between $30.4 million and $55.9 million. 

Net income for the processing sector is more difficult to estimate. Relative to the fishing sector, 

with ex-vessel value of $181 million in 2010, the processing sector provides an approximately 

equal value added of $209 million in 2010 (first wholesale value of $390 million in 2010 less the 

cost of buying fish at the ex-vessel cost of $181 million. (Figure 4) However, information on 

profits or net income for this sector are difficult to obtain. As with permit prices, processor 

profits are highly variable year-to-year. The average value added associated with salmon 

processing for the Bristol Bay fishery is generally equal to or more than the ex-vessel value. 

Salmon processors in the Bristol Bay fishery have an “oligopsony” market structure, in that a 

small number of buyers of raw fish exist in the market. Additionally, these buyers are largely 

“price makers” in that they set the price paid per pound to fishermen each season. Given the 

unique relationship between fisherman that the small number of processors in the Bristol Bay, it 

is estimated that processors derive profits (net economic value) equal to that earned by 

fishermen. Therefore, for the purposes of this report it is estimated that the NEV for salmon 

producers is equal to that for the fishing fleet. Estimation of harvest and processing sector net 

income using a second independent set of net income estimates and assumptions supports the 

result that a range of annual NEV commercial fisheries estimates from $60.8 to $111.8 million 

provides a conservative estimate for this sector.

Selected Bristol Bay Salmon Processor Costs, 2001-2009

0

50

100

150

200

250

300

200120022003200420052006200720082009

millions of nominal dollars

Other costs

and profits

Cost of labor

(fish processing

earnings)

Cost of fish

(ex-vessel

value)

Source: ADFG, ADLWD

Figure 4. Selected Bristol Bay Salmon Processor Costs: 2001-2009 

6 Huppert, Ellis and Nobel (1996) estimated the real discount rate associated with sales of Alaska drift gill-net 

commercial permits of 13.52%. Karpoff (1984) estimated the discount rate from sales of Alaska limited entry 

permits at 13.95%. 

24 

 
The sportfish net economic values are angler recreational benefits (consumer surplus) in Duffield 

et al. (2007). These estimates are consistent with values from the extensive economic literature 

on the value of sportfishing trips (for example Duffield, Merritt and Neher 2002). Sport hunting 

values are based on studies conducted in Alaska McCollum and Miller (1994). Direct use values 

for all uses total from $237 million to $354 million per year. In addition to recreationist’s net 

benefits, net income (producer’s surplus) is recognized by the recreation and tourism industry. 

This is a component that remains to be estimated. 

Based on the National Research Council panel on guidelines for valuation of ecosystem services

(NRC 2005), it is important to include intrinsic or passive use values (aka “non-use” values) in 

any net economic accounting of benefits (Figure 5).

Figure 5. Flows of Ecosystem Services (adapted from (National Research Council 2005)) 

A major unknown is the total value related to existence and bequest motivations for passive use 

values. Goldsmith et al. (1998) estimated the existence and bequest value for the federal wildlife 

25 
refuges in Bristol Bay at $2.3 to $4.6 billion per year (1997 dollars). There is considerable 

uncertainty in these estimates, as indicated by the large range of values. Goldsmith’s estimates 

for the federal wildlife refuges are based on the economics literature concerning what resident 

household populations in various areas (Alberta, Colorado) (Adamowicz et al. 1991; Walsh et al. 

1984; Walsh et al. 1985) are willing to pay to protect substantial tracts of wilderness. Similar 

literature related to rare and endangered fisheries, including salmon, could also be applied here. 

It is possible that from a national perspective the Bristol Bay wild salmon ecosystems and the 

associated economic and cultural uses are sufficiently unique and important to be valued as 

highly as wilderness in other regions of the U.S.. Goldsmith et al.’s (1998) estimates assume that 

a significant share of U.S. households (91 million such households) would be willing to pay on 

the order of $25 to $50 per year to protect the natural environment of the Bristol Bay federal 

wildlife refuges. The number of these households used in Goldsmith’s analysis is based on a 

willingness to pay study (the specific methodology used was contingent valuation) conducted by 

the State of Alaska Trustees in the Exxon Valdez oil spill case (Carson et al. 1992). These 

methods are somewhat controversial among economists, but when certain guidelines are 

followed, such studies are recommended for use in natural resource damage regulations (for 

example, see Ward and Duffield 1992). The findings of the Exxon Valdez study were the basis 

for the $1 billion settlement between the State and Exxon in this case. Willingness-to-pay 

analyses have also been upheld in court (Ohio v. United States Department of Interior, 880 F.2d 

432-474 (D.C. Cir.1989)) and specifically endorsed by a NOAA-appointed blue ribbon panel 

(led by several Nobel laureates in economics) (Arrow et al. 1993). 

While the primary source of passive use values for Bristol Bay are likely to be with national 

households (lower 48), it is important to note that the Alaska natives living in Bristol Bay also 

likely have significant passive use values for the wild salmon ecosystem. For example, Boraas 

(2011) quotes Bristol Bay natives in saying “We want to give to our children the fish, and we 

want to keep the water clean for them...It was a gift to us from our ancestors, which will then be 

given to our children.) (Boraas p. 33). 

Goldsmith’s estimates for just the federal refuges may be indicative of the range of passive use 

values for the unprotected portions of the study area. However, there are several caveats to this 

interpretation. First, Goldsmith et al. estimates are not based on any actual surveys to calculate 

the contingent value specific to the resource at issue in Bristol Bay. Rather, they are based on 

inferences from other studies, a method referred to as benefits transfer. Second, these other 

studies date from the 1980’s and early 1990’s and the implications of new literature and methods 

have not been examined. Additionally, the assumptions used to make the benefits transfer for 

the wildlife refuges may not be appropriate for the larger Bristol Bay study area which includes 

not only the wildlife refuge, but also two large national parks. This topic is an area for future 

research.

26 
Table 7. Summary of Bristol Bay Wild Salmon Ecosystem Services, Net Economic Value 

per Year (Million 2009 $)

Ecosystem Service Low estimate High estimate

Commercial salmon fishery

 Fishing Fleet $30.4 $55.9

 Fish Processing $30.4 $55.9

Sport fishing $12.2 $12.2

Sport hunting $1.4 $1.4

Wildlife viewing / tourism $8.1 $8.1

Subsistence harvest and activity $154.4 $220.6

 Total Direct Use Value $236.90 $354.10

Table 7 provides a summary of annual net economic values. Since these are values for renewable 

resource services that in principle should be available in perpetuity, it is of interest to also 

consider their present value (e.g. total discounted value of their use into the foreseeable future). 

The controlling guidance document for discounting in cost benefit analysis, OMB Circular A-4 

(2003), generally requires use of discount rates of 3% and 7%, but allows for lower, positive 

consumption discount rates, perhaps in the 1 percent to 3 percent range, if there are important 

intergenerational values. Weitzman (2001), conducted an extensive survey of members of the 

American Economic Association, and suggests a declining rate schedule, which may be on the 

order of 4 percent (real) in the near term and declining to near zero in the long term. He suggests 

a constant rate of 1.75% as an equivalent to his rate schedule. Weitzman’s work is cited both in 

the EPA guidance (EPA 2000) and in OMB guidance (Circular A-4 (2003) ). Table 8 shows the 

estimated net present value in perpetuity of direct use values within the Bristol Bay Ecosystem. 

The table shows a range of alternative discount rates from the standard “intragenerational” rates 

of 7% and 3% to the more appropriate “intergenerational” rates for the Bristol Bay case of 1.75% 

and 1.0%. The entire range of NPV estimates in the table is from $3.4 to $35.4 billion. The range 

of estimated direct use NPV of the resource using the more appropriate intergenerational 

discount rates is from $13.5 to $35.4 billion. These estimates are likely quite conservative as 

they do not include estimates of passive use values, but are limited to direct economic uses of the 

wild salmon ecosystem services.

Table 8. Estimated Net Present Value of Bristol Bay Ecosystem Net Economic Use Values 

and Alternative Assumed Perpetual Discount Rates

Estimate 

Annual Value

Net Present Value (million 2009 $)

7% Discount 3% Discount 1.75% Discount 1% Discount

Low Estimate $236.9 $3,384 $7,897 $13,537 $23,690

High Estimate $354.1 $5,059 $11,803 $20,234 $35,410

 

27 
1.0 Introduction and Setting

This report provides information on the importance of wild fisheries and the natural environment 

in the Bristol Bay region to the economies of the Bristol Bay region, the State of Alaska and the 

U.S. as a whole. 

1.1 Study Objectives and Report Organization

The primary purpose of this report is to estimate baseline levels of economic activity and values 

associated with the current Bristol Bay Region wild salmon resource. This comprehensive report 

includes and synthesizes individual reports on separate components of economic activity and 

values linked to the Bristol Bay Ecosystem. Economic activity linked to Bristol Bay includes 

sportfishing, subsistence harvest, sport hunting, and commercial fishing. Additionally, an 

analysis of the structure of the Bristol Bay economy and the significance of these ecosystemrelated economic activities to the economy is presented.

This report on the baseline levels of economic activities (as of 2009) within the Bristol Bay 

Ecosystem is organized as follows:

Section 1: Introduction and Setting

Section 2: Baseline Recreation and Subsistence Economics

Section 3: Baseline Commercial Fisheries Activity

Section 4: Economic Significance Analysis (Schworer et al.)

Section 5: Baseline Net Economic Values

The major components of the total value of the Bristol Bay area wild salmon ecosystems include 

subsistence use, commercial fishing and processing, sportfishing, and the preservation values (or 

indirect values) held by users and the U.S. resident population. The overall objectives of this 

work are to estimate the share of the total regional economy (expenditures, income and jobs) that 

is dependent on these essentially pristine wild salmon ecosystems, and to provide a preliminary 

but relatively comprehensive estimate of the total economic value associated with the ecosystem.

It is important to note that while the geographic scope of this economic characterization report is 

targeted to the Bristol Bay wild salmon ecosystem, the scope of the proposed mining activity is 

somewhat narrower, including the Nushugak and Kvichak drainages. Values tied to, and specific 

to, the proposed mining activity (and discharges) in the Nushugk and Kvichak Drainages would 

be a subset of those reported here, and have not been identified in this general characterization 

analysis. 

 

This report used existing information and data to target this economic characterization report to 

ecosystem services and associated economic activity and values, specific to the Bristol Bay 

Region. However, data on different economic sectors vary in quality, and available data on some 

28 
economic activities (such as non-consumptive tourism) make it more difficult to identify 

activities and associated economic values narrowly targeted to the Bristol Bay area. The overall 

intent of this report is to provide a general picture of the full range of economic values associated 

with ecosystem services supplied by the entire Bristol Bay region. 

1.2 Definition of Study Area

The Bristol Bay region is located in southwestern Alaska. The region, which includes Bristol 

Bay Borough, the Dillingham Census Area, and a large portion of Lake and Peninsula Borough, 

contains a relatively small number of communities, the largest of which are shown in Figure 6. 

The area is very sparsely populated and the large majority of its population is comprised of 

Alaskan Natives (Table 9). Although median household income varies among census areas 

within the region, outside of the relatively small Bristol Bay Borough, income is somewhat lower 

than for the state of Alaska as a whole. As noted, Alaskan Natives make up over two-thirds of 

the total population within the region as compared to approximately 15% for the entire state 

(Table 9) 

Table 9. Demographic and Socioeconomic Characteristics of the Bristol Bay Region

Area Population 

2010

Percent 

Alaska 

Native

Percent 18 

or over

Number of 

households

Median household 

income 2009

Bristol Bay Borough 997 48.2% 77.4% 423 $ 64,418

Dillingham Census Area 4,847 80.4% 67.1% 1,563 $ 46,580

Lake & Peninsula Borough 1,631 74.6% 69.8% 553 $ 42,234

 Total Bristol Bay Region 7,745 73.8% 66.7% 2,539 $ 48,010

State of Alaska 710,231 14.8% 73.6% 234,779 $ 66,712

Source: US Census Quickfacts. Quickfacts.census.gov 

29 
Table 10. Bristol Bay Area Communities and Populations

Bristol Bay Area Community Population 

(2010 census)

Aleknagik 219

Clark's Point 62

Dillingham 2,329

Egegik 109

Ekwok 115

Igiugig 50

Iliamna 109

King Salmon 374

Kokhanok 170

Koliganek 209

Levelock 69

Manokotak 442

Naknek 544

New Stuyahok 510

Newhalen 190

Nondalton 164

Pedro Bay 42

Pilot Point 68

Port Alsworth 159

Port Heiden 102

South Naknek 79

Ugashik 12

Togiak City 817

Portage Creek 2

Twin Hills 74

Figure 6. Bristol Bay Area Location and Major Communities

30 
This study focuses on the economic contributions of the Bristol Bay ecosystem. The rivers that 

flow into the Bristol Bay comprise some of the last great wild salmon ecosystems in North 

America (Figure 7). All five species of Pacific salmon are abundant, and the rich salmon-based 

ecology also supports many other fish species, including healthy populations of rainbow trout. 

The Naknek, Nushagak-Mulchatna, and Kvichak-Lake Iliamna watersheds are relatively pristine 

with very little roading or extractive resource development. The existing mainstays of the 

economy in this region are all wilderness-compatible and sustainable in the long run: subsistence 

use, commercial fishing, and wilderness sportfishing. Commercial fishing largely takes place in 

the salt water outside of the rivers themselves and is closely managed for sustainability. The 

subsistence and sportfish sectors are relatively low impact; primarily personal use and catch and 

release fishing, respectively. Additionally, there are important public lands in the headwaters, 

including Lake Clark National Park and Preserve, Katmai National Park and Preserve, and 

Togiak National Wildlife Refuge. 

The Bristol Bay area includes the political designations of Bristol Bay Borough, the Dillingham 

census area, and most of Lake and Peninsula Borough. The largest town in the area is 

Dillingham. In 2010 the Dillingham census area had an estimated population of 4,847 (US 

Census, Quick Facts).

31 
Figure 7. Map of Bristol Bay Study Area 

1.3 Focus of Study-Economic Uses

As noted, this report focuses on estimating baseline levels of ecosystem services provided by the 

Bristol Bay Region. These services are broad and substantial and include, but are not limited to 

commercial, aesthetic, recreational, cultural, natural history, wildlife and bird life, and ecosystem 

services.

A primary dichotomy of economic value is the division of values into those that are, or can be 

traded within existing economic markets, and those for which no developed market exists. 

Examples of ecosystem services specific to the Bristol Bay region that are traded in markets are 

commercial fish harvests and guided fishing trips. While a number of services provided by 

Bristol Bay natural resources can be classified as market services (with associated marketderived values), there are many services provided by this area that are classified as non-market 

services. These non-market resource services include noncommercial fishing, wildlife watching, 

subsistence harvests, protection of cultural sites, and aesthetic services.

A second dichotomy of resource services and associated values is that of direct use and passive 

use services and values. The most obvious type, direct use services, relates to direct onsite uses. 

The second type of resource services are so-called passive use services. These services have 

values that derive from a given resource and are not dependent on direct on-site use. Several 

types of passive use values were first described by Weisbrod (1964) and Krutilla (1967), and 

32 
include existence and bequest values. Existence values can derive from merely knowing that a 

given natural environment or population exists in a viable condition. For example, if there were 

a proposal to significantly alter the Bristol Bay natural ecosystem, many individuals could 

experience a real loss, even though they may have no expectation of ever personally visiting the 

area. Bequest values are associated with the value derived from preserving a given natural 

environment or population for future generations. While use values may or may not have 

associated developed markets for them, passive use services are exclusively non-market services.

When passive use and use values are estimated together, the estimate is referred to as total 

valuation. This concept was first introduced by Randall and Stoll (1983) and has been further 

developed by Hoehn and Randall (1989). 

The National Research Council in their 2005 publication “Valuing Ecosystem Services: Toward 

Better Environmental Decision Making” provided an outline of ecosystem services. Table 11 

provides an application of the NRC outline to Bristol Bay resources, and details examples of the 

ecosystem services, both use and passive use, that are produced by natural resources such as 

those found in the Bristol Bay region. 

Table 11: Types of Ecosystem Services

Use Values Nonuse Values

Direct Indirect Existence and Bequest 

Values

Commercial and recreational 

fishing

Aquaculture

Transportation

Wild resources

Potable water

Recreation

Genetic material

Scientific and educational 

opportunities

Nutrient retention and cycling

Flood control

Storm protection

Habitat function

Shoreline and river bank 

stabilization

Cultural heritage

Resources for future 

generations

Existence of charismatic 

species

Existence of wild places

A comprehensive economic evaluation of these Bristol Bay wild salmon ecosystems needs to 

include two distinct accounting frameworks. One is regional economics or economic 

significance, focused on identifying cash expenditures that drive income and job levels in the 

regional economy. The other is a net economic value framework that includes all potential costs 

33 
and benefits from a broader social perspective. The latter necessarily includes non-market and 

indirect benefits, such as the benefits anglers derive from their recreational activity, over and 

above their actual expenditure. Both perspectives are important for policy discussions and 

generally both accounting frameworks are utilized in evaluating public decisions. 

34 
2.0 Bristol Bay Recreation and Subsistence Economics 

Section 2 of this report addresses the regional economic activity associated with the recreation 

and subsistence sectors. Primary recreational activities examined include sportfishing, sport 

hunting, and tourism/wildlife viewing. 

2.1 Bristol Bay Sportfishing Economics

Sportfishing is a consistently economically significant economic activity in the Bristol Bay 

Region. Information sources for this section are the Duffield et al. (2007) report on Bristol Bay 

Salmon Ecosystem economics (referred to hereafter as the 2005 Bristol Bay Study), and Alaska 

Department of Fish and Game estimates of the total populations of anglers fishing the Bristol 

Bay Area waters. (pers. Comm. G. Jennings, August 2011) 

The sport angler and trip characteristics, expenditures, and values are presented using several 

sub-sample breakouts. Comparisons of sub-samples are presented to highlight similarities as 

well as differences between sample groups. Primary sub-samples examined include non-resident 

anglers, non-local Alaska resident anglers, and Bristol Bay resident anglers. 

The 2005 Bristol Bay study examined angler responses to a wide range of questions on their 

opinions, preferences, and experiences relating to fishing in the Bristol Bay area. The following 

sportfishing results focus on key characteristics of Bristol Bay sportfishing. Estimates of angler 

spending and net economic values have been adjusted from the original 2005 dollars to 2009 

dollars using the Consumer Price Index-Urban (CPI-U). 

2.1.1 Bristol Bay Area Trip Characteristics and Angler Attitudes

The 2005 Bristol Bay Study reported several differences between how nonresident anglers and 

Alaska anglers access Bristol Bay fisheries and the types of accommodations they use when 

there. For non-resident anglers the most common trip included staying at a remote lodge and 

flying or boating with a guide (35.2%). Resident anglers accessed the Bristol Bay area with their 

own plane or boat (49.9%), driving to area by motor vehicle (11.3%), and “other” type of trips 

(24%). Those who reported driving to access Bristol Bay fisheries were primarily residents and 

nonresidents staying in the King Salmon and Dillingham area, where a few local roads exist and 

provide some access to nearby fisheries.

35 
Table 12. Bristol Bay Angler Distribution across Trip Types, by Residency

Trip Type Non-residents 

(%)

Alaska 

Residents (%)

Stayed at a remote lodge and flew or boated with a guide to fishing 35.2 -

Stayed at a tent or cabin camp and fished waters accessible from camp 23.7 7.8

Hired other lodging in an area community and either fished on own or 

contracted for travel on a daily basis

6.4 4.2

Floated a section of river with a guided party 3.9 2.8

Hired a drop-off service and fished and camped on our own 4.3 2.2

Accessed the area with my own airplane or boat 8.3 49.9

Drove to the area by motor vehicle 4.3 11.3

Other 14.0 24.0

Sample Size 246 55

Note: sample size for resident sample is not large enough to divide into local and non-local sub-samples

35%

24%

15%

8%

4%

14%

0%

8%

9%

50%

11%

24%

0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00%

Stayed at a remote

lodge

Stayed at a tent or cabin

camp

Hired float, drop off, or

other lodging

Accessed area with own

boat or plane

Drove to area

Other

Percent of respondents

Nonresidents Residents

Figure 8. Comparison of Resident and Nonresident Bristol Bay Angler Trip Types

Respondents to the 2005 Bristol Bay survey were asked what was the primary purpose of their 

trip to the Bristol Bay area. A majority of nonresidents (73%) reported fishing as their major 

purpose; 30% of resident anglers reported fishing as the main purpose of their most recent 

Bristol Bay trip. Table 13 also shows that a much larger proportion of non-residents (45%) than 

residents (11.4%) were on their first trip to their primary fishing destination.

36 
Table 13: Bristol Bay Angler Trip Characteristics.

Statistic Nonresidents

(sample size)

Alaska Residents

Major purpose of trip 

was for fishing

72.7%

(246)

29.5%

(54)

Trip was first trip to 

primary destination

45.2%

(245)

11.4%

(48)

Survey respondents in the 2005 study were asked what fish species they targeted on their most 

recent trip to Bristol Bay. Table 14 reports these results. Overall, king salmon and rainbow trout 

were the most frequently targeted species for both residents and non-residents. 

Table 14: Bristol Bay Angler Survey, Targeted Species. 

Bristol Bay Anglers

Primary species targeted on 

trip / statistic

Nonresidents Alaska Residents

Rainbow Trout 30.6% 31.3%

King Salmon 35.2% 29.8%

Silver Salmon 16.3% 16.5%

Sockeye Salmon 9.1% 0%

Other Species 8.8% 22.4%

 Sample size 235 48

Respondents to the 2005 Bristol Bay angler survey were presented with a series of statements 

regarding fishing conditions on their Bristol Bay area trip. They were asked to indicate their 

level of agreement or disagreement with each statement. Table 15 shows the percent of residents 

and non-residents who either “agreed” or “strongly agreed” with each statement. Across all of 

the statements presented in the survey, majorities of both resident and non-resident respondents 

agreed with the positive statements about their fishing experience. The highest levels of 

agreement for both nonresidents and Alaska resident anglers were with the statements “there was 

a reasonable opportunity to catch fish”, “there was minimal conflict with other anglers”, and 

“fishing was in a wilderness setting.” 

37 
Table 15: Bristol Bay Angler Rating of Selected Attributes of Fishing Trip

Statement % of respondents who either 

"agree" or "strongly agree"

Nonresidents Alaska Residents

Fishing conditions were un-crowded 87.2% 75.4%

There was a reasonable opportunity to catch fish 96.5% 93.0%

There was minimal conflict with other anglers 93.3% 90.7%

Fishing was in a wilderness setting 92.4% 95.0%

There was opportunity to catch trophy-sized fish 81.4% 70.0%

There was opportunity to catch and release large # of fish 87.3% 76.6%

Sample Size 235 47

2.1.2 Bristol Bay Angler Expenditures

Respondents to the 2005 Bristol Bay angler survey were asked a series of questions relating to 

the amount of money they spent on their fishing trips. Average spending per trip was estimated 

for three types of anglers: local Bristol Bay Area residents, Alaska residents from outside the 

Bristol Bay region, and nonresidents. Adjusted to 2009 price levels, nonresidents reported 

spending the most for their sportfishing trips to Bristol Bay ($3,995). Alaska resident anglers, 

those from outside Bristol Bay spent an average of $1,582 per trip and those living within the 

Bristol Bay region reported spending an average of $373 per sportfishing trip. 

Table 16 breaks out average expenditures by impact region and type of fishing trip for the 

nonresident angler sample. Where money is spent on a trip determines local economic impacts. 

For instance, a given amount of money spent within the very small Bristol Bay economy has a 

much greater relative impact than the same amount of money spent in a larger economy, such as 

Anchorage. Table 16 shows that the largest per-trip spending is made by nonresident anglers 

who stay at a remote lodge with daily guiding services ($6,950/trip). This compares to the 

lowest spending levels per trip of about $1,400 for driving to the fishing site, accessing the area 

with own plane or boat, and hiring a drop-off service and fishing or camping on own. 

The first two rows of Table 16 show that a large portion of Alaska trip costs for remote lodge or 

tent or cabin camp trips is associated with the cost of a sport-fishing package or tour. This sportfishing package spending is assumed to be spent in the Bristol Bay region. 

38 
Table 16. Nonresident Trips to Bristol Bay Waters, Mean Expenditure Per Trip Estimates 

By Trip Type

Trip type Total Reported 

Trip Spending

Bristol Bay 

spendinga 

Package sportfishing trip 

spending

Stayed at a remote lodge and flew or boated with a 

guide to fishing sites most days $6,950 $1,900 $6,089

Stayed at a tent or cabin camp and fished waters 

accessible from this base camp $4,158 $1,357 $3,517

Hired other lodging in an area community and either 

fished on own or contracted for travel on a daily 

basis $2,643 $1,818 $2,576

Floated a section of river with a guided party $2,187

Hired a drop-off service and fished and camped on 

our own $1,515 $1,145

Accessed the area with my own airplane or boat $1,437 $1,291

Drove to the area by motor vehicle $1,453 $1,062

Other $2,233 $1,047 $2,422 a all spending in Bristol Bay except package sportfishing trip expenditures (package trip expenditures are also assumed spent in 

the Bristol Bay Region)

Note: cells with less than 5 observations are left blank. Category values are the average values for those respondents reporting an 

expense in that category. Bristol Bay spending and Package sport-fishing tour spending will not necessarily sum to Total spending 

due to varying sample sizes.

Table 17 details the distribution of Bristol Bay trip spending across expenditure categories. For 

non-residents visitors, the largest three spending categories within the Bristol Bay area were for 

commercial and air taxi service and for lodging or camping fees (totaling about 66% of all 

spending in Bristol Bay). For non-local Alaska residents the three largest categories of spending 

were “gas and other Alaska travel costs,” camping fees, and commercial air travel (totaling about 

58% of all Bristol Bay spending by non-local Alaska residents).

Table 17: Distribution of Trip Expenditures across Spending Categories, by Residency and 

Area

Nonresidents non-local AK 

residents

Expenditure category In Bristol Bay In rest of AK In Bristol Bay

Commercial air travel 31.1% 51.9% 18.1%

Air taxi service 20.5% 1.3% 11.1%

Transportation by boat 0.0% 0.0% 0.0%

Boat or vehicle rental 5.3% 4.8% 7.5%

Gas or other travel costs in AK 4.1% 1.4% 16.3%

Lodging or camping fees 13.9% 11.9% 23.6%

food or beverages 9.2% 19.3% 16.7%

Guide fees 6.2% 0.6% 0.0%

Fishing supplies 4.1% 5.2% 6.7%

Other non-fish package tours 0.1% 0.7% 0.0%

Other 5.4% 2.9% 0.0%

39 
2.1.3 Aggregate Direct Sport fishing Expenditures in Bristol Bay 

In order to derive estimated aggregate angler expenditures related to sportfishing in the Bristol 

Bay region, two primary pieces of information were needed: 1) the number of angler trips per 

year to the region by Alaska residents and nonresidents, and 2) the average spending per trip by 

resident and nonresident anglers. A trip is defined here as a roundtrip visit from home, and 

return. Estimates of the number of anglers who fished in the Bristol Bay region in 2009 were 

derived by ADF&G staff (Table 18). The average number of trips per angler, estimated from 

responses to the 2005 Bristol Bay angler survey, is also shown in Table 18. In total 

approximately 29,000 sport fishing trips were taken in 2009 to Bristol Bay freshwater fisheries. 

These trips are roughly split between 12,000 nonresident trips, 13,000 Bristol Bay resident trips, 

and 4,000 trips by Alaskans living outside of the Bristol Bay area.

Table 18. Estimated 2009 Bristol Bay area angler trips, by Angler Residency

Statistic Nonresidents Out-of-area AK 

residents

BB Residents

Annual Anglers 

fishing Bristol Bay 

waters

9,572 2,561 1,133 

Average trips per 

angler for 2005 

1.30 1.49 11.54

Estimated total 

trips

12,464 3,827 13,076 

Table 19 presents the aggregation of total angler expenditures within the Bristol Bay region. 

This table shows average and aggregate estimated expenditures for three angler groups: 1) 

nonresident anglers, 2) local-area resident anglers (those who live in the Bristol Bay area), and 3) 

non-local resident anglers (those Alaska residents living outside of the Bristol Bay region). This 

table also shows average and total annual spending by nonresident anglers for package 

sportfishing trips in the Bristol Bay region.

Overall, the large majority of angler spending in the region is attributable to nonresident anglers. 

Additionally, the majority of nonresident spending is due to the purchase of sportfishing 

packages such as accommodation and angling at one of the areas remote fishing lodges. 

Estimates of variability were derived for average expenditure levels, and total visitation 

estimates. It is estimated that annually Bristol Bay anglers spend approximately $58 million 

within the Bristol Bay economy. Given the variability in the components of this estimate, the 

95% confidence interval for Bristol Bay area spending by anglers from outside the area ranges 

from $0 to $130 million annually. The vast majority of this spending (approximately $47 million 

annually) is spent by nonresident anglers. 

40 
Table 19. Estimated Aggregate Spending Associated with Sportfishing in the Bristol Bay 

Region (2009 dollars) 

Nonresidents out-of-area AK 

residents

BB Residents Total

All Non Residents Remote Lodge 

Increment 

Mean expenditures in Bristol 

Bay region

$ 1,471 $4,698 $ 1,582 $ 373

Estimated trips 12,464 6,187 3,827 13,076 29,367

Total Bristol Bay direct 

expenditures 

$ 18,333,187 $ 29,068,303 $ 6,053,700 $ 4,874,848 $ 58,330,039

Table 20 presents total estimated direct angler expenditures by residency, and location of 

spending. Again, among all direct spending related to Bristol Bay angling, the large majority is 

associated with nonresidents traveling to Alaska. Additionally, the large majority of this 

spending is reported to have occurred within the Bristol Bay economy. This table categorizes 

spending by origin and destination. This classification is then used in the regional economic 

significance analysis presented in Section 4. 

Table 20. Bristol Bay Sportfishing: Aggregate in and out of Region and State Spending

(2009) 

Population In Bristol Bay Spending In Alaska Spending

Total spending in 

Bristol Bay

Total spending 

from outside 

Bristol Bay

Total in-state 

spending 

Spending from 

outside Alaska

NONRESIDENT Base trip spending $ 18,333,187 $ 18,333,187 $ 20,727,318 $ 20,727,318 

NONRESIDENT Sportfish package 

spending $ 29,068,303 $ 29,068,303 $ 29,068,303 $ 29,068,303 

 NONRESIDENT TOTAL $ 47,401,490 $ 47,401,490 $ 49,795,621 $ 49,795,621 

RESIDENTS

 OUT-OF-BB RESIDENT base trip 

spending $ 6,053,700 $ 6,053,700 $ 6,053,700 $ - 

 BB RESIDENT base trip spending $ 4,874,848 $ - $ 4,874,848 $ - 

 ALASKA RESIDENT TOTAL $ 10,928,549 $ 6,053,700 $ 10,928,549 $ - 

TOTAL $ 58,330,039 $ 53,455,190 $ 60,724,170 $ 49,795,621 

41 
2.2 Bristol Bay Subsistence Harvest Economics 

The subsistence harvest within the Bristol Bay region generates regional economic impacts when 

Alaskan households spend money on subsistence-related supplies. Goldsmith (1998) estimated 

that Alaskan Native households that use Bristol Bay wildlife refuges for subsistence harvesting 

spend an average of $2,300 per year on subsistence-related equipment to aid in their harvesting 

activities. Additionally, Goldsmith estimated that Non-Native households spend $600 annually 

for this purpose. Correcting for inflation from 1998 to 2009 implies annual spending for 

subsistence harvest of about $3,054 for Native households and $796 for Non-Native 

households.7

 

Figure 9 shows the general distribution of subsistence harvest by Bristol Bay residents. Overall, 

salmon make up the largest share of all harvest (on a basis of usable pounds), and accounts for 

over one-half of all harvest. Another nearly one third of harvest come from land mammals 

(31%), and non-salmon fish comprise another 10% of harvest.

7 A 1998-99 survey of the village of Atyqasuk (North Slope Borough) found that 33% of households spent between 

$4,000 and $10,000 on subsistence activities and 9% spent more than $10,000 per year (US DOI, BLM and MMS 

2005). The simple parametric mean for this inland community that harvested no whales was $3,740 per year per 

household (1999 dollars). The use of the adjusted Goldsmith estimates therefore likely provides a conservative 

estimate of subsistence expenditures.

42 

 
 Salmon

52%

Land Mammals

31%

Marine Mammals

2%

Marine Invertebrates

Birds and Eggs 0%

2%

Vegetation

3%

 Non-Salmon Fish

10%

Figure 9. Distribution of Bristol Bay Subsistence Harvest

Table 21 shows average per capita and total estimated community subsistence harvest for the 

Bristol Bay communities. In total, individuals in these Bristol Bay communities harvest about 

2.6 million pounds of subsistence harvest per year for an average of 343 pounds per person 

annually. Table 22 and Table 23 detail Bristol Bay area subsistence harvest by salmon species 

and location. 

Table 21. ADF&G Division of Subsistence Average Per Capita Subsistence Harvest for 

Bristol Bay Communities

Bristol Bay Area Community /year 

of AKF&G harvest data survey

Population 

(2010 census)

Per Capita Harvest

(raw pounds of 

harvest)(AKF&G 

Subsistence 

Surveys)

Total Annual 

Harvest

Aleknagik 2008 219 296 64,824

Clark’s Point 2008 62 1210 75,020

Dillingham 1984 2,329 242 563,618

Egegik 1984 109 384 41,856

43 
Ekwok 1987 115 797 91,655

Igiugig 2005 50 542 27,100

Iliamna 2004 109 469 51,121

King Salmon 2008 374 313 117,062

Kokhanok 2005 170 680 115,600

Koliganek 2005 209 899 187,891

Levelock 2005 69 527 36,363

Manokotak 2008 442 298 131,716

Naknek 2008 544 264 143,616

New Stuyahok 2005 510 389 198,390

Newhalen 2004 190 692 131,480

Nondalton 2004 164 358 58,712

Pedro Bay 2004 42 306 12,852

Pilot Point 1987 68 384 26,112

Port Alsworth 2004 159 133 21,147

Port Heiden 1987 102 408 41,616

South Naknek 2008 79 268 21,172

Ugashik 1987 12 814 9,768

Togiak City 2000 817 246 200,982

Twin Hills 2000 74 499 36,926

 Total surveyed communities 7,018

Un-surveyed communities 457 --

Total including un-surveyed areas 7,475 343 2,563,313

44 
Table 22. Historical Subsistence Salmon Harvest for Bristol Bay, Alaska: 1975-2007 

(ADF&G Division of Subsistence ASFDB) 

Year Permits

Number of Fish Harvested

Chinook Sockeye Coho Chum Pink Total

Harvest 

per permit

1975 686 8,600 175,400 8,500 7,500 1,300 192,700 280.9

1976 716 8,400 120,900 3,500 9,100 4,400 137,900 192.6

1977 738 7,000 127,900 6,600 9,100 300 143,900 195

1978 773 8,100 127,600 4,400 16,200 12,700 160,900 208.2

1979 829 10,300 116,500 7,300 7,700 500 132,000 159.2

1980 1,243 14,100 168,600 7,300 13,100 10,000 199,000 160.1

1981 1,112 13,000 132,100 12,200 11,500 2,600 158,400 142.4

1982 806 13,700 110,800 11,500 12,400 8,600 143,300 177.8

1983 829 13,268 143,639 7,477 11,646 1,073 177,104 213.6

1984 882 11,537 168,803 16,035 13,009 8,228 217,612 246.7

1985 1,015 9,737 142,755 8,122 5,776 825 167,215 164.7

1986 930 14,893 129,487 11,005 11,268 7,458 174,112 187.2

1987 996 14,424 135,782 8,854 8,161 673 167,894 168.6

1988 938 11,848 125,556 7,333 9,575 7,341 161,652 172.3

1989 955 9,678 125,243 12,069 7,283 801 155,074 162.4

1990 1,042 13,462 128,343 8,389 9,224 4,455 163,874 157.3

1991 1,194 15,245 137,837 14,024 6,574 572 174,251 145.9

1992 1,203 16,425 133,605 10,722 10,661 5,325 176,739 146.9

1993 1,206 20,527 134,050 8,915 6,539 1,051 171,082 141.9

1994 1,193 18,873 120,782 9,279 6,144 2,708 157,787 132.3

1995 1,119 15,921 107,717 7,423 4,566 691 136,319 121.8

1996 1,110 18,072 107,737 7,519 5,813 2,434 141,575 127.5

1997 1,166 19,074 118,250 6,196 2,962 674 147,156 126.2

1998 1,234 15,621 113,289 8,126 3,869 2,424 143,330 116.2

1999 1,219 13,009 122,281 6,143 3,653 420 145,506 119.4

2000 1,219 11,547 92,050 7,991 4,637 2,599 118,824 97.5

2001 1,226 14,412 92,041 8,406 4,158 839 119,856 97.8

2002 1,093 12,936 81,088 6,565 6,658 2,341 109,587 100.3

2003 1,182 21,231 95,690 7,816 5,868 1,062 131,667 111.4

2004 1,100 18,012 93,819 6,667 5,141 3,225 126,865 115.3

2005 1,076 15,212 98,511 7,889 6,102 1,098 128,812 119.7

2006 1,050 12,617 95,201 5,697 5,321 2,726 121,564 115.8

2007 1,063 15,444 99,549 4,880 3,991 815 124,679 117.3

Average 1,035 13,825 121,906 8,329 7,733 3,099 152,371 153

45 
Table 23. Bristol Bay Subsistence Salmon Harvests by District and Location Fished, 2007. 

(Fall et al. 2009) 

46 
In 2010 the US Census reported an estimated 1,873 Native and 666 non-native households in the 

Bristol Bay Region (Bristol Bay Borough, Lake and Peninsula Borough, and Dillingham). Based 

on the Goldsmith (1998) estimate of direct expenditures related to subsistence harvest, this 

implies an annual direct subsistence-related expenditure of approximately $6.3 million in the 

Bristol Bay region. 

Table 24. Estimated Total Annual Bristol Bay Area Subsistence-Related Expenditures

(2009 $) 

Area Population 

2010 

Percent Alaska 

native 

Number of 

households 

Number of 

Native 

Households 

Number of 

non-native 

Households 

Bristol Bay Borough 997 48.2% 423 204 219

Dillingham Census Area 4847 74.6% 553 413 140

Lake & Peninsula Borough 1631 80.4% 1563 1257 306

 Total Bristol Bay Region 7,475 73.8% 2539 1873 666

Annual Spending/ household $ 3,054 $ 796 

Total Estimated 

Subsistence Spending $ 5,720,054 $ 530,350

Total $ 6,250,404 

2.3 Bristol Bay Sport Hunting and Non-consumptive 

Economics 

2.3.1 Sport Hunting

In addition to sport fishing, sport hunting also plays a significant (but smaller) role in the local 

economy of the Bristol Bay region. While not a large share of the economy, sport hunting in the 

Bristol Bay area offers high quality hunting opportunities for highly valued species. Bristol Bay 

sport hunting provides hunting opportunities for caribou, moose, and brown bear, among other 

species. Table 25 shows reported hunter numbers for the most recently reported representative 

years for several species hunted in the region. The big game hunting numbers are reported for 

the two Game Management Units (GMUs) that comprise the Bristol Bay Region. GMUs are 

spatial areas delineated by AKF&G to more closely correspond to wildlife habitat and population 

ranges than do other geographical or political boundaries. 

47 
Table 25. ADF&G Reported Big Game Hunting in Bristol Bay and Alaska Peninsula Game 

Management Units

Most recent Big Game Hunting Estimates from ADF&G Wildlife Management Reports

(Number of hunters) 

Alaska Peninsula 

(GMU 9)

Bristol Bay 

(GMU 17) 

 

 

 

 

Non-local 

Residents

Nonreside

nts

Non-local 

Residents Nonresidents

Moose 91 157 200 195

Caribou 0 0 311 230

Brown bear 600 624 117 117

691 781 628 542

The caribou estimate for GMU 17 is for the Mulchatna herd and extends beyond GMU 17 borders

Shaded cells include both non-local residents and local residents

Sources: AKDF&G Species-specific Wildlife Management Reports

Table 26 outlines the estimation of total annual expenditures for big game hunting within the 

Bristol Bay region. These estimates are based on an assumption of one trip per hunter per year 

for a species, and utilize estimates of hunter expenditures per trip developed by Miller and 

McCollum (1994) adjusted to 2009 price levels.

Table 26. Estimated annual big game hunting expenditures for Bristol Bay region

Statistic Non-local Residents Nonresidents

Estimated trips 1,319 1,323 

Expenditure per trip $ 1,068 $ 5,170 

Total estimated direct 

expenditure $ 1,408,351 $ 6,839,301 

Total $ 8,247,652.52 

In total, it is estimated that Bristol Bay area big game hunters living outside of the area spend 

about $8.2 million per year in direct hunting-related expenditures. The expenditure estimate 

above may include some caribou hunting of the Mulchatna herd outside of the closely defined 

Bristol Bay region game management units, resulting in an overestimate of spending for hunting 

this species. 

2.3.2 Non-consumptive Wildlife Viewing / Tourism Economics

Many of the sport fishing and sport hunting visitors to the Bristol Bay region also engage in 

other activities such as kayaking, canoeing, wildlife viewing or bird watching. These activities 

48 
are typically referred to as non-consumptive because unlike hunting or fishing, no resource is 

“consumed,” rather the goal is to leave the resource (flora and fauna) unchanged.

The Bristol Bay region has a number of nationally-recognized special management areas for 

wildlife. These include Katmai and Lake Clark National Parks, the Togiak and Becherof 

National Wildlife Refuges, and Wood-Tikchick State Park. The most accessible and popular 

destination for visitors interested in non-consumptive recreation activities is Katmai National 

Park, and in particular Brooks Camp on Naknek Lake which is world famous as a site for bear 

viewing. The camp accommodates both day and overnight visitors who are there to view the 

bears, as well as sport fishermen.

Information on the number of non-consumptive use visitors, their itineraries and activities while

in the region, and their expenditures is somewhat limited. Unlike sport fishing and sport hunting, 

no license is required for these other activities so there is no consistent and comprehensive 

record documenting these trips. 

The visitation estimates that form the basis for the analysis of non-consumptive use in Southwest 

Alaska are primarily based on McDowell Group's (2006) Alaska Visitor Statistics Program 

(AVSP) estimate . The AVSP is a comprehensive State of Alaska research program initiated in 

1982 and follows a strict and proven methodology. The methodology utilizes an exit survey to 

intercept visitors. As a result of the concentration of visitors in urban parts of the state, the 

survey method tends to oversample urban visitors and undersample rural visitors. Based on a 

separate stratified rural sample conducted during the 2001 AVSP, it is known that the survey 

methodology tends to underestimate visitation to remote rural parts of the state such as 

Southwest Alaska. Thus, the overall visitation used for this analysis can be considered 

conservative. In addition to McDowell Group (2006), Fay and Christensen (2011)'s 2007 

estimate of visitation to Katmai was utilized. 

For this analysis non-consumptive users are defined as those who reported wildlife viewing, 

camping, kayaking, hiking, or photography as their primary purpose of their visit. We adjust the 

most recent 2006 summer and winter visitor estimate for Southwest Alaska excluding Kodiak by 

applying the 2006-2009 percent difference in air travelers for Alaska overall (McDowell Group, 

2007a & 2007b). The trend in air travelers to Alaska serves as the best indicator for changes to 

visitation in Southwest Alaska for two reasons. First, visitors to rural Alaska are mainly 

independent travelers, and second they primarily arrive by air in comparison to the statewide 

largest share of visitors who arrive by cruise ship. The Southwest Alaska region closely matches 

the Bristol Bay study region with the exception of Kodiak and the Aleutian Islands. Our analysis 

excludes Kodiak but includes an insignificant portion of visitors to the Aleutian Islands. 

Since the Alaska Visitor Statistics Program counts out-of-state visitors only, we calculate visitor 

volume originating within the state based on Littlejohn and Hollenhorst (2007) and Colt and 

Dugan (2005) resident share of between ten and eleven percent. We treat visitation to Katmai 

NPP separate from other areas of the Bristol Bay region. Visitor volume and expenditure for 

Katmai NPP are from Fay and Christensen (2010) and for the remaining Bristol Bay area are 

from McDowell Group (2007a). We net out sport fishing and hunting visitation in Katmai NPP 

using Littlejohn and Hollenhorst (2007) and for the rest of the region by applying the McDowell 

49 
Group (2007a and 2007b) estimate. We assume equal expenditures for residents and nonresidents because the non-resident per person expenditure estimate in both cases does not include 

the cost of travel to and from Alaska. For most non-residents all in-state travel expenditures are 

included, based on the assumption that the primary reason for the travel to Alaska is the visit the 

Bristol Bay region. For all of these estimates, we paid special attention to the potential for double 

counting and addressed those issues. 

Based on the most recent studies of non-resident visitors to the state and two studies that 

estimated visitation and economic impacts related to Katmai National Park and Preserve, we 

estimate that on an annual basis including summer and winter visitation, approximately 2,300 

residents and 18,900 non-residents visited Katmai NPP. Other areas in the Bristol Bay region 

received approximately 2,300 resident visitors and 19,000 non-resident visitors. Note, these 

estimates exclude visitation where sport fishing or sport hunting was in part or the primary 

activity of choice. After adjusting the per capita expenditures to 2009 dollars we estimate per 

person expenditures to amount to $2,245 annually for Katmai NPP and $2,873 per person 

annually for visiting other destinations in the Bristol Bay region. 

To be consistent with the expenditure data for sport fishing and hunting, we assume that the visit 

to the Bristol Bay region was the primary reason for their visit to Alaska. Based on these 

assumptions, 2009 total expenditure for this group is estimated to be $104.2 million. 

It should be noted that an earlier estimate of Bristol Bay non-consumptive (wildlife watching) 

visitor expenditures (Duffield et al. 2007) reported a much lower spending level by this group 

($17.1 million). As noted in that report, the estimate was based on extremely limited and dated 

information from one location within the region (Brooks Camp). The estimate was derived and 

presented as an approximation, as was also noted in the report, “This is an approximate estimate 

based on limited and outdated information, and is an area for further research.”(Duffield et al. 

2007, p. 91). 

The estimates derived in this later, current report utilizes both visitation and expenditure 

estimates that were not available when the earlier report was drafted.

 

50 
3.0 Bristol Bay Commercial Fisheries

3.1 Introduction

This section provides an economic overview of Alaska’s Bristol Bay commercial salmon 

industry. The report begins with a brief overview of the industry. Subsequent sections discuss 

harvests, products and markets, prices, harvest and wholesale value, fishermen, processors, 

employment, taxes, the regional distribution of permit holders, fishery earnings and processing 

employment, and the role of the industry in the Bristol Bay regional economy. The final section

discusses selected economic measures of the Bristol Bay salmon industry.

A challenge in characterizing the Bristol Bay fishery is that there is wide variation from year to 

year in catches, prices, earnings, employment and other measures of the fishery. No single 

recent year or period is necessarily “representative” of the fishery or what it will look like in the 

future. To illustrate the range of historical variation in the fishery, wherever possible this report 

provides data or graphs for at least the years since 2000, and in many cases for longer periods. 

This report focuses on the economic significance of the entire Bristol Bay commercial salmon 

fishery. The fishery harvests salmon returning to several major river systems, including the 

Nushagak and Kvichak. Currently, because of potential future resource development in these 

watersheds, there is particular interest in the fisheries resources and economic significance of 

these two river system. As discussed in greater below, historically the relative contribution of 

these river systems to total Bristol Bay commercial salmon harvests has varied widely from year 

to year and over longer-term periods. There is no simple way to characterize what share of the 

Bristol Bay commercial fishery is attributable to the Nushagak and Kvichak river systems, or 

what this share will be in the future. 

Some of the prices and values presented in this report are presented as nominal prices and values 

(not adjusted for inflation), and others are presented as real prices and values (adjusted for 

inflation). In general, we used nominal prices where our primary purpose was to show actual 

prices and values over time (and as they appeared to people over time), and we used real prices 

where our primary purpose was to compare prices and values over time. Prices and values are 

expressed in nominal dollars except where the report specifically notes that they are real dollars. 

All real prices are expressed in 2010 dollars, as calculated using the Anchorage Consumer Price 

Index. This is far from an ideal measure, but it is the only long-term measure of inflation 

available for any Alaska location.

8

8 In theory, it may appear more technically accurate to express all prices in real dollars. In 

practice, there are several reasons why nominal prices are preferable for much of the data 

presented in this report. First, it is far from obvious what the measure of inflation should be: 

while the Anchorage CPI is the best available measure, it is not necessarily a good 

characterization of the inflation actually experienced by Bristol Bay fishermen or processors. 

Secondly, when price or value data are converted to “real” values it is harder to compare them to 

other data unless those data have been converted to real values for the same year. Data 

converted to real dollars quickly use their utility as a reference source. Third, people familiar 

51 

 
The report presents a wide variety of data for the Bristol Bay salmon industry in graphs and 

tables as well as in the text of the report. Detailed information on the data sources for all graphs , 

tables and text are provided in the data appendix at the end of the report. The report is based on 

data available as of October 2011. 

We’ve included pictures in the report to help readers who haven’t had the opportunity to visit 

Bristol Bay to have a sense of what the industry looks like. Except where otherwise noted, 

pictures in the report were taken by Gunnar Knapp. 

3.2 Overview of the Bristol Bay Salmon Industry

The Bristol Bay salmon fishery is one of the world’s largest and most valuable wild salmon 

fisheries. Between 2006 and 2010, the Bristol Bay salmon industry averaged: 

• Annual harvests of 31 million salmon (including 29 million sockeye salmon) 

• 51% of world sockeye salmon harvests 

• Annual “ex-vessel” value (the value earned by fishermen) of $129 million

• Annual first wholesale value after processing of $268 million. 

• 26% of the “ex-vessel” value to fishermen of the entire Alaska salmon harvest.

• Seasonal employment of more than 6800 fishermen and 3700 processing workers. 

Bristol Bay is located in southwestern Alaska. Each year tens of millions of sockeye salmon 

return to the major river systems which flow into Bristol Bay, of which the most significant (in 

numbers of returning salmon) are the Nushagak, Kvichak, Naknek and Egegik Rivers. Sockeye 

salmon spend a year or more in freshwater lakes before migrating to saltwater. The large lakes 

of the Bristol Bay region provide habitat for sockeye salmon during this life stage. 

with the Bristol Bay fishing industry remember what fish and permit prices actually were in any 

given year: it is harder for them to recognize and believe prices or values converted to real 

dollars.

52 

 
Figure 10. Major Bristol Bay River Systems 

Map source: www.purebristolbay.com/images/layout/BBNC_Base_Map-800.jpg 

Almost all Bristol Bay commercial fish harvests occur during a brief four-week season from 

mid-June to mid-July. At the peak of the season, millions of salmon may be harvested in a single 

day. 

The Naknek River near King Salmon

53 
Two kinds of fishing gear are used in the Bristol Bay fishery: drift gillnets (operated from 

fishing boats) and set gillnets (operated from shore). Drift gillnets account for most of the total 

catch. Technically, the drift gillnet fishery and the set gillnet fishery are managed as separate 

fisheries. 

Both the drift gillnet fishery and the set gillnet fishery are managed under a “limited entry” 

management system which was implemented for all of Alaska’s twenty-seven salmon fisheries in 

the mid-1970s. The basic purpose of the limited entry system is to limit the number of boats 

fishing in each fishery, which makes it easier for managers to control the total fishing effort and 

makes the fishery more profitable for participants than it would be if entry (participation) were 

unrestricted and more boats could fish. Every drift gillnet fishing boat or set net operation must 

have a permit holder on board or present—so the number of boats or set net operations cannot 

exceed the number of permit holders. There are approximately 1860 drift gillnet permits and 

approximately 1000 set net permits. Section 3.7 below (Bristol Bay Salmon Fishermen) 

provides more details about the limited entry system and Bristol Bay management regulations. 

Drift Gillnet Boats Fishing in the Naknek River

The Bristol Bay salmon harvest is processed by about 10 large processing companies and 20 

smaller companies employing about 3700 processing workers at the peak of the season in both 

land-based and floating processing operations. Most of the land-based processors operate only 

during the short summer salmon season. Most of the workers are flown in from outside the 

region and live in bunkhouse facilities at the processing plants. 

54 
The Ekuk Processing Plant in the Nushagak District near Dillingham, photographed at low tide. Extreme tides 

complicate logistics for land processing facilities in Bristol Bay. At many plants, fish can be delivered only when 

the tide is in.

Most Bristol Bay salmon is processed into either frozen headed and gutted salmon or canned 

salmon. Formerly almost all Bristol Bay frozen salmon was exported to Japan. In recent years 

exports to Japan have declined sharply while shipments to the U.S. domestic market have 

increased and exports have increased to Europe and to China (for reprocessing into fillets sold in 

Europe, Japan and the United States). Most canned salmon is exported, primarily to the United 

Kingdom, Canada, and other markets. 

Bristol Bay salmon catches vary widely from year 

to year and over longer periods of time. Catches 

set all-time records in the early 1990s, fell sharply 

after 1995, and then rose again after 2002. The 

2011 catch was about 25% lower than the average 

for the previous five years. 

Wholesale prices for Bristol Bay salmon products 

and “ex-vessel” prices paid to fishermen increased 

during the 1980s, peaked in 1988, and then 

declined dramatically during the 1990s. The main 

cause of the decline in prices was competition in 

world markets from dramatically increasing world 

production of farmed salmon, although many 

other factors also contributed. Since 2001, 

wholesale and ex-vessel prices have been 

increasing, as the growth of farmed salmon 

production has slowed and new markets for 

Bristol Bay sockeye salmon have been developed. 

The decline in catches and prices during the 1990s 

led to a drastic decline in value in the Bristol Bay 

Fish on a Bristol Bay fishing boat

Photograph by Gabe Dunham

55 
salmon fishery. The ex-vessel value paid to fishermen fell from a peak of $214 million in 1990 

to just $32 million in 2002. The loss in value led to a severe economic crisis in the Bristol Bay 

salmon industry. Many land-based salmon processing operations closed and many floating 

processors left Bristol Bay. Many fishing permit holders stopped fishing, and permit prices fell 

drastically.

As catches and prices have improved since 2002, the Bristol Bay salmon industry has 

experienced a significant economic recovery. The ex-vessel value paid to fishermen increased 

to $149 million in 2010. Participation in the fishery has increased and permit prices have 

strengthened. Among both fishermen and processors there is a renewed sense of optimism about 

the economic future of the Bristol Bay salmon industry, taking advantage of growing world 

demand for wild salmon. This optimism is tempered by recognition of the variability of harvests 

and value associated with fluctuations in salmon returns and markets. 

A tender, floating processor, and freighter anchored in the Nushagak district

Photograph by Gabe Dunham

A Bristol Bay processing worker holding a sockeye salmon

Photograph by Gabe Dunham 56 
3.3 Bristol Bay Salmon Harvests

Although all five species of Pacific salmon are caught in Bristol Bay, commercial salmon 

harvests are overwhelmingly sockeye salmon. Between 2001 and 2010, sockeye accounted for 

94% of total Bristol Bay salmon catches. Except where otherwise noted, references in this report 

to harvests, production, prices, etc. are specifically for Bristol Bay sockeye salmon. 

Between 1975 and 2010, annual Bristol Bay commercial sockeye salmon harvests ranged from 5 

million to 44 million fish, with an annual average of 22.5 million fish. Harvests increased from 

depressed levels of less than 6 million fish in the mid-1970s to more than 15 million fish for 

most of the 1980s and more than 25 million fish annually for the years 1989-1996. Sockeye 

salmon harvests peaked at 44 million fish in 1995. Harvests then fell off sharply to lows of 10 

million fish in 1998 and 2002 before rebounding to 29 million fish in 2007 and 31 million fish in 

2009—the highest sockeye harvest since 1995. The 2011 harvest of 22 million fish was 

significantly lower than the previous five years and the lowest since 2003. 

Bristol Bay Commercial Salmon Harvests

0

5

10

15

20

25

30

35

40

45

50

1975197719791981198319851987198919911993199519971999200120032005200720092011

Source: Commercial Fisheries Entry Commission; Alaska Department of Fish and Game

millions of fish

Other

Species

Sockeye

Figure 11. Bristol Bay Commercial Salmon Harvests. 

57 
The average weight of a Bristol Bay sockeye salmon is typically about 6 pounds. Between 1975 

and 2010 average weights varied from as low as 5.3 pounds to as high as 6.7 pounds. . There 

was no significant trend in average fish weight over this period. Fish weight tended to be 

slightly lower in years when more fish were harvested.9 

Bristol Bay sockeye salmon harvests may be expressed either in fish, pounds, or metric tons. 

Over the period 1975-2010, sockeye salmon harvests averaged: 

 22.7 million sockeye 

 = 133 million pounds (@ average weight of 5.9 pounds per fish) 

 = 60,200 metric tons (@ 2204.6 pounds per metric ton) 

For commercial fishery management purposes, Bristol Bay is divided into five different fishing 

districts: Naknek-Kvichak, Egegik, Nushagak, Ugashik, and Togiak, which correspond to 

different major Bristol Bay river systems.

7.9 

.5

8.6

2.8 

5.7 

Numbers in boxes are average annual 

harvests for each district in millions of 

fish for the years 1991-2010

Figure 12. Bristol Bay Fishing Districts. Source: ADFG map posted at: 

www.adfg.alaska.gov/index.cfm?adfg=CommercialByFisherySalmon.salmonmaps_districts_bristolbay

9 The correlation between fish weight and the number of fish harvested was -.433, which is statistically significant at 

the 1% level in a one-tailed t-test (N = 36).

58 

 
Annual harvests within each district vary widely from year to year, as does the relative share of 

each district in the total catch. Most of the record Bristol Bay catches of the mid-1990s were 

caught in the Naknek-Kvichak and Egegik districts. Similarly, most of the decline in catches 

after the mid-1990s resulted from a decline in catches in these two districts—particularly the 

Naknek-Kvichak. Most of the recovery in catches since 2002 has also occurred in these two 

districts, as well as in the Nushagak district, where catches have been very strong. 

Bristol Bay Commercial Sockeye Salmon Harvests, by District

0

5

10

15

20

25

19861987198819891990199119921993199419951996199719981999200020012002200320042005200620072008200920102011

Source: ADFG

millions of fish

NaknekKvichak

Egegik

Nushagak

Ugashik

Togiak

Figure 13. Bristol Bay Commercial Sockeye Salmon Harvests, by District.

59 
Currently, there is particular interest in the fisheries resources and economic significance of the 

Nushagak and Kvichak watersheds because of potential future resource development in these 

watersheds, Given the wide variation in catches by district from year to year and over longer 

time periods of time, there no obvious way to characterize the relative share of the Bristol Bay 

commercial salmon fishery attributable to these river systems or to the rivers, streams and lakes 

that make up each river system. 

In general, over most of the past decade, the Nushagak and Naknek-Kvichak districts have 

accounted for about 60% of the total Bristol Bay commercial sockeye harvest (Figure 14).

Share of Bristol Bay Commercial Sockeye Salmon Harvest, by District

0%

20%

40%

60%

80%

100%

19861987198819891990199119921993199419951996199719981999200020012002200320042005200620072008200920102011

Source: ADFG

Togiak

Ugashik

Egegik

Nushagak

NaknekKvichak

Figure 14. Share of Bristol Bay Commercial Sockeye Salmon Harvest, by District.

Note however that both districts include other major rivers beside the Nushagak and Kvijak 

rivers. For example, the Kvichak River generally accounts for less than half of Naknek-Kvichak 

district harvests (Figure 15).

60 
61 

Naknek-Kwijak District Sockeye Salmon Harvests, by River of Origin

0

2

4

6

8

10

12

2004200520062007200820092010

Source: ADFG

millions of fish

Naknek

River

Branch River

Kvichak

River

Figure 15. Naknek-Kvichak District Sockeye Salmon Harvests, by River of Origin.

As discussed more below, economic measures of the Bristol Bay commercial fishery are not 

necessarily proportional to fish harvests. If total fish harvests were to change by a given 

percentage, the value of the fishery, employment, and other measures would not change by the 

same percentage amount. 

Bristol Bay Gear Types 

All Bristol Bay salmon are harvested using gillnets. Gillnets hang in the water perpendicular to 

the direction in which returning salmon are swimming. The fish get their heads stuck in the nets 

and are “picked” from the net as it is pulled from the water. 

There are two types of gillnet fishing operations in Bristol Bay: drift gillnets and set gillnets.

Drift gillnets hang in the water behind the fishing boat. After a period of time, the nets are 

pulled back into the boat for picking. 
Gillnetters catch salmon by setting curtain-like nets 

perpendicular to the direction in which the fish are traveling 

as they migrate along the coast toward their natal streams. 

The net has a float line on the top and a weighted lead line 

on the bottom. The mesh openings are designed to be just 

large enough to allow the . . . fish to get their heads stuck 

(“gilled”) in the mesh. . . . Net retrieval is by hydraulic 

power which turns the drum. Fish are removed from the net 

by hand “picking” them from the mesh as the net is reeled 

onboard. 

Source: Alaska Department of Fish and 

Game, “What kind of fishing boat is that?” 

www.cf.adfg.state.ak.us/geninfo/pubs/fv_n_a

k/fv_ak1pg.pdf.

Picking salmon from the net on a Bristol Bay drift gillnet boat

Bristol Bay fishing boats stored in a Naknek boat yard 

for the winter 

Most Bristol Bay drift gillnet fishing boats 

are used only during the short, intense 

summer salmon season (although some are 

used to fish for herring in the spring) and are 

stored in boat yards for the rest of the year. 

The fact that fishing boats and processing 

plants are idle for much of the year adds to 

costs in the fishery.

62 
Crowded fishing near the boundary of a Bristol 

Bay fishing district

Photograph by Bart Eaton

Drift gillnet fishermen have the advantage of 

being able to move to where the fishing is best—

and the disadvantage that other fishermen are 

likely to want to fish in the same places. Bristol 

Bay drift gillnet fishing boats are often crowded 

along the “lines” which are the boundaries of 

legal fishing districts, established by GPS 

coordinates. Often fishing is best when fishermen 

are able to place their nets along the line, catching 

fish as they swim into the district.

Bristol Bay drift gillnet fishing boats are limited 

to 32 feet in length. Over time, wider and taller 

boats have been built as fishermen try to get more 

working space and hold capacity. 

Drift gillnet boats waiting for an opening in the Nushagak district

Photograph by Gabe Dunham

63 
In set gillnet fishing, one end of the net is attached to the shore, while the other is attached to an 

anchor in the water. Fishermen pick the fish from a skiff or from the beach at low tide. 

 

A set-net fishing operation on the Nushagak River

There are more drift gillnet permits 

fished than set gillnet permits, and 

average catches are higher for drift 

gillnet permits than for set gillnet 

permits. As a result, drift gillnet 

permits account for about four-fifths of 

the Bristol Bay sockeye salmon catch.

Table 27. Comparison of Bristol Bay Drift Gillnet and Set Gillnet Fisheries (2006-10 

Average) 

Drift

Gillnet

Set

Gillnet Total

Ratio,

Drift Gillnet

to Set Gillnet

Drift

Gillnet %

Set

Gillnet %

Total Permits Fished 1,470 847 2,317 1.7 63% 37%

Average Pounds 102,109 37,575 139,684 2.7

Total Pounds 150,053 31,813 181,866 4.7 83% 17%

Comparison of Bristol Bay Drift Gillnet and Set Gillnet Fisheries (2006-10 Averages)

Source: Commercial Fisheries Entry Commission, Basic Information Tables.

64 
Bristol Bay Salmon Harvests, by Fishery

0

50

100

150

200

250

197519771979198119831985198719891991199319951997199920012003200520072009

Source: CFEC Basic Information Tables

millions of pounds (all species)

Drift

gillnet

Set

gillnet

Figure 16. Bristol Bay Salmon Harvests, by Fishery 

Relative Scale of Bristol Bay Sockeye Salmon Harvests 

There are several ways to measure the relative scale of Bristol Bay sockeye salmon harvests in 

comparison with other sources of supply, which are illustrated by the three graphs below: 

Sockeye salmon fisheries. Bristol Bay is by far the largest sockeye salmon fishery in the world. 

Between 1980 and 2009 Bristol Bay averaged 59% of total Alaska sockeye salmon supply and 

44% of total world sockeye salmon supply. 

65 
World Sockeye Salmon Supply

0

50,000

100,000

150,000

200,000

250,000

198019821984198619881990199219941996199820002002200420062008

metric tons

Japan

Lower 48

Canada

Russia

Other

Alaska

Bristol

Bay

Source: ADF&G, NMFS, FAO

Figure 17. World Sockeye Supply

Alaska salmon fisheries. In most years, Bristol Bay sockeye is the single largest fishery in 

Alaska. Between 1980 and 2009, Bristol Bay sockeye salmon averaged 20% of Alaska salmon 

supply for all species combined. 

66 
Alaska Salmon Supply

0

50

100

150

200

250

300

350

400

450

500

198019821984198619881990199219941996199820002002200420062008

thousands of metric tons

Total Alaska

coho &

chinook

Total Alaska

chum

Total Alaska

pink

Other Alaska

sockeye

Bristol Bay

sockeye

Source: ADF&G, FAO, NMFS

Figure 18. Alaska Salmon Supply

World salmon supply. World farmed salmon and trout production has grown extremely rapidly 

since the early 1980s. As farmed salmon and trout production increased, Bristol Bay’s share of 

total world salmon supply fell from 11% in 1980 to just 3% in 2009. 

Mending gillnets at the historic Peter Pan processing plant in Dillingham

67 
World Salmon and Trout Supply

0

500

1,000

1,500

2,000

2,500

3,000

3,500

198019821984198619881990199219941996199820002002200420062008

thousands of metric tons

Farmed trout

Farmed

salmon

Other wild

salmon

Other

Alaska

salmon

Bristol Bay

wild salmon

Source: ADF&G, FAO, NMFS

Note: "Other wild 

salmon" includes

Lower 48, Canada, 

Russia & Japan

Figure 19. World Salmon and Trout Supply

Future Bristol Bay Salmon Harvests

It is very difficult to predict how Bristol Bay salmon harvests may change in the future. Every 

year the Alaska Department of Fish and Game, as well as the University of Washington Fisheries 

Research Institute (FRI) make pre-season projections of how many salmon will return to Bristol 

Bay and what the harvest will be. The projections are based on estimates for previous years of 

escapements, the number of juvenile salmon entering saltwater, and the numbers of adult salmon 

of different age classes which returned.

The pre-season projections provide at best a rough guide to what actual harvests will be. 

Between 1990 and 2011, actual catches ranged from 51% below the Alaska Department of Fish 

and Game’s projections to 128% over the projections, with an average annual projection error of 

31%. 

68 
Bristol Bay Sockeye Salmon Preseason Projection and Actual Commercial Catch

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

45,000

50,000

19901992199419961998200020022004200620082010

Source: ADF&G

thousands of fish

Preseason Projection Actual

69 

Figure 20. Bristol Bay Sockeye Preseason Projection and Actual Commercial Catch

There are no formal projections of how Bristol Bay salmon harvests may change over the longer 

term future. As shown by the graph on the following page, historically harvests have varied 

widely from decade to decade. Analysis of lake-bed sediments has also shown significant 

historical variation in salmon returns in previous centuries prior to commercial harvesting. 

Long-term changes in salmon returns have been shown to be associated with periodic changes in 

ocean conditions such as water temperature and currents, known as “regime shifts.” The much 

lower average harvests from the 1950s through the 1970s are thought to have resulted in part 

from a different ocean regime (although other factors, such as interceptions of Bristol Bay 

salmon by foreign fishing fleets, likely also played a role). 

The potential for significant future changes in ocean conditions associated with not only regime 

shifts but also global climate change could significantly affect future Bristol Bay salmon returns 

and harvests—but it is very difficult to predict what changes might occur or when they might 

occur. 
Bristol Bay Sockeye Salmon Harvests, 1895-2009

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

45,000

189519001905191019151920192519301935194019451950195519601965197019751980198519901995200020052010

thousands of fish

Note: The black line 

shows the average 

annual catch for the 

preceding 10-years.

Source: ADF&G

Figure 21. Bristol Bay Salmon Harvests, 1985-2009 

Until the 1950s, only sailboats were allowed to harvest salmon in Bristol Bay

70 

Source: “Sailing for Salmon” exhibition of historic Bristol Bay photographs

at Anchorage Museum, summer 2011 (http://www.anchoragemuseum.org) 
3.4 Bristol Bay Salmon Products and Markets

The major products produced from Bristol Bay sockeye salmon are canned salmon, frozen 

headed and gutted (H&G) salmon, frozen salmon fillets, fresh H&G salmon, and salmon roe. 

Frozen H&G salmon and canned salmon account for most of the product volume. 

Bristol Bay canned salmon Headed and gutted salmon on trays for freezing

Bristol Bay sockeye salmon fillet Processing Bristol Bay sockeye salmon roe

For most of the more than one-hundred year history of the Bristol Bay salmon fishery, 

production was overwhelmingly canned salmon. Processing plants were called “canneries” and 

processing companies were called “canners.”

However, in the 1970s frozen salmon production increased rapidly, as technologies for freezing 

salmon and shipping frozen salmon developed, and as Japanese demand for frozen Bristol Bay 

salmon expanded with the end of Japanese salmon fishing in international waters and within the 

U.S. 200-mile limit. By the mid-1980s, more than 80% of Bristol Bay salmon production was 

71 
frozen, almost entirely for export to Japan. The shares of different product forms in Bristol Bay 

production over time reflect changes in changes in relative prices and total harvests. From the 

mid-1990s to the mid-2000s, as frozen sockeye salmon prices fell due to increased competition 

in the Japanese market from farmed salmon, and as harvest volumes fell, the frozen share of 

production declined and the canned share increased. Since the mid-2000s, as frozen sockeye and 

harvest volumes have increased, the frozen share of production has risen (Figure 22 and Figure 

23).

Bristol Bay Sockeye Salmon Production

0.0

20.0

40.0

60.0

80.0

100.0

120.0

140.0

160.0

180.0

19841986198819901992199419961998200020022004200620082010

Source: ADFG Commercial Operator Annual Report database

millions of pounds

Roe

Fresh

Canned

Frozen

Figure 22. Bristol Bay Sockeye Salmon Production 

Share of Sockeye Salmon Production in Bristol Bay

0%

20%

40%

60%

80%

100%

19841986198819901992199419961998200020022004200620082010

Source: ADFG, COAR

Roe

Fresh

Canned

Frozen

Figure 23. Share of Sockeye Salmon Production in Bristol Bay

72 
Table 28 provides more detail about product forms for canned and frozen Bristol Bay salmon in 

recent years. In 2010, about one-third of canned salmon production was “talls” (14.75 ounce 

cans) and about two-thirds “halves” (7.5 ounce cans). Between 2006 and 2010, the share of 

frozen fillets in total frozen production increased from about 6% to about 18%. 

Table 28. Sales of Selected Sockeye Salmon Products.

Type Form 2006 2008 2010

Canned Halves 23,349,893 23,672,655 23,486,265

Canned Talls * * 10,592,344

Frozen Fillet 3,939,220 7,930,710 13,788,359

Frozen H&G 61,270,959 53,590,871 63,720,557

Fresh Fresh H&G 2,958,201 1,904,051 * 

Roe Roe 2,902,082 3,186,876 3,657,859

Note: Includes only sales reported by processors with more than 1 million pounds of sales of 

salmon products in the previous year.

Source: Alaska Department of Revenue, Annual Salmon Price Reports

Sales of Selected Sockeye Salmon Products

by Major Bristol Bay Salmon Processors (pounds)

Canned

Frozen

* Not reported due to confidentiality restrictions

In any given year, the total volume of Bristol Bay salmon products is less than the annual harvest 

volume, because part of the weight (25%-35%) is lost in processing as the fish heads and guts are 

removed, and also because some fish are shipped to plants outside the Bristol Bay region for 

processing. Between 1984 and 2010, the reported volume of processed salmon products sold by 

Bristol Bay salmon processors, or production, averaged 67% of the volume of harvests, and 

ranged from as low as 59% to as high as 75%. The annual variation in the ratio of production 

weight to harvest weight results from several factors including changes in average fish size, 

changes in the mix of products produced, and changes in the share of the catch shipped outside 

the region for processing. 

73 
Bristol Bay Sockeye Salmon Harvests and Production

0.0

50.0

100.0

150.0

200.0

250.0

300.0

19841986198819901992199419961998200020022004200620082010

Source: CFEC, ADFG

millions of pounds

Harvests

Production

74 

Figure 24. Bristol Bay Sockeye Salmon Harvests and Production
 

Monthly Sales Volume, Bristol Bay Frozen H&G Sockeye Salmon

0

5,000

10,000

15,000

20,000

25,000

May-08 May-09 May-10 May-11

Source: Alaska Department of Revenue Salmon Price Reports

thousands of pounds

Monthly Sales Volume, Bristol Bay Sockeye Salmon Fillets, Fresh & H&G and Roe

0

1,000

2,000

3,000

4,000

5,000

6,000

May-08 May-09 May-10 May-11

Source: Alaska Department of Revenue Salmon Price Reports

thousands of pounds

Frozen and

Fresh

Fillets

Fresh H&G

Roe

Monthly Sales Volume, Bristol Bay Canned Salmon

0

500

1,000

1,500

2,000

2,500

3,000

3,500

May-08 May-09 May-10 May-11

Source: Alaska Department of Revenue Salmon Price Reports

thousands of pounds

Canned

Halves

Canned

Talls

Figure 25. Monthly Sales Volume of Bristol Bay Salmon Products

75 
The timing of processors’ sales of Bristol Bay salmon reflects the highly seasonal character of 

the industry. Sales of products for which storage costs are relatively high—including frozen 

H&G salmon, frozen and fresh fillets, fresh H&G and roe—are concentrated in the summer in 

the months during and immediately after the season. Sales of canned salmon are distributed 

more evenly over the year. For some products, no data are available for sales for some months 

(to preserve confidentiality, sales are only reported if at least three processors report sales). 

Bristol Bay Salmon Markets

Data are not available on the end-markets to which Bristol Bay sockeye salmon products are 

shipped. However, because Bristol Bay represents such a large share of Alaska and United 

States sockeye salmon production, we can make reasonable inferences about end markets for 

Bristol Bay sockeye salmon by comparing U.S. export data with Alaska statewide production 

data.

Prior to about 1998, almost all U.S. frozen sockeye salmon production (including Bristol Bay 

production) was exported, and almost all exports were to Japan. Beginning in about 1999, this 

pattern changed in two important ways. First, exports declined relative to production—

indicating that significant volumes of Alaska frozen sockeye were beginning to be sold in the 

U.S. market rather than exported. Secondly, significant volumes of frozen sockeye began to be 

exported to countries other than Japan—particularly EU countries and China—substantially 

reducing the Japanese share of U.S. sockeye salmon exports (Figure 26).

These two trends together resulted in a dramatic decline in the volume of Alaska sockeye salmon 

shipped to Japan—from more than 100,000 metric tons in 1993 to 20,000 lbs or less since 

2006—and a corresponding dramatic decline in the dependence of Alaska (and Bristol Bay) 

sockeye on the Japanese frozen salmon market.

76 
Alaska Frozen Sockeye Production & U.S. Frozen Sockeye Exports

0

20,000

40,000

60,000

80,000

100,000

120,000

19891991199319951997199920012003200520072009

Sources: ADFG COAR database; NMFS trade data

metric tons

Alaska

frozen

production

US exports,

total

US exports

to Japan

US exports

to EU

US exports

to China

Note: Export data 

are for the period 

May of the 

production year to 

April of the 

following year.

77 

Figure 26. Alaska Frozen Sockeye Production and U.S. Frozen Sockeye Exports.
The volume of Alaska frozen sockeye salmon sold to U.S. domestic markets may be estimated as 

total production minus exports. This in turn allows estimation of the end-market shares of the 

United States and export markets. End-market shares have changed dramatically from the early 

1990s, when almost all production was estimated to Japan. Between 2006 and 2010, 27-39% of 

production was exported to Japan, 20-31% was sold in the United States, 10-21% was exported 

to China, 11-16% was exported to the European Union, and 7-13% was exported to other 

countries. 

Estimated End-Markets for Alaska Frozen Sockeye Salmon (%)

0%

20%

40%

60%

80%

100%

19891991199319951997199920012003200520072009

USA

Other export

China

European

Union

Japan

Note: USA 

estimated as 

Alaska 

production 

minus exports.

Figure 27. Estimated End-Markets for Alaska Frozen Sockeye Salmon

Note that most of the frozen sockeye exported to China are not consumed in China. Rather, they 

are thawed and reprocessed—using much cheaper Chinese labor—into fillet and other valueadded products which are then re-exported to end-markets in Europe, the United States and 

Japan. Thus the final end-market shares for Europe, the United States and Japan are larger than 

are shown in the graph (but data are not available to indicate how much larger.)

78 
Boxes of frozen Bristol Bay sockeye in the cold storage

 of a Chinese reprocessing plant, 2007 

Most Alaska canned sockeye—including Bristol Bay canned sockeye—is exported. Total 

reported U.S. exports are approximately equal to total Alaska production (Figure 28).10 

Historically the United Kingdom was by far the most important market for canned sockeye. In 

recent years, exports of canned sockeye to Canada have grown dramatically—from which 

significant volumes are likely re-exported to the UK and other markets. 

 

Alaska Canned Sockeye Production & U.S. Canned Sockeye Exports

0

5,000

10,000

15,000

20,000

25,000

30,000

19891991199319951997199920012003200520072009

Sources: ADFG COAR database; NMFS trade data

metric tons

All other

exports

Exports to

Australia

Exports to

Canada

Exports to

UK

Alaska

canned

production

Note: Export data 

are for the period 

May of the 

production year to 

April of the 

following year.

Figure 28. Alaska Canned Sockeye Production and U.S. Canned Sockeye Exports

10 In some years reported US exports of canned sockeye salmon exceed reported Alaska production. The reasons for 

this are not entirely clear. One likely contributing factor is that in years of large sockeye production, significant 

volumes may be kept in inventory and sold during a later year. 

79 

 
Relatively small volumes of fresh salmon are produced in Bristol Bay. It is difficult for Bristol 

Bay to compete with other areas of Alaska in supplying fresh markets because of the greater 

distance and cost required to transport fish to the United States market.

Salmon roe accounts for a relatively small share of total Bristol Bay product volume—typically 

less than 3%--but accounts for a higher share of product value because it commands a higher 

price per pound than other product forms. Most Bristol Bay sockeye salmon roe is exported as 

sujiko (roe in whole skeins) to Japan. 

3.5 Bristol Bay Salmon Prices

Between the late 1980s and 2001, Bristol Bay fishermen and processors experienced a dramatic 

decline in prices paid for Bristol Bay salmon. The “ex-vessel price” paid to fishermen fell from 

a peak of $2.10/lb in 1988 to $.42/lb in 2001. After 2001 the ex-vessel price recovered gradually 

to $.66/lb in 2006 and $.80/lb in 2009 and then rose sharply to $1.07/lb in 2010. Final data for 

Bristol Bay ex-vessel prices in 2011 were not available when this report was prepared but were 

expected to be similar to 2010. 

In nominal terms 2010 ex-vessel prices were similar to prices for much of the 1990s. In “real” 

prices adjusted for inflation they remained lower than any year except 1993. 

Average Ex-Vessel Price of Bristol Bay Sockeye Salmon, 1975-2010

$0.00

$0.50

$1.00

$1.50

$2.00

$2.50

$3.00

$3.50

197519771979198119831985198719891991199319951997199920012003200520072009

Source: ADFG, Commercial Operator Annual Reports

$/lb

Nominal price

(not adjusted for inflation)

Real price

(adjusted for inflation, 

expressed in 2010

 dollars)

Figure 29. Average Ex-Vessel Price of Bristol Bay Sockeye Salmon, 1975-2010 

80 
Cannery at Clark’s Point, Nushagak District

Photograph by Gabe Dunham 

The decline in ex-vessel prices during the 1990s reflects a decline in first wholesale prices paid 

to processors for both canned and frozen salmon. Similarly, the increase in ex-vessel prices after 

2001 reflects in first wholesale prices for both canned and frozen salmon—particularly for frozen 

salmon (Figure 30).

Average Ex-Vessel and Wholesale Prices of Bristol Bay Sockeye Salmon

$0.00

$1.00

$2.00

$3.00

$4.00

$5.00

$6.00

19841986198819901992199419961998200020022004200620082010

Source: Alaska Department of Fish and Game

$/lb (nominal price)

Frozen

wholesale

price

Canned

wholesale

price

Ex-vessel

price

Figure 30. Average Wholesale and Ex-Vessel Prices of Bristol Bay Sockeye Salmon 

81 
A loaded Bristol Bay gillnetter

Photograph by Gabe Dunham

Monthly wholesale price data, available for years since 2001, provide more detail about 

wholesale price trends. Wholesale prices may fluctuate widely over the course of a year due to 

changes in supply and other market factors. 

Wholesale prices for frozen headed and gutted (H&G) salmon increased from about $1.75/lb in 

2001 to about $3.00/lb in early 2011. Wholesale prices for canned salmon halves increased from 

an average of about $2.50/lb in 2001 to about $3.50/lb in early 2011. Wholesale prices for 

canned salmon talls fell from an average of about $2.30/lb in 2001 to about $2.10/lb in 2005 

before increasing to $3.30/lb in early 2011. 

82 
Average Monthly First Wholesale Prices,

Bristol Bay Canned and Frozen H&G Sockeye Salmon

$0.00

$0.50

$1.00

$1.50

$2.00

$2.50

$3.00

$3.50

$4.00

$4.50

May01May02May03May04May05May06May07May08May09May10May11May12

Source: Alaska Department of Revenue Salmon Price Reports

$/l b

Canned

Halves

Canned

Talls

Frozen H&G

83 

Figure 31. Average Monthly First Wholesale Prices.

In general, wholesale prices paid to processors for canned Bristol Bay sockeye salmon are 

similar to wholesale prices for canned sockeye salmon from other regions of Alaska. In contrast, 

wholesale prices paid to processors for frozen Bristol Bay sockeye salmon are typically lower 

than wholesale prices for frozen sockeye salmon from other regions of Alaska (Figure 32). This 

may reflect differences in product mix and/or differences in the perceived quality of Bristol Bay 

frozen sockeye compared with frozen sockeye from other parts of Alaska. 

In turn, Bristol Bay ex-vessel price for sockeye salmon are typically lower than ex-vessel prices 

for sockeye salmon in southcentral and southeast Alaska (Figure 33). This may reflect the fact 

that processors receive lower wholesale prices for frozen sockeye, as well as the fact that 

processors face higher operating costs in Bristol Bay than in less remote regions of southcentral 

and southeast Alaska, as well as generally higher costs for transporting products to market. 
Average Wholesale and Ex-Vessel Prices of Sockeye Salmon:

Bristol Bay and the Rest of Alaska

$0.00

$1.00

$2.00

$3.00

$4.00

$5.00

$6.00

19841986198819901992199419961998200020022004200620082010

Source: Alaska Department of Fish and Game

$/lb

Rest-of-Alaska

canned

wholesale

Bristol Bay

canned

wholesale

Rest-of-Alaska

frozen

wholesale

Bristol Bay

frozen

wholesale

Rest of Alaska

ex-vessel

Bristol Bay exvessel

Figure 32. Average Wholesale and Ex-Vessel Prices, Bristol Bay and Rest of Alaska

Average Ex-Vessel Prices of Sockeye Salmon, Selected Alaska Areas

$0.00

$0.50

$1.00

$1.50

$2.00

$2.50

199619971998199920002001200220032004200520062007200820092010

Source: ADFG, 1984-2010 Salmon Exvessel Pice Time Series by Species

$/lb

Prince

William

Sound

Southeast

Cook Inlet

Kodiak

Bristol Bay

84 

Figure 33. Average Ex-Vessel Prices of Sockeye Salmon, Selected Alaska Areas.
Factors Affecting Bristol Bay Salmon Prices

Changes in Bristol Bay salmon prices over the past three decades reflect dramatic changes in 

world salmon markets over this period. The most important change was a dramatic increase in 

world salmon supply resulting from rapid growth in farmed salmon production, mostly in 

Norway, Chile, the United Kingdom and Canada. 

In particular, during the 1990s, Japan—where the market for “red-fleshed salmon has previously 

been dominated by Alaska sockeye—began to import large volumes of farmed coho salmon 

from Chile and farmed trout from Chile and Norway. This, together with lower Bristol Bay 

salmon harvests, led to a dramatic decline in the share of Bristol Bay sockeye salmon in its most 

important market. 

Japanese "Red-Fleshed" Salmon Imports, May-April

0

50,000

100,000

150,000

200,000

250,000

1992-931993-941994-951995-961996-971997-981998-991999-002000-012001-022002-032003-042004-05

metric tons

Frozen trout

fillets

Frozen trout

(excl. fillets)

Frozen coho

Frozen sockeye

85 

Figure 34. Japanese Red-Fleshed Salmon Imports, May-April

The effects of growing supply were compounded by an economic recession in Japan, changes in 

the Japanese fish distribution system which increased the market power of retailers, and longterm changes in Japanese food consumption patterns. The combined result was a sharp decline 

in Japanese wholesale prices paid for Bristol Bay sockeye salmon as well as farmed salmon

(Figure 35). This in turn was reflected in a sharp decline in prices paid to Alaska processors and 

fishermen (Figure 36). 
Bristol Bay headed and gutted sockeye salmon 

Japanese "Red-Fleshed" Frozen Salmon Imports & Wild Sockeye Wholesale Price

0

50,000

100,000

150,000

200,000

250,000

1986-871987-881988-891989-901990-911991-921992-931993-941994-951995-961996-971997-981998-991999-002000-012001-022002-032003-042004-05

imports (metric tons)

0

200

400

600

800

1000

1200

1400

1600

1800

average wholesale price (yen/kilo)

Sockeye wholesale price

Total imports

Wild sockeye imports

"Red-fleshed"

farmed salmon

& trout imports

Figure 35. Japanese Red-Fleshed Frozen Salmon Imports & Wild Sockeye Wholesale Price 

86 
Japanese Wholesale Prices and Bristol Bay Prices for Sockeye Salmon

$0.00

$1.00

$2.00

$3.00

$4.00

$5.00

$6.00

1980198219841986198819901992199419961998200020022004200620082010

$/lb

August

Japanese

wholesale

price, Bristol

Bay frozen

sockeye

Average first

wholesale

price, Bristol

Bay frozen

sockeye

Average

Bristol Bay exvessel price

87 

Figure 36. Japanese Wholesale Prices and Bristol Bay Prices for Sockeye Salmon

Just as multiple factors contributed to the fall in Bristol Bay salmon prices during the 1990s, 

multiple factors contributed to the recovery in prices after 2001. Probably the most important 

factors was a strong recovery in world market prices for farmed salmon, driven by rapidly rising 

world demand and a slowing of the growth in world salmon production (Figure III-9), 

exacerbated by major disease problems in the Chilean salmon industry which greatly reduced 

Chilean production. Prices of farmed Atlantic salmon in particular rose dramatically from 2002 

through 2010 (Figure 37 and Figure 38).
Average United States Import Prices of Selected Farmed Salmon Products$/lb)

$0.00

$1.00

$2.00

$3.00

$4.00

$5.00

$6.00

$7.00

Jan-95Jan-96Jan-97Jan-98Jan-99Jan-00Jan-01Jan-02Jan-03Jan-04Jan-05Jan-06Jan-07Jan-08Jan-09Jan-10Jan-11Jan-12

US average import

price, Canadian fresh

Atlantic fillets

US average import

price, Chilean fresh

Atlantic fillets

US average import

price,Chilean frozen

Atlantic fillets

Source: NMFS

Figure 37. Average United States Import Prices of Selected Farmed Salmon Products

U.S. Wholesale Prices for Selected Wild and Farmed Salmon Products

reported in Urner Barry's Seafood Price Current

$0.00

$1.00

$2.00

$3.00

$4.00

$5.00

$6.00

Jan-91Jan-92Jan-93Jan-94Jan-95Jan-96Jan-97Jan-98Jan-99Jan-00Jan-01Jan-02Jan-03Jan-04Jan-05Jan-06Jan-07Jan-08Jan-09Jan-10Jan-11Jan-12

Source: Urner Barry Publications, Inc., Seafood Price Current.

$/lb

Fresh farmed Atlantic, pinbone-out fillets Fresh farmed Atlantic, whole fish

Frozen H&G wild sockeye

88 

Figure 38. U.S. Wholesale Prices for Selected Wild and Farmed Salmon Products
Other factors which contributed to the increase in prices for Bristol Bay sockeye salmon after 

2001 include the strengthening of exchange rates between the yen and the dollar and between the 

euro and the dollar, diversification of markets for frozen sockeye, and the development of new 

product forms, particularly fillets. 

Unlike frozen salmon markets, canned salmon markets have not been directly affected by 

competition from farmed salmon—because relatively little farmed salmon is canned. However, 

canned salmon markets are influenced by frozen market conditions—and thus indirectly by 

farmed salmon. When frozen prices are high, processors tend to freeze relatively more salmon 

and can relatively less, which reduces the supply of canned salmon, causing canned salmon 

prices to rise. When frozen prices are low, processors tend to freeze relatively less salmon and 

can relatively more, which increases the supply of canned salmon, causing canned salmon prices 

to fall. Put differently, the ability of processors to shift between freezing and canning salmon 

causes frozen and canned salmon prices to tend to move together. 

This can be seen in the decline in the downward trend in canned salmon prices in the early 

1990s, and the upward trend since the early 2000s (Figure 37). However, many other factors 

affect canned salmon prices, including in particular wild salmon harvests, exchange rates 

between the dollar and the UK pound, and changing demand patterns for canned salmon. 

Monthly Average Wholesale Case Prices for Alaska Canned Sockeye Salmon

$0

$50

$100

$150

$200

$250

Jul-85Jul-86Jul-87Jul-88Jul-89Jul-90Jul-91Jul-92Jul-93Jul-94Jul-95Jul-96Jul-97Jul-98Jul-99Jul-00Jul-01Jul-02Jul-03Jul-04Jul-05Jul-06Jul-07Jul-08Jul-09Jul-10Jul-11

Source: Alaska Department of Revenue salmon price reports. Data prior to August 2000 are 

statewide average canned sockeye prices; later data are average prices for Bristol Bay canned 

sockeye.

$/case

48 talls

48

halves

Figure 39. Monthly Average Wholesale Case Prices for Alaska Canned Sockeye Salmon.

89 
Future Bristol Bay Salmon Prices

Since the beginning of 2011 prices of farmed Atlantic salmon have fallen sharply, in response to 

oversupply of world markets as Chilean production has recovered (Figure 37 and Figure 38, 

above). Of great importance for the Bristol Bay salmon industry will be the extent to which 

prices of Bristol sockeye salmon remain high, or alternatively follow the recent downward trend 

in farmed salmon prices. At the time this report was written, it was too soon to tell how deep or 

long the decline in farmed salmon prices may be, or how much it may affect sockeye salmon 

markets.

More generally, the future outlook for Bristol Bay salmon prices is promising but uncertain. 

There are several reasons for optimism, including growing demand for wild sockeye salmon in 

the United States and Europe, the development of new higher-valued product forms (particularly 

fillets), and improvements in the quality of Bristol Bay salmon (discussed below). However, the 

Bristol Bay salmon industry will face challenges in taking advantage of these new market 

opportunities. These include continued competition from farmed salmon and other new farmed 

species, the logistical difficulties of market development given the wide variation in annual 

Bristol Bay catches, high costs of transportation and labor, and highly concentrated seasonal 

production which adds to costs and makes it difficult to slow down production and improve 

quality. These factors make it relatively easier for other regions of Alaska than for Bristol Bay to 

take advantage of growing market opportunities for wild sockeye salmon. 

Bristol Bay Salmon Quality

In an increasingly competitive world seafood industry, quality is of increasing importance. An 

important challenge for the Bristol Bay salmon industry has been a reputation for quality 

problems. Many people in the industry believe these problems have historically kept wholesale 

and ex-vessel prices lower than they would have been with better quality—although it is difficult 

to quantify how important the effect of quality on prices has been. 

Quality problems in the Bristol Bay fishery derive in part from handling practices such as those 

depicted in these pictures posted on the internet. During the short, hectic and fast-paced Bristol 

Bay season, fishermen have historically been focused on catching large volumes of fish fast than 

on handling fish carefully. (In the highly quality-conscious salmon farming industry, it would be 

unthinkable to step on fish.) 

Source: http://bbda.org/Stern_Load06.jpg Source: 

www.adn.com/static/includes/highliner/cowboys.jpg

90 
Quality problems in the Bristol Bay fishery have been compounded by the absence of ice or 

chilling capacity on many fishing boats; the logistics of tendering salmon long distances from 

fishing grounds to processors, which makes it more difficult to separate fish which have been 

handled carefully from those which have not (and to pay quality-conscious fisherman a 

corresponding price premium); and the difficulty of processing salmon soon after they are 

caught, especially during peak fishing periods. 

Improving quality has been a primary focus of the Bristol Bay Regional Seafood Development 

Association (BBRSDA), 11 a fishermen’s marketing association for the drift gillnet fishery 

financed by permit holders by means of a 1% assessment on the ex-vessel value of landings 

(harvests). BBRDSA has undertaken a number of projects focused on encouraging chilling 

(through icing and/or refrigerated sea water) as well as improved handling practices. Annual 

processor surveys funded by BBRDSA suggest that the share of fish which are delivered chilling 

is increasing (Figure V-12).

12

Estimated Chilled and Unchilled Shares of Bristol Bay Salmon Harvests

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2008 2009 2010

Unchilled

Chilled

Source: Northern Economics, 2010 Bristol Bay Processor Survey 

Figure 40. Estimated Chilled and Un-chilled Shares of Bristol Bay Salmon Harvests

11 BBRSDA was established in 2005. Fishermen voted for the 1% assessment in 2006. Information about 

BBRSDA may be found at www.bbrsda.com. 12 Northern Economics, 2010 Bristol Bay Processor Survey. Prepared for Bristol Bay Regional Seafood

Development Association, February 2011. http://www.bbrsda.com/layouts/bbrsda/files/documents/

bbrsda_reports/BB-RSDA%202010%20Survey%20Final%20Report.pdf

91 

 
Bristol Bay fishing boats waiting to unload to a tender

Photograph by Gabe Dunham

3.6 Bristol Bay Salmon Ex-Vessel and Wholesale Value

The decline in catches and prices during the 1990s led to a drastic decline in value in the Bristol 

Bay salmon fishery. The nominal ex-vessel value paid to fishermen fell from a peak of $214 

million in 1989 to just $32 million in 2002—a decline of 86%. The inflation-adjusted “real” 

value (expressed in 2010 dollars) fell by an even greater 89% from a 1989 value of $359 million 

to $39 million in 2002. 

92 
Ex-Vessel and First Wholesale Value of Bristol Bay Sockeye Salmon

Harvests and Production, 1984-2010

0

100

200

300

400

500

600

700

19841986198819901992199419961998200020022004200620082010

millions of dollars

Real first

wholesale value

(2010$)

Nominal first

wholesale value

Real ex-vessel

value (2010 $)

Nominal exvessel value

Source: CFEC, ADFG

Figure 41. Ex-Vessel and First Wholesale Value: 1984-2010 

As catches and prices have improved after 2002, the Bristol Bay salmon industry experienced a 

significant economic recovery. Ex-vessel value increased to $181 million in 2010. However, 

this was well below the inflation-adjusted “real” value of the highest-value years of the late 

1980s and early 1990s. 

The first wholesale value of Bristol Bay salmon production exhibited similar trends over time as 

ex-vessel value. The nominal first wholesale value fell from a peak of $351 million in 1992 to 

$100 million in 2002. As catches and prices improved, nominal wholesale value rose to a record 

$390 million in 2010. Adjusted for inflation, however, the 2010 first wholesale value remained 

well below the 1989 peak real wholesale value of $616 million. 

The decline in value of the Bristol Bay fishery during the 1990s and the rise in value after 2002 

was experienced by both processors and fishermen. Like the ex-vessel value to fishermen, the 

value retained by processors after deducting payments to fishermen (sometimes called the 

processors’ margin) fell dramatically during the 1990s and rose dramatically after 2002 (Figure 

42).

93 
Distribution of Nominal Value of Bristol Bay Sockeye Salmon

0.0

50.0

100.0

150.0

200.0

250.0

300.0

350.0

400.0

19841986198819901992199419961998200020022004200620082010

millions of nominal dollars

Total first

wholesale

value

Ex-vessel

value received

by fishermen

Value to

processors

after

deducting

payments to

fishermen 

Source: CFEC, ADFG

Figure 42. Distribution of Nominal Value of Bristol Bay Sockeye Salmon

The share of first wholesale value received by fishermen fell from 83% in 1988 to 32% in 2002 

and then rose to 46% in 2010 (Figure 43). 

 

94 
Distribution of Value of Bristol Bay Sockeye Salmon

0%

20%

40%

60%

80%

100%

19841986198819901992199419961998200020022004200620082010

Value to

processors after

deducting

payments to

fishermen 

Ex-vessel value

received by

fishermen

Source: CFEC, ADFG

Figure 43. Distribution of Value of Bristol Bay Sockeye Salmon

The relative share of wholesale value received by fishermen and processors has been a subject of 

contention between fishermen and processors.13 During the 1990s, fishermen argued that they 

had experienced a disproportionate and unfair share of the decline in wholesale value. Note, 

however, that there is no economic reason to expect fishermen or processors’ shares of gross 

wholesale value to remain constant over time. Regardless of wholesale value, processors must 

cover the costs of processing—which account for a relatively larger share of wholesale value as 

wholesale value declines.

The loss in value during the 1990s led to a severe economic crisis in the Bristol Bay salmon 

industry. As discussed above, as the value of the fishery declined, the prices of limited entry 

permits plummeted and many fishermen stopped fishing their permits. Similarly, many landbased salmon processing operations closed and many floating processors left Bristol Bay. 

13 The decline in the fishermen’s share of ex-vessel value was a key issue in an unsuccessful class-action lawsuit 

filed in 1995, in which Bristol Bay permit holders alleged that major processors and Japanese importers of Bristol 

Bay salmon had conspired to fix prices paid to fishermen (Alakayak v. All Alaskan Seafoods, Inc). The author 

served as an expert witness on behalf of the defendant processors and importers.

95 

 
3.7 Bristol Bay Salmon Fishermen

As discussed earlier, both the Bristol Bay drift gillnet fishery and the Bristol Bay set gillnet 

fishery are managed under a “limited entry” management system which was implemented for all 

of Alaska’s twenty-seven salmon fisheries in the mid-1970s. The basic purpose and effect of the 

limited entry system is to limit the number of boats fishing in each fishery, which makes it easier 

for managers to control the total fishing effort and makes the fishery more profitable for 

participants than it would be if entry (participation) were unrestricted and more boats could fish. 

There are approximately 1860 drift gillnet permits and approximately 1000 set net permits. 

Every drift gillnet fishing boat or set net operation must have a permit holder on board or present 

while fishing—so the number of boats or set net operations cannot exceed the number of permit 

holders. 

A permit represents a right (legally a revocable privilege) to participate in a fishery. Unlike 

individual fishing quota (IFQ) or catch-share systems which have been implemented in some 

United States fisheries, a permit does not restrict a permit-holder to catching a specific number of 

fish. Fishermen may catch as many fish as they can—as long as they follow the numerous 

regulations which restrict when, where and how they may fish. 

When limited entry management was implemented in 1975, permits were allocated for free to 

individuals who had historically participated in the fishery. Permit holders may hold permits in 

perpetuity, although they must renew their permits each year for a nominal administrative fee. 

Persons without permits can acquire them only by gift, inheritance, or by buying them from 

existing permit holders. 

Permit holders must register to fish in one of the five Bristol Bay fishing districts. They may 

transfer to fish in another district, but must wait 48 hours before fishing in the new district. 

A “permit stacking” regulation implemented in 2004 for the drift gillnet fishery allows two 

permit holders who opt to fish together on a single vessel to use 200 fathoms of drift gillnet gear 

(an additional 50 fathoms more than the usual limit of 150 fathoms). The objective of the 

regulation was to allow two permit holders to team up to reduce their combined harvesting costs 

to create a more profitable operation. 

In addition to permit holders, there are an average of about two crew members for each drift 

gillnet fishing boat and about two crew members for each set gillnet site. Crew members are 

usually paid a percentage share of gross earnings after deducting costs of food and fuel. A 

typical drift gillnet crew share is about 10%. 

The Commercial Fisheries Entry Commission (CFEC) maintains detailed public data about 

salmon permit holders, including their names, addresses, and vessel information. It also 

publishes annual data on the total number of permits fished, total pounds landed, total gross 

earnings, and average prices paid for permits sold.14

14 The data may be found at the Commercial Fisheries Entry Commission website: http://www.cfec.state.ak.us/. 

96 

 
In contrast, almost no data are available about Bristol Bay crew members. Although crew are 

required to purchase an annual Alaska fishing crew license for a nominal fee, no data are 

available about whether they participate in fishing, which fisheries they fish in, or how much 

they earn. For this reason, most of the data presented in this section are about Bristol Bay permit 

holders. But keep in mind that about two-thirds of the people working in Bristol Bay fish 

harvesting are crew members.

Fishery Participation

Until the late 1990s, most Bristol Bay permits were fished (Figure 44). However, beginning in 

the late 1990s, a growing number of permit holders stopped participating in the Bristol Bay 

fishery, because they couldn’t make enough money to cover their costs. In 2002—the lowest 

year for Bristol Bay ex-vessel value since the start of the limited entry program in 1975—only 

63% of drift gillnet permits and 66% of set gillnet permits were fished. 

Since 2002, as the value of the fishery increased, fishery participation also increased, although 

many permits remained unfished. In 2010, 80% of drift gillnet permits and 86% of set gillnet 

permits were fished.

Number of Limited Entry Permits Issued and Fished in Bristol Bay

0

200

400

600

800

1000

1200

1400

1600

1800

2000

1980198219841986198819901992199419961998200020022004200620082010

Source: CFEC Salmon Basic Information Tables

Drift gillnet

permits

issued

Drift gillnet

permits

fished

Set gillnet

permits

issued

Set gillnet

permits

fished

Figure 44. Number of Limited Entry Permits Issued and Fished in Bristol Bay

Understanding the extent of participation in the Bristol Bay drift gillnet fishery since 2004 is 

complicated by the permit-stacking option for the drift gillnet fishery, under which two permit 

holders may opt to fish together (with an additional 50 fathoms of gear) from a single boat. 

97 
A CFEC analysis of the 2009 fishery, based on district registration data (both permit-holders in a 

two-permit operation are required to register for fishing in that district) concluded that “for the 

fishery as a whole, two-permit operations occurred on an estimated 20.9% (278) of the 1,331 

vessels registered during the season and one-permit only operations occurred on 79.1% (1,053) 

of the vessels. Of the 1,610 distinct permit holders who registered during the season, 34.7% 

(558) were involved in a two-permit operation during the season, while 65.3% (1,052) were 

involved in a one-permit operation only.”15

Table 29 and Table 30 (on the following page) provides selected indicators of participation in the 

Bristol Bay drift gillnet fishery in 2009, based on various measures reported by CFEC. A total 

of 1863 permits were issued to 1838 permit holders. Of these, 1610 registered to fish during the 

season in one or more of the Bristol Bay fishing districts. Of these an estimated 1052 fished 

alone and 558 fished with another permit holder. Of those who fished with another permit 

holder, an estimated 401 reported landings on their permits while 157 reported no landings on 

their permits (all of the operation’s landings were reported on the other permit holder’s permit). 

Thus the CFEC data for the “number of permits fished,” shown in Figure 44 above (1453 in 

2009), overstates the number of boats which fished (1331 in 2009), but understates the number 

of permit holders who participated in the fishery (1610 in 2009). 

Table 29. Selected Indicators of Participation in 2009 Drift Gillnet Fishery

Row Indicator Source Number

1 Total permits issued a, b 1,863

2 Number of permit holders b 1,838

3 Number of distinct permit holders who registered during the season c 1,610

4 Estimated number involved in a one-permit operation only during the season c 1,052

5 Estimated number involved in a two-permit operation during the season c 558

6 Number of fishermen who fished (reported landings on their permits) b 1,453

7 Total permits fished (with reported landings) a, b 1,444

8 Number of vessels registered during the season c 1,331

9 Estimated number on which only one-permit operations occurred c 1,053

10 Estimated number on which two-permit operations occurred c 278

(a) CFEC, Salmon Basic Informaton Tables, Bristol Bay Drift Gillnet Salmon Fishery, 

http://www.cfec.state.ak.us/bit/X_S03T.HTM.

(b) CFEC, "Permit & Fishing Activity by Year, State, Census Area or City," data for "Grand Total: All 

Fishermen Combined", http://www.cfec.state.ak.us/gpbycen/2009/00_ALL.htm.

(c) Schelle, K., N. Free-Sloan, and C. Farrington, “Bristol Bay Salmon Drift Gillnet Two-Permit 

Operations: Preliminary Estimates from 2009 District Registration Data (CFEC Report No. 09-6N, 2009). 

http://www.cfec.state.ak.us/RESEARCH/09-6N/bbr_final_v4_121409.pdf.

Selected Indicators of Participation in the 2009 Bristol Bay Drift Gillnet Salmon Fishery

15 Schelle, K., N. Free-Sloan, and C. Farrington, “Bristol Bay Salmon Drift Gillnet Two-Permit Operations: 

Preliminary Estimates from 2009 District Registration Data (CFEC Report No. 09-6N, 2009). 

http://www.cfec.state.ak.us/RESEARCH/09-6N/bbr_final_v4_121409.pdf.

98 

 
Table 30. Estimated Number of 2009 Drift Gillnet Permit Holders who Fished Alone, With 

another Permit Holder, or Did Not Fish

Number of permit holders who: Estimates How calculated*

Fished alone 1,052 4

Fished with another permit holder 558 5

 Fished with another permit holder and reported landings 401 5 - (3 - 6)

 As the only permit holder who reported landings 122 6 - 8

 With both reporting landings 279 5 - (3 -6) - (6-8)

 Fished with another permit holder but did not report landings 157 3 - 6

Held permit but did not fish it 228 2 - 3

TOTAL NUMBER OF PERMIT HOLDERS 1,838 2

*Numbers refer to rows in the previous table.

Estimated Numbers of 2009 Drift Gillnet Permit Holders Who Fished Alone,

Fished with Another Permit Holder, or Did Not Fish

Distribution of Earnings

In both the drift gillnet and set gillnet fisheries, each year there is wide variation among permit 

holders in average earnings, reflecting differences in vessel size, fishing style, fishing experience 

and skill, how aggressively and for how long they fish, what fishing districts they choose to fish 

in, and good or bad luck. These differences are reflected in average earnings among four 

“quartile” groups of permit holders, each of which accounts for one quarter of total Bristol Bay 

earnings. 

In the drift gillnet fishery, typically, the first quartile has about one-third to one-fourth as many 

fishermen as the fourth quartile, earning on average of about three to four times as much (Figure 

45). 

99 
Average Gross Earnings of Bristol Bay Drift Gillnet Permit Holders,

by Quartile

$0

$50,000

$100,000

$150,000

$200,000

$250,000

197519771979198119831985198719891991199319951997199920012003200520072009

Source: Commercial Fisheries Entry Commission quartile tables

nominal dollars (not adjusted for inflation)

First

quartile

Second

quartile

Third

quartile

Fourth

quartile

100 

Figure 45. Average Gross Earnings of Bristol Bay Drift Gillnet Permit Holders

Average earnings in the set gillnet fishery are much lower than in the drift gillnet fishery. The 

highest earning “first quartile” set gillnet permit holders earn about half as much as the “first 

quartile” drift gillnet permit holders (Figure 46). There is a wider range of variation in earnings 

of set net permit holders, reflecting in part wide differences in the number of fish swimming past 

set net sites in different Bristol Bay locations.
Average Gross Earnings of Bristol Bay Set Gillnet Permit Holders,

by Quartile

$0

$20,000

$40,000

$60,000

$80,000

$100,000

$120,000

197519771979198119831985198719891991199319951997199920012003200520072009

Source: Commercial Fisheries Entry Commission quartile tables

nominal dollars (not adjusted for inflation)

First

quartile

Second

quartile

Third

quartile

Fourth

quartile

Figure 46. Average Gross Earnings of Bristol Bay Set Gillnet Permit Holders

Permit Prices

The prices paid for Bristol Bay permits have fluctuated dramatically over time. Expressed in 

nominal dollars, average prices paid for drift gillnet permits rose from $66,000 in 1980 to 

$249,000 in 1989, fell to $20,000 in 2002, and rose again to $102,000 in 2010. Average prices 

paid for set gillnet permits rose from $29,000 in 1980 to $65,000 in 1989, fell to $12,000 in 

2002, and rose again to $29,000 in 2010. 

101 
Average Prices Paid for Bristol Bay Limited Entry Permits

$0

$50,000

$100,000

$150,000

$200,000

$250,000

1980198219841986198819901992199419961998200020022004200620082010

nominal dollars (not adjusted for inflation)

Drift gillnet

permits

Set gillnet

permits

Source: CFEC Salmon Basic Information Tables

Figure 47. Average Prices Paid for Bristol Bay Limited Entry Permits

Bristol Bay limited entry permit prices are clearly strongly related to total earnings in the fishery. 

In both fisheries, trends over time in permit prices closely track trends over time in total earnings 

(Figure 48 & Figure 49). Economic theory suggests that permit prices would be driven by 

fishermen’s expectations of future profits from the fishery. The close relationship between total 

earnings and permit prices suggests that expectations of future profits are driven by trends in 

average profits in recent years. 

Costs of Fishing

Not all Bristol Bay permit holder earnings are profits, of course. Permit holders face significant 

costs of fishing, some of which are relatively fixed regardless of the volume or value of their 

catch—which makes fishing profits relatively more volatile than earnings. 

No data are collected on a regular basis on the costs faced by Bristol Bay permit holders. From 

time to time, studies have estimated costs of fishing based on surveys of Bristol Bay permit 

holders. However, it is difficult to characterize fishing costs, for several reasons. First, costs 

may vary widely between fishing operations, because of differences in factors such as vessel 

size, number of crew, how and where permit holders fish, and where permit holders and crew 

live. Second, costs may vary significantly from year to year due to changes in prices of fuel, 

insurance and other inputs to fishing. Third, fixed costs such as vessel storage and insurance 

may vary widely from year to year when expressed on a per-pound basis due to changes in 

harvest volumes. 

102 
Average Permit Prices and Total Earnings: Bristol Bay Drift Gillnet Fishery

$0

$50,000

$100,000

$150,000

$200,000

$250,000

1980198219841986198819901992199419961998200020022004200620082010

Average permit price

$0

$20

$40

$60

$80

$100

$120

$140

$160

$180

$200

Total earnings (millions of dollars)

Average permit price ($) Total earnings ($ million)

Source: CFEC Salmon Basic Information Tables

Figure 48. Average Permit Prices and Total Earnings: Bristol Bay Drift Gillnet Fishery

Average Permit Prices and Total Earnings: Bristol Bay Set Gillnet Fishery

$0

$10,000

$20,000

$30,000

$40,000

$50,000

$60,000

$70,000

1980198219841986198819901992199419961998200020022004200620082010

Average permit price

$0

$5

$10

$15

$20

$25

$30

$35

Total earnings (millions of dollars)

Average permit price ($) Total earnings ($ million)

Source: CFEC Salmon Basic Information Tables

103 

Figure 49. Average Prices and Earnings: Bristol Bay Set Gillnet Fishery
Figure 50 summarizes the estimated 2008 fishery-wide distributions of operating costs and 

incomes to Bristol Bay permit holders and crew reported by the Anchorage-based economic 

consulting firm Northern Economics in a recent detailed study of the importance of Bristol Bay 

salmon fisheries to the Bristol Bay region and its residents, conducted for the Bristol Bay 

Economic Development Corporation. The estimates were based on updates of estimates of 

previous analyses by CFEC and Northern Economics to account for changes in fuel prices and 

other costs. A review of the details of how the estimates were prepared and their limitations is 

beyond the scope of this report. We include them here as a general indicator of the kinds of costs 

which are important in the fishery and their approximate magnitudes relative to 2008 earnings. 

Note that operating costs in both fisheries include fuel and oil, net maintenance, gear, boat and 

net storage, transportation, food, insurance, taxes, fees and services. Permit holders also face 

costs of crew share payments (about 10% of gross earnings per crew member, after deducting 

costs of fuel and food), as well as loan payments for permits and boats. 

Figure 50. Northern Economics’ Estimates of the Breakdown of Operating Costs

and Incomes to Crew and Permit Holders, Bristol Bay Salmon Fisheries, 2008

Source: Northern Economics, The Importance of the Bristol Bay Salmon Fisheries to the Region and its Residents

(report prepared for the Bristol Bay Economic Development Corporation, October 2009). Estimates based in part 

on earlier analyses by Northern Economics and CFEC.

104 
3.8 Bristol Bay Salmon Processors

Fish processing is an integral part of the Bristol Bay commercial salmon industry, employing 

approximately half as many people as fish harvesting and more than doubling the value of the 

fish.

Bristol Bay salmon are processed in both land-based processing facilities and on floating 

processors. Salmon are canned only in large land-based facilities, which also have salmon 

freezing capacity. Floating processors produce only frozen salmon. As discussed, the Bristol 

Bay salmon processing industry typically employs about 3000 to 4000 workers annually at the 

height of the salmon processing season—depending upon the size of the harvest. Of these, fewer 

than 5% are residents of the Bristol Bay region. Another 10% to 15% are residents of other parts 

of Alaska, and about 75% to 80% are residents of other states or countries. Most are relatively 

unskilled short-term workers: only about 20% work in Bristol Bay for more than five years. 

Almost all live in bunkhouses provided by the processing companies. 

Yardarm Knot Cannery, Naknek

Source: http://www.yardarm.net/red%20salmon%20cannery/cannery%20home4_files/image301.jpg

Icicle Seafoods’ Floating Processor Bering Star in the Nushagak River

(the ship on the left is a cargo vessel loading frozen salmon for shipment to Japan)

105 
In 2010, six companies operated salmon canning facilities in Bristol Bay. These included some 

of the largest seafood processing companies operating in Alaska, such as Trident Seafoods, 

Ocean Beauty Seafoods, Icicle Seafoods and Peter Pan Seafoods. Most of these companies have 

both land-based and floating processing operations in many parts of Alaska, which process not 

only salmon but other major Alaska species as well, such as pollock, crab and halibut. All large 

processors have home offices in or near Seattle. 

In 2010, all of the processors with canning facilities, and five other larger processors purchased 

salmon in multiple Bristol Bay districts. There were twenty-five other buyers and smaller 

processors who bought salmon in just one district. 

Most of the land-based processing facilities in the Bristol Bay region are located in or near a 

small number of communities with regularly-scheduled air transportation. The largest number of 

processors are located in Naknek along the Naknek River. Most of the other land-based facilities 

are in Dillingham, Egegik and Togiak. 

Bristol Bay salmon processing is not an easy business. The list of companies buying and 

processing salmon in Bristol Bay changes from year to year. The number of large processors 

operating in Bristol Bay declined in the 1990s, reflecting consolidation in the industry forced by 

harvest volumes and lower profits. Many land-based processing plants closed and the number of 

floating processors brought into Bristol Bay each year to process salmon also declined sharply. 

This consolidation helped to make the industry more efficient and more profitable. 

Number of Companies Reporting Salmon Production in Bristol Bay,

by Product

0

5

10

15

20

25

30

35

40

45

198419851986198719881989199019911992199319941995199619971998199920002001200220032004200520062007200820092010

Frozen

salmon

Canned

salmon 

Fresh

salmon

Source: ADF&G Commercial Operator Annual Reports

Figure 51. Number of Companies Reporting Salmon Production in Bristol Bay, by Product

106 
Fish account for the largest share of costs of Bristol Bay processors. Other important costs 

include labor, fish tendering, packaging (boxes and cans), transportation of products and 

workers, utilities and taxes, maintenance, and costs of equipment and buildings. 

Another important “cost” is the adjustment for the yield from the “round pound” weight of fish 

purchased from fishermen to the “processed pound” weight of fish products. In effect, for any 

given ex-vessel prices, the lower the yield, the higher the cost of fish per pound of final product 

weight. 

Costs per pound vary between product forms and may also vary widely from year to year as 

fixed costs are spread over different volumes of salmon. Table 31 provides rough estimates of 

Bristol Bay salmon processing costs from an analysis for 1994 and 1995. Note that costs have 

likely risen considerably since these estimates were prepared, due to changes in costs of labor, 

energy and other factors. However, salmon ex vessel prices are highly variable and not directly 

tied to general changes in price levels. Therefore the Table 31 data is provided as a picture of 

two specific years, and not indexed to current price levels.

Table 31. Estimates of Bristol Bay Processor Costs, Prices and Profits

1994 1995 1994 1995 1994 1995

Price paid to fishermen $0.97 $0.75 $0.97 $0.75 $0.97 $0.75

+ Taxes and assessments $0.03 $0.02 $0.03 $0.02 $0.03 $0.02

+ Tender cost $0.17 $0.17 $0.17 $0.17 $0.17 $0.17

+ Costs of services to fishermen $0.03 $0.03 $0.03 $0.03 $0.03 $0.03

= Fish cost per round lb. $1.20 $0.97 $1.20 $0.97 $1.20 $0.97

- Roe value per round lb. (= roe yeild x roe price) $0.09 $0.09 $0.00 $0.00 $0.07 $0.07

= Fish cost per round lb., net of roe value $1.11 $0.88 $1.20 $0.97 $1.13 $0.90

÷ Processing yield 74% 74% 97% 97% 59% 59%

= Fish cost per processed lb., net of roe value $1.51 $1.20 $1.24 $1.00 $1.92 $1.53

+ Processing costs per processed lb. $0.60 $0.60 $0.40 $0.40 $0.73 $0.73

+ Transportation and storage costs before sale $0.00 $0.00 $0.00 $0.00 $0.10 $0.10

+ Other costs $0.10 $0.10 $0.10 $0.10 $0.10 $0.10

= Processor's total cost $2.21 $1.90 $1.74 $1.50 $2.85 $2.46

Average price received by processor $2.45 $1.80 $2.20 $1.00 $2.71 $2.80

Profit or loss (= average price - total cost)

 per processed lb. $0.24 -$0.10 $0.46 -$0.50 -$0.14 $0.34

 per round lb. $0.18 -$0.07 $0.45 -$0.49 -$0.08 $0.20

Note: Costs and prices can vary widely between processors. Any given processor's profits or lesses could be higher or lower than showin in this table.

Source: Currents: A Journal of Salmon Market Trends, University of Alaska Anchorage, Salmon Market Information Service, December 1995.

Frozen Dressed Frozen Round Canned

Estimates of Bristol Bay Processor Costs, Prices, and Profits: Mid-Range Estimates for 1994 and 1995

107 
Selected Bristol Bay Salmon Processor Costs, 2001-2009

0

50

100

150

200

250

300

200120022003200420052006200720082009

millions of nominal dollars

Other costs

and profits

Cost of labor

(fish processing

earnings)

Cost of fish

(ex-vessel

value)

Source: ADFG, ADLWD

Figure 52. Selected Bristol Bay Salmon Processor Costs, 2001-2009 

Most larger Bristol Bay salmon processors contract with tender vessels to transport salmon from 

fishing vessels at or near the best fishing areas to land-based or floating processing facilities. 

Tendering represents a significant cost for the industry. Many tender vessels are larger vessels 

used seasonally in other Alaska fisheries such as the Bering Sea crab fisheries. No data are 

available on the number of tender vessels used in the Bristol Bay fishery. A rough guess is that 

there are about fifty. 

 

Fishermen delivering salmon to a tender. As fish are 

caught, they are placed in brailer bags in the hold of 

the fishing boat. Here, a brailer bag is being hoisted 

aboard a tender, where the fish are kept in refrigerated 

water during transport to the processor.

Photograph by Gabe Dunham

Fish are pumped from tenders into processing plants

Photograph by Gabe Dunham

108 
Sockeye salmon entering a processing plant Workers cleaning salmon

A processing line Packaging is an important cost of fish processing

3.9 Bristol Bay Salmon Industry Employment

Challenges in Measuring Bristol Bay Salmon Industry Employment

Measuring employment in the Bristol Bay salmon industry is complicated by several factors. 

First, no employment data are collected for commercial fishing comparable to the employment 

data collected for most other industries. This is because commercial fishermen (both permit 

holders and crew) are considered self-employed, and they do not pay unemployment insurance. 

Employment data for most industries (including fish processing) are based on unemployment 

insurance reporting forms filed by employers. To make up for this significant gap in Alaska 

employment data, as discussed below, the Alaska Department of Labor and Workforce 

Development (ADLWD) Research and Analysis Division estimates monthly commercial fishing 

employment by multiplying the number of permits for which fish landings are reported each 

month by assumed average employment per permit fished (crew factors).

109 
Second, the Bristol Bay salmon industry is highly seasonal. Most of the fishing and processing 

occurs between the middle of June and the middle of July, with smaller numbers of fishermen 

and processing workers engaged in smaller-scale fishing and processing as well as start-up and 

close-down activities earlier and later in the year. Thus a Bristol Bay fishing or processing job 

which typically lasts less than two months is not directly comparable to a year-round job in 

another industry. As discussed below, to provide a basis for comparing employment in the 

Bristol Bay salmon industry with year-round employment in other industries, we estimate 

“annual average employment,” calculated as the total number of months worked divided by 12. 

Third, the “Bristol Bay Region” for which ADLWD reports fish processing employment and 

estimated salmon fishing employment includes the Chignik salmon fishery—an important 

Alaska salmon fishery although much smaller than the Bristol Bay fishery. By way of 

comparison, between 2006 and 2010, expressed as a percentage of the Bristol Bay salmon 

fisheries, total pounds landed in the Chignik salmon fishery were 7.7% of Bristol Bay, earnings 

were 6.3% of Bristol Bay, and total permits fished were 2.4% of Bristol Bay. Thus ADLWD fish 

harvesting and processing employment estimates and data for the “Bristol Bay region” slightly 

overestimate employment for the Bristol Bay salmon fishery. 

Fourth, estimates of fish processing employment are not available by fishery—because in 

reporting employment fish processing plants do not distinguish between the species of fish that 

their workers were processing during the reporting period. Thus fish processing employment 

estimates for the Bristol Bay region include some employment in processing other species such 

as herring. However, it is likely that fish processing employment data for the Bristol Bay region 

are overwhelmingly dominated by Bristol Bay salmon. For a comparison of the relative scale of 

the two fisheries, between 2006 and 2010, expressed as a percentage of the Bristol Bay salmon 

fisheries, total pounds landed in the Bristol Bay (Togiak) herring seine and gillnet fisheries 

22.6% of pounds landed in the Bristol Bay salmon fisheries, earnings were 2.1% of earnings in 

the salmon fisheries, and the total permits fished were 2.6% of permits fished in the salmon 

fisheries. Note also that Bristol Bay herring processing is much less labor intensive than salmon 

processing because Bristol Bay herring are entirely frozen round for export. 

 

Terminology for Measures of Employment

In the subsequent discussion, we use the following terms for different kinds of employment 

estimates:

 Jobs: The number of distinct work positions 

 Workers: The number of different individuals who worked 

 Annual average employment The number of months worked divided by 12 

For example, suppose a permit holder fishes for two months with two crew members on board 

his boat. After one month one crew member leaves and is replaced by another crew member. 

The permit holder’s operation would account for 3 jobs, 4 workers, and annual average 

employment of 0.5 (3 jobs x 2 months = 6 job months which is 6/12 or 0.5 job years). 

110 
Estimates of Bristol Bay Salmon Harvesting and Processing Employment

Table 32 (on the following page) summarizes available estimates of Bristol Bay salmon 

harvesting and processing employment from several different sources calculated in several 

different ways. Figure 53 (on the subsequent page) graphs several of the estimates shown in 

Table 32. 

Estimated fishing jobs based on salmon permits fished (Rows 1-4)

A simple way to estimate Bristol Bay salmon fishing jobs is from Commercial Fisheries Entry 

Commission (CFEC) data for the number of permits fished and the Alaska Department of Labor 

and Workforce Development (ADLWD) assumption of three jobs for each drift gillnet and each 

setnet fishing operation.16 Based on this methodology, between 2000 and 2010, the number of 

Bristol Bay salmon fishing jobs ranged between 5592 and 8232. The estimated number of jobs 

varied from year to year because the number of permits fished varied from year to year.

A problem with this method of estimating fishing jobs is that since the introduction of “permit 

stacking” in the drift gillnet fishery, there is no longer necessarily a direct relationship between 

the number of permits fished and the number of vessels fished. As discussed, the number of 

permits fished each year likely understates the number of permit holders who fished but likely 

overstates the number of vessels which fished (since some permit holders fished together on the 

same vessel).

CFEC reported that 1444 permits were fished in 2009, but only 1331 vessels were registered to 

fish during the season. This would imply that the number of permits fished overstated that 

number of vessels fished by 113, which would in turn imply that the estimates in Row 4 

overstate the number of fishing jobs by 339. For the same reason, the estimates in rows 6 and 9-

12 of Table 32 (discussed below) may also slightly overestimate the number of fishing workers. 

16 According to a table of crew factors provided to Gunnar Knapp by ADLWD in 2004 (crewfactor.xls), ADLWD 

assumed crew factors of 3.0 for both the Bristol Bay drift gillnet and set gillnet fisheries. 

111 

 
Table 32. Indicators and Estimates of Bristol Bay Salmon Industry Fishing Processing 

Employment

Measure Row 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Estimated fishing jobs based on salmon 

permits fished (a)

Permits fished, drift gillnet fishery 1 1,823 1,566 1,184 1,424 1,411 1,447 1,475 1,468 1,469 1,444 1,494

Permits fished, set gillnet fishery 2 921 834 680 761 795 829 844 835 850 843 861

Permits fished, total 3 2,744 2,400 1,864 2,185 2,206 2,276 2,319 2,303 2,319 2,287 2,355

Estimated number of fishing jobs (= permits 

fished x 3 jobs/permit fished) 4 8,232 7,200 5,592 6,555 6,618 6,828 6,957 6,909 6,957 6,861 7,065

ADLWD estimates of Bristol Bay region 

salmon fishing workers (b)

Individuals who fished permits 5 2,412 1,867 2,196 2,210 2,286 2,340 2,239 2,245 2,309

Total estimated workforce 6 6,969 5,334 6,324 6,294 6,444 7,020 6,717 6,735 9,236

Ratio of estimated workforce to individuals 

who fished permits 7 2.89 2.86 2.88 2.85 2.82 3.00 3.00 3.00 4.00

Estimated crew workers 8 4,557 3,467 4,128 4,084 4,158 4,680 4,478 4,490 6,927

ADLWD estimates of Bristol Bay region 

salmon fishing workers by month (c)

June 9 6,771 4,830 6,045 6,093 6,135 6,201 5,982 6,060 6,393

July 10 7,098 5,514 6,465 6,513 6,750 6,936 6,891 6,969 6,768

August 11 276 309 249 375 279 540 444 504 504

September 12 0 0 0 84 15 3 0 12 54

Bristol Bay region fish processing workers, 

all species (d)

Total worker count 13 2,862 2,273 2,484 3,474 3,272 2,940 3,512 3,952 4,522

Bristol Bay region food manufacturing 

employment (e)

July 14 2,414 3,026 4,189 3,946 4,391 4,480

Annual average 15 765 992 1,139 1,147 1,339 1,385

Assumed total salmon industry workers

Fishing (July employment) (Row 10) 16 7,098 5,514 6,465 6,513 6,750 6,936 6,891 6,969 6,768

Processing (total worker count) (Row 13) 17 2,862 2,273 2,484 3,474 3,272 2,940 3,512 3,952 4,522

Total 18 9,960 7,787 8,949 9,987 10,022 9,876 10,403 10,921 11,290

Estimated annual average

salmon industry employment

Fishing

(= total months of employment / 12) 19 1,179 888 1,063 1,089 1,098 1,140 1,110 1,129 1,143

Fish processing (f) 20 475 366 409 581 532 483 566 640 764

Total 21 1,654 1,254 1,472 1,669 1,631 1,623 1,675 1,769 1,907

Indicators and Estimates of Bristol Bay Salmon Industry Fishing and Processing Employment, 2000-2010

Sources and notes: (a) CFEC Salmon Basic Information Tables, http://www.cfec.state.ak.us/bit/MNUSALM.htm; (b) ADLWD, "Fish Harvesting Workforce and 

Gross Earnings by Species, 2001 - 2009," 

http://www.labor.state.ak.us/research/seafood/BristolBay/BBFHVWrkrErngSpec.pdf. Estimated crew workers= Total estimated workforce - Individuals who 

fished permits. (c) ADLWD, "Fish Harvesting Employment by Species and Month, 2000-2009, Bristol Bay Region," 

http://labor.alaska.gov/research/seafood/BristolBay/BBAvgMonthlyRegSpc.pdf; (d) ADLWD, "Bristol Bay Region Seafood Industry, 2003-2009, Processing," 

http://labor.alaska.gov/research/seafood/BristolBay/BBSFPOver.pdf. 2001 & 2002 data are earlier estimates formerly posted at the same website; (e) ADLWD, 

Quarterly Census of Employment and Wages Data, http://labor.alaska.gov/research/qcew/qcew.htm; (f) annual average fish processing employment estimated by 

assuming the same ratio of annual average employment to total worker count as the ratio of estimated annual average fishing employment to July fishing 

employment.

ADLWD estimates of Bristol Bay region salmon fishing workers (rows 5-8)

These are ADLWD estimates of the salmon harvesting workforce (number of workers) in the 

Bristol Bay region for the years 2001-2009.17 Note that these include workers in the Chignik 

salmon fishery. The total estimated workforce (row 6) was estimated by multiplying the number 

17 The estimates are posted at http://labor.alaska.gov/research/seafood/BristolBay/BBFHVWrkrErngSpec.pdf. A 

discussion of the methodology used to prepare the estimates is posted on the ADLWD website at: 

112 

 
of individuals who fished permits (row 5) by assumed crew factors for each fishery.18 We 

calculated estimated crew workers (row 8) by subtracting individuals who fished permits (Row 

5) from the total estimated workforce (row 6).

Selected Estimates of Bristol Bay Salmon Fishing and Processing Workers

0

2,000

4,000

6,000

8,000

10,000

12,000

20002001200220032004200520062007200820092010

Assumed total fishing and

processing workers

(Row 18)

Estimated fishing jobs

(Row 4)

Estimated July salmon fishing

workers

(row 10)

Estimated fishing workforce

(Row 6)

Food manufacturing July

employment

(Row 14)

Fish processing worker count

(Row 13)

Note: Row numbers 

refer to previous table.

Figure 53. Selected Estimates of Bristol Bay Salmon Fishing and Processing Workers

ADLWD estimates of Bristol Bay region salmon fishing workers by month (Rows 9-12)

These are ADLWD estimates of the salmon harvesting workforce (number of workers) by month 

in the Bristol Bay region for the years 2001-2009.19 The methodology used for these estimates 

http://labor.alaska.gov/research/seafood/Methodology.pdf. Additional discussion of the methodology is provided in 

Josh Warren and Rob Kreiger, “Fish Harvesting in Alaska (Alaska Economic Trends, November 2011); Josh 

Warren and Jeff Hadland, “Employment in Alaska’s Seafood Industry” (Alaska Economic Trends, November 2009); 

and Paul Olson and Dan Robinson, “Employment in the Alaska Fisheries: A special project estimates fish 

harvesting jobs” (Alaska Economic Trends, December 2004), These articles are posted on the ADLWD website at 

http://labor.alaska.gov/trends/. 18 No documentation was provided as to what crew factors were used for these estimates. The ratio of estimated 

workforce to individuals who fished permits (Row 7) suggests that crew factors of 3.0 were used for the years 2006-

2009. It is not clear why the ratio was lower for the years 2001-2005 (between 2.82-2.89) and much higher for 2009 

(4.00), suggesting that different crew factors were used for these years. The estimate for 2009, based on a 25% 

higher crew factor of 4.0, is indicated with a dashed line in Figure 53. 

19 The estimates are posted at http://labor.alaska.gov/research/seafood/BristolBay/BBAvgMonthlyRegSpc.pdf. 

113 

 
was similar but not identical to that used to for the estimates of salmon fishing workers in rows 

5-8), resulting in slightly higher estimates.20

Bristol Bay region fish processing workers, all species (Row 13)

These are ADLWD estimates of the total worker count for Bristol Bay region seafood 

processing.21, 22 

Bristol Bay region food manufacturing employment (Rows 14 & 15)

These are the sum of ADLWD data for food manufacturing employment in Bristol Bay Borough, 

Lake and Peninsula Borough, and the Dillingham Census Area (the ADLWD’s Bristol Bay 

region).23 Table 33 provides the same detail in more detail, by month. Presumably, almost all 

food manufacturing in the Bristol Bay region is fish processing. It is not clear why the July food 

manufacturing employment (Row 14) is considerably larger than the total worker count for fish 

processing for the same region (Row 13). 

Assumed total salmon industry workers (Rows 14 & 15)

For the purposes of this report, we assume that the total number of workers in the Bristol Bay 

salmon industry is July salmon fishing workers (Row 10) and the ADLWD total worker count 

(Row 13). The inconsistencies between the different estimates discussed above suggest that 

while these should be considered reasonable indicators of the general magnitude of the number 

rather than precise data. In general, it appears reasonable to assume that in recent years the total 

number of workers in Bristol Bay salmon fishing and processing has exceeded 10,000. 

Estimated annual average salmon industry employment (Rows 19-21)

These are estimates of salmon industry annual average employment, or job months / 12. Again, 

these should be considered reasonable indicators of the general magnitude of annual average 

employment rather than precisely accurate data. In general, it appears reasonable to assume that 

in recent years average annual employment in Bristol Bay salmon fishing and processing has 

exceeded 1600. 

20 According to notes provided with the estimates, for these estimates “. . . the permit itself is considered the 

employer. In other tables where a count of workers was estimated, the employer was considered to be the vessel, or 

permit holders for fisheries that did not typically use vessels. This means that a permit holder who makes landings 

under two different permits (in the same vessel) in the same month will generate two sets of jobs whereas for tables 

where the vessel is the employer there would be only one set of workers.”

21 The data are posted at http://labor.alaska.gov/research/seafood/BristolBay/BBSFPOver.pdf. 22 The only information about how the data source or methodology is the following: “The Alaska Department of 

Labor and Workforce Development’s Occupational Database (ODB) is the primary source of seafood processing 

employment data. The ODB contains quarterly information for all Alaska workers covered by unemployment 

insurance (UI).” (http://labor.alaska.gov/research/seafood/Methodology.pdf). 23Quarterly Census of Employment and Wages Data posted at http://labor.alaska.gov/research/qcew/qcew.htm. 

114 

 
Seasonality of Bristol Bay Fish Processing Employment

ADLWD monthly data for Bristol Bay food manufacturing employment provide an indication of 

the seasonality and geographic distribution of Bristol Bay salmon processing (Figure 54 and 

Table 33). Presumably salmon processing accounts for most but not all of Bristol Bay region 

food manufacturing employment. One indicator of this is that for the years 2001-2009, the total 

fish harvesting workforce for other fisheries for which ADLWD reported Bristol Bay region 

harvesting workforce estimates, expressed as a percentage of the salmon harvesting workforce 

estimates, averaged 5.5% for herring, 2.1% for halibut and 0.4% for sablefish.24

Bristol Bay region food manufacturing employment peaks in July, and is generally much higher 

during the months from May through September than at other times in the year. Note that a 

significant part of the work in fish processing occurs before the season starts (getting ready for 

processing) and after the season ends (closing down processing operations and preparing for the 

next season). Some people are employed throughout the year in activities such as plant 

maintenance and repair. 

Monthly Employment in Food Manufacturing, Bristol Bay Region, 2002-2007

0

1,000

2,000

3,000

4,000

5,000

January 

February

March

April

May

June

July

August

September

October

November

December

Source: Alaska Department of Labor and Workforce Development

2007

2006

2005

2004

2003

2002

Figure 54. Monthly Employment in Food Manufacturing, Bristol Bay Region 

24 ADLWD, “Fish Harvesting Workforce and Gross Earnings by Species, 2001-2009, Bristol Bay Region,” 

http://labor.alaska.gov/research/seafood/BristolBay/BBFHVWrkrErngSpec.pdf. 

115 

 
Table 33. Monthly Employment in Food Manufacturing, by Borough or Census Area.

Area Month 2002 2003 2004 2005 2006 2007 2008 2009 2010

Units reporting 8 9 11 14 11 11 10 12 12

January 7 52 11 11 14 12 16

February 8 56 10 12 13 11 19

March 8 57 21 19 25 19 27

April 441 197 81 81 113 73 96

May 495 464 678 818 894 651 977

June 713 1,115 1,299 1,365 1,957 1,635 1,819

July 977 1,915 2,644 2,663 2,898 3,018 3,489

August 325 1,291 1,250 1,424 1,471 1,661 1,738

September 51 728 834 847 789 826 914

October 42 41 46 68 61 671 92

November 29 49 59 72 74 504 66

December 34 22 46 51 53 188 59

Average 261 499 582 619 697 772 776

Units reporting 4 3 3 4 4 3 3 3 3

January 283 124 184 123 232 332

February 529 512 519 543 418 259

March 590 495 496 507 487 366

April 455 373 451 377 477 326

May 372 390 285 392 455 338

June 384 339 739 799 951 760

July 1,091 775 1,035 1,057 1,164 1,162

August 392 544 544 694 987 901

September 347 618 552 567 789 1,040

October 283 270 331 306 305 293

November 149 260 253 257 199 315

December 48 84 147 82 97 167

Average 410 399 461 475 547 522

Units reporting 7 5 5 4 4 4 4 3 3

January 20 10 5 4 11 10 9

February 21 34 5 4 17 15 15

March 19 11 11 5 19 17 16

April 23 40 27 9 26 25 29

May 53 53 52 38 62 61 69

June 222 191 258 171 242 197 156

July 346 336 510 226 329 300 319

August 278 329 250 135 258 215 24

September 87 90 18 17 89 97 20

October 15 14 8 11 41 66 5

November 13 10 7 9 27 59 5

December 28 8 6 10 20 24 5

Average 94 94 96 53 95 91 56

Units reporting 19 17 19 22 19 18 17 18 18

January 310 186 200 138 257 354 9

February 558 602 534 559 448 285 15

March 617 563 528 531 531 402 16

April 919 610 559 467 616 424 29

May 920 907 1,015 1,248 1,411 1,050 69

June 1,319 1,645 2,296 2,335 3,150 2,592 156

July 2,414 3,026 4,189 3,946 4,391 4,480 319

August 995 2,164 2,044 2,253 2,716 2,777 24

September 485 1,436 1,404 1,431 1,667 1,963 20

October 340 325 385 385 407 1,030 5

November 191 319 319 338 300 878 5

December 110 114 199 143 170 379 5

Average 765 992 1,139 1,147 1,339 1,385 56

Monthly Employment in Food Manaufacturing, by Borough or Census Area, Bristol Bay Region, 2002-2010

Source: Alaska Department of Labor and Workforce Development, Quarterly Census of Employment and Wages Data, historical data for 2002-

2010, Excel file annual.xls, http://labor.alaska.gov/research/qcew/qcew.htm, downloaded November 27, 2011. Blank cells indicate data were not 

available.

Bristol Bay 

Borough

Dillingham 

Census 

Area

Lake and 

Peninsula 

Borough

Total, 

Bristol Bay 

Region

116 
3.10 Bristol Bay Salmon Industry Taxes

The Bristol Bay salmon industry pays millions of dollars annually in state, local and federal 

taxes. This section briefly describes these taxes and provides estimates, where available, of taxes 

paid in recent years.

Alaska Fisheries Business Tax

The Alaska Fisheries Business Tax (AS 43.75.015) accounts for the largest share of local and 

state taxes paid by the Bristol Bay salmon industry. Under the fisheries business tax, salmon 

processors pay the state:

5.0% of the ex-vessel value of salmon processed on floating facilities

4.5% of the ex-vessel value of salmon canned at shore-based facilities

3.0% of the ex-vessel value of other salmon processed at shore-based facilities 

(e.g. salmon processed frozen, fresh, or in other ways except for canning) 

The State of Alaska does not publish data on fisheries business tax revenues for specific species 

and regions. Rows 1-4 of Table 34 provide a lower-bound estimate of tax obligations (before 

credits) of Bristol Bay salmon processors, assuming that processors pay a tax rate of 5.0% for a 

share of ex-vessel value equivalent to the share of canned salmon production in total Bristol Bay 

salmon production, and 3.0% of ex-vessel value on the remaining share of ex-vessel value. This 

estimate suggests that during the period 2000-2010, fisheries business tax obligations ranged 

from as low as $1.3 million in 2002 to $6.4 million. Fisheries business tax payments are directly 

proportional to ex-vessel value and thus highly sensitive to the effects of changes in catches and 

prices on ex-vessel value.

Actual tax obligations are likely higher than the lower-bound estimates in Row 4, since (a) the 

estimates do not take account of the higher tax rate (5.0%) on salmon processed on floating 

processing; and (b) the share of salmon which is canned is likely higher than the share of canned 

production in total production, because average yields are lower for canning. 

Processors are entitled to credits against Fisheries Business Tax obligations up to certain limits 

for certain kinds of expenditures, including for example investments in salmon product 

development (AS 43.75.035); investments to improve salmon utilization (AS 43.75.036), and 

and contributions to the University of Alaska and other Alaska higher education institutions (AS 

43.75.018). No data are available on the extent to which these tax credits reduce Bristol Bay 

fisheries business tax revenues.

117 
Table 34. Selected Data and Estimates for Bristol Bay Salmon Taxes 

Row 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Simple lower-bound estimate of 

fisheries business tax obligations 

Ex-vessel value of Bristol Bay salmon 

harvests ($ 000)

1 $84,014 $40,359 $31,898 $46,684 $76,461 $94,556 $108,570 $115,763 $116,717 $144,200 $180,818

Canned share

(assumed tax rate = 5.0%)

2 37% 32% 49% 39% 34% 32% 34% 35% 28% 25% 27%

Non-canned share

(assumed tax rate = 3%)

3 63% 68% 51% 61% 66% 68% 66% 65% 72% 75% 73%

Lower-bound estimate of fisheries tax 

obligation ($ 000)

4 $3,145 $1,467 $1,270 $1,760 $2,818 $3,439 $3,998 $4,287 $4,163 $5,061 $6,383

State of Alaska Shared Business Tax 

Payments to Bristol Bay Boroughs 

and Cities ($ 000) (a)

Bristol Bay Borough 5 $1,440 $918 $494 NA $451 $835 $1,178 $1,296 $1,564 $1,543 $1,797

Lake and Peninsula Borough 6 $357 $246 $162 NA $113 $71 $99 $134 $138 $152 $215

Dillingham 7 $203 $176 $49 NA $100 $154 $148 $184 $176 $187 $239

Egegik 8 $30 $176 $78 NA $36 $29 $29 $74 $63 $63 $85

Total 9 $2,029 $1,517 $784 NA $700 $1,089 $1,454 $1,687 $1,941 $1,944 $2,335

Selected Data and Estimates for Bristol Bay Salmon Taxes

(a) Source: Alaska Department of Revenue, Annual Shared Taxes and Fees Reports, www.tax.alaska.gov. NA: Not available.

Fisheries Business Tax Refunds

The State of Alaska “refunds” a major share of Fisheries Business Tax revenues to Alaska local 

governments, as follows (AS 43.75.130): 

Cities receive 50% of the tax revenues collected in unified municipalities and in 

cities outside organized boroughs, and 25% of tax revenues collected in cities in 

organized boroughs 

Boroughs receive 50% of the tax revenues collected in areas of boroughs outside 

cities and 25% of the tax revenues collected in cities inside Boroughs. 

Rows 5-9 of Table X-1 provide data on State of Alaska shared fisheries tax payments to Bristol 

Bay boroughs and cities. In total, these payments ranged from $700 thousand in 2004 to $2.3 

million in 2010. 

Local Government Taxes

Several local governments in the Bristol Bay region impose taxes on the ex-vessel value of 

salmon processed within their jurisdictions. In 2010, these included the following:25

Bristol Bay Borough: 4% fish taxEgegik: 3% 

raw fish tax

Lake and Peninsula Borough: 2% raw fish tax

Pilot Point: 3% raw fish tax

25 Alaska Office of the State Assessor, 2010 Alaska Taxable, Table 2, Sales/Special Taxes and Revenues, 

http://www.dced.state.ak.us/dca/osa/osa_summary.cfm. 

118 

 
Local governments also impose property taxes on processing facilities. No data are published on 

Bristol Bay local government fish taxes or property taxes. However, it is likely that these taxes 

are comparable in magnitude to fisheries business taxes, and represent a major share of total 

local government tax revenues.

Federal Government Taxes

Like all U.S. industries, the Bristol Bay salmon industry pays federal taxes including corporate 

and individual income taxes paid by processing companies, processing workers, and fishermen. 

No data are available on federal taxes specifically attributable to the Bristol Bay salmon industry, 

although it is likely that they significantly exceed total taxes paid to the state and local 

governments. 

3.11 Regional Distribution of Bristol Bay Permit Holders, Fishery 

Earnings, and Processing Employment

An important characteristic of the Bristol Bay commercial salmon industry is that shares of the 

participants in the industry—both fishermen and processing workers—do not live in the Bristol 

Bay region but rather in other parts of Alaska or other states and countries. In this section we 

review available data on trends in the regional distribution of permit holdings, earnings and 

processing employment between “local” residents of the Bristol Bay region, other Alaskans, and 

non-Alaskans.

The Bristol Bay Region 

There are twenty-six communities in the Bristol Bay region the Commercial Fisheries Entry 

Commission (CFEC) considers “local” to the fishery for its analyses (Figure 55). Residents of 

these villages are considered “Bristol Bay residents” for the CFEC data presented below on 

permit holdings and earnings of Bristol Bay residents. 

Residents of five additional villages on the south side of the Alaska Peninsula (Chignik City, 

Chignik Lagoon, Chignik Lake, Perryville and Ivanof) are also considered “Bristol Bay 

residents” for the Alaska Department of Labor and Workforce Development (ADLWD) data on 

seafood processing employment. 

119 
Figure 55. Bristol Bay Region Local Communities Source: 

www.visitbristolbay.org/bbvc/images/bb_map_large.jpg

Regional Distribution of Permit Holders

Limited entry was implemented for most Alaska salmon fisheries in 1975, including the Bristol 

Bay drift gillnet and set gillnet fisheries. The permits were initially issued for free to individuals 

based on their degree of economic dependence upon the fishery and the extent of their past 

participation in the fishery. The purpose and effect of this initial allocation system was to 

ensure that significant numbers of rural local residents received permits in regions of Alaska with 

limited other economic opportunities, such as Bristol Bay (Knapp, 2011). 

120 
Number of Bristol Bay Drift Gillnet Permit Holders, by Residency

0

200

400

600

800

1,000

1,200

19781980198219841986198819901992199419961998200020022004200620082010

Source: CFEC, Changes in the Distribution of Alaska's Commercial Fisheries Entry Permits,

1975-2010 

Residents

of other

states

Other

Alaska

residents

Bristol Bay

residents

Number of Bristol Bay Set Gillnet Permit Holders, by Residency

0

100

200

300

400

500

600

19781980198219841986198819901992199419961998200020022004200620082010

Source: CFEC, Changes in the Distribution of Alaska's Commercial Fisheries Entry Permits,

1975-2010 

Residents

of other

states

Other

Alaska

residents

Bristol Bay

residents

Figure 56. Number of Bristol Bay Permit Holders by 

Residency

Soon after the implementation of 

limited entry a significant longterm decline began in the share of 

permits held by local residents in 

the Bristol Bay fisheries and many 

other rural Alaska fisheries. There 

has been a corresponding increase 

in the number of permits held by 

other Alaska residents as well as 

non-Alaska residents. This decline 

in local permits has been an 

important concern at both the 

regional and state level. 

Between 1978 and 2010, the 

number of permits Bristol Bay 

drift gillnet permits held by local 

residents fell from 614 to 383 

(Figure 56). The share of drift 

gillnet permits held by local 

residents fell from 36% to 21%.

Between 1978 and 2010, the 

number of permits Bristol Bay set 

gillnet permits held by local 

residents fell from 530 to 353. The 

share of permits held by local 

residents fell from 59% to 36%.

The decline in local permit 

ownership has come about as a 

result of both net permit transfers 

(sales and gifts) from residents of 

the region to non-local residents, as well as migration of permit holders out of the region. 

Initially net permit transfers played a far greater role, but migration of permit holders out of the 

region has also played an important role in recent years.

121 
Drift Gillnet Permit Holders Average Earnings Per Permit Fished, by Residency

$0

$20,000

$40,000

$60,000

$80,000

$100,000

$120,000

$140,000

19751977197919811983198519871989199119931995199719992001200320052007

Residents of other

states

Other Alaska

residents

Bristol Bay

residents

Set Gillnet Permit Holders Average Earnings Per Permit Fished, by Residency

$0

$5,000

$10,000

$15,000

$20,000

$25,000

$30,000

$35,000

$40,000

$45,000

19751977197919811983198519871989199119931995199719992001200320052007

Residents of other

states

Other Alaska

residents

Bristol Bay

residents

Figure 57. Permit Holders Average Earnings, by Residency

Regional Distribution of Fishery Earnings

Historically, Bristol Bay

residents have had the 

lowest average earnings 

(gross revenues) per permit 

fished, while residents of 

other stages have had had 

the highest average 

earnings per permit fished. 

For example, in 2007—the 

latest year for which CFEC 

earnings data by residency 

are available, in the Bristol 

Bay drift gillnet fishery, 

average earnings per permit

fished were $44,604 for 

Bristol Bay residents, 

$66,191 for other Alaska 

residents, and $73,391 for 

non-Alaska residents 

(Figure 57). 

In the Bristol Bay set 

gillnet fishery, average 

earnings per permit fished 

were $22,991 for Bristol 

Bay residents, $23,259 for 

other Alaska residents, and 

$25,333 for non-Alaska 

residents (Figure 57). 

A variety of factors may 

contribute to these 

differences in average 

earnings per permit fished 

by residency. In the drift 

gillnet fishery, the vessels operated by Bristol Bay residents tend to be older and smaller, with 

lower average horsepower and fuel capacity than those of other Alaska residents or residents of 

other states (Table 35). A much smaller share of the vessels operated by Bristol Bay residents 

have refrigeration capacity. All of these differences may reflect less access to capital for Bristol 

Bay residents than for other Alaska residents or residents of other states. However, the reasons 

for differences in earnings between groups have not been studied in detail or conclusively 

explained. 

122 
Table 35. Comparison of Vessels Used in the Bristol Bay Drift Gillnet Fishery, by 

Residency of Permit Holder

Group 1983 1988 1993 1998 2003 2008

Bristol Bay Residents 9 11 14 18 22 26

Other Alaska Residents 9 11 14 17 21 24

Residents of Other States 11 12 13 16 20 24

Average 10 11 14 17 21 25

Bristol Bay Residents 239 279 282 294 287 337

Other Alaska Residents 243 271 315 345 350 373

Residents of Other States 252 286 335 368 372 382

Average 245 278 311 336 336 364

Bristol Bay Residents 10 12 12 12 12 12

Other Alaska Residents 12 13 13 13 14 15

Residents of Other States 12 12 13 14 14 14

Average 11 12 13 13 13 14

Bristol Bay Residents 239 288 282 294 287 299

Other Alaska Residents 306 334 364 357 357 360

Residents of Other States 283 311 348 352 350 364

Average 276 311 331 335 331 341

Bristol Bay Residents 0.5% 0.5% 2.3% 4.5% 5.5% 7.7%

Other Alaska Residents 1.3% 2.3% 7.5% 13.7% 15.3% 20.8%

Residents of Other States 0.5% 2.0% 8.1% 15.5% 17.8% 22.2%

Average 0.8% 1.6% 6.0% 11.2% 12.9% 16.9%

Percent of 

vessels with 

refrigeration 

capacity

Comparison of Vessels Used in the Bristol Bay Drift Gillnet Fishery, by Residency of Permit Holder

Northern Economics. 2009. The Importance of the Bristol Bay Salmon Fisheries to the Region and its 

Residents. Report prepared for the Bristol Bay Economic Development Corporation. 193 pages. Data are 

from tables on pages 136 and 137 of report. Based on data provided by the Commercial Fisheries Entry 

Commission.

Average age

of vessels

(years)

Average 

horsepower of 

vessels

Average 

displacement of 

vessels

(gross tons)

Average fuel 

capacity of 

vessels (gallons)

123 
Share of Total Earnings of Bristol Bay Drift Gillnet Permit Holders, by Residency

0%

10%

20%

30%

40%

50%

60%

70%

19751977197919811983198519871989199119931995199719992001200320052007

Residents of other

states

Other Alaska

residents

Bristol Bay

residents

Figure 58. Share of Total Earnings of Bristol Bay Drift Gillnet Permit Holders, by 

Residency

Trends over time in the share of different groups in total earnings of Bristol Bay permit holders 

represent the combined effects of trends over time in each group’s share of permit holdings as 

well as differences between groups in average earnings. In the drift gillnet fishery, the share of 

Bristol residents in total earnings fell from about 35% in the late 1970s to just 15% in 2007. The 

share of non-Alaska residents increased from less than 50% in the late 1970s to 60% in 2007 

(Figure 58).

124 
Share of Total Earnings of Bristol Bay Set Gillnet Permit Holders, by Residency

0%

10%

20%

30%

40%

50%

60%

70%

19751977197919811983198519871989199119931995199719992001200320052007

Residents of other

states

Other Alaska

residents

Bristol Bay

residents

Figure 59. Share of Total Earnings of Bristol Bay Set Gillnet Permit Holders, by 

Residency

125 

In the set gillnet fishery, the share of Bristol residents in total earnings fell from about 63% in the 

late 1970s to 35% in 2007. The share of non-Alaska residents increased from about 20% in the 

late 1970s to 34% in 2007 (Figure 59).

Regional Distribution of Processing Employment 

Employment in Bristol Bay seafood processing is overwhelmingly dominated by residents of 

other states and countries. In 2009, according to Alaska Department of Labor and Workforce 

Development data, Bristol Bay residents accounted for less than 2% of Bristol Bay processing 

workers, and other Alaska residents accounted for only 12%. Residents of other states and 

countries accounted for 87%. (Processing employment data by residency are only available for 

the years 2004-2009).(Figure 59).
Share of Bristol Bay Seafood Processing Employment, by Residency

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

200420052006200720082009

Source: Alaska Department of Labor and Workforce Development, Research and Analysis Division

Residents of other

states or countries

Other Alaska

residents

Bristol Bay

residents

Figure 60. Share of Bristol Bay Seafood Processing Employment, by Residency 

A Primarily Non-Local Fishery—With Widely Distributed Benefits

As is clear from the preceding figures, local residents account for a relatively small and declining 

share of the jobs and earnings in the Bristol Bay salmon industry (Figure 61). In contrast, nonAlaska residents account for relatively large and growing share of the jobs and earnings. 

126 
Local Bristol Bay Resident Share of the Bristol Bay Salmon Fisheries: 

Selected Measures

0%

10%

20%

30%

40%

50%

19781980198219841986198819901992199419961998200020022004200620082010

Source: CFEC, Changes in the Distribution of Alaska's Commercial Fisheries Entry Permits,

1975-2010 

Total

permits

held*

Total

earnings*

Processing

employment

*Shares for 

both fisheries 

combined.

Figure 61. Local Bristol Bay Resident Share of Salmon Fisheries: Selected Measures

This does not mean, of course, that the Bristol Bay salmon fishery is unimportant as a source of 

jobs or income for local residents. As we discuss in greater detail previously, it remains very 

important. However, it is not as important for local residents as it might appear if one were to 

erroneously assume that all the jobs were held by local residents and all the income was earned 

by local residents.

Bristol Bay processing worker from Turkey

127 
A different perspective is that the Bristol Bay fishery is not just economically important for a 

remote region of southwestern Alaska. Rather, it is of major economic importance for other 

parts of Alaska and other states, particularly the Pacific Northwest. Thousands of residents of 

other parts of Alaska and other states work in and earn significant income from participating in 

Bristol Bay fishing and processing. For example, as shown in Table 36, in 2010, 597 residents 

of other parts of Alaska, 656 residents of Washington, 125 residents of Oregon and 119 residents 

of California fished Bristol Bay salmon permits. They had gross earnings of $40 million (other 

Alaskans), $59 million (Washington residents), $10 million (Oregon residents, and $9.5 million 

(California residents). 

Table 36. Participation and Gross Earnings in Bristol Bay Salmon Fisheries

Drift gillnet 

fishery

Set gillnet 

fishery Total

Drift gillnet 

fishery

Set gillnet 

fishery Total

Bristol Bay Residents, Total 301 297 598 18,250 10,670 28,920

Dillingham Census Area 202 183 385 11,170 6,451 17,620

Bristol Bay Borough 56 83 139 4,227 3,162 7,389

Lake and Peninsula Borough 43 31 74 2,854 1,057 3,911

Other Alaska Residents, Total 359 238 597 31,215 8,858 40,074

Anchorage 86 120 206 6,479 4,288 10,767

Kenai Peninsula Borough 86 44 130 7,968 1,685 9,652

Matanuska-Susitna Borough 38 42 80 3,593 1,504 5,097

Wrangell-Petersburg Census Area 18 18 2,445 0 2,445

Kodiak Island Borough 42 9 51 3,951 321 4,272

Other parts of Alaska 89 23 112 6,780 1,061 7,841

Alaska Residents, Total 660 535 1195 49,466 19,528 68,994

Other States and Countries, Total 850 281 1131 84,671 11,494 96,165

Washington 538 118 656 55,342 4,179 59,521

Oregon 87 39 126 8,383 1,618 10,001

California 87 32 119 8,058 1,449 9,507

Other States & Countries 138 92 230 12,888 4,249 17,136

TOTAL 1510 816 2326 134,137 31,022 165,159

*Number of fishermen who made at least one landing as a permit holder.

Source: Commercial Fisheries Entry Commission, Fishery Participation and Earnings Statistics, 2010: 

http://www.cfec.state.ak.us/gpbycen/2010/mnu.htm.

Number of Fishermen Who Fished* Estimated Gross Earnings ($1000)

Group

Participation and Gross Earnings in Bristol Bay Salmon Fisheries, by Group, 2010

128 
3.12 Distribution of Salmon Permits and Earnings within The Bristol 

Bay Region

Above, we discussed the distribution of Bristol Bay 

salmon permits and earnings between local residents of 

the Bristol Bay region and residents of other parts of 

Alaska and other states. In this section, we discuss the 

distribution of permits and earnings within the Bristol 

Bay region. 

For this analysis, we used the Commercial Fisheries 

Entry Commission (CFEC) definition of the Bristol Bay 

region as the twenty-six communities within the Bristol 

Bay watershed. For the analysis in this section, we use 

the Alaska Department of Labor and Workforce 

Development (ADLWD) definition of the Bristol Bay 

region as the Bristol Bay Borough, the Lake and 

Peninsula Borough, and the Dillingham Census Area. 

The ADLWD definition is slightly larger because it 

includes five communities outside the Bristol Bay 

watershed (Chignik City, Chignik Lagoon, Chignik 

Lake, Perryville and Ivanof). 

129 

We further divide the Bristol 

Bay region into seven smaller 

regions, consisting of the groups 

of communities: 

Bristol Bay Borough

Dillingham Region

Togiak-Manokotak Region 

Upper Nushugak Region 

Lake Region 

South Bristol Bay Region 

Chignik Region 

We omit the Chignik Region 

from the figures because 

residents of the region have very 

little involvement with the 

Bristol Bay fishery.

Table 37 summarizes population, numbers of permit holders, and salmon fishery earnings for 

each community and region in 2000 and 2010. These data were used to calculate per capita 
permit holdings and earnings shown in Table 38 and Table 39. We used similar data to calculate 

Figure 62 through Figure 69 which show trends by region over time. 

Table 37. Population, Permit Holders, and Salmon Earnings, by Community: 2000 & 2010 

2000 2010 2000 2010 2000 2010 2000 2010 2000 2010

BRISTOL BAY BOROUGH 1257 997 63 63 117 101 $1,939 $4,227 $1,506 $3,162

King Salmon 442 374 14 15 17 17 $589 $1,209 $291 $749

Naknek 678 544 37 38 70 69 $1,120 $2,695 $920 $2,184

South Naknek 137 79 12 10 30 15 $230 $323 $295 $229

DILLINGHAM CENSUS AREA 4,922 4,847 326 262 231 199 $10,287 $10,913 $3,901 $6,246

Dillingham Region 2800 2614 167 142 115 97 $6,284 $6,855 $2,005 $3,032

Aleknagik 221 219 19 15 9 6 $530 $752 $131 $174

Clarks Point 75 62 8 7 5 4 $329 $0 $68 $117

Dillingham 2,466 2,329 139 120 101 87 $5,425 $6,103 $1,806 $2,742

Ekuk 2 2 0 0 0 0 - - - -

Portage Creek 36 2 1 0 0 0 - - - -

Togiak-Manokotak Region 1277 1333 107 80 106 97 $2,918 $3,222 $1,811 $3,213

Manokotak 399 442 28 24 44 35 $847 $696 $646 $1,547

Togiak 809 817 72 53 60 62 $2,071 $2,526 $1,165 $1,666

Twin Hills 69 74 7 3 2 0 $0 $0 $0 $0

Upper Nushagak Region 783 834 52 40 10 5 $1,084 $836 $85 $0

Ekwok 130 115 5 3 0 0 $117 - - -

Koliganek 182 209 14 16 3 2 $300 $456 - -

New Stuyahok 471 510 33 21 7 3 $667 $380 $85 -

LAKE AND PEN. BOROUGH 1,823 1,631 86 57 64 45 $1,454 $2,018 $436 $599

Lake Region 986 953 36 28 32 27 $371 $865 $109 $499

Igiugig 53 50 4 3 0 1 - - - -

Iliamna 102 109 8 9 7 6 $116 $450 $51 $215

Kokhanok 174 170 4 3 4 6 $76 $0 $0 $143

Levelock 122 69 8 4 6 2 $130 $189 $0 $0

Newhalen 160 190 6 6 2 4 $49 $226 $0 $141

Nondalton 221 164 4 2 8 4 - - $57 -

Pedro Bay 50 42 1 0 2 3 - - - -

Port Alsworth 104 159 1 1 3 1 - - - -

South Bristol Bay Region 346 291 49 28 31 17 $1,083 $1,152 $328 $100

Egegik 116 109 23 10 15 7 $494 $468 $222 $100

Pilot Point 100 68 9 8 11 5 $232 $0 $106 $0

Port Heiden 119 102 15 8 3 3 $357 $684 $0 $0

Ugashik 11 12 2 2 2 2 - - - -

Chignik Region 456 362 1 1 1 1 - - - -

Chignik 79 91 0 0 0 0 - - - -

Chignik Lagoon 103 78 0 0 0 0 - - - -

Chignik Lake 145 73 1 1 1 1 - - - -

Ivanof Bay 22 7 0 0 0 0 - - - -

Perryville 107 113 0 0 0 0 - - - -

BRISTOL BAY, TOTAL (a) 8003 7475 475 382 412 345 $13,679 $17,158 $5,843 $10,007

BRISTOL BAY, TOTAL (b) 7547 7113 474 381 411 344 $13,679 $17,158 $5,843 $10,007

(a) Total includes the Chignik Region; (b) Total excludes the Chignik Region. Note: "-" indicates that earnings data were confidential 

and not reported. Sources: U.S. Censuses, 2000 and 2010; CFEC.

Population, Salmon Permit Holders, and Bristol Bay Salmon Earnings, by Community, 2000 & 2010

Resident drift

gillnet earnings

($000)

Resident set

gillnet earnings

Population ($000)

Drift gillnet 

permit holders

Set gillnet 

permit holders

130 
Estimated Bristol Bay Area Population, by Borough / Census Area

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1980198219841986198819901992199419961998200020022004200620082010

Bristol Bay Area, Total

Dillingham Census Area

and Lake & Peninsula

Borough Combined

Dillingham Census Area

Lake and Peninsula

Borough

Bristol Bay Borough

Figure 62. Estimated Bristol Bay Area Population, by Area 

Estimated Population, by Region

0

500

1000

1500

2000

2500

3000

19841986198819901992199419961998200020022004200620082010

Dillingham Region

Togiak-Manokotak Region

Bristol Bay Borough

Lake Region

Upper Nushagak Region

South Bristol Bay Region

Figure 63. Estimated Population by Region 

Bristol Bay Population Trends

Figure 62 and Figure 63 show population trends for the Bristol Bay region. Note that the 

population data should be considered estimates rather than precise data. They are based on the 

decennial United States censuses conducted in 1980, 1990, 2000 and 2010, and were estimated 

for intervening years by the Alaska Department of Labor and Workforce Development. In 

addition, given the 

seasonality of the Bristol 

Bay area employment and 

the fact that much of the 

workforce is non-resident, 

it is difficult to define or 

measure population 

precisely. It is most 

useful to focus on longterm population trends 

and relative populations of 

different regions rather 

than short-term changes 

which may result from 

changes in how the data 

were estimated rather than 

actual population changes. 

 In general, the population 

of the Bristol Bay area 

increased rapidly during 

the 1980s, grew more 

slowly during the 1990s, 

and declined gradually 

during the 2000s. The 

total 2010 population was 

about 7500. 

Of the six regions within 

the Bristol Bay area 

(excluding Chignik) the 

Dillingham Region has by 

far the largest population 

and the south Bristol Bay 

region has by far the 

smallest.

131 
Number of Drift Gillnet Permit Holders, by Region

0

50

100

150

200

250

19841986198819901992199419961998200020022004200620082010

Dillingham Region

Togiak-Manokotak Region

Bristol Bay Borough

Upper Nushagak Region

South Bristol Bay Region

Lake Region

Figure 64. Number of Drift Gillnet Holders, by Region

Number of Drift Gillnet Permit Holders per 100 Residents, by Region

0

5

10

15

20

25

19841986198819901992199419961998200020022004200620082010

South Bristol Bay Region

Togiak-Manokotak Region

Bristol Bay Borough

Dillingham Region

All Bristol Bay Regions

Upper Nushagak Region

Lake Region

Figure 65. Number of Drift Gillnet Holders per 100 Residents,

by Region 

Permit Holders

Figure 64 shows the number of drift gillnet permit holders by region for the years 1984-2010. 

The number is highest for the Dillingham Region, followed by the Togiak-Manokotak Region. 

The number of drift gillnet permit holders has declined in all regions since 1984. The rate of 

decline has been somewhat less for the Bristol Bay Borough, particularly since 2000. 

Figure 65 shows number 

of drift gillnet permit 

holders per 100 residents, 

by region. This measure 

is equal to per capita 

permit holdings multiplied 

by 100. 

By adjusting for 

differences in population 

over time and between 

regions, it provides a way 

of comparing the relative 

degree of participation by 

residents in the drift 

gillnet fishery over time 

and between regions. 

Because the Bristol Bay 

population is currently 

higher than it was in the 

early 1980s, permit 

holdings per 100 residents 

have declined relatively 

more sharply than total 

permit holdings, and have 

fallen by about half since 

1984 in all regions except 

the Bristol Bay Borough. 

In 2010, the number of 

permit holders per 100 

residents was highest in 

the South Bristol Bay 

Region (10) and lowest in 

the Lake Region (3). 

Thus the degree of 

participation in the drift 

gillnet fishery varies 

between these regions by 

132 
Number of Set Gillnet Permit Holders, by Region

0

20

40

60

80

100

120

140

160

19841986198819901992199419961998200020022004200620082010

Bristol Bay Borough

Togiak-Manokotak Region

Dillingham Region

Lake Region

South Bristol Bay Region

Upper Nushagak Region

Figure 66. Number of Set Gillnet Holders, by Region

Number of Set Gillnet Permit Holders per 100 Residents, by Region

0

2

4

6

8

10

12

14

16

19841986198819901992199419961998200020022004200620082010

Bristol Bay Borough

South Bristol Bay Region

Togiak-Manokotak Region

All Bristol Bay Regions

Dillingham Region

Lake Region

Upper Nushagak Region

Figure 67. Number of Set Gillnet Permit Holders per 100 

Residents, by Region

a factor of 3. 

Figure 66 shows the number of set gillnet permit holders by region for the years 1984-2010. The 

number is highest for the Bristol Bay Borough, Togiak-Manokotak Region, and Dillingham 

Region, and is much lower for the other three regions. Since 1984, the number of set gillnet 

permit holders has declined in four regions (Bristol Bay Borough, Dillingham Region, Lake 

Region, and South Bristol 

Bay Region). However, 

the declines have 

generally not been as 

steep as the declines in the 

number of drift gillnet 

permit holders. The 

number of set gillnet 

permit holders has stayed 

about the same in the 

Togiak-Manakotak 

Region. It is very small in 

the Upper Nushagak 

Region. 

Figure 67 shows number 

of set gillnet permit 

holders per 100 residents, 

by region. In general, the 

number of set gillnet 

permit holders per 100 

residents has trended 

downward in all regions 

except for the Bristol Bay 

Borough. 

There is wide variation 

between regions in the 

degree of participation in 

the set gillnet fishery, 

from as high as 10 permit 

holders per 100 residents 

in the Bristol Bay 

Borough to as low as 1 in 

the Upper Nushagak 

Region. 

Just as there is wide 

variation between regions 

in the numbers of permit 

holders per 100 residents, there is also wide variation between individual communities within 

133 
regions and within the Bristol Bay watershed as a whole (Table 38). In 2010, some 

communities, such as Ekwok and Nondalton, had fewer than 5 permit holders (drift and set 

gillnet combined) per 100 residents. Others communities, such as Naknek and South Naknek, 

had 20 or more. 

Table 38. Salmon Permit Holders per 100 Residents, by Community

2000 2010 2000 2010 2000 2010

BRISTOL BAY BOROUGH 5 6 9 10 14 16

King Salmon 3 4 4 5 7 9

Naknek 5 7 10 13 16 20

South Naknek 9 13 22 19 31 32

DILLINGHAM CENSUS AREA 7 5 5 4 11 10

Dillingham Region 6 5 4 4 10 9

Aleknagik 9 7 4 3 13 10

Clarks Point 11 11 7 6 17 18

Dillingham 6 5 4 4 10 9

Ekuk 0 0 0 0 0 0

Portage Creek 3 0 0 0 3 0

Togiak-Manokotak Region 8 6 8 7 17 13

Manokotak 7 5 11 8 18 13

Togiak 9 6 7 8 16 14

Twin Hills 10 4 3 0 13 4

Upper Nushagak Region 7 5 1 1 8 5

Ekwok 4 3 0 0 4 3

Koliganek 8 8 2 1 9 9

New Stuyahok 7 4 1 1 8 5

LAKE AND PEN. BOROUGH 5 3 4 3 8 6

Lake Region 4 3 3 3 7 6

Igiugig 8 6 0 2 8 8

Iliamna 8 8 7 6 15 14

Kokhanok 2 2 2 4 5 5

Levelock 7 6 5 3 11 9

Newhalen 4 3 1 2 5 5

Nondalton 2 1 4 2 5 4

Pedro Bay 2 0 4 7 6 7

Port Alsworth 1 1 3 1 4 1

South Bristol Bay Region 14 10 9 6 23 15

Egegik 20 9 13 6 33 16

Pilot Point 9 12 11 7 20 19

Port Heiden 13 8 3 3 15 11

Ugashik 18 17 18 17 36 33

Chignik Region 0 0 0 0 0 1

Chignik 0 0 0 0 0 0

Chignik Lagoon 0 0 0 0 0 0

Chignik Lake 1 1 1 1 1 3

Ivanof Bay 0 0 0 0 0 0

Perryville 0 0 0 0 0 0

BRISTOL BAY, TOTAL (a) 6 5 5 5 11 10

BRISTOL BAY, TOTAL (b) 6 5 5 5 12 10

(a) Total includes the Chignik Region; (b) Total excludes the Chignik Region. Sources: U.S. Censuses, 2000 and 2010; 

CFEC.

Salmon Permit Holders Per Hundred Residents, by Community, 2000 & 2010

Drift gillnet permit holders 

per hundred residents

Set gillnet permit holders 

per hundred residents

Total permit holders per 

hundred residents

134 
Salmon Fishery Earnings

Total Salmon Fishery Earnings, by Region

$0

$5,000

$10,000

$15,000

$20,000

$25,000

19841986198819901992199419961998200020022004200620082010

thousands of dollars

Dillingham Region

Bristol Bay Borough

Togiak-Manokotak Region

South Bristol Bay Region

Lake Region

Upper Nushagak Region

Figure 68. Total Salmon Fishery Earnings, by Region 

Per Capita Salmon Fishery Earnings, by Region

$0

$5,000

$10,000

$15,000

$20,000

$25,000

19841986198819901992199419961998200020022004200620082010

South Bristol Bay Region

Bristol Bay Borough

Togiak-Manokotak Region

Dillingham Region

Lake Region

Upper Nushagak Region

Figure 69. Per Capita Salmon Fisheries Earnings, by Region 

Figure 68 and Figure 69 show total and per capita salmon fishery earnings for Bristol Bay 

regions. Note that trends in fishery earnings for each region, as well as differences between 

regions, reflect the combined effects of three factors: (1) trends in overall catches, prices and 

value of the fishery; (2) trends in the number of permit holders in each region; and (3) trends in 

average catch shares of 

permit holders within each 

region. 

The combined effect of 

the decline in total value 

of the fishery as well as a 

decline in the number of 

permit holders was a 

dramatic decline in 

salmon fishery earnings 

and per capita earnings for 

all regions between the 

late 1990s and 2002. Note 

that this effect would 

appear even more 

dramatic if adjusted for 

the inflation which 

occurred during this 

period of time. 

Between 2002 and 2010, 

both earnings and per 

capita earnings have 

recovered significantly 

in all regions. However, 

except for the Bristol Bay 

Borough, per capita 

earnings were well below 

the levels of the 1980s, 

particularly for the Lake 

Region and Upper 

Nughagak Region. 

Just as there is wide 

variation between regions 

in per capita salmon 

fishery earnings, there is 

also wide variation 

between individual communities within regions and within the Bristol Bay watershed as a whole 

135 
(Table 39). In 2010, per capita salmon fishery earnings in some communities, such as Kokhanok 

and Newhalen, were less than $2000. Presumably they were much lower in other communities, 

such as Nondalton and Ekwok, for which earnings data were confidential due to the small 

number of permit holders. In other communities, such as Naknek, South Naknek, Iliamna and 

Port Heiden, they per capita earnings exceeded $6000. Thus there is clearly wide variation 

within the Bristol Bay watershed in the extent to which communities and regions participate in 

and benefit economically from Bristol Bay salmon fisheries. 

Table 39. Bristol Bay Salmon Fishery Earnings, by Community 

2000 2010 2000 2010 2000 2010

BRISTOL BAY BOROUGH $1,542 $4,240 $1,198 $3,172 $2,740 $7,411

King Salmon $1,334 $3,232 $657 $2,004 $1,991 $5,236

Naknek $1,652 $4,954 $1,357 $4,015 $3,009 $8,969

South Naknek $1,675 $4,093 $2,154 $2,892 $3,829 $6,986

DILLINGHAM CENSUS AREA $2,090 $2,252 $793 $1,289 $2,882 $3,540

Dillingham Region $2,244 $2,623 $716 $1,160 $2,960 $3,783

Aleknagik $2,399 $3,435 $591 $794 $2,990 $4,229

Clarks Point $4,385 $0 $901 $1,882 $5,286 $1,882

Dillingham $2,200 $2,620 $733 $1,177 $2,933 $3,798

Ekuk

Portage Creek

Togiak-Manokotak Region $2,285 $2,417 $1,418 $2,410 $3,703 $4,828

Manokotak $2,123 $1,576 $1,619 $3,500 $3,742 $5,075

Togiak $2,560 $3,091 $1,440 $2,039 $4,000 $5,131

Twin Hills $0 $0 $0 $0 $0 $0

Upper Nushagak Region $1,384 $1,002 $109 $0 $1,494 $1,002

Ekwok $900

Koliganek $1,649 $2,182

New Stuyahok $1,416 $745 $181 $1,597

LAKE AND PEN. BOROUGH $798 $1,237 $239 $367 $1,037 $1,604

Lake Region $377 $908 $110 $524 $487 $1,432

Igiugig

Iliamna $1,137 $4,127 $504 $1,975 $1,640 $6,102

Kokhanok $435 $0 $0 $842 $435 $842

Levelock $1,067 $2,743 $0 $0 $1,067 $2,743

Newhalen $309 $1,191 $0 $740 $309 $1,931

Nondalton

Pedro Bay

Port Alsworth

South Bristol Bay Region $3,129 $3,960 $947 $343 $4,076 $4,302

Egegik $4,261 $4,296 $1,911 $915 $6,173 $5,211

Pilot Point $2,316 $0 $1,058 $0 $3,375 $0

Port Heiden $2,998 $6,705 $0 $0 $2,998 $6,705

Ugashik

Chignik Region

Chignik

Chignik Lagoon

Chignik Lake

Ivanof Bay

Perryville

BRISTOL BAY, TOTAL (a) $1,709 $2,295 $730 $1,339 $2,439 $3,634

BRISTOL BAY, TOTAL (b) $1,813 $2,412 $774 $1,407 $2,587 $3,819

(a) Total includes the Chignik Region; (b) Total excludes the Chignik Region. Blank cells indicate that earnings data were 

confidential and not reported. Sources: U.S. Censuses, 2000 and 2010; CFEC.

Bristol Bay Salmon Fishery Per Capita Earnings, by Community, 2000 and 2010

Drift gillnet fishery per 

capita earnings

Set gillnet fishery per capita 

earnings

Total salmon fishing per 

capita earnings

136 
3.13 Economic Measures of the Bristol Bay Salmon Industry

There is no single or best economic measure for the Bristol Bay fishery. Which measure is 

appropriate depends upon the question being asked. 

For example, if we want to know how the Bristol Bay salmon fishery compares in scale with 

other fisheries, we should look at total harvests or ex-vessel or wholesale value. If we want to 

know how it affects the United States balance of payments, we should look at estimated net 

exports attributable to the fishery. If we want to know how much employment the industry 

provides for residents of the local Bristol Bay region, Alaska or the United States, we should 

look at estimated employment in fishing and processing for residents of these regions. If we 

want to know the net economic value attributable to the fishery, we should look at estimated 

profits of Bristol Bay fishermen and processors. These different measures vary widely in units, 

in scale, and how economically “important” they make the fishery appear. 

In this section, we summarize selected economic measures of the Bristol Bay commercial fishery 

for recent years. These include harvests, gross ex-vessel and wholesale value, estimated export 

value, direct employment and earnings in fishing and processing by region of residency, and 

limited entry prices and total estimated limited entry permit value. We present tables of each of 

these measures for the years 2000-2010. Where data are available, we present graphs for longer 

periods, showing dollar values in both nominal and real (inflation-adjusted) prices expressed in 

2010 dollars. Blank cells in the tables indicate that data were not available as of November 

2011. Refer to earlier sections in this report for more detailed discussions of each measure. 

Harvests

The Bristol Bay salmon fishery is a world-scale commercial salmon fishery. Between 2000 and 

2010, Bristol Bay averaged 60% of total Alaska sockeye salmon harvests (by volume), 45% of 

world sockeye salmon harvests, 18% of all Alaska wild salmon harvests, 7% of all world wild 

salmon harvests, and 2% of all world salmon production (wild and farmed combined). 

137 
Table 40. Economic Measures of Bristol Bay Salmon Industry: Sockeye Salmon Harvests 

Measure 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Avg.

Harvests

Millions of fish 21 14 11 15 26 25 28 30 28 31 29 23 11 - 31

Millions of pounds 125 96 65 93 152 155 165 173 160 183 170 140 65 - 183

Bristol Bay harvest

volume as a share of:

Alaska sockeye salmon 61% 56% 48% 50% 59% 58% 69% 62% 71% 71% 74% 62% 48% - 74%

World sockeye salmon 45% 40% 28% 38% 47% 47% 49% 47% 52% 55% 45% 28% - 55%

Alaska wild salmon (all species) 18% 12% 10% 13% 19% 16% 22% 18% 23% 25% 18% 10% - 25%

World wild salmon (all species) 7% 5% 4% 5% 8% 7% 8% 7% 9% 7% 7% 4% - 9%

World wild & farmed salmon

 (all species) 3% 2% 1% 2% 3% 3% 3% 3% 3% 3% 2% 1% - 3%

Sources: Alaska Department of Fish and Game, National Marine Fisheries Service, FAO.

Range

Economic Measures of the Bristol Bay Salmon Industry: Sockeye Salmon Harvests

138 

Bristol Bay Commercial Salmon Harvests

0

5

10

15

20

25

30

35

40

45

50

1975197719791981198319851987198919911993199519971999200120032005200720092011

Source: Commercial Fisheries Entry Commission; Alaska Department of Fish and Game

millions of fish

Other

Species

Sockeye

Figure 70. Bristol Bay Commercial Salmon Harvests
Gross Ex-Vessel Value and First Wholesale Value

During the period 2000-2010, Bristol Bay sockeye salmon harvests had an average annual real 

ex-vessel value to fishermen of $101 million (expressed in 2010 $). During this period of time, 

the value was generally increasing, from a low or $39 million in 2002 to $181 million in 2010. 

The real first wholesale value of salmon products processed from Bristol Bay sockeye salmon in 

Bristol Bay was more than twice as high as harvest value, averaging $234 million for the period 

2000-2010, and increasing from $124 million in 2002 to $390 million in 2010. 

Table 41. Economic Measures of Bristol Bay Salmon Industry: Sockeye Value

Measure 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Avg.

Ex-Vessel Value

($ mllions)

Nominal value (not inflation-adjusted) 80 40 32 48 76 95 109 116 117 144 181 94 32 - 181

Real value (inflation adjusted, 2010 $) 104 51 39 57 90 107 119 125 120 147 181 104 39 - 181

First wholesale value

Nominal value (not inflation-adjusted) 175 115 100 114 176 220 237 249 262 293 390 212 100 - 390

Real value (inflation adjusted, 2010 $) 227 144 124 137 206 250 261 268 270 298 390 234 124 - 390

Bristol Bay sockeye salmon

share of:

Alaska wild salmon ex-vessel value

(all species) 23% 14% 16% 19% 24% 24% 28% 24% 22% 29% 25% 23% 14% - 29%

World wild salmon ex-vessel value

(all species) * 12% 6% 6% 8% 13% 12% 13% 11% 10% 9% 10% 6% - 13%

United States fish & shellfish

landed value (all species) 2% 1% 1% 1% 2% 2% 2% 2% 2% 3% 3% 2% 1% - 3%

Rank of Naknek-King Salmon among 

U.S. ports in annual landed value 21 49 87 58 12 8 8 7 7 4 4 24 87 - 4

* Valued at average prices of Alaska wild salmon, by species.

Sources: Alaska Department of Fish and Game, National Marine Fisheries Service, FAO.

Economic Measures of the Bristol Bay Salmon Industry: Sockeye Salmon Ex-Vessel Value and First Wholesale Value

Range

139 
Ex-Vessel and Wholesale Value of Bristol Bay Sockeye Salmon

0

100

200

300

400

500

600

700

197519771979198119831985198719891991199319951997199920012003200520072009

millions of dollars

Real first

wholesale

value

Nominal

first

wholesale

value

Real exvessel

value

Nominal

ex-vessel

value

Source: Alaska Department of Fish and Game

Note: Real (inflationadjusted) values are 

expressed in 2010 

dollars

Figure 71. Ex-Vessel and Wholesale Value of Bristol Bay Sockeye Salmon

Between 2000 and 2010, Bristol Bay averaged 23% of the ex-vessel for all Alaska wild salmon, 

an estimated 10% of the harvest value of world wild salmon harvests, and 2% of the value of 

U.S. fish and shellfish landings of all species combined. 

As ex-vessel value increased dramatically between 2003 and 2010, the Bristol Bay port of 

Naknek-King Salmon rose from a rank of 87th to 4th among all U.S. ports in annual landed 

value (ex-vessel value, or value paid to fishermen, of fish landed in the port). 

Export Value of Bristol Bay Salmon Products

During the period 2000-2010, the value of Bristol Bay salmon products exported from the United 

States averaged $173 million for the years 2000-2010, and was $254 million in 2010. 

140 
Table 42. Economic Measures of the Bristol Bay Salmon Industry: Export Value. 

Measure 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Avg.

Nominal value of exports

(millions of dollars)

Canned 44 49 41 45 68 65 79 79 84 86 80 65 41 - 86

Frozen 8 3 11 10 13 10 5 8 8 8 8 8 3 - 13

Fresh 87 76 40 48 82 105 80 82 92 113 146 87 40 - 146

Roe 11 8 5 7 8 13 9 14 22 24 20 13 5 - 24

Total 150 137 97 111 172 193 173 183 206 230 254 173 97 - 254

Real value of exports

(millions of 2010 $)

Canned 57 62 50 54 80 74 86 85 86 87 80 73 50 - 87

Frozen 11 4 14 12 15 11 6 9 8 8 8 10 4 - 15

Fresh 112 96 49 58 96 119 88 89 94 115 146 97 49 - 146

Roe 14 11 6 8 9 14 10 15 23 24 20 14 6 - 24

Total 193 173 120 133 201 219 191 197 212 234 254 193 120 - 254

Economic Measures of the Bristol Bay Salmon Industry: Estimated Export Value of Bristol Bay Sockeye Salmon Products

Range

Note: The value of US exports of Bristol Bay sockeye salmon products was estimated as the total value of US sockeye salmon exports 

multiplied by the share of Bristol Bay sockeye in total Alaska sockeye salmon havests. The value of Bristol Bay sockeye salmon roe exports 

was assumed to be equal to the first wholesale value of sockeye salmon roe production. The data source for US exports was the National 

Marine Fisheries Serivce Foreign Trade in Fisheries Products website.

Estimated Value of US Exports of Bristol Bay Salmon Products

$0

$50,000

$100,000

$150,000

$200,000

$250,000

$300,000

199920002001200220032004200520062007200820092010

Source: NMFS trade data, ADFG COAR data for roe production value

thousands of dollars

Roe

Fresh

Canned

Frozen

Real total

export value

(2010 dollars)

Nominal total

export value

141 

Figure 72. Estimated Value of US Exports of Bristol Bay Salmon Products 
Employment

During the period 2001-2009, estimated peak employment in the Bristol Bay salmon industry 

averaged 6,656 fishermen and 3,255 processing workers, for average total peak employment of 

9,911. 

Because the fishery occurs almost entirely in June and July, estimated annual average 

employment is only about one-sixth as high as peak employment. During the period 2001-2009, 

estimated annual average employment averaged 1,093 in fishing and 535 in processing, for a 

total of 1,628 annual average jobs. 

During this period Bristol Bay salmon annual average fishing employment averaged 15% of 

Alaska statewide annual average fishing employment. Peak Bristol Bay commercial fishing 

employment averaged 33% of peak statewide Alaska commercial fishing employment. Put 

differently, in July—the busiest month for Alaska commercial fishing—about one third of all the 

people fishing commercially in Alaska were fishing in Bristol Bay. Bristol Bay fish processing 

accounted for an average of 14% of the individuals who worked in Alaska fish processing. 

Table 43. Economic Measures of the Bristol Bay Salmon Industry: Employment 

Measure 2001 2002 2003 2004 2005 2006 2007 2008 2009 Avg.

Estimated peak employment or

number of workers

Peak (July) fishing employment 7,098 5,514 6,465 6,513 6,750 6,936 6,891 6,969 6,768 6,656 5,514 - 7,098

Number of fish processing workers 2,862 2,273 2,484 3,474 3,272 2,940 3,512 3,952 4,522 3,255 2,273 - 4,522

Total 9,960 7,787 8,949 9,987 10,022 9,876 10,403 10,921 11,290 9,911 7,787 - 11,290

Estimated annual average

employment

Fishing 1,179 888 1,063 1,089 1,098 1,140 1,110 1,129 1,143 1,093 888 - 1,179

Fish processing 475 366 409 581 532 483 566 640 764 535 366 - 764

Total 1,654 1,254 1,472 1,669 1,631 1,623 1,675 1,769 1,907 1,628 1,254 - 1,907

Bristol Bay share of estimated Alaska 

total

Annual average fishing employment 15% 12% 14% 15% 15% 16% 15% 16% 16% 15% 12% - 16%

Peak (July) employment in fishing 33% 30% 33% 33% 33% 35% 34% 34% 34% 33% 30% - 35%

Number of fish processing workers 13% 11% 11% 16% 15% 13% 15% 17% 19% 14% 11% - 19%

Source: Alaska Department of Labor and Workforce Development, Research and Analysis Division.

Economic Measures of the Bristol Bay Salmon Industry: Employment

Range

142 
Limited Entry Permit Prices and Values

Limited entry permit prices provide a measure of the value to the marginal permit holder of the 

present and future right to participate in the fishery. Economic theory suggests that this will be 

the marginal permit holder’s present discounted present value of expected future profits from the 

fishery. During the period 2002-2010 Bristol Bay permit prices increased from $19,700 to 

$102,100 for drift gillnet permits and from $11,900 to $28,700 for set gillnet permits. The 

dramatic recovery in permit prices reflects a dramatic increase in profitability of the fishery and 

expectations of continued profitability. 

The total value of Bristol Bay permits—calculated as the number of permits multiplied by the 

permit price—provides an estimate of the total present discounted value of expected future 

profits from the fishery. During the period 2000-2010 the estimated total value of Bristol Bay 

permits (both fisheries combined) ranged from $48 million to $218 million. 

Multiplying the total value of a permit by the rate of return a permit holder demands on a permit 

investment provides a measure of the annual profit permit holders expect to earn. We do not 

know the rate of return demanded by permit holders. However, it is likely that it is between 5% 

and 20% (Hupert et al 1996). This suggests that in 2010 annual expected profits from Bristol 

Bay commercial fishing between $10.9 million and $43.7 million. Note that this does not 

include expected profits from fish processing. 

Table 44. Economic Measures of the Bristol Bay Salmon Industry: Permit Prices and 

Values. (Source: www.cfec.state.ak.us/bit/MNUSALM.htm ) 

Measure 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Avg.

Number of permanent permits 

issued

Drift gillnet fishery 1858 1,861 1,863 1,861 1,857 1,859 1,859 1,861 1,863 1,863 1,863 1,861 1,857 - 1,863

Set gillnet fishery 1,007 1,008 1,004 999 988 988 985 983 979 982 982 991 979 - 1,008

Total 1,007 2,869 2,867 2,860 2,845 2,847 2,844 2,844 2,842 2,845 2,845 2,683 1,007 - 2,869

Average nominal permit price 

($)

Drift gillnet fishery 80,500 34,700 19,700 29,300 37,000 51,200 75,000 79,400 89,800 78,300 102,100 61,545 19,700 - 102,100

Set gillnet fishery 32,400 25,300 11,900 12,600 14,700 15,100 22,400 24,000 27,400 28,200 28,700 22,064 11,900 - 32,400

Estimated total nominal value 

($ millions) (a)

Drift gillnet fishery 149.6 64.6 36.7 54.5 68.7 95.2 139.4 147.8 167.3 145.9 190.2 114.5 36.7 - 190.2

Set gillnet fishery 32.6 25.5 11.9 12.6 14.5 14.9 22.1 23.6 26.8 27.7 28.2 21.9 11.9 - 32.6

Total 182.2 90.1 48.6 67.1 83.2 110.1 161.5 171.4 194.1 173.6 218.4 136.4 48.6 - 218.4

Implied annual nominal 

profits ($ millions) (b) 

assuming permit holders 

demand a rate of return of:

5% 9.1 4.5 2.4 3.4 4.2 5.5 8.1 8.6 9.7 8.7 10.9 6.8 2.4 - 10.9

10% 18.2 9.0 4.9 6.7 8.3 11.0 16.1 17.1 19.4 17.4 21.8 13.6 4.9 - 21.8

15% 27.3 13.5 7.3 10.1 12.5 16.5 24.2 25.7 29.1 26.0 32.8 20.5 7.3 - 32.8

20% 36.4 18.0 9.7 13.4 16.6 22.0 32.3 34.3 38.8 34.7 43.7 27.3 9.7 - 43.7

Economic Measures of the Bristol Bay Salmon Industry: Permits Prices and Values

Range

(a) Calculated as average permit price x number of permanent permits issued. (b) Estimated total value x assumed rate of return demanded. Source: Commercial 

Fisheries Entry Commission, Salmon Basic Information Tables.

143 
Estimated Total Value of Bristol Bay Limited Entry Permits

0

100

200

300

400

500

600

700

800

900

19781980198219841986198819901992199419961998200020022004200620082010

Source: Estimated from CFEC Salmon Basic Information Tables

millions of dollars

Real

(2010)

dollars

Nominal

dollars

Figure 73. Estimated Total Value of Bristol Bay Limited Entry Permits

3.14 Bristol Bay Commercial Fisheries: Summary

The Bristol Bay sockeye salmon fishery is one of the world’s largest and most valuable wild 

salmon fisheries. Between 2006 and 2010, the Bristol Bay salmon industry averaged: 

• Annual harvests of 31 million salmon (including 29 million sockeye salmon) 

• 51% of world sockeye salmon harvests 

• Annual “ex-vessel” value to fishermen of $129 million 

• Annual first wholesale value after processing of $268 million. 

• 26% of the “ex-vessel” value to fishermen of the entire Alaska salmon harvest.

• Seasonal employment of more than 6800 fishermen and 3700 processing workers. 

Participation in the Bristol Bay salmon fishery is limited to holders of limited entry permits and 

their crew. There are approximately 1860 drift gillnet permits for fishing from boats and 

approximately 1000 set net permits for fishing from the shore. The driftnet fishery accounts for 

about 80% of the harvest. Most of the harvest is processed by about ten large processing 

144 
companies in both land-based and floating processing operations which employ mostly nonresident seasonal workers.

Bristol Bay Salmon Harvests

Sockeye salmon account for about 94% of the volume of Bristol Bay salmon harvests and an 

even greater share of the value. Total catches vary widely from year to year. Between 1980 and 

2010, Bristol Bay sockeye salmon harvests ranged from as low as 10 million fish to as high as 44 

million fish. Harvests can vary widely from year to year. Annual pre-season forecasts are 

subject to a wide margin of error. 

Bristol Bay Commercial Salmon Harvests

0

5

10

15

20

25

30

35

40

45

50

1975197719791981198319851987198919911993199519971999200120032005200720092011

Source: Commercial Fisheries Entry Commission; Alaska Department of Fish and Game

millions of fish

Other

Species

Sockeye

Figure 74. Bristol Bay Commercial Salmon Harvests

There are no formal long-term forecasts of future Bristol Bay harvests. The variability and 

uncertainty of annual salmon returns are important factors influencing how the fishery is 

managed and how fish are harvested, processed and marketed. 

The Bristol Bay commercial salmon fishery harvests salmon which spawn in and return to 

numerous rivers over a broad area. For management purposes, the fishery is divided into five 

fishing districts. Catches in each district vary widely from year to year and over longer time 

periods of time, reflecting wide variation in returns to river systems within each district (Table ). 

There is no obvious way to characterize the relative share of the Bristol Bay commercial salmon 

fishery attributable to particular river systems or to the individual streams and lakes that make up 

each river system. 

145 
Table 45. Distribution of Harvests for Bristol Bay Fishing Districts, 1986-2010 

Measure District Minimum

10th 

percentile Mean

90th 

percentile Maximum

Standard 

deviation

Naknek-Kvichak 0.6 2.7 8.0 15.3 20.3 5.0

Nushagak 1.7 2.7 5.1 8.0 11.1 2.3

Egegik 2.3 4.0 8.3 13.3 21.6 4.3

Ugashik 0.5 1.5 2.8 4.5 5.0 1.3

Togiak 0.1 0.2 0.5 0.8 0.8 0.2

Naknek-Kvichak 5% 18% 30% 46% 52% 11%

Nushagak 9% 10% 22% 32% 45% 10%

Egegik 16% 21% 34% 48% 62% 11%

Ugashik 3% 7% 11% 15% 32% 5%

Togiak 0% 1% 2% 4% 6% 1%

Source: Alaska Department of Fish and Game, Bristol Bay Annual Management Reports

Share of total 

harvests (%)

Distribution of Harvests for Bristol Bay Fishing Districts, 1986-2010

Harvests 

(millions of 

fish)

Currently there is particular interest in the significance of fisheries resources of river systems in 

the Nushagak and Kvichak districts, because of potential future resource development in these 

watersheds. Over the period 1986-2010, the Naknek-Kvichak catches ranged from as low as 5% 

to as high as 52% of total Bristol Bay catches; Nushagak district catches ranged form as low as 

9% to as high as 45% of total Bristol Bay catches. For most of the past decade, the combined 

Nushagak and Naknek-Kvichak districts have accounted for about 60% of the total Bristol Bay 

commercial sockeye harvest.

In general, a decline in salmon returns associated with any particular river system might have a 

relatively small effect on average catches over a long period of time in the Bristol Bay fishery. 

But it might have a much larger effect on catches in those years when the river system would 

have contributed a relatively larger share of total harvests. For example, if a particular river 

system accounts for an average of 1% of the return on average but 10% of the return in some 

years, the loss of that system would reduce catches by only 1% on average but would reduce 

catches in some years by 10%. Put differently, a decline in catches from any particular river 

system would increase the variability in catches in the fishery and the overall economic risk 

associated with the fishery. 

An inherent question here is whether 51% of the world’s sockeye are caught in Bristol Bay 

because that is where the fish are or because that is where the boats go. One could envision 

circumstances where the boats prefer to go to areas that are more safe/convenient (more 

sheltered, closer to port, etc.) and there are enough fish available there that they don’t need to go 

elsewhere. It is not clear if severe degradation of the Bristol Bay commercial fishery may

necessarily result in the total loss of 51% of the world’s harvest, but rather displace it to other 

areas (possibly even in another area of AK). However, such changes in the Alaska and Bristol 

Bay fishery could result in more dangerous working conditions, negatively affect Alaska native 

participation in the fishery; and will change the Alaska commercial fishery market structure. 

Evaluating such impacts is beyond the scope of this baseline assessment.

146 
Bristol Bay Salmon Production and Markets 

Most Bristol Bay salmon is processed into either frozen or canned salmon. Traditionally most 

frozen salmon has been frozen headed and gutted (H&G) for further processing elsewhere, 

particularly in Japan. However, in recent years production of frozen salmon fillets in the Bristol 

Bay region has increased. 

Formerly almost all Bristol Bay frozen salmon was exported to Japan as frozen headed and 

gutted salmon. Over the past decade exports of frozen head and gutted salmon to Japan have 

declined while exports have increased to Europe and to China (for reprocessing into fillets). 

Most Bristol Bay canned salmon is exported, primarily to the United Kingdom and Canada. 

Estimated Shares of Bristol Bay Sockeye Salmon Production, 2010

Canned

talls

6% Canned

halves

14%

Frozen H&G

56%

Frozen

fillets

12%

Fresh

10%

Roe

2%

Canned

20%

Frozen

68%

Source: Estimated 

from ADFG COAR 

data and ADOR 

Annual Alaska Salmon 

Price Report data

Figure 75. Estimated Shares of Bristol Bay Sockeye Salmon Production, 2010 

147 
Bristol Bay Salmon Prices and Value 

Ex-vessel prices paid to fishermen and first wholesale prices received by processors in the 

Bristol Bay salmon fishery have varied widely over the past three decades, reflecting dramatic 

changes in world salmon markets during this period. 

Average Ex-Vessel and Wholesale Prices of Bristol Bay Sockeye Salmon

$0.00

$1.00

$2.00

$3.00

$4.00

$5.00

$6.00

19841986198819901992199419961998200020022004200620082010

Source: Alaska Department of Fish and Game

$/lb

Frozen

wholesale

price

Canned

wholesale

price

Ex-vessel

price

Figure 76. Average Ex-Vessel and Wholesale Prices of Bristol Bay Sockeye Salmon

Strong Japanese demand from frozen sockeye salmon drove a sharp rise in Bristol Bay salmon 

prices during the 1980s. Competition from rapidly increasing farmed salmon production drove a 

protracted and dramatic decline in prices between 1988 and 2001, which led to an economic 

crisis in the industry. Growing world salmon demand, a slowing of farmed salmon production 

growth, diversification of Bristol Bay salmon products and markets, and improvements in quality 

have driven a strong recovery in prices over the past decade. Many other factors, such as 

changes in wild salmon harvests, exchange rates, and global economic conditions have also 

affected prices. In general, changes in ex-vessel prices paid to fishermen have reflected changes 

in first wholesale prices paid to processors.

Changes in prices, harvests and production have combined to drive dramatic changes in the exvessel and first wholesale value of Bristol Bay salmon over the past three decades . Adjusted for 

inflation (expressed in 2010 $), the real ex-vessel value paid to fishermen fell from $359 million 

in 1988 to $39 million in 2002, and rose to $181 million in 2010. The real first wholesale value 

of Bristol Bay salmon production fell from $616 million in 1988 to $124 million in 2002, and 

then rose to $390 million in 2010. 

148 
Ex-Vessel and First Wholesale Value of Bristol Bay Sockeye Salmon

Harvests and Production, 1980-2010

0

100

200

300

400

500

600

700

19841986198819901992199419961998200020022004200620082010

millions of dollars

Real first

wholesale value

(2010$)

Nominal first

wholesale value

Real ex-vessel

value (2010 $)

Nominal exvessel value

Source: CFEC, ADFG

Figure 77. Ex-Vessel and First Wholesale Value 1980-2010

Bristol Bay Salmon Industry Employment 

The number of Bristol Bay permits fished each year has varied over time depending on economic 

conditions in the fishery. Over the past decades, between about 1200 and 1500 drift gillnet 

permits and between about 700 and 900 set gillnet permits were fished each year. 

On average, for each permit fished, about three people were engaged in fishing (the permit 

holder and two crew members). The estimated total number of people working in fishing during 

the Bristol Bay season ranged from about 5500 to 7100. Because most of the commercial 

harvest occurs within a period of a few weeks in late June and early July, annual average 

employment in the fishery is much smaller than peak employment, ranging from about 900 to 

1200 over the past decade. 

Over the past decade Bristol Bay fish processors employed between about 2300 and 4500 

workers, with annual average employment ranging from about 360 to 760. Together, about 

7,800-11,300 people worked seasonally in fishing and processing, for combined annual average 

employment of 1200 to 1900. 

149 
Geographic Distribution of Bristol Bay Salmon Fishery Participation and Earnings 

Local residents of the Bristol Bay region account for a relatively small and declining share of 

employment and earnings in the Bristol Bay salmon industry. Non-Alaska residents account for 

a relatively large and growing share of employment and earnings. 

Table 46. Geographic Distribution of Bristol Bay Salmon Industry Employment and 

Earnings.

Bristol Bay 

region 

residents

Other 

Alaska 

residents

Residents 

of other 

states or 

countries Total

Bristol Bay 

region 

residents

Other 

Alaska 

residents

Residents 

of other 

states or 

countries

Permit holders, drift gillnet fishery 383 471 1,009 1,863 21% 25% 54%

Permit holders, set gillnet fishery 353 311 317 982 36% 32% 32%

Permit holders, total 736 782 1,326 2,845 26% 27% 47%

Earnings, drift gillnet fishery (2007) ($000) $14,273 $25,020 $58,821 $98,115 15% 26% 60%

Earnings, set gillnet fishery (2007) ($000) $6,989 $6,071 $6,840 $19,900 35% 31% 34%

Earnings, total (2007) ($000) $21,262 $31,091 $65,661 $118,014 18% 26% 56%

Processing workers (2009) 76 529 3,916 4,521 2% 12% 87%

Processing workers' earnings (2009) ($000) $1,000 $3,025 $27,162 $31,187 3% 10% 87%

Sources: Gho, Marcus, K. Iverson, C. Farrington, and N. Free-Sloan, "Changes in the Distribution of Alaska's Commercial 

Fisheries Entry Permits, 1975 – 2010," CFEC Report 11-3N (2011); Permit holder earnings: Iverson, Kurt, "Permit Holdings, 

Harvests, and Estimated Gross Earnings by Resident Type in the Bristol Bay Salmon Gillnet Fisheries," CFEC Rpt 09-1N (2009); 

Processing workers and earnings: Alaska Department of Labor and Workforce Development estimates, 

http://labor.alaska.gov/research/seafood/seafoodbristol.htm. 

Measure by Residency Share of Total

Geographic Distribution of Bristol Bay Salmon Industry Employment and Earnings: Selected Measures

Measure

Local Bristol Bay Resident Share of the Bristol Bay Salmon Fisheries: 

Selected Measures

0%

10%

20%

30%

40%

50%

19781980198219841986198819901992199419961998200020022004200620082010

Source: CFEC, Changes in the Distribution of Alaska's Commercial Fisheries Entry Permits,

1975-2010 

Total

permits

held*

Total

earnings*

Processing

employment

*Shares for 

both fisheries 

combined.

Figure 78. Local Bristol Bay Resident Share of Bristol Bay Salmon Fisheries.

150 
This does not mean, of course, that the Bristol Bay salmon fishery is unimportant as a source of 

jobs or income for local residents. It remains very important—but not as important as it would 

be if all the jobs were held by local residents and all the income were earned by local residents.

A different perspective is that the Bristol Bay fishery is not just economically important for a 

remote region of southwestern Alaska. Rather, it is of major economic importance for other 

parts of Alaska and other states, particularly the Pacific Northwest. Thousands of residents of 

other parts of Alaska and other states work in and earn significant income from participating in 

Bristol Bay fishing and processing. 

Distribution of Salmon Permits and Earnings within the Bristol Bay Region

Within the Bristol Bay region, there is wide variation in the extent to which residents of different 

communities participate in and derive income from the Bristol Bay salmon fisheries. In 2010, 

the number of permits held per 100 residents ranged from as high as 16 in the Bristol Bay 

Borough to as low as 5 in the Upper Nushagak Region. Per capita salmon fishery earnings 

ranged from more than $7000 in the Bristol Bay Borough to only $1000 in the Upper Nushagak 

Region. 

Table 47. Relative Indicators of 2010 Salmon Fishery Participation and Earnings.

Drift gillnet 

fishery

Set gillnet 

fishery

Combined 

fisheries

Drift gillnet 

fishery

Set gillnet 

fishery

Combined 

fisheries

Bristol Bay Borough 6 10 16 $4,240 $3,172 $7,411

Togiak-Manokotak Region 6 7 13 $2,417 $2,410 $4,828

South Bristol Bay Region 10 6 15 $3,960 $343 $4,302

Dillingham Region 5 4 9 $2,623 $1,160 $3,783

Lake Region 3 3 6 $908 $524 $1,432

Upper Nushagak Region 5 1 5 $1,002 * $1,002

Bristol Bay Watershed 5 5 10 $2,412 $1,407 $3,819

Relative Indicators of 2010 Salmon Fishery Participation and Earnings, Bristol Bay Watershed Regions

Number of permit holders per 100 residents Per capita salmon fishery earnings

* Confidential. Sources: U.S. Censuses, 2000 and 2010; CFEC.

Economic Measures of the Bristol Bay Salmon Industry

There are many potential economic measures of the Bristol Bay salmon industry. Which 

measure is most useful depends upon the question being asked. For example, if we want to know 

how the Bristol Bay salmon fishery compares in scale with other fisheries, we should look at 

total harvests or ex-vessel or wholesale value. If we want to know how it affects the United 

States balance of payments, we should look at estimated net exports attributable to the fishery. If 

we want to know how much employment the industry provides for residents of the local Bristol 

Bay region, Alaska or the United States, we should look at estimated employment in fishing and 

151 
processing for residents of these regions. If we want to know the net economic value attributable 

to the fishery, we should look at estimated profits of Bristol Bay fishermen and processors. 

These different measures vary widely in units, in scale, and how economically “important” they 

make the fishery appear.

Table 48. Selected Economic Measures of the Bristol Bay Salmon Industry, 2000-2010. 

Measure 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Avg.

Sockeye Salmon Havests

Millions of fish 21 14 11 15 26 25 28 30 28 31 29 23 11 - 31

Millions of pounds 125 96 65 93 152 155 165 173 160 183 170 140 65 - 183

Bristol Bay harvest

volume as a share of:

Alaska sockeye salmon 61% 56% 48% 50% 59% 58% 69% 62% 71% 71% 74% 62% 48% - 74%

World sockeye salmon 45% 40% 28% 38% 47% 47% 49% 47% 52% 55% 45% 28% - 55%

Alaska wild salmon (all species) 18% 12% 10% 13% 19% 16% 22% 18% 23% 25% 18% 10% - 25%

World wild salmon (all species) 7% 5% 4% 5% 8% 7% 8% 7% 9% 7% 7% 4% - 9%

World wild & farmed salmon

 (all species) 3% 2% 1% 2% 3% 3% 3% 3% 3% 3% 2% 1% - 3%

Gross Value ($ mllions)

Ex-vessel value 80 40 32 48 76 95 109 116 117 144 181 94 32 - 181

First wholesale value 175 115 100 114 176 220 237 249 262 293 390 212 100 - 390

Total value of US exports of 

Bristol Bay salmon products 150 137 97 111 172 193 173 183 206 230 254 173 97 - 254

Workers

Peak (July) fishing employment 7,098 5,514 6,465 6,513 6,750 6,936 6,891 6,969 6,768 6,656 5,514 - 7,098

Number of fish processing 

workers 2,862 2,273 2,484 3,474 3,272 2,940 3,512 3,952 4,522 3,255 2,273 - 4,522

Total 9,960 7,787 8,949 9,987 10,022 9,876 10,403 10,921 11,290 9,911 7,787 - 11,290

Estimated annual average

employment

Fishing 1,179 888 1,063 1,089 1,098 1,140 1,110 1,129 1,143 1,093 888 - 1,179

Fish processing 475 366 409 581 532 483 566 640 764 535 366 - 764

Total 1,654 1,254 1,472 1,669 1,631 1,623 1,675 1,769 1,907 1,628 1,254 - 1,907

Average permit price ($ 000)

Drift gillnet fishery 81 35 20 29 37 51 75 79 90 78 102 62 20 - 102

Set gillnet fishery 32 25 12 13 15 15 22 24 27 28 29 22 12 - 32

Estimated total permit value ($ 

millions)

Drift gillnet fishery 149.6 64.6 36.7 54.5 68.7 95.2 139.4 147.8 167.3 145.9 190.2 114.5 36.7 - 190.2

Set gillnet fishery 32.6 25.5 11.9 12.6 14.5 14.9 22.1 23.6 26.8 27.7 28.2 21.9 11.9 - 32.6

Total 182.2 90.1 48.6 67.1 83.2 110.1 161.5 171.4 194.1 173.6 218.4 136.4 48.6 - 218.4

Selected Economic Measures of the Bristol Bay Salmon Industry, 2000-2010

Range

Economic impacts and net economic value of the Bristol Bay salmon industry are not necessarily 

proportional to harvests or gross value, particularly in the short run. Put differently, economic 

impacts and net economic value are disproportionately affected by changes in value. A 1% 

change in harvests results in less than a 1% change in fishing and processing employment—

particularly if it is unexpected. In contrast, because many of the costs of the fishery are fixed, a 

1% change in value results in more than a 1% change in profits and net economic value. For 

these reasons, short term changes in future fish harvests would likely have less-than-proportional 

or greater-than-proportional economic effects. Longer-term changes in fish harvests would tend 

to have proportional economic effects as the scale of the fishing and processing industry changed 

over time. 

152 
Future Economic Importance of the Bristol Bay Salmon Industry

It is impossible to predict the future economic importance of the Bristol Bay salmon industry 

with certainty. Historically, catches, prices and value have varied dramatically both from year to 

year and over longer-term periods of time. They are likely to continue to vary.

No particular recent year or period is necessarily a good indicator of future Bristol Bay catches 

and value. However, it seems likely that future catches, prices and values will fall within the 

wide range experienced between 1980 and 2010. 

Table 49. Distribution of Selected Economic Measures for the Bristol Bay Commercial 

Salmon Fishing Industry, 1980-2010 

Measure Minimum

10th 

percentile Mean

90th 

percentile Maximum

Standard 

deviation

Total sockeye salmon harvest (million fish) 10.0 14.0 24.8 35.2 44.2 8.8

Total sockeye salmon harvest (million pounds) 57.7 87.8 145.6 195.5 243.6 48.8

Ex-vessel price paid to fishermn ($/lb) $0.53 $0.61 $1.31 $2.18 $3.79 $0.70

Average first wholesale price, frozen H&G salmon ($/lb) $1.48 $1.64 $2.18 $2.73 $3.77 $0.54

Average first wholesale price,canned salmon ($/lb) $2.21 $2.32 $3.05 $3.86 $5.72 $0.76

Total ex-vessel value ($ millions) 39.3 89.5 184.0 311.8 359.2 90.5

Total first wholesale value ($ millions) 123.9 160.8 324.8 486.2 616.5 131.2

Drift gillnet permit price ($ thousands) 24.3 43.6 180.5 311.6 434.7 106.1

Set gillnet permit price ($ thousands) 14.7 17.2 54.2 83.6 107.2 27.0

Estimated total permit value ($ millions) 60.0 113.3 375.6 623.6 879.5 212.0

Distribution of Selected Economic Measures for the Bristol Bay Commercial Salmon Fishing Industry, 1980-2010

Note: All prices and values are adjusted for inflation to real 2010 dollars. 10th and 90th percentiles are interpolated. Estimated 

total permit value calculated by mulltiplying average permit prices by the number of permanent permits renewed. First wholesale 

prices and values are for the years 1984-2010. Data are from Alaska Department of Fish and Game and Commercial Fisheries 

Entry Commission.

3.15 Appendix: Data Sources

A rich variety of data exists for the Bristol Bay commercial salmon fishery. However, the data 

can be difficult and confusing to work with, for a number of reasons. Some data are not 

published, and are available only upon request from Alaska state government agencies. Many 

data series are available only for limited periods of time: some have been discontinued and are 

not available for recent years; others have been collected or published only beginning relatively 

recently and are not available for earlier years. Many data series are inconsistent: reports 

published by the same agency in different years may provide different data for the same series. 

Preliminary data (particularly for prices and values) are often revised later, sometimes 

substantially. Some kinds of data are confidential except when aggregated for minimum 

threshold numbers of permit holders, processors or other firms. Some kinds of data are 

proprietary (particularly price data gathered by private market information services). Most 

importantly, what data mean, how they were collected or estimated, and how reliable they are is 

often unclear. For all these reasons, pulling together the variety of data presented in this report 

153 
was a significant task, building on a variety of research conducted over many years, much of it 

devoted to finding data sources and learning what they meant (and didn’t mean). 

The purpose of this appendix is to document, as best practical, the sources for the analysis, both 

for the benefit of readers and for other researchers. The appendix provides details on the data 

sources for all of the text references, graphs and tables in this report, except where the source is 

obvious or reported in detail in the text. 

This section begins with a description of the major data sources for this report (those used 

multiple times), listed in alphabetical order of the names used to refer to them. 

This section then describes the sources for all data provided in the report, text, figures and tables, 

except where the source information is provided in the report or is otherwise clear. These are 

listed in the chronological order in which they appear in the report. 

The final section of the appendix provides the price index data used to convert selected prices 

and values in the report from “nominal” dollars (not adjusted for inflation) to “real” dollars 

(adjusted for inflation).

Researchers wishing more detailed information about data sources may contact Gunnar Knapp at 

Gunnar.Knapp@uaa.alaska.edu or 907-786-7717. 

Major Data Sources for This Report

Below are descriptions of the major data sources used in this report (those used multiple times), 

listed in alphabetical order of the names used to refer to them (shown in bold font). Website 

addresses were current as of October 2011 for all data found online.

ADFG Annual Run Forecasts and Harvest Projections. Each year the Alaska Department of 

Fish and Game publishes a report on “Run Forecasts and Harvests Projections for Alaska Salmon 

Fisheries” for the current year, which also includes a review of the salmon fisheries for the 

previous season. This report includes forecasts for the coming season of commercial sockeye 

salmon harvests in Bristol Bay. The reports for the most recent years are available at the 

“Commercial Salmon Fisheries Forecasts” website:

http://www.adfg.alaska.gov/index.cfm?adfg=commercialbyfisherysalmon.salmonforecast 

Reports for earlier years available on the Alaska Department of Fish and Game “Fishing and 

Subsistence” Publications Searchable Database at: 

http://www.adfg.alaska.gov/sf/publications/

To find them, search for the following: Report = All Reports; Field = Title; Operator = 

Contains; Search String = Forecast. Then scroll through several pages out output until you 

come to “Commercial Fisheries Reports.”

154 
ADFG Bristol Bay Annual Management Reports. These are detailed reports for each salmon 

season compiled by Alaska Department of Fish and Game Division of Commercial Fisheries 

Bristol Bay area management staff. Each report also contains an extensive data appendix with 

dozens of tables of catches and escapements by district, day, gear type, etc. The reports are 

available on the Alaska Department of Fish and Game “Fishing and Subsistence” Publications 

Searchable Database at: 

http://www.adfg.alaska.gov/sf/publications/

To find them, search for the following: Report = Commercial Fisheries Annual Management 

Reports; Field = Title; Operator = Contains; Search String = Bristol Bay.

ADFG Bristol Bay Salmon Season Summaries. These are news releases prepared by compiled 

by Alaska Department of Fish and Game Division of Commercial Fisheries Bristol Bay area 

management staff after each Bristol Bay salmon season after each salmon season which 

summarize catches and preliminary ex-vessel price information. The news releases are available 

on the ADFG Bristol Bay website at: 

http://www.cf.adfg.state.ak.us/region2/finfish/salmon/salmhom2.php

ADFG Commercial Operator Annual Report (COAR) Data. In April of every year, all 

Alaska fish processors are required to submit “Commercial Operator Annual Reports” to the 

Alaska Department of Fish and Game. In these reports they are required to report the total 

volume of fish purchased, by species and area; the total amount paid for fish purchased, by 

species and area; the total volume (weight) of production, by product, species and area; and the 

total first wholesale value of production. Information about the COAR reporting forms is at: 

http://www.adfg.alaska.gov/index.cfm?adfg=fishlicense.coar

The COAR data are not posted on the internet or published regularly by ADF&G (which is 

unfortunate), but are available by special request from ADF&G. The data used for this report 

were provided on August 2, 2011 to Gunnar Knapp and were saved as Excel file “Statewide and 

regional COAR production 1984-2011 provided by ADFG 8-2-11.xls.” Average “first wholesale 

prices” were calculated by dividing first wholesale value by production volume. 

ADFG Alaska Commercial Salmon Harvests and Ex-vessel Values Reports. These reports 

provide summary annual data for each of 11 Alaska salmon harvest areas. The data include 

average fish weight, average price per pound, numbers of fish, harvest volume in pounds, and 

estimated value in dollars. Prices for the most recent year are generally preliminary estimates 

based on fish tickets and reports from area managers. Prices for earlier years are generally based 

on “Commercial Operators Annual Report and area staff reports.” The reports are available at: 

http://www.adfg.alaska.gov/index.cfm?adfg=commercialbyfisherysalmon.salmoncatch

ADFG Salmon Ex-Vessel Price Time Series by Species 1984-2008. This is a two-page table 

of ex-vessel prices by species, 1984-2008, for the following areas: Cook Inlet, Kodiak, Alaska 

155 
Peninsula, Bristol Bay, Prince William Sound, Southeast, and Statewide. Original source is cited 

as the Commercial Operator Annual Reports database. 

http://www.cf.adfg.state.ak.us/geninfo/finfish/salmon/catchval/blusheet/84-08exvl.pdf 

ADLWD Bristol Bay Region Fishing and Seafood Industry Data. The Alaska Department of 

Labor and Workforce Development (ADLWD) Research and Analysis Division posts a variety 

of economic information for the Bristol Bay Seafood Industry on its “Bristol Bay Region Fishing 

and Seafood Industry Data” website at: 

http://labor.alaska.gov/research/seafood/seafoodbristol.htm. 

ADOR Annual Salmon Price Reports. Every year, “large” Alaska salmon processors (those 

with sales exceeding 1 million pounds in the previous calendar year) are required to report sales 

volumes and first wholesale values for major salmon product categories to the Alaska 

Department of Revenue. Annual statewide summary reports of these data are available on the 

Alaska Department of Revenue’s Tax Division Reports website at:

http://www.tax.alaska.gov//programs/reports.aspx 

Once on this page, click on “Alaska Salmon Price/Production.” Note that the “Annual Salmon 

Price Reports” differ from (and sometimes are inconsistent with the “Annual Salmon Production 

Reports” and “Monthly Salmon Price Reports” which are also available at the same website. 

ADOR Canned Salmon Wholesale Price Reports. For many years prior to 2001, the Alaska 

Department of Revenue prepared “Canned Salmon Average Wholesale Reports.” These reported 

monthly statewide average prices for canned salmon, by species, compiled from information 

reported by Alaska salmon processors. The University of Alaska Anchorage Institute of Social 

and Economic Research (ISER) maintains a collection of these reports beginning with the period 

April 1-September 30, 1983. 

ADOR Monthly Salmon Price Reports. Every four months, large Alaska salmon processors 

(those with sales exceeding 1 million pounds in the previous calendar year) are required to 

submit salmon price reports to the Alaska Department of Revenue for the following four-month 

periods: January-April, May-August , and September-December. 

The reports include sales volumes and first wholesale values for major salmon product, by area 

and month. Summaries of the data from these reports, for each four-month period, are available 

on the Alaska Department of Revenue’s Tax Division Reports website at:

http://www.tax.alaska.gov//programs/reports.aspx. 

Once at this page, click on “Alaska Salmon Price/Production.” Note that these “Monthly Salmon 

Price Report” differ from (and sometimes are inconsistent with the “Annual Salmon Price 

Reports” and the “Annual Salmon Production Reports” which are also available at the same 

website. Data are not reported for product-area-month combinations for which fewer than three 

processors reported sales. 

156 
CFEC Basic Information Tables. The Commercial Fisheries Entry Commission (CFEC) posts 

“Basic Information Tables” for each Alaska salmon fishery on its website at: 

http://www.cfec.state.ak.us/bit/MNUSALM.htm

These tables provide a useful summary of trends since 1975 in each salmon fishery for numbers 

of permits issued/renewed, numbers of permits fished, total pounds harvested, average pound 

harvested, gross earnings, average earnings, and average annual permit prices. The most recent 

data currently available are for 2010. 

CFEC Data for Alaska Salmon Harvests 1980-2005. 1980-2005: CFEC Alaska Salmon 

Summary Data 1980-2005 061113. These are Commercial Fisheries Entry Commission data for 

Alaska commercial salmon harvest (number of fish, pounds, earnings, and price), by species, for 

the years 1980-2005. This file was prepared by the Commercial Fisheries Entry Commission on 

March 31, 2005, in response to a request by Professor Gunnar Knapp of the University of Alaska 

Anchorage Institute of Social and Economic Research (ISER). The data was provided as an 

Excel file named SWPrices.xls, containing the worksheet of this file named "Original data." 

Professor Knapp maintains a copy of the file named “CFEC_Alaska_Salmon_Summary_Data 

_1980-2005.xls.” The data were calculated from CFEC fish ticket database. The harvest and 

earnings figures include set and drift gill net, test fishing, confiscated and educational permit 

harvests, and any other harvest where the product was sold. 

CFEC Data for Bristol Bay Salmon Harvests 1975-2003. These are Commercial Fisheries 

Entry Commission data for Bristol Bay commercial salmon harvests for the years 1975-2003, 

provided by Kurt Iverson, June 9, 2004, as file BBayEarnHarv1.xls. The data were calculated 

from CFEC fish ticket database. The harvest and earnings figures include set and drift gill net, 

test fishing, confiscated and educational permit harvests, and any other harvest where the product 

was sold.

CFEC Quartile Tables. The Commercial Fisheries Entry Commission (CFEC) posts annual 

“Quartile Tables” for each Alaska salmon fishery on its website at: 

http://www.cfec.state.ak.us/quartile/mnusalm.htm

These tables show the number of permit holders and average earnings per permit holder in each 

“quartile group”—calculated by ranking permit holdings in each year by earnings, and then 

dividing them into four “quartile” groups with equal total earnings. The first quartile has the 

smallest number of permit holders with the highest average earnings; the fourth quartile has the 

highest number of permit holders with the lowest average earnings.

CFEC Permit and Fishing Activity Data. The Commercial Fisheries Entry Commission 

(CFEC) posts annual data on permit and fishing activity by year, state, census area and Alaska 

city on its website at:

http://www.cfec.state.ak.us/fishery_statistics/earnings.htm

157 
For each state, census area and city in which permit holders reside, and for each fishery for 

which residents held permits, data include the number of permits issued, number of permit 

holders, number of permits with recorded landings, total pounds landed and estimated gross 

earnings. Earnings data are confidential for fisheries in which fewer than four permit holders in a 

census area or community had landings. 

FAO FishstatJ Database. FAO FishstatJ is software for fishery statistical time series developed 

by the Food and Agricultural Organization of the United Nations (FAO) Fisheries and 

Aquaculture Department, based in Rome. The software is designed to be used with global 

datasets for capture (wild) fisheries catches and aquaculture production, by species, country and 

year. The software and the global datasets can be downloaded from the FAO Fisheries and 

Aquaculture Department website at:

http://www.fao.org/fishery/statistics/software/fishstatj/en

NMFS Commercial Fishery Landings Database. The National Marine Fisheries Service 

(NMFS) Office of Science and Technology maintains an online database of US Commercial 

Fishery Landings (volume and value) by state, species and year. Customized datasets for Alaska 

and other states may be downloaded from NMFS Commercial Fishery Landings webite at: 

http://www.st.nmfs.noaa.gov/st1/commercial/index.html

NMFS Foreign Trade in Fisheries Products Data. The National Marine Fisheries Service 

posts very detailed data online about U.S. exports and imports of fisheries products at:

http://www.st.nmfs.noaa.gov/st1/trade/

The export data in this report were calculated from the “Monthly Trade Data by Product, 

Country/Association” option at this website.

NMFS Major Ports Data. The National Marine Fisheries Service publishes an annual report 

entitled Fisheries of the United States which provides a wide variety of useful data on United 

States fisheries. A regular table in this report (on page 7 in recent years), entitled “Commercial 

Fishery Landings and Value at Major U.S. Ports,” lists the value and volume of landings for the 

top 50 United States ports (ranked by value). The Fisheries of the United States reports are 

available at:

http://www.st.nmfs.noaa.gov/st1/publications.html

Data Sources for Report Text, Figures and Tables

Below are descriptions of the sources for data provided in the report text, figures and tables. 

Except where text sources are given below, the data in the text is from the same sources as the 

adjacent figures and tables in the same sections of the report. Except where text sources are 

given below, all of the material discussed in the “Overview” and “Summary” sections of the 

report is discussed in greater detail in corresponding sections of the report. Refer to the body of 

158 
the report for more details as well as sources for information presented in the “Overview” and 

“Summary” sections. 

Page 52. “Annual harvests of 31 million salmon . . .” Source: ADFG Alaska Commercial 

Salmon Harvests and Exvessel Values Reports.

Page 52. “51% of world sockeye salmon harvests.” Source: See discussion below of sources 

for Figure 22 (World Sockeye Supply). 

Page 52. “Annual ex-vessel” value to fishermen of $129 million.” Source: ADFG Alaska 

Commercial Salmon Harvests and Exvessel Values Reports.

Page 52. “Annual first wholesale value . . . of $268 million.” ADFG Commercial Operator 

Annual Report (COAR) Data.

Page 52. “26% of the ex-vessel value . . .“ Source: ADFG Alaska Commercial Salmon 

Harvests and Exvessel Values Reports.

Page 52. “Seasonal employment of more than 6800 fishermen and 3700 processing workers.” 

Source: See sources for Table 36, page 112. 

Figure 11. Bristol Bay Commercial Salmon Harvests. Sources: 1975-2003: CFEC Data for 

Bristol Bay Salmon Harvests; 2004-2010: ADFG Alaska Commercial Salmon Harvests and 

Exvessel Values Reports; 2011: ADFG 2011 Bristol Bay Salmon Season Summary (9/26/2011). 

Page 57. “The average weight of a Bristol Bay sockeye salmon is typically about 6 pounds. . . . 

average weights varied from as low as 5.3 pounds to as high as 6.7 pounds.” Data sources are 

the same as for Figure 11. 

Figure 12. Bristol Bay Fishing Districts. Average annual harvests for the years 1991-2010 were 

calculated from the same data used for Figure 13. 

Figure 13. Bristol Bay Commercial Sockeye Salmon Harvests, by District. Sources: 1986-1989: 

ADFG Bristol Bay Annual Salmon Management Report, 2006, Appendix A3.–Sockeye salmon 

commercial catch by district, in numbers of fish, Bristol Bay, 1990–2010; 1990-2010: ADFG 

Bristol Bay Annual Salmon Management Report, 2010, Appendix A3.–Sockeye salmon 

commercial catch by district, in numbers of fish, Bristol Bay, 1990–2010. 2011: ADFG Bristol 

Bay Salmon Season Summary, 2011. 

Figure 14. Share of Bristol Bay Commercial Sockeye Salmon Harvest, by District. Same 

sources as for Figure 13. 

Figure 15. Naknek-Kvichak District Sockeye Salmon Harvests, by River of Origin. Compiled 

from ADFG Bristol Bay Annual Management Reports for each year (usually tables 18, 19 or 20). 

159 
Table 27. Comparison of Bristol Bay Drift Gillnet and Set Gillnet Fisheries (2006-10 Averages). 

Source: CFEC Basic Information Tables.

Figure 16. Bristol Bay Salmon Harvests, by Fishery. Source: CFEC Basic Information Tables.

Figure 17. World Sockeye Salmon Supply. Bristol Bay: Sources are the same as for Figure 16. 

Other Alaska: Calculated by subtracting Bristol Bay data from Alaska data. Alaska data: 1980-

2005: CFEC Data for Alaska Salmon Harvests 1980-2005; 2006-2009: ADFG Alaska 

Commercial Salmon Harvests and Exvessel Values Reports. Lower 48: NMFS Commercial 

Fishery Landings Database, data for Washington, Oregon and California; Canada, Russia and 

Japan: FAO FishstatJ Database. 

Figure 18. Alaska Salmon Supply. Bristol Bay sockeye: Sources are the same as for Figure 11. 

Other Alaska sockeye: Calculated by subtracting Bristol Bay data from Total Alaska data. Total 

Alaska data: 1980-2005: CFEC Data for Alaska Salmon Harvests 1980-2005; 2006-2009: 

ADFG Alaska Commercial Salmon Harvests and Exvessel Values Reports. 

Figure 19 World Salmon and Trout Supply. Wild salmon: Sources are the same as for Figure 17. 

Farmed salmon and farmed trout: FAO FishstatJ Database. Includes only farmed production of 

Atlantic, Coho and Chinook salmon. Includes only farmed rainbow trout farmed in a 

"mariculture" (saltwater) environment. 

Figure 20. Bristol Bay Sockeye Preseason Projection and Annual Commercial Catch. Preseaon 

Projections: 1990-2005: ADFG Bristol Bay Annual Management Reports; Beginning 2006: 

ADFG Annual Run Forecasts and Harvest Projections. Actual harvests: same sources for Figure 

11. 

Figure 21 Bristol Bay Sockeye Salmon Harvests, 1895-2009. 1893:-1997: Byerly, Mike; 

Beatrice Brooks, Bruce Simonson, Herman Savikko and Harold Geiger. 1999. Alaska 

Commercial Salmon Catches, 1878-1997. Alaska Department of Fish and Game Regional 

Information Report No. 5J99-05. March 1999. 1998-2003: CFEC Data for Bristol Bay Salmon 

Harvests 1975-2003. 2004-2011: ADFG Alaska Commercial Salmon Harvests and Exvessel 

Values Reports. 

Figure 22. Bristol Bay Sockeye Salmon Production. ADFG Commercial Operator Annual Report 

(COAR) Data. 

Figure 23. Share of Sockeye Salmon Production in Bristol Bay. ADFG Commercial Operator 

Annual Report (COAR) Data. 

Table 28. Sales of Selected Sockeye Salmon Products by Major Bristol Bay Salmon Processors. 

ADOR Annual Salmon Price Reports. 

Figure 24. Bristol Bay Sockeye Salmon Harvests and Production. Harvests: See sources for 

Figure 11. Production: ADFG Commercial Operator Annual Report (COAR) Data. 

160 
Figure 25. Monthly Sale Volume of Bristol Bay Salmon Products. ADOR Monthly Salmon 

Reports 

Figure 26. Alaska Frozen Sockeye Production and U.S. Frozen Sockeye Exports. ADFG 

Commercial Operator Annual Report (COAR) Data; NMFS Foreign Trade in Fisheries Products 

Data.

 

Figure 27. Estimated End-Markets for Alaska Frozen Sockeye Salmon. Sources: ADFG 

Commercial Operator Annual Report (COAR) Data; NMFS Foreign Trade in Fisheries Products 

Data. The estimates for the “USA” were calculated by subtracting exports from Alaska 

production as reported in the COAR data. For the years 1989-1992 reported exports exceeded 

reported Alaska production. The estimate for the USA was assumed to be zero for these years. 

This is almost certainly an underestimate. In reality, some frozen sockeye production 

undoubtedly went to the US market, but the production and export data suggest that the amount 

going to the US market was relatively low, with most of the production being exported. 

Figure 28. Alaska Canned Sockeye Production and U.S. Canned Sockeye Exports. Sources: 

ADFG Commercial Operator Annual Report (COAR) Data; NMFS Foreign Trade in Fisheries 

Products Data. 

Figure 29. Average Ex-Vessel Price of Bristol Bay Sockeye Salmon. See data sources for Figure 

11. Real prices calculated using Anchorage CPI, as discussed below.

Figure 30. Average Wholesale and Ex-Vessel Prices of Bristol Bay Sockeye Salmon. Ex-vessel 

prices: See data sources for Figure 11. Wholesale Prices: ADFG Commercial Operator Annual 

Report (COAR) Data.

Figure 31. Average Monthly First Wholesale Prices. Sources: ADOR Monthly Salmon Price 

Reports 

Figure 32. Average Wholesale and Ex-Vessel Prices, Bristol Bay and Rest of Alaska. Rest-ofAlaska wholesale and ex-vessel prices were calculated by dividing Rest -of -Alaska value by 

Rest-of-Alaska volume. Rest-of-Alaska wholesale value and volume were calculated by 

subtracting Bristol Bay wholesale value and volume from total Alaska wholesale value and 

volume, as reported in ADFG Commercial Operator Annual Report (COAR) Data. Rest-ofAlaska ex-vessel value and volume were calculated by subtracting Bristol Bay ex-vessel value 

and volume (from sources for Figure 16, page 61) from total Alaska ex-vessel value and volume. 

Sources for total Alaska ex-vessel value and volume were: 1980-2005: CFEC Data for Alaska 

Salmon Harvests 1980-2005; 2006-2009: ADFG Alaska Commercial Salmon Harvests and Ex

vessel Values Reports. 

Figure 33. Average Ex-Vessel Prices of Sockeye Salmon, Selected Alaska Areas. Sources: 

ADFG Alaska Commercial Salmon Harvests and Exvessel Values Reports. 

Figure 34. Japanese Red-Fleshed Salmon Imports, May-April. Sources: Japanese monthly 

import data reported in Bill Atkinson’s News Report (a weekly compilation of articles and 

161 
information from the Japanese seafood industry press, translated into English, published until 

2006 by industry analyst Bill Atkinson) and Japanese import data reported on the National 

Marine Fisheries Service “Fishery Market News” website at: 

http://www.st.nmfs.noaa.gov/st1/market_news/index.html. 

Figure 35. Japanese Red-Fleshed Frozen Salmon Imports & Wild Sockeye Wholesale Prices. 

Japanese red-fleshed salmon imports are data for May-April, from the same sources as for Figure 

34. Sockeye wholesale price data are average prices for the period May-April, from the same 

sources as for Figure 36.

Figure 36. Japanese Wholesale Prices and Bristol Bay Prices for Sockeye Salmon. Source for 

ex-vessel price: see sources for Figure 11. Source for average first wholesale price: ADFG 

Commercial Operator Annual Report (COAR) Data. Sources for Japanese monthly wholesale 

prices: January 1980-December 1989: Tokyo Central Wholesale Market reports, average price 

for all frozen sockeye. January 1990-April 2002. Suisan Tsushin (Seafood News), Marine 

Products Power Data Book, 2002. Beginning May 2002: Japanese frozen market salmon prices 

posted on www.fis.com and the predecessor “Seaworld” website (data are prices reported for the 

first day of the month). Monthly wholesale prices in yen/kilo converted to prices in $/lb using 

monthly Japanese exchange rate data reported on the website of the Federal Reserve Bank of St. 

Louis (series EXJPUS, available at: http://research.stlouisfed.org/fred2/series/EXJPUS).

Figure 37. Average United States Import Prices of Selected Farmed Salmon Products. Source: 

NMFS Foreign Trade in Fisheries Products data.

Figure 38. U.S. Wholesale Prices for Selected Wild and Farmed Salmon Products. Prices are 

from Urner Barry’s Seafood Price-Current, a twice-weekly market report for U.S. seafood 

wholesale prices. Data shown in the figure are “low” reported prices for the first reporting date

of the month. Products are as follows: “Fresh farmed Atlantic, whole fish”: Northeast, 

Domestic and Canadian Atlantic, 6-8 lbs; “Fresh farmed Atlantic, pinbone-out fillets”: Fob 

Miami, Chilean Atlantic Fillets, Scale-on/Standard, C Trim/Premium,Pinbone out, 2-3 lbs; 

“Frozen H&G wild sockeye”: Red/Sockeye, Gillnet, 4-6 lbs. Information on Seafood PriceCurrent is at www.urnerbarry.com. 

Figure 39. Monthly Average Wholesale Case Prices for Alaska Canned Sockeye Salmon. Data 

through August 2000: ADOR Canned Salmon Wholesale Price Reports (statewide data for 

canned sockeye salmon). Data beginning September 2000: ADOR Monthly Salmon Price 

Reports (data for Bristol Bay canned sockeye salmon). 

Figure 40. Estimated Chilled and Unchilled Shares of Bristol Bay Salmon Harvests. Northern 

Economics, 2010 Bristol Bay Processor Survey. Prepared for Bristol Bay Regional Seafood 

Development Association, February 2011. Available at: 

http://www.bbrsda.com/layouts/bbrsda/files/documents/ 

bbrsda_reports/BB-RSDA%202010%20Survey%20Final%20Report.pdf 

162 
Figure 41. Ex-Vessel and First Wholesale Value of Bristol Bay Sockeye Salmon Harvests and 

Production, 1984-2010. Ex-vessel value: Same data sources as for Figure 11. Wholesale value: 

ADFG Commercial Operator Annual Report (COAR) Data.

Figure 42. Distribution of Nominal Value of Bristol Bay Sockeye Salmon. Sources for ex-vessel 

value and wholesale value are the same as for Figure 46, page 94. Value to processors after 

deducting payments to fishermen was calculated by subtracting ex-vessel value from wholesale 

value. 

Figure 43. Distribution of Value of Bristol Bay Sockeye Salmon. Calculated from data used for 

Figure 42. 

Figure 44. Number of Limited Entry Permits Issued and Fished in Bristol Bay. Source: CFEC 

Basic Information Tables.

Figure 45. Average Gross Earnings of Bristol Bay Drift Gillnet Permit Holders, by Quartile. 

Source: CFEC Quartile Tables.

Figure 46. Average Gross Earnings of Bristol Bay Set Gillnet Permit Holders, by Quartile. 

Source: CFEC Quartile Tables.

Figure 47. Average Prices Paid for Bristol Bay Limited Entry Permits. Source: CFEC Basic 

Information Tables. 

Figure 48. Average Permit Prices and Total Earnings: Bristol Bay Drift Gillnet Fishery. Source: 

CFEC Basic Information Tables.

Figure 49. Average Permit Prices and Total Earnings: Bristol Bay Drift Gillnet Fishery. Source: 

CFEC Basic Information Tables.

Figure 51. Number of Companies Reporting Salmon Production in Bristol Bay, by Product. 

Source: ADFG Commercial Operator Annual Report (COAR) Data.

Figure 52. Selected Bristol Bay Salmon Processor Costs, 2001-2009. “Cost of labor” data are 

ADLWD Bristol Bay Region Fishing and Seafood Industry Data. They are from the column 

titled “Seafood Processing Wages” in a table named “Bristol Bay Region Seafood Industry 2003-

2009” (as well as earlier versions of the same table no longer posted online) posted at: 

http://labor.alaska.gov/research/seafood/BristolBay/BBoverall.pdf

The data are also accessible by clicking on “Harvesting and Processing Workers and Wages” at 

the ADLWD Bristol Bay Region Fishing and Seafood Industry Data website. “Cost of fish” are 

ex-vessel values from the same data sources as Figure 11. “Other costs and profits” were 

calculated by subtracting “cost of labor” and “cost of fish” from wholesale value, as reported in 

ADFG Commercial Operator Annual Report (COAR) Data. 

163 
Figure 54. Monthly Employment in Food Manufacturing, Bristol Bay Region, 2002-2007. 

Alaska Department of Labor and Workforce Development, Quarterly Census of Employment 

and Wages Data, historical data for 2002-2010, Excel file annual.xls, downloaded November 27, 

2011 from: 

http://labor.alaska.gov/research/qcew/qcew.htm

Table 34. Selected Data and Estimates for Bristol Bay Taxes. Ex-vessel value of Bristol Bay 

salmon harvests: see data sources for Figure 11. Canned and non-canned share of production: 

ADFG Commercial Operator Annual Report (COAR) Data. 

Figure 56. Number of Bristol Bay Permit Holders by Residency. Source: Gho, Marcus, K. 

Iverson, C. Farrington, and N. Free-Sloan, Changes in the Distribution of Alaska's Commercial 

Fisheries Entry Permits, 1975 – 2010, CFEC Report 11-3N (2011), Appendix C. Available at:

http://www.cfec.state.ak.us/RESEARCH/12-1N/12-1N.htm

Figure 57. Permit Holders Average Earnings, by Residency. Source: Kurt Iverson, CFEC 

Permit Holdings, Harvests, and Estimated Gross Earnings by Resident Type in the Bristol Bay 

Salmon Gillnet Fisheries, CFEC Report 09-1N (February, 2009). Available at: 

http://www.cfec.state.ak.us/RESEARCH/09_1N/09_1N.pdf. 

Figure 58. Share of Total Earnings of Bristol Bay Drift Gillnet Permit Holders, by Residency. 

Same source as for Figure 57.

Figure 58. Share of Total Earnings of Bristol Bay Set Gillnet Permit Holders, by Residency. 

Same source as for Figure 57. 

Figure 60. Share of Bristol Bay Seafood Processing Employment, by Residency. Source: 

ADLWD Bristol Bay Region Fishing and Seafood Industry Data, posted at: 

http://labor.alaska.gov/research/seafood/seafoodbristol.htm

In particular, see the following tables: 

(A) “Bristol Bay Region Seafood Industry, 2003-2009, Processing" at: 

http://labor.alaska.gov/research/seafood/BristolBay/BBSFPOver.pdf

(B) “Local Seafood Processing Workforce, 2003-2009, Bristol Bay Region" at: 

http://labor.alaska.gov/research/seafood/BristolBay/BBSFPLocal.pdf 

The number and percentage of residents of other states or countries was calculated from data in 

(A). The number and percentage of Bristol Bay residents was calculated from data in (B). The 

share of “Other Alaska residents” was calculated as the residual.

164 
Figure 61. Local Bristol Bay Resident Share of Salmon Fisheries: Selected Measures. Source 

for local resident share of total permits held: Gho, Marcus, K. Iverson, C. Farrington, and N. 

Free-Sloan, Changes in the Distribution of Alaska's Commercial Fisheries Entry Permits, 1975 – 

2010, CFEC Report 11-3N (2011), Appendix C. Available at: 

http://www.cfec.state.ak.us/RESEARCH/12-1N/12-1N.htm

Source for local resident share of total earnings: Iverson, Kurt, CFEC Permit Holdings, 

Harvests, and Estimated Gross Earnings by Resident Type in the Bristol Bay Salmon Gillnet 

Fisheries, CFEC Report 09-1N (2009). Available at:

http://www.cfec.state.ak.us/RESEARCH/09_1N/09_1N.pdf

Source for local resident share of processing employment: Alaska Department of Labor and 

Workforce Development, “Local Seafood Processing Workforce, 2003-2009, Bristol Bay 

Region," available at:

http://labor.alaska.gov/research/seafood/BristolBay/BBSFPLocal.pdf

Table 37. Population, Permit Holders, and Salmon Earnings, by Community: 2000 & 2010. 

Source for population: U.S. Census, 2000 and 2010, in “Alaska Population Estimates by 

Borough, Census Area, City and Census Designated Place (CDP), 2000-2011,” Excel 

spreadsheet available on website of Alaska Department of Labor and Workforce Development, 

Research and Analysis Division at:

http://labor.alaska.gov/research/pop/popest.htm

Source for numbers of permit holders and earnings: CFEC Permit and Fishing Activity Data. 

Figure 63. Estimated Bristol Bay Population, by Area and Region. Data for 2000-2010 are from 

“Alaska Population Estimates by Borough, Census Area, City and Census Designated Place 

(CDP), 2000-2011,” Excel spreadsheet available on website of Alaska Department of Labor and 

Workforce Development, Research and Analysis Division, at: 

http://labor.alaska.gov/research/pop/popest.htm 

Data for 1984-1999 are from Northern Economics, The Importance of the Bristol Bay Salmon 

Fisheries to the Region and its Residents, Report prepared for the Bristol Bay Economic 

Development Corporation (October 2009), Tables A1-A12. 

Figure 63 [TOP FIGURE]. Estimated Bristol Bay Population, by Area. Data for 2000-2010 are 

from “Alaska Population Estimates by Borough, Census Area, City and Census Designated Place 

(CDP), 2000-2011,” Excel spreadsheet available on website of Alaska Department of Labor and 

Workforce Development, Research and Analysis Division. Data for 1984-1999 are from 

Northern Economics, The Importance of the Bristol Bay Salmon Fisheries to the Region and its 

Residents, Report prepared for the Bristol Bay Economic Development Corporation (2009), 

Tables A1-A12. 

165 
Figure 63 [BOTTOM FIGURE]. Estimated Population by Region. Data for 2000-2010 are from 

“Alaska Population Estimates by Borough, Census Area, City and Census Designated Place 

(CDP), 2000-2011,” Excel spreadsheet available on website of Alaska Department of Labor and 

Workforce Development, Research and Analysis Division. Data for 1984-1999 are from 

Northern Economics, The Importance of the Bristol Bay Salmon Fisheries to the Region and its 

Residents, Report prepared for the Bristol Bay Economic Development Corporation (2009), 

Tables A1-A12. 

Figure 65 [TOP FIGURE]. Number of Drift Gillnet Holders, by Region. Source: CFEC Permit 

and Fishing Activity Data. 

Figure 65 [BOTTOM FIGURE]. Number of Drift Gillnet Holders per 100 Residents, by Region. 

Calculated by dividing data for number of drift gillnet holders, shown in Figure 65 [TOP 

FIGURE], by data for estimated population by region, from the same sources as for Figure 63 

[BOTTOM FIGURE].

Figure 67 [TOP FIGURE]. Number of Set Gillnet Holders, by Region. Source: CFEC Permit 

and Fishing Activity Data. 

Figure 67 [BOTTOM FIGURE]. Number of Set Gillnet Holders per 100 Residents, by Region. 

Calculated by dividing data for number of set gillnet holders, shown in Figure 67 [TOP 

FIGURE], by data for estimated population by region, from the same sources as for Figure 63 

[BOTTOM FIGURE].

Table 38. Salmon Permit Holders per 100 Residents, by Community. Calculated by dividing 

data for number of permit holders by community, from CFEC Permit and Fishing Activity Data, 

by data for population by community, from the same sources as for Figure 63 [BOTTOM 

FIGURE].

Figure 69 [TOP FIGURE]. Total Salmon Fishery Earnings, by Region. Source: CFEC Permit 

and Fishing Activity Data. 

Figure 69 [BOTTOM FIGURE]. Per Capita Salmon Fisheries Earnings, by Region. Calculated 

by dividing data for total salmon fisheries earnings, shown in Figure 69 [TOP FIGURE], by data 

for estimated population by region, from the same sources as for Figure 63 [BOTTOM 

FIGURE].

Table 39. Bristol Bay Salmon Fishery Earnings, by Community, 2000 and 2010. Calculated by 

dividing data for salmon fishery earnings by community, from CFEC Permit and Fishing 

Activity Data, by data for population by community, from the same sources as for Figure 63 

[BOTTOM FIGURE].

Table 40. Economic Measures of Bristol Bay Salmon Industry: Sockeye Salmon Harvests. 

Same sources as for Figure 11, Figure 17, Figure 18 and Figure 19.

166 
Figure 70. Bristol Bay Commercial Salmon Harvests. Same sources as for Figure 16.

Table 41. Economic Measures of Bristol Bay Salmon Industry: Sockeye Value. Source for exvessel value is the same as for Figure 11. Source for first wholesale value is ADFG Commercial 

Operator Annual Report (COAR) Data. Source for Bristol Bay ex-value used in calculation of 

Bristol Bay sockeye salmon shares of value is the same as for Figure 11. Source of Alaska wild 

salmon ex-vessel value used to calculate Bristol Bay share of Alaska wild salmon ex-vessel 

value is the same as for Alaska data for Figure 17. World wild salmon harvest value estimated 

by multiplying world wild salmon harvests (from the same sources as for Figure 17) by Alaska 

average ex-vessel prices (from the same sources as for Figure 17). Source for United States Fish 

and Shellfish Landed Value is NMFS, Fisheries of the United States, various years, available at:

http://www.st.nmfs.noaa.gov/st1/publications.html

Source for “Rank of Naknek-King Salmon among U.S. ports in annual landed value” is NMFS 

Major Ports Data. 

Figure 71. Ex-Vessel and Wholesale Value of Bristol Bay Sockeye Salmon. Same sources as 

for Figure 46. 

Table 41. Economic Measures of the Bristol Bay Salmon Industry: Export Value. Source for 

U.S. export value is NMFS Foreign Trade in Fisheries Products Data. Source for estimated share 

of Bristol Bay sockeye in total Alaska sockeye salmon harvests is the same as for Figure 18. 

Source for first wholesale value of sockeye salmon roe production is ADFG Commercial 

Operator Annual Report (COAR) Data. 

Figure 72. Estimated Value of US Exports of Bristol Bay Salmon Products. Same sources as for 

Table 41.

Table 43. Economic Measures of the Bristol Bay Salmon Industry: Employment. Source for 

estimated peak employment and estimated annual average employment is Table 43. Source for 

Alaska totals used to calculate Bristol Bay share is the Alaska Department of Labor and 

Workforce Development (ADLWD) Research and Analysis Division website for “Statewide 

Data, Fishing and Seafood Industry” at: 

http://labor.alaska.gov/research/seafood/seafoodstatewide.htm

Table 44. Economic Measures of the Bristol Bay Salmon Industry: Permit Prices and Values. 

Source for permits issued and permit prices is CFEC Basic Information Tables.

Figure 74. Bristol Bay Commercial Salmon Harvests. Same sources as for Figure 11. 

Table 45. Distribution of Harvests for Bristol Bay Fishing Districts. See the data sources for 

Figure 13 for the sources for harvests by district used to calculate the distribution data shown in 

the table.

167 
Figure 75. Estimated Shares of Bristol Bay Sockeye Salmon Production, 2010. Frozen, Canned, 

Fresh and Roe share estimated from ADFG Commercial Operator Annual Report (COAR) Data. 

Frozen fillet and frozen H&G shares and canned talls and canned halves shares estimated from 

the shares of these products in frozen production and canned production reported in ADOR 

Annual Salmon Price Reports. 

Figure 76. Average Ex-Vessel and Wholesale Prices of Bristol Bay Sockeye Salmon. Same 

sources as for Figure 30. 

Figure 77. Ex-Vessel and First Wholesale Value of Bristol Bay Sockeye Salmon Production, 

1980-2010. Same sources as for Figure 41. 

Figure 78. Local Bristol Bay Resident Share of Bristol Bay Salmon Fisheries: Selected 

Measures. Same sources as for Figure 61.

Table 47. Relative Indicators of 2010 Salmon Fishery Participation and Earnings, Bristol Bay 

Watershed Region. Calculated from data in Table 37. 

Table 48. Selected Economic Measures of the Bristol Bay Salmon Industry. Selected data from 

Table 40-Table 44.

Table 49. Distribution of Selected Economic Measures for the Bristol Bay Commercial Salmon 

Fishing Industry. Sources for distribution calculations are as follows: Harvest, ex-vessel price, 

and ex-vessel value: Same data sources as for Figure 11. First wholesale prices and first 

wholesale value: ADFG Commercial Operator Annual Report (COAR) Data. Permit prices and 

estimated permit value: CFEC Basic Information Tables.

168 
Price Index Data for Converting from Nominal Dollars to Real Dollars 

The Anchorage Consumer Price Index (CPI) was used to convert selected “nominal” price and 

value data (not adjusted for inflation) presented in this report to “real” price and value data 

(adjusted for inflation). 

Anchorage CPI US CPI

1980 85.500 82.400 2.282 2.646

1981 92.400 90.900 2.112 2.399

1982 97.400 96.500 2.004 2.260

1983 99.200 99.600 1.967 2.189

1984 103.300 103.900 1.889 2.099

1985 105.800 107.600 1.844 2.027

1986 107.800 109.600 1.810 1.990

1987 108.200 113.600 1.804 1.920

1988 108.600 118.300 1.797 1.843

1989 111.700 124.000 1.747 1.759

1990 118.600 130.700 1.645 1.668

1991 124.000 136.200 1.574 1.601

1992 128.200 140.300 1.522 1.554

1993 132.200 144.500 1.476 1.509

1994 135.000 148.200 1.446 1.471

1995 138.900 152.400 1.405 1.431

1996 142.700 156.900 1.368 1.390

1997 144.800 160.500 1.348 1.359

1998 146.900 163.000 1.328 1.338

1999 148.400 166.600 1.315 1.309

2000 150.900 172.200 1.293 1.266

2001 155.200 177.100 1.257 1.231

2002 158.200 179.900 1.234 1.212

2003 162.500 184.000 1.201 1.185

2004 166.700 188.900 1.171 1.154

2005 171.800 195.300 1.136 1.117

2006 177.300 201.600 1.101 1.082

2007 181.237 207.342 1.077 1.052

2008 189.497 215.303 1.030 1.013

2009 191.744 214.537 1.018 1.016

2010 195.144 218.056 1.000 1.000

2011 201.427 224.939 0.969 0.969

Adjustment factor to convert to 

2010 dollars using:

(a) Anchorage CPI: Consumer Price Index for Anchorage Municipality; (b) US CPI: 

United States Consumer Price Index, All Urban Consumers. Source: U.S. Dept. of 

Labor, Bureau of Labor Statistics (BLS), downloaded March 15, 2012 from Alaska 

Department of Labor & Workforce Development website: 

http://labor.alaska.gov/research/cpi/cpi.htm.

Year Anchorage CPI US CPI

Anchorage and US Consumer Price Indexes

For any given year, the adjustment factor to convert from nominal dollars to real dollars is the 

Anchorage CPI for 2010 (195.144) divided by the Anchorage CPI for the year. For example, a 

nominal price of $1.00 in 1990 would have a “real” 2010 value of (195.144 / 118.600) x $1.00 = 

1.645 x $1.00 = $1.64. 

169 
This report uses the Anchorage CPI rather than the US CPI because it is the only available

measure of inflation for Alaska, and it is the most appropriate measure for accounting for the 

effects of inflation for Alaskans. The table above also shows the corresponding alternative 

adjustment factors using the US CPI. In practice, using the US CPI would have resulted in very 

similar “real” prices and values, and would not have resulted in any meaningful changes in any 

of the analysis or conclusions of this report. The source for both the Anchorage CPI and the US 

CPI was the U.S. Dept. of Labor, Bureau of Labor Statistics (BLS). These data are available on 

the Alaska Department of Labor & Workforce Development website at

http://labor.alaska.gov/research/cpi/cpi.htm. 

170 
4.0 Economic Significance of Healthy Salmon Ecosystems in 

the Bristol Bay Region: Summary Findings

The purpose of this section is to assess the economic significance of commercial activities that 

are dependent on ecosystems in the Bristol Bay watershed and important to the regional 

economy and to the state economy of Alaska. The study region consists of the Bristol Bay 

Borough, the Dillingham Census Area, and the Lake and Peninsula Borough. This economic 

significance analysis measures how many annual average jobs and how much personal income 

was generated in Alaska by expenditures associated with the Bristol Bay commercial salmon 

industry, subsistence activities, as well as various types of recreational activities dependent on 

Bristol Bay salmon ecosystems. We divide recreation into sport fishing, sport hunting, and nonconsumptive use, based on the primary activity reported by visitors to the Bristol Bay region. 

For 2009, we estimate that about 6,300 annual average jobs are attributable to the wild salmon 

ecosystem in the Bristol Bay region. Residents of Alaska hold more than 80 percent of all jobs. 

About 60 percent of all Alaskans working in the Bristol Bay region live in other parts of Alaska. 

About 20 percent of all jobs are held by non-residents from outside Alaska. At the peak of the 

summer season, there are almost 15,000 jobs in the Bristol Bay region associated with the 

commercial salmon fishery and recreation industries. In 2009, the total payroll traceable to this 

economic activity amounts to more than $282 million of which $182 million went to Alaska 

residents, and more than $100 million was received by non-residents from outside Alaska 

working seasonally in the commercial salmon fishery, recreation industries, or service providing 

industries. About $77 million went to local residents of the Bristol Bay region. 

The commercial fishing industry provides the biggest contribution to the economic significance 

of the Bristol Bay ecosystem. In terms of the overall direct employment in the region, half of all 

jobs are in the fishing industry, followed by government (32 percent), recreation (15 percent), 

and mineral exploration (3 percent). The largest recreation related contributor of direct jobs in 

the region is the non-consumptive recreational use sector providing 9 percent of the overall 

employment followed by sport fishing (5 percent) and sport hunting (1 percent). 

171 
Table 50. Estimated Economic Significance of Bristol Bay Ecosystems

Total Residents NonNon-local Local Total Residents

Direct jobs

 Peak 14,227 4,365 2,273 6,639 7,587

Commercial fish 11,572 3,251 1,089 4,341 7,231

Recreation 2,655 1,114 1,184 2,298 356

Subsistence non-mkt. non-mkt. non-mkt. non-mkt. non-mkt.

 Annual average 2,811 914 585 1,499 1,313

Commercial fish 1,897 530 177 707 1,190

Recreation 914 384 408 792 123

Subsistence non-mkt. non-mkt. non-mkt. non-mkt. non-mkt.

Multiplier Jobs 3,455 2,008 1,447 3,455 -

Total jobs

(annual average)

6,266 2,922 2,032 4,954 1,313

Direct wages 

($000)

$166,632 $40,149 $31,048 $66,199 $100,435

Commercial fish $134,539 $22,698 $17,608 $40,307 $94,233

Recreation $32,093 $12,451 $13,440 $25,892 $6,202

Subsistence non-mkt. non-mkt. non-mkt. non-mkt. non-mkt.

Multiplier wages $115,976 $69,250 $46,724 $115,976 -

Total wages $282,608 $104,399 $77,772 $182,175 $100,435

Note, table does not include jobs related to mineral exploration, commercial trapping, commercial fisheries other 

than salmon, or government. 

172 
4.1 Introduction

The purpose of this section is to assess the economic significance of commercial activities that 

are dependent on ecosystems in the Bristol Bay watershed and important to the regional 

economy and to the state economy of Alaska. 

“Economic significance” refers to how many annual average jobs and how much personal 

income was generated in Alaska by expenditures associated with the Bristol Bay commercial 

salmon industry as well as various types of recreational activities and subsistence activities 

dependent on Bristol Bay ecosystems. Thus it represents the jobs and income supported by a 

healthy Bristol Bay ecosystem. The study region consists of the Bristol Bay Borough, the 

Dillingham Census Area, and the Lake and Peninsula Borough. An economic significance 

analysis is different from an economic impact analysis that quantifies the change in management 

policy or some factor influencing the use of natural resources in the region. This analysis does 

not attempt to quantify any changes in the ecosystem, rather seeks to estimate economic activity 

dependent on a healthy Bristol Bay ecosystem. 

Note the following important limitations of this analysis: the analysis does not measure the net 

economic value of the natural resources occurring in the Bristol Bay region to Alaska and/or the 

U.S. as a whole. For example, we do not measure the economic value visitors and non-visitors to 

the region place on preservation of fish, wildlife, and wilderness within the Bristol Bay region. 

Second, the analysis shows the contributions to the regional economy of Bristol Bay and the rest 

of Alaska but excludes the contributions occurring in other states of the U.S. or other parts of the 

world. Fourth, the model shows only a one-year-snapshot of the economy. The analysis is based 

on data sources of earlier years that have been adjusted to reflect 2009 conditions or they are 

based on 2009 data. Given the large annual variations that occur in catches for the commercial 

salmon fishery and for visitation and expenditures related to tourism, the estimated economic 

significance for 2009 is not necessarily representative of historical or future economic 

significance.

The following sections of the report first describe the methods used to quantify the economic 

significance of economic activity in the Bristol Bay region. We then provide a brief regional 

economic overview followed by the multiplier results for each economic activity. The rationale 

and uncertainties related to assumptions relevant for the analysis are also discussed. Information

about all data sources used is also provided. 

Except where noted, all values are expressed in 2009 dollars and where necessary were adjusted 

using the Anchorage Consumer Price Index, the only available measure of inflation for Alaska. 

We report employment estimates for residents of three different regions: the local Bristol Bay 

region (local), other parts of Alaska (non-local residents), and residents of other states or 

countries (non-residents).

Note, for the purpose of this study, we report peak employment as a point estimate of the 

maximum count of workers observed, and state all other employment estimates (including 

173 
multiplier jobs) in terms of annual average jobs. For example, six jobs held for 2 month of the 

year in commercial salmon fishing would result in one annual average job. 

4.2 Methods

An economic significance analysis measures the importance of economic activity occurring in a 

region to the regional and statewide economies. We use jobs and income as two measures to 

show this significance. To conduct this analysis, we first identify the expenditures and jobs 

directly associated with the primary economic activity of the region including commercial 

fishing, recreation, and subsistence. We then calculate the additional expenditures, annual 

average jobs, and payroll generated by dollars re-circulating through the economy to support 

industries located in the region and elsewhere in Alaska. These effects are commonly referred to 

as multiplier effects. Note that these effects are only measuring trade flows in dollars and do not 

account for non-market trade flows such as bartering and the exchange of goods and services 

related to subsistence activity. 

The process by which purchases by an industry or by households stimulate purchases by other 

businesses and households is known as the multiplier effect. For this study, we measure 

multiplier effects for indirect and induced employment and wages. Indirect effects occur when 

primary industry purchases inputs to their operation from support sectors. For example, fishing 

boat captains purchase diesel fuel from local gas stations. Induced effects consist of the 

additional jobs and payroll created when employees of the primary and support industries spend 

their personal income on consumer goods and services. For example, the manager of the local 

gas station, where the fishermen purchased fuel, buys bread from the local bakery. 

In order to appropriately calculate the effects of re-circulating dollars through the economy, we 

use a regional Input-Output model developed by University of Alaska Anchorage Economics 

Professor Scott Goldsmith for the state of Alaska. Models are an imperfect representation of the 

real world and while they are essential for understanding reality, they should not be confused 

with that reality itself (Hilborn and Mangel, 1997). Thus the model results we represent are 

suggestive rather than definitive. If we wished to definitively measure the economic significance 

of the Bristol Bay ecosystem, we would need to conduct a very large and comprehensive survey 

of all the economic activity originating from the region and the payment flows that they generate. 

Such a study would be far outside the scope of this analysis both in terms of its cost as well as 

the time that it would take to complete.

We refer to the model used in this analysis as the ‘ISER Input-Output model” (Goldsmith, 2000). 

The model reflects the simplified economic structure of the Alaska economy, consisting of four 

regions, with the Southwest region encompassing the Bristol Bay study area. Since the model 

represents the structure of the entire region of Southwest Alaska, it is dominated by the larger 

urban area (Kodiak and Dutch Harbor), where most of the jobs are located. Other more rural 

communities, such as those of the Bristol Bay region, have a more rudimentary market economy. 

As a consequence, the Input-Output model may overstate the local economic activity in a rural 

area compared to what that spending may actually generate locally In other words, in rural areas, 

the local jobs multiplier tends to be overstated. However, this slight distortion averages out 

174 
across the region of Southwest Alaska and statewide. Thus, the aggregate regional effects across 

Southwest Alaska and the state-wide Alaska economy can be considered more accurate than the 

estimated local effects within the Bristol Bay region. 

Similarly to variation of economic activity within a region, there is also variation among regions. 

For example, Anchorage serves as the trade and service center for the state. Thus, any spending 

occurring in rural parts of the state has economic effects in the rural region and in the 

Southcentral region, where Anchorage is located. An important feature of the ISER Input-Output 

model is that wages paid in Anchorage can be attributed back to expenditures made in rural 

areas.

Another important characteristic of the ISER Input-Output model is that it establishes supply 

constraints. In Alaska, inter-industry purchases mainly occur with services and raw materials that 

are supply-constrained due to resource scarcity and the limited availability of capital and labor to 

extract the raw materials. “Off-the-shelf” Input-Output models developed primarily for other less 

resource-dependent states, such as IMPLAN, do not take this characteristic into account, and 

potentially overestimate multiplier effects within Alaska (MIG, 2011). Another important 

attribute of the Alaska economy is that inter-industry purchases are less important in Alaska 

compared to more mature economies. The absence of a developed manufacturing sector in 

Alaska means that most goods must be purchased outside the state, creating large leakages and 

small indirect multiplier effects. 

Despite the outlined advantages of the ISER Input-Output model, there remain many challenges 

to the analysis. One of these challenges is that the economic structure depends in large part on 

determining where the workers reside when they are not working. Many workers, particularly in 

the commercial fishing industry, don’t live in the Bristol Bay region. These workers only come 

to the region for a two to four months long period in the summer but live elsewhere the rest of 

the year. 

Another challenge is that there is no Input-Output model currently available that incorporates 

subsistence activity as an industry. Current Input-Output models solely reflect market economies 

and their sectors and ignore non-market sectors such as household work or subsistence activity. 

Due to the importance of subsistence to the regional economy of the Bristol Bay region, we 

believe that ideally the subsistence sector would be incorporated into input-output analysis of the 

economies of rural Alaska regions such as Bristol Bay where it is an important part of the 

economy. However, this kind of research would require additional effort and time far beyond the 

scope of this analysis. 

Sections 4.8 and 4.9 further discuss data sources used and the implications of assumptions made 

on overall results. Due to a lack of certain kinds of data and other sources of uncertainty further 

discussed in the appendix, the reader should interpret the estimated impacts as suggestive rather 

than definitive. 

The following two tables show how many jobs and income are associated with $1 million in 

2009 spending in Southwest Alaska. For example, $1 million dollars of in-state spending on air 

transportation in Southwest Alaska creates approximately six jobs in Southwest Alaska and one 

175 
job in Southcentral Alaska (Table 51). In addition, this spending generates $344,000 in payroll in 

Southwest Alaska and $54,000 in payroll in Southcentral Alaska (Table 52). 

Table 51. Annual average jobs associated with $1 million in spending in each sector in 

Southwest Alaska, 2009 

SOUTH SOUTH SOUTH NORTH STATE

EAST CENTRAL WEST TOTAL

I II III IV

-------------- ---------------- ------------ ------------ ------------

Agriculture and AFF Services 0.0 0.9 5.5 0.0 6.3

Forestry 0.0 0.3 4.2 0.0 4.4

Fishing 0.0 0.2 4.2 0.0 4.3

Crude Petroleum and Natural Gas 0.0 0.9 0.6 0.0 1.5

Other Mining 0.0 0.9 4.2 0.0 5.1

New Construction 0.0 0.0 4.1 0.0 4.1

Maintenance and Repair 0.0 4.0 10.2 0.0 14.1

Food and Kindred Products 0.0 0.2 5.3 0.0 5.5

Paper and Allied Products 0.0 0.0 5.0 0.0 5.0

Chemicals and Petroleum Processing 0.0 0.1 1.1 0.0 1.2

Lumber and Wood Products 0.0 0.0 5.6 0.0 5.7

Other Manufacturing 0.0 0.4 8.4 0.0 8.8

Railroads 0.0 0.2 4.1 0.0 4.3

Local and Interurban Transit 0.0 0.2 11.7 0.0 12.0

Motor Freight and Warehousing 0.0 1.1 10.2 0.0 11.2

Water Transportation 0.0 0.3 4.4 0.0 4.7

Air Transportation 0.0 1.0 6.4 0.0 7.4

Pipelines 0.0 0.1 3.7 0.0 3.8

Transportation Services 0.0 0.3 6.8 0.0 7.2

Communication 0.0 1.3 6.1 0.0 7.4

Electric, Gas, Water, and Sanitary 0.0 0.8 2.7 0.0 3.5

Wholesale Trade 0.0 4.6 10.0 0.0 14.6

Retail Trade 0.0 12.3 30.4 0.0 42.7

Finance 0.0 4.0 9.2 0.0 13.2

Insurance 0.0 2.1 8.9 0.0 11.0

Real Estate 0.0 0.9 0.7 0.0 1.6

Hotels, Lodging, Amusements 0.0 1.9 15.0 0.0 16.9

Personal Services 0.0 2.0 24.2 0.0 26.3

Business Services 0.0 6.4 20.2 0.0 26.6

Eating and Drinking 0.0 8.5 26.8 0.0 35.3

Health Services 0.0 4.8 18.8 0.0 23.6

Miscellaneous Services 0.0 4.6 15.1 0.0 19.7

Federal Government Ent 0.0 0.4 6.3 0.0 6.7

State & Local Government Ent 0.0 0.1 8.3 0.0 8.4

176 
Table 52. Annual payroll associated with $1 million in spending in each sector in Southwest 

Alaska, 2009 

SOUTH SOUTH SOUTH NORTH

EAST CENTRAL WEST

I II III IV

----------------------- ----------------------- --------------------- -----------------------

Agriculture and AFF Services $ - $ 43,276 $ 274,635 $ -

Forestry $ - $ 13,755 $ 209,563 $ -

Fishing $ - $ 8,821 $ 209,563 $ -

Crude Petroleum and Natural Gas $ - $ 150,128 $ 92,746 $ -

Other Mining $ - $ 72,014 $ 326,900 $ -

New Construction $ - $ 254 $ 254,526 $ -

Maintenance and Repair $ - $ 243,764 $ 626,678 $ -

Food and Kindred Products $ - $ 7,446 $ 181,843 $ -

Paper and Allied Products $ - $ 524 $ 165,218 $ -

Chemicals and Petroleum Processing $ - $ 12,003 $ 97,505 $ -

Lumber and Wood Products $ - $ 1,092 $ 211,898 $ -

Other Manufacturing $ - $ 15,244 $ 299,200 $ -

Railroads $ - $ 16,082 $ 296,407 $ -

Local and Interurban Transit $ - $ 5,409 $ 269,956 $ -

Motor Freight and Warehousing $ - $ 35,723 $ 336,974 $ -

Water Transportation $ - $ 21,311 $ 316,516 $ -

Air Transportation $ - $ 54,410 $ 344,270 $ -

Pipelines $ - $ 4,718 $ 268,972 $ -

Transportation Services $ - $ 14,772 $ 296,132 $ -

Communication $ - $ 87,937 $ 423,144 $ -

Electric, Gas, Water, and Sanitary $ - $ 55,677 $ 186,376 $ -

Wholesale Trade $ - $ 227,652 $ 494,997 $ -

Retail Trade $ - $ 365,739 $ 904,797 $ -

Finance $ - $ 206,101 $ 476,973 $ -

Insurance $ - $ 108,765 $ 463,912 $ -

Real Estate $ - $ 29,189 $ 23,538 $ -

Hotels, Lodging, Amusements $ - $ 46,021 $ 360,382 $ -

Personal Services $ - $ 44,267 $ 526,104 $ -

Business Services $ - $ 298,171 $ 940,459 $ -

Eating and Drinking $ - $ 151,775 $ 479,206 $ -

Health Services $ - $ 197,932 $ 785,286 $ -

Miscellaneous Services $ - $ 172,055 $ 565,071 $ -

Federal Government Ent $ - $ 25,818 $ 403,554 $ -

State & Local Government Ent $ - $ 5,415 $ 360,384 $ -

Households $ - $ 9,129 $ 22,931 $ -

Source: ISER Input-Output Model (Goldsmith, 2000).

177 
4.3 Regional Economic Overview

The economy of the Bristol Bay Region depends on three main activities (basic sectors)—

publicly funded services through government and non-profits, commercial activity associated 

with the use of natural resources (mainly commercial fishing and recreation), and subsistence. 

Subsistence is a non-market activity in the sense that there is no exchange of money associated 

with the subsistence harvest. However, local participants invest a significant portion of their time 

and income to participate in subsistence and the harvest has considerable economic value and 

their expenditures have significant economic effects. 

Public services and commercial activities bring money into the economy (basic sectors) and 

provide the basis for a modest support sector. The support sector (non-basic sector) consists of 

local businesses that sell goods and services to the basic sectors including the commercial fishing 

industry, the recreation industry, the government and non-profit sectors. The support sector also 

sells goods and services to participants in subsistence activities. 

The relative importance within the regional economy of government as contrasted with 

commercial fishing and recreation can be measured by the annual average employment in each 

sector. In 2009, more than two thousand jobs were directly associated with government spending 

from federal, state, and local sources. Commercial fishing and recreation accounted for 

approximately three thousand or 57 percent of total basic sector jobs (Table 53). Since much of 

the recreation is using public lands and resources, a share of the government sector; for example 

administration of the federal and state parks and wildlife refuges, is directly related to providing 

jobs and opportunities in the recreation sector. Accordingly, the estimate of recreation-dependent 

jobs is conservative.

The annual spending of federal dollars in the region is another indicator of the importance of the 

government sector in the region. Table 54 shows that in 2009, $119 million in federal spending 

flowed into the three labor market areas of the Bristol Bay region. 

The support sector depends on money coming into the regional economy from outside mainly 

through government, commercial fishing, and recreation. The relative dependence of the support 

sector on the three main sectors is difficult to measure. One reason for this is that government 

employment is stable throughout the year, while employment in commercial fisheries and 

recreation vary seasonally. Due to the seasonal stability of government jobs, the payroll spending 

of people employed in government is likely to contribute more to the stability of support sector 

jobs in the region than their share of basic sector jobs indicates. 

178 
Table 53. Employment Count by Place of Work in the Bristol Bay Region, 2009 

Annual 

Average Summer Winter Swing

Total jobs count 6,648 16,386 3,792 12,594

Basic 5,490 14,877 2,430 12,447

 Fish harvesting 1,409 6,909 - 6,909

 Fish processing 1,374 4,480 354 4,126

 Recreation 432 1,297 - 1,297

 Government & Health 2,039 1,712 2,056 (344)

 Mineral Exploration 197 450 70 380

Non-basic 1,406 1,509 1,362 147

 Construction 61 92 55 37

 

Trade/Transportation/Leisure

634 717 593 124

 Finance 155 142 162 (20)

 Other wage & salary 239 241 235 6

 Non-basic self employed 317 317 317 -

Resident jobs count 4,675 10,351 3,225 7,126

Note, estimates based on ISER Input-Output Model (Goldsmith, 2000).

Note, fish harvesting and processing include other fisheries but salmon, thus employment numbers cannot 

be compared with other tables shown in this report. Summer and winter employment shown, are point 

estimates that either show the maximum or minimum job count. Swing refers to the difference between 

maximum and minimum. See Appendix B for sources used. 

Table 54. Federal Spending in the Bristol Bay Region, 2009 ($000) 

Bristol Bay Dillingham Lake & Pen Total

Total $49,600 $54,345 $16,013 $119,958

Retirement $6,934 $6,764 $545 $14,243

Other direct to individuals $1,930 $10,235 $4,799 $16,964

Grants $32,867 $32,467 $7,878 $73,212

Procurement $4,440 $1,005 $857 $6,302

Wages $3,430 $3,874 $1,934 $9,238

Source: U.S. Department of Commerce (2009). 

179 
Table 55. Estimated Residence of Workers in the Bristol Bay Region 2009

Local Other 

Alaska

Outside 

Alaska Total

Bristol Bay

 State government 24 14 9 47

 Local government 126 12 18 156

 Private sector 273 332 1,916 2,521

 Sum 423 358 1,943 2,724

Dillingham

 State government 90 24 8 122

 Local government 877 66 94 1,037

 Private sector 1,033 270 728 2,031

 Sum 2,000 360 830 3,190

Lake & Pen

 State government 7 7 3 17

 Local government 417 105 66 588

 Private sector 179 322 685 1,186

 Sum 603 434 754 1,791

Total Private 1,485 924 3,329 5,738

Share 26% 16% 58% 100%

Source: ADOL (2009). Note, this is a count of workers (unique individuals) and not a measure of Full 

Time Equivalent or annual average jobs. Also, the table includes processing workers but excludes 

harvesters in the commercial fishery (private sector).

The estimated personal income in the region varies by borough/census area. The Bureau of 

Economic Analysis (BEA) reports more than $58,000 as the 2009 per capita personal income for 

the Bristol Bay Borough. Per capital personal income in the Lake and Peninsula Borough or in 

the Dillingham Census Area is approximately equal to $35,000 (Table 56). For comparison, the 

2009 per capita personal income in Anchorage amounts to $48,598. 

The commercial salmon fishery provides above average income to seasonal workers and 

residents of the region. Because of the large amounts of income received by seasonal workers 

that do not reside in the Bristol Bay region, BEA applies the Alaskan seasonal worker 

adjustment. This residence adjustment lowers the income generated in the region by the amount 

that is believed to be received by people working in Bristol Bay but not residing in the region. In 

part, it is a subjective measure for the amount of income flowing out of the Bristol Bay Borough 

to other areas of Alaska and to Washington State, Oregon, and California (BEA, 2007). Thus, the 

per capita income measures stated here are uncertain and should be viewed as suggestive rather 

than definitive. 

180 
Table 56. Estimated Personal Income in the Bristol Bay Region, 2009 (000$) 

Bristol Bay Dillingham Lake & Pen Total

Wages $57,018 $96,654 $27,551 $181,223

+ Supplements to wages $16,694 $28,021 $9,164 $53,879

+ Proprietor income $9,421 $16,194 $2,605 $28,220

= Earnings by place of work $83,133 $140,869 $39,320 $263,322

- Contributions for government 

social insurance

$8,799 $14,820 $3,736 $27355

+ Residence adjustment -$39,175 -$4,530 -$1,055 -$44,760

= Net earnings by place of 

residence

$35,159 $121,519 $34,529 $191,207

+ Dividends $7,382 $20,314 $7,980 $35,676

+ Transfers $9,189 $35,764 $11,981 $56,934

= Personal Income $51,730 $177,597 $54,490 $283,817

Population 881 4,957 1,485 7,323

Per Capita Income $58,717 $35,828 $36,694 $38,757

Source: BEA (2009).

181 
4.4 Commercial Salmon Fisheries

The largest share of jobs and income generated in the Bristol Bay region comes from commercial 

salmon fishing, including drift gillnet and set gillnet fisheries. The commercial salmon fishery is 

described in detail in Section 3 of this report. Here we provide a brief summary description prior 

to presenting estimates of the economic significance of the industry. 

The number of commercial fishing jobs and income varies from year to year due to the varying 

size and value of the salmon harvest. For example, the ex-vessel value paid to fishermen fell 

from a peak of $214 million in 1989 to $32 million in 2002, and recovered to $148 million in 

2009. The 2009 harvest was 192 million pounds. The whole sale value of these fish amounted to 

$300.2 million.26 

At the peak of the 2009 commercial salmon fishery, about 1,000 local residents and 6,000 

seasonal workers from outside the region participated in the commercial salmon fishery’s 

harvest. In addition, approximately 4,500 non-local processing workers came to the Bristol Bay 

region. At the peak of the season approximately 11,500 workers had jobs in harvesting and 

processing combined. About 4,300 of these workers were Alaska residents and approximately 

7,200 came from outside the state. 

We estimate that total income to harvesters in 2009 was approximately $103 million of which 

permit holders received $72 million (70 percent) and $31 million went to crew members. 

Alaskans participating directly in harvesting and processing earned approximately $40 million 

amounting to 42 percent of total direct wages. Local residents of the Bristol Bay region earned 

$17.6 million (12 percent) of total direct income in processing and harvesting combined. 

The commercial salmon season is highly seasonal. Almost all fishing and processing activity 

occurs between June and August. For the purpose of our analysis, we assume that each seasonal 

fishing job lasts two months. Therefore, six seasonal jobs equate to one annual average job. 

The in-state spending by harvesters, processors, and workers in the region and in other places of 

Alaska created additional jobs in other sectors of the economy through the multiplier effect. We 

estimate that on an annual average basis, 1,586 additional jobs (754 locally and 832 in the rest of 

Alaska) and $54.7 million in indirect wages were traceable to commercial fisheries. These jobs 

were in the trade, service, finance, and other support industries. Jobs created outside of the state 

are not included in these estimates. 

In 2009, the total income traceable to commercial salmon fishing in Bristol Bay equaled $189 

million. Accounting for the short two months summer season in commercial salmon fishing, the 

11,500 direct commercial salmon fishing jobs translate to approximately 1,900 jobs on an annual 

average basis. With the addition of multiplier jobs, about 3,500 annual average jobs would be 

attributable to the commercial salmon fishing industry (Table 57). 

26 Estimates of some year-specific commercial fishery total harvest and total sales vary slightly within this report. 

This is due to differences in how these data are aggregated and reported by the Alaska Fish and Game, and the point 

in time these statistics were accessed during the preparation of this report. 

182 

 
Table 57. Estimated Economic Significance of Commercial Fishing

Total Residents NonNon-local Local Total Residents

Direct jobs

 Peak 11,572 3,251 1,089 4,341 7,231 Harvesting 7,050 2,694 1,013 3,708 3,342

 Processing 4,522 557 76 633 3,889

 Annual average 1,897 530 177 707 1,190 Harvesting 1,143 437 164 601 542

 Processing 754 93 13 106 648

Multiplier Jobs 1,586 832 754 1,586 -

Total jobs

(annual average)

3,483 1,362 931 2,293 1,190

Direct wages 

($000)

$134,539 $22,698 $17,608 $40,307 $94,233

 Harvesting $103,354 $19,645 $16,609 $36,255 $67,100

 Processing $31,185 $3,053 $999 $4,052 $27,133

Multiplier wages $54,705 $28,101 $26,604 $54,705 -

Total wages $189,244 $50,799 $44,212 $95,012 $94,233

Note, estimates based on ISER Input-Output Model (Goldsmith, 2000).

183 
4.5 Recreation 

The second largest portion of jobs and income generated by spending dependent on Bristol Bay 

salmon resources comes from the recreation sector which directly employs approximately 2,600 

workers during peak season translating to about 900 annual average jobs with an annual payroll 

of more than $32 million. Most recreational visits occur during the summer months, creating a 

peak in economic activity that largely coincides with the peak of the commercial salmon fishery. 

Recreational activity concentrates in Katmai National Park and Preserve, Lake Clark National 

Park and Preserve as well as the National Wildlife Refuges: Alaska Peninsula/Becharof, 

Ixembek, and Togiak. Sport fishing activity occurs mainly in the Nushagak and Naknek River 

watersheds, whereas sport hunting occurs predominately in the Mulchatna River watershed. 

Visitors travel to Alaska by air, ferry, highway, and cruise ship. Each of these travel markets has 

distinct visitor attributes, demographics and regional impacts. Visitation to Southwest Alaska is 

primarily driven by independent travelers who predominately arrive by air. Statewide visitation 

declined 5.8 percent between 2008 and 2009 as a result of the recession following the collapse of 

financial markets in late 2008. Cruise passenger volume remained essentially the same in 2009 

because ship deployment decisions require a longer lead time than air. In contrast, air visitor 

traffic decreased by 15 percent in 2009. 

The rebound in Alaska visitation in 2010 was led by independent travelers arriving by air, and to 

a lesser extent road, ferry, and international visitors. This rebound is expected to continue in 

2011 and again be comprised primarily of independent travelers. These independent visitors 

tend to visit Alaska's more remote regions, while cruise visitors primarily visit the marine 

accessible Southeast region and the Southcentral and Interior regions including Denali National 

Park and Preserve. Katmai National Park and Preserve in Southwest Alaska showed a rebound in 

visitor numbers in 2010 after declines in 2008 and 2009, based on National Park Service 

Commercial Use Authorization permit report data. Among those that reported boosts in 

independent-visitor traffic are lodges, tour operators, and campgrounds, according to the Alaska 

Travel Industry Association. 

We estimate that there were approximately 40,964 non-consumptive recreation visitors to 

Southwest Alaska in 2009 of which approximately 10 percent were Alaska residents. Visitor 

related spending amounted to approximately $173.3 million in 2009. The average spending per 

visitor and the average length of stay are higher in Southwest Alaska compared to respective 

statewide averages. Based on the Alaska Visitor Statistics Program (2011), non-residents visiting 

Southwest Alaska spent $2,873 per visitor and stayed 12.9 nights whereas the statewide average 

visitor spent $992 and stayed 9.1 nights. Fay and Christensen (2010) estimate per visitor 

spending in Katmai to amount to $2,332. Also, recreational expenditures occurring inside 

Katmai NPP are relatively high for a remote Alaska park because of the location of Brooks 

Camp and concession businesses located inside the park. Based on the visitor spending reported 

by the Alaska Visitor Statistics Program (2011) and Fay and Christensen (2010), we estimate 

non-consumptive visitor spending in the Bristol Bay region to equal $2,548 per visitor and year. 

Among all recreational users of the region, non-residents spent the largest amount, equaling 

$149.5 million or 86 percent of total spending. Alaskans from outside the region spent an 

estimated $18.9 million, whereas locals had the smallest amount equaling $4.9 million in 

184 
recreation related expenditures. The per-visitor expenditures to destinations in Southwest Alaska 

are higher compared to other locations in Southcentral Alaska because most travelers go by air to 

the more remote locations such as Bristol Bay, whereas the largest portion of visitors to 

Southcentral Alaska come to Alaska by cruise ship.

Table 58. Estimated Recreational Visitors and Expenditures in the Bristol Bay Region, 

2009 

Local 

residents

Non-local 

residents

Nonresidents Total 

Visitors

 Non-consumptive - 4,506 36,458 40,964

 Sport fishing 13,076 3,827 12,464 29,367

 Sport hunting - 1,319 1,323 2,642

Total 13,076 9,652 50,245 72,973

Spending per visitor

 Non-consumptive - $2,548 $2,548

 Sport fishing $373 $1,582 $3,995

 Sport hunting - $1,068 $5,170

Spending ($million)

 Non-consumptive - $11.5 $92.9 $104.4

 Sport fishing $4.9 $6.0 $49.8 $60.7

 Sport hunting - $1.4 $6.8 $8.2

Total $4.9 $18.9 $149.5 $173.3

Note that some visitors combine fishing with non-consumptive use activities. These visitors are included 

here in sport fishing. Cost of travel to Alaska for non-residents not shown. Annual spending per nonconsumptive visitor is the weighted average of visitor spending related to Katmai and other locations in 

the Bristol Bay Region. 

The local economic impact of visitor spending occurs primarily through local purchases of goods 

and services. This effect is captured in the multiplier jobs and wages in . The multiplier jobs are 

held in the transportation, accommodation, and trade sectors of the economy. A large share of 

these jobs is located outside the Bristol Bay region in Southcentral Alaska where most of the 

goods and services originate from. The jobs in these sectors are more likely to be filled by 

Alaska residents who live where they work, and they are more likely year-round rather than 

seasonal jobs. 

For 2009, we estimate the total annual average number of jobs that are traceable to recreational 

visits to the Bristol Bay region to equal 2,715 with total payroll of $90.8 million. On an annual 

average basis, the majority (44 percent) of the 914 direct jobs were held by local residents of the 

region followed by other Alaska residents (384 jobs). Other Alaskans either moved into the 

185 
region to fill a job during the summer season, or their job was located in Anchorage and 

attributable to recreation occurring in the Bristol Bay region. A smaller share of total jobs (13 

percent) was taken by non-residents. Also, some of the indirect jobs in transportation, trade, and 

accommodations were probably filled by non-residents rather than residents. Important to note is 

that due to a lack of data, the distribution of jobs and income by residency is uncertain. However, 

total employment and total income estimates are more robust measures. 

Note, since many of the goods and services consumed in Alaska, are produced outside of Alaska 

and consequently have economic effects elsewhere, these spillover effects are not part of this 

economic analysis. 

Table 59. Estimated Economic Significance of All Recreation

Total Residents NonNon-local Local Total Residents

Direct jobs

 Peak 2,655 1,114 1,184 2,298 356 Non-cons. 1,669 735 741 1,475 193

 Sport Fish 854 328 383 712 142

 Sport Hunt 132 51 60 111 21

 Annual average 914 384 408 792 123 Non-cons. 575 253 255 509 67

 Sport Fish 294 113 132 245 49

 Sport Hunt 45 18 21 38 7

Multiplier Jobs 1,801 1,129 672 1,801 -

Total jobs

(annual average)

2,715 1,513 1,080 2,593 123

Direct wages 

($000)

$32,093 $12,451 $13,440 $25,892 $6,202

 Non-cons. $19,107 $7,823 $7,925 $15,748 $3,359

 Sport Fish $11,279 $4,020 $4,777 $8,797 $2,482

 Sport Hunt $1,707 $608 $738 $1,347 $361

Multiplier wages $58,672 $39,380 $19,290 $58,672 -

Total wages $90,765 $51,831 $32,730 $84,564 $6,202

Note, estimates based on ISER Input-Output Model (Goldsmith, 2000). All direct jobs are in the Bristol 

Bay region. Multiplier jobs are divided between Bristol Bay and Southcentral Alaska. Multiplier jobs are 

assumed to be all taken by residents of the region where they occur. Peak and annual average direct 

wages are assumed to be equal.

186 
4.5.1 Non-Consumptive Use

Most of recreational spending in the Bristol Bay region is related to non-consumptive use, for 

example wildlife viewing of coastal brown bears and bird species, or kayaking and camping 

activities. For this part of the analysis we estimate visitation based on the most recent studies of 

non-resident visitors to the state and two studies that estimated visitation and economic impacts 

related to Katmai National Park and Preserve. On an annual basis including summer and winter 

visitation, approximately 2,300 residents and 18,900 non-residents visited Katmai NPP. Other 

areas in the Bristol Bay region received approximately 2,300 resident visitors and 19,000 nonresident visitors. Note, these estimates exclude visitation where sport fishing or sport hunting 

was in part or the primary activity of choice. After adjusting the per capita expenditures to 2009 

dollars we estimate per person expenditures to amount to $2,245 annually for Katmai NPP and 

$2,873 per person annually for visiting other destinations in the Bristol Bay region. 

To be consistent with the expenditure data for sport fishing and hunting, we assume that the visit 

to the Bristol Bay region was the primary reason for their visit to Alaska. For these visitors we 

include all their instate spending in the calculation of multiplier jobs and income. 

 

We estimate a total of 1,681 annual average jobs to be attributable to non-consumptive use of 

natural resources in the Bristol Bay region with a payroll of $54.8 million. The main proportion 

(57 percent) of jobs are held by residents of Alaska that do not live in the Bristol Bay region 

either because they move to Bristol Bay for the summer months to fill a seasonal job or because 

they work in Anchorage for a supplier of goods and services to the Bristol Bay region. The total 

income generated in 2009 for residents of Alaska amounted to $51.4 million. 

Table 60. Estimated Economic Significance of Non-Consumptive Use

Total Residents NonNon-local Local Total Residents

Direct jobs

 Peak 1,669 735 741 1,475 193 Annual average 575 253 255 509 67

Multiplier Jobs 1,106 703 403 1,106 -

Total jobs

(annual average)

1,681 956 658 1,615 67

Direct wages 

($000)

$19,107 $7,823 $7,925 $15,748 $3,359

Multiplier wages $35,668 $24,059 $11,608 $35,668 -

Total wages $54,775 $31,882 $19,533 $51,416 $3,359

Note, estimates based on ISER Input-Output Model (Goldsmith, 2000). All direct jobs are in the Bristol 

Bay region.

187 
4.5.2 Sport Fishing

The second largest share of total recreational expenditures in the Bristol Bay region is associated 

with sport fishing, either as the only or as the primary activity of the visitor. Non-residents 

account for 53 percent of visitors that fish in the region and spend 82 percent of total sport fish 

related expenditures attributable to the region, excluding travel to Alaska. Non-residents are 

most likely to hire guides and stay at local lodges. Alaska residents account for 47 percent of 

visitation and spend 10 percent of total sport-fish-related expenditures. We also include spending 

on sport fishing by local residents, even though that spending does not bring in money from 

outside the region to the Bristol Bay region. If there would not be any sport fishing opportunities 

in the region, that local spending could likely shift to other areas outside the region and thus 

provides the rationale for including it in our calculations. 

At the peak of the fishing season in July, employment in sport fishing reaches 854 direct 

seasonal jobs. The annual average employment traceable to sport fishing in the region amounts 

to approximately 300 annual average jobs, of which almost half are taken by local residents. The 

total estimated payroll attributable to sport fishing activities in the Bristol Bay region amounts to 

$31.4 million in 2009. We estimate that about a third of total payroll went to local residents of 

the Bristol Bay region. After counting for multiplier jobs, more than 900 annual average jobs are 

traceable to sport fishing occurring in the Bristol Bay region. 

Table 61. Estimated Economic Significance of Sport Fishing

Total Residents NonNon-local Local Total Residents

Direct jobs

 Peak 854 328 383 712 142 Annual average 294 113 132 245 49

Multiplier Jobs 608 371 237 608 -

Total jobs

(annual average)

902 484 368 853 49

Direct wages 

($000)

$11,279 $4,020 $4,777 $8,797 $2,482

Multiplier wages $20,118 $13,339 $6,779 $20,118 -

Total wages $31,397 $17,359 $11,556 $28,915 $2,482

Note, estimates based on ISER Input-Output Model (Goldsmith, 2000). All direct jobs are in the Bristol 

Bay region.

188 
4.5.3 Sport Hunting

Compared to other recreation activities, sport hunting accounts for the smallest share of total 

recreational expenditures (3 percent) and the fewest visitors overall (5 percent) (Table 58). The 

larger per person expenditure of $3,122 per visitor is related to higher travel costs. In addition, 

non-residents are by law required to hire local guide services which adds to the cost for hunting, 

including air service to remote hunting locations. Sport hunters are also more likely to hire 

commercial operators for sport hunting. Of the 125 total annual average jobs in Alaska 

attributable to sport hunting, most are taken by residents of the state with the majority of workers 

residing outside the Bristol Bay region. The total payroll attributable to spending traceable to 

sport hunting in the Bristol Bay region is more than $4 million, with the majority going to nonlocal residents of Alaska residing in the Southcentral region of Alaska. 

Table 62. Estimated Economic Significance of Sport Hunting

Total Residents NonNon-local Local Total Residents

Direct jobs

 Peak 132 51 60 111 21 Annual average 45 18 21 38 7

Multiplier Jobs 87 55 32 87 -

Total jobs

(annual average)

132 73 53 125 7

Direct wages 

($000)

$1,707 $608 $738 $1,347 $361

Multiplier wages $2,886 $1,982 $903 $2,886 -

Total wages $4,593 $2,590 $1,641 $4,233 $361

Note, estimates based on ISER Input-Output Model (Goldsmith, 2000). All direct jobs are in the Bristol 

Bay region.

189 
4.6 Subsistence

Subsistence is an important component of the regional economy even though it is not part of the 

market economy. Consequently there is no official measure for employment or the amount of 

payroll associated with the pursuit of subsistence resources. However, there remains a link 

between subsistence and the market economy in form of equipment, goods, and services 

purchased by households participating in subsistence. Typically these purchases include boats, 

rifles, nets, snow mobiles, and fuel used exclusively to take part in subsistence activities. 

Data on expenditures related to subsistence activities in the Bristol Bay region is not publically 

available. Our estimate of $3,054 per household relies on data from a survey conducted in 1993 

in the North Slope Borough (North Slope Borough, 1993; Goldsmith, 1998). Although, income, 

employment opportunities, and subsistence methods used in the North Slope Borough are 

different, there is evidence that suggests the estimate is justified. The results of a 1980s 

subsistence survey in Western Alaska communities are consistent with the 1993 North Slope 

estimate (Peterson et al., 1992). 

A large share of the 68 multiplier jobs occurs in the Southcentral region (47 jobs) with more than 

$1.8 million in payroll. Local multiplier jobs amount to approximately 16 and an annual payroll 

of $830,000. The small number of multiplier jobs that are generated by household spending on 

equipment is also affected by the limited capacity of local businesses to supply goods and 

services. 

Table 63. Estimated Economic Significance of Subsistence

Total Residents NonNon-local Local Total Residents

Direct jobs

 Peak Nonmkt.

Non-mkt. Non-mkt. Non-mkt. Non-mkt.

 Annual average

Multiplier Jobs 68 47 21 68 -

Total jobs

(annual average)

68 47 21 68 -

Direct wages 

($000)

Nonmkt.

Non-mkt. Non-mkt. Non-mkt. Non-mkt.

Multiplier wages $2,599 $1,769 $830 $2,599 -

Total wages $2,599 $1,769 $830 $2,599 -

Note, estimates based on ISER Input-Output Model (Goldsmith, 2000). All direct jobs are in the Bristol 

Bay region.

190 
4.7 Conclusions

In 2009, the Bristol Bay salmon ecosystem supported more than 6,000 annual average jobs with 

a payroll of $282 million. Non-residents of Alaska held one fifth of all jobs and received one 

third of all income generated, about $100 million. Alaskans held approximately 5,000 jobs (80 

percent of all jobs) and earned $182 million, one third of total income. Local residents of the 

Bristol Bay region held about a third of all jobs and earned almost $78 million (28 percent) of 

total income traceable to the Bristol Bay salmon ecosystem (Table 64). 

The majority of jobs held by Alaskans are taken by residents from other regions of Alaska, 

particularly by harvesters in the commercial salmon fishery. More than half of all jobs are held 

by workers in the support industries for commercial fishing and recreation, which are mainly 

located in Southcentral Alaska. Multiplier wages amount to about a third of total income 

generated. 

The regional economy is primarily driven by the commercial salmon industry, followed by 

tourism and participation in subsistence, considered to be a non-market economic activity. The 

economy of the Bristol Bay is a mixed cash-subsistence economy, where subsistence activity 

requires labor inputs without exchange of money for the labor performed. Subsistence creates 

non-cash jobs to local residents of the region who are pursuing subsistence activities to support 

their families’ need for food. The subsistence economy provides a direct link between the health 

of the Bristol Bay salmon ecosystem and human well-being. Subsistence is integral to the local 

way of life in the Bristol Bay region. However, even though it is an important part of the regional 

economy, work related to subsistence similar to household work, is not officially measured and 

neither is it subject to an exchange of money for the work performed. Thus, in the context of this 

study which is solely focused on market values, we are unable to quantify the economic 

significance of subsistence in the sense of direct jobs and income. Thus we present these jobs as 

non-market jobs. However, we present multiplier jobs resulting from subsistence-related 

spending on capital equipment and gasoline for example. These expenditures are necessary 

inputs to participating in subsistence activities and are included under multiplier jobs and wages 

(Table 64). 

191 
Table 64. Estimated Economic Significance of Bristol Bay Ecosystems

Total Residents NonNon-local Local Total Residents

Direct jobs Peak 14,227 4,365 2,273 6,639 7,587

Commercial fish 11,572 3,251 1,089 4,341 7,231

Recreation 2,655 1,114 1,184 2,298 356

Subsistence non-mkt. non-mkt. non-mkt. nonmkt.

non-mkt.

 Annual average 2,811 914 585 1,499 1,313

Commercial fish 1,897 530 177 707 1,190

Recreation 914 384 408 792 123

Subsistence non-mkt. non-mkt. non-mkt. nonmkt.

non-mkt.

Multiplier Jobs 3,455 2,008 1,447 3,455 -

Total jobs

(annual average)

6,266 2,922 2,032 4,954 1,313

Direct wages 

($000)

$166,632 $40,149 $31,048 $66,199 $100,435

Commercial fish $134,539 $22,698 $17,608 $40,307 $94,233

Recreation $32,093 $12,451 $13,440 $25,892 $6,202

Subsistence non-mkt. non-mkt. non-mkt. nonmkt.

non-mkt.

Multiplier wages $115,976 $69,250 $46,724 $115,976 -

Total wages $282,608 $104,399 $77,772 $182,175 $100,435

Note, estimates based on ISER Input-Output Model (Goldsmith, 2000). All direct jobs are in the Bristol 

Bay region.

192 
4.8 Key Assumptions and Uncertainties

Description Potential Bias

Sensitivity 

relative to 

overall 

results

GENERAL

The ISER Alaska InputOutput model consists of four 

regions. The Bristol Bay 

region is only part of one of 

these regions, the Southwest 

region. Larger communities 

outside Bristol Bay such as 

Kodiak and Dutch Harbor are 

part of the Southwest region.

The expenditures related to economic activity in 

the Bristol Bay region overestimate the 

employment generated in the region and 

underestimate the employment generated in other 

regions. The bias in overall Alaska economic 

impact is unknown. 

Moderate

The commodity by industry 

matrix is part of the InputOutput model and allocates 

commodity expenditures 

among costs of goods, 

transportation margins, trade 

margins, and to industries, 

based on statewide averages.

Transportation and trade margins may be higher 

for purchases made in small, rural parts of Alaska 

than for the state as a whole. This would result in 

an underestimate of the transportation and trade 

share of the total economic impact. Bias in 

overall Alaska economic impact is unknown. 

Moderate

Composition of household 

expenditures is based on 

statewide averages.

The composition of rural household expenditures 

may be different from the state average, which is 

heavily weighted by urban households. Bias in 

overall Alaska economic impact is unknown. 

Moderate

COMMERCIAL FISHING

Unrepresentative base year for 

harvest and ex-vessel value 

estimates

Given the large annual variations that occur in 

catches for the commercial salmon fishery the 

estimated economic significance for 2009 is not 

necessarily representative of historical or future 

economic significance.

High

Assumptions about the level 

of expenditures per harvester 

and processor

Unknown Moderate

Assumptions about the 

composition of harvester and 

processor purchases 

Unknown Moderate

Assumption about the regional 

allocation of expenditures by 

Unknown Moderate

193 
Description Potential Bias

Sensitivity 

relative to 

overall 

results

harvesters and processors

Assumption about the 

residence of harvesters and 

processor employees

Unknown Moderate

Travel cost related to nonresident and Alaska resident 

travel between place of 

residence and place of work in 

Bristol Bay.

While we consider the in-state economic impact 

of all earnings for harvesters’ and processors’ 

earnings, we ignore the in-state cost of travel 

between place of residency and place of work for 

participants in the commercial fishing industry. 

Negligible

RECREATION: NON-CONSUMPTIVE USE

Assumptions about the 

number of local resident 

visitors, non-local residents, 

and non-residents

Underestimate due to the potentially higher 

number of resident visitors (Fix, 2010). 

Moderate

Assumptions about the level 

of expenditures per trip 

Underestimate. Other sources state higher per trip 

expenditures for Southwest Alaska destinations 

ranging from $3,068 to $3,760 per person and 

trip (Colt and Dugan, 2005; Littlejohn and 

Hollenhorst, 2007). 

Moderate

Regional allocation of nonconsumptive expendituresUnknown Negligible

Assumption about the regional 

allocation of guide, charter, 

and lodge purchases.

Unknown Negligible

Assumption about the 

residence of guide, charter, 

and lodge employees

Unknown Negligible

RECREATION: SPORT FISHING & HUNTING

Assumptions about the 

number of trips by local 

residents, non-local residents, 

and non-residents 

Given the annual variations that occur in the 

number of visitors to Southwest Alaska the 

estimated economic significance for 2009 is not 

necessarily representative of historical or future 

economic significance.

Moderate

Assumptions about the level 

of expenditures per trip 

Given the national recession and worldwide 

economic slump the annual variations in visitor 

expenditures, the estimated economic 

significance for 2009 is not necessarily 

representative of historical or future economic 

Moderate

194 
Description Potential Bias

Sensitivity 

relative to 

overall 

results

significance.

Regional allocation of sport 

fishing and sport hunting 

expenditures

Unknown Negligible

Assumption about the regional 

allocation of guide, charter, 

and lodge purchases.

Unknown Negligible

Assumption about the 

residence of guide, charter, 

and lodge employees

Unknown Negligible

Capital expenditures related to 

residents’ boats, cabins, and 

other equipment 

We ignore capital expenditures related to 

equipment due to the difficulty of apportioning a 

usage-share to specifically sport fishing or 

hunting in the Bristol Bay region. 

Moderate

SUBSISTENCE

Assumption of number of 

households engaged in 

subsistence activities

Unknown Moderate

Assumption about the level of 

expenditures on subsistence 

per household 

Unknown. Estimate is from the North Slope of 

Alaska where there is a different subsistence 

culture compared to Bristol Bay. Similar 

subsistence surveys in Western Alaska indicate 

that the estimate used is justified. The direction 

of bias is unknown. 

Moderate

Assumptions about the 

composition of subsistence 

related expenditures

Unknown Negligible

Assumption about the regional 

allocation of subsistencerelated expenditures

Unknown Negligible

Source: adapted from Goldsmith et al. (1998).

195 
4.9 Data Sources

(Methods).

Expenditures that are excluded from the Input-Output modeling exercise are tax revenues 

generated through locally occurring economic activity, expenditures associated with natural 

resource management, and the commercial trapping industry. In addition, the study excludes the 

economic importance of herring fisheries in the Bristol Bay region. Compared to salmon, herring 

fisheries in Bristol Bay are much smaller amounting to $2.5 million in ex-vessel value in 2009 

compared to salmon with $148 million (CFEC, 2009). We do not evaluate mineral exploration 

because it is not dependent on healthy ecosystems in the Bristol Bay region. 

(Regional Economic Overview). There are three data sources related to jobs reported in the 

Bristol Bay region. The Alaska Department of Labor and Workforce Development offers annual 

average employment for wage earners (ADOL, 2009e) and information on participation in the 

commercial fisheries such as crew shares and processor employment (ADOL, 2009a-c). The 

third data source is an annual count of proprietors provided by the U.S. Bureau of Economic 

Analysis (BEA, 2009). Data from ADOL does not include fishing employment, but BEA 

provides an estimate of proprietors (including fish harvesters and other proprietors) in the region. 

Since ADOL data is measured in annual average jobs and the BEA data is a count of workers, 

we adjust the proprietor data to reflect seasonality assuming a six week harvesting season. 

Proprietors include local resident crew and local resident captains which are based on crew 

factors from ADOL (2004) and resident share of crew from ADOL (2009c). In addition, we use 

information on the number of local permits fished from CFEC (2009) to get an estimate of the 

number of local captains participating in the fishery. It is important to note that the ADOL data 

only provides employment estimates by place of work. The BEA proprietor data is based on 

income tax returns, thus the BEA proprietors counted in our analysis are only the ones that show 

a business address in the Bristol Bay region. Our analysis does not include businesses registered 

elsewhere in Alaska or out of state. Consequently, the proprietor data used in this study and 

shown in Table 2 is an underestimate of the jobs that likely exist. For this reason, employment 

estimates in Table 2 are not comparable to employment estimates elsewhere in the report. 

(Commercial fisheries). For this study we divide the commercial fisheries sector into harvesting 

and processing. For the harvest sector, harvest data by residency of permit holder came from the 

Commercial Fisheries Entry Commission’s Basic Information Tables (CFEC, 2009). Residency 

of captains is based on Iverson (2009). Residency of crew is unknown but was inferred from 

crew license data available at ADOL (2009a) for all commercial fisheries in the Bristol Bay 

region. ADOL (2009a) shows that local captains hire 1.46 local crew in all of Bristol Bay’s 

commercial fisheries. Since the salmon fisheries are by far the largest fisheries in the region we 

assume that each local captain hires 1.46 local crew with the remainder of crew members coming 

from other places in Alaska. Non-local captains are assumed to hire exclusively non-local crew 

and non-resident captains exclusively non-resident crew. The crew size for Bristol Bay 

commercial salmon fisheries amounts to three including the skipper and is the same in the set net 

and drift gill net fisheries (ADOL 2004). Crew shares for the set net and drift gill net fisheries 

are based on a ten year average proportion of crew shares to gross earnings as stated in Schelle et 

al. (2004). In addition, Schelle et al. (2004) provides expenditure categories for harvesters for 

196 
the drift gillnet fishery. Due to a lack of data on expenditures in the set gill net fishery, we

assume costs to be about half of what they are in the drift gill net fishery with lower insurance, 

moorage and storage and other boat related expenses due to the much smaller boats being used 

for set net operations. We further allocate these expenditures within a commodity by industry 

matrix to form a final demand vector that is passed to the ISER I-O Model following Goldsmith 

(2000). For the processing sector, we assume that 95 percent of the harvest is processed in the 

Bristol Bay region, including on-shore and off-shore processing. For simplicity, the Input-Output 

model assumes processor expenditures for off-shore processing to be similar to on-shore 

processing. Residency of processing workers is from ADOL (2009). Wholesale value for salmon 

roe and non-roe combined are from ADF&G (2009). Average processor yield is calculated based 

on the combined net product weight stated in ADF&G (2009) and pounds harvested (CFEC, 

2009). Note, all direct jobs are in the Bristol Bay region. Multiplier jobs are divided between 

Bristol Bay and Southcentral Alaska. Multiplier jobs are assumed to be all taken by residents of 

the region where they occur. Peak and annual average direct wages are assumed to be equal.

(Recreation). 

No comprehensive analysis has been completed on the economic significance of recreation and 

tourism in Southwest Alaska. One of the greatest challenges is estimating visitor volume for 

residents and non-residents. A number of separate studies provide some indication of pertinent 

levels and patterns of visitation activities. Non-resident visitation, length of stay, and expenditure 

per visitor to Southwest Alaska are from McDowell Group ( 2007a). Bluemink (2010) and the 

Alaska Travel Industry Association provided information on current trends in visitation and so 

did the National Park Service Commercial Use Authorization permit report data (National Park 

Service, 2010). 

For this study we separated visitor impacts by residency and by type of activity. For sport 

fishing and sport hunting, Duffield and Neher (2002), estimated visitor volume and 

expenditures for sport fishing and sport hunting based on license data and visitor specific 

expenditure data from ADF&G (2009b). In addition, Duffield et al. (2007) conducted a lodge 

survey in the Bristol Bay region that offered detailed angler expenditure categories by residency, 

as well as expenditure detail for lodges and guiding outfits. After adjusting for inflation, we 

develop separate final demand vectors for sport hunting and fishing by residency. The analysis 

follows Goldsmith (2000) and Duffield et al. (2007). According to ADF&G’s hunting 

regulations, the sport hunting season for moose, caribou and bear is mainly in the fall months and 

varies by area. For the calculation of annual average jobs, we assume the main season for sport 

hunting to be three months long (ADF&G, 2011). 

We define non-consumptive users as those who reported wildlife viewing, camping, kayaking, 

hiking, or photography as their primary purpose of their visit. We adjust the most recent 2006 

summer and winter visitor estimate for Southwest Alaska excluding Kodiak by applying the 

2006-2009 percent difference in air travelers for Alaska overall (McDowell Group, 2007a & 

2007b). The trend in air travelers to Alaska serves as the best indicator for changes to visitation

in Southwest Alaska for two reasons. First, visitors to rural Alaska are mainly independent 

travelers, and second they primarily arrive by air in comparison to the statewide largest share of 

visitors who arrive by cruise ship. The Southwest Alaska region closely matches the Bristol Bay 

197 
study region with the exception of Kodiak and the Aleutian Islands. Our analysis excludes 

Kodiak but includes an insignificant portion of visitors to the Aleutian Islands. 

Since Alaska Visitor Statistics Program counts out-of-state visitors only, we calculate visitor 

volume originating within the state based on Littlejohn and Hollenhorst (2007) and Colt and 

Dugan (2005) resident share of between ten and eleven percent. We treat visitation to Katmai 

NPP separate from other areas of the Bristol Bay region. Visitor volume and expenditure for 

Katmai NPP are from Fay and Christensen (2010) and for the remaining Bristol Bay area are 

from McDowell Group (2007a). We net out sport fishing and hunting visitation in Katmai NPP 

using Littlejohn and Hollenhorst (2007) and for the rest of the region by applying the McDowell 

Group (2007a and 2007b) estimate. We assume equal expenditures for residents and nonresidents because the non-resident per person expenditure estimate in both cases does not include 

the cost of travel to and from Alaska. For the expenditure categories associated with nonconsumptive use, we modeled the final demand vector based on Fay and Christensen (2010). 

These expenditures categories include transportation within Alaska, food, lodging, guiding 

services, supplies, licenses, etc. For most non-residents all in-state travel expenditures are 

included, based on the assumption that the primary reason for the travel to Alaska is the visit the 

Bristol Bay region. We allocated these expenditures within a commodity by industry matrix to 

form the final demand vector that’s then passed to the ISER I-O Model developed by Goldsmith 

(2000). For all of these estimates, we paid special attention to the potential for double counting 

and addressed those issues. 

Note, all direct jobs are in the Bristol Bay region but the residency of workers and the location 

where these workers spend their income is difficult to trace. Multiplier jobs are divided between 

Bristol Bay and Southcentral Alaska. Multiplier jobs are assumed to be all taken by residents of 

the region where they occur. Peak and annual average direct wages are assumed to be equal.

(Subsistence). 

We estimate annual expenditures related to subsistence activities for households based on the 

only publically available source (North Slope Borough, 1993) and adjust for inflation to 2009$. 

This estimate is justified as results from similar subsistence surveys are similar (Peterson et al., 

1992). We assume that every household in the region participates in subsistence activities with 

varying degrees of involvement and expense. We assume Native households to be participating 

in subsistence extensively resulting in the entire per household expenditure, whereas Non-Native 

households are assumed to be less involved with about a quarter of expenditures related to 

subsistence activities compared to Native households as indicated by North Slope Borough 

(1993). Due to the lack of data, the economic significance is quite small if compared to 

commercial fishing or non-consumptive use, both in terms of the market jobs and the payroll 

generated. For the expenditure categories related to subsistence, we assume maintenance and 

repair of boats and trucks to amount to 10% of total annual expense each, purchase of boats and 

trucks (10% each), hunting equipment (7%), fuel, repair, and parts (13% each). 

Note, all direct jobs are in the Bristol Bay region. Multiplier jobs are divided between Bristol 

Bay and Southcentral Alaska. Multiplier jobs are assumed to be all taken by residents of the 

region where they occur. Peak and annual average direct wages are assumed to be equal. 

198 
5.0 Bristol Bay Net Economic Values

The second general accounting framework under which ecosystem services can be measured is 

the Net Economic Value (NEV) framework. Net economic value is the value of a resource or 

activity that is over and above regular expenditures associated with engaging in an activity or 

visiting a resource area. The framework for this accounting perspective is the standard federal 

guidelines for estimating net economic benefits in a system of national accounts (Principles and 

Standards, U.S. Water Resources Council 1985). EPA (2010) is a more recent and 

complementary set of guidelines. 

5.1 Commercial Fisheries

In addition to the regional economic impact of commercial fish harvest in the Bristol Bay, the 

commercial fishery has a net economic value related to the expected differences over time 

between the ex vessel revenues and the costs of participating in this fishery. One method for 

estimating this value is to look at the market prices for commercial fishing permits in the Bristol 

Bay. Bristol Bay commercial fishing permits are of two types, drift net permits and set net 

permits. Regulations closely control many aspects of this permitted commercial harvest, 

including types of nets, size of boats, areas fished, and start and end dates of season. The value 

of holding one of these perpetual commercial permits is reflected in the prices that these permits 

command when they are transferred between owners. These market prices reflect the value that 

commercial operators place on their right to fish the region. That value in turn is a judgment of 

the value of the net income stream that would reasonably be expected from operating the permit 

given current and expected future salmon harvest levels and salmon prices. 

In 2011, there were 1,862 salmon drift net permits in the Bristol Bay fishery and 981 salmon set 

net permits in the fishery. Every year a portion of these permits are sold and change hands. 

Since 1991, an annual average of 155 drift net permits and 89 set net permits have been sold and 

changed hands in the Bristol Bay fishery.27 Permit transfers each year generally account for 

approximately 8% to 10% of all issued salmon permits in the fishery.

The Commercial Fish Entry Commission also reports average permit transfer prices annually 

(and monthly) for the Bristol Bay salmon fishery.28 Over the period from 1991-2011 the average 

sales price for Bristol Bay drift net permits has been $149,000 (in constant 2011 dollars). The 

average price for set net permits over the same period has been $42,200. The 95% confidence 

interval on the mean drift net price for this period ranges from $105,500 to $192,700. For the set 

net permit transfers, the 95% C.I. on the mean sales price was between $28,700 and $55,700.29 

Table 65 presents the estimated 95% C.I. range of total Bristol Bay drift and set net salmon 

permit value based on the 1991-2011 permit transfer data. For both types of permits it is 

27 The Alaska Fish and Game Commercial Fish Entry Commission publishes annual data on permit transfers at, 

http://www.cfec.state.ak.us/RESEARCH/12-1N/12-1N.htm 28 A long time series of monthly and annual permit transfer prices is continuously updated at, 

http://www.cfec.state.ak.us/pmtvalue/mnusalm.htm 29 Over the period 1991-2011, a total of 3,246 Bristol Bay drift net salmon permits and 1,867 set net salmon permits 

were reported sold by the Commercial Fish Entry Commission.

199 

 
estimated that the total value of the permits ranges from approximately $225 million to $414 

million.

In order to be comparable to other annual net economic values in this analysis (such as sport 

fishing or sport hunting) the market value of commercial fishing permits must be converted into 

an annual value reflecting expected annual permit-related net income. The market value of the 

permits can be annualized using an appropriate amortization (or discount) rate. The decision to 

sell a commercial fishing permit at a given price is an individual (or private) decision. In 

deciding on an acceptable sales price, a permit holder considers past profits from operating the 

permit, risk associated with future operation of the permit (both physical and financial), and 

many other factors. All these considerations weigh on how heavily a permit seller discounts 

(reduces) potential future profits from fishing the permit in order to arrive at a lump-sum value 

for the permit. Huppert et al. (1996) specifically looked at Alaska commercial salmon permit 

operations and sales and estimated the individual discount rate on drift net permit sales in the 

Bristol Bay and surrounding fisheries. This discount rate was estimated from both profitability 

and permit sales price data. Huppert et al. estimated the implied discount rate appropriate for 

annualizing permit sales prices in this setting at 13.52%. This estimate was consistent with 

previous estimates for the fishery.30 Use of the 13.52% discount rate from Huppert results in an 

estimated annual permit net profit or net income associated with Bristol Bay commercial salmon 

fishing of between $30.4 million and $55.9 million. 

Table 65. Current Bristol Bay Salmon Fishing Permit Numbers and sale prices, 2011 

Permit type Number 

of 

permits

Current market value Total 

Lower Value -

95% 

Confidence 

Interval

Upper Value -

95% 

Confidence 

Interval

Lower Value - 95% 

Confidence Interval

Upper Value -

95% Confidence 

Interval

Salmon (Drift net) 1862 105,500 192,700 196,500,000 358,800,000

Salmon (Set net) 981 28,700 55,700 28,100,000 54,700,000

 Total 224,600,000 413,500,000

 Estimated annual net income

(at 13.52% real discount rate) $30,400,000 $55,900,000 

Just as there is an implied net economic value associated with the fishing aspect of the Bristol 

Bay commercial salmon fishery, as outlined above, there is also a net economic value associated 

with expected future profits from investments in fish processing facilities in the region. Data on 

Bristol Bay salmon processor average aggregate profit levels is not published. Table 31, above, 

shows estimated profit (loss) margins for two years. Clearly, as with permit prices, processor 

30 Huppert, Ellis and Nobel (1996) estimated the real discount rate associated with sales of Alaska drift gill-net 

commercial permits of 13.52%. Karpoff (1984) estimated the discount rate from sales of Alaska limited entry 

permits at 13.95%. 

200 

 
profits are highly variable year-to-year. The average value-added associated with salmon 

processing for the Bristol Bay fishery is generally equal to or more than the ex-vessel value. 

Salmon processors in the Bristol Bay fishery have an “oligopsony” market structure, in that a 

small number of buyers of raw fish exist in the market. Additionally, these buyers are largely 

“price makers” in that they set the price paid per pound to fishermen each season. Given the 

unique relationship between fisherman that the small number of processors in the Bristol Bay, it 

is estimated that processors derive profits (net economic value) equal to that earned by 

fishermen. Therefore, for the purposes of this report it is estimated that the NEV for salmon 

producers is equal to that for the fishing fleet. 

A second estimate of estimated annual net income for the Bristol Bay commercial salmon 

harvest and processing sectors is derived from data presented in a 2003 study of the industry 

(Link et al. 2003). The 2003 report, titled “An analysis of options to restructure the Bristol Bay 

salmon fishery”, includes estimates of both Bristol Bay harvester and processor annual profits 

(net income) for the period 1990-2001. These estimates can be scaled to 2011 values using both 

changes in general price levels (CPI-U) and changes in harvester permit values. The table below 

(Table 66) shows the estimation of 2011 harvester and processor net income estimated from the 

Link et al. (2003) report.

Use of this second set of net income estimates and assumptions leads to a calculation of 

estimated harvest and processing sector net income that is near the upper 95% bound of the 

estimates calculated in this report. While the analysis based on 1990-2001 data presented above 

does suggest that the Table 65 analysis significantly undervalues the harvest sector, while the 

assumption of an equal processing sector net income somewhat overvalues the processing sector. 

The net effect is that the range of values for the combined harvest and processing sectors include 

values significantly below the estimate developed by the second (Table 66) analysis above. For 

purposes of presenting a conservative range of value estimates for the commercial salmon sector, 

an estimate of total harvester and processor net incomes from $60.8 to $111.8 million is used.

201 
Table 66. Estimation of Total 2011 Net Income for the Bristol Bay Salmon Harvest and Processing Sectors 

based on Reported 1990-2001 Net Income (Link et al. 2003).

Parameter Assumption/operation Value

(A) BB Commercial Salmon Harvester Sector Average Annual Net Income Estimation

Average 1990-2001 harvest 

sector net income

Data from Link et al (2003). Table 12 

(p.43). 

$93.7 million

Average annual BB 

commercial salmon fishing 

sector net income (1990-2001) 

in 2011 dollars 

Annual values updated to 2011 dollars using 

CPI-U $113.15 million

Adjusted 2011 profitability 

based on differences between 

1990-2001 average permit 

values and 2011 permit values 

The correlation between profitability in year 

X and permit sales price in year x+1 for this 

period is 0.857. Based on this observed 

close relationship, net income is scaled by 

the ratio of 2011 permit prices to the average 

1990-2001 price, or by 79.27% 

$89.69 million

(B) BB Salmon Processing Sector Average Annual Net Income Estimation

Average BB net income of the 

salmon processing sector for 

the years 1990-2001 in 2011 

$. (Link et al. 2003) 

There is no observed correlation between 

processor profits and permit prices 

(r=0.053). Average processor profits are 

assumed to be a constant 23.3% of harvester 

profits (the average ratio observed in the 

1990-2001 data by Link (2003)) 

$20.90 million

(C)Estimated Sum of Harvest and Processing Sectors Average Annual Net Income

Total estimated annual harvester and processor net income (2011$) derived 

from 1990-2001 data 

$110.59 million

(D) Estimated Range of Harvest and Processing Sector Average Annual Net Income

Range of estimates developed in this analysis 

$60.8 to $111.8 

million

5.2 Subsistence Harvest

The Alaska Department of Fish and Wildlife, Division of Subsistence reports that most rural 

families in Alaska depend on subsistence fishing and hunting. ADF&G surveys of rural 

202 
communities find that from 92% to 100% of sampled households used fish, 79% to 92% used 

wildlife, 75% to 98% harvested fish, and 48% to 70% harvested wildlife. Because subsistence 

foods are widely shared, most residents of rural communities make use of subsistence foods 

during the course of the year. The subsistence food harvest in rural areas constitutes about 2% of 

the fish and game harvested annually in Alaska. Commercial fisheries harvest about 97% of the 

statewide harvest, while sport fishing and hunting take about 1%. Though relatively small in the 

statewide picture, subsistence fishing and hunting provide a major part of the food supply of 

rural Alaska (Subsistence in Alaska, a 2000 Update 

http://www.subsistence.adfg.state.ak.us/download/subupd00.pdf ).

The Alaskan subsistence harvest is not traditionally valued in the marketplace. Because the 

subsistence resources are not sold, no price exists to reveal the value placed on these resources 

within the subsistence economy. The prices in external markets, such as Anchorage, are not 

really relevant measures of subsistence harvest value. The supply/demand conditions are unique 

to the villages, many of which are quite isolated. Native preferences for food are strongly held 

and often differ from preferences in mainstream society. Additionally, because these are highly 

vertically-integrated economies, substantial value-added may occur before final consumption 

(such as drying, or smoking fish and meats). In their research on estimating the economic value 

of subsistence harvests, Brown and Burch (1992) suggest that these subsistence harvests have 

two components of value, a product value, and what they call an “activity value.” The product 

value is essentially the market value of replacing the raw subsistence harvest. The activity value 

would primarily include the cultural value of participating in a subsistence livelihood. The 

activity value component is also associated with the value of engaging in subsistence harvest and 

food processing activities. This activity value would include maintaining cultural traditions 

associated with a subsistence livelihood.

Duffield (1997) estimated the value per pound of Alaskan subsistence harvest though use of a 

cross-sectional hedonic model of community-specific harvest per capita and community per 

capita income levels. This “wage-compensating differential model” essentially estimates the 

average tradeoff across communities between per-capita subsistence harvest (in pounds of usable 

harvest) and per capita income levels. In essence, residents of rural Alaskan communities 

tradeoff the opportunity to have higher income in a less rural environment with the opportunity 

to harvest larger amounts of subsistence resources in more rural communities. 

There is a substantial economics literature that utilizes the hedonic wage, or wage compensating 

differential model. For example, estimates of the trade-off of wages and workplace risk of 

mortality are the basis of the statistical value of life estimates widely used in regulatory analysis 

of ambient air and other standards (EPA 2008). There is also a literature that relates wages and 

amenity values as revealed through choice of location (e.g. Henderson 1982, Clark and Khan 

1988). These later models are generally applied to intercity data sets, such as across U.S. 

Standard Metropolitan Statistical Areas (SMSA) These models are also used to estimate the 

benefits and costs of climate change (e.g. Maddison and Bigano 2003). 

The application of a compensating wage model to a cross-section of Alaska Villages and towns 

is consistent with the view that these Alaska cash-subsistence economies are not just a transitory 

203 
phase in economic development. Rather the village economies represent an equilibrium that is a 

function of individual choice of where to live and work (Wolfe and Walker 1987; Kruse 1991). 

Wolfe and Walker (1987) were the first to estimate a statistical relationship between wage 

income and subsistence livelihoods using harvested usable pounds as a measure of subsistence 

productivity. Wolfe and Walker were interested in factors that influenced subsistence 

productivity, including construction of roads, settlement activity and income. The data was 

based on extensive surveys of Alaska villages undertaken by the applied anthropology group at 

Alaska Fish and Game, Division of Subsistence. Duffield (1997) used the Wolfe and Walker 

dataset for 98 villages in a compensating wage specification to inform subsistence harvest 

valuation in the context of the Exxon Valdez oil spill litigation. Hausman (1993), who 

represented the defendant in the case (Exxon) also estimated a compensating wage model using 

the Wolfe and Walker dataset. Hausman introduced the use of applying an instrumental variable 

approach to estimating the model, since wages and subsistence harvests are jointly determined.

Hausman’s (1993) estimate of the value of subsistence harvests (1982 dollars) was $33.60 per 

pound and Duffield’s (1997) was quite similar at $32.46. The estimated Hausman and Duffield 

harvest income models are now based on 30 year-old data. Indexing these results using average 

Alaska personal income per capita suggests that were this same relationship to hold today, total 

subsistence harvest NEV would be on the order of $75.58 per pound. In order to avoid making 

the assumption that the income—harvest relationship observed in the early 1980s was still valid, 

the Duffield (1997) model was updated using the most recently available per capita income,31

subsistence harvest,32 education,33 and cost of living data34 for the 90 communities included in 

both the Hausman and the Duffield models. 

The updated estimated wage compensating differential model shown in Table 66 uses a twostage least squares methodology and a linear specification. The two-stage least squares method 

is used to statistically address the fact that income and harvest levels in the communities are at 

least partly co-determined. The first stage of the model uses an instrumental variable (the 

percent of adults in each community with 4 or more years of college education) along with the 

remaining regional indicator variables to predict adjusted gross income per capita for each 

community. This predicted income level then was used in the second stage regression. The 

model explains 54% of the observed variation in harvest levels across communities, and a large 

majority of the 14 explanatory variables are significant at the 90% level of confidence or greater. 

The implied value per pound of subsistence harvest is calculated from the parameter estimate for 

Adjusted Gross Income Per Capita. The implied value per pound is the negative inverse of the 

income parameter (-0.01162). [(1/-0.01162)*-1 = $86.06] 

31 American Community Survey 5-year averages 2006-2010 (Table B19301) www.census.gov/acs/ 32 Alaska Fish and Game Department of Subsistence , http://www.adfg.alaska.gov/sf/publications/ 33 American Community Survey 5-year averages 2006-2010 (Table GCT1502) www.census.gov/acs/ 34 McDowell Group, Alaska Geographic Differential Survey: 2008.

204 

 
Table 67. Estimated Two-Stage Least Squares Wage Compensating Differential Model of Subsistence 

Harvest in 90 Alaska Communities (Duffield 1997).

Variable Parameter Estimate

Intercept 936.45

(137.89)***

Adjusted Gross Income Per 

Capita

-0.01162

(0.0051)**

Alaska Peninsula -174.227

(119.08)

Copper Basin -522.132

(86.37)***

Kenai Peninsula -448.975

(120.61)***

Kodiak -465.551

(111.31)***

North Slope 227.2387

(172.49)

NW Arctic -112.557

(227.61)

N Cook Inlet -548.580

(230.87)**

Prince William Sound -248.607

(173.95)

South East -314.787

(103.27)**

South West -265.364

(101.56)**

Upper Tanana -514.022

(130.35)***

Urban -590.972

(169.66)***

West -22.1552

(105.28)

Observations 90

R-Squared 0.536

Endogenous Variable Adjusted Per Capita personal income (BEA 2010) (adjusted to 

Anchorage dollars using cost-of-living index)

Instrumental Variable % of adults with 4 or more years of college (plus region indicator 

variables)

*=significant at 90% confidence level; **=significant at 95% confidence level; ***=significant 

at 99% confidence level.

205 
One difference between the Hausman and Duffield models and the updated subsistence model is 

in the per capita income measure used. Hausman and Duffield both used Alaska Department of 

Revenue data on community level adjusted gross income (AGI). However, Duffield’s updated 

model utilized average community per capita personal income. This second measure is the more 

appropriate income measure in that it includes certain amounts that are deducted from total 

income in the calculation of AGI. The updated income measure is consistently larger than the 

Alaska AGI originally used, with the latter being on average an estimated 70% of the former.35

The magnitude of the income measure used is directly proportional to the estimated value of 

subsistence harvest NEV per pound calculated from the estimated model income parameter. For 

purposes of this report, a range of values in the following analysis uses both the estimated $86.06 

value, based on the updated dataset and adjusted per capita personal income, and a lower bound 

estimate of $60.24 per pound ($86.06*0.70) based on the assumption of consistently using 

Alaska AGI. 

Based on both the Hausman (1993) and Duffield (1997) analyses, in principle the correct way to 

value subsistence harvests is to use the compensating wage differential approach. With reference 

to the Brown and Burch (1992) perspective, the compensating wage estimate includes both 

product and activity value. Duffield (1997) also reports a replacement cost estimate of just 

product values for subsistence harvests at $13.28 per pound.36 In 2009 dollars, this product 

value is estimated at $18.86 per pound.37

Table 67 shows the accounting of ADF&G Division of Subsistence estimates of total annual 

subsistence harvest in most communities in Bristol Bay. This total has been adjusted to include 

population in the region not included in the ADF&G subsistence harvest estimates. In total, we 

estimate that about 2.6 million usable pounds of subsistence harvest per year occur in the Bristol 

Bay region. Valued at an estimated range of $60.24 to $86.06 per pound, this harvest results in 

an estimated net economic value annually for subsistence harvest of between $154.4 and $220.6 

million (Table 69).

35 http://www.irs.gov/uac/SOI-Tax-Stats---Historical-Data-Tables “Table 4. Comparison of Personal Income in the 

National Income and Product Accounts (NIPA) with Adjusted Gross Income (AGI). For Specified Tax Years, 1990-

2005).

36 This value is the simple average of the replacement cost of lost harvest between two definitions of households in 

the Duffield (1997) paper. p. 109, Table 4.

37 It should be noted that a significant component of subsistence harvest in some communities is marine mammals, a 

resource with a very high market replacement cost.

206 

 
Table 68. Estimated Total Annual Bristol Bay Subsistence Harvest (usable pounds of harvest)

Bristol Bay Area Community /year of harvest 

data

Total Usable Pounds Raw Subsistence 

Harvest

Aleknagik 1989 64,824

Clark's Point 1989 75,020

Dillingham 1984 563,618

Egegik 1984 41,856

Ekwok 1987 91,655

Igiugig 2005 27,100

Iliamna 2004 51,121

King Salmon 2008 117,062

Kokhanok 2005 115,600

Koliganek 2005 187,891

Levelock 2005 36,363

Manokotak 2000 131,716

Naknek 2008 143,616

New Stuyahok 2005 198,390

Newhalen 2004 131,480

Nondalton 2004 58,712

Pedro Bay 2004 12,852

Pilot Point 1987 26,112

Port Alsworth 2004 21,147

Port Heiden 1987 41,616

South Naknek 2008 21,172

Ugashik 1987 9,768

Togiak City 2000 200,982

Twin Hills 2000 36,926

Total surveyed communities 2,406,599

Un-surveyed communities (estimated) 156,714

Total including un-surveyed areas 2,563,313

Source: Estimates of community-specific subsistence harvest levels are contained within the Subsistence Technical 

Report Series, available at, http://www.adfg.alaska.gov/sf/publications/

It should be noted that although the total annual value of subsistence harvests implied by the 

wage compensating differential model is large, simply the market replacement cost of these 

resources is fully 32% of the lower-bound estimate and 22% of the upper-bound estimate. In 

addition to simply procuring the usable pounds of raw subsistence harvest, many of these 

resources have substantial value-added in the form of processing by drying, smoking, or other 

preserving, cleaning, or other processing methods. This value-added is also captured within the 

context of the wage compensating differential model. 

Another perspective on the revealed economic significance of subsistence harvests in Bristol Bay 

is seen by comparing the implied NEV associated with subsistence activities and reported per 

capita income in the region. For the 7,475 Bristol Bay residents (74% of who are Native 

Alaskan) subsistence harvests valued at $60.24 per pound imply that the value of these harvests 

are about 34% of their total combined per capita 2009 personal income (as reported by BEA) 

plus estimated total subsistence value. Valued at $86.06 per pound, subsistence harvest value is 

207 
about 42% of total income and subsistence value. Another component of subsistence value is the 

relative effort or allocation of time put into the subsistence sector instead of spending time in the 

cash income sector. The effort put into the subsistence sector is estimated to be the same or more 

than the full-time equivalent jobs included in the cash sector. 

Table 69. Estimated Net Economic Annual Value of Bristol Bay Area Subsistence Harvest

Estimates of Subsistence Value

Per Pound

Value

Total 

Subsistence 

Harvest

Total Annual Value 

(Million 2009 $)

Value based on Harvested Product 

Value $18.86 2,563,313 $48.3

Value based on Wage Compensating 

Differential Approach (Adjusted to AK 

DOR AGI income measure))

$60.24 2,563,313 $154.4

Value based on Wage Compensating 

Differential Approach (Based on BEA 

per capita personal income measure)

$86.06 2,563,313 $220.6

5.3 Sport Fishing Net Economic Value

In addition to the direct expenditures that Bristol Bay area sport anglers make each year, there is 

substantial net economic value attached to the trips these anglers take to the region. A measure 

of the net economic value of sport fishing trips is the amount anglers are willing to pay over and 

above the costs of their trips. The 2005 Bristol Bay angler survey asked respondents a series of 

questions relating to what they spent on their fishing trip, and how much, if any, more they 

would have been willing to spend to have the same experience. This willingness to pay is also 

referred to as net economic benefit. There is a large economics literature on estimating sport 

fishing net economic benefits (Rosenberger and Loomis 2001). The method for estimating these 

benefits here is contingent valuation using the so called “payment card” question format. 

Respondents were presented with a set of amounts ranging from $0 to $2,000, and asked to mark 

the greatest additional increase in spending they would have made to take the same trip. Table 

72 shows the mean willingness to pay estimate for the two groups. The net economic value from 

the survey data was estimated using an interval estimation model.

Following questions on their trip expenditures, survey respondents were asked whether they felt 

their trip was worth more than the amount they actually spent. Those who answered “yes” were 

then asked, “What is the largest increase over and above your actual costs that you would have 

208 
paid to be able to fish your primary destination?” Respondents were presented with a series of 

dollar amounts ranging from $10 to $2,000. Table 70 shows the percentage of both resident and 

nonresident Bristol Bay anglers who responded that they would have paid the various additional 

amounts to take their Bristol Bay fishing trip.

Table 70. Responses to Current Trip Net Economic Value Question

NONRESIDENTS RESIDENTS

Percent Percent

Willing to Pay More 63.0% 73.3%

$ 10 1.1% 0%

$ 25 0.3% 2.1%

$ 50 0.2% 3.6%

$ 100 6.2% 16.5%

$ 250 16.2% 20.5%

$ 500 15.9% 7.5%

$ 750 2.5% 3.6%

$ 1,000 9.1% 0%

$ 1,500 3.7% 0%

$ 2,000 2.3% 3.6%

Other amount 4.3% 15.7%

 

The estimates of willingness to pay models based on the Table 70 data were developed using a 

maximum likelihood interval approach (Welsh and Poe 1998). As noted, respondents were 

asked to choose the highest amount he or she was willing to pay from a list of possible amounts. 

It was inferred that the respondent’s true willingness to pay was some amount located in the 

interval between the amount the respondent chose and the next highest amount presented. The 

SAS statistical procedure LIFEREG was used to estimate the parametric model of willingness to 

pay based on the underlying payment card responses. 

 

Table 71 shows the estimated parametric willingness to pay for trips to Bristol Bay fisheries. 

Nonresident anglers state their trip was worth approximately $500 more, on average, than they 

actually paid. Resident Bristol Bay anglers stated they were willing on average to pay an 

additional $352 for their most recent trip. These estimates are similar to other estimates for 

Alaska sport fishing (Duffield et al. 2002; Jones and Stokes 1987). 

Table 71: Estimated Mean Willingness to Pay for Anglers’ Recent Trip to Bristol Bay

Statistic Non-residents Residents

Estimated mean willingness to pay in addition to trip 

costs for those willing to pay more $793 $480

Percent of respondents willing to pay more for their 

trip 

63.0% 73.3%

Net willingness to pay for Bristol Bay fishing trips for 

all anglers

$500 $352

209 
The net economic value per trip estimates shown in Table 71 were calculated from the results of 

a bivariate statistical model of the payment card response data using a variant of survival 

analysis to examine censored interval data. The chi-square test of significance for the key 

parameters from these models show the estimated coefficients to be statistically significant. 

Based on an estimated annual use level of 12,464 trips for nonresidents, and 16,903 trips for 

Alaska residents, we estimate that the annual net economic value of fishing trips in the Bristol 

Bay region is approximately $12.2 million. 

Table 72. Estimated Willingness to Pay for Sportfishing Fishing in the Bristol Bay Region

Residents Nonresidents

Estimated mean net willingness to pay $ 352 $ 500

Estimated number of trips/year 16,903 12,464

Total estimated Net Economic Value $5,950,093 $6,228,350

 Total annual value $12,178,443

5.4 Sport Hunting Net Economic Value

As in the case of sport fishing, there is additional value associated with sport hunting, above 

what is actually spent on the activity. Table 73 details the estimation of annual net economic 

value of big game hunting in the Bristol Bay region. Table 73 utilizes ADF&G estimates of 

hunter numbers in the game management units associated with the Bristol Bay area, and on 

estimates of net willingness to pay per trip for hunting (from Miller and McCollum 1994, 

adjusted to current, 2009 dollars). It is estimated that nonresident net economic value of Bristol 

Bay hunting is approximately $1 million annually. The annual net economic value of big game 

hunting in the Bristol Bay region for Alaska residents is estimated at about $380,000. Therefore 

the total annual estimated net economic value of big game hunting in this region is $1.4 million. 

Table 73. Estimated annual big game hunting net economic value for Bristol Bay region

Species / Statistic Nonresidents Non-local residents

trips Value/ trip NEV Trips Value/ trip NEV

Moose 352 $581 $ 204,549 291 $ 268 $ 77,998

Caribou 230 $ 640 $ 147,298 311 $ 250 $ 77,892

Brown bear 741 $ 897 $ 665,028 717 $ 307 $ 220,535

Total $ 1,017,000 $ 376,000

210 
5.5 Wildlife Viewing and Tourism Net Economic Value

The 1991 study by McCollum and Miller estimated the net economic value of wildlife watching 

trips in Alaska. These values adjusted to current dollars results in an estimated value per trip of 

$199. Using the 40,164 visitor trips to the region we estimate a 2009 net economic value of 

wildlife watching of about $8.1 million. 

5.6 Total Net Economic Value and Present Value and Inter-temporal 

Issues

Commercial salmon fishery net economic values for fishermen are derived by annualizing the 

total value of the perpetual permits to fish the Bristol Bay waters held by fishermen. The value of 

these permits is reflected in the prices paid for them when they are exchanged in an open market 

and reported by the Commercial Fish Entry Commission. These are on the order of $156,000 for 

a drift gillnet permit in 2011, and have been as high as $200,000 as recently as 1993. 

The total value of Bristol Bay permits—calculated as the number of permits multiplied by the 

permit price—provides an estimate of the total present discounted value of expected future 

profits from the fishery. Based on 1991-2011 average permit sales prices (in constant 2011 

dollars) the estimated 95% confidence interval on the total value of Bristol Bay permits (both 

drift net and set net fisheries combined) was between $224.6 million and $413.5 million. 

Multiplying the total value of a permit by the rate of return a permit holder demands on a permit 

investment provides a measure of the annual profit permit holders expect to earn. Using a 

13.52% amortization (or discount) rate estimated by Huppert et al. (1996) suggests that annual 

expected profits (net economic value) from Bristol Bay commercial fishing is currently between 

$30.4 million and $55.9 million. Note that this does not include expected profits from fish 

processing. 

Net income for the processing sector is more difficult to estimate. Relative to the fishing sector, 

with ex-vessel value of $181 million in 2010, the processing sector provides an approximately 

equal value added of $209 million in 2010 (first wholesale value of $390 million in 2010 less the 

cost of buying fish at the ex-vessel cost of $181 million (Figure 79). However, information on 

profits or net income for this sector is difficult to obtain. For purposes of this report, net income 

in the processing sector is assumed to be equal to the value for the fishing fleet.

211 
Selected Bristol Bay Salmon Processor Costs, 2001-2009

0

50

100

150

200

250

300

200120022003200420052006200720082009

millions of nominal dollars

Other costs

and profits

Cost of labor

(fish processing

earnings)

Cost of fish

(ex-vessel

value)

Source: ADFG, ADLWD

Figure 79. Selected Bristol Bay Salmon Processor Costs: 2001-2009 

The sportfish net economic values are angler recreational benefits (consumer surplus) in Duffield 

et al. (2007). These estimates are consistent with values from the extensive economic literature 

on the value of sportfishing trips (for example Duffield, Merritt, and Neher 2002). Sport hunting 

values are based on studies conducted in Alaska by McCollum and Miller (1994). Annual direct 

use net economic values for recreation use of the Bristol Bay area is estimated to be $22.1 

million, including $12.2 million for sport fishing, $1.8 million for sport hunting, and $8.1 million 

for wildlife viewing and other tourism. In addition to recreationist’s net benefits, net income 

(producer’s surplus) is recognized by the recreation and tourism industry. This is a component 

that remains to be estimated. 

Subsistence harvests are valued based on the willingness-to-pay revealed through tradeoffs of 

income and harvest in choice of residence location (Duffield 1997). 

Based on the National Research Council panel on guidelines for valuation of ecosystem services 

(NRC 2005), it is important to include intrinsic or passive use values (aka “non-use” values) in 

any net economic accounting of benefits (Figure 80).

212 
Figure 80. Flows of Ecosystem Services (adapted from (National Research Council 2005)) 

A major unknown is the total value related to existence and bequest motivations for passive use 

values. Goldsmith et al. (1998) estimated the existence and bequest value for the federal wildlife 

refuges in Bristol Bay at $2.3 to $4.6 billion per year (1997 dollars). There is considerable 

uncertainty in these estimates, as indicated by the large range of values. Goldsmith’s estimates 

for the federal wildlife refuges are based on the economics literature concerning what resident 

household populations in various areas (Alberta, Colorado) (Adamowicz et al. 1991; Walsh et al. 

1984; Walsh et al. 1985) are willing to pay to protect substantial tracts of wilderness. Similar 

literature related to rare and endangered fisheries, including salmon, could also be applied here. 

It is possible that from a national perspective the Bristol Bay wild salmon ecosystems and the 

associated economic and cultural uses are sufficiently unique and important to be valued as 

highly as wilderness in other regions of the U.S. Goldsmith et al.’s (1998) estimates assume that 

a significant share of U.S. households (91 million such households) would be willing to pay on 

the order of $25 to $50 per year to protect the natural environment of the Bristol Bay federal 

wildlife refuges. The number of these households used in Goldsmith’s analysis is based on a 

willingness to pay study (the specific methodology used was contingent valuation) conducted by 

the State of Alaska Trustees in the Exxon Valdez oil spill case (Carson et al. 1992). These 

213 
methods are somewhat controversial among economists, but when certain guidelines are 

followed, such studies are recommended for use in natural resource damage regulations (for 

example, see Ward and Duffield 1992). The findings of the Exxon Valdez study were the basis 

for the $1 billion settlement between the State and Exxon in this case. Willingness-to-pay 

analyses have also been upheld in court (Ohio v. United States Department of Interior, 880 F.2d 

432-474 (D.C. Cir.1989)) and specifically endorsed by a NOAA-appointed blue ribbon panel 

(led by several Nobel laureates in economics) (Arrow et al. 1993). 

While the primary source of passive use values for Bristol Bay are likely to be with national 

households (lower 48), it is important to note that the Alaska natives living in Bristol Bay also 

likely have significant passive use values for the wild salmon ecosystem. For example, Boraas 

(2011) quotes Bristol Bay natives in saying “We want to give to our children the fish, and we 

want to keep the water clean for them...It was a gift to us from our ancestors, which will then be 

given to our children.) (Boraas p. 33). 

Goldsmith’s estimates for just the federal refuges may be indicative of the range of passive use 

values for the unprotected portions of the study area. However, there are several caveats to this 

interpretation. First, Goldsmith et al. estimates are not based on any actual surveys to calculate 

the contingent value specific to the resource at issue in Bristol Bay. Rather, they are based on 

inferences from other studies a method referred to as benefits transfer. Second, these other 

studies date from the 1980’s and early 1990’s and the implications of new literature and methods 

have not been examined. Additionally, the assumptions used to make the benefits transfer for 

the wildlife refuges may not be appropriate for the larger Bristol Bay study area which includes 

not only the wildlife refuge, but also two large national parks. This topic is an area for future 

research.

Table 74. Summary of Bristol Bay Wild Salmon Ecosystem Services, Net Economic Value 

per Year (Million 2009 $)

Ecosystem Service Low estimate High estimate

Commercial salmon fishery

 Fishing Fleet $30.4 $55.9

 Fish Processing $30.4 $55.9

Sport fishing $12.2 $12.2

Sport hunting $1.4 $1.4

Wildlife viewing / tourism $8.1 $8.1

Subsistence harvest $154.4 $220.6

 Total Direct Use Value $236.90 $354.10

Table 74 details the estimates of annual net economic values for the major sectors tied to the 

Bristol Bay Ecosystem. The scope of this characterization report is to use existing data, 

information, and estimates to provide a comprehensive picture of the economic structure and 

associated values related to the Bristol Bay Ecosystem. The estimates shown in the table are 

based on a variety of sources and methods, and based on data and estimates from a range of 

years. These estimates have been presented in constant 2009 dollars. 

214 
Differences in net economic values across sectors are driven by several factors, including the 

number of individuals impacted, the type of market structure, and the scope of resources and 

resource services included in the estimates. For instance, the estimates for subsistence NEV are 

between 38% and 73% higher than for the commercial salmon fishery (and processing) sectors. 

These two sectors have several key differences, however. The market for commercial salmon is 

highly competitive, with other fisheries (as well as farmed salmon) providing strong price 

competition and thus keeping profits and implied NEV low in the sector. Additionally, the 

estimates of commercial fishery NEV are based on commercial fishing permit sales prices. 

These sales of generally less than 10% of active permits in a given year represent “marginal” 

prices, rather than the “average permit value” to all permit holders. Those permit holders who do 

not sell value their permits more highly than those who do. The commercial fishery NEV 

estimates, therefore, are based on conservative marginal values while the subsistence values are

less conservative “average” values. A third difference between these estimates is that the 

commercial fishery NEV is narrowly tailored to salmon fishing and processing, while the 

subsistence harvest NEV includes all resources used (including land and marine mammals, fish, 

shellfish, and plants). Salmon harvest only accounts for about one-half of all Bristol Bay 

subsistence harvest (in usable raw harvest weight).

The estimates in Table 74 are for annual net economic values. Since these are values for 

renewable resource services that in principle should be available in perpetuity, it is of interest to 

also consider their present value (e.g. total discounted value of their use into the foreseeable 

future). Recent literature (OMB 2003; EPA 2010; Weitzman 2001) provides some guidance on 

the use of social discount rates for long term (intergenerational) economic comparisons. 

The controlling guidance document for discounting in Federal cost benefit analysis, OMB 

Circular A-4 (2003), generally requires use of discount rates of 3% and 7%, but allows for lower, 

positive consumption discount rates, perhaps in the 1 percent to 3 percent range, if there are 

important intergenerational values. The circular states,

“Special ethical considerations arise when comparing benefits and costs across generations. 

Although most people demonstrate time preference in their own consumption behavior, it 

may not be appropriate for society to demonstrate a similar preference when deciding 

between the well-being of current and future generations. Future citizens who are affected by 

such choices cannot take part in making them, and today’s society must act with some 

consideration of their interest. 

One way to do this would be to follow the same discounting techniques described above and 

supplement the analysis with an explicit discussion of the intergenerational concerns (how 

future generations will be affected by the regulatory decision). Policymakers would be 

provided with this additional information without changing the general approach to 

discounting. 

Using the same discount rate across generations has the advantage of preventing timeinconsistency problems. For example, if one uses a lower discount rate for future generations, 

then the evaluation of a rule that has short-term costs and long-term benefits would become 

more favorable merely by waiting a year to do the analysis. Further, using the same discount 

rate across generations is attractive from an ethical standpoint. If one expects future 

215 
generations to be better off, then giving them the advantage of a lower discount rate would in 

effect transfer resources from poorer people today to richer people tomorrow. 

Some believe, however, that it is ethically impermissible to discount the utility of future 

generations. That is, government should treat all generations equally. Even under this 

approach, it would still be correct to discount future costs and consumption benefits generally 

(perhaps at a lower rate than for intragenerational analysis), due to the expectation that future 

generations will be wealthier and thus will value a marginal dollar of benefits or costs by less 

than those alive today. Therefore, it is appropriate to discount future benefits and costs 

relative to current benefits and costs, even if the welfare of future generations is not being 

discounted. Estimates of the appropriate discount rate appropriate in this case, from the 

1990s, ranged from 1 to 3 percent per annum.” (p. 35)

The key question in deciding on an appropriate discount rate or range of rates for analysis is 

whether the Bristol Bay ecosystem is a resource of intergenerational significance. Clearly, this 

resource base and ecosystem that has been relied on for thousands of years by Alaska natives, 

and now has a long-term significance to a growing number of nonnatives, is the very definition 

of an intergenerational resource. 

Weitzman (2001), conducted an extensive survey of members of the American Economic 

Association, and suggests a declining rate schedule, which may be on the order of 4 percent 

(real) in the near term and declining to near zero in the long term. He suggests a constant rate of 

1.75% as an equivalent to his rate schedule. Weitzman’s work is cited both in the EPA guidance 

(EPA 2000) and in OMB guidance (Circular A-4 (2003) ). Table 75 shows the estimated net 

present value in perpetuity of direct use values within the Bristol Bay Ecosystem. The table 

shows a range of alternative discount rates from the standard “intragenerational” rates of 7% and 

3% to the more appropriate “intergenerational” rates for the Bristol Bay case of 1.75% and 1.0%. 

The entire range of NPV estimates in the table is from $3.4 to $35.4 billion. The range of 

estimated direct use NPV of the resource using the more appropriate intergenerational discount 

rates is from $13.5 to $35.4 billion. These estimates may be quite conservative as they do not 

include estimates of passive use values held by those living outside the Bristol Bay Region, but 

are limited to direct economic uses of the wild salmon ecosystem services.

Table 75. Estimated Net Present Value of Bristol Bay Ecosystem Net Economic Use Values 

and Alternative Assumed Perpetual Discount Rates

Estimate 

Annual Value

Net Present Value (million 2009 $)

7% Discount 3% Discount 1.75% Discount 1% Discount

Low Estimate $236.9 $3,384 $7,897 $13,537 $23,690

High Estimate $354.1 $5,059 $11,803 $20,234 $35,410

216 
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224 
AN ASSESSMENT OF POTENTIAL MINING IMPACTS ON 

SALMON ECOSYSTEMS OF BRISTOL BAY, ALASKA 

VOLUME 3—APPENDICES E-J

Appendix F: Biological Characterization: Bristol Bay Marine 

Estuarine Processes, Fish and Marine Mammal 

Assemblages 
Biological Characterization: An Overview of

Bristol, Nushagak, and Kvichak Bays; 

Essential Fish Habitat, Processes, and

Species Assemblages

December 2013

Prepared by

National Marine Fisheries Service, Alaska Region

National Marine Fisheries Service, Alaska Region
ii
iii

PREFACE

The Bristol Bay watershed supports abundant populations of all five species of Pacific salmon 

found in North America (sockeye, Chinook, chum, coho, and pink), including nearly half of the 

world’s commercial sockeye salmon harvest. This abundance results from and, in turn, 

contributes to the healthy condition of the watershed’s habitat. In addition to these fisheries 

resources, the Bristol Bay region has been found to contain extensive deposits of low-grade 

porphyry copper, gold, and molybdenum in the Nushagak and Kvichak River watersheds. 

Exploration of these deposits suggests that the region has the potential to become one of the 

largest mining developments in the world. 

The potential environmental impacts from large-scale mining activities in these salmon habitats 

raise concerns about the sustainability of these fisheries for Alaska Natives who maintain a 

salmon-based culture and a subsistence lifestyle. Nine federally recognized tribes in Bristol Bay 

along with other tribal organizations, groups, and individuals have petitioned the U.S. 

Environmental Protection Agency (EPA) to use its authority under the Clean Water Act to 

restrict or prohibit the disposal of dredged or fill material from mining activities in the Bristol 

Bay watershed. In response to these petitions and to better understand the potential impacts of 

large-scale mining, the EPA is conducting an assessment of the biological and mineral resources 

of the Bristol Bay watershed to inform future government decisions related to protecting and 

maintaining the physical, chemical, and biological integrity of the watershed. As part of this 

process, the EPA requested assistance from National Marine Fisheries Service (NMFS) as the 

agency responsible for the nation’s living marine resources.

The EPA assessment focuses on salmon populations, their habitat, and the supporting ecosystem 

processes in the Nushagak and Kvichak watersheds. Under Section 305(b)(2) of the MagnusonStevens Fishery Conservation and Management Act (Magnuson Stevens Act), NMFS has 

designated the region’s fresh and marine waters as Essential Fish Habitat (EFH) for anadromous 

salmon, groundfish, and other invertebrate species. EFH for salmon consists of the aquatic 

habitat necessary to support a long-term sustainable salmon fishery and salmon contributions to

healthy ecosystems. Natural wild salmon populations are currently stable and abundant, and their 

habitat at the ecosystem scale, from headwater streams through marine processes, is functionally 

intact.

This report summarizes our current understanding of the region’s oceanic and freshwater 

influence on the nearshore areas of Nushagak and Kvichak Bays; of the invertebrate, fish, and 

marine mammal assemblages found east of 162° West longitude; and of the range and 

distribution of Bristol Bay salmon. This report also highlights our understanding of the trophic 

contribution of Bristol Bay salmon both as smolt leaving the watersheds and as returning adults 

and our understanding of the importance of estuaries and nearshore habitat as nutrient rich

nursery areas for numerous marine species. 
iv

ACKNOWLEDGEMENTS

This report was compiled and written by Douglas Limpinsel, NOAA Fisheries, Habitat 

Conservation Division, Alaska Region. Robert McConnaughey, NOAA Fisheries, Alaska 

Fisheries Science Center, and Jeanne Hanson and Jim Hale, NOAA Fisheries, Alaska Regional 

Office, provided technical and editorial reviews that improved the organization and readability of 

this report. The following people also contributed in various ways to this discussion: 

Alaska Department of Fish and Game: Timothy Baker, Lowell Fair, Laura Jemison, Lori 

Quakenbush 

Bristol Bay Native Community and Associates: Robert Andrew, Gregory Andrew, Peter 

Andrew, Daniel Chythlook, Susan Flensburg, Tina Tinker 

NOAA/NMFS - Alaska Fisheries Science Center and National Marine Mammal Lab: 

Robin Angliss, Kerim Aydin, Steve Barbeaux, Troy Buckley, Daniel Cooper, Keith Cox, 

Douglas Demaster, Edward Farley, Robert Foy, Sarah Gaichas, Jeffry Guyon, Paula Johnson, 

Sonja Kromann, Robert Lauth, Jamal Moss, Philip Mundy, James Murphy, Daniel Nichol, Olav 

Ormseth, Elizabeth Sinclair, Thomas Wilderbuer 

NOAA/NMFS - Alaska Region, Habitat Conservation Division: Matthew Eagleton, Jon

Kurland, Brian Lance, John Olson, Eric Rothwell

NOAA/NMFS - Alaska Region, Protected Resources Division: Michael Williams

University of Alaska - Fairbanks and Bristol Bay Campus: Ken Coyle, Todd Radenbaugh 

University of Washington - School of Fisheries and Joint Institute for the Study of the 

Atmosphere and Ocean: Nancy Kachel, Katherine Myers (retired), Thomas Quinn, Daniel 

Schindler.
v

ABSTRACT

This report summarizes our current understanding of Bristol Bay as Essential Fish Habitat (EFH) 

for salmon at various life stages as well as for other species of marine invertebrates, fish, and 

marine mammals. As an ecosystem, the currently healthy habitat of the bay both supports and 

results from the interactions between natural processes and the presence and abundance of all

five species of Pacific salmon. As a keystone species, Bristol Bay salmon facilitate energy and 

nutrient transport to and from the inner bay’s terrestrial watersheds and the marine ecosystems of 

the eastern Bering Sea. Outbound migrations of billions of salmon smolts provide nutrition to 

numerous trophic levels and marine species, and salmon returning in their adult phase provide a 

valuable nutrient source to marine mammals and subsidize watersheds in the form of salmonderived nutrients.
vi

Table of Contents

Bristol Bay - Overview ................................................................................................................................. 1 

Marine Influence ....................................................................................................................................... 2 

Fresh Water Influence ............................................................................................................................... 2 

Bristol Bay - Fish and Invertebrate Assemblages ......................................................................................... 3 

Nushagak and Togiak Bays ...................................................................................................................... 3 

Nearshore .............................................................................................................................................. ...4

Offshore .................................................................................................................................................... 4 

Bristol Bay - Salmon..................................................................................................................................... 6 

Range and Distribution ............................................................................................................................. 6 

Salmon Contribution to Trophic Levels.................................................................................................... 8 

Bristol Bay - Marine Mammals .................................................................................................................... 9 

Pinnipeds................................................................................................................................................... 9 

Whales: Toothed Whales........................................................................................................................ 11 

Whales: Baleen Whales .......................................................................................................................... 12 

Discussion ................................................................................................................................................... 13 

Habitat Condition.................................................................................................................................... 13 

Water....................................................................................................................................................... 13 

Estuaries .................................................................................................................................................. 14 

Salmon Food Habits................................................................................................................................ 14 

Salmon Critical Size ............................................................................................................................... 15 

Trophic Contribution .............................................................................................................................. 15 

Summary ................................................................................................................................................. 17 

Bibliography ............................................................................................................................................... 19 

Tables .......................................................................................................................................................... 43 

Table 1: Fish and Invertebrate Species List ........................................................................................... 43 

Table 2: Marine Mammals Species List ................................................................................................. 53
BRISTOL BAY

Overview

Bristol Bay is a large, shallow sub-arctic bay (Buck et al. 1974, Straty 1977, Straty and Jaenicke 

1980, NOAA 1997 and 1998, Wilkinson 2009). Its benthic topography is essentially flat, with an 

average gradient of 0.02 percent and a maximum depth of approximately 70 meters at the 162

° 

West longitude line (Moore 1964, Buck et al. 1974). The substrate throughout the bay consists of 

silts and mud and vast aggregates of sand, gravel, cobble, and boulder (Sharma et al. 1972, 

NOAA 1987; see Smith and McConnaughey 1999 for a detailed description of benthic 

substrate). 

° Fig1. Bristol Bay. Waters east of the 162 West longitude line are defined by the North Pacific Fishery Management Council as the Bristol Bay

No-Trawl-Zone Protected Area. 

The chemical properties of Bristol Bay waters are highly variable and constantly shift under the 

influence of dramatic currents, tide cycles, and severe weather events from the Bering Sea in the 
2

west and the influence of terrestrial freshwater discharges from Nushagak River, Kvichak River, 

and a number of other, smaller rivers in the east. 

Earlier literature distinguishes the inner bay from the outer bay by physical properties such as 

salinity, temperature, and turbidity (Buck et al. 1974, Straty 1977, Straty and Jaenicke 1980). 

More recent investigations, however, distinguish different parts of the bay by depth, with an 

inner or coastal domain from the shoreline to 50 meters deep, a middle domain from 50 to 100 

meters deep, and outer domain beyond the 100-meter contour (Kinder and Coachman 1978, 

Kinder and Schumacher 1981, Coachman 1986, Schumacher and Stabeno 1998, Stabeno et al.

2001).

Inner bay processes are continuously fed large volumes of fresh water from numerous 

watersheds, with salinity increasing toward the 162° West longitude line, while currents from the 

eastern Bering Sea move through the bay in a counter-clockwise gyre under the influence of 

tides ranging from 3 to 23 feet (Buck et al. 1974, Straty 1977, Straty and Jaenicke 1980).

Marine Influence 

Bristol Bay is essentially an extension of the eastern Bering Sea. Flood tides from the North 

Pacific enter the eastern Bering Sea through several Aleutian Island passes contributing to the 

Aleutian North Shore Current (Schumacher et al. 1979, Reed and Stabeno 1994, Stabeno et al. 

2002 and Stabeno et al. 2005). East of Unimak Pass, the marine current flows northeast as the 

Bering Coastal Current along the Alaska Peninsula and into Bristol Bay where it turns in a 

counter-clockwise gyre (Kachel 2011, pers. comm.). The majority of this current diverts north 

near the 50-meter contour and eventually flows west and then north around Cape Newenham 

toward Nunivak and Pribilof Islands (Coachman 1986). Part of the current, however, continues 

east and delivers marine nitrates, carbon, phosphates, and silica into the inner bay. These mix 

with fresh water discharges and dissolved organic material from several river systems at the 

eastern end of the bay (Buck et al. 1974, Stockwell et al. 2001, Kachel et al. 2002, Coyle and 

Pinchuk 2002, Stabeno and Hunt 2002, Ladd et al. 2005).

Fresh Water Influence

Estuarine characteristics of Nushagak and Kvichak Bays are the result of continual freshwater 

runoff from several watersheds (Straty 1977, Buck 1974, Straty and Jaenicke 1980). Four large 

rivers flow into Nushagak Bay: the Igushik, Snake, Wood-Tikchik and Nushagak; and three 

rivers flow into Kvichak Bay: the Naknak, Alagnak, and Kvichak. The discharge of these rivers 

contributes to the estuarine character of these bays (Buck et al. 1974). Of the rivers that drain

into the inner domain, we measure the discharge of only two, the Nushagak and Kvichak Rivers, 

which together drain 22,172 square miles (14,190,134 acres) of watershed (USGS 2011). The 

Nushagak River has a mean annual discharge of 28,468 cubic feet per second (CFS) based on 

readings from the Nushagak River gauge (USGS No. 15302500, 23,645 cfs) and the Wood River 
3

gauge (USGS No. 15303000, 4,823 cfs). The Kvichak River has a mean annual discharge of 

17,855 cfs based on readings from the USGS gauge (15300500) located at the outlet of Lake 

Iliamna. If these three gauges represent an accurate estimate, the total discharge is 46,323 cfs, or 

approximately 33,536,000 acre feet squared per year. This fresh water influence dominates 

Nushagak and Kvichak Bays between April and November creating the characteristic estuarine 

water chemistry. Other sources of fresh water also discharge into Bristol Bay and influence the 

water quality, but their flows are not monitored and cannot be currently included in estimates.

Out-welling freshwater contributions are significantly higher in spring and summer when winter 

snow and ice melt and rains are prevalent. As a result, summer ebb tide currents often 

considerably exceed the flood tides. Discharge from the watersheds keeps the waters of 

Nushagak and Kvichak Bays colder in early spring; however, by mid-summer these temperatures 

reverse with warmer terrestrial discharges (Buck et al. 1974). Furthermore, the counterclockwise current pushes freshwater discharge from Kvichak Bay into Nushagak Bay which 

maintains a slightly lower salinity. Generally, lower sea surface salinity measurements are 

observed in Nushagak Bay than in Kvichak Bay (Radenbaugh 2011, pers. comm.).

Because of this seasonal terrestrial freshwater influence, Nushagak and Kvichak Bays exhibit the 

lowest salinity and greatest temperature fluctuation in Bristol Bay (Buck et al. 1974, Straty and 

Jaenicke 1980). Similar temperature and salinity gradients have been observed in the inner 

domain (temperature 11.4 °C, salinity 28.9%) and the middle domain (temperature 7.4 °C, 

salinity 32.7%) (NOAA 1987). Marine characteristics then dominate off shore. More recent 

analyses and descriptions of oceanographic currents and nutrients generally describe shallow, 

wind-driven, well-mixed, homogenous, nutrient-laden waters (Coyle and Pinchuk 2002, Kachel 

et al. 2002, Stabeno and Hunt 2002).

Bristol Bay - Fish and Invertebrate Assemblages

Nushagak and Togiak Bays 

Recent mid-water surveys in Nushagak Bay have found the dominant species in numbers and 

biomass to include bay shrimp (Crangon alaskensis) and Gammarid amphipods and mysiids 

(Gammarus sp.) and confirm the presence of walleye pollock (Theragra chalcogramma, a 

marine pelagic species) and flatfish species (Pleuronectiformes) such as yellowfin sole (Limanda 

aspera) in this nearshore habitat (depths less than 30m), along with numerous other fish and 

invertebrate species (Radenbaugh 2010, pers. comm.). Additional surveys specific to Nushagak 

Bay shore line at low tide captured over 6,000 fish of 17 species. Two species accounted for 95% 

of the total catch: rainbow smelt and pond smelt (Hypomesus olidus) (Johnson 2012). 

Recent surveys conducted in both Nushagak and Togiak Bays encountered over 40 fish and 

invertebrate species (Olmseth 2009). Most captured individuals were less than 20 cm in length. 

Of these species, shrimp (Crangonidae) and rainbow smelt (Osmerus mordax) were the most 
4

abundant species encountered, occurring in almost every trawl and beach seine, and were 

especially dominant in very shallow water with mud and silt bottoms. Forage fish species 

identified by these surveys were salmon smolt (Salmonidae), capelin (Osmeridae) and Pacific 

herring (Clupeidae), as well as poachers (Agonidae), sculpin (Cottoidea), flatfish 

(Pleuronectidae and Bothidae), and greenling (Hexagraaidae).

Nearshore

In addition to the surveys of Nushagak and Togiak Bays, surveys of other nearshore waters of 

Bristol Bay document forage fish species such as Pacific herring, eulachon (Thaleichthys 

pacificus), capelin, and rainbow smelt (Warner and Shafford 1981, Mecklenburg et al. 2002, 

Bernard 2010). In an evaluation of historical data, Gaichas and Aydin (2010) found that salmon 

smolts rank as one of the top ten nearshore forage fish. Pacific herring are also known to spawn 

in nearshore waters of Togiak Bay and along the northern shoreline of the Alaska Peninsula 

(Bernard 2010). Sand lance (Ammodytes hexapterus) have been found in particular abundance in 

these nearshore waters of the Alaska Peninsula (McGurk and Warburton 1992). 

Surveys conducted to characterize the presence and distribution of forage fish species in Bristol 

Bay nearshore waters also identified several species of groundfish: Pacific cod (Gadus 

macrocephalus) and walleye pollock, as well as juvenile sockeye salmon (Oncorhynchus nerka) 

(Isakson et al. 1986, Houghton 1987). During one phase of these surveys, juvenile sockeye 

salmon were more abundant than any forage fish or juvenile ground fish species encountered. 

Present again, though in fewer numbers, were Pacific herring, capelin, pond and surf smelt, and 

eulachon. The presence, abundance, and biodiversity of these species in Bristol Bay nearshore 

habitat support our current understanding of these areas as nutrient rich fish nurseries.

Similar surveys of nearshore habitat conducted in neighboring Alaskan waters further illustrate

the complexity and diversity of fish and invertebrate assemblages (Norcross et al. 1995, 

Abookire et al. 2000, Abookire and Piatt 2005, Arimitsu and Piatt 2008, Thedinga et al. 2008, 

Johnson et al. 2010). Anadromous species, as well as groundfish, forage fish, and invertebrate 

species, are all well represented in many of these nearshore areas in a variety of different habitat 

and substrate types and water conditions.

Offshore 

Fisheries surveys of the offshore waters of Bristol Bay have been conducted since the 1930s. The 

AFSC has conducted annual surveys in the eastern Bering Sea offshore and outer Bristol Bay 

waters since 1982 using standardized gear and repeatable methods. These surveys identify 

numerous groundfish species inhabiting the eastern Bering Sea and Bristol Bay, generally deeper 
5

than the 15-20m contour (Lauth 2010)1. The more common species represented in the surveys 

are cod and pollock (Gadidae); fifteen species of flatfish (Pleuronectiformes); forage fish species 

such as herring, eulachon, capelin, smelts, sand lance, and sandfish; and dozens of other species 

well represented, such as skate (Rajidae), poachers (Psychrolutidae), greenling (Hexagrammos), 

rockfish (Scorpaenidae), sculpin (Cottidae), crab (Cancer), and salmon. In Table 1 we identify 

all species known to inhabit these waters.

The hundreds of fish species and invertebrate species that inhabit Bristol Bay waters contribute 

to trophic levels at various life stages; tides and currents transport and distribute larval marine 

fish and invertebrate species from offshore to nearshore nursery areas (Norcross et al. 1984, 

Lanksbury et al. 2007). The relationship between marine and nearshore processes and species 

presence in Bristol Bay has been well documented in the life histories of species such as walleye 

pollock, red king crab (Paralithodes camtschaticus), and yellowfin and rock sole. Larval forms 

of each species are transported and concentrated in nutrient-rich nearshore habitat. These four 

species illustrate relevant examples of recognized marine species with population segments that 

in a larval or juvenile phase rely on nearshore marine habitat (depths less than 30 m) for refuge 

and nutrition.

Walleye pollock are generally recognized as a pelagic species spawning in open marine waters 

(Bailey et al. 1999). As Coyle (2002) notes, pollock in their larval and juvenile forms are known 

to be transported into nearshore nursery zones: the current carries the eggs and larvae along the 

north shore of the Alaska Peninsula and into the nearshore nursery zones of Bristol Bay (Napp et 

al. 2000). A recent investigation of trophic interactions shows that juvenile pollock feed on 

euphasiid and mysiid populations nearshore, especially mysiids, which have been shown to be 

more abundant in the diets of pollock found in the northern nearshore zones than those found in 

deep water (Aydin 2010). 

Bristol Bay is also home to the second-largest population of red king crab (Dew and 

McConnaughey 2005, Chilton et al. 2010). Although red king crab of both genders and several 

stages of maturity occur throughout central Bristol Bay, immature larvae and juveniles are often 

concentrated along nearshore areas. The Aleutian North Shore and Bering Coastal currents 

transport larval king crab from the eastern Bering Sea to inner Bristol Bay (Dew and 

McConnaughey 2005). Larval red king crab (smaller than 2 mm) settle in cobble and gravel 

substrates of Kvichak Bay2 (Armstrong et al. 1981, McMurray 1984, Loher et al. 1998); 

juveniles are present along the nearshore zone in the Togiak district (Armstrong et al. 1993,

1 All species were found east of the 162° West longitude line and in waters deeper than 15m. Because the surveys represent a snap shot of species 

present at a particular time, they may not represent complete species diversity. Also, because standardized trawl gear mesh is size selective, 

juvenile and larval specimens of a species may not be well represented. It is important to note that salmon species at any life stage may not be well 

represented due to seasonality of surveys and species migration. 

2 Larval red king crab were present on substrates less than 70 to 80 feet (approximately 21 to 24 meters) at mean low water in Kvichak Bay. 
6

Olmseth 2009). These juvenile phases inhabit nearshore rocks, shell hash, or a variety of 

biological cover in shallow depths (from 5 to 70 meters).

Yellowfin and rock sole are among several species of flatfish that inhabit the eastern Bering Sea 

and for which nearshore substrates (depths less than 30 meters) in Bristol Bay are optimal habitat 

(McConnaughey and Smith 2000, Lauth 2010; Table 1). Life histories of these species and other 

flatfish take advantage of the same currents that transport larvae into nearshore nursery areas 

(Nichol 1998, Wilderbuer et al. 2002, Norcross and Holladay 2005, Lanksbury et al. 2007, 

Cooper et al. 2011). Larval and juvenile yellowfin sole are abundant in shallow nearshore areas 

along the northern shore and Togiak Bay (Olmseth 2010, Nichol 1998, Wilderbuer et al. 2002).

These findings for Pollock, red king crab, and yellowfin and rocksole substantiate our 

understanding of nearshore and estuary zones as nutrient rich fish nurseries, providing juvenile 

fish species with greater forage opportunity in the form of abundant invertebrate populations.

Bristol Bay – Salmon

The ecological role of Bristol Bay salmon is complex. Salmon facilitate energy and nutrient 

exchange across multiple trophic levels from terrestrial headwaters through estuarine and marine 

ecosystems. Each species migrates through these waters at slightly different times depending on 

life history and watershed of origin. Because of their abundance, distribution, and overall 

economic importance, Bristol Bay sockeye salmon have been more extensively studied than 

other salmonids in the region. Generally, once in marine waters juvenile salmon spend their first 

summer in relatively shallow waters on the southeastern Bering Sea shelf, feeding, growing and 

eventually moving offshore into the Bering Sea basin and North Pacific Ocean (Meyers et al. 

2007, Farley et al. 2011, Farley 2012, pers. comm.).

Range and Distribution 

The Magnuson-Stevens Act defines EFH as “waters and substrate necessary to fish for spawning, 

breeding, feeding, or growth to maturity.” For salmon, EFH consists of those fresh and marine 

waters needed to support healthy stocks in order to provide long-term sustainable salmon 

fisheries. Because of the broad range and distribution of salmon in Alaskan waters, all marine 

waters over the continental shelf in the Bering Sea extending north to the Chukchi Sea and over 

the continental shelf throughout the Gulf of Alaska and in the inside waters of the Alexander 

Archipelago are defined as EFH for all juvenile salmon (Echave et al. 2011). EFH for immature 

and mature Pacific salmon (Oncorhynchus spp) includes nearshore and oceanic waters, often 

extending well beyond the shelf break (Echave et al. 2011). 

In their emigration phase, anadromous juvenile salmon occupy shallows of estuaries and 

nearshore zones, although timing, duration, and abundance vary throughout the year depending 

on species, stock, and life history stage (Groot and Margolis 1991, Quinn 2005). Nearshore and 
7

estuarine habitats act as transition zones supporting osmoregulatory changes (the physiological 

changes by which smolt adapt between fresh and salt water) (Hoar 1976 and 1988, Clarke and 

Hirano 1995, Dickhoff et al. 1997). Studies have shown that sub-yearling salmon in the Pacific 

Northwest move repeatedly between zones of low and high salinity, and although no studies 

have yet shown Bristol Bay salmon to behave similarly, the Pacific Northwest studies suggest 

that such behavior may be integral to the survival and growth of young salmon (Healey 1982, 

Levings 1994, Levings and Jamieson 2001, Simenstad et al. 1982, Simenstad 1983, Thom 1987). 

The eastern Bering Sea shelf is an important nursery ground for juvenile and sub-adult Bristol 

Bay sockeye salmon (Farley et al. 2009). Early models of eastern Bering Sea and North Pacific 

salmon stocks describe migrations and broad distributions to the south and east in winter and 

spring and to the north and west in summer and fall (French et al. 1975, French et al. 1976, 

Rogers 1987, Burgner 1991, Shuntov et al. 1993). These studies were the first to suggest that 

population migrations crossed the Aleutian Island chain into the North Pacific (Myers et al.

1996, Myers 2011 pers. comm.). Recent investigations incorporating genetic (DNA) and scale 

pattern analysis validate these observations (Bugaev 2005, Farley et al. 2005, Habicht et al.

2005, Habicht et al. 2007, Myers et al. 2007). Investigations conducted in autumn 2008 and

winter 2009 substantiate the migration of juvenile Bristol Bay sockeye salmon from the Eastern 

Bering Sea shelf to the North Pacific, south of the Aleutian Island chain (Habicht et al. 2010, 

Farley et al. 2011, Seeb et al. 2011):

In their first oceanic summer and fall, juveniles are distributed on the eastern Bering Sea 

shelf, and by the following spring immature salmon are distributed across a broad region 

of the central and eastern North Pacific. In their second summer and fall, immature fish 

migrate to the west in a band along the south side of the Aleutian chain and northward 

through the Aleutian passes into the Bering Sea. In subsequent years, immature fish 

migrate between their summer/fall feeding grounds in the Aleutians and Bering Sea and 

their winter habitat in the North Pacific. In their last spring, maturing fish migrate across 

a broad, east-west front from their winter/spring feeding grounds in the North Pacific, 

northward through the Aleutian passes into the Bering Sea, and eastward to Bristol Bay. 

(Farley et al. 2011) 

More than 55% of ocean age-1 sockeye salmon sampled during the 2009 winter survey in the 

North Pacific were from Bristol Bay stocks. These broad seasonal shifts in distribution likely 

reflect both genetic adaptations and behavioral responses to environmental cues (e.g., prey 

availability and water temperature) that are mediated by bioenergetic constraints (Farley et al.

2011). This extensive range and distribution suggest that Bristol Bay sockeye salmon contribute 

to the trophic dynamics in the Bering Sea as well as the North Pacific. 
8

Salmon Contribution to Trophic Levels

A recent evaluation was conducted by the AFSC Ecosystem Modeling Team to assess the 

contribution of Nushagak and Kvichak River sockeye salmon to trophic dynamics of the eastern 

Bering Sea shelf and North Pacific ecosystems (Gaichas and Aydin 2010). Using estimates of 

outbound salmon smolt survival and adult returns, researchers calculate that these two rivers 

account for nearly 70% (56,000 of 81,100 tons) of adult salmon biomass in the eastern Bering 

Sea. In the open ocean, sockeye salmon represent 47% of total estimated salmon biomass present 

in the eastern subarctic gyre (Aydin et al. 2003). Bristol Bay sockeye salmon from the Nushagak 

and Kvichak Rivers compose 26% of total sockeye salmon biomass and 12% of total salmonid 

biomass in the entire eastern subarctic gyre. The Nushagak and Kvichak Rivers produce a 

significant portion of all salmon in offshore marine ecosystems and the majority of salmon on 

the eastern Bering Sea shelf, thus producing the majority of juveniles and returning adults in the 

salmon biomass (Gaichas and Aydin 2010). The AFSC’s evaluation indicates sockeye salmon 

from these river systems rank among the top ten forage groups, comparable to Pacific herring or 

eulachon as a nutritional source for other marine species in the Bering Sea and North Pacific. 

One study supports this rational indicating that outbound salmon smolt export substantial levels

of nitrogen and phosphorus seaward (Moore and Schindler 2004).

Returning adult salmon enrich watersheds in the form of salmon-derived nutrients (Gende et al. 

2002, Schindler et al. 2003, Wilson et al. 2004), and these nutrients are flushed back into 

estuaries by out-welling

3 river waters. Salmon-derived nutrients are transported in the form of 

partial and whole salmon carcasses or particulates and dissolved nutrients (carbon, nitrogen and 

phosphorous) moving from watersheds back to the estuaries. Early studies identified the flow of 

salmon carcasses out of the coastal watersheds into marine estuaries as a result of high 

precipitation events (Brickell and Goering 1970, Richey et al. 1975). Salmon-derived nutrients 

stimulate primary production in estuaries where nitrogen and phosphorus are often limiting 

nutrients (Rice and Ferguson 1975). Estuarine algae use dissolved nutrients, in turn feeding 

copepods which feed juvenile salmon (Fujiwara and Highsmith 1997). One investigation 

identified several species of marine invertebrates feeding on salmon carcasses (Reimchen 1994). 

Stationary whole salmon carcasses were completely consumed in a week. Gende (2004) 

estimated that 43% of the tagged salmon carcasses washed into the study estuary within days. 

More recent investigations conducted in Alaskan waters suggest that 60% of the total nutrient or 

biomass transported into the watershed by salmon may be transported back to the estuary 

(Johnston et al. 2004, Mitchell and Lamberti 2005).

3 Terrestrial freshwater runoff from large river systems and watersheds drains into marine estuaries. In referenced 

literature, this runoff is often referred to as “outflow” or “outwelling.” Outwelling freshwater chemistry, 

temperature, and nutrient plumes influence marine estuary chemistry, productivity, and salinity gradients. 
9

In Nushagak and Kvichak Bays, nutrients liberated from tens of millions of decomposing adult 

salmon likely have a significant influence on estuarine trophic interactions and biodiversity in 

the manner discussed above. Estuarine processes such as primary and secondary production and 

countless marine fish and invertebrate species benefit from this mass transport of nutrients. 

Numerous studies indicate that marine estuarine vegetation and larval and juvenile invertebrate 

and fish populations benefit from enrichment of nutrients flushed back into the marine estuaries. 

The influence of outwelling freshwater and nutrients from watersheds and terrestrial river 

systems on marine estuaries and processes can be substantial.

Bristol Bay - Marine Mammals

The eastern Bering Sea supports numerous species of marine mammals including whales 

(Cetacea) of the suborders Odontoceti (toothed whales and porpoise) and Mysticeti (baleen 

whales). Several species of seals (pinnipeds) are also represented (Otariidae, Phocidae, and 

Odobenidae) in these waters (Allen and Angliss 2011). Of marine mammals present in the 

eastern Bering Sea, twenty species occur in Bristol Bay waters in significant numbers and 

regularity (Table 2). Three species of baleen whale (fin, right and humpback whales) and one 

pinniped species (Western Distinct Population Segment Steller sea lion) found in Bristol Bay are 

listed as endangered under the Endangered Species Act. The seven species we discuss below are 

those Bristol Bay marine mammals known to feed on salmon.

In Bristol Bay, the presence of marine mammals and their prey species is highly variable 

depending on the season and location within the bay. For example, the presence and feeding 

habitats of sea lions or fur seals are difficult to identify because of variations in their seasonal 

range, in whether they are at sea or in rookeries, and in the migratory patterns of their prey. Less 

is known about pinniped prey selection in the open ocean because scat and stomach content 

studies are only conducted while specimens are on the rookery. Thus, the only prey species 

represented in dietary analysis are prey species near the rookeries.

Some marine mammal diet data show seasonal dependence on salmon. Several studies 

demonstrate that salmon are a prominent nutritional source for several marine mammal species 

(Pauly et al. 1998a). Many marine mammals, especially pinniped and ondontocete species, prey 

on adult and juvenile salmon in nearshore and estuary zones.

Pinnipeds 

Steller Sea lions 

Steller Sea lion predation on salmon has been confirmed by data from scat and stomach content 

studies from which researchers have estimated the level of consumption and frequency of 

occurrence (NMFS 1992, Merrick 1995, Merrick et al. 1997, Sinclair and Zeppelin 2002, Trites 

and Donnelly 2003, Jemison 2011, pers. comm.). Depending on seasonal range and migratory 
10

patterns, salmon ranked high as a selected prey species in Steller sea lion diets (Sinclair and 

Zeppelin 2002). The endangered western stock of Steller sea lions relies on salmon during 

summer; salmon rank second in frequency of occurrence in summer diets in regions sampled 

between 1990 and 1998 (Sinclair and Zeppelin 2002). These regions include the Bering Sea shelf 

and waters surrounding the Aleutian Islands, where salmon were noted to increase in diets during 

winter due to out-migrating sub-adult Bristol Bay salmon (Sinclair and Zeppelin 2002).

Fur seals

Fur seals also feed on salmon throughout the Pacific range, from California to Alaska (Perez and 

Bigg 1986). One more recent investigation conducted to determine prey species of northern fur 

seals in the Pribilof Islands indicates salmon composed part of the diet of fur seals on St. George 

and St. Paul Islands (Sinclair et al. 2008). Pacific salmon had a mean annual frequency of 

occurrence of 14.4%, and 10% in any one year on St. George and St. Paul Islands respectively. 

Similar nutrition studies of eastern Bering Sea northern fur seals indicate salmon rank second 

among fish in frequency of occurrence for animals on both Pribilof Islands from late July 

through September, 1990-2000 (Gudmundson et al. 2006). 

Harbor seals

Harbor seals also are found throughout Bristol Bay and the eastern Bering Sea and prey upon 

species of Pacific salmon (Jemison et al. 2000, Small et al. 2003, Allen and Angliss 2011, 

Jemison 2011, pers. comm.). The Bristol Bay population of harbor seals numbers approximately 

18,000 seals and is increasing (Allen and Angliss 2013). Lake Iliamna supports a year-round 

population of harbor seals, which are currently included as part of the Bristol Bay stock. The 

number of seals residing in Lake Iliamna is relatively small; aerial surveys of hauled-out harbor 

seals count as many as 321 (which counts do not reflect absolute abundance) (Mathisen and 

Kline 1992, Small 2001, Burns et al. 2012; Migura 2013, pers. Comm.). Although this 

population has colonized Lake Iliamna from Bristol Bay via the Kvichak River, no scientific 

evidence shows that harbor seals migrate to and from Bristol Bay. However, some residents and 

Alaska Native subsistence hunters in the Iliamna Lake area say that harbor seals are seen within 

the entire expanse of the Kvichak River and migrate between the lake and Bristol Bay (Migura

2013, pers. Comm.). Harbor seals have also been identified in the Nushagak and Wood River 

systems. In the Wood River system, harbor seals are observed in Lake Aleknagik (B. Andrew 

2011, pers. comm., D. Chythlook 2011, pers. comm., Tinker 2011, pers. comm.).

Spotted seals

Spotted seals have also been sighted in Bristol Bay. Other spotted seals tagged in Alaskan and 

Russian sectors of the Bering Sea show clear seasonal preference for nearshore habitat and 

associated fisheries, which suggests that spotted seals sighted in Bristol Bay may have a 
11

persistent presence there. These populations feed mostly on salmon, saffron cod (Eleginus 

gracilus), and herring (Burkanov 1989, Lowery et al. 2000). 

Whales: Toothed Whales 

Beluga whales

Beluga whales are abundant in Bristol Bay waters primarily from spring through fall near the 

mouths of the Kvichak, Nushagak, Wood, and Igushik rivers. Early studies document the 

importance and contribution of sockeye salmon for beluga nutrition (Brooks 1955). Lensink 

(1961) notes that belugas fare poorly in Bristol Bay when migratory (anadromous) fish are not 

available. In addition to following the general movements of its prey, belugas appear to feed 

specifically where their prey species are most concentrated. The frequency of occurrence of 

salmon species in beluga stomachs is correlated with the abundance of each species during their 

respective migrations (Brooks 1955). Studies conducted by Brooks in the 1950s further indicate 

that beluga whales feed on both juvenile and adult salmon, as well as on several other forage fish 

and invertebrate species (Klinkhart 1966). 

From 1993 to 2005, the beluga population increased in abundance by 4.8% per year, and while 

thresholds of prey abundance needed for belugas to thrive are not fully understood, the larger 

size of red salmon runs before and during the period covered by aerial surveys may partially 

explain the increased beluga numbers (Lowry et al. 2008). Belugas are well known to travel up 

these regional rivers in pursuit of salmon. They have been seen feeding on salmon in the 

Kvichak River past Levelock to the Igiugig Flats (Cythlook and Coiley 1994, G. Andrew 2011, 

pers. comm.). Traditional knowledge also indicates that beluga whales have also been seen in 

Lake Illiamna (M. Migura 2013, pers. comm.). In summer, belugas are routinely observed in the 

Nushagak River (P. Andrew 2011, pers. comm.). In the Wood River system, belugas have been 

observed in Lake Aleknagik (Fried et al. 1979, B. Andrew 2011, pers. comm, Tinker 2011, pers. 

comm).

Killer whales

Killer whales also inhabit Bristol Bay waters. They have been seen in nearshore waters and 

frequent the lower river reaches chasing and preying upon salmon and beluga whales (Frost and 

Lowry 1981, Frost et al. 1992, Allen and Angliss 2011, Quakenbush 2011, pers. comm.). In a 

recent observation (July 17, 2002), killer whales displayed cooperative feeding behaviors near 

the Nushagak spit. A pod formed a circle with their tails facing toward the center, flukes slapping 

on the surface of the water. A male killer whale emerged through the center of the circle with a 

mouth full of salmon (Tinker 2011, pers. comm.). In the Nushagak River, killer whales have 

been observed chasing both belugas and coho (Oncorhynchus kisutch) salmon (D. Cythlook 

2011, pers. comm.). In late fall, in the absence of beluga whales, killer whales pursue late-run 

and fall coho up the Nushagak River (P. Andrew 2011, pers. comm.).
12

Although they are opportunistic feeders, fish-eating killer whales outside of Bristol Bay show an 

affinity for salmon. In Prince William Sound, the results of a 14-year study of the diet and 

feeding habits of killer whales identify two non-associating groups of killer whale, termed 

resident and transient (Bigg et al. 1987). The resident groups (fish-eaters) appear to prey 

principally on salmon, preferring coho (O. kisutch) over other more abundant salmon species 

(Saulitis et al. 2000). Another distinct population of Alaskan fish-eating killer whales off the 

coast of British Columbia moves seasonally to target salmon populations (Nichol and Shackleton

1996). Field observations of predation and stomach content analysis of stranded killer whales 

collected over a 20-year period document 22 species of fish and one species of squid that 

dominated the diet of fish-eating resident-type killer whales (Ford et al. 1998). Despite the 

diversity of fish species taken in these studies, fish-eating resident killer whales showed a clear 

preference for salmon: 96% of fish taken were salmonids. Of the six salmonid species identified, 

by far the most common was Chinook (Oncorhynchus tshawytscha) representing 65% of the 

total sample. The second most common was pink at 17% (Oncorhynchus gorbuscha), followed 

by chum (6%) (Oncorhynchus keta), coho (6%), sockeye (4%), and steelhead (2%) 

(Oncorhynchus mykiss) (Ford et al. 1998). Although a separate population, Bristol Bay killer 

whales may have similar feeding behaviors. 

Sperm whales

Sperm whales are also known to prey upon salmon and have been sighted, however infrequently, 

in Bristol Bay. Sperm whales feed primarily on mesopelagic squid in the North Pacific, but have 

also been documented consuming salmon as well as several other species of fish (Tomilin 1967, 

Kawakami 1980).

Whales: Baleen Whales: Humpback Whales 

Investigations of baleen whale food habits in the North Pacific and Bering Sea have documented 

species such as humpbacks targeting small schooling fish populations. Salmon were among 

numerous species of fish identified (Nemoto 1959, Tomilin 1967, Kawamura, 1980). More 

recently, humpback whales have been observed off Cape Constantine in Bristol Bay in the spring 

of year, presumably feeding on schooling herring and possibly outmigrating salmon smolts (D. 

Cythlook 2011, pers. comm.). In southeast Alaska, humpback whales have been observed 

preying upon both wild and hatchery outbound salmon smolts as well as adult pink salmon 

(Straley et al. 2010, Straley 2011, pers. comm.). Humpback whales have been shown to exhibit 

site fidelity to feeding areas, and return year after year to the same feeding locations (Baker et al. 

1987, Clapham et al. 1997). There is very little interchange between feeding areas (Baker et al. 

1986, Calambokidis et al. 2001, Waite et al. 1999, Urban et al. 2000. The humpback whales 

observed off Cape Constantine may reasonably be assumed to exhibit a similar site fidelity for 

purposes of feeding. 
13

Discussion

The primary purpose of this report is to identify the range, distribution, and trophic contribution 

of salmon originating from the Nushagak and Kvichak watersheds and bays. In a broader 

context, this report also presents information on known species assemblages and environmental 

influences on the estuarine and marine habitat. This report also attempts to acknowledge other 

habitat attributes that influence nearshore and estuary conditions and are important to salmon 

smolt physiology and to the trophic dynamics that support the abundance and resilience of 

current salmon populations.

Habitat Condition 

The abundance, resilience, and stability of regional salmon populations are at once a product of 

and contribute to the currently healthy habitat, which includes the water quality. Natural 

ecosystem and hydro-geomorphic processes in the region remain functionally intact from 

headwater tributaries through marine waters. Salmon are abundant at various life history stages, 

which abundance influences and contributes to the productivity of other fisheries at multiple 

trophic levels. At their current abundance, salmon influence habitat condition in these watersheds 

by providing a rich source of nutrition to a broad range of invertebrates, fish, and marine 

mammals, as well as to countless terrestrial flora and fauna. Salmon enrich watersheds and 

influence water chemistry.

Water

Fish habitat includes not only structure such as hard substrate, reefs or rock, and vegetation such 

as eel grass or kelp, but also—and it seems odd to have to say so—the water itself. The success 

and abundance of a species are largely determined by the quality of the water, its temperature, its 

salinity, and its chemical composition, which includes the availability of nutrients necessary for 

life. If nutrient sources, forage opportunities, and prey are diminished, the habitat itself is 

changed, and all the dynamics of the food web are thus altered. 

Nushagak and Kvichak Bays resemble other Alaskan estuaries as subarctic and allochthonous 

(turbid) in nature. As discussed above, these waters are dominated by seasonal freshwater runoff 

from snow melt and rains. Turbidity in the bays minimizes photosynthesis, primary production, 

and associated algal blooms; however, nutrient is carried in outwelling discharge of detritus, 

dissolved organic material, and salmon-derived nutrients. These materials provide the essential 

nutrients and energy for lower trophic levels supporting assemblages of minute bacteria, fungi 

and algae, through larval stages of plankton, invertebrates, juvenile fish and salmon smolt. The 

abundance and availability of nutrient sources at the lower trophic levels are essential to the 

survival of salmon smolt in their early estuarine and marine phase. Successful smolt survival is 

reflected years later in the strength of returning adult runs and escapement.
14

Estuaries 

Although no studies to date have been conducted specifically identifying the importance of 

estuarine habitat to salmon smolt in Nushagak and Kvichak Bays, a number of other studies 

conducted in Alaska and the Northwest document several attributes of estuaries important to 

juvenile salmon smolt (Murphy et al. 1984, Heifetz et al. 1989, Johnson et al. 1992, Thedinga et 

al. 1993 and 1998, Koski and Lorenz 1999, Halupka et al. 2003, Koski 2009). Cited studies 

identify estuaries as an often preferred habitat choice for coho salmon, providing increased food 

and growth, expanding their nursery area, and increasing overall production from the watershed. 

The high productivity of some estuarine habitats in Alaska and the Northwest allows an array of 

life history patterns (Healey 1983). One such pattern involves rearing in both rivers and 

estuaries, allowing salmon to migrate and rear in estuaries for a summer and in some cases return 

and over-winter in rivers (Reimers 1971, Murphy et al. 1984, 1997, Harding 1993, Koski and 

Lorenz 1999, Miller and Sadro 2003, M. Wiedmer 2013, pers. comm.). Being able to move 

between estuary and river increases feeding opportunities, allows smolt to achieve critical size 

(as discussed below), and supports osmoregulatory change in their early marine phase. The 

dominant freshwater influence of Nushagak and Kvichak Bays supports osmoregulatory 

adjustment prior to entry into the highly saline marine phase. It should also be recognized that 

smolt outmigration coincides with increased freshwater influence in these estuaries. Similar 

studies and literature of northwest salmon substantiate the importance of estuarine habitat to 

salmon smolt survival (Rich 1920, Healey 1982, Levy 1992, Thorpe 1994, Groot and Margolis

1998, Bottom 2005, Quinn 2005, Koski 2009).

Studies focused on flatfish species in other regions further identify the importance of estuarine 

habitat as fish nurseries. Disproportionate numbers of juvenile flatfish from estuarine habitat 

compose adult populations found in nearshore marine waters (Brown 2006). In this instance, 

although estuarine habitat composes only about 6% of the available juvenile habitat, the estuary 

appears to be the source of approximately half of the adult fish collected in the region. These 

results validate previous findings further explaining the linkage between estuarine and nearshore 

habitats for other species (Yamashita et al. 2000, Forrester and Swearer 2002, Gillanders et al.

2003). As noted in this review, these nearshore waters are “fish nurseries” supporting numerous 

species in their larval and juvenile life history stages.

Salmon Food Habits

Studies of the feeding habits of North Pacific salmon in general (that is, not specific to Bristol 

Bay salmon) show that the species’ feeding habits vary by species, life stage, region, and 

seasonal prey availability. Prey species repeatedly identified were euphausiids, hyperiids, 

amphipods, copepods, pteropods, and chaetognaths. Egg, larval, and juvenile stages of numerous 
15

forage fish, groundfish, and invertebrate species were also identified. Landingham and 

Sturdevant (1997) report that the prey spectrum for juvenile salmon species was composed of 30 

taxa. The six taxa groups of most importance were calanoid copepods, hyperiid amphipods, 

euphausiids, decapods, larval tunicates and fishes. Other studies identify similar prey 

assemblages: euphausiids, hyperiids, amphipods, copepods, pteropods, chaetognaths, and 

polychaetes (Auburn and Ignell 2000, Orsi et al. 2000, Powers et al. 2006, Weikamp and 

Sturdevant 2008). Food habit studies conducted in Cook Inlet and Knik Arm further illustrate the 

importance of nearshore invertebrate prey assemblages for salmon smolt (Houghton 1987, 

Moulton 1997, summarized in USFWS 2009). Brodeur and Pearcy (1990) describe prey of all 

five North Pacific salmon and ocean-phase trout in all regions where they occur. 

These studies analyzed stomach-content data and reveal that juvenile salmon ingest substantial 

quantities of food while in nearshore and estuary habitat. Salmon smolts tended to be well 

nourished and in some cases demonstrated prolonged estuarine residence time feeding 

extensively on plentiful larval invertebrate and juvenile fish species. Although these studies are 

not specific to Bristol Bay, the salmon prey species identified in these studies are also abundant 

in the Nushagak and Kvichak Bays.

Salmon Critical Size 

The importance of abundant prey opportunities during the transition from fresh to marine waters, 

especially in the early marine phase, has been illustrated in “critical size” discussions. Earlier 

studies suggest that more slowly growing salmon smolt experience greater size-selective 

predation (Parker 1968, Willette et al. 1999). Smolt that fail to achieve a critical threshold size 

by late spring and early summer commonly fail to survive their first winter (Mahnken et al.

1982). Stunted smolt suffer protein-energy deficiency and are more likely to become prey for 

other marine species. Salmon smolt need to reach a critical size and strength to survive their first 

year in the open ocean (Beamish 2001 and 2004). Studies of Bristol Bay salmon in their marine 

phase in the eastern Bering Sea again suggest that reduced growth during their first year at sea 

may lead to substantial mortality (Moss et al. 2005, Farley et al. 2007). Greater nutrition and 

prey availability lead to larger juvenile salmon which gain a survival advantage over smaller 

individuals (Farley et al. 2007, Farley et al. 2011).

Trophic Contribution

Salmon-derived nutrients subsidize watersheds with organic nutrients such as carbon, nitrogen, 

and phosphorus, first in the form of whole carcasses and large solids and later as dissolved 

particulates (Willson et al. 1998, Cederholm et al. 1999, Gende et al. 2002, Naiman et al. 2002). 

Salmon carcasses, which are considerably enriched in carbon and nitrogen, contribute to primary 

production in freshwater streams, lakes, and estuaries (Stockner 1987, Cederholm et al. 1989 and 

2000, Kline et al. 1990 and 1993, Bilby et al. 1996, Wipfli et al. 1998). As discussed above, 

marine estuaries and nearshore zones benefit from seasonal pulses of these nutrients. Terrestrial 
16

and aquatic species, from invertebrates and insects to mammals, as well as aquatic and riparian

vegetation, also receive benefit from these seasonal pulses (Reimchen 1994, Wilson and Halupka 

1995, Bilby et al. 1996 and 1998, Ben-David et al. 1997 and 1998, Wipfli et al. 1998, Cederholm 

et al. 1999, Gende and Wilson 2001, Helfield and Naiman 2001, Chaloner et al 2002, Chaloner 

and Wipfli 2002, Darimont and Reimchen 2002, O'Keefe and Edwards 2002, Reimchen et al.

2002 and 2003, Darimont et al. 2003, Mathewson et al 2003, Johnston et al. 2004, Lessard and 

Merritt 2006, Moore et al. 2007, Christie 2008, Christie and Reimchen 2008, Janetski 2009).

Coastal watersheds drain to the ocean-influencing estuaries and nearshore coastal zones 

(Kennish 1992, Caddy 1995 and 2000, Milliman 2010, Dade 2012). Watershed and riparian 

processes influence downstream estuaries through the transport of terrestrial and freshwater 

nutrients (Murphy 1984, Jauquet et al. 2003, Jonsson and Jonsson, 2003, Cak 2008, Von Biela 

2013). Nutrient metabolism in estuaries can be strongly influenced by freshwater river inputs of 

organic and inorganic material (Hopkinson 1995, Kennish 2002). Some studies have 

demonstrated the importance of terrestrial-generated carbon to juvenile and adult bottomdwelling marine fish species in periods of even moderate river discharge (Darnaube 2005). 

Recently, these nutrient sources have been identified as contributing to coastal estuaries and 

trophic interaction in Arctic zones as well (Dunton 2006 and 2012, Von Biela 2013).

Salmon-derived nutrients influence and contribute to estuary production of seasonal larval and 

juvenile plankton, invertebrate and fish species. One early study to suggest the influence of these 

nutrients on estuary water chemistry was conducted in Port Walther, Alaska (Brickell and 

Goering 1970). This study found that after spawning and dying in Sashin Creek, salmon 

carcasses were flushed into the estuary and elevated levels of organic nitrogen. Richey (1975) 

observed similar flushing of salmon carcasses into estuaries. Reimchen (1994) observed entire 

salmon carcasses rapidly consumed by several species of estuarine invertebrates. Gende (2004) 

reports that 43% of tagged carcasses in one watershed washed into the estuary within days. 

Fujiwara (1997) presents evidence suggesting that dissolved nutrients fuel estuarine productivity 

and associated bacteria and algae, which in turn increase the numbers of harpacticoid copepods 

that serve as primary prey for outbound juvenile salmon. Estimates of recent nutrient transport 

indicate that substantial amounts of salmon-derived nutrients (46%-60%) move directly back to 

the estuary (Mitchell and Lamberti 2005). A similar study suggests that bivalves also benefit 

from these nutrients (Chow 2007).

The results of this research indicate an influence of salmon-derived nutrients on trophic 

productivity in marine estuaries. These studies also suggest a positive feedback mechanism in 

salmon production, given that decomposing adult salmon subsidize lower trophic levels and 

provide prey species to their outbound offspring (Fujiwara and Highsmith 1997, Gende et al.

2004). As Aydin (2010) explains, “Mysiids, as an inshore zooplankton (appearing in diets 

primarily in shallow waters of Bristol Bay) have a nitrogen isotope (δ15N) level higher than 

deepwater forage fish.” This strong nitrogen signal was observed in euphausiid and walleye 
17

pollock inhabiting northern Bristol Bay nearshore waters. This unusually high nitrogen signal 

may result from the seasonal increase of freshwater discharge and dissolved organic matter (a 

seasonal terrestrial nutrient pulse from salmon) carried on currents along the northern shore of 

Bristol Bay. In addition, smolt emigration theoretically exports more nutrients out of the 

watersheds than previously recognized, and salmon in sub-adult and adult phases in the eastern 

Bering Sea and North Pacific also contribute to marine mammal diets. 

Summary 

Pacific salmon are a keystone species providing nutrients that influence the habitat condition of 

terrestrial, estuarine and marine ecosystems (Willson and Halupka 1995; Cedarholm et al.1999; 

Helfield and Naiman 2001; Piccolo et al. 2009). Due to their life history, anadromy, range, and 

distribution, Bristol Bay salmon represent a link between fresh water and marine systems. 

Discharges of seasonal freshwater transport dissolved organic matter to the estuary. The 

freshwater discharge facilitates osmoregulatory adaption in salmon smolts, providing a buffer to 

highly saline marine conditions. The estuary provides rich foraging opportunities and a rearing 

environment that allow smolt to achieve the size essential for survival in the early marine phase. 

At the beginning of their life cycle, emigrating smolt from rivers contribute to estuarine and 

marine productivity as a forage fish species. At the end of their life cycle, adult salmon provide 

the nutrients that influence productivity from watersheds through the estuary. These nutrient 

sources provide a feedback mechanism to their outbound offspring fueling lower trophic levels, 

from minute bacteria and fungi to a multitude of plankton, invertebrate, fish, and marine 

mammal species. 

Bristol Bay provides EFH for salmon at various life stages as well as other marine species. The 

Nushagak and Kvichak estuaries provide nutrient-rich transition zones where salmon smolt can 

achieve critical size while acclimating to the marine environment. At an ecosystem level, from 

the head water tributaries through the marine environment, the healthy habitat of the bay both 

supports and results from the interactions between natural processes and the presence and 

abundance of Bristol Bay salmon. 
18
19

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Tables

Table 1: Fish and Invertebrate Species List

Species listed have been identified in the NOAA-AFSC Bering Sea Trawl Surveys between 

1982-2010 (Lauth 2010). 

FISH SPECIES

Common Name Scientific Name

Salmonidae

Chinook salmon Oncorhynchus tshawytscha 

Chum salmon Oncorhynchus keta 

Steelhead Oncorhynchus mykiss

Gadidae

Pacific cod Gadus macrocephalus 

Walleye pollock Theragra chalcogramma 

Arctic cod Boreogadus saida 

Saffron cod Eleginus gracilis

Anoplopomatidae

Sablefish Anoplopoma fimbria

Osmeridae

Eulachon Thaleichthys pacificus 

Capelin Mallotus villosus 

Rainbow smelt Osmerus mordax 

Smelt unident Osmeridae

Clupeidae

Pacific herring Clupea pallasi

Ammodytidae

Pacific sand lance Ammodytes hexapterus

Trichodontidae

Pacific sandfish Trichodon trichodon

Pleuronectidae

Pacific halibut Hippoglossus stenolepis
44

Yellowfin sole Limanda aspera 

Northern rock sole Lepidopsetta polyxystra 

Rock sole unident. Lepidopsetta sp.

Flathead sole Hippoglossoides elassodon

Dover sole Microstomus pacificus 

Rex sole Glyptocephalus zachirus 

Butter sole Isopsetta isolepis

Sand sole Psettichthys melanostictus

Starry flounder Platichthys stellatus

Alaska plaice Pleuronectes quadrituberculatus

Arrowtooth flounder Atheresthes stomias 

Kamchatka flounder Atheresthes evermanni 

Longhead dab Limanda proboscidea 

Sanddab unident. Citharichthys sp.

Scorpaenidae

Northern rockfish Sebastes polyspinis

Rajidae

Big skate Raja binoculata 

Bering skate Bathyraja interrupta 

Starry skate Raja stellulata 

Alaska skate Bathyraja parmifera 

Aleutian skate Bathyraja aleutica

Hexagrammos

Whitespotted greenling Hexagrammos stelleri

Rock greenling Hexagrammos lagocephalus 

Kelp greenling Hexagrammos decagrammus 

Smooth lumpsucker Aptocyclus ventricosus 

Greenling unident. Hexagrammidae

Psychrolutidae 

Sawback poacher Leptagonus frenatus 

Gray starsnout Bathyagonus alascanus

Sturgeon poacher Podothecus accipenserinus 

Aleutian alligatorfish Aspidophoroides bartoni 

Arctic alligatorfish Ulcina olrikii

Warty poacher Chesnonia verrucosa

Bering poacher Occella dodecaedron
45

Anarhichadidae

Wolf-eel Anarrhichthys ocellatus

Bering wolffish Anarhichas orientalis

Gymnocanthus sp. 

Threaded sculpin Gymnocanthus pistilliger 

Arctic staghorn sculpin Gymnocanthus tricuspis 

Armorhead sculpin Gymnocanthus galeatus 

Northern sculpin Icelinus borealis

Sculpin unident. Cottidae

Artediellus sp. 

Hookhorn sculpin Artediellus pacificus 

Irish lord Hemilepidotus sp.

Red Irish lord Hemilepidotus hemilepidotus

Yellow Irish lord Hemilepidotus jordani

Triglops sp. Ribbed

sculpin Triglops pingeli 

Brightbelly sculpin Microcottus sellaris

Warty sculpin Myoxocephalus verrucosus

Great sculpin Myoxocephalus polyacanthocephalus

Plain sculpin Myoxocephalus jaok

Myoxocephalus sp. 

Pacific staghorn sculpin Leptocottus armatus 

Antlered sculpin Enophrys diceraus 

Spinyhead sculpin Dasycottus setiger 

Crested sculpin Blepsias bilobus 

Eyeshade sculpin Nautichthys pribilovius

Sailfin sculpin Nautichthys oculofasciatus 

Bigmouth sculpin Hemitripterus bolini 

Thorny sculpin Icelus spiniger

Spatulate sculpin Icelus spatula

Liparis sp. 

Variegated snailfish Liparis gibbus 

Snailfish unident. Liparidinae
46

Stichaeidae

Daubed shanny Lumpenus maculatus 

Snake prickleback Lumpenus sagitta 

Decorated warbonnet Chirolophis decoratus 

Bearded warbonnet Chirolophis snyderi 

Polar eelpout Lycodes turneri

Cryptacanthodidae

Giant wrymouth Cryptacanthodes giganteus

INVERTEBRATE SPECIES

Common Name Scientific Name

Octopus

Octopodidae sp.

Common Octopus Octopoda

Eastern Pacific bobtail Rossia pacifica

Crab

Cancer sp.

Oregon rock crab Cancer oregonensis 

Graceful decorator crab Oregonia gracilis 

Tanner crab Chionoecetes bairdi 

Circumboreal toad crab Hyas coarctatus 

Pacific lyre crab Hyas lyratus

Snow crab Chionoecetes opilio 

Hybrid tanner crab Chionoecetes hybrid 

Helmet crab Telmessus cheiragonus 

Hermit crab unident. Paguridae

Pagurus sp. 

Sponge hermit Pagurus brandti 

Aleutian hermit Pagurus aleuticus

Splendid hermit Labidochirus splendescens

Knobbyhand hermit Pagurus confragosus 

Fuzzy hermit crab Pagurus trigonocheirus 

Bering hermit Pagurus beringanus 

Alaskan hermit Pagurus ochotensis 

Longfinger hermit Pagurus rathbuni 

Widehand hermit crab Elassochirus tenuimanus 

Hairy hermit crab Pagurus capillatus
47

Purple hermit Elassochirus cavimanus

Wrinkled crab Dermaturus mandtii

Hapalogaster sp.

Fuzzy crab Hapalogaster grebnitzkii

Red king crab Paralithodes camtschaticus

Horsehair crab Erimacrus isenbeckii

Shrimp

Pandalus sp.

Ocean shrimp Pandalus jordani 

Alaskan pink shrimp Pandalus eous 

Humpy shrimp Pandalus goniurus 

Shrimp unident. Hippolytidae

Lebbeus sp.

Spiny lebbeid Lebbeus groenlandicus

Crangon sp.

Abyssal crangon Crangon abyssorum 

Twospine crangon Crangon communis 

Ridged crangon Crangon dalli 

Sevenspine bay shrimp Crangon septemspinosa 

Crangonid shrimp unident. Crangonidae

Argis sp.

Arctic argid Argis dentata

Sclerocrangon sp.

Sculptured shrimp Sclerocrangon boreas

Kuro argid Argis lar

Clams, Mussels, Scallop, Cockles

Mytilidae sp.

Northern horse mussel Modiolus modiolus

Mytilus sp. Blue 

mussel Mytilus edulis 

Weathervane scallop Patinopecten caurinus 

Arctic hiatella Hiatella arctica

Arctic roughmya Panomya norvegica

Yoldia sp. 

Crisscrossed yoldia Yoldia seminuda 

Northern yoldia Yoldia hyperborea 

Discordant mussel Musculus discors 

Boreal astarte Astarte borealis
48

Many-rib cyclocardia Cyclocardia crebricostata

Mactromeris sp.

Arctic surfclam Mactromeris polynyma

Tellina sp.

Alaska great-tellin Tellina lutea

Macoma sp.

Bent-nose macoma Macoma nasuta

Siliqua sp. 

Pacific razor Siliqua patula 

Alaska razor Siliqua alta

Mya sp.

Softshell clam Mya arenaria

Alaska falsejingle (soft oyster) Pododesmus macrochisma

Soft shell unident. Anomiidae

Ciliatum sp.

Hairy cockle Clinocardium ciliatum

California cockle Clinocardium californiense

Serripes sp.

Greenland cockle Serripes groenlandicus

Broad cockle Serripes laperousii

Cyclocardia sp. 

Clinocardium sp.

Coral, Soft coral

Gersemia sp.

Sea raspberry Gersemia rubiformis

Gorgonacea sp.

Sea pen (sea whip) Pennatulacea

Snail, snails, welk

Natica clausa sp.

Aleutian moonsnail Cryptonatica aleutica 

Rusty moonsnail Cryptonatica russa 

Pale moonsnail Euspira pallida

Great slippersnail Crepidula grandis

Moonsnail eggs unident Naticidae eggs

Volutopsius sp.

Warped whelk Pyrulofusus deformis 

Beringius sp. 

Beringius kennicottii
49

Beringius beringii

Neptunea sp.

Pribilof whelk Neptunea pribiloffensis

Neptunea borealis

Lyre whelk Neptunea lyrata

Fat whelk Neptunea ventricosa

Neptunea heros

Helmet whelk Clinopegma magnum 

Plicifusus kroyeri 

Neptunea sp.

Oregon triton Fusitriton oregonensis

Tritonia sp.

Rosy tritonia Tritonia diomedea

Buccinum sp. Angular 

whelk Buccinum angulosum 

Sinuous whelk Buccinum plectrum 

Ladder whelk Buccinum scalariforme 

Polar whelk Buccinum polare 

Smooth lamellaria Velutina velutina

Hyas sp.

Snail eggs Gastropod eggs

Snail eggs unident. Neptunea sp. eggs

Barnacles

Balanus sp.

Giant barnacle Balanus evermanni 

Beaked barnacle Balanus rostratus 

Barnacle unident. Thoracica

Anemone

Halipteris sp.

Sea anemone unident. Actiniaria

Metridium sp.

Clonal plumose anemone Metridium senile

Metridium farcimen (=Metridium

Gigantic anemone giganteum)

Stomphia sp. 

Urticina sp.

Mottled anemone Urticina crassicornis

Chevron-tentacled anemone Cribrinopsis fernaldi
50

Tentacle-shedding anemone Liponema brevicornis

Stony coral unident. Scleractinia

Star fish, sea star

Evasterias sp.

Mottled sea star Evasterias troschelii

Giant sea star Evasterias echinosoma

Leptasterias groenlandica

Blackspined sea star Lethasterias nanimensis

Henricia sp.

Blood sea star Henricia leviuscula

Tumid sea star Henricia tumida 

Leptasterias polaris 

Leptasterias katharinae 

Leptasterias arctica 

Leptasterias sp. 

Crossaster sp.

Grooved sea star Crossaster borealis

Rose sea star Crossaster papposus

Asterias sp.

Purple-orange sea star Asterias amurensis

Brittlestarfish unident. Ophiuroidea

Basketstar Gorgonocephalus eucnemis

Notched brittlestar Ophiura sarsi

Sea urchin

Echinacea sp.

Green sea urchin Strongylocentrotus droebachiensis 

Strongylocentrotus sp. 

Strongylocentrotus polyacanthus

Sand dollar Echinarachnius parma

Sponges

Stelletta sp.

Stone sponge Suberites ficus

Clay pipe sponge Aphrocallistes vastus

Barrel sponge Halichondria panicea

Suberites sp.

Sponge Porifera
51

Jelly fish

Amphilaphis sp.

Jelly Fish Chrysaora melanaster 

Lion's mane Cyanea capillata 

Chrysaora jellyfish Chrysaora sp.

Jellyfish unident. Scyphozoa

Comb jelly unident. Ctenophora

MiscellaneousInvertabrate Species

Worm

Polychaeta

Giant scale worm Eunoe nodosa

Depressed scale worm Eunoe depressa

Striped sea leech Notostomobdella cyclostoma

Echiuroid worm unident. Echiura

Cat worm unident. Nephtyidae 

Scale worm unident. Polynoidae 

Peanut worm unident. Sipuncula

Tube worm unident.

Hydroids

Abietinaria sp.

Bryozoans

Feathery bryozoan Eucratea loricata

Leafy bryozoan Flustra serrulata

Alcyonidium pedunculatum

Ribbed bryozoan Rhamphostomella costata

Bryozoan unident. Bryozoa

Sea Cucumbers

Cucumaria sp.

Sea football Cucumaria fallax

Sea cucumber Holothuroidea

Cucumaria frondosa

Foraminiferan unident. Psolus sp.

Foraminifera
52

Ascidians

Orange sea glob Aplidium sp.

Sea pork Aplidium californicum

Molgula sp.

Sea grape Molgula grifithsii

Sea clod Molgula retortiformis
53

Table 2: Marine Mammals Species List

Marine mammal species listed have been identified from several sources (Allen 2011, ADFG 

2010, BBESI 2001, BB-CRSA 2009). 

MARINE MAMMALS

Common Name Scientific Name

Toothed Whales Cetaceans - Ondontocetes 

Beluga whale Delphinapterus leucas 

Killer whale Orcinus orca

Pacific white-sided dolphin Lagenorhynchus obliquidens

Harbor porpoise Phocoena phocoena 

Dall’s porpoise Phocoenoides dalli 

Baird’s beaked whale Berardius bairdii

Baleen Whales Cetaceans – Balenotropha

Gray whale Eschrichtius robustus 

Humpback whale Megaptera novaeangliae 

Fin whale Balaenoptera physalus 

Minke whale Balaenoptera acutorostrata 

Bowhead whale Balaena mysticetus

Sealion Pinnipeds - Otariidae

Steller sea lion (Eastern) Eumetopias jubatus

Northern fur seal (Eastern) Callorhinus ursinus

Seals Pinnipeds - Phocidae

Harbor seal Phoca vitulina 

Spotted seal Phoca largha 

Bearded seal Erignathus barbatus 

Ringed seal Pusa hispida

Ribbon seal Histriophoca fasciata

Pinnipeds – Odobenidae

Walrus Odobenus rosmarus

Mustelidae - Lutrinae

Northern Sea Otter Enhydra lutris kenyoni
AN ASSESSMENT OF POTENTIAL MINING IMPACTS ON 

SALMON ECOSYSTEMS OF BRISTOL BAY, ALASKA 

VOLUME 3—APPENDICES E-J

Appendix G: Foreseeable Environmental Impact of Potential 

Road and Pipeline Development on Water Quality and 

Freshwater Fishery Resources of Bristol Bay, Alaska 
Appendix G

Foreseeable Environmental Impact of 

Potential Road and Pipeline Development on 

Water Quality and Freshwater Fishery Resources 

of Bristol Bay, Alaska

By

Christopher A. Frissell, Ph.D.

Pacific Rivers Council

PMB 219, 48901 Highway 93, Suite A 

Polson, MT 59860 

chris@pacificrivers.org

phone 406-471-3167 

Maps and Spatial Analysis by

Rebecca Shaftel

Alaska Natural Heritage Program 

University of Alaska Anchorage 

Beatrice McDonald Hall, Suite 106

rsshaftel@uaa.alaska.edu

Report prepared for 

University of Alaska Anchorage 

Environment and Natural Resources Institute 

And Alaska Natural Heritage Program

Daniel Rinella, Project Leader

rinella@uaa.alaska.edu

January 2014
ABSTRACT

While Pacific salmon fishery resources have diminished around the Pacific Rim for more 

than a century, the Bristol Bay region of Alaska supports a globally unique, robust, 

productive, and sustainable salmon fishery associated with extremely high quality waters 

and high integrity freshwater ecosystems. The Bristol Bay watershed has seen a bare 

minimum of road development to date. However, State of Alaska long range plans 

envision a future of extensive inter-community transportation routes, including both 

highways and pipelines. Other developments being considered for the area would also 

require an infrastructure of roads and pipelines that would traverse previously roadless 

areas of the Kvichak and Nushagak river drainages. As a plausible example of such 

potential infrastructure, this report uses the 138-km-long access road and four pipelines 

likely to be part of Northern Dynasty Minerals’ Pebble Mine, should the company elect 

to pursue development of that prospect. It reviews the known physical and biological 

effects of road and pipeline development on streams, rivers, lakes, and wetlands. The 

report identifies two key conditions in the Bristol Bay ecosystem that particularly 

contribute to its water quality and biological productivity and resilience: 1) a geologic 

and geomorphic template that provides abundant shallow groundwater resources and 

strong vertical linkage between surface waters and groundwater, across all stream sizes 

and wetland types; and 2) the lack of past industrial disturbance, including road 

development across most of the Bristol Bay watershed. The example Pebble Mine 

transportation corridor would bisect this landscape with the potential to shape the 

hydrology, water quality and fish habitat integrity of many of the Kvichak and Nushagak 

river drainages. Drawing from the literature that conceptualizes how to spatially project 

risk-impact footprints from road designs and landscape and stream network data, the 

report maps the spatial extent of potential harm from construction, operation, accidents 

and accidents response on the Pebble transportation corridor. More than 30 large streams 

and rivers known to support spawning salmon would intersect with the proposed 

transportation corridor, potentially affecting between twenty and thirty percent of known 

spawning populations of sockeye salmon in the Iliamna Lake system. The eastern half of 

Iliamna Lake supports the highest concentrations of rearing sockeye salmon and would 

also be very close to the road and pipeline corridor. The corridor would also bisect or 

closely approach more than 70 streams known to support resident fishes such as Dolly 

Varden, arctic grayling, and others. The report also assesses potential mitigation 

measures and identifies practices that could potentially reduce the risk of impact to water 

quality, freshwater ecosystem function, and Bristol Bay fishery resources should the 

corridor be developed.

2 
I. INTRODUCTION AND SCOPE OF THIS REPORT

While Pacific salmon fishery resources have diminished around the Pacific Rim to the 

point that many populations are managed as endangered or threatened species, the Bristol 

Bay region of Alaska supports a globally unique, robust and productive salmon fishery 

(Burgner 1991, Schindler et al. 2010). Commercial fishers harvest five Pacific salmon 

species in Bristol Bay, including a sockeye salmon landing of over 29 million fish in 

2010 (ADFG 2010). Bristol Bay’s wild rivers support sport fisheries likely exceeding 

90,000 angler days and millions of dollars in related expenditures (Duffield et al. 2007). 

Hilborn et al. (2003) identified key factors sustaining the productivity and resilience of 

Bristol Bay, specifically, 1) a highly accountable system of fishery regulation, 2) 

favorable ocean conditions in recent years, and 3) a stock complex sustained by variable 

production from an abundance and high diversity of freshwater and estuarine habitats., 

Salmon production in different Bristol Bay rivers and lakes, in their current, largely 

natural and undeveloped condition, varies independently over time spans of decades. 

Despite the local variability, the system sustains a high overall fishery production 

because at any given time, a collection of extremely high-quality habitats contributes 

extraordinarily high abundance and production of fishes. These same factors (i.e., 

diversity and high quality of interconnected habitats) likely confer to Bristol Bay a degree 

of resilience in the face of future climate and environmental change (Hilborn et al. 2003, 

Woody and O’Neal 2010, Schindler et al. 2010). 

Although some planners have projected extensive highways and industrial development 

in the Bristol Bay region (BBAP 2005), the Pebble Mine is the most likely large-scale 

development to be proposed in the near future. Development of the Pebble project would 

include a major 138-km-long access road, pipeline, and electric utility corridor between 

the mine site, north of Lake Iliamna, and a deepwater port on Cook Inlet, to the east 

(Ghaffari et al. 2011) (Figure 1). This corridor would cross many tributaries of the of the 

Kvichak and Nushagak Rivers, including tributaries of Iliamna lake, as well as bisecting 

numerous wetlands and groundwater-rich areas that connect to and sustain the water 

quantity and quality in those fish habitats. 

 

3 
Figure 1. Existing roads in the Bristol Bay region, and the proposed route of the Pebble 

Mine transportation corridor. Mapped by Rebecca Shaftel (Alaska Natural Heritage 

Program, Anchorage) based on data from Alaska Department of Transportation and 

Alaska Department of Natural Resources (Anchorage).

Through its contractor for this report, NatureServe, U.S. Environmental Protection 

Agency charged the author with providing a review of: 1) relevant literature and expert 

input on the risks, threats, and stressors to Bristol Bay area water quality and salmon 

resources associated with the construction, operation, and maintenance of reasonably 

foreseeable roads in the region; and 2) mitigation practices used to abate such impacts, 

including both commonly used and available, but uncommonly used practices. 

Accordingly, after a brief review of known consequences of road and pipeline 

development on streams, rivers, and lakes, this report will assess the scope of likely and 

possible environmental impacts on the water quality and fishery resources of the Bristol 

Bay region from development of the potential Pebble Mine Transportation Corridor. 

4 
II. THE BRISTOL BAY ECOSYSTEM 

Bristol Bay is one of the world’s few remaining, large virtually roadless near-coastal

regions. There are but a few short segments of state highway and road, and no railroads, 

pipelines, or other major industrial transportation infrastructure. Roadways presently link 

Iliamna Lake (Pile Bay) to Cook Inlet (tidewater at Williamsport); the Iliamna area 

(including Iliamna airport) north to a proposed bridge over the Nondalton River and then 

to the village of Nondalton; and two other short road segments from Dillingham to 

Aleknagik and Naknek to King (Figure 1). A short road system also connects the village 

of Pedro Bay with its nearby airstrip. Improvements have been proposed by the state of 

Alaska for the road between Iliamna and Nondalton, in part to alleviate erosion and 

sedimentation.

Glacial landforms dominate much of Bristol Bay’s surface geology and geomorphology 

and include extensive glacial outwash glacial till mantles on hillslopes, expansive, 

interbedded glacial lake deposits, and glacial and periglacial stream deposits (Hamilton 

2007). These landforms, and more specifically, the extensive, interconnected surface and 

near-surface groundwater systems resulting from them, are one of the two factors that 

principally account for Bristol Bay’s high productivity for salmon. (The other key factor 

is the dearth of industrial and commercial development in the basin.) 

Most available information on fish distribution and abundance in the Bristol Bay region 

focuses on large rivers (in part because they can be surveyed from the air, at least for 

sockeye salmon). However, a myriad of smaller streams and wetlands also provide highquality habitat for coho salmon, Dolly Varden, rainbow trout, and arctic grayling, as well 

as other species including round whitefish, pond smelt, lamprey, slimy sculpin, northern 

pike, sticklebacks and burbot (Rinella 2011, personal communication, and Shaftel 2011, 

personal communication). In the most comprehensive published field inventory, Woody 

and O’Neal (2010) reported detection of one or more of these species from 96 percent of 

the 108 small waters they sampled in the vicinity of the projected site of Pebble prospect 

in the Nushagak and Kvichak River drainages. They summarize:

Small headwater streams are often assumed not to be important 

salmon producing habitats in Alaska, although collectively they 

produce millions of salmon and determine water flow and 

chemistry of larger rivers. As illustrated by this and numerous 

other studies, headwaters comprise a significant proportion of 

essential spawning and rearing habitat for salmon and non-salmon 

species all of which are important to subsistence users in the 

region. 

5 
III. ROADS AND PIPELINES PROPOSED OR FORESEEABLE IN BRISTOL BAY

In evaluating the environmental impact of any road, it is important to recognize that the 

development of a new road is often only the first step toward industrial or commercial 

development of the landscape in general, including the proliferation of additional roads 

(Trombulak and Frissell 2000, Angermeier et al. 2004). Additional large-scale landscape 

development, facilitated by the initial road, is a reasonably foreseeable impact of road 

construction in a roadless area. Essentially, finance and construction of the initial road 

subsidizes future developments that rely on that road to route traffic, particularly when 

that initial road connects to a possible trade hub, such as a deepwater port. The 

environmental impact of the ensuing development can dwarf by orders of magnitude the 

direct, local effects of constructing the initial road segment (Angermeier at al. 2004).

That there is some interest in industrialization of Bristol Bay beyond the Pebble Mine is 

evident in various State of Alaska sources. The ADNR’s Bristol Bay Area Plan from the 

(BBAP 2005, citing the ADOT’s Southwest Alaska Transportation Plan, November 

2002), lays out an ambitious long-range vision for future development of a network of 

roads and highways in the Bristol Bay region. The roads, highways, and related 

infrastructure envisioned by the BBAP include “regional transportation corridors” that 

would connect Cook Inlet to the area of the Pebble prospect, as well as Aleknagik 

(already connected by road to Dillingham), King Salmon, Naknek, Egegik, and Port 

Heiden, and finally, to Chignik and Perryville, on the southern Alaska Peninsula. The 

State also foresees other “community transportation projects” that involve extensions, 

improvements, or new roads within or adjacent to Bristol Bay watershed (Chignik Road 

Intertie, King Cove-Cold Bay Connection, Newhalen River Bridge, Iliamna-Nondalton 

Road Intertie, and Naknek-South Naknek Bridge and Intertie). The plans also identify 

three potential “Trans-Peninsula transportation corridors” (Wide Bay/Ugashik Bay, 

Kuiulik Bay/Port Heiden, and Balboa Bay/Herendeen Bay,) routes that could serve for 

roads, oil and gas pipelines or other utilities as needed (BBAP 2005, Figure 2.5). 

Several other large ore bodies and at least seven different complexes of mineral claims lie 

within a roughly concentric 24-km radius around the existing Pebble Prospect, 

encompassing a vast swath of the Bristol Bay watershed north of Iliamna Lake (Ghaffari 

et al. 2011, The Nature Conservancy 2010). The area spans the headwaters of the 

Koktuli, Stuyahok, and Newhalen Rivers, as well as Kaskanak, and both Lower and 

Upper Talarik Creeks. There are other large mineral leases farther afield within Bristol 

Bay, including tracts north and west of the Nushagak and Mulchatna Rivers. Although 

they are at various stages of exploration, these prospects could yield future mine 

proposals, particularly if road and other transportation improvements completed for 

Pebble Mine provided a transportation stepping stone to them. 

IV. EFFECTS OF ROADS AND PIPELINES ON WATER AND FISH HABITAT

Roads have persistent multifaceted impacts on ecosystems and can strongly affect water 

quality and fish habitat. Several authors have reviewed the suite and scope of 

6 
environmental impacts from roads (e.g., Forman and Alexander 1998, Trombulak and 

Frissell 2000, Gucinski et al. 2001) with particular focus on water quality and fish habitat 

impacts found in sources such as Furniss et al. (1991), Jones et al. (2000), and 

Angermeier et al. (2004). The increasing presence of roads in the developed and 

developing world has been identified as a threat to native freshwater species and water 

quality alike. Czech et al. (2000), for example, identified roads as a likely contributing 

factor in the local extinction and endangerment of 94 taxa across the U.S. 

Road construction causes mortality and injury of stationary and slow-moving organisms 

both within and adjacent to the construction footprint and alters the physical conditions in 

the area, as well (Trombulak and Frissell 2000), often including direct conversion of 

habitat to non-habitat within and adjacent to the footprint (Forman 2004). Behavior 

modification depends on species and road size/type. Voluntary modification ranges from 

use of the road corridor to avoidance; involuntary modification may result when a road 

completely blocks the movement of organisms, resulting in fragmentation or isolation of 

populations, often with negative demographic and genetic effects and with potential 

consequences as grave as local population or species extinction and loss of biodiversity 

(Forman 2004, Gucinski et al. 2001, Trombulak and Frissell 2000). Truncation of fish 

migrations due to passage barriers created by roads is one example of involuntary 

behavioral alterations that compromise survival and productivity. Other behavior 

modifications include changes in home range, reproductive success, escape response, 

and/or physiological state (Forman and Alexander 1998, Trombulak and Frissell 2000). 

Roads can create long-term, local changes in soil density, temperature, and water content, 

light, dust, and/or surface water levels, and flow, runoff, erosion, and/or sedimentation 

patterns, as well as adding heavy metals, deicing salts, organic molecules, ozone, and 

nutrients to roadside environments (Forman 2004, Gucinski et al. 2001, Trombulak and 

Frissell 2000, Forman and Deblinger 2000). When delivered to streams, road-derived 

pollutants directly and indirectly impact water quality. The extension of natural stream 

networks to integrate eroding road surfaces can cause sustained delivery of fine 

sediments that alter bed texture and reduce the permeability of streambed gravels (Furniss 

et al. 1995, Wemple et al. 1996, Jones et al. 2000, Angermier et al. 2004). Increased 

loading of fine sediments has been linked to adverse impacts on fish though several, often 

co-occurring biological mechanisms, including decreased fry emergence, decreased 

juvenile densities, loss of winter carrying capacity, increased predation on fish, and 

reduced benthic organism populations and algal production (Newcombe and MacDonald 

1991, Newcombe and Jensen 1996, Gucinski et al. 2001, Angermier et al. 2004, Suttle et 

al. 2004, and many others). In steeper terrain, roads greatly increase the frequency of 

slope failure and debris flow, with the resulting episodic sediment delivery to streams and 

rivers (Montgomery 1994, Jones et al. 2000, Gucinski et al. 2001). Roads often promote 

the dispersal of exotic species and pathogens by altering habitats, stressing native species, 

and providing corridors and vehicle transport for seed/organism dispersal (Forman 2004, 

Trombulak and Frissell 2000, Gucinski et al. 2001). So long as they remain accessible 

and passable enough to facilitate human use, roads also lead to increased hunting, fishing, 

poaching, fish and wildlife harassment, use conflicts, lost soil productivity, fires, 

landscape modifications, and decreased opportunities for solitude (Forman 2004, 

7 
Gucinski et al. 2001, Trombulak and Frissell 2000, Angermeier et al. 2004). Although 

impacts to water and fish are the primary focus of this report, the direct and indirect 

impacts of roads on other resources and their use should also be recognized. 

While the only certainly effective mitigation to avoid the impacts of roads and pipelines 

is to find alternatives that do not require building and using them, it does not appear 

geographically or operationally feasible to develop the Pebble mine without a road and 

pipeline corridor. 

Immediate Effects of Construction versus Long-term Impact of Use and Maintenance 

Following Angermeier et al. (2004), the effects of roads are distributed across scales of 

space and time in three discernible quanta. The first is the immediate and site-specific 

effect from the construction of a new road. Many of these impacts are either transient or 

are acute only during and shortly after initial construction. An example is the delivery of 

large pulses of sediment to streams during runoff events after placement of fill or major 

ground disturbance by heavy equipment. The second quantum is the suite of effects 

caused by sustained operation, maintenance, and/or mere existence of the roadway. 

Examples include seasonal runoff of pollutants such as deicing salts into nearby streams, 

transport of wind-eroded dust from road surfaces to adjacent areas, chronic delivery of 

sediment from erosion of road surfaces, ditches, and cut slopes, and the alteration or 

sustained displacement of natural vegetation in the footprint and influence zone of the 

road. Finally, often the greatest impact of road development is the ancillary 

development of the landscape, or change in the pattern of human habitation, resource 

extraction, and land and water use of a region, that the road in some way facilitates. The 

remainder of this report focuses on the first two quanta, while acknowledging that the 

third class of impacts is likely the most significant for Bristol Bay. 

The hydrologic and biological effects of roads are generally similar in nature for 

wetlands, streams, rivers, and lakes. Darnell et al. (1976, see especially pp. 129-136) 

identified basic construction activities typically associated with industrial projects, 

including roads and pipelines: 

1) Clearing and grubbing; 

2) Disposition of materials; 

3) Excavation; 

4) Sub-grade and slope/cut stabilization, including riprap; 

5) Placement of fill;

6) Aggregate production; 

7) Paving; 

8) Equipment staging; 

9) Borrow pits;

10) Landfills (disposal sites of excess excavated material). 

The authors summarized the categories of possible or likely impact from such projects 

8 
and activities on adjoining aquatic areas as follows:

 1) Loss of natural vegetation; 

 2) Loss of topsoil; 

 3) Change of water table elevation; 

4) Increased erosion;

5) Leaching of soil minerals from exposed and eroding soil surfaces; 

6) Fluctuations in streamflow;

7) Fluctuations in surface water levels;

8) Increased downstream and upstream flooding; 

9) Increased sediment load;

10) Increased sedimentation; 

11) Increased turbidity;

12) Changes in water temperature; 

13) Changes in pH; 

14) Changes in chemical composition of soils and waters; 

15) Leaching of pollutants from pavement; 

16) Introduction of hydrocarbons to soils and waters; 

17) Addition of heavy metals; 

18) Addition of asbestos fibers (dispersed from industrial or natural sources); and

19) Increased oxygen demand (caused by organic matter export to and 

accumulation in waterways).

These various alterations interact in complex cause-and-effect chains. Although 

recognizing that long-term consequences of these alterations are to a significant degree 

dependent on local circumstances, Darnell et al. (1976) nevertheless identified common, 

general long-term outcomes that include 1) permanent loss of natural habitat; 2) increased 

surface runoff and reduced groundwater flow; 3) channelization or structural 

simplification of streams and hydrologic connectivity; and 4) persistent changes in the 

chemical composition of water and soil. 

Three other categories of impact common to roads have been identified in more recent 

literature (Trombulak and Frissell 2000, Forman 2004): 1) disruption of movements of 

animals, including fishes and other freshwater species; 2) aerial transport of pollutants via 

road dust; and 3) disruption of near-surface groundwater processes, including 

interception or re-routing of hyporheic flows, and conversion of subsurface slope 

groundwater to surface flows. Because of their potential importance in the Bristol Bay 

region, these are further described in the following section. 

Connectivity and Barriers to Fish Movement 

Because roads alter surface drainage, and their stream crossing structures can either by 

design or by subsequent alteration by erosion or plugging with debris, roads can form 

barriers to the movement of freshwater organisms (Roeloffs et al. 1991, Trombulak and 

Frissell 2000, Gucinski et al. 2001.) Barriers to upstream passage into headwater streams 

9 
are most common. Pipelines may or may not have similar effects, depending on their 

crossing design and association with access and maintenance roads. 

Small headwater streams are the lifeblood of rivers and lakes; they sustain processes and 

natural communities that are critically and inextricably linked to water quality, habitat 

and ecosystem processes that sustain downstream resources (Lowe and Likens 2005). 

The direct dependence of some fish on headwater streams for habitat is just one example 

of these linkages. When road crossings block fish passage—as they often do (Harper and 

Quigley 2000, Gucinski et al. 2001, FSSSWP 2008), the isolated population(s) 

immediately lose migratory (anadromous or freshwater migrant) species and life history 

types. Resident species that remain are also at risk of permanent extirpation because 

barriers can hinder their dispersal and natural recolonization after floods, drought, or 

other disturbances. 

Bryant et al. (2009) found in southeast Alaska that Dolly Varden char moved upstream 

into very small streams primarily in fall, and coastal cutthroat trout primarily in spring. 

Both species moved upstream just prior to their spawning season, but during low water 

intervals, not during high-runoff events. Wigington et al. (2006) developed clear 

quantitative evidence that free access to spawning and early rearing habitat in small 

headwater streams is critical for sustaining coho salmon in an Oregon river. Culverts 

and other road crossing structures not designed, constructed, and maintained to provide 

free passage of such species can curtail migration, isolate these species from their 

spawning and nursery habitats, and fragment populations into small demographic isolates 

that are vulnerable to extinction (Hilderbrand and Kirshner 2000, Young et al. 2004). 

Drawing inference from natural long-term isolates of coastal cutthroat trout and Dolly 

Varden in Southeast Alaska, Hastings (2005) found that About 5.5 km length of perennial 

flow headwater stream habitat supporting a census population size of greater than 2000 

adults is required for a high likelihood of long-term population persistence. Beyond 

diminishing potential survival and reproduction, barriers to movement can truncate life 

history and genetic diversity of populations, reducing resilience and increasing their 

vulnerability to environmental variability and change (Hilborn et al. 2003, Bottom et al. 

2009). 

The loss of some fish species due to road blockages and other barriers can bring 

cascading ecological effects by altering key biological interactions. For example, the 

blockage of anadromous salmon from headwater streams could trigger declines in food 

web productivity caused by loss of marine-derived nutrients that originate from carcasses 

and gametes of spawning salmon (Bilby et al. 1996, Wipfli and Baxter 2010). 

Dust and Its Impact 

Previous syntheses of the impacts of roads have not sufficiently addressed the effects of 

road dust. Dust results from traffic operating on unpaved roads in dry weather, grinding 

and breaking down road materials into fine particles (Reid and Dunne 1984). The 

resulting fines either transport aerially in the dry season or are mobilized by water in the 

10
wet season. The dust particles may also include trace contaminants including deicing 

salts, hydrocarbons, and a variety of industrial substances used in construction or 

maintenance, or that are dispersed intentionally or unintentionally by vehicles on the road 

(e.g., heavy metals or cyanide from transported mining waste, or asbestos fibers in some 

mine and treatment projects). Especially after initial suspension by vehicle traffic, aerial 

transport by wind spreads dust over varying terrain and long distances, meaning that it 

can reach surface waters that are otherwise buffered from sediment delivery via aqueous 

overland flow. Walker and Everett (1987) evaluated the impacts of road dust generated 

in particular from traffic on the Dalton Highway and Prudhoe Bay Spine Road in 

northern Alaska. Dust deposition altered the albedo of snow cover, causing earlier (and 

presumably more rapid) snowmelt up to 100 meters from the road margin, as well as 

increased depth of thaw in roadside soils. The authors also associated dust with loss of 

lichens, sphagnum and other mosses, and a reduction of plant cover (Walker and Everett 

1987). Loss of near-roadway vegetation has important implications for water quality, as 

that vegetation is a major contributor to filtration of sediment from road runoff. Hence, 

dust deposition not only contributes to stored sediment that will mobilize to surface 

waters in wet weather, but can also reduce the capacity of roadside landscapes to filter 

that sediment. 

Near-Surface Groundwater and Hyporheic Flows

The potential Pebble Mine transportation corridor would have a high frequency of 

crossings of streams, wetlands, and areas of shallow groundwater. These groundwater 

systems include extensive hyporheic flow networks that connect surface waters through 

shallow, subsurface flow paths. In the Bristol Bay watershed, they appear to be 

especially associated with alluvial, glacio-fluvial and glacio-lacustrine deposits, but also 

locally with slope-mantling till and other locally porous deposits. Existing research sheds 

relatively little light on the crucial subject of the impacts of road development on shallow 

groundwater and the connectivity to surface water habitats important to fish. Due to the 

apparent large extent and hydrologic importance of subsurface-to-surface hydrologic 

connectivity to streams, lakes and wetlands in Bristol Bay (e.g., Woody and Higman 

2011, Woody and O’Neal 2010), and to the recognized importance of groundwater-fed 

habitats for northern latitude fishes (e.g., Cunjak 1996, Power et al. 1999, Malcom et al. 

2004), this review pays particular attention to those linkages and how they can be 

impacted by roads. 

Rudimentary groundwater studies at roads traversing moderate slopes of conifer forest 

and muskeg in southeast Alaska (Kahklen and Moll 1999) revealed there could be either 

a bulge or a drawdown in groundwater level near the upslope ditch, while immediately 

downslope of the road the water table was most often depressed. These effects appeared 

for distances between 5 and 10 meters on each side of the road prism. The effect of 

observed water table deformation on the downslope flux of groundwater remains 

unknown. 

The distance to which a road influences subsurface flow paths may be considerably 

11
greater in gently sloping alluvial and glaciolacustrine terrain, typically characterized by 

shallower, porous zones of subsurface hyporheic or channeled subsurface flow that roads 

can unearth or compact (Jones et al. 2000). It is well-recognized that management of 

roads in such terrain types can be unpredictable and challenging, in part because it is very 

difficult to anticipate the extent and nature of disruption to subsurface flow paths, large 

volumes of water may be involved, and with low gradients, the effects of water table 

deformation can project hundreds of meters from the road itself (Darnell et al. 1976). 

The field observations reported by Hamilton (2007) and Woody and O'Neal (2010) 

in the Pebble mine area indicate terrain with an abundance of near-surface 

groundwater and a high incidence of seeps and springs associated with complex 

glaciolacustrine, alluvial, and slope till deposits. The abundance of mapped 

wetlands (see main report) further testifies to the pervasiveness of shallow 

subsurface flow processes and high connectivity between groundwater and surface 

water systems in the areas traversed by the transportation corridor. The 

construction and operation of roadways and pipelines can fundamentally alter the 

intricate connections between shallow aquifers and surface channels and ponds, leading 

to further impacts on surface water hydrology, water quality, and fish habitat (Darnell et 

al. 1976, Stanford and Ward 1993, Forman and Alexander 1998, Hancock 2002). In 

wetlands, for example, hydrologic disruptions from roads, by altering hydrology, 

mobilizing minerals and stored organic carbon, and exposing soils to new wetting and 

drying and leaching regimes, can lead to changes in vegetation, nutrient and salt 

concentrations, and reduced water quality (e.g., Ehrenfeld and Schneider 1991). 

Hyporheic exchange processes may be further altered by changes in sediment supply, 

both positive and negative, which alter infiltration, porosity, and exfiltration of 

subsurface flow paths, as well as affecting mixing of upwelled and surface water 

(Hancock 2002, Kondolf et al. 2002). Roads can either reduce sediment supply by 

blocking downslope or downstream sediment transport or increase sediment supply by 

creating a new source of eroded material (e.g., road fills, cuts, landslides), often 

exacerbated by stream diversions that result in more erosive flows (Montgomery 1994). 

Ground disturbance and catchment alteration by roads and other land use practices 

generally increases erosion and sediment delivery to streams. In the Bristol Bay region, 

many streams and rivers connect, directly or indirectly, to lakes. Of particular regard to 

Pebble project is Lake Iliamna, which supports abundant and diverse sockeye salmon and 

other species (Schindler et al. 2010). Accelerated sedimentation and accompanying 

phosphorus deposition in lakes, as well as mobilization of dissolved and particulate 

carbon and nitrogen result from shoreline and catchment disturbance (Birch et al. 1980, 

Stendera and Johnson 2006), and these inputs can, in turn, trigger profound changes in 

lake trophic status and food webs that could result in harmful effects on production of 

sockeye salmon and other lake-dwelling species (Schindler and Scheurell 2002). 

Nutrient delivery from road runoff and other road-related hydrologic alterations differs in 

seasonal timing, quantity, and chemical makeup from nutrients delivered to streams and 

lakes by anadromous fishes that die after spawning, hence it may have different 

ecosystem–level effects. For example, road-associated runoff commonly combines 

inputs of carbon, phosphorus, and nitrogen with suspended sediments, and the physical 

12
and light-reducing properties of the sediments can profoundly impact the processing of 

those nutrients by microbial films, plants, and filter feeders (Newcombe and Jensen 1996, 

Donohue and Molinos 2009). While the most profound and detectable physical and 

biological effects occur in littoral zones and deltas, where sediments and nutrients are 

directly delivered (and where sockeye spawning is often concentrated, [Woody 2007]), 

suspended sediment and accelerated nutrient delivery can produce lake-wide effects 

(Schindler and Scheurell 2002, Stendera and Johnson 2006, Donohue and Molinos 2009, 

Ask et al. 2009). Ultraoligotrophic lakes (nutrient concentrations in both the water 

column and lake sediments are extremely low) such as Iliamna can be among the most 

vulnerable to major changes in lake status and function in response to increases in 

nutrient or sediment inputs (e.g., Ramstack et al. 2004, Bradshaw et al. 2005). 

Relationship of Road Density and Roadless Condition to Salmon 

Across many studies in North America, higher abundances and more robust populations 

of native salmonids typically correlate to areas of relatively low road density or large 

roadless blocks (e.g., Baxter et al. 1999, Trombulak and Frissell 2000, Gucinski et al. 

2001). One study from Alberta documented that bull trout occur at substantially reduced 

abundance when even limited road development (road density of less than one mile per 

square mile) occurs in the local catchment, compared to their typical abundance in 

roadless areas (Ripley et al. 2005). In Montana, Hitt et al. (2003) found the incidence of 

hybridization that threatens the westslope cutthroat trout within its native range increased 

with increasing catchment road density. However consistent the correlations, the specific 

causal links between roads and harm to fish are complex and manifold, and seldom laid 

clear in existing research.

Nevertheless, in light of the already dramatic and widespread influence of roads in North 

America (Forman 2000), protection of remaining roadless areas has been identified as a 

potentially crucial and fiscally sound step for effective regional conservation of fish and 

wildlife (Trombulak and Frissell 2000, Gucinski et al. 2001). 

Pipeline Spills

Pipelines have similar environmental effects as roads, with the primary difference being 

that pipelines constantly or semi-continuously transport potentially toxic or harmful 

materials that are only intermittently transported on roadways. In contrast to vehicle 

transport, pipeline transport is often remote from direct oversight by human operators, 

putting heavy reliance on remote leak detection. As a consequence, accidents with 

pipelines can lead to dramatically larger spills than roadway accidents. Beyond pipeline 

design, effective leak detection systems and inspection protocols are crucial for reducing 

risk of leaks and spills, particularly in a relatively active seismic zone such as the Pebble 

Mine area. However, in a review of recent pipeline spills in North America, Levy (2009) 

finds that existing technology and contemporary practice does not provide firm assurance 

against catastrophic spills. 

13
Pipeline crossings of streams are an obvious source of direct channel disturbance and 

sediment entry, and as a result they have received considerable study (e.g., Lawrence and 

Campbell 1980, Lévesque and Dubé 2007, Levy 2009). Pipeline installation can avoid or 

reduce direct disturbance to channels by building full-span pipeline bridges over 

waterways (at less expense than road bridges), or by boring underneath the streambed. 

In addition to the access road, Ghaffari et al. (2011) describes a transportation corridor 

(Figure 3) with four pipelines: 

1) An 8-inch diameter steel pipeline to transport a slurry of copper-molybdenum 

concentrate from the mine site to the port site, with one pump station at the mine 

end of the line and a choke station at the port terminal; 

2) A 7-inch diameter steel line returning reclaimed filtrate water (remaining after 

extraction of the concentrate) to the mine site, fed from a pump station at the port 

site;

3) A 5-inch diameter steel pipeline for pumping diesel fuel from the port site to the 

mine site;

4) An 8-inch diameter pipeline for delivering natural gas from the port site to the 

mine site (specifics of design not yet released). 

All four lines would be contained in close proximity, for an unspecific portion of the 

distance buried about five feet below the ground surface in a common trench, either 

adjacent to or—in steeper terrain—beneath the road surface. The combined lines would 

cross streams via either subsurface borings or suspended bridges, apparently with all 

pipes encased in a secondary containment pipe, although the specific circumstances that 

would receive secondary containment and what the containment design would be are not 

available. In the design presented in Ghaffari et al. (2011, p. 336), there would be no 

secondary encasement of the pipelines away from stream crossings

Available documents do not discuss the composition or potential toxicity of the mineral 

slurry concentrate. However, it is likely that such a slurry would be toxic to some 

organisms and that, due to its concentrated, aqueous form, it would readily transport 

downstream or downslope of a spill site, and deposited materials on terrestrial surfaces 

could generate leachate that enters groundwater systems. Projected chemical 

composition of the returned slurry filtrate is also not available, but it is likely that this 

water would have toxic levels of acidity and/or metals. As for the third line, diesel fuel 

has known toxicity, with both acute and chronic effects on fish and other organisms 

(Levy 2009 and elsewhere). 

Liquefied natural gas, the product that the fourth line would carry, consists primarily of 

methane, which dissipates rapidly when released into water or the air, and is considered 

non-toxic in those circumstances (Levy 2009). Large-scale explosions of natural gas 

pipelines have occurred as a result of the accumulation of gas from slow leaks. Such an 

explosion could pose a major risk of damaging or destroying the other pipelines in the 

14
Pebble Mine corridor, disabling electronic leak detection and severing road access 

necessary for emergency shut-offs or repairs. Containing all four pipelines, the primary 

access road, and the utility lines in a single narrow corridor, while reducing spatial 

footprint impacts like erosion and sedimentation, would also bring the consequence, 

albeit a low-probability one, of compounding the risk and potential scope of 

environmental impact from a catastrophic event such as a methane explosion.

Figure 2. Anticipated location of the road, pipeline, and utility transmission corridor for 

Pebble Mine (Ghaffari et al. 2011, p. 326). The new road and pipeline corridor would 

connect the Pebble Mine operations with a new seaport on Cook Inlet. Not shown is an 

existing north-south connecting tie road from near Nondalton to the Iliamna area (see 

Figure 1). The Pebble segment from Cook Inlet west to near Lake Iliamna would be 

reconstructed over an existing lower-standard roadway. 

15
V. IMPACT FOOTPRINT OF THE PROPOSED PEBBLE MINE TRANSPORTATION 

CORRIDOR ON WATER AND FISH

The Preliminary Assessment of the Pebble Project produced for Northern Dynasty 

Minerals, Ltd. (Ghaffari et al. 2011) included a map and moderately detailed description 

of the route of the potential Pebble Mine transportation corridor (see Fig. 2). The 

following summary relies on that source for road location, while noting the caveat cited 

in the document that the project ultimately proposed may be different. 

According to Ghaffari et al. (2011), the proposed access road and pipelines would 

provide for the basic infrastructural and transportation needs of the mine and its products 

and have a fifty-year design life, consistent with the anticipated operating life of the 

mine. The 86-mile corridor would contain an all-weather road with a two-lane, 30-foot 

wide gravel driving surface. The road would link with the Iliamna airfield, as well as a 

new deepwater port on Cook Inlet, from which ships would transport ore elsewhere for 

processing. Northern Dynasty anticipates that the route would require twenty bridges, 

ranging from 40 to 600 feet in total span, as well as 1,880 feet of causeway passing over 

the upper end of Iliamna Bay and five miles of fill embankment along the shorelines of 

Iliamna and Iniskin Bays. 

The route of the transportation corridor stays south of the Lake Clark National Park 

boundary. About eighty percent of the potential alignment is on private land held by 

Alaska Native Village Corporations and other corporate landowners, with the rest owned 

by the State of Alaska (Ghaffari et al. 2011). The route was reportedly selected with 

regard to transportation and environmental concern in mind, but also with regard to 

avoiding parcels of private land held by individuals (Ghaffari et al. 2011). 

The Preliminary Assessment (Pp. 326-328) characterizes the proposed route as amenable 

to road and pipeline construction with 

. ...terrain favourable for road development. In general, soils are good to 

excellent; where rock is encountered, it is fairly competent, useable for 

construction material and amenable to reasonable slope development. The 

numerous stream crossings appear to have favourable conditions for 

abutment foundations. There are no significant occurrences of permafrost 

or areas of extensive wetlands. Where the terrain is challenging, the rock 

or soil conditions are generally favourable. In intertidal areas, subsurface 

conditions appear favourable for placement of rock to create the required 

road embankment 

A comparison of the route to National Wetlands Inventory (NWI) data available for the 

middle portions indicates that while the proposed route might avoid areas of particularly 

extensive wetlands, nevertheless the route intersects or closely approaches a large number 

of mapped wetlands (see main report). The route also crosses a great number of mapped 

(and likely many more unmapped) tributary streams to Iliamna Lake on its 86-mile 

traverse. The Preliminary Assessment does not identify alternative routes that would 

16
avoid or reduce impacts to wetlands, streams or shorelines. Identifying alternative routes 

to accomplish this would be very difficult given the high density of such hydrologic 

features.

Summarizing the account of Ghaffari et al. (2011, pp. 327-329), traveling eastward from 

the Pebble Mine site, north of Iliamna Lake, the proposed transportation corridor passes 

through diverse terrain and climatic zones. From the mine site, at an elevation of 1,100 

feet above mean sea level, the road traverses variably sloping upland terrain over glacial 

drift before descending to the Newhalen River valley, 11 kilometers north of Iliamna 

Lake. From there, the route crosses variable terrain of dry, open tundra until approaching 

Roadhouse Mountain, about 8 kilometers east of the river. The terrain and climatic 

conditions of this western portion of the route are typical of western interior Alaska, with 

relatively light precipitation, mild summers and winters with windblown snow. East of 

Roadhouse Mountain, the route parallels the shoreline of Iliamna Lake apparently at a 

distance of about five to eight kilometers from the shoreline, spanning a transitional 

landscape of increasing snowpack and extensive spruce-hardwood forest cover. Roughly 

20 kilometers west of Pedro Bay, the route approaches and occupies the shoreline of 

Iliamna Lake, traversing the steep escarpment of Knutson Mountain, an area vulnerable 

to avalanches, debris flows, and other high-energy montane processes. After skirting the 

face of Knutson Mountain above the lakeshore, the route traverses an extensive outwash 

plain northeast of Iliamna Lake, then ascends rugged terrain to cross Iliamna Pass and 

wends its way some 32 kilometers through rugged terrain and increasingly warmer and 

wetter Maritime climatic conditions until descending to the Iniskin Bay port site on Cook 

Inlet.

This report, together with material referenced on wetlands, provides a quantitative 

conceptualization of the potential impact footprint of the Pebble Mine transportation 

corridor on the following known resources: 

1) Wetlands (see main report);

2) Anadromous fish-bearing streams (Figures 3a and 3b); 

3) Sockeye salmon spawning (Figure 4) and rearing (Figure 5) areas in the 

Iliamna Lake system; and

4) Resident fish (Dolly Varden, arctic grayling, rainbow trout, three-spine 

stickleback, nine-spine stickleback, northern pike, and slimy sculpin; Figures 

6a, 6b, and 6c). 

17
Figure 3a. Anadromous fish-bearing streams (documented to support at least one species 

of salmon) crossed by the eastern half of the potential Pebble Mine transportation 

corridor (Chekok Creek east to Y Valley Creek).1 Map compiled from Alaska 

Department of Fish and Game catalog sources (ADFG 2012, Johnson and Blanche 2011a, 

2011b)2, supplemented with additional spawner count data (Morstad 2003). 

1 Median alignment of the corridor was defined by scanning and geo-referencing the Pebble 

transportation corridor route map from Ghaffari et al. (2011. Figure 1.9.2, p.57).

2 Field surveys indicate that ADFG Catalog (Johnson and Blanche 2011a, 2011b) underrepresents the actual extent of salmon spawning (Woody and O’Neal 2010, and Daniel 

Rinella, University of Alaska, Anchorage, AK, unpublished data), although these figures do 

reflect updates based on recent surveys. 

18

 
Figure 3b. Anadromous fish-bearing streams (documented to support at least one 

species of salmon) crossed by the western half of the potential Pebble Mine 

transportation corridor (Upper Talarik Creek east to Canyon Creek).3

 Map compiled 

from Alaska Department of Fish and Game catalog sources (ADFG 2012, Johnson and 

Blanche 2011a, 2011b)4, supplemented with additional spawner count data (Morstad 

2003). 

3 Median alignment of the corridor was defined by scanning and geo-referencing the Pebble 

transportation corridor route map from Ghaffari et al. (2011. Figure 1.9.2, p.57).

4 Field surveys indicate that ADFG Catalog (Johnson and Blanche 2011a, 2011b) underrepresents the actual extent of salmon spawning (Woody and O’Neal 2010, and Daniel 

Rinella, University of Alaska, Anchorage, AK, unpublished data), although these figures do 

reflect updates based on recent surveys. 

19

 
Figure 4. Pattern in abundance of spawning sockeye salmon in Iliamna Lake and 

tributary streams relative to the potential Pebble Mine transportation corridor. A general 

concentration of sockeye spawning is apparent in the northeast portion of Iliamna Lake. 

Spawner density data compiled from Johnson and Blanche (2011a, 2011b, as average 

counts collected with varying regularity between 1955-2011).5

 

5

 Morstad (2003) with additional information on sampling locations from Harry Rich 

(2011, and University of Washington, Seattle, WA, unpublished data) 

20

 
Figure 5. Iliamna Lake juvenile sockeye catches in tow-net sampling, 1961-1976, 

relative to the potential Pebble Mine transportation corridor. High-density rearing sites 

are concentrated in the eastern half of the lake, where the transportation corridor comes 

closest to the lakeshore and intersects with numerous tributaries. Compiled from data 

provided by Harry Rich (2011, and University of Washington, Seattle, WA, unpublished 

data).6

 

6

 Sampling methods for these data are described in Rich (2006). 

21

 
Figure 6a. Resident or nonanadromous fish streams crossed or potentially affected by7

the eastern one-third of the potential Pebble Mine transportation corridor.8

 Compiled 

from the Alaska Freshwater Fish Inventory (AFFI) Database (ADFG 2012, Johnson and 

Blanche 2011a and 2011b, additional information provided by Joe Buckwalter, ADFG, 

Anchorage, AK, Unpublished data). Stream names and fish species known present are 

summarized in Attachment A. 

7

 Secondary tributaries entering trunk streams downstream of the transportation corridor 

are indicated because they could be isolated and freshwater migrant life histories harmed 

by spills affecting the trunk stream. 

8

 Median alignment of the corridor was defined by scanning and geo-referencing the 

Pebble transportation corridor route map from Ghaffari et al. (2011).

22

 
Figure 6b. Resident or non-anadromous fish streams crossed or potentially affected by9

the central one-third of the potential Pebble Mine transportation corridor.10 Compiled 

from the Alaska Freshwater Fish Inventory (AFFI) Database (ADFG 2012, Johnson and 

Blanche 2011a and 2011b, additional information provided by Joe Buckwalter, ADFG, 

Anchorage, AK, Unpublished data). Stream names and fish species known present are 

summarized in Attachment A. 

9

 Secondary tributaries entering trunk streams downstream of the transportation corridor 

are indicated because they could be isolated and freshwater migrant life histories harmed 

by spills affecting the trunk stream. 

10 Median alignment of the corridor was defined by scanning and geo-referencing the 

Pebble transportation corridor route map from Ghaffari et al. (2011).

23

 
Figure 6c. Resident or non-anadromous streams crossed or potentially affected by11 the 

western one-third of the potential Pebble Mine transportation corridor.12 Compiled from 

the Alaska Freshwater Fish Inventory (AFFI) Database (ADFG 2012, Johnson and 

Blanche 2011a and 2011b, additional information provided by Joe Buckwalter, ADFG, 

Anchorage, AK, Unpublished data). Stream names and fish species known present are

summarized in Attachment A. 

11 Secondary tributaries entering trunks downstream of the transportation corridor are 

indicated because they could be isolated and freshwater migrant life histories harmed by 

spills affecting the trunk stream.

12 Median alignment of the corridor was defined by scanning and geo-referencing the 

Pebble transportation corridor route map from Ghaffari et al. (2011).

24

 
Drawing on published conceptualizations that plot the extent of environmental and 

ecological influences of roads as a spatial footprint (Forman 2000, Forman and Deblinger 

2000, Trombulak and Frissell 2000, Jones et al. 2000), Figures 3a through 6c illustrate 

that the potential Pebble transportation corridor could have widespread regional effect on 

the aquatic ecosystems that feed Iliamna Lake. Figures 6a, 6b, and 6c identify both 

upstream and downstream habitat that is susceptible to loss or degradation due to 

structural failures, spills, sedimentation, or other impacts originating in the transportation 

corridor. Through hydrological dispersion of sediment or toxicants, the maps illustrate 

that a large proportion of Iliamna Lake salmon habitat would be vulnerable to indirect 

impact, or direct impact at a point removed from the origin of a spill, either through 

potential exposure to pollutants downstream of the transportation corridor or blockage of 

migration to spawning and nursery habitats upstream. 

A significant fraction of Iliamna Lake’s sockeye salmon resource would be vulnerable to 

impacts from the Pebble transportation corridor. Migration and spawning in these streams 

could be compromised below the corridor crossing by sedimentation or contamination 

from spills, and habitat upstream from the crossings could be cut off from access by spills 

or structural failures. To roughly estimate the proportion at risk, we adjusted the stream 

length potentially affected by the transportation corridor in each system by the average 

surveyed spawner density for that system (Figure 4). This analysis suggests that about 

twenty percent of known stream spawning populations of Iliamna system sockeye 

reproduces in streams and rivers intersected by the Pebble corridor. Moreover, many 

principal sockeye fluvial spawning areas lie in close proximity to road and pipeline 

crossing sites. In addition, a major sockeye salmon beach spawning site is located at the 

mouth of Knutsen Creek (Rich 2006, and unpublished data), a stream that the Pebble 

transportation corridor would cross, making its delta vulnerable to impacts from 

upstream. If the Knutsen Creek delta spawning population is included in the tally of 

potentially affected waters, roughly thirty percent of known Iliamna Lake sockeye 

spawners could be at risk. A similar analysis from the University of Washington 

Fisheries Research Institute came to a similar conclusion (Rich 2011, and unpublished 

data). 

Available data show that rearing sockeye salmon are most concentrated in the eastern 

half of the lake (Figure 5), where the Pebble transportation corridor would intersect with 

numerous direct tributaries to the lake and for some distance would occupy the lakeshore 

itself, posing a high risk, if not a certainty of affecting Iliamna Lake habitats. 

25
VI. MITIGATION MEASURES AND THEIR LIKELY EFFICACY

It is commonly recognized that the environmental impact of a major construction project 

like a road or major pipeline corridor can never be fully mitigated (Trombulak and 

Frissell 2000). Indeed, inherent to the underlying purpose of road projects (i.e., to alter 

natural conditions so that vehicle transportation is possible where it was physically 

impossible before) are changes to landscape structure that not only irretrievably alter 

ecosystem and biological conditions within the construction footprint, but also interrupt 

or modify the natural flux of water, sediment, nutrients, and biota across the ecosystem, 

usually permanently (Darnell et al. 1976, Rhodes et al. 1994, Forman and Alexander 

1998, Forman 2000, Forman and Deblinger 2000, Trombulak and Frissell 2000). 

Moreover, engineering or implementation failures, unanticipated field conditions, and/or 

unforeseen environmental events inevitably test and compromise the effectiveness of 

mitigation measures applied in large projects (e.g., Espinosa et al. 1997, Levy 2009). The 

only sure way to avoid impacts to a freshwater ecosystem from a large road or pipeline 

project is to refrain from building such a project in that ecosystem (Frissell and Bean 

2009). 

Unfortunately the scientific and professional literature on the subject of the effectiveness 

of environmental mitigation measures for water and fish is sparse and poorly synthesized. 

There are lists of standard practices and there are a scattering of short-term, site-specific 

studies of efficacy of mitigation measures for roads and pipelines (e.g., assessment of 

mitigation of the delivery of sediment and its local impact on biota). Some report 

showing adverse impact, or ineffectiveness of mitigation measures, and others report not 

detecting adverse effects, which is often taken as circumstantial evidence that mitigation 

measures were effective. Exceedingly few of these studies extend to medium- or longterm evaluation of mitigation effectiveness, and fewer still have been published in 

accessible peer-reviewed forums. Therefore, evaluating the effectiveness of proposed 

mitigation measures remains a process of best professional judgment and logical 

evaluation of premises, specific environmental context, and likely operational 

circumstances. The release of the Preliminary Assessment for the Pebble project 

(Ghaffari et al. 2011) allows some specific analysis of the potential transportation 

corridor.

A few synthesis documents also provide some guidance (e.g., Rhodes et al. 1994), but the 

over-arching theme is that implementation of site-specific mitigation measures is fraught 

with uncertainty and risk and that, overall, mitigation has proven to be ineffective in fully 

protecting water quality and conserving freshwater fishery resources (Esiponsa et al. 

1997). 

26
Mitigation Measures for Pebble Road and Pipelines

In the following section I cite mitigation measures identified in Ghaffari et al. (2011) for 

the Bristol Bay transportation corridor and briefly assess 1) their likely effectiveness to 

avoid or prevent harm to Bristol Bay water quality and fishery values, 2) possible adverse 

side effects of applying the mitigation measure, and 3) alternative mitigation measures 

that could be more effective, given the project is assumed to proceed. 

As far as practicable, minimize areas of disturbances (Ghaffari et al. 2011, p.329). This 

means restricting the footprint of construction activities and the final footprint of the 

project to the minimum practical surface area (for example, by stacking the road and 

pipelines in a single corridor). The effectiveness of this measure depends on the location 

of disturbance relative to resources at risk. Even a small footprint that involves 

permanent alteration of soils, vegetation, and hydrology can have significant adverse 

effects that propagate across the landscape by hydrologic and other vectors. This 

measure must be practiced in the context of measures to avoid sensitive locations to be 

effective. Secondly, the effectiveness of this measure depends on how other project 

parameters, including capital cost, delimit what is “practicable.” Limiting the area 

disturbed can often involve expensive practices such as long-distance hauling of waste 

material in preference to onsite storage. Finally, it is important to reiterate there are 

potential risks associated with minimizing the footprint of the transportation corridor by 

“stacking” the road and pipelines closely together. A pipeline failure or gas explosion 

could sever the sole available route for ground transportation of equipment and personnel 

to take emergency remedial measures. 

As far as practicable, minimize stream crossings and avoid anadromous streams 

(Ghaffari et al. 2011, p.329). This mitigation measure can be effective if three conditions 

are met: 1) the landscape structure supports a route that avoids and is buffered from 

strong interaction with streams, wetlands, and areas of near-surface groundwater; 2) 

implementation does not result in a route so long and tortuous that it encumbers 

additional environmental risk (e.g., to upland vegetation and wildlife), 3) resources are 

sufficient to ensure that costly but environmentally sounder locations and possibly longer 

routes are “practicable.” Ghaffari et al. (2011, pp. 329-330) lists several other criteria that 

constrain choice of road location, such as: 

1) Avoiding certain “unfavorable” land ownerships; 

2) Avoiding potential (albeit unspecified) geologic hazards; 

3) Keeping road gradients under 8 percent;

4) Maintaining minimum curvature and design speeds; 

5) Facilitating high axle loads for transporting assembled mine equipment; 

6) Optimizing crossings of soils suitable to maintaining roadway structure and 

stability;

7) Optimizing access to sources of construction and surfacing rock; 

8) Incorporating minimum 2.5–foot (76 centimeter) ditches (possibly necessary 

for maintaining subgrade stability in many wet or seasonally wet areas); and 

9) Minimizing area of disturbance. 

27
These competing objectives for the roadway, coupled with the large number of streams in 

the landscape between the Pebble Mine site and Cook Inletserve to limit the 

effectiveness of this measure. To be most effective, minimizing stream crossings must 

take primacy above other objectives of economic or operational convenience in project 

siting and route location. However, even then, one potential side effect of basing route 

selection on minimization of stream crossings in a stream-rich landscape would likely be 

a route that is tortuous, countervailing the preceding mitigation measure of minimizing 

area of disturbance. Hence the two most potentially effective mitigation measures can 

stand in opposition to each other, especially in landscapes of relatively high stream 

density. 

Appropriate Best Management Practices (BMPs) will be utilized for the maintenance of 

the road during operations and construction. Ghaffari et al. (2011, p. 370). The 

Preliminary Assessment does not identify the appropriate practices for road maintenance 

and construction, so it is not possible to specifically address their likely effectiveness at 

reducing water quality and fisheries impacts. Specifically with regard to maintenance, 

BMPs should include a strict prohibition on the disposal of material generated from 

grading and snow removal into surface waters, and should specify grading practices that 

retain a local road contour necessary to disperse road surface drainage away from 

streams, rivers, Iliamna Lake and areas that drain to those waterways (Weaver and 

Hagans 1994, Wemple et al. 1999, Furniss et al. 1991, Moll 1999). Construction 

specifications should also designate sites for waste rock disposal and temporary materials 

storage and stipulate that they be in locations with minimum risk of subsequent transport 

of material to streams, rivers, or Iliamna Lake, whether by water, wind, or mass failure 

(Weaver and Hagans 1994). These practices pose minimal risk of environmental side 

effects, though they may increase annual operational costs. However, because these 

practices are also effective at reducing roadway harm from erosion, over years they may 

reduce maintenance and repair costs of the roadway. 

Road dust abatement measures. Ghaffari et al. (2011, p. 458) mentions dust suppression 

as a generic need, but the only allusion to specific mitigation regards procurement of a 

water spreading truck (Ghaffari et al. 2011, p. 313). The Preliminary Assessment 

mentions developing a dust dispersion model as part of the permitting process for air 

emissions (Ghaffari et al. 2011, p. 458), but it does not address dust impacts to surface 

waters. Depending on mineralogy, water application can be effective at reducing dust 

transport, if application is frequent and of appropriately limited volume (USDA Forest 

Service 1999). There are, however, offsetting factors: moderate or heavy application of 

water that exceeds the very low infiltration capacity of the road surface mobilizes dust in 

fluid runoff instead of aerial deposition. Wherever a road is in close proximity to surface 

waters, such runoff can deliver suspended sediments, perhaps quite frequently, to 

locations where, or at seasons when, they are otherwise virtually nonexistent. Loss of 

fines from the road rock matrix can contribute to breakdown and accelerated erosion of 

the road surface (USDA Forest Service 1999). On the other hand under-application of 

water fails to fully abate dust generation. 

28
Dust abatement measures can bring unintended side effects. Even when dust abatement 

is effective in retaining fines within the road rock matrix during the dry season, these 

fines are simply mobilized by water and transported to the surrounding landscape in wet 

season runoff (Reid and Dunne 1984). The fine sediments are not eliminated—merely 

reallocated. Other dust controls, including chloride salts, clays, lignosulfanate or other 

organic compounds, and petroleum distillates (Hoover 1981) bring risk of toxic effects 

when they run off and enter surface waters, though little research is available to assess 

their environmental risks or safe conditions of application (USDA Forest Service 1999). 

In the case of chloride salts, one recommendation is to avoid application within 8 meters 

of surface waters or anywhere groundwater is near the surface (USDA Forest Service 

1999). Adverse biological effects are likely to be particularly discernible in naturally 

low-conductivity waters like those of Bristol Bay, although research is needed to 

substantiate this speculation. The best practice to minimize dust pollution is to avoid 

road construction; the next most effective mitigation is surfacing all roadways with highgrade asphalt pavement, with diligent maintenance of the paved road surfaces.

Paving can measurably reduce (though not eliminate) the chronic generation and delivery 

of both wet-weather surface-erosion and dust (Furniss et al. 1991, Weaver and Hagans 

1994). However, asphalt production, deposition, and weathering generates hydrocarbons 

that may, in some circumstances, be harmful to aquatic life (Spellerberg 1998, 

Trombulak and Frissell 2000). In addition, off-site transfer of heavy metals and other 

contaminants from road treatments such as deicing salts could be more rapid and direct 

from paved road surfaces. Moreover, in the case of the potential Pebble transportation 

corridor, pavement could complicate excavation needed to access pipelines buried under 

the road for visual inspection or repairs of leaks. 

River and stream crossing structures have been designed to minimize the impact of the 

project on areas of sensitive habitat (Ghaffari et al. 2011, p. 370). The Preliminary 

Assessment further specifies that structural elements, including foundation elements, will 

be designed to comply with a Memorandum of Agreement between ADOT and ADFG 

regarding the design of culverts for fish passage and habitat protection. Wherever 

culverts are not “suitable,” Ghaffari et al. state the road would incorporate single- or 

multiple-span bridges, with specifications based on “hydrological considerations, local 

topography and fish passage requirements.” Although criteria for determining crossing 

structure type are not provided, the Preliminary Assessment identifies thirteen possible 

multi-span bridge crossings, at “major” rivers, including 600-foot spans both at the 

Newhalen River and across tidal flats at Iliamna Bay (Ghaffarri et al. 2011, p. 332). 

Road crossing designs are much improved over historic practice, but where rivers are 

wide and river or stream channels shift location frequently, any crossing structure short of 

fully spanning the channel migration or flood-prone valley width can prove problematic. 

Because of the nature of design structures and geomorphic setting, crossings of small 

streams (under about 3 meters in width) pose greater risk of causing barriers to animal 

migration and movement of sediment and natural debris, whereas crossings of larger 

streams pose risk of erosion, sedimentation, channel and floodplain alteration, and 

29
delivery of pollutants from spills. The importance of small streams in Bristol Bay for 

Dolly Varden and other fish species (Woody and O’Neal 2010) underscores the need for 

culverts to provide fish passage and maintain fish habitat, even where salmon are absent. 

Numerous studies also document that connectivity between small headwater streams 

(including streams with intermittent or seasonal flow) and downstream habitats is 

important and, in some cases, critical for productivity and survival of salmonids (e.g., 

Hilderbrand and Kirshner 2000, Young et al. 2004, Fausch et al. 2002, Hastings 2005, 

Wigington et al. 2006, Bryant et al. 2009). 

In general, culvert crossings of small streams remain problematic, even under 

contemporary standards and practices as applied by state highway departments and land 

management agencies. Gibson et al. (2005) surveyed a 210-kilometer segment of the 

Trans-Labrador highway, newly constructed under prevailing Canadian government and 

provincial regulations for fish protection, and found that more than half of the culverts 

posed fish passage problems due to inadequate design or poor installation. Chestnut 

(2002), in a survey of stream crossings in Kamloops, British Columbia, found that out of 

31 culverts assessed, all but one failed to meet Department of Fisheries and Oceans 

objectives for juvenile fish passage and maintenance of fish habitat. In an audit of two 

other Provincial Forest Districts in British Columbia, Harper and Quigley (2000) 

concluded about a third of road culverts blocked fish passage to upstream habitat. 

In small streams without significant near-surface groundwater associations, the 

effectiveness of different stream crossing structures depends on the geomorphic setting, 

including stream gradient and channel stability, road slope and angle of interception, 

flashiness of water and sediment flows, potential for ice rafting and plugging, and 

abundance and size range of wood and other waterborne debris. In small prairie streams, 

for example, Bouska et al. (2010) found that large box culverts were less disruptive of 

stream morphology and hydrodynamics than were low water crossings and corrugated 

metal culverts. Large-width, bottomless arch or “squashed design” culverts that preserve 

or restore a natural channel bed material train through the length of the culvert are the 

current standard norm for stream crossings to maintain both physical and biological 

connectivity (Weaver and Hagans 1994, FSSSWG 2008). In recent years, the US Forest 

Service has worked to reduce risk of failure and improve passage of fish and other biota 

at road at road crossings using a new so-called “Stream Simulation” design protocol for 

culvert crossings of small streams that emphasizes dramatically wider, open-bottom arch 

stream crossing designs that strive to maintain both geomorphic and biological continuity 

through the crossing (FSSSWG 2008). Greater expense of initial design and installation 

may be compensated by longer life spans (round corrugated steel culverts commonly 

have a functional life span of 20 years, if properly functioning) and fewer emergency 

maintenance and repair costs (Weaver and Hagans 1994). 

Effective mitigation of adverse roadway impacts to streams must account explicitly not 

just for the passage of fish and surface waters; in ecosystems like Bristol Bay that are rich 

in shallow groundwater, roadways must also avoid disrupting or obstructing hyporheic 

flow paths and shallow aquifers. Short of not building new roads altogether, the most 

effective practice to avoid alteration of hydrology and hydrologic connectivity is to locate 

30
the route well away from streams, wetlands, springs, seeps, areas of near-surface 

groundwater, pond and lake shorelines, and alluvial fans and glacio-alluvial valley trains 

where frequently shifting stream courses are present. Due to the number and density of 

streams, zones of near-surface groundwater, and associated wetlands in the area of the 

potential transportation corridor (Hamilton 2007), complete avoidance of “sensitive 

habitat” would be exceedingly difficult. If avoidance of these sensitive hydrologic 

features is impossible, the next best mitigation is bridge the roadway across them, 

completely spanning the area of both surface water and near-surface groundwater, 

thereby reducing direct physical intersection of the roadway and water features. At 

streams, crossings should occur only where channels are stable, not migrating and not 

branching. Where long suspensions are necessary to bridge multiple or coextensive 

hydrologic features, special engineering is required to manage stormwater drainage that 

accrues on the extensive suspended roadway and route and disperse this discharge to 

areas well away from surface waters.

Where spanning extensive areas of shallow groundwater is impracticable (e.g., due to 

expense), the next most effective mitigation would be to “lift” the road surface over them 

by use of porous fills. Porous fills (commonly large, angular open-framework rock 

capped by a surface of mixed material) can provide a stable road prism and support heavy 

vehicle loads, while passing overland or sheet flow with limited concentration and 

maximum dispersion of water, thereby reducing erosive forces and impacts to local 

hydrology (Moll 1999). Nevertheless, porous fills do partly obstruct surface drainage, 

blocking the movement of sediment, debris, and aquatic organisms and despite some 

filtering capacity, they do not fully control delivery of sediment and other pollutants from 

the road surface into surface waters. Under heavy tire loads, porous fill road beds may, 

over time, subside into subsurface soils and alluvial deposits, allowing native fines to 

enter and clog the porous matrix, eventually making it a barrier to subsurface flow. 

Burial in a common trench. (Ghaffari et al. 2011, p. 336). Burial aids in insulation of the 

pipeline. It also can reduce pipeline impact on wildlife movements, and in steep, 

mountainous terrain, it can partially protect pipelines from damage and potential spills 

caused by surface processes like avalanches, landslides and debris flows (Levy 2010). 

Equally important, clustering of pipelines reduces the direct spatial footprint of 

disturbance to habitat by concentrating construction and maintenance activity. The 

smaller footprint, in turn, minimizes the area destabilized by excavation and backfill, thus 

reducing impacts to water quality from construction site runoff. The downsides of 

pipeline burial are that: 1) it prevents visual inspection of the lines for leakage and visual 

monitoring of spilled materials; 2) it typically does not incorporate secondary 

containment measures for spills and leaks; and 3) it can disrupt subsurface hydrology by 

severing, damming, or capturing buried flow paths. Visual inspection is a vital backup to 

electronic leak detection systems and may be the only sure way to detect some chronic, 

slow leaks. Finally, buried pipelines are still vulnerable to stress and rupture from 

subsurface processes, such as earthflows, slumps, and seismic shocks. 

Secondary containment of buried lines, using an impermeable lining for the trench, could 

help limit the discharge of material in the event of leaks or spills, but would have the 

31
opposing effect of causing greater distortion of natural subsurface flow paths. By acting 

as a subsurface dam, a lined trench could not only disrupt natural hydrology patterns, but 

by obstructing subsurface water flow, belowground containment structures could 

complicate the management of drainage that is necessary to maintain the road surface and 

the trench itself. From the standpoint of the protection of water quality and fish 

resources, ideal mitigation measures could include: 1) keeping the pipelines above 

ground and visible (except where landslide and avalanche risks are moderate to high); 2) 

incorporating some means of secondary containment for spills and leaks; 3) installing 

manual shutoff valves at either side of all surface water crossings and all locations 

vulnerable to damaging landslides or avalanches; and 4) implementing robust plans for 

both very frequent or full-time visual inspection for leaks, and rapid response for 

containment, shutdown, repair, and disposal of contaminated material when leaks do 

occur. Note that these measures may have adverse side effects; for example, elevated 

pipelines may be more disruptive of wildlife movements, such as caribou migrations. 

There is another drawback of clustering that the above mitigation measures would not 

resolve. With common proximity of the lines, there might be some risk that natural gas 

leakage and subsequent explosion could both damage the other lines and hinder rapid 

response to repair damage and contain spills (due to damage to the road). This risk bears 

close examination by appropriate experts.

Boring pipelines under stream (Ghaffari et al. 2011, p.337). Horizontal boring of a 

pipeline under stream crossings can reduce much of the channel disruption, erosion and 

sedimentation associated with trenching and exposed line surface crossings. However, 

the method suffers from the same drawbacks identified above under Burial in a common 

trench. In particular, leakage of the lines under the stream course could result in 

undetected contamination of hyporheic, thence surface waters. To reduce impacts to fish 

and water quality, the most effective mitigation measure likely would include suspending 

pipelines (along with road crossings) on full-span bridges that minimize disturbance to 

surface water, as well as containing the pipelines in a secondary pipe designed for and 

operated under a plan that includes frequent visual inspection and robust spill response 

procedures. Burial—with secondary containment—could be appropriate for unavoidable 

crossings of areas with unstable slopes prone to landslides and avalanches. Note that 

these measures may have adverse side effects; for example, elevated pipelines may be 

more disruptive of wildlife movements. 

Secondary containment pipe (“encased in a protective layer”) for overhead stream 

crossings on bridges (Ghaffari et al. 2011, p. 337). Secondary containment is a 

particularly important measure for isolating and managing leaks or spills wherever the 

pipeline is directly above surface water. Ideally, some form of secondary containment 

should extend to other locations where leaks or spills could reach and contaminate 

surface or subsurface waters. There also should be specific procedures and requirements 

for response and materials handling in the event of leaks or spills into the containment 

system, to prevent secondary pollution from leaching or spill of contaminated materials.

Advance designation and preparation of an array of well-distributed storage pads for 

contaminated soils at dry, stable sites far removed from surface waters or shallow 

32
groundwater would be among the needs to implement this measure effectively. These 

precautionary structural measures are likely to be costly. 

Manual isolation valves on either side of major river crossings (Ghaffari et al. 2011, p. 

376). The Preliminary Assessment does not define “major” river crossings, but they 

would presumably include multi-span crossings such as that of the Newhalen River. The 

effectiveness of manual closure correlates directly to the effectiveness of leak detection 

and rapid response. Coupled with full-time, fully redundant electronic and visual leak 

detection systems and valve locations as suggested above, manual valves could 

considerably improve the odds of successful stream protection from leaks and spills. 

Again, the surveillance and logistical measures needed to support a rapid response to 

accidents can be costly. 

Electronic Leak Detection Systems (Ghaffari et al. 2011, p. 376). The Preliminary 

Assessment discusses implementing an electronic leak detection system for the pipelines, 

using pressure transmitters located along the length of the lines. It also specifies a 

SCADA (Supervisory Control and Data Acquisition) system for monitoring and control 

of the pumping stations, with fiber optic communications between the concentrator and 

the port site tying the detection systems together. The most effective approach to leak 

detection includes redundant systems for each separate pipeline. However, the proposed 

approach appears to tie leak detection for all four systems to a single fiber optic line. 

Coupled with the close proximity of the four pipelines, a single communications line 

increases the chance that leak detection could be disrupted by the same event that 

triggered a leak (e.g., a seismic dislocation, lake seiche wave, or large landslide). As 

suggested above, providing for rigorous visual inspection would further increase the 

effectiveness of electronic leak detection and reduce the risk of undetected spills.

Likely Effectiveness of Mitigation Measures

Special circumstances prevail in Bristol Bay and specifically in the area proposed for 

the Pebble Mine road and pipeline corridor that render the effectiveness of standard 

or even “state of the art” mitigation measures highly uncertain. These include: 

1) Subarctic extreme temperatures and frozen soil conditions could complicate 

planning for remediation, with outcomes uncertain as a result of variable 

conditions and spill material characteristics. 

2) Subarctic climatic conditions limit the lushness and rapidity of vegetation growth 

or re-growth following ground disturbance, reducing the effectiveness of 

vegetated areas as sediment and nutrient filtration buffers. 

3) Widespread and extensive areas of near-surface groundwater and seasonally or 

permanently saturated soils limit potential for absorption or trapping of road 

runoff, and increase likelihood of its delivery to surface waters. 

4) Likelihood of ice flows and drives during thaws that can make water crossing 

structures problematic locations for jams and plugging. 

33
5) Seismically active geology; even a small increment of ground deformation can 

easily disturb engineered structures and alter patterns of surface and subsurface 

drainage in ways that render engineered mitigations inoperative or harmful. 

6) Remote locations that are not frequented by human users, hence mitigation 

failures and accidents may not be detected until substantial harm to waters has 

occurred. 

While many possible mitigation measures can be identified and listed in a plan, they 

cannot all be ideally applied in every instance. Mitigation measures are commonly 

mutually limiting or offsetting in field application, as is common knowledge to 

practicing engineers. As a salient example for the potential Pebble Mine corridor, 

choosing a road location that minimizes crossings of streams, wetlands, and areas of 

shallow groundwater in a landscape that is rich in those hydrologic features can result 

in a tortuous alignment, or one that is substantially lengthened, and might involve 

substantially more vertical curvature to accommodate upland terrain. A tortuous 

alignment greatly increases the total ground area disturbed, and increased road 

curvature in either horizontal and vertical dimensions may increase risk of traffic 

accidents and consequent spills. Moreover in this case it would increase the length 

and structural complexity of the road-parallel pipelines. Avoidance of sensitive 

features therefore elevates other environmental risks. This underscores the fact that 

there is no “free lunch” when it comes to mitigating the environmental impacts of a 

new road in a previously roadless landscape.

VII. CONCLUSIONS

• Bristol Bay’s robust and resilient salmon fishery is in part associated with the 

watershed’s extremely high quality waters and high integrity freshwater 

ecosystems, minimally impacted by roads and industrial development. 

• A second major contributor to the Bristol Bay watershed’s productivity for 

salmon is its abundant and extensive near-surface groundwater and strong vertical 

linkage between surface waters and groundwaters, across a wide range of stream 

sizes and landscape conditions.

• Any environmental analysis and planning of a road project such as the Pebble 

Mine road must consider the significance of initial road development as an 

economic and social stepping stone to future roads and developments. 

• Roads, in particular can foster the incremental decline of salmon and other native 

fishes by their own direct environmental impact, but equally important is that 

roads facilitate a variety of human activities that bring their own suite of impacts 

including increased access to primitive lands, increasing legal and illegal hunting 

and fishing, use of off-highway vehicles, increased mineral prospecting, and 

others. 

34
• For the Pebble road corridor, each stream or wetland crossing has the potential for 

impacts to not just salmon populations in the stream itself, but also downstream in 

Iliamna Lake, which is in close proximity. 

• The Pebble transportation corridor poses risks of direct and acute impacts to 

salmonids, including possible loss of populations due to blocking of migration 

pathways from spills or from stream crossing dysfunctions. Like any such 

development, it will certainly cause chronic, pervasive “press disturbances” 

(Yount and Niemi 1990) all along its length and for its entire existence, 

contributing to deterioration of quality of spawning habitats, reduced habitat 

diversity, disrupted groundwater hydrology, alteration of roadside vegetation, and 

related impacts that stem from construction, operation and maintenance.

• Many environmental mitigation measures identified for the Pebble Project suffer 

from being mutually exclusive or offsetting, from being potentially superseded or 

limited by engineering, operational, maintenance, or fiscal concerns, or are likely 

to be ineffective given the hydrogeomorphology, subarctic climate and 

hydrogeologic conditions, seismicity, and pristine condition and inherent 

sensitivity of the environment in Bristol Bay watershed.

35
ACKNOWLEDGEMENTS

Rebecca Shaftel of the Alaska Natural Heritage Program, Anchorage contributed 

immensely to the analytic and graphical content of this report; she prepared all the maps. 

We thank Harry Rich and Dr. Thomas Quinn of the University of Washington School of 

Fisheries and Aquatic Sciences for critical data and analytic leadership in the assessment 

of risk to sockeye salmon and other fishery resources.

36
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44
Attachment A 

Resident fish streams potentially affected, crossed or closely approached by the potential 

Pebble Mine transportation corridor.

Compiled from the Alaska Freshwater Fish Inventory (AFFI) Database (ADFG 2012, 

Johnson and Blanche 2011a and 2011b, additional information provided by Joe 

Buckwalter, ADFG, Anchorage, AK, Unpublished data). 

Stream names from the Alaska Freshwater Fish Inventory Database. 

“Yes (spp?)” entry in the Anadromous Fish column means the AFFI database classifies 

the stream as “Anadromous,” but anadromous species present are not identified.

45
Stream 

No.

(west to 

east)

Stream Name

(if known)

NHD Reach Code Stream 

Order 

(Map)

Resident 

Fish

Anadromous 

Fish

1 19030206007351 1 Dolly 

Varden, 

rainbow 

trout, slimy 

sculpin

Coho

2 19030206007354 1 Dolly 

Varden, 

slimy 

sculpin

Coho

3 Upper Talarik Cr. 19030206007015 4 Arctic 

grayling, 

Dolly 

Varden, 

ninespine 

stickleback, 

rainbow 

trout, slimy 

sculpin, 

threespine 

stickleback

Chinook, 

chum, coho, 

sockeye

4 19030206007159 1 [none 

reported]

Coho

5 19030206007175 1 Dolly 

Varden, 

ninespine 

stickleback, 

rainbow 

trout, slimy 

sculpin, 

threespine 

stickleback

6 19030205007587 2 Ninespine 

stickleback, 

slimy 

sculpin

7 19030205007593 2 Dolly 

Varden

46
Stream 

No.

(west to 

east)

Stream Name

(if known)

NHD Reach Code Stream 

Order 

(Map)

Resident 

Fish

Anadromous 

Fish

8 19030205007598 2 Dolly 

Varden

9 19030205007606 2 Slimy 

sculpin

Yes (spp.?)

10 19030205007602 2 Slimy 

sculpin 

Yes (spp.?)

11 19030205007615 2 Arctic 

grayling, 

longnose 

sucker

12 Newhalen River 19030205000002 5+ Arctic 

grayling, 

jumpback 

whitefish, 

longnose 

sucker, 

rainbow 

trout, round 

whitefish, 

sculpin

Arctic char, 

chinook, 

coho, 

sockeye

13 19030205013069 3 [no data]

14 19030205013055 2 [no data]

15 19030205013057 1 [no data]

16 19030205013041 2 [no data]

17 19030205010623 1 [no data]

18 19030205010628 1 [no data]

19 19030205010629 1 [no data]

20 Roadhouse Cr 19030206006712 1 Slimy 

sculpin

21 NW Eagle Bay 

Cr

19030206006678 2 Dolly 

Varden

Arctic char, 

sockeye

22 19030206006677 1 Ninespine 

stickleback, 

slimy 

sculpin

23 19030206006644 2 Dolly 

Varden 

47
Stream 

No.

(west to 

east)

Stream Name

(if known)

NHD Reach Code Stream 

Order 

(Map)

Resident 

Fish

Anadromous 

Fish

24 19030206006671 2 Dolly 

Varden, 

ninespine 

stickleback 

25 19030206006663 2 Dolly 

Varden, 

ninespine 

stickleback

Arctic char, 

sockeye

26 NE Eagle Bay Cr 19030206006654 1 Ninespine 

stickleback, 

Rainbow 

trout, slimy 

sculpin

Sockeye

27 Young’s Cr, 

mainstem

19030206006598 3 Dolly 

Varden, 

ninespine 

stickleback, 

rainbow 

trout, slimy 

sculpin

Arctic char, 

coho, 

sockeye

28 Young’s Cr, east 

branch 

19030206006553 3 Dolly 

Varden, 

rainbow 

trout, slimy 

sculpin

Arctic char, 

coho, 

sockeye

29 Chekok Cr, west 

branch 

19030206006533 2 [no data] Arctic char, 

coho, 

sockeye

30 Chekok Cr, 

mainstem

19030206032854 3 Rainbow 

trout, slimy 

sculpin

Arctic char, 

sockeye

31 Canyon Cr 19030206006359 3 Dolly 

Varden, 

slimy 

sculpin

Arctic char, 

sockeye

32 19030206006336 1 [no data]

33 19030206006337 1 [no data]

34 19030206006236 1 [no data]

48
Stream 

No.

(west to 

east)

Stream Name

(if known)

NHD Reach Code Stream 

Order 

(Map)

Resident 

Fish

Anadromous 

Fish

35 19030206006331 1 [no data]

36 19030206006329 1 [no data]

37 19030206006327 1 [no data]

38 19030206006325 1 [no data]

39 19030206006322 1 [no data]

40 19030206006320 1 [no data]

41 19030206006321 1 [no data]

42 19030206006318 1 [no data]

43 19030206006317 1 [no data]

44 19030206006316 1 [no data]

45 19030206006315 1 [no data]

46 19030206006314 1 [no data]

47 19030206006251 1 [no data]

48 Knutson Cr 19030206006255 4 Dolly 

Varden, 

slimy 

sculpin

Arctic char, 

sockeye

49 19030206006280 1 Dolly 

Varden, 

slimy 

sculpin

50 Pedro Cr 19030206006239 1 [no data]

51 Russian Cr 19030206006248 1 [no data]

52 19030206006231 1 [no data]

53 19030206006230 1 [no data]

54 19030206006228 1 [no data]

55 19030206006227 1 Dolly 

Varden, 

slimy 

sculpin

56 19030206006222 1 [no data]

57 Pile River 19030206000474 3 Slimy 

sculpin, 

threespine 

stickleback

Arctic char, 

sockeye

49
Stream 

No.

(west to 

east)

Stream Name

(if known)

NHD Reach Code Stream 

Order 

(Map)

Resident 

Fish

Anadromous 

Fish

58 (Long L. 

outlet) 

19030206010632 1 Threespine 

stickleback, 

rainbow 

trout, slimy 

sculpin

Yes (spp?)

58a 19030206010632_2 1 [no data] Yes (spp?)

59 Iliamna R 19030206000032 4 Dolly 

Varden, 

slimy 

sculpin

Chinook, 

chum, coho, 

pink, 

sockeye, 

Dolly Varden

60 19030206005773 1 [no data]

61 19030206005761 2 Dolly 

Varden, 

slimy 

sculpin

62 19030206005759 1 [no data]

63 19030206005754 2 [no data]

64 Chinkelyes Cr 19030206005737 2 (at 

crossing)

Slimy 

sculpin

65 19020602004863 1 [no data]

66 19020602004864 1 [no data]

67 19020602004865 1 [no data]

68 19020602004866 1 [no data]

69 Y-Valley Cr 19020602004967 1 Dolly 

Varden

Arctic char, 

chinook, 

chum, coho, 

pink, 

sockeye 

70 19020602004882 No fish 

recorded or 

observed

50
AN ASSESSMENT OF POTENTIAL MINING IMPACTS ON 

SALMON ECOSYSTEMS OF BRISTOL BAY, ALASKA 

VOLUME 3—APPENDICES E-J

Appendix H: Geologic and Environmental Characteristics of 

Porphyry Copper Deposits with Emphasis on Potential Future 

Development in the Bristol Bay Watershed, Alaska 
Geologic and Environmental Characteristics of Porphyry 

Copper Deposits with Emphasis on Potential Future 

Development in the Bristol Bay Watershed, Alaska 

By Robert R. Seal, II

U.S. Department of the Interior Approved: April 2012

U.S. Geological Survey Revised and Approved: December 2012
Geologic and Environmental Characteristics of Porphyry Copper Deposits 

ii

Contents

Introduction.................................................................................................................................................................... 1

Geologic Characteristics of Porphyry Copper Deposits................................................................................................. 2

Geologic Setting of the Bristol Bay Watershed .......................................................................................................... 2

Mineral Resource Potential of the Nushagak and Kvichak Watersheds..................................................................... 2

General Characteristics of Porphyry Copper Deposits............................................................................................... 4

Geologic Features: ............................................................................................................................................. 4

Economic Characteristics: .................................................................................................................................. 5

Geology of Bristol Bay Porphyry Copper Deposits: ............................................................................................ 6

Mining and Beneficiation Considerations:........................................................................................................... 9

Environmental Characteristics of Porphyry Copper Deposits .......................................................................................10

Overview ...................................................................................................................................................................10

Acid-Generating Potential .........................................................................................................................................10

Waste Rock...............................................................................................................................................................13

Tailings .....................................................................................................................................................................17

Copper Concentrate..................................................................................................................................................22

Summary ......................................................................................................................................................................24

References Cited..........................................................................................................................................................26

Figures

Figure 1. Generalized geologic map of the central part of the Bristol Bay watershed showing the general locations 

of the Pebble, Humble, and Big Chunk prospects.. ....................................................................................................... 3

Figure 2. Map showing location of Phanerozoic porphyry deposits with representative deposits labeled.. ............... 5
Geologic and Environmental Characteristics of Porphyry Copper Deposits 

iii

Figure 3. Idealized cross section through a porphyry copper deposit showing the relationship of the ore zone to 

various alteration types.................................................................................................................................................. 6

Figure 4. Grade-tonnage characteristics of the Pebble deposit compared to other porphyry-type deposits. . ......... 8

Figure 5. Plot of neutralizing potential (NP) and acid-generating potential (AP) for mineralized rock types at the 

Bingham Canyon porphyry copper deposit, Utah.. ...................................................................................................... 11

Figure 6. Plan view of the distribution of net-neutralization potential (NNP) values at the Bingham Canyon porphyry 

copper deposit, Utah.................................................................................................................................................... 12

Figure 7. Dissolved copper concentrations and water hardness values for various potential end-member waters 

around the Pebble site in the Bristol Bay watershed associated with waste-rock piles.. .............................................. 16

Figure 8. Dissolved copper concentrations and water hardness values for various potential end-member waters 

around the Pebble site in the Bristol Bay watershed associated with a tailings impoundment..................................... 22

Tables

Table 1. Deposit types with significant resource potential for large scale mining in the Nushagak and Kvichak 

watersheds.. .................................................................................................................................................................. 4

Table 2. Global grade and tonnage summary statistics for porphyry copper deposits (n = 256; Model 17, Singer 

and others, 2008) compared to the Pebble deposit... .................................................................................................... 7

Table 3. Annual consumption of copper, molybdenum and gold compared to the Pebble deposit.......................... 7

Table 4. Summary of geochemical results from humidity-cell tests on waste-rock samples conducted by the 

Pebble Partnership (2011). .......................................................................................................................................... 15

Table 5. Geochemical composition of porphyry copper tailing samples. ............................................................... 18

Table 6. Geochemical composition of test tailings samples from the Pebble deposit from metallurgical testing 

conducted by the Pebble Partnership.. ........................................................................................................................ 19
Geologic and Environmental Characteristics of Porphyry Copper Deposits 

iv

Table 7. Summary of geochemical results from humidity-cell tests on tailing samples and the supernatant solution 

from metallurgical testing conducted by the Pebble Partnership. ................................................................................ 21

Table 8. Geochemical analysis of the copper concentrate from the Aitik porphyry copper mine, Sweden. ........... 23

Table 9. Geochemical analyses of dissolved constituents in leachates from tailings and copper concentrate from 

the Aitik Mine, Sweden.. .............................................................................................................................................. 25
Geologic and Environmental Characteristics of Porphyry Copper Deposits 

1

Geologic and Environmental Characteristics of Porphyry 

Copper Deposits with Emphasis on Potential Future 

Development in the Bristol Bay Watershed, Alaska

By Robert R. Seal, II

US Geological Survey

954 National Center

12201 Sunrise Valley Drive

Reston, VA 20192

Introduction

This report is prepared in cooperation with the Bristol Bay Watershed Assessment being conducted by the U.S. 

Environmental Protection Agency. The goal of the assessment is to help understand how future large-scale 

development in this watershed may affect water quality and the salmon fishery. Mining has been identified as a 

potential source of future large scale development in the region, especially because of the advanced stage of 

activity at the Pebble prospect. The goal of this report is to summarize the geologic and environmental 

characteristics of porphyry copper deposits in general, largely on the basis of literature review. Data reported in the 

Pebble Project Environmental Baseline Document, released by the Pebble Limited Partnership in 2011, are used to 

enhance the relevance of this report to the Bristol Bay watershed.

The geologic characteristics of mineral deposits are paramount to determining their geochemical signatures in 

the environment. The geologic characteristics of mineral deposits are reflected in the mineralogy of the 

mineralization and alteration assemblages; geochemical associations of elements, including the commodities being 

sought; the grade and tonnage of the deposit; the likely mining and ore-processing methods used; the 

environmental attributes of the deposit, such as acid-generating and acid-neutralizing potentials of geologic 

materials; and the susceptibility of the surrounding ecosystem to various stressors related to the deposit and its 

mining, among other features (Seal and Hammarstrom, 2003). Within the Bristol Bay watershed, or more 

specifically the Nushagak and Kvichak watersheds, the geologic setting is permissive for the occurrence of several 

mineral deposit types that are amenable for large-scale development. Of these deposit types, porphyry copper 

deposits (e.g., Pebble) and intrusion-related gold deposits (e.g., Shotgun) are the most important on the basis of 

the current maturity of exploration activities by the mining industry. The Pebble deposit sits astride the drainage 

divide between the Nushagak and Kvichak watersheds, whereas the Humble, Big Chunk, and Shotgun deposits 

are within the Nushagak watershed. The Humble and Big Chunk prospects are geophysical anomalies that exhibit 

some characteristics similar to those found at Pebble. Humble was drilled previously in 1958 and 1959 as an iron 

prospect on the basis of an airborne magnetic anomaly. Humble is approximately 85 miles (137 km) west of 
Geologic and Environmental Characteristics of Porphyry Copper Deposits 

2

Pebble; Big Chunk is approximately 30 miles (48 km) north-northwest of Pebble; and Shotgun is approximately 110 

miles (177 km) northwest of Pebble. The H and D Block prospects, west of Pebble, represent additional porphyry 

copper exploration targets in the watershed.

Geologic Characteristics of Porphyry Copper Deposits

Geologic Setting of the Bristol Bay Watershed

The Nushagak and Kvichak watersheds are characterized by a complex geologic history. The history, going 

back at least 100 million years, has been dominated by northward movement and subduction of the oceanic crust 

beneath the Alaskan continental landmass, which continues today. The northward subduction of oceanic crust led 

to the accretion of island land masses to the Alaskan mainland. The divide between the Nushagak and Kvichak 

watersheds is near the geologic boundary between the Peninsular Terrane to the southeast and the Kahiltna 

Terrane to the northwest (Decker and others, 1994; Nokleberg and others, 1994). The Peninsular Terrane consists 

of Permian limestone, Triassic limestone, chert, and volcanic rocks, Jurassic volcanic and plutonic rocks, and 

Jurassic to Cretaceous clastic sedimentary rocks. 

The Pebble porphyry copper deposit and the Humble and Big Chunk prospects are located within the southern 

Kahiltna Terrane (Fig. 1). The southern Kahiltna Terrane consists of a deformed sequence of Triassic to Jurassic 

basalt, andesite, tuff, chert, and minor limestone of the Chilikadrotna Greenstone, which is overlain by the Jurassic 

to Cretaceous Koksetna River sequence comprising turbiditic sandstones, siltstone, and shales (Wallace and 

others, 1989). The area was intruded by Cretaceous to Tertiary plutons, which include those associated with the 

Pebble deposit. The area also was partially covered by Tertiary to Quaternary volcanic rocks and varying 

thicknesses of glacial deposits (Detterman and Reed, 1980; Bouley and others, 1995).

The underlying geology can exert a significant influence on water chemistry, and therefore the possible toxicity 

of trace elements to aquatic organisms. The presence or absence of carbonate minerals and pyrite is the most 

significant influences on water chemistry in terms of pH, hardness, and alkalinity. Carbonate minerals such as 

calcite – the main constituent of limestone – can raise the pH and increase water hardness and alkalinity. 

Limestone, dolomite, and siltstone with abundant calcareous concretions are the most common hosts of carbonate 

minerals and are most abundant in Kvichak watershed in the vicinity of Lake Clark (Detterman and Reed, 1980; 

Bouley and others, 1995). Pyrite, a potential source of acid, can be a minor constituent of turbiditic sediments such 

those found in the Koksetna River sequence, northeast of Pebble. Hydrothermal activity associated with the 

formation of mineral deposits, discussed below, also can introduce significant amounts of both pyrite and carbonate 

minerals.

Mineral Resource Potential of the Nushagak and Kvichak Watersheds

The geologic setting of the Nushagak and Kvichak watersheds has characteristics that indicate that the region 

is favorable for several different mineral-deposit types (Schmidt and others, 2007). These deposit types include 

porphyry copper deposits, copper and iron skarn deposits, intrusion-related gold deposits, tin greisen deposits, 

epithermal gold-silver vein deposits, hot spring mercury deposits, placer gold deposits, and sand and gravel 

deposits (Table 1). Of these deposit types, porphyry copper deposits and intrusion-related gold deposits are 

represented by current prospects within the area that could prompt large-scale development. Copper skarn 

deposits hold less potential, in the absence of infrastructure from other mine development in the region, because of 

their typical smaller size (John and others, 2010). Significant exploration activity associated with porphyry copper 
Figure 1. Generalized geologic map of the central part of the Bristol Bay watershed showing the general locations of the Pebble, Humble, and Big 

Chunk prospects. Adapted from Wilson and others (2006). Map was made by Keith Labay (USGS).
Geologic and Environmental Characteristics of Porphyry Copper Deposits – April 2012

4

deposits is currently being done at the Pebble prospect, and to a lesser extent the Humble and Big Chunk 

prospects. Several other porphyry copper prospects are immediately adjacent to Pebble, including the H Block and 

D Block prospects. Although the Humble (also known as Kemuk Mountain) prospect is currently being promoted 

as a porphyry copper target (http://www.millrockresources.com/projects/humble/), the initial exploration (1957 – 

1959) identified significant iron and titanium resources in a mafic intrusive complex (ALS Chemex, 2008). Notable 

exploration also is being done in the watershed at several gold properties including Shotgun, Kisa, and Bonanza 

Hills.

The Pebble deposit is the most advanced among the mining prospects in the Bristol Bay watershed in terms of 

exploration and progress towards the submission of mine permit applications. Therefore, the potential for largescale mining development within the watershed in the near future is greatest for porphyry copper deposits. 

Accordingly, the remainder of the report will focus exclusively on this deposit type – porphyry copper deposits.

Table 1. Deposit types with significant resource potential for large-scale mining in the Nushagak and Kvichak 

watersheds.

Deposit type Commodities Examples References

Porphyry copper Cu, Mo, Au, 

Ag

Pebble, Big Chunk, 

Kijik River

Schmidt and others (2007); Bouley 

and others (1995)

Intrusion-related gold Au, Ag Shotgun/Winchester,

Kisa, Bonanza Hills

Schmidt and others (2007); 

Rombach and Newberry (2001)

Copper(-iron-gold) skarn Cu, Au, Fe Kasna Creek, Lake 

Clark Cu, Iliamna 

Fe, Lake Clark

Schmidt and others (2007), 

Newberry and others (1997)

General Characteristics of Porphyry Copper Deposits

Geologic Features: 

The geologic characteristics of porphyry copper deposits recently have been reviewed by John and others 

(2010), Sinclair (2007), and Seedorff and others (2005). Therefore, only salient features are summarized here. 

Porphyry copper deposits are found around the world, most commonly in areas with active or ancient volcanism 

(Fig. 2). The economic viability of porphyry copper deposits is dictated by the economy of scale – they typically are 

low grade (average 0.44 % copper in 2008), large tonnage (typically hundreds of millions to billions of metric tonnes 

of ore) deposits that are exploited by bulk mining techniques (John and others, 2010). Because of their large size, 

their mine lives typically span decades.

Primary (hypogene) ore minerals found in porphyry copper deposits are structurally controlled and genetically 

associated with felsic to intermediate composition, porphyritic intrusions that typically were emplaced at shallow 

levels in the crust. Mineralization commonly occurs both within the associated intrusions and in the surrounding 

wall rocks. The primary minerals fill veins, veinlets, stockworks and breccias. Pyrite (FeS2) is generally the most 

abundant sulfide mineral. The main copper-sulfide ore minerals are chalcopyrite (CuFeS2) and bornite (Cu5FeS4). 

A number of other minor copper sulfide minerals are commonly found; most notable from an environmental 

perspective is the arsenic-bearing mineral enargite (Cu3AsS4). Molybdenite (MoS2) is the main molybdenum 

mineral. Gold in porphyry copper deposits can be associated in appreciable amounts with bornite, chalcopyrite, 
Geologic and Environmental Characteristics of Porphyry Copper Deposits – April 2012

5

and pyrite; the gold may occur as a trace element within these sulfide minerals or as micrometer-scale grains of 

native gold (Kesler and others, 2002).

Hydrothermal mineralization produces hydrothermal alteration haloes that are much larger than the actual ore 

deposit. The classic alteration zonation includes a potassium feldspar-biotite rich core, surrounded by a 

muscovite/illite sericitic (phyllic) alteration zone, which is surrounded by a clay-rich argillic alteration zone and finally 

by a chlorite-epidote rich propylitic zone (Fig. 3; Lowell and Gilbert, 1970). The ore zones generally coincide with 

the potassic and sericitic alteration zones. From an environmental perspective, the importance of these alteration 

types is that the sericitic and argillic alteration tends to destroy the acid-neutralizing potential of the rock, while 

enhancing the acid-generating potential through the addition of pyrite. In contrast, the outer portion of the propylitic 

zone tends to have enhanced acid-neutralizing potential due to the introduction of trace amounts of carbonate 

minerals.

Figure 2. Map showing location of Phanerozoic porphyry deposits with representative deposits labeled. 

Modified from Seedorff and others (2005) and John and others (2010).

Supergene (weathering) processes, which occur long after the initial hydrothermal mineralizing events, can 

lead to zones of supergene enrichment near the tops of these deposits (John and others, 2010). The supergene 

enrichment zones can be either oxide- or sulfide-dominated depending on the prevailing oxidation state at the site 

of formation, the depth of the water table, and climate. Mined material from the oxide enrichment zone is amenable 

to a heap-leaching method of ore processing known as “solvent-extraction – electrowinning” (SX-EW; Jergensen, 

1999). However, supergene ores are likely to be minor in Alaska due to recent glaciation.

Porphyry copper deposits can be divided into three subtypes on the basis of Au (g/t)/Mo (%) ratios: porphyry 

Cu, porphyry Cu-Mo, and porphyry Cu-Au deposits, where Cu-Au deposits have Au/Mo ratios greater than or equal 

to 30, Cu-Mo deposits have Au/Mo ratios less than or equal to 3, and Cu deposits are all other deposits not within 

these bounds (Sinclair, 2007; Singer and others, 2008). On the basis of these criteria, the Pebble deposit would be 

classified as a porphyry Cu deposit.
Geologic and Environmental Characteristics of Porphyry Copper Deposits – April 2012

6

Economic Characteristics: 

Porphyry copper deposits are important sources of copper, molybdenum, gold, and silver; they also can supply 

significant amounts of byproduct rhenium, tellurium, and platinum-group metals. Porphyry copper deposits supply 

over 60 percent of the copper for global copper production and together with porphyry molybdenum deposits, 

account for over 95 percent of the molybdenum production (Sinclair, 2007; John and others, 2010). In 2010, the 

United States consumed 1,730,000 tonnes of copper, of which 30 percent was imported, chiefly from Chile, 

Canada, and Peru. In the same year, the United States consumed 48,000 tonnes of molybdenum, and was a net 

exporter. In 2010, the United States consumed 380 tonnes of gold of which 33 percent was imported, primarily 

from Canada, Mexico, Peru, and Chile. These commodities serve myriad uses (U.S. Geological Survey, 2011). 

Copper is used primarily in building construction (wiring and pipes; 49 %), electric and electronic products (20 %), 

vehicles (12 %), consumer products (10 %), and industrial machinery and equipment (9 %). Molybdenum is 

primarily used as a steel alloy (75 %). Gold is used mainly for jewelry (69 %), and electrical and electronic products 

(9 %). Silver is used for a variety of applications including industrial and medical uses, electronics, coins and 

silverware, and photography (albeit a declining application). Rhenium is principally used as an alloy in turbine 

engines (70 %) and for petroleum refining (20 %). Tellurium is primarily used as an alloy with steel, iron, and lead, 

but increasingly is being used in photovoltaic cells. Platinum-groups metals (platinum, palladium, rhodium, 

ruthenium, iridium, and osmium) principally are used in vehicle catalytic converters, as catalysts for chemical 

manufacturing, in electronics and in emerging applications to fuel cells.

Figure 3. Idealized cross section through a porphyry copper deposit showing the relationship of the ore zone to 

various alteration types. A. Distribution of alteration types; B. Distribution of ore mineral assemblages. The 

causative intrusion corresponds to the potassic alteration zone. From John and others (2010) and modified from 

Lowell and Guilbert (1970).

The grade and tonnage of porphyry copper deposits vary widely (Singer and others, 2008). Summary statistics 

compiled for 256 porphyry copper deposits are presented in Table 2 and Figure 4. For total tonnage of ore, Pebble 

is in the upper 5th percentile, lower 50th percentile for copper grade, upper 10th percentile for molybdenum grade, 

and upper 10th percentile for gold grade. The amount of metal contained in the Pebble deposit corresponds to a 

21-year supply of copper for the United States, a 53-year supply of molybdenum, and a 9-year supply of gold, 

based on 2010 consumption statistics (Table 3). From the perspective of future discoveries in the watershed, it is 
Geologic and Environmental Characteristics of Porphyry Copper Deposits – April 2012

7

therefore highly unlikely that new deposits will approach the size of Pebble, but instead will be considerably 

smaller.

Geology of Bristol Bay Porphyry Copper Deposits:

Several porphyry copper prospects within the Bristol Bay watershed are being explored, and include Pebble, 

Humble, and Big Chunk. The Pebble deposit is the only one with a significant published description of its geology 

(Bouley and others, 1995; Kelley and others, 2010). The deposit is controlled by the Pebble Limited Partnership – 

a joint venture between Northern Dynasty Minerals, Ltd., and Anglo American. The Pebble deposit may be viewed 

as consisting of two contiguous ore bodies: Pebble West and Pebble East, with the buried Pebble East having the 

higher ore grades. Pebble West was discovered in 1989 at the surface, and delineation drilling in 2005 resulted in 

discovery of Pebble East beneath a 300 to 600 m thick cover of Tertiary volcanic rocks. The deposit has been 

explored extensively with more than 1,150 drill holes that total greater than 949,000 feet (289,250 m) (Northern

Dynasty Minerals, 2011).

Table 2. Global grade and tonnage summary statistics for porphyry copper deposits (n = 256; Model 17, Singer 

and others, 2008) compared to the Pebble deposit.

Parameter 10th Percentile 50th Percentile 90th Percentile Pebble1

Tonnage (Mt) 1,400 250 30 10,777

Cu grade (%) 0.73 0.44 0.26 0.34

Mo grade (%) 0.023 0.004 0.0 0.023

Ag grade (g/t) 3.0 0.0 0.0 unknown

Au grade (g/t) 0.20 0.0 0.0 0.31

Sources: 1PLP (0.3 % Cu cut-off grade), includes measured, indicated, and inferred resources (http://www.pebblepartnership.com/) 

Table 3. Annual consumption of copper, molybdenum and gold compared to the Pebble deposit.

Commodity US Annual Consumption (2010)1 Pebble Resource2 Years of 2010 

Consumption

Copper (tonnes) 1,730,000 36,636,364 21

Molybdenum (tonnes) 48,000 2,531,818 53

Gold (tonnes) 380 3,337 9

Sources: 1U.S. Geological Survey (2011); 2PLP (0.3 % Cu cut-off grade), includes measured, indicated, and inferred resources 

(http://www.pebblepartnership.com/) 

The oldest rocks in the vicinity of the deposit are Jurassic to Cretaceous (ca. 150 Ma) clastic sedimentary rocks 

(i.e., mudstone, siltstone, and sandstone), which were intruded by dominantly granitic plutons from 100 to 90 Ma; 

granodiorite stocks and sills, spatially and genetically related to the Cu-Au-Mo mineralization, were intruded about 

90 Ma (Kelley and others, 2010). Intrusion of these granodiorite bodies resulted in hydrothermal activity that 

produced the mineralization and associated alteration of the intrusions and surrounding rocks. The Pebble West 

deposit extends from the surface to a depth of about 500 m and encompasses roughly 6 square kilometers on the 

surface. Pebble East is covered by a wedge of post-mineralization Tertiary volcanic rocks that exceeds 600 m in 

thickness towards the east. The eastern end of the deposit is truncated by a high-angle fault that offsets the 

deposit 600 to 900 m down to the east (Kelley and others, 2010). Early copper mineralization was dominated by 
Geologic and Environmental Characteristics of Porphyry Copper Deposits – April 2012

8

pyrite, chalcopyrite, and gold, which was overprinted by pyrite, bornite, digenite, covellite, and minor enargite, 

followed by quartz-molybdenite veinlets (Bouley and others, 1995; Kelley and others, 2010).

Figure 4. Grade-tonnage characteristics of the Pebble deposit compared to other porphyry-type deposits. A. 

Copper; B. Molybdenum; C. Gold. The Pebble deposit is shown as the yellow star. Selected, noteworthy 

deposits are labeled. Pebble is classified as a porphyry Cu deposit (red squares). The dashed diagonal lines 

represent the total contained metal. Modified from Sinclair (2007).
Geologic and Environmental Characteristics of Porphyry Copper Deposits – April 2012

9

Geologic information on the Humble prospect (also known as Kemuk) is limited to the details found on the 

Millrock Resources, Inc. website (http://www.millrockresources.com/projects/humble/). The prospect is covered by 

glacio-fluvial gravels and sands 30 to greater than 140 m thick. The site was identified on the basis of the presence 

of an airborne geophysical (magnetic) anomaly and the presence of igneous rocks similar to those found at Pebble. 

The Humble Oil Company drilled the property in 1958 and 1959 as an iron prospect. No mention is made of CuAu-Mo mineralization from the 1950s drilling, and there are no recent data available. Information on the Big Chunk 

Super project is limited to details on the Liberty Star Uranium and Metals Corporation website 

(http://www.libertystaruranium.com/www/projects/big-chunk-super-project). Current exploration efforts are focused 

on six to seven airborne electromagnetic geophysical anomalies from data collected in 2009 that are consistent 

with porphyry-style mineralization. Although exploratory drilling is mentioned on the web site, no results are 

discussed. 

Mining and Beneficiation Considerations: 

Mining and ore-processing methods can vary based on whether or not parts of the ore are weathered, and on 

the commodities being extracted. Due to their large size and low grades, porphyry copper deposits are mined by 

bulk mining methods such as open-pit mining for deposits near the surface, and block caving for deposits at depth. 

Because the copper ore grades are generally less than 2 percent, greater than 98 percent of the material mined 

ends up as waste. The beneficiation of the ore is distinctly different between hypogene (primary) sulfide ores and 

supergene (secondary) oxide ores. Mining begins with the removal of waste rock, which may or may not be acidgenerating. Country rocks that host the mineralization are commonly acid-generating due to the presence of 

hydrothermal pyrite formed during the mineralizing event. These rocks may be classified as subeconomic ore and 

may be stockpiled separately from barren waste rock. The processing of subeconomic ore commonly is prompted 

by either an increase in metal prices making the material economically viable, or if a high-grade zone is 

encountered during mining, the subeconomic ore may be mixed with high-grade ore to ensure that an optimal 

grade of material is being fed to the mill. In either case, subeconomic ore generally is handled in a similar fashion 

to that of waste rock during mine operations because of its acid-generating potential.

The primary (hypogene) sulfide ore is crushed to sand or silt size prior to ore-concentrate separation using the 

froth flotation method (Fuerstenau and others, 2007). For porphyry copper deposits, such as Pebble, separate 

concentrates for copper and molybdenum generally are produced. The gold in porphyry copper deposits can be 

partitioned variably among the copper-sulfide minerals (chalcopyrite, bornite, chalcocite, digenite, and covellite), 

pyrite, and free gold (Kesler and others, 2002). Gold associated with the copper minerals remains with the copper 

concentrate and is recovered at an off-site smelter. Gold associated with pyrite will end up in the tailings, unless a 

separate pyrite concentrate is produced. Pyrite concentrates can be produced during froth flotation for the recovery 

of gold or to more effectively manage the high acid-generating potential of this material. Gold commonly is 

recovered by cyanidation, but gold recovery from sulfide-rich material is poor (Marsden and House, 2006). To 

improve gold recovery, pyritic material typically is oxidized by various means including high-temperature 

(pyrometallurgical) roasting; low-temperature, pressurized autoclaving; or bio-oxidation using bacteria. Following 

oxidation, the material then is leached with cyanide, usually in a vat to recover gold (Marsden and House, 2006). 

The resulting spent iron oxides generally are disposed with the tailings. Autoclaving is probably the most likely 

option in southwest Alaska because cyanide can be managed effectively in a vat-leaching operation. Hightemperature roasting is energy intensive and presents additional challenges with respect to stack emissions. 

Bioleaching may be more difficult because of the cold climate and slow biotic oxidation rates at lower temperatures.

Tellurium generally is recovered from the copper anode slimes at the refinery (John and others, 2010). 

Rhenium is recovered as a byproduct of the roasting of the molybdenum concentrate at the refinery (U.S. 

Geological Survey, 2011). The platinum-group metals generally are associated with copper concentrates (Tarkian 
Geologic and Environmental Characteristics of Porphyry Copper Deposits – April 2012

10

and Stribrny, 1999) and thus, would not be recovered on site at Pebble. Therefore, the recovery of tellurium and 

platinum-group metals from Pebble or other porphyry copper deposits in the watershed would likely be an activity 

conducted off-site when ore concentrates are further processed.

Supergene (secondary) oxide ores commonly are beneficiated using a heap-leach method known as solvent 

extraction-electrowinning (SX-EW). This process involves placing coarsely crushed ore on a lined pad and 

applying sulfuric acid to leach copper from the ore. The pregnant leach solution is collected and the copper is 

removed from the leachate electrolytically (Jergensen, 1999). The supergene enrichment zone at Pebble is poorly 

developed and dominated by the secondary copper sulfide minerals covellite (CuS), digenite (Cu1-xS), and 

chalcocite (Cu2S), in part due to recent glaciation (Bouley and others, 1995). Therefore, processing of oxide ore is 

unlikely at Pebble or geologically similar deposits within the watershed.

Environmental Characteristics of Porphyry Copper Deposits

Overview

Porphyry copper deposits can pose geochemical risks to aquatic and terrestrial ecosystems, and to human 

health. The risks can range from nil to significant and depend upon a variety of factors. Factors that influence the 

environmental characteristics of mineral deposits range from geologic setting (both local and regional), hydrologic 

setting, climatic settings, and mining methods, to ore beneficiation methods. The sources of the risk can be 

considered in the broad categories of acid-generating potential, trace element associations, mining and ore 

beneficiation methods, and waste disposal practices. The significance of these sources of risk will vary from 

deposit to deposit, but some generalizations can be made for porphyry copper deposits as a whole.

Acid-Generating Potential

Acid generation can be considered a “master variable” for aqueous risks. Metals and other cations are more 

soluble at low pH than at neutral or high pH. Therefore, the acid-generating or acid-neutralizing potentials of the 

waste rock, tailings, and mine walls are of prime importance in identifying the potential environmental risks 

associated with mining and ore beneficiation.

The acid-generating or acid-neutralizing character of a rock or mine waste material is evaluated in terms of an 

“acid-base account”. Acid-base accounting uses static tests to assess maximum acid-generating potential. Static 

tests are based on a single analysis of waste material and therefore are independent of rates of reactions. In 

contrast to static tests, kinetic tests expose mine waste samples for weeks, months, or years. Most proposed 

mining projects take a staged approach to evaluating acid-generating potential starting with acid-base accounting 

data to screen numerous samples, which are followed by the more laborious kinetic testing process on fewer, 

carefully selected samples.

The acid-generating potential of rocks and mine waste samples can be evaluated using a variety of techniques 

(Price, 2009; INAP, 2011). In North America, one of the most common techniques investigates the difference or 

ratio of the acid-generating and acid-neutralizing potential of the sample. Theoretically, a sample with an acidneutralizing potential (NP) equal to its acid-generating potential (AP) is “net neutral”, meaning that its acidneutralizing potential (NP) should theoretically cancel (or neutralize) its acid-generating potential (AP). 

Numerically, this is expressed as a “net neutralizing potential” (NNP) of zero, where

NNP = NP – AP
Geologic and Environmental Characteristics of Porphyry Copper Deposits – April 2012

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Values for AP, NP, and NNP are typically expressed in the units of kilograms of calcium carbonate per tonne of 

waste material (kg CaCO3/t), such that the amount of calcium carbonate amendment that would be needed to 

achieve “net neutrality” is readily apparent. The AP values are generally based on an analysis of the sulfide-sulfur 

content of the sample, and the NP values are based on either an analysis of the carbonate content of the sample or 

by leaching of the sample followed by a wet chemical titration of the resulting leachate. NNP values that are 

greater than zero have theoretical acid-neutralizing potential present in excess of acid-generating potential and 

those below zero have theoretical acid-generating potential present in excess of acid-neutralizing potential. 

Alternatively, the acid-base account of a sample also can be expressed in terms of its neutralizing potential ratio 

(NPR), which is simply the ratio of its NP to its AP:

NPR= NP/AP

Thus, a sample with a NPR equal to one is net neutral, greater than one has theoretical acid-neutralizing potential 

exceeding acid-generating potential, and less than one has theoretical acid-generating potential exceeding acidneutralizing potential. Current industry standards generally divide rocks and mine waste samples into three distinct 

categories based on the NPR values: potentially acidic drainage generating (PAG) for NPR less than 1; uncertain 

(possibly) acidic drainage generating for NPR between 1 and 2; and non-potentially acidic drainage generating 

(non-PAG) greater than 2 (INAP, 2011). Note that the requirement that non-PAG material have a NPR value 

greater than 2 represents twice the amount of alkalinity needed for net neutrality under equilibrium conditions. In 

practice, kinetic considerations are important, which is why a NPR greater than 2 is desirable. However, no 

universal consensus exists on the NPR value required to ensure no acid generation; recommended values range 

from 1 to 4 (White and others, 1999). The NPR is typically used as a screening tool and mine-waste management 

decisions will be based on more extensive characterization using additional techniques (Price, 2009).

The rocks associated with porphyry copper deposits, in general, tend to straddle the boundary between having 

net acid-generating potential and not having net acid-generating potential. This aspect is illustrated well by the 

study of Borden (2003) on the Bingham Canyon porphyry copper deposit in Utah (Figures 5 and 6), which shares 

many similar geologic features with the Pebble deposit. The AP values for porphyry copper deposits approximately 

reflect the distribution of pyrite. The distribution of acid-generating and non-acid-generating material in plan view at 

the Bingham mine matches well with the idealized cross section of porphyry copper deposits shown in Figure 3B. 

The pyrite-poor, low-grade core corresponds to the central part of the Bingham Canyon deposit where NNP values 

are greater than 0. The progression out to the ore shell and pyrite shell with their increasing abundance of pyrite in 

these areas is reflected in the progressively more negative NNP values.

During mining of porphyry copper deposits, a variety of materials with differing NNP values may be 

encountered. The low NNP, largely barren pyrite shell likely represents waste rock that may need to be removed to 

access the ore (Fig. 3B). The boundary between the ore shell and the pyrite shell is cryptic and typically is defined 

operationally on the basis of a cut-off copper grade. Therefore, some of the “waste” material with significant, 

subeconomic copper grades could be stockpiled for potential future beneficiation. The intrusions that produce 

porphyry copper deposits can intrude any rock type. Therefore, the NNP values of the country rock of 

undiscovered deposits cannot be predicted reliably. Likewise, geologic events following ore formation could 

juxtapose a variety of rock types against an ore deposit, which can have a range of NNP values. In the case of 

Pebble, subsequent volcanic activity after mineralization covered the eastern part of the deposit with material that 

has limited acid-generating potential (Kelley and others, 2010; Pebble Partnership, 2011).

The mining method will influence the amount of waste rock removed. Open pit mining can require the removal 

of large volumes of potentially acid-generating material. A waste-to-ore ratio of 2:1, meaning that two tonnes of 

waste are removed for each tonne of ore mined, is not uncommon for porphyry copper deposits (Porter and 

Bleiwas, 2003). Underground block caving of ore requires that a shaft or decline be sunk to facilitate mining. The 
Geologic and Environmental Characteristics of Porphyry Copper Deposits – April 2012

12

amount of waste rock removed for block caving is much less than that removed in a typical open pit operation. In 

the specific case of Pebble, the volcanic rocks overlaying Pebble East have limited amounts of pyrite and are 

generally classified as non-PAG material, which would not require special handling to mitigate acidic drainage 

(Pebble Partnership, 2011). In fact, this material could be used for a variety of construction projects on site (e.g., 

road fill, tailings dam construction). In contrast, the Pre-Tertiary rocks at Pebble are generally classified as PAG, 

with some samples having uncertain potential for generating acid and fewer with no potential for generating acid 

(non-PAG). During mining, some of this rock will be waste rock removed to access the ore, and some of it will be 

ore that will be processed to extract mineral concentrates.

Figure 5. Plot of neutralizing potential (NP) and acid-generating potential (AP) for mineralized rock types at the 

Bingham Canyon porphyry copper deposit, Utah. Modified from Borden (2003).

The most profound influence that beneficiation of ore can have on mine tailings derived from froth flotation 

centers on the fate of pyrite (Fuerstenau and others, 2007). At many porphyry copper mines, the pyrite is 

discharged with the waste tailings, thereby contributing to the acid-generating potential of the tailings. However, 

the option exists to produce a pyrite concentrate to manage more effectively the acid-generation risks associated 

with tailings, to extract gold associated with the pyrite, or both. The production of a pyrite concentrate will decrease 

the acid-generating potential of the tailings.

Waste Rock

Waste rock associated with porphyry copper deposits reflects the geologic history of the deposit. Because 

porphyry copper deposits are associated with igneous rocks intruded into shallow levels of the Earth’s crust, the 

geochemical properties of the country rocks can vary widely, particularly in terms of their acid-base accounting 

properties and their trace element compositions. The hydrothermal activity that forms the ore deposits introduces 
Geologic and Environmental Characteristics of Porphyry Copper Deposits – April 2012

13

sulfur, which commonly forms sulfide minerals such as pyrite, and a variety of trace elements. Introduced sulfur 

may also occur as the sulfate minerals anhydrite (CaSO4), or barite (BaSO4), which are environmentally benign 

with respect to acid-generating potential. In fact, for acid-base accounting, the portion of sulfur that occurs as 

sulfate should be subtracted from the total amount of sulfur present to accurately estimate acid-generating potential 

(Price, 2009). The hydrothermal alteration haloes around these deposits are significantly more extensive than the 

ores themselves (Fig. 3) and commonly represent waste rock with significant associated environmental risks. 

Rocks that form after the mineralization event, and not affected by supergene processes, are devoid of these 

hydrothermal overprints of sulfur and trace elements.

Figure 6. Plan view of the distribution of net neutralizinig potential (NNP) values at the Bingham Canyon 

porphyry copper deposit, Utah. NNP values above zero are “net alkaline”; those below zero are “net acid”. 

Modified from Borden (2003).

An early step in mining is to remove the waste rock to access the ore. For open pit mines, waste to ore 

(stripping) ratios commonly can exceed 2:1 (Porter and Bleiwas, 2003). As discussed in the previous section, the 

acid-generating potential of the waste rock can span the range from potentially acid-drainage generating (PAG) to 

non-PAG. The ability of leachate generated from waste rock to mobilize metals and oxyanions will vary, depending 

in part, on the pH of the resulting solution, which largely is a function of the pyrite content of the waste rock.

The primary environmental concerns associated with waste rock are due to the oxidation of waste-rock

material, which may result in contamination of either groundwater or surface water. The oxidation of sulfide 

minerals such as pyrite produces sulfuric acid, which then can dissolve metals and related elements from 

associated sulfide, silicate, and carbonate minerals. The magnitude of this risk will depend upon waste 

management practices and whether or not drainage is treated.
Geologic and Environmental Characteristics of Porphyry Copper Deposits – April 2012

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The geochemical characteristics of waste-rock dump drainage have been investigated by several studies. Day 

and Rees (2006) conducted a study of dump seepage associated with several operating or recently closed 

porphyry copper and porphyry molybdenum mines in British Columbia, many of which are located in the Fraser 

River watershed. Porphyry copper mines included in their study were Gibraltar, Huckleberry, Island Copper, and 

Mount Polley; the data from Huckleberry were from laboratory column tests only. These deposits fell into two 

groups: those that produced low pH drainage and those that did not. The pH of waste-dump drainage from 

Gibraltar and Huckleberry ranged from neutral down to approximately 2, whereas drainage from Island Copper only 

reached a low of approximately 4.5. In contrast, the pH of waste-rock drainage at Mount Polley ranged between 7 

and 8.5. The concentrations of sulfate and metals were negatively correlated with pH. The maximum 

concentrations of sulfate (<30,000 mg/L), Al (< 1,000 mg/L), Mn (< 100 mg/L), and Cu (< 1,000 mg/L) were all 

highest from Gibraltar; the highest concentrations of Zn (< 100 mg/L) were found in the Huckleberry column tests 

(Day and Rees, 2006). For comparison, Lister and others (1993) found that 41 percent of the NPR values for 

waste rock at Island Copper were below 1, 23 percent were between 1 and 3, and 36 percent were above 3, which 

is consistent with the range of pH values, from 4.5 to 8, observed by Day and Rees (2003). Khorasanipour and 

others (2011) found similar geochemical trends, but in a more arid environment, for drainage associated with 

waste-rock dumps at the Sarcheshmeh mine in southeastern Iran. The pH ranged between 3.1 and 6.3, specific 

conductance between 0.72 and 2.25 mS/cm, sulfate between 365 and 1,590 mg/L, Al between < 0.05 and 60 mg/L, 

Mn between 14.6 and 95.8 mg/L, Cu between 2.15 and 70 mg/L, and Zn between 2.4 and 27.4 mg/L.

In the vicinity of the proposed Pebble mine, the best insights into the potential behavior of waste rock come 

from the humidity-cell tests being conducted by the Pebble Limited Partnership and its contractors (Pebble 

Partnership, 2011). Management of waste rock during mine operation typically involves placing waste rock in

subaerial piles on site. This configuration is similar to the conditions of humidity-cell tests where samples are 

exposed to a weathering protocol under unsaturated conditions (Price, 2009). Standard procedures for humiditycell tests require that rock be crushed to less than 6 mm, placed in cylinders, cycled through moist and dry air for 

six days, and leached on the seventh day, all at room temperature. This requirement produces a material that has 

significantly more surface area than waste rock produced during mining, which makes the test material more 

reactive than the actual material. As such, this approach does not incorporate the temperature and precipitation 

variations encountered on site, or the heterogeneous grain size of typical waste rock. “Barrel” kinetic tests were 

conducted also, where rather than weathering samples in the laboratory, larger volumes of material were placed in 

barrels in the field and the samples were exposed to site conditions. The goal of barrel testing is to scale-up 

laboratory results to conditions that are more representative of the site in terms of amount and seasonality of 

precipitation and temperature variations. The barrel test results are only discussed on a limited basis in this report. 

However, despite these caveats, the humidity-cell results presented by the Pebble Partnership (2011) provide 

relevant information.

Pebble Partnership (2011) has divided material at the site into several different groups, for both Pebble West 

and Pebble East: Pre-Tertiary sedimentary and volcano-sedimentary units, Pre-Tertiary plutonic units, and Tertiary 

volcanic units. In general, results from the Pre-Tertiary rocks from Pebble West and Pebble East were not 

significantly different. The Pre-Tertiary rocks were present at the time of mineralization and therefore have the 

potential to be significantly mineralized. The Tertiary volcanic rocks were deposited after mineralization, and 

therefore should have limited concentrations of sulfide minerals to serve as a sources of acidity and dissolved 

metals.

The results of the Pebble Partnership (2011) humidity-cell tests are summarized in Table 4. Table 4 presents 

the mean composition of leachate from these a number of individual tests divided into three groups: Tertiary rocks, 

hydrothermally altered Pre-Tertiary rocks (undifferentiated) from Pebble West, and hydrothermally altered PreTertiary rocks (undifferentiated) from Pebble East. The results from the variety of Pre-Tertiary rock types were 
Geologic and Environmental Characteristics of Porphyry Copper Deposits – April 2012

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grouped together here with the assumption that individual waste-rock types would not be selectively removed 

during mining. Individual humidity-cell tests can show a range of leachate concentrations that vary over the course 

of the experiment. In general, the concentrations of dissolved constituents are most erratic and highest during the 

initial flush covering the first few one-week cycles in humidity-cell tests; several weeks after the start of the 

experiments, the concentrations of dissolved constituents tend to stabilize. The average release rates used in 

Table 4 obscure this variability, although its magnitude can be assessed by the standard deviations presented with 

means in Table 4. The concentration of constituents in the leachate was calculated from the average release rate 

data presented by the Pebble Partnership using the formula:

Concentration (mg/L) = [Release (mg/kg/week) x Mass of Sample (kg)]/Leachate Recovered (L),

where the average release rate, the mass of the solid sample, and amount of leachate recovered are provided in 

the Pebble Partnership (2011) report. The results from Pebble include a number of parameters (Pebble 

Partnership, 2011): pH, conductivity, acidity, alkalinity, total dissolved solids, hardness, F, Cl, SO4, Al, Sb, As, Ba, 

Be, Bi, B, Cd, Ca, Cr, Co, Cu, Fe, Pb, Mg, Mn, Hg, Mo, Ni, K, Se, SiO2, Ag, Na, Tl, Sn, V, and Zn. The present 

discussion focuses on pH, sulfate, Cu, Mo, As, and Zn. The pH of a solution is a master variable that controls the 

solubility of most elements. Sulfate is a proxy for pyrite oxidation, which produces the acid in acid-mine drainage. 

Copper is a cationic species, and the most likely inorganic ecologic stressor expected at the site, especially for 

aquatic organisms. Zinc commonly occurs in base-metal hydrothermal systems, but typically not in economic 

concentrations in porphyry copper deposits. Arsenic and molybdenum are oxyanion species, which behave 

differently from cations; arsenic is a potentially significant stressor, especially with respect to drinking water 

contamination, whereas molybdenum is an important ore constituent with less potential to be an environmental 

stressor. 

The Pre-Tertiary rocks show a range of responses in the humidity-cell tests as reflected by the significant 

standard deviations associated with their mean leachate concentrations (Table 4). The leachates from the PreTertiary rocks are characterized by neutral to acidic pH values. As expected from the role of pyrite oxidation in acid 

generation, the samples that generated the lowest pH values had the higher sulfate concentrations and lower 

alkalinity values. For example, the mean pH for humidity-cell leachates for Pebble East was 4.8 ± 1.9 compared to 

6.6 ± 1.7 for Pebble West, presumably reflecting the higher grade and pyrite content of Pebble East. The pH of the 

samples correlated negatively with the alkalinity of the leachates. Copper concentrations generally correlate with 

sulfate concentrations and low pH, as would be expected from the higher solubility of metals with acidic pH 

conditions. The mean concentrations of copper in humidity-cell leachates from both Pebble West and Pebble East 

were high compared to other metals and exceeded 1 mg/L. The mean zinc concentration reached 0.5 mg/L. In 

contrast, the highest mean molybdenum concentration was less than 0.005 mg/L and the highest mean arsenic 

concentration was 0.008 mg/L. The high standard deviations associated with all parameters in the leachate 

chemistry from Pre-Tertiary waste-rock types underscore the challenges associated with predicting waste-rock 

seepage chemistry with a high level of confidence. At an operating mine, the drainage from waste-rock piles will be 

a mixture of direct leachates from the waste rock and local ambient surface water and precipitation. The relative 

proportion of these sources will depend upon local climatic conditions, the natural topography, alterations to the 

natural topography made during mine construction, and engineering controls put in place during mine construction

to manage surface water. The range of potential compositions of seepage is shown in Figure 7, which shows 

average dissolved copper and hardness values for various waters. The leachate values associated with the Pebble 

East Zone humidity-cell tests (PEZ HCT), the Pebble West Zone humidity-cell tests (PWZ HCT), the Pebble West 

Zone Barrel test (PWZ Barrel), and the Tertiary Waster Rock humidity-cell tests are all averages of mean release 

rates from individual experiments. The mean values for the North Fork of the Koktuli River are merely meant to 
Geologic and Environmental Characteristics of Porphyry Copper Deposits – April 2012

16

Table 4. Summary of geochemical results from mean humidity-cell tests on waste-rock samples conducted by the 

Pebble Partnership (2011). 

Parameter Units Tertiary Waste Rock Pebble West Pre-Tertiary 

Waste Rock

Pebble East Pre-Tertiary Waste 

Rock

Mean Standard 

Deviation

Mean Standard 

Deviation

Mean Standard 

Deviation

Pebble 

Partnership 

(2011) Source

Table 11-31 

(calc); 

Appendix 

11C (pH)

Table 11-31 

(calc); 

Appendix 11C 

(pH)

Table 11-21 

(calc); 

Appendix 11C 

(pH)

Table 11-21 

(calc); 

Appendix 11C 

(pH)

Table 11-21 

(calc); 

Appendix 11C 

(pH)

Table 11-21 

(calc); 

Appendix 11C 

(pH)

pH S.U. 7.2 1.3 6.6 1.7 4.8 1.9

Alkalinity mg/L CaCO3 65.9 51.0 18.5 16.4 9.9 14.1

Hardness mg/L CaCO3 74.0 88.1 59.2 51.9 21.9 23.1

Cl mg/L 0.53 0.11 0.52 0.01 0.91 0.91

F mg/L 0.06 0.09 0.12 0.12 0.11 0.16

SO4 mg/L 28.0 83.8 60.8 68.4 51.9 52.0

Ag mg/L 0.000011 0.000003 0.000027 0.000044 0.000019 0.000013

Al mg/L 0.08 0.21 0.32 0.85 0.38 0.58

As mg/L 0.0027 0.0042 0.0015 0.0018 0.0080 0.0189

B mg/L 0.0177 0.0122 0.0159 0.0085 0.0125 0.0052

Ba mg/L 0.0572 0.0824 0.0136 0.0087 0.0045 0.0056

Be mg/L 0.0003 0.0005 0.0003 0.0003 0.0006 0.0006

Bi mg/L 0.0005 0.0002 0.0007 0.0004 0.0006 0.0003

Ca mg/L 21.3 31.6 12.7 8.9 6.3 5.3

Cd mg/L 0.0002 0.0006 0.0004 0.0007 0.0032 0.0083

Co mg/L 0.0039 0.0157 0.0070 0.0146 0.0097 0.0120

Cr mg/L 0.0006 0.0002 0.0007 0.0004 0.0016 0.0023

Cu mg/L 0.0032 0.0061 1.5989 3.2469 1.4162 2.1609

Fe mg/L 0.140 0.484 1.671 6.042 10.195 16.051

Hg mg/L 0.000010 0.000001 0.000011 0.000002 0.000010 0.000001

K mg/L 1.85 2.24 1.41 0.72 0.96 0.69

Mg mg/L 5.06 7.49 6.69 8.68 1.50 3.40

Mn mg/L 0.1015 0.3990 0.7289 1.5653 0.3386 1.0745

Mo mg/L 0.0063 0.0138 0.0018 0.0018 0.0043 0.0070

Na mg/L 7.21 12.46 2.05 0.03 2.07 0.06

Ni mg/L 0.0044 0.0165 0.0068 0.0143 0.0105 0.0168

Pb mg/L 0.0001 0.0002 0.0002 0.0003 0.0004 0.0004

Sb mg/L 0.0021 0.0019 0.0031 0.0018 0.0008 0.0018

Se mg/L 0.0019 0.0020 0.0038 0.0057 0.0032 0.0024

Sn mg/L 0.0013 0.0015 0.0001 0.0001 0.0019 0.0022

Tl mg/L 0.00007 0.00003 0.00041 0.00098 0.00009 0.00010

V mg/L 0.0018 0.0022 0.0007 0.0004 0.0024 0.0056

Zn mg/L 0.0159 0.0500 0.0556 0.1080 0.4786 1.3618
Geologic and Environmental Characteristics of Porphyry Copper Deposits – April 2012

17

represent generic, uncontaminated surface water in the vicinity of the Pebble deposit. The triangular field shown in 

Figure 7 defined by the composition of the North Fork of the Koktuli River, the average humidity-cell results from

samples of the Pebble East Zone, and the barrel test results from the Pebble West Zone represent the likely range 

of potential surface-water compositions downstream of Pre-Tertiary (i.e., mineralized) waste-rock piles in the 

vicinity of the Pebble deposit (mine). Likewise, the dashed line connecting the average composition of the North 

Fork of the Koktuli River and the average humidity-cell results for Tertiary waste rock represents the likely range of 

potential surface-water compositions downstream of Tertiary (i.e., unmineralized) waste-rock piles in the vicinity of 

the Pebble deposit (mine). The location of the hypothetical compositions either within the triangular field for those 

waters associated with the Pre-Tertiary waste-rock piles or along the join associated with Tertiary waste-rock piles 

will depend on the water balance of the contributing drainages and will be influenced by the mine plan.

0.1

1 

10

100

1000

10000

100000

1 10 100 1000 10000

Dissolved Copper μg/L

Hardness mg/L CaCO3 

pre-Tertiary Waste 

Rock

North Fork Koktuli 

River

Tertiary Waste Rock

PWZ HCT

PEZ 

HCT

PWZ

Barrel

Figure 7. Dissolved copper concentrations and water hardness values for various potential end-member waters 

around the Pebble site in the Bristol Bay watershed associated with waste-rock piles. The humidity-cell test 

concentrations are from Table 4. The barrel-test results and the mean concentration for the North Fork of the 

Koktuli River are from Pebble Partnership (2011). The triangle represents the range of potential compositions 

that could be expected for seepage from Pebble West and Pebble East waste rock piles and the dashed line 

represents the range of potential compositions that could be expected from piles of Tertiary waste rock (see text). 

Abbreviations: PWZ, Pebble West Zone; PEZ, Pebble East Zone; HCT, Humidity-Cell Test.

The average humidity-cell test results for the Tertiary volcanic rocks yielded more coherent results than did the 

Pre-Tertiary rocks discussed above. Invariably, the humidity-cell test results show no ability to generate acid with 

all pH values ranging between 7 and 9 with a mean pH 7.2 ± 1.3. Sulfate concentrations generally range between 1 

and 100 mg/L with a mean concentration of 28.0 mg/L, but the lack of correlation with pH suggests that the 

resulting sulfate may be derived from benign sulfate minerals rather than acid-generating iron sulfide minerals. 

Copper concentrations were low and generally correlated with sulfate concentrations.
Geologic and Environmental Characteristics of Porphyry Copper Deposits – April 2012

18

Tailings

Mill tailings are the waste products from froth flotation, a process used to produce concentrates of economic 

minerals. The specific minerals separated greatly influence the character of the waste material. For porphyry 

copper deposits, it is typical to separate the copper-sulfide minerals [chalcopyrite (CuFeS2) and bornite (Cu5FeS4)] 

as a copper concentrate, and the molybdenum-sulfide mineral, molybdenite (MoS2) as a molybdenum concentrate 

(Fuerstenau and others, 2007). Gold commonly is associated with the copper sulfide minerals or pyrite. The gold 

associated with the copper concentrate will be recovered during smelting, typically conducted off-site. Gold 

associated with pyrite will require additional processing commonly on-site, as described above, to recover the gold. 

Thus, pyrite, the main source of acid-mine drainage, can be disposed with the tailings or it can be separated as a 

concentrate to either recover gold or to more effectively manage acid-generation risks. Therefore, the acidgenerating potential and mobility of trace metals will be affected by whether or not pyrite is separated from tailings 

prior to disposal.

A greater number of environmental concerns are associated with tailings due to their finer grain size compared 

to waste rock. Like waste rock, tailings can weather and the associated leachate can contaminate surface water 

and groundwater (Stollenwerk, 1994; Brown and others, 1998; Khorasanipour and others, 2011). Furthermore, 

because of the sand to silt size grains, tailings are prone to be transported by waters, especially in the case of 

tailings dam failure, and wind. Thus, they present additional potential risks to aquatic organisms through sediment 

contamination.

A compilation of geochemical analyses of “pristine”, unoxidized tailings from porphyry copper deposits is 

presented in Table 5. These data include analyses of tailings from the Aitik mine, Sweden (R. Seal, unpublished 

data), the El Teniente mine, Chile (Smuda and others, 2008; Dold and Fontboté, 2001), the Andina mine, Chile 

(Dold and Fontboté, 2001), the El Salvador mine, Chile (Dold and Fontboté, 2001), and the Sarcheshmeh mine, 

Iran (Khorasanipour and others, 2011). It is important to note that none of these tailings had a pyrite concentrate 

removed.

A summary of the geochemistry of tailings derived from metallurgical testing of drill core from the Pebble 

deposit is summarized in Table 6 from the PLP Environmental Baseline Document (Pebble Partnership, 2011). 

That report presents data from three sample sets, 2004, 2005, and 2008, which were used in the humidity-cell tests 

described below. The 2004 and 2005 samples were from Pebble West. The 2008 samples were from Pebble West

and Pebble East. The analyses for all sets included acid-base accounting analyses. The analyses for the 2004 

and 2005 samples focused on a more restricted group of analytes, limited mostly to elements for which regulatory 

guidance exists (Ag, As, Cd, Co, Cr, Cu, Hg, Mn, Mo, Ni, Pb, Sb, Se, Tl, and Zn). The analyses for the 2008 

samples included a larger group of analytes (Ag, Al, As, Au, B, Ba, Be, Bi, Ca, Cd, Ce, Co, Cr, Cs, Cu, Fe, Ga, Ge, 

Hf, Hg, In, K, La, Li, Mg, Mn, Mo, Na, Nb, Ni, P, Pb, Rb, Re, S, Sb, Sc, Se, Sn, Sr, Ta, Te, Th, Ti, Tl, U, V, W, Y,

Zn, and Zr. The table includes average values, the standard deviation for the average, and the low and high

values. For the entire dataset, paste pH values are near neutral, ranging from 6.6 to 8.9. The NP/AP ratio ranges

from 0.1 to 9.0, corresponding to probably acidic drainage generating values (PAG) to not probably acidic drainage 

generating (non-PAG), with the average being 2.7 (non-PAG). None of the tailing samples presented in Table 5 

had pyrite separated; all of their NNP values are negative, indicating a net acidic character, unlike the Pebble 

tailings, which had pyrite removed. Otherwise, the overall chemistry of the tailing samples in Tables 5 and 6 

compares favorably in terms of the range of values. It is worth noting that the 2005 LT C2 Combined Pre-Cleaner 

Tailings sample (Table 11-46 of the Pebble Project Environmental Baseline Document) has a copper concentration 

(2,050 mg/kg) that is 68 percent of the 0.3 percent cut-off grade, a molybdenum concentration (188 mg/kg) that 80 

percent of the published resource molybdenum grade, and one of the lowest NNP values (-30 kgCaCO3/t). Further 

metallurgical testing presumably will seek to improve copper and molybdenum recovery, which also will improve 

the separation of sulfide minerals and increase NNP of the resulting tailings.
Geologic and Environmental Characteristics of Porphyry Copper Deposits – April 2012

19

Table 5. Geochemical composition of porphyry copper tailing samples from the literature and unpublished USGS 

studies.

Mine Unit Aitik El Teniente El Teniente CauquenesTenientePiquenesAndinaEl Salvador Sarcheshmeh

Country Sweden Chile Chile Chile Chile Chile Iran

Sample No. Aitik 1 Channel 

average

Sediment 

average

T1 average A2 average E2 average S6/S7 average

Source 1 2 2 3 3 3 4

Al2O3 % 15.65

CaO % 3.425

Fe2O3 % 10.3

K2O % 4.775

MgO % 2.185

MnO % 0.32

Na2O % 2.36

P2O5 % 0.64

SiO2 % 54.4

TiO2 % 0.74

As mg/kg 3.50 33.0 36.0 92.9 62.0 136.3 18.5

Ba mg/kg 930.5 382 384 470.3 721.3 418.3

Be mg/kg 1.55

Bi mg/kg 1.505

Cd mg/kg <0.01

Co mg/kg 61.45 27.6

Cr mg/kg 20 67 64 29.4 14.4 8.5 53

Cu mg/kg 478 1035 921 3037 2515.2 5091.2 1205

Mn mg/kg 2165 358 376 334.5 592.3 67.3 700.5

Mo mg/kg 11.75 89 101 108.5 53 234.6 96.7

Ni mg/kg 14.15 23 23 40

Pb mg/kg 9.85 20 36.9 22.5 46.0

Sb mg/kg 2.77

U mg/kg 4.45

V mg/kg 155.5 243 230 208.9 125.5 139.9

Zn mg/kg 74 62 58 92.94 208.98 42.9 210

S % 2.64 3.62 3.43

Carbonate C % 0.01

Total C % 0.01

LOI % 3.55

NNP kg CaCO3/t -74.3 -18.2 -28.3 -101.6

Sources: 1. This study; 2. Smuda and others (2008); 3. Dold and Fonboté (2001); 4. Khorasanipour and others (2011)

Additional insights into aquatic concerns associated with tailings can be found in case studies from mines. The 

geochemical characteristics of tailings seepage have been investigated by several studies. Smuda and others 

(2008) investigated the geochemical environment associated with tailings at the El Teniente porphyry copper

deposit, Chile. They found a range of values for various water-quality parameters associated with the tailings pond. 

These parameters included pH (7.2-10.2), sulfate (1556-5574 mg/L), Fe (1.44-8.59 mg/L), Al (below detection - 

0.886 mg/L), Mn (0.001-20.1 mg/L), Ni (0.008-0.393 mg/L), Cu (0.003-0.250 mg/L), Zn (0.007-130 mg/L), Mo 

(0.033-13.2 mg/L), and As (below detection–0.345 mg/L). Khorasanipour and others (2011) studied the 
Geologic and Environmental Characteristics of Porphyry Copper Deposits – April 2012

20

geochemical environment associated with tailings at the Sarcheshmeh mine, Iran. They too found a range of 

values for water-quality parameters such as pH (3.6-7.9),sulfate (1348-4479 mg/L), Fe (<0.01-19.3 mg/L), Al (<0.5-

154 mg/L), Mn (5.6-73.7 mg/L), Ni (0.088-1.74 mg/L), Cu (< 0.002-149.9 mg/L), Zn (0.094-20.3 mg/L), Mo (0.027-

2.9 mg/L), and As (< 0.005-0.04 mg/L).

Table 6. Geochemical composition of test tailings samples from the Pebble deposit from the Pebble Project 

Environmental Baseline Document. Summary statistics include all samples presented in Tables 11-46 and 11-47 in 

Pebble Partnership (2011).

Parameter Units Average Standard 

Deviation

Low High

Ag mg/kg 0.7 0.5 0.23 2.17

As mg/kg 25.2 31.6 4.2 169

Ba mg/kg 30.0 10.6 20 50

Be mg/kg 0.3 0.1 0.18 0.64

Bi mg/kg 0.6 0.5 0.2 1.98

Cd mg/kg 0.1 0.1 0.03 0.4

Co mg/kg 8.1 10.2 2.2 45.9

Cr mg/kg 149.9 177.3 6 748

Cu mg/kg 682.9 414.0 142 2050

Hg mg/kg 0.1 0.1 < 0.01 0.56

Mn mg/kg 359.9 201.4 84 880

Mo mg/kg 51.9 35.1 10.5 188

Ni mg/kg 67.7 111.6 6.3 452

Pb mg/kg 15.0 16.6 3.3 88.4

Sb mg/kg 1.0 1.0 0.2 5.41

Se mg/kg 1.8 2.0 0.4 8.8

Tl mg/kg 0.3 0.2 0.07 1.2

U mg/kg 0.4 0.2 0.17 0.87

V mg/kg 87.3 36.0 36 149

Zn mg/kg 87.4 66.3 29 267

Paste pH Standard Unit 8.2 0.4 6.6 8.9

Total S % 0.5 0.9 0.09 4.19

Sulfate % 0.0 0.0 -0.01 0.2

Sulfide % 0.5 0.9 0.05 4.12

AP kg CaCO3/t 14.2 27.8 1.56 128.8

TIC % 0.3 0.2 0.05 0.75

TIC kg CaCO3/t 22.6 15.5 4.5 62.5

NP (Modified) kg CaCO3/t 13.5 6.9 4.6 25.9

NP/AP ratio 2.7 1.9 0.1 9

NNP kg CaCO3/t -0.5 27.2 -110.2 22.4
Geologic and Environmental Characteristics of Porphyry Copper Deposits – April 2012

21

Morin and Hutt (2001) compared predictions for tailing leachate chemistry with actual drainage chemistry at the 

Bell mine in British Columbia on the basis of samples collected seven years after closure. The predictions 

indicated that drainage from the tailing piles would start at near neutral pH conditions, but would turn acidic over the 

course of several decades. Their post-closure sampling results indicated that acid generation is roughly 100 times 

less than predicted. The authors attributed this discrepancy to basing prediction on an insufficient number of 

humidity-cell tests and incorrect assumptions about the rate of sulfide oxidation. Weibel and others (2011) found 

similar results in studies of a porphyry copper mine in Chile.

As with the waste rock at Pebble, the best insights into the potential behavior of mill tailings come from the 

humidity-cell tests being conducted by the Pebble Limited Partnership and its contractors (Pebble Partnership, 

2011). The Pebble Partnership initiated two sets of humidity-cell tests on tailings derived from preliminary

metallurgical testing: one set in 2005 and one set in 2008 (Pebble Partnership, 2011). Humidity-cell tests represent 

one of the best predictors of long-term weathering of tailings in an aerobic environment (Price, 2009). The test 

conditions are most representative of unsaturated tailings exposed at the surface of a pile. The geochemical 

environment found at depth in the saturated zone is typically quite different (Blowes and others, 2003). The 2005 

tailings samples originated from a relatively simple set of metallurgical methods, whereas the 2008 samples 

originated from a greater variety of metallurgical processing methods. The humidity-cell tests for the tailings 

samples were conducted using standard procedures, as described above for the waste-rock samples (Price, 2009). 

However, the grain size of the tailings is well below the 6 mm maximum size of waste-rock samples, which means 

that the tailings should be more reactive than the waste-rock samples in humidity-cell tests. The results included 

the same set of parameters as with the waste-rock testing. As for the waste-rock samples, the following discussion 

focuses on pH, sulfate, copper, zinc, molybdenum, and arsenic.

The mean humidity-cell results were similar for both the 2005 and 2008 sets of tailings (Pebble Partnership, 

2011). Both sets had pH values ranging between 7 and 8.5 in experiments lasting up to five years for the 2005 

samples and for more than one year for the 2008 samples (Table 7). As with the waste-rock samples, individual 

humidity-cell tests for tailings can show a range of leachate concentrations that vary over the course of the 

experiment. In general, the concentrations of dissolved constituents are most erratic and highest in the initial flush 

covering the first few one-week cycles in humidity-cell tests; several weeks after the start of the experiments, the 

concentrations of dissolved constituents tends to stabilize. The average release rates used in Table 7 obscure this 

variability, although its magnitude can be assessed by the standard deviations present with means in Table 7. 

Sulfate concentrations for both sets (2005 and 2008) generally are below 40 mg/L after the initial flush of soluble 

sulfate salts. The mean sulfate release concentration was 17.4 ± 8.0 mg/L. The mean copper (5.3 ± 2.2 μg/L), and 

zinc (3.2 ± 1.7 μg/L) concentrations were less than those from the waste-rock samples, whereas the molybdenum 

(33.5 ± 23.7 μg/L), and arsenic (5.5 ± 8.4 μg/L) concentrations were higher (Table 4).

The chemical composition of the pond on top of the tailing impoundment is difficult to estimate, but bounds can

be placed on its composition. During mine operation, the water should represent a mixture of the supernatant 

solution from the mill that is pumped with the tailings slurry to the impoundment, solutes derived from aerobic 

leaching of the tailings material, which can be limited by the average humidity-cell results from tailings, and ambient 

surface water and precipitation, which can be approximated generically by the mean composition of the North Fork 

of the Koktuli River. The range of potential compositions is shown in Figure 8 by the triangle, which limits the range 

from these three sources in terms of dissolved copper concentration and water hardness. The supernatant solution 

has the highest copper concentration and water hardness of the three end members. The variability of its 

composition in the samples from metallurgical testing is reflect by the standard deviations shown in Table 7. The 

location of the hypothetical compositions either within the triangular field for those waters associated with the PreTertiary waste-rock piles will depend on the water balance of water-management practices during and after mining.
Geologic and Environmental Characteristics of Porphyry Copper Deposits – April 2012

22

Table 7. Summary of geochemical results from mean humidity-cell tests on tailing samples and the supernatant 

solution from metallurgical testing conducted by the Pebble Partnership (2011)

Parameter Units Tailings Humidity Cell Supernatant 

Average Standard Deviation Average Standard Deviation

Pebble Partnership 

(2011) Source

Table 11-49 (calc); 

Appendix 11L (pH)

Table 11-49 (calc); 

Appendix 11L (pH)

Table 11-48 Table 11-48

pH S.U. 7.8 0.2 7.9 0.3

Alkalinity mg/L CaCO3 59.7 15.5 74.8 20.4

Hardness mg/L CaCO3 66.8 13.6 322.8 254.8

Cl mg/L 0.52 0.08 nr nr

F mg/L 0.451 0.440 nr nr

SO4 mg/L 17.4 8.0 318.7 372.1

Thiosalts (S2O3) mg/L nr nr 44.1 156.1

Ag mg/L 0.00001 0.00000 0.00002 0.00025

Al mg/L 0.02 0.03 0.07 0.08

As mg/L 0.0055 0.0084 0.0172 0.0212

B mg/L 0.0107 0.0010 nr nr

Ba mg/L 0.0092 0.0050 nr nr

Be mg/L 0.0002 0.0000 nr nr

Bi mg/L 0.0005 0.0000 nr nr

Ca mg/L 22.6 3.9 116.0 101.2

Cd mg/L 0.00001 0.00000 -0.00008 0.00018

Co mg/L 0.0002 0.0002 -0.0001 0.0004

Cr mg/L 0.0005 0.0000 -0.0010 0.0012

Cu mg/L 0.0053 0.0022 0.0078 0.0049

Fe mg/L 0.03 0.00 0.02 0.32

Hg mg/L 0.000010 0.000000 -0.000037 0.000103

K mg/L 4.02 1.69 25.95 8.16

Mg mg/L 2.55 2.07 8.00 5.53

Mn mg/L 0.0441 0.0224 0.0719 0.0631

Mo mg/L 0.0335 0.0237 0.0697 0.0560

Na mg/L 2.10 0.26 43.78 132.40

Ni mg/L 0.0005 0.0001 -0.0008 0.0018

Pb mg/L 0.00006 0.00001 0.00023 0.00062

Sb mg/L 0.0018 0.0017 0.0060 0.0058

Se mg/L 0.0015 0.0006 0.0076 0.0062

Sn mg/L 0.0029 0.0040 nr nr

Tl mg/L 0.00005 0.00000 0.00002 0.00022

V mg/L 0.0008 0.0008 nr nr

Zn mg/L 0.0032 0.0017 0.0043 0.0080

nr: not reported
Geologic and Environmental Characteristics of Porphyry Copper Deposits – April 2012

23

The composition of water potentially seeping from the base of tailing piles is more problematic to estimate. At 

depth in the saturated zone in tailing piles, dissolved oxygen is rapidly removed by reaction with trace amounts of 

sulfide minerals, which limits the ability to generate acid during further interaction with tailings material. In these 

acid-limited environments, silicate minerals such as feldspars and trace amounts of carbonate minerals can 

effectively neutralize acid and restrict the ability of groundwater to dissolve additional metals and other trace 

elements (Blowes and others, 2003). Under these conditions, the chemical composition of seepage from a tailings 

pile should fall along the join between the average humidity-cell test composition and ambient surface water and 

groundwater (Figure 8).

0 

2 

4 

6 

8 

10

0 50 100 150 200 250 300 350

Dissolved Copper μg/L

Hardness mg/L CaCO3 

North Fork Koktuli River

Tailings Average HCT

Supernatant Average

Figure 8. Dissolved copper concentrations and water hardness values for various potential end-member waters 

around the Pebble site in the Bristol Bay watershed associated with a tailings impoundment. The humidity-cell 

test concentrations are from Table 7. The mean concentrations for the North Fork of the Koktuli River are from 

Pebble Partnership (2011). The triangle represents the range of potential compositions that could be expected 

for a tailing pond during mine operation; after closure, once ore processing has ceased, the join between the 

North Fork and the Tailings Average HCT compositions may be more representative of the range of potential 

compositions (see text). Abbreviations: HCT, Humidity-Cell Test.

Copper Concentrate

Limited data are available on the geochemistry of copper concentrates from porphyry copper deposits. The 

geochemical analysis by USGS laboratories of a single sample of a copper concentrate from the Aitik porphyry 

copper deposit is presented in Table 8. X-ray diffraction analysis indicates that the sample is dominated by 

chalcopyrite with trace amounts of pyrite, quartz, and possibly molybdenite. The ideal composition of chalcopyrite is 

34.6 weight percent Cu, 30.4 weight percent Fe, and 34.9 weight percent S. For the analysis presented in Table 8, 
Geologic and Environmental Characteristics of Porphyry Copper Deposits – April 2012

24

the Cu concentration is above the upper detection limit. However, the analyzed concentration of S (33.4 wt. %) 

indicates that the sample is greater than 95 percent chalcopyrite, whereas that of Fe (25.8 wt. %) indicates 

approximately 85 percent chalcopyrite. The most notable trace elements in this concentrate are Zn (2190 mg/kg), 

presumably reflecting the presence of minor sphalerite, Mo (1100 mg/kg), presumably reflecting the presence of 

molybdenite, and Mn (346 mg/kg), likely hosted by sphalerite or traces of the Fe-carbonate mineral siderite.

Table 8. Geochemical analysis of the copper concentrate (Aitik 2) from the Aitik porphyry copper mine, Sweden

Element Units Concentration

Al % 0.98

Ca % 0.32

Fe % 25.8

K % 0.49

Mg % 0.11

Na % 0.19

Ti % 0.05

Ag mg/kg >10

As mg/kg 12

Ba mg/kg 59

Bi mg/kg 44.9

Cd mg/kg 2.4

Co mg/kg 53.9

Cu mg/kg >10000

Ga mg/kg 0.88

In mg/kg 2.35

Mn mg/kg 345

Mo mg/kg 1100

Ni mg/kg 72.1

Pb mg/kg 64.9

Sb mg/kg 43.4

Te mg/kg 4.1

Th mg/kg 1.5

Tl mg/kg 0.2

U mg/kg 2.2

V mg/kg 23

Zn mg/kg 2190

S % 33.4

The solution chemistry associated with the transport of concentrate as a slurry in a pipeline can be assessed 

by conducting leaching experiments on the Aitik copper concentrate sample described above, which is 

mineralogically similar to copper concentrates from most porphyry copper mines. In flotation circuits, chalcopyrite 

is not especially sensitive to pH, but pH may be adjusted to alkaline values to separate molybdenite or pyrite 

(Fuerstenau and others, 2007).
Geologic and Environmental Characteristics of Porphyry Copper Deposits – April 2012

25

The leachability of elements from copper concentrate was evaluated using the Synthetic Precipitation Leaching 

Procedure (USEPA Method 1312), and a modification of this protocol. The standard procedure reacts a sample in 

a 20:1 (solution: sample) ratio with a weak acidic solution (pH 5), made of a mixture of sulfuric and nitric acids, 

under continuous agitation for 18 hours, after which the solution is sampled. Additional leaching experiments were 

conducted in which the copper concentrate sample was leached following the same procedure except that the 

starting leaching solution was either distilled water + NaOH solutions (pH 6, 7, 8, 9), or distilled water + Na2CO3

solutions (pH 7, 9) adjusted to various starting pH values. The purpose of these experiments was to evaluate the 

range of starting pH values that may be associated with a copper-concentrate slurry discharged from a mill to a 

pipeline.

The results of the leaching experiments on the copper concentrate are presented in Table 9. Results from a 

copper tailings sample from Aitik are also presented in Table 9. One of the most striking features of these 

experiments using the copper concentrate is that regardless of the starting pH (pH = 5 to 9), the final pH after 18 

hours for all experiments ended up between 4.1 and 4.2. Equally striking was the fact that dissolved copper 

concentrations in the leachate ranged between 15,300 and 16,800 μg/L, dissolved iron concentrations ranged 

between 5,480 and 10,200 μg/L, and dissolved sulfate ranged between 183.7 and 208.8 mg/L.

Summary 

The Pebble deposit in the Bristol Bay watershed, southwestern Alaska, shares many geologic attributes with 

typical porphyry copper deposits throughout the world. These features include: (1) its spatial association with 

coeval granitic intrusions; (2) its large tonnage of ore and its low grade, although the size of Pebble places it in the 

upper 5 percent of porphyry copper deposits globally; (3) the association of copper, molybdenum, and gold; (4) the 

style of mineralization as veinlets, stockworks, and disseminations with igneous and sedimentary host rocks; and 

(5) its zoned ore-mineral and alteration assemblages. From an environmental perspective, the acid-generating 

potential of Pebble is similar to that found at other porphyry copper deposits: waste rock and tailings span the 

range from potentially acidic drainage generating to non-potentially acidic drainage generating due to the low 

contents of pyrite and other sulfide minerals as potential sources of acid, and the presence of silicate minerals such 

as feldspars and trace amounts of carbonate minerals to neutralize acid. Humidity-cell tests by Pebble Partnership 

(2011) indicate that drainage associated with Pre-Tertiary waste rocks is likely to have higher concentrations of 

solutes and lower pH than drainage associated with mine tailings. Solutions associated with a copper concentrate 

slurry are likely to be weakly acidic and have high concentrations of dissolved copper and zinc.
Geologic and Environmental Characteristics of Porphyry Copper Deposits – April 2012

26

Table 9. Geochemical analyses of dissolved constituents (< 0.45 μm) in leachates from tailings and copper 

concentrate from the Aitik Mine, Sweden, using USEPA Method 1312 and a modified leaching method. 

Field No. Units Tailings Copper Concentrate

Base (Acid) WSP* WSP* NaOH NaOH NaOH NaOH Na2CO3 Na2CO3

Starting pH S.U. 5 5 6 7 8 9 7 9

Final pH S.U. 7.3 4.2 4.2 4.2 4.2 4.1 4.2 4.2

Spec. 

Cond.

μS/cm 133 349 362 350 345 372 340 340

DO mg/L 10

T °C 22.6

Alkalinity mg/L 

CaCO3

9.3 0 0 0 0 0 0 0

Ag μg/L <1 <10 <10 <10 <10 <10 <10 <10

Al μg/L 158 1,910 1,820 1,790 1,770 1,850 1,950 1,870

As μg/L <1 <10 <10 <10 <10 <10 <10 <10

Ba μg/L 50.5 38.6 39.2 40 40.7 38.5 37.9 36.2

Ca mg/L 16 30 28.9 29 28.5 28.7 28.2 28.3

Cd μg/L <0.02 6.3 6 5.9 5.9 6 6.3 6

Co μg/L 0.43 157 151 152 151 151 154 152

Cr μg/L <1 <1 <1 <1 <1 <1 <1 <1

Cu μg/L 0.8 16,500 16,300 15,400 15,300 16,800 16,300 15,600

Fe μg/L <50 7,940 9,190 7,440 7,070 10,200 5,560 5,480

K mg/L 2.15 3.4 3.7 3.4 3.4 3.8 3 3.1

Mg mg/L 0.38 5.5 5.2 5.3 5.3 5.2 5.5 5.4

Mn μg/L 20 931 887 891 880 883 918 899

Mo ug/L < 2 < 20 < 20 < 20 < 20 < 20 < 20 < 20

Na mg/L 4.67 0.41 0.52 0.84 0.89 1 0.87 1.5

Ni μg/L <0.4 634 607 613 609 607 620 612

Pb μg/L <0.05 6.16 6.93 6.15 6.08 7.92 5.36 5.55

Sb μg/L 0.47 17.4 13.4 16.6 16.2 14.7 16.8 16.6

Se μg/L < 1 <10 <10 <10 <10 <10 <10 <10

SiO2 mg/L 1.8 <2 <2 <2 <2 <2 <2 <2

U μg/L < 0.1 33.7 33.8 31.2 31.9 34 34.8 33

Zn μg/L 0.6 2,040 1,920 1,950 1,940 1,940 2,040 1,980

Cl mg/L 0.8 2.6 2.6 2.8 2.6 2.6 2.6 2.5

F mg/L 0.2 1.4 1.5 1.5 1.5 1.5 1.6 1.5

NO3 mg/L 0.7 0.4 <0.08 <0.08 <0.08 <0.08 <0.08 <0.08

SO4 mg/L 43.6 192.6 200.8 191.4 185.1 208.8 183.7 184.5

*WSP: Mixture of H2SO4 and HNO3 with pH = 5.0 in accordance with EPA Method 1312.
Geologic and Environmental Characteristics of Porphyry Copper Deposits – April 2012

27

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AN ASSESSMENT OF POTENTIAL MINING IMPACTS ON 

SALMON ECOSYSTEMS OF BRISTOL BAY, ALASKA 

VOLUME 3—APPENDICES E-J

Appendix I: Conventional Water Quality Mitigation Practices 

for Mine Design, Construction, Operation, and Closure 
 

Appendix I

Conventional Water Quality Mitigation 

Practices for Mine Design, Construction, 

Operation, and Closure 

Barbara A. Butler, Ph.D.

U.S. EPA Office of Research and Development

National Risk Management Research Laboratory

Land Remediation and Pollution Control Division

Remediation and Redevelopment Branch

Office of Research and Development

U.S. Environmental Protection Agency

Washington, DC
Mitigation includes the steps needed to avoid, minimize, or compensate for any 

potential adverse impacts on the environment from a given activity (Hough and 

Robertson, 2009). Hardrock metal mining is an activity that provides metals for 

numerous purposes, but it has the potential to have adverse effects on nearby aquatic 

environments. Many mitigation measures developed to avoid or minimize impacts to 

water quality and aquatic ecosystems have become current industry practice and 

several of these are presented in this document for selected waste streams associated 

with mining, along with discussions of accidents and failures associated with storage of 

waste rock and tailings. Compensatory mitigation, which may be required under Section 

404 of the Clean Water Act (CWA) when there are unavoidable impacts anticipated to 

lead to the loss of wetland, stream, or other aquatic resource, is not included in this 

Appendix. 

 

The most important aspects of mitigation for any mining site are proper planning, 

design, construction, operation, management, and closure of waste and water 

containment and treatment facilities, and monitoring and maintenance over all minelife phases, including following closure. A failure in any aspect of mitigation may result 

in environmental and/or human health impacts. Planning for design and construction 

must consider site-specific factors such as climate, topography, hydrology, geology, 

seismicity, and waste material specific factors such as geochemistry, mineralogy, 

particle size, and presence of process chemicals. These factors should be based upon 

accurate characterization and conservative estimates of future conditions to minimize 

potential for failure over time. In addition, the planning and design should incorporate 

considerations for the land’s use following closure of mining operations. 

1. WASTE ROCK

Overburden is unconsolidated surface material that would be removed to expose the 

ore/waste rock zone and often comprises alluvium, colluvium, glacial tills, or other soils; 

overburden may be stockpiled separately for later use in reclamation. Waste rock 

includes rock that is removed above the ore and rock that is removed along with the 

ore, but cannot be mined economically at the time of mining (sub-economic ore). The 

particle size distribution of waste rock may vary from sand-sized fines to large boulders, 

with the quantity in a given particle size class dependent upon the site geology and the 

specifics of the method(s) in which it was extracted (e.g., blasting strength). The sources 

of potential environmental influence to surface water from waste rock piles include 

sediment loading due to erosion and deposition of fugitive dusts, and contaminant 

loading due to leaching of acidity and inorganic contaminants, such as metals and 

metalloids, contained in the waste rock. Precipitation and surface water run-on can 

lead to weathering and erosion of materials into runoff (dissolved and particulate) 

transported to surface water. Percolation and infiltration that lead to leaching and 

transport of ions through seepage of the leachate to groundwater may occur also, as 

may seepage through sloped pervious material to a surface water body. Additional 

1 
routes of environmental exposure include movement of material mass (e.g., through 

rockslides due to physical instability) into a water body and wind erosion carrying finer 

particles (dust) through the air.

Waste rock, and other mining materials may be classified as potentially acid-generating 

(PAG) or non-acid generating (NAG, also called non-PAG); this distinction is determined 

through geochemical characterization, acid-base accounting (ABA) static tests, and 

kinetic leachate testing [e.g., see (American Society for Testing and Materials (ASTM) 

2000, Hornberger and Brady 1998, Lapakko 2002)]. ABA tests are rapid methods to 

determine the acid-generation potential (AP) and neutralization potential (NP) of a rock 

or mining waste material, independent of reaction rates (i.e., in contrast to kinetic 

tests). These potentials are then compared to one another by either their differences 

(net neutralization potential, NNP) or their ratios (neutralization potential ratio, NPR).

Although methods used for ABA have limitations, it is common industry practice to 

consider materials that have an NPR of 1 or less as potentially acid generating (PAG) 

(e.g., Brodie et al., 1991; Price, 2009; Price and Errington, 1998) and materials with a 

ratio greater than 3 (Brodie et al., 1991) or 4 (Price and Errington, 1998) as having no 

acid generation potential (non-PAG or NAG). Materials having ratios between 1 and 4 

require further testing via kinetic tests and geochemical assessment for classification 

(Brodie et al., 1991; Price, 2009; Price and Errington, 1998). This further testing and 

assessment are necessary because if neutralizing minerals react before acid generating 

minerals, the neutralizing effect may not be realized and acid might be generated in the 

future. Additionally, some toxic elements (e.g., selenium and arsenic) may be released 

from mining materials under neutral or higher pH conditions, which would be observed 

during kinetic leaching tests conducted at variable pH values. 

Waste rock is susceptible to acid generation and leaching of ions due to the open pore 

network allowing for easy advection of air (Mining Minerals and Sustainable 

Development (MMSD) 2002) to oxidize minerals, which subsequently are dissolved in 

water that encounters the rocks. 

1.1 CONVENTIONAL PRACTICES

There are numerous mitigation measures available for waste rock piles. The selection of 

mitigation measures are site-specific and depend on the sizes and amounts of the 

material to be placed in the pile, the methods employed during mining, the mineralogy 

of the material, the site’s specific hydrology, climate, seismicity, and topography, and 

plans for future land-use. 

1.1.1 Operational Phase

Non-reactive (i.e., NAG) waste rock might be used in creation of mining roadways or 

transported off-site for use in roadways or another purpose requiring rockfill, with 

2 
unused waste rock stored in piles. Waste rock piles generally are disposed in locations 

close to the mine site to reduce handling costs and are placed in locations that provide 

physical stability. Waste rock and overburden piles typically are not placed on lined 

foundations because of the cost and stability risk (Mining Minerals and Sustainable 

Development (MMSD) 2002), but rather are constructed on natural terrain; although 

the decision for lined or unlined piles is site-specific. Prior to placement of a waste rock 

pile, the topsoil is removed and stockpiled for later use in reclamation. The angle of 

repose (where the outer slope is just stable under static loading conditions) is typically 

37-40° (Mining Minerals and Sustainable Development (MMSD) 2002), but will depend 

on site-specific and material-specific factors. Piles constructed in lifts or by using 

benches typically have lower slope angles and concurrent increased stability (U.S. 

Environmental Protection Agency (U.S.EPA) 1995b, Mining Minerals and Sustainable 

Development (MMSD) 2002). 

When waste rock contains materials that have the potential to generate acid or release 

metals, metalloids, or other ions of concern that would have environmental or human 

health impacts, management of the materials must include practices to minimize 

potential for any environmental impacts. Mitigation/management measures used 

during the operational phase can include a variety of methods either used 

independently or in combination; these include diversion systems to route water away 

from the pile, use of liners underneath the waste rock pile, selective handling / 

segregation, blending and layering, minimization of infiltration potential, leachate 

collection systems and seepage drains and routing systems to divert leachate to 

treatment facilities, addition of bactericides to slow oxidation of PAG, encapsulation, 

and/or adding low permeability materials to slow infiltration rates (Boak and Beale 

2008, Mining Minerals and Sustainable Development (MMSD) 2002, U.S. Environmental 

Protection Agency (U.S.EPA) 1995b, U.S. Environmental Protection Agency (Region 10) 

2003a, U.S. Environmental Protection Agency (Region 10) 2003b, Perry et al. 1998). 

Additionally, the amount of waste rock exposed to the environment can be reduced by 

disposing the rock into depleted pits or underground mine tunnels, or through 

reclamation activities conducted concurrent with active mining (called progressive 

reclamation).

Selective handling involves placement of materials combined with management 

strategies to avoid or minimize release of acidic drainage. Physical separation of PAG 

and NAG materials will not prevent acid-rock drainage formation, but may be necessary 

to control the amount and location of potential drainage and to manage the PAG 

material. PAG material can be kept completely saturated to minimize air exposure (e.g., 

placed into the open pit post active mining), disposed in a separate lined or unlined 

engineered containment system, or blended with NAG material and stored in an 

aboveground pile, coupled with minimizing exposure to water. 

Blending involves mixing waste rock types of varying acid-producing potential (AP) and 

neutralization potential (NP) to create a mixture that has acceptable quality (i.e., no net 

3 
acid-generation potential). The viability of blending as a mitigation measure depends on 

the materials available and the mine plan, the stoichiometric balance between acid 

generating and neutralizing materials, geochemical properties, reactivity of waste rock 

types, flow pathways created within the waste rock pile, and extent of mixing and 

blending. If a site does not have sufficient neutralizing material with which to blend the 

PAG material, limestone or other neutralizing rock might be used, if available from 

another location on-site, or trucked into the site. The geochemical characteristics of the 

materials being blended and mixed must be well-characterized in order to attain a 

resultant mix that has no net acid production potential. 

PAG materials may be kept isolated from direct exposure to precipitation and oxygen 

transfer by layering NAG materials on top of them in the waste pile. This would involve 

layering of PAG with a mix of PAG-NAG material, with a top layer of NAG only material, 

or another combination. 

Encapsulation of a waste rock pile with an impermeable layer serves to limit infiltration 

and oxygen transfer. Progressive reclamation with multiple impermeable layers within a 

waste rock pile can minimize infiltration, seepage, and oxygen transfer. Compaction is 

used also, if it can be done safely (physically). Once a pile is covered, overburden or 

other non-reactive material can be placed on top and the site vegetated to provide 

stability against erosion and to meet regulatory requirements for restoration.

Some microorganisms are able to facilitate rapid oxidation of PAG sulfidic minerals; 

thus, a bactericide could be added to eliminate their presence and slow the oxidation 

rate. Such an amendment must be mixed thoroughly into the PAG material as the pile is 

constructed to ensure effectiveness.

Sub-economic ore removed during the active mining phase might be segregated from 

the primary waste rock pile to be mined if/when it becomes economically feasible. 

These piles may be mined with their resultant waste disposed into a tailings 

impoundment or placed directly in the completed pit, if mined at closure. 

Building an under-drain system to collect seepage/leachate water potentially containing 

leached ions/acidity allows this water to be directed toward collection systems for 

either use in processing or treatment and discharge to a surface water body. Diversion 

structures collect and direct runoff and seepage to treatment and/or settling ponds. 

Groundwater monitoring wells are used downstream of these structures to evaluate 

their performance. 

1.1.2 Closure and Post-Closure

During the closure phase of mining, a dry cover (or encapsulation) can be placed over 

the waste rock pile to isolate it from water and oxygen, or the pile can placed into the 

completed open pit to be kept below the water line (subaqueous disposal if PAG 

4 
material), with choices dependent upon site specifics (O’Kane and Wels 2003). 

Additionally, in some settings, it is beneficial to fill the pit with waste rock and other 

waste material and then construct a dry cover over the filled pit area. When stored 

above ground, the stockpiled overburden may be used to cover the pile and then it is 

vegetated to provide stability against erosion. Blight and Fourie (Blight and Fourie 2003)

recommend that outer slopes reclaimed with vegetation not exceed 15 degrees. Postclosure monitoring, maintenance, and inspection are conducted indefinitely when a pile 

requires long-term collection and treatment of leachate through use of the drainage 

collection and monitoring structures in place during the operational phase of mining. A 

number of different types of covers could be used, with each having their benefits and 

limitations. Factors affecting the long-term performance of covers include physical 

stability, volume change, vegetation, soil evolution, and ecological stability (Wilson, 

Williams and Rykaart 2003). 

1.2 ACCIDENTS AND FAILURES 

If waste rock piles are designed properly with appropriate mitigation measures, 

monitored and maintained, release of contaminants is possible, but unlikely; however, 

accidents and failures causing contaminants to be transported may still occur. Seven

major factors affecting the physical stability of a waste rock pile against failure are: 1) 

configuration; 2) foundation conditions; 3) waste material properties; 4) method of 

construction; 5) dumping rate; 6) piezometric and climatic conditions; and 7) seismic 

and blasting activities ((Piteau Associates Engineering Ltd. 1991), as referenced in (U.S. 

Environmental Protection Agency (U.S.EPA) 1995b). An additional factor to consider is 

monitoring and maintenance for early detection of conditions that indicate inadequate 

stability. Although it depends on a number of site-specific factors, data indicate that 

most waste dump failures occur on foundations with slopes in excess of 20 degrees (U.S. 

Environmental Protection Agency (U.S.EPA) 1995b). 

Physical failures of waste rock piles may occur through slope failures. These result from 

changes in the effective stresses of the rock material, variations in material properties 

(including particle size and gravity sorting), or changes in the rock pile’s geometry 

(Pastor et al. 2002, Tesarik and McKibbin 1999). Changes in effective stress can result 

from earthquakes, human actions, changes in underlying soil properties, or through 

changing pore pressures resulting from rainfall, snowmelt, or changes in drainage 

conditions. Properties of the rock will change over time due to weathering and from the 

influence of acid dissolution, if any nearby PAG materials are oxidized and dissolved. 

Changes in a waste rock pile’s geometry can result from erosion or from actions such as 

excavation, construction, or rebuilding/reshaping of the pile. 

Waste rock piles typically have heterogeneous particle size distribution and varied 

permeability throughout the depth and breadth of the pile. In a field test using tracers, 

Eriksson et al. (Eriksson, Gupta and Destouni 1997), found that 55-70% of the total 

water followed preferential flow pathways. The authors also found that chemical 

5 
tracers behaved differently in weathered waste rock piles versus newer piles. Results 

from Eriksson et al. (Eriksson et al. 1997), support the need for understanding longerterm behavior of the materials and their distribution within a waste rock pile through 

leaching tests, modeling, and field measurements. Blending waste rock with limestone 

is a standard practice to minimize the production of acidic leachate; however, the 

mixing method used during construction of the pile construction may influence the 

method’s success. For example, Miller et al. (Miller et al. 2006), reported blending 

during waste rock pile construction to have only limited success when using haul trucks, 

due to insufficient blending of the limestone with the finer size fraction of waste rock, 

but that better mixing was achieved using a conveyer and stacker. Morin and Hutt 

(Morin and Hutt 2004), as presented in Price (Price 2009), found that variability in 

acidity from seeps of a single waste rock dump ranged from zero to approximately 90 g 

CaCO3/L (standard unit for acidity, where 50 grams of CaCO3 neutralizes 1 mol H+

) in one 

year, which further supports the need for homogenous blending of neutralizing 

materials and complete characterization of waste rock materials. 

Isolation covers have the highest probability of success against geochemical failure (i.e., 

leaching of acidic and/or contaminant-laden water), with their purpose being to limit 

infiltration and oxygen transfer. In a study of a waste rock pile at a mine site in Papau 

Province, Indonesia, however, Andrina et al. (Andrina et al. 2006), found aspects of a 

waste rock pile, including the type of waste rock, particle size distribution, and dumping 

methods, each influenced variations in oxygen and temperature profiles. At that site, 

they found that an impermeable surface cover had only a limited effect on oxygen 

concentrations within the profile of the waste rock pile and concluded that advection of 

airflow through the coarse rock / rubble zone at the foundation of the dump was the 

primary pathway for oxygen transport. 

Monitoring and maintenance activities must continue beyond construction of a waste 

rock pile. Although the pile may have been constructed based on sound slope stability 

studies, and have appropriate covers and means to divert water, the properties of the 

pile may change over time and breaches to covers may occur. Additionally, freeze/thaw 

cycling in colder climates may cause cracks, channeling, and exposure of surfaces below 

the cover (Sartz et al. 2011) and should be considered when designing piles and 

mitigation measures in these climates. Such cycling could result in accelerated 

weathering and leaching of materials (Dawson and Morin 1996, SRK Consulting 2009). 

With careful monitoring and early remedy of observed defects, some catastrophic 

consequences can be avoided. 

2. TAILINGS

Tailings are a solid-liquid slurry material comprising fine-grained waste particles 

remaining after ore processing (e.g., milling, flotation, separation, leaching) and typically 

in the silt size-fraction ranging from 0.001 to 0.6 mm, along with water and residual 

6 
chemicals (Mining Minerals and Sustainable Development (MMSD) 2002, U.S. 

Environmental Protection Agency (U.S.EPA) 1994). Similar to waste rock, tailings 

materials may be potentially acid-generating (PAG) or non-acid generating (NAG) and 

testing is conducted to assess their characteristics. The majority of ore mined and 

processed ends up as tailings. Tailings slurries have a solids content from 15 to 55 

percent weight (U.S. EPA 1994). The liquid portion of tailings comprises water and 

chemicals used in processing of the ore (e.g., sodium ethyl xanthate, methyl isobutyl 

ketone, hydroxy oxime, acids, alcohols). Cyanide and metals may be present if the 

process includes cyanidation or pyrite suppression, with disposal of waste solution and 

tailings in the tailings impoundment. Logsdon et al (Logsdon, Hagelstein and Mudder 

1999) present concentrations of cyanide and various metals that might be expected (if 

present in the ore) in solutions following gold extraction: total cyanide (50-2000 mg/l), 

arsenic (0-115 mg/l), copper (0.1-300 mg/l), iron (0.1-100 mg/l), lead (0-0.1 mg/l), 

molybdenum (0-4.7 mg/l), nickel (0.3-35 mg/l) and zinc (13-740 mg/l). 

The sources of potential environmental impacts to water from tailings storage facilities 

(TSF) are sediment loading and leaching of acidity and inorganic contaminants, such as 

metals and metalloids, and other chemicals used that may be present in the processing 

waste tailings. The main environmental influences originate from seepage of 

contaminants into groundwater, leakage through containment walls, and exposure of 

waterfowl (if a tailings pond is present) to chemical contaminants. Additional routes of 

environmental exposure include movement of material mass from structural failure of a 

tailings impoundment (e.g., through breach of embankments) into a water body, and 

wind erosion carrying finer particles through the air during construction.

2.1 CONVENTIONAL PRACTICES

The selection and design of a tailings disposal site is site specific and depend on factors 

such as climate, topography, geology, hydrology, seismicity, economics, and 

environmental and human safety (e.g., see (Commonwealth of Australia 2007, U.S. 

Environmental Protection Agency (Region 10) 2003a, U.S. Environmental Protection 

Agency (Region 10) 2003b). The most basic requirements of any tailings storage facility 

(TSF), also called a tailings disposal facility, are that it is safe, stable, and economical, 

and that it presents negligible public health and safety risks and acceptably low social 

and environmental impacts during operation and post-closure. Effective construction 

must be based on a correct geotechnical assessment.

2.1.1 Operational Phase

Disposal options for tailings include 1) land-based placement into an impoundment; 2) 

disposal into underground workings or open pits; and 3) underwater (sub-aqueous) 

disposal into an existing water body or a constructed water body. The most common 

method of disposal is into a tailings slurry impoundment. Tailings impoundments are 

constructed as water-holding structures. This generally is accomplished by constructing 

7 
a tailings dam in a valley. As tailings are placed behind the dam, a basin is formed. The 

solid portion of the tailings settles and the liquid portion creates a tailings pond. 

Construction of a tailings impoundment is done in lifts over the life of the mine. Tailings 

deposited against the embankment in creation of beaches leads to water draining away 

from the embankment, which reduces seepage and increases dam stability. Water 

levels in the tailings pond are controlled through removal of excess water for use in the 

mining process or for treatment and discharge to the local surface water; this minimizes 

water storage to enhance stability. 

Special care must be taken during operations and post-closure to isolate acidproducing/metal leaching tailings from oxidation. A common method is for disposal of 

such tailings underwater (either into an existing water body or into a tailings pond). 

Sub-aqueous disposal is common in Canada and is considered a BMP for long-term 

isolation of tailings from oxidation; loss of any existing water body through this method 

must be replaced (O’Kane and Wels 2003). Sub-aqueous disposal has the potential for 

problems with physical stability, seepage, and water quality; however, if properly 

designed, constructed, and maintained, this type of storage provides good long-term 

isolation post-closure. At least a 30-cm barrier of stagnant water should overly the 

tailings (wave action would re-suspend particles closer to the surface if not stagnant); in 

Canada, a minimum recommended depth is 100-cm (SRK Consulting 2005). Subaqueous disposal is not applicable in all environments (e.g., arid regions), and disposal 

into an existing water body is not supported at all in Australia (Witt et al. 2004). 

Tailings impoundments can be constructed using upstream, downstream, and centerline 

methods. The upstream method involves construction of walls on top of consolidated 

and desiccated tailings in an upstream direction, using waste rock or tailings for 

construction material; the downstream method involves construction with waste rock 

or borrow materials in a downstream direction; and the centerline method involves 

construction of the walls above a fixed crest alignment, using waste rock, borrow 

materials, or tailings (Commonwealth of Australia 2007). According to the International 

Commission on Large Dams (ICOLD), from a seismic standpoint, tailings dams built by 

the upstream method are less stable than dams built by either the downstream or the 

centerline method (International Commission on Large Dams (ICOLD) 2001). The state 

of Idaho considers upstream construction unsuitable for impoundments intended to be 

very high and/or to contain large volumes of water or solids 

(http://www.idl.idaho.gov/Bureau/Minerals/bmp_manual1992/p16-ch4.pdf). The 

downstream method is considered more stable from a seismic standpoint, but it also is 

the most expensive option; centerline construction is a hybrid of upstream and 

downstream construction types and has risks and costs lying between them (Chambers 

and Higman 2011, Martin et al. 2002). 

When tailings impoundments are constructed in earthquake-prone locations, a critical 

design criterion is magnitude of earthquake that could be expected to occur. The most 

conservative design would consider the maximum credible earthquake (MCE), which 

8 
would be the largest quake that could occur reasonably at any location at the mine site, 

based on seismological and geological evidence and interpretation (Chambers and 

Higman 2011). 

Dewatering (thickening) of tailings prior to disposal enables more process water to be 

directly recycled back to mineral processing plant to reduce losses and operational 

demand, while reducing the amount of water stored in the TSF. Reduction of water 

quantity will reduce risks of overtopping, seepage, and evaporative losses of water that 

could be used in the mining process (rather than fresh water). Depositional beach 

angles also are steeper, which aids in containment. 

Paste tailings technology requires thickening (water content ~ 20%) the tailings and 

placing them onto a lined disposal site. Dry stack tailings require filtering the tailings 

and placing the tailings onto a lined pad. Tailings thickened to a paste and filtered 

tailings can be ‘stacked’ for long-term storage. This method is relatively new, but has 

the advantages of reduced potential for liquefaction during an earthquake and tailings 

release from a breach in containment would be localized instead of flowing long 

distances (Witt et al. 2004). Filtered (e.g., moisture content ~ < 20%) and stacked 

tailings require a smaller footprint for storage, are easier to reclaim both at closure and 

by progressive reclamation, and have lower potential for structural failure and 

environmental impacts (Martin et al. 2002). Additionally, in cold climates, dry stacking 

prevents pipes from freezing, prevents frosting problems associated with conventional 

impoundments, and assists in retention and recycling of process water during cold 

weather operations (Access Consulting Group 2007). Disadvantages include that dry 

stacking is not appropriate for acid-generating tailings and pumping to the storage 

facility is difficult due to high viscosity and resistance to flow (filtered tailings for 

stacking are transported to storage via truck). There also is potential for generation of 

dusts (Witt et al. 2004). Thickened and paste tailings disposal is becoming more 

widespread; past limitations were high costs and lack of suitable thickener technology 

(Commonwealth of Australia 2007). This type of storage has less application at larger 

operations where tailings ponds may serve a dual role of process and excess water 

storage as well as tailings storage. Dry stacked tailings disposal is most applicable in arid 

regions or in cold regions where water handling is difficult (Martin et al. 2002). 

Mitigation measures for a TSF may include any combination of a liner, under-drains, and 

decant systems when there is expectation of seepage or the presence of groundwater, 

and prevention of the formation of low permeability lenses or layers on tailings beaches 

that could cause future seepage or stability concerns (Commonwealth of Australia 

2007). Liners can include a high-density polyethylene (HDPE) or other type of 

geosynthetic material, a clay cover over an area of high hydraulic conductivity, or a 

combination. A properly constructed clay liner could be expected to have a saturated 

hydraulic conductivity of 10-8 m/s and a geomembrane to have a hydraulic conductivity 

of ~ 10-10 m/s; however, the lifetime of a geomembrane may vary widely, depending on 

a number of factors, including composition and site temperature. For example, Koerner 

9 
et al. (2011) presents that a nonexposed HDPE liner could have a predicted lifetime (“as 

measured by its halflife”) of 69 years at 40 °C to 446 years at 20 °C. Where 

geomembranes are used, a drainage layer atop the membrane is commonly included to 

reduce the water pressure on the liner and minimize leakage. Liners may cover the 

entire impoundment area, or only the pervious bedrock or porous soils. Full liners 

beneath TSFs are not always used; however, there is a growing requirement to use 

liners to minimize risks of groundwater contamination, with new mines in Australia 

being required to justify why one wouldn’t be required (Commonwealth of Australia 

2007). Under-drains serve a dual purpose of reducing water saturation of the tailings 

sediments to improve geotechnical strength and safety of the facility as well as for 

directing drainage toward a storage area for subsequent treatment. If seepage from the 

TSF is expected (or if observed during monitoring), mitigation or remedial measures 

include interception trenches and/or seepage recovery wells to be installed around the 

perimeter and downstream to capture the water for redirection to a treatment facility. 

A spillway diversion commonly is constructed to provide a catchment for precipitation 

runoff. 

The flotation process used to produce metal sulfide concentrates from porphyry 

deposits results in two tailings waste streams: one from the rougher circuit (to remove 

gangue material comprising silicates and oxides) and one from the cleaner circuit 

(pyrite-rich). It is possible to use a technique called “selective flotation” to separate 

most of the pyrite into the cleaner circuit tailings (PAG) with the rougher tailings 

comprising mostly NAG. Traditionally, these tailings streams were combined, but they 

could be separated selectively, with the PAG being discharged deeper into the TSF and 

the NAG discharged and used as a cover for the PAG. Success is dependent upon the 

ore and the efficiency of a clean separation (Martin et al. 2002). 

In leaching of gold ore, mitigation practices include not locating leaching operations in 

or near a water body, detoxification of materials prior to disposal or closure, and 

ensuring that the solution can be contained in the presence of increased flows, up to 

the maximum reasonable storm event (U.S. Environmental Protection Agency (U.S.EPA) 

1995a). When tank leached, the tailings and spent solution are stored in the TSF. The 

conventional method for recovery of gold from ore typically involves tank leaching with 

dilute (100-500 ppm) sodium cyanide (Logsdon et al. 1999). Following leaching, either 

zinc metal or activated carbon is added to the solution to recover the gold. The residual 

solution either is treated in a water treatment plant or stored with the process tailings 

in the TSF pond. When stored in the TSF pond, the cyanide concentrations should be 

such that there would be no adverse effects to wildlife, such as birds landing on the 

pond. Although rates could depend on the climate and other site specifics, cyanide 

concentrations are known to decrease through natural attenuation, including 

volatilization and subsequent interactions with UV, biological oxidation, and 

precipitation (Logsdon et al. 1999). 

10
Monitoring groundwater quality for contaminant transport includes piezometers for 

groundwater mounding assessment. Regular inspections/monitoring for TSF stability 

include evaluation of seepage discharges through the dams, foundations, abutments, 

and liners; phreatic surface in ponds and dams; pore pressures; horizontal and vertical 

movement; and the status of leak detection systems, secondary containment, auto flow 

measurement and fault alarms, condition of pump and pipelines. Azam and Li (Azam 

and Li 2010) point out the importance of monitoring pore water pressures and 

embankment deformation based on correlation with several types of failure, and 

provides a basis to rectify the situation before failure ensues.

2.1.2 Closure and Post-Closure

Closure requires the TSF to have either a continuous water cover or an engineered cover 

to prevent oxidation of tailings. Sufficient capital is required to finance inspections, 

maintenance, and repairs in post-closure for as long as the tailings exist. 

Closure of a TSF includes containment/encapsulation, minimization of seepage, 

stabilization with a surface cover to prevent erosion and infiltration, diversions and 

collection of precipitation, and design of final landform to minimize post-closure 

maintenance (the final landform desired should be considered during the planning 

phase). There are a number of cover types and depths that can be chosen; the choice is 

site specific and depends on climate, type and volume of tailings, size and geometry of 

the TSF, available cover material, and the end-use for the property (e.g., (O’Kane and 

Wels 2003, Wilson et al. 2003). A conventional cover is typically a low hydraulic 

conductivity layer of clay (and/or a geosynthetic membrane) overlain with protective 

soil layers and generally 1.2 to 1.5 meters thick (O’Kane and Wels 2003). The soil layers 

minimize deterioration due to desiccation, frost action, erosion, animal burrowing, and 

infiltration of plant roots [(Caldwell and Reith 1993) as reported in (O’Kane and Wels 

2003)]. Covers are not used for submerged tailings, and placing covers on tailings that 

have not been dewatered can cause future stability problems 

(http://www.idl.idaho.gov/Bureau/Minerals/bmp_manual1992/p16-ch4.pdf).

Diversions and spillway structures are constructed to minimize potential erosion of the 

cover from surface water. Traditionally, water in TSF ponds has been drained as 

completely as possible prior to closure to reduce potential for overtopping and erosion 

of the embankments; raising water levels in large dams could cause considerable longterm risk. However, water covers might be used when feasible to maintain a 

submerged condition, such as in regions where the hydrology is well-understood and 

the terrain is flat, such as has been used and encouraged in Canada (Martin et al. 2002). 

Regardless of the type of reclamation used for closure, the reclaimed facility must be 

monitored and maintained to ensure stability over time. Post-closure monitoring for 

contaminant transport is the same as during the operational phase, with piezometers 

for assessment of ground water mounding and monitoring wells for groundwater 

11
quality. The reclaimed facility should be monitored for any deformations, structural 

changes, or weaknesses, and the surfaces should be inspected for intrusion by animals, 

humans, or vegetation, any of which could compromise long-term stability. 

2.2 ACCIDENTS AND FAILURES 

The main causes of physical failures of tailings storage facilities are related to 1) a lack of 

control on the water balance; 2) lack of control on construction; and 3) a general lack of 

understanding of the features that control safe operating conditions (International 

Commission on Large Dams (ICOLD) 2001). Additionally, the upstream method for dam 

construction was found to be more prone to failure as compared to those constructed 

via the downstream method most likely due to embankment material generally having a 

low relative density and high water saturation (U.S. EPA, 1994). 

In order of prevalence, failure mechanisms observed for TSFs are slope instability, 

earthquakes, overtopping, inadequate foundations, seepage, and structural problems 

(Blight and Fourie 2003, Commonwealth of Australia 2007). Failure during operation 

could occur from any of the following: 1) rupture of delivery pipeline or decant water 

return pipeline; 2) rainfall induced erosion or piping of outer tailings face; 3) 

geotechnical failure or excessive deformation of containment dyke; 4) overfilling of the 

tailings storage facility leading to overtopping by water; 5) seepage through 

containment dyke; and/or 6) seepage into the foundation. In addition to the above 

(aside from deliver and return pipelines), failures post-closure could result from failure 

of the spillway (if present), or failure of the cover through internal or external forces, 

including weathering of materials, erosion, extreme weather events, or intrusion by 

vegetation or wildlife (Commonwealth of Australia 2007, Witt et al. 2004). 

Earthquakes can cause liquefaction, which is a process in which a soil mass loses shear 

resistance through increased water pressure. Liquefaction in the absence of an 

earthquake is called static liquefaction. Static liquefaction can result from slope 

instability or another mechanism. As reported in Davies (Davies 2001), upstream 

constructed dams are “more susceptible to liquefaction flow events and are solely 

responsible for all major static liquefaction events”; the author also states that 

earthquakes are of little concern for non-upstream dams. Liquefaction of a large 

volume of tailings causes them to flow out of a breach as a viscous liquid which is 

capable of moving long distances before coming to rest. For example, 3 million cubic 

meters of tailings escaped at Bafokeng, South Africa, and travelled 42 km before the 

remaining 2 million cubic meters was stopped by flowing into a water retention dam 

(Blight and Fourie 2003). Conventional TSF materials can have very low shear strength 

and are susceptible to liquefaction. Therefore, earthquake-induced liquefaction is a key 

design consideration to minimize risks of failure resulting from an earthquake event 

(Martin et al. 2002). Earthquake risks also are reduced when tailings have a higher 

density or are dry tailings.

12
Overtopping is caused by excessive water inflow, such as through precipitation or rapid 

snowmelt, and is cited as being the primary failure mode for almost half of all reported 

incidents occurring at inactive dams (Davies 2001). Overtopping can result in erosion 

and breaching of the embankment to release tailings and contaminated water 

downstream. Internal erosion by water (called piping) is a slow process and related to 

seepage/infiltration causing internal water pressures to exceed the critical hydraulic 

gradient and result in a pathway through which particles are carried. Guidelines exist 

for TSF design to minimize this risk; however, Jantzer and Knutsson (Jantzer and 

Knutsson 2010) believe that, at least in Sweden, critical gradient guidelines are 

insufficient to yield long-term stability. Unstable materials experience particle migration 

at much lower hydraulic gradients than do more stable or compacted materials. 

Structural failure could result in the release of large amounts of tailings solids and 

water; for example, a failure at Church Rock, New Mexico released 357,000 cubic 

meters of tailings water and ~990 tons of solids into an adjacent stream in 1979 (Witt et 

al. 2004). Closed facilities are more prone to failures caused by external erosion, 

primarily because of a lack of frequent monitoring, which occurs more easily when the 

site is occupied daily during active mining. Diversion ditches help prevent erosion by 

redirecting surface flow away from the TSF. Usually, failures result from a combination 

of factors, with climate, tailings properties, and geometry influencing which of these 

processes is likely to be the most prominent cause. Seepage-related failures are the 

main failure mode for tailings dams constructed using downstream or centerline 

methods (Davies 2001). Increases in seepage rates or turbidity can be key indicators of 

a developing failure situation (Alaska Department of Natural Resources (AK DNR) 2005). 

Thus, adequate planning, suitable design, and monitoring and control of operation and 

post closure may prevent deteriorative actions.

The failure rate of tailings dams depends directly on the engineering methods used in 

design and the monitoring and inspection programs in the other mine-life stages. 

According to Witt et al. (Witt et al. 2004), with an assumption of 3500 worldwide tailings 

dams and failure rates of 2-5 dams per year, the annual probability of a TSF failure is 

between 1 in 700 to 1 in 1750, in contrast to < 1 in 10,000 apparent for conventional 

water dams. Using data obtained from the World Information Service of Energy (WISE, 

www.wise-uranium.org/mdaf.html) for the 10 years prior to March 22, 2011, Chambers 

and Higman (Chambers and Higman 2011) report that the worldwide failure rate of 

tailings dams has remained at 1 failure every 8 months (i.e. two failures every 3 years). 

Azam and Li (Azam and Li 2010), using databases from the United Nations 

Environmental Protection (UNEP), the International Commission on Large Dams (ICOLD), 

the World Information Service of Energy (WISE), the United States Commission on Large 

Dams (USCOLD), and the United States Environmental Protection Agency (U.S. EPA), 

found that causes of observed failures occurring in the years of 2000-2009, regardless of 

country (e.g., North American, South American, European, Asian, African, and 

Australian), were unusual weather, management, seepage, instability, and defect, in 

13
order of decreasing percentage contribution. Weather causes were observed to have 

increased by 15% from pre-2000 failures and management issues by 20%. Azam and Li 

(Azam and Li 2010) report that failures in all but Europe and Asia have decreased since 

2000; this is attributed to improved engineering practices, with none from 2000-2009 

being due to subsidence of the foundation or to overtopping. Additionally, seismic 

liquefaction was not a causal mechanism in failures between 2000 and 2009, but 

accounted for 14% of failures prior to 2000. Data presented indicate that failures 

peaked to about 50 per decade in the 1960’s through the 1980’s and has dropped to 

about 20 per decade over the last 20 years, with the frequency of failure occurrences 

shifting to developing countries. The authors also estimate that, on average, one fifth of 

the stored tailings are released resulting from tailings dam failure. Dalpatram 

(Dalpatram 2011) presented a slide at a recent Workshop on Dam Break Analysis that 

indicated volumes released range from 20-40% of the stored tailings.

Reports of failures generally discuss physical failures causing a large release of tailings 

and/or water, but failure in design, construction, monitoring, and/or maintenance of the 

entire TSF system could result in slow release of contaminants into surface water or 

groundwater. Additionally, releases could result from compromise to the cover over 

PAG material or from inaccurate prediction of acid-generation potential for storage of 

PAG versus NAG tailings.

3. PIT

Following open-pit mining, a wide and deep hole remains that typically is filled in (or fills 

naturally) with water to form a pit lake. The source of environmental influence from 

pits and resultant lakes includes their size and the potential for acid-rock drainage (ARD) 

from dissolution of sulfidic minerals exposed on pit walls. Contaminated water may 

seep into groundwater, overflow into surface water, or adversely affect waterfowl 

landing in the formed pit lake. Additionally, the steep pit slopes generally remain after 

closure and continue to pose a risk to wildlife from falling into the pit and not being able 

to get out. Mitigation methods chosen will depend on site-specific considerations, as 

well as the future use envisioned for the pit (McCullough 2011). 

3.1 CONVENTIONAL PRACTICES

3.1.1 Operational Phase

During the operational phase, pit walls are monitored closely for signs of weakness that 

might lead to a failure. Suggested means for reducing operational hazards from a slope 

failure in a pit include “1) safe geotechnical designs; 2) secondary supports or rock fall 

catchment systems; 3) monitoring devices for adequate advance warning of impending 

failures; and 4) proper and sufficient scaling of loose/dangerous material from 

14
highwalls” (Girard 2001). Typically, water is pumped or drained out of the pit to allow 

safe access as well as to expose material being mined.

3.1.2 Closure and Post-Closure

At closure, pits may be used as a repository for waste rock, followed by sealing of the 

area against air and water exposure, such as by an isolation cover, to minimize the 

potential for generation of acidity. Partial backfilling and regrading of upper levels with 

subsequent vegetation and/or creation of wetlands provides for passive water 

treatment. Most commonly, pits naturally fill with water over time, from groundwater, 

surface water, and precipitation inflows. Filling may be accelerated by pumping water 

from the TSF or other storage ponds both to minimize exposure of any PAG rock wall 

materials and PAG waste rock and/or tailings disposed into the pit at closure to oxygen, 

and to balance high pore water pressures to help prevent slope failures. Once the 

desired water level is achieved to retain the pit lake as a sink, water can be directed 

away from entering the pit through diversions that were used during the operational 

phase, or pit water can be pumped and treated prior to discharge to a surface water 

body. 

Because the pit walls contain mineralized rock that has been exposed during the mining 

period, and during the period over which the pit lake forms, pit lake water can become 

acidic and/or contain metals and metalloids from natural geochemical processes. If 

acidity is anticipated from pit walls, mitigation measures to control for acid generation 

(e.g., sealing the rock against oxidation) and/or for ensuring that any such acidic or 

metal/metalloid-laden water would not migrate to surface or groundwater must be 

considered. 

Water quality modeling can assist in identifying if a pit lake will become acidic and/or 

accumulate metals and metalloids. The three basic processes of importance and 

considered in modeling include the chemical loading by water sources flowing into the 

pit; loading from the rock walls, benches, and fractures behind the walls, and the 

geochemistry of the water during the time it has been in the pit (Morin and Hutt, 2001). 

Factors important in these processes include the time of exposure of a surface to both 

oxygen and water, and the surface area of reactive materials exposed. During mining, 

oxidized pit wall surfaces are washed with precipitation and that water is pumped out of 

the pit, but not all surfaces are reached by precipitation (e.g., fractures behind walls) 

and may have years of accumulation of oxidized minerals that will release acid and/or 

metals/metalloids into the pit lake once exposed to water. Although not the only issue, 

one inherent difficulty in prediction is that it is difficult to measure or estimate 

percentages of surface areas that are flushed regularly, intermittently, or never during 

the operational phase of mining for use in modeling anticipated pit water chemistry 

(Morin, 1994). Nonetheless, modeling is useful in planning for closure and post-closure 

of the pit.

15
If production of acidity and contaminant ions are anticipated, and exposed surfaces 

cannot be covered or sealed against oxidation, chemicals may be added to the pit lake 

to neutralize acidity and precipitate metals. Organic material and microorganisms may 

be added and conditions optimized for sulfate-reducing bacteria (SRB) to allow for 

formation of insoluble metal sulfides in the anaerobic regions of the lake. If pit water 

becomes contaminated, treatment of any water leaving the pit would be necessary to 

meet applicable water quality standards prior to any discharge.

Barriers, such as fences, berms, or other structures, are constructed to mitigate 

unauthorized access by humans and access by wildlife and should be monitored and 

maintained regularly for stability.

4. UNDERGROUND MINE WORKINGS

The sources of potential environmental influences from underground mining are similar 

to those for open pit mining, i.e., waste rock piles, tailings, dust, and wastewater. An 

additional source of potential impact to both groundwater and surface water is from 

acid rock drainage from tunnels and adits created during mining. Depending on many 

factors, including the depth of the underground mine to the surface and the strength of 

the overburden rock, mine workings have the potential to subside and may create a 

depression in the landscape and alterations in surface and ground water flows. 

4.1 CONVENTIONAL PRACTICES

The mitigation measures to prevent potential significant environmental impacts from 

wastes originating from underground mining are similar to those for open pit mining. In 

addition, waste rock and or tailings may be disposed in mined out tunnels, which may 

assist in minimizing impacts from subsidence. Additionally, void-filling grout may be 

used to mitigate subsidence. In regions where there is potential for ground water 

interaction with mine workings, cracks may be sealed with grouting or other material. 

Additionally, groundwater flow paths may be intercepted (such as by grouting of faults 

and sheer zones, or by a grout curtain) and thus redirected to avoid the mined out area, 

minimizing contact of the water with potentially acid-generating rock surfaces (e.g., 

(Wireman and Stover 2011)). In some cases, the mine workings are flooded, which, if 

done prior to oxidation occurring on PAG surfaces and kept anaerobic, will minimize the 

formation of acidic drainage. 

5.0 DUST

Mining activities can generate dust during multiple stages in the operational phase, 

including those generated during construction of roads, trucking of materials, and heavy 

equipment exhaust. Fugitive dusts are diffuse and generated through wind erosion of 

16
large areas, including waste rock piles, tailings, the pit, and other disturbed areas. Other 

dusts originate at locations where processes are occurring, such as blasting, crushing, 

grinding, and milling. Dusts containing metals from mining activity pose human health 

concerns through inhalation. The particles are carried by the wind and may cause 

environmental concerns through sedimentation in water bodies and/or by being 

transported further downstream. 

5.1 CONVENTIONAL PRACTICES

Mitigation of dust from processing points within mining operations can include 

collection by dry collectors, wet scrubbers, enclosures at the source, and/or wetting of 

surfaces (Commonwealth of Australia 1998). A cover on a truck bed can minimize dusts 

originating from materials being hauled. Wetting of surfaces is most useful for active 

blasting, haul roads, and material movement and placement activities, and may involve 

the use of water or water mixed with a chemical dust suppressant. Typically, dust from 

waste rock piles is controlled by wetting during the operational phase. During closure, 

waste rock piles are covered and vegetated; this can be done as piles are completed 

during the operational phase to minimize potential for dust production. Although wet 

slurry tailings do not pose a dust issue, dust from large dry beaches of tailings facilities is 

a concern, and wetting or using special products to stabilize the surfaces is used for 

temporary wind erosion and dust control. Tailings beaches are covered with gravel (or 

other material) and may be vegetated during closure. 

6. STORM AND WASTEWATER

Storm and wastewater have the potential to contain suspended sediment and 

particulate and dissolved contaminants that could contaminant water bodies if they 

were to leave the site untreated. The main environmental influences originate from 

seepage of contaminants into groundwater, leakage through barriers (e.g., tailings 

embankment), and flooding or washout into nearby surface water bodies. 

6.1 CONVENTIONAL PRACTICES

Mitigation of stormwater begins with designing components using an accurate site 

water balance to assure adequate storage and treatment capacity. Conventionally, 

runoff and seepage are diverted through ditches and diversion channels to a treatment 

pond, or to a settling pond if the water source is solely from precipitation. Water from 

settling ponds can be decanted and discharged (if it meets required water quality 

criteria), or used in the mining process if of sufficient quality. Spillway diversions 

commonly are constructed around waste rock and tailings facilities to provide 

catchments for precipitation runoff. Excess water in tailings ponds is controlled through 

removal and treatment for use in the mining processes or discharge to the surface 

water. Traditionally, water in TSF ponds is drained as completely as possible prior to 

17
closure to minimize potential for overtopping due to precipitation. For TSF ponds 

containing sub-aqueously disposed PAG tailings, sufficient water would remain in the 

pond post-closure to ensure they remain isolated from oxygen. 

Stormwater from undisturbed areas may require treatment only for sediment, which is 

accomplished through simple settling in a sedimentation pond. Stormwater from 

disturbed areas and mining wastewater is treated via either active or passive methods 

prior to being used in the mining process or released into a water body. Active 

treatment of wastewater generally involves a chemical addition (e.g., lime, alum, iron 

oxides) to precipitate and/or adsorb metals and metalloids followed by dewatering of 

the precipitated solid and disposal; and/or a physical process (e.g., reverse osmosis, 

filtration, microfiltration). Operating mines generally have high volumes of water 

needing treatment prior to discharge to a surface water body and thus rely on active 

treatment methods. Active treatments also include microbial methods, such as the use 

of contained bioreactors, but these generally require lower flows and are options for 

post-closure or co-treatment during operations. Passive treatments are those that 

capitalize on natural processes and do not require constant reagent addition for 

operation. Wetlands are an example of a commonly used passive treatment system for 

water contaminants, as are anaerobic biochemical reactors (also called sulfate-reducing 

bioreactors). Passive treatment options are most commonly used post-closure, 

although they can be used during the operational phase for other purposes. For 

example, a biochemical reactor could be used to treat contaminants present in brine 

from reverse osmosis treatment. Passive treatment technologies generally require large 

land areas and low flows to allow sufficient time for biological processes to convert 

them to non-toxic forms. Additional passive and active treatment options for potential 

use post-closure can be found in U.S. EPA (2006).

7. CHEMICALS

Chemicals used at mining sites have the potential to enter into the environment through 

accidental spills during transport, storage, and/or use, or from excess usage in processes 

to recover metals being mined (e.g., during flotation/frothing, cyanidation, or smelting).

7.1 CONVENTIONAL PRACTICES

Conventional practices include having a chemical hygiene plan and training of all 

personnel in the proper handling of chemicals, including how to deal with cleanup of 

spills, provision of spill kits and personal protective equipment, and availability of MSDS 

for consultation (e.g., see (Logsdon et al. 1999)). Secondary containment (dikes or 

collection basins) must be used and incompatible chemicals must be isolated from one 

another during storage and use. Storage containers are commonly equipped with 

indicators and instrumentation to monitor levels in tanks to ensure that a spill does not 

occur, or that any spill/leak is captures quickly when it begins.

18
8. PIPELINES

A slurry-concentrate pipeline break or spill has potential to affect aquatic life adversely, 

if into a nearby stream. Additionally, placement of pipelines results in land disturbance 

and can cause soil/sediment to enter streams through runoff.

8.1 CONVENTIONAL PRACTICES

Pipelines that might be necessary for mining operations include those for transport of 

slurry, return water, and fuel for the mining site. Standard practices for construction, 

operation, and monitoring of slurry pipelines are available from the American Society of 

Mechanical Engineers (American Society of Mechanical Engineers (ASME) 2003). 

Mitigation measures for pipelines include using the proper pipe material, protection 

against leaks, breaks, and corrosion, containment drains or sumps along the corridor, 

and secondary containment of the pipeline where crossing a river or transportation 

route. Protection includes increased wall thickness, corrosion inhibitors, and internal 

linings or coatings. Joints, welds, valves, etc. are designed to accommodate expected 

stress, as based on flows desired for the pipeline. Pipelines may be equipped with 

monitoring systems to detect flow, temperature, or pressure changes, along with alarms 

and automatic shutoffs. Pipelines are stress-tested for leaks and weaknesses prior to 

being placed into operation; and they require routine inspections over the course of 

their use. Mitigation of construction impacts, such as soil erosion and turbid storm 

water runoff caused by pipe installation (e.g., excavation and boring), can include silt 

fences, ditches, or other temporary diversions. Pipelines that are constructed near 

water bodies require containment and may or may not be placed above ground on 

bridge structures.

9. NON-MINING MATERIAL AND DOMESTIC WASTE

Mining operations produce a number of wastes in addition to waste mineral materials. 

Additionally, there is domestic waste produced from persons employed. These wastes 

have the potential to attract wildlife (food wastes), or to contaminate water bodies 

(e.g., sewage waste) and thus must be managed.

9.1 NON-MINING MATERIAL AND DOMESTIC WASTE

At remote mining sites, non-hazardous wastes generally are managed on site. Nonhazardous solid wastes typically would be disposed in engineered solid waste landfills 

that meet regulatory requirements. For some types of wastes, and in some locations, 

incineration may be an acceptable alternative. Recycling of segregated wastes such as 

19
paper and plastic may be preferable, but high transportation costs could make this 

option economically unattractive.

Sanitary waste often is treated via a decentralized system (e.g., septic tank) or in a 

packaged sewage treatment plant, with the effluent discharged after verification that it 

meets the permitted discharge standards. Sewage sludge may be land-farmed, hauled 

to a licensed treatment facility, or land filled on site depending on local requirements. 

 

20
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24
AN ASSESSMENT OF POTENTIAL MINING IMPACTS ON 

SALMON ECOSYSTEMS OF BRISTOL BAY, ALASKA 

VOLUME 3—APPENDICES E-J

Appendix J: Compensatory Mitigation and Large-Scale 

Hardrock Mining in the Bristol Bay Watershed 
December 2013 

 

Appendix J 

Compensatory Mitigation and 

Large-Scale Hardrock Mining in the Bristol Bay 

Watershed 

Palmer Hough

U.S. Environmental Protection Agency

Office of Water

Office of Wetlands, Oceans and Watersheds

Heather Dean

U.S. Environmental Protection Agency

Region 10

Alaska Operations Office

Joseph Ebersole

U.S. Environmental Protection Agency

Office of Research and Development

Western Ecology Division

Rachel Fertik

U.S. Environmental Protection Agency

Office of Water

Office of Wetlands, Oceans and Watersheds
Table of Contents 

1 Overview of Clean Water Act Section 404 Compensatory Mitigation Requirements........... 2

1.1 Compensatory Mitigation Methods........................................................................................... 3 

1.2 Compensatory Mitigation Mechanisms.................................................................................... 4 

1.3 Location, Type, and Amount of Compensation........................................................................ 4 

1.4 Compensatory Mitigation Guidance for Alaska....................................................................... 6 

2 Compensatory Mitigation Considerations for the Bristol Bay Assessment............................. 7 

2.1 Important Ecological Functions and Services Provided by Affected Streams and 

Wetlands.............................................................................................................................................. 7 

2.2 Identifying the Appropriate Watershed Scale for Compensatory Mitigation..................... 9 

3 Potential Compensatory Mitigation Measures in Bristol Bay................................................... 11

3.1 Mitigation Bank Credits............................................................................................................... 11

3.2 In-Lieu Fee Program Credits........................................................................................................ 13

3.3 Permittee-Responsible Compensatory Mitigation.................................................................. 13

3.3.1 Opportunities within the NFK, SFK, and UTC Watersheds............................................... 13

3.3.1.1 Increase Habitat Connectivity........................................................................................ 14 

3.3.1.1.1 Remove Beaver Dams.............................................................................................. 15

3.3.1.1.2 Connect Off-channel Habitats and Habitat Above Impassible Waterfalls....... 16 

3.3.1.2 Increase Habitat Quality................................................................................................. 19 

3.3.1.3 Increase Habitat Quantity.............................................................................................. 21

3.3.1.4 Manage Water Quantity................................................................................................. 23

3.3.1.4.1 Direct Excess On-site Water.................................................................................... 23

3.3.1.4.2 Augment Flows.......................................................................................................... 25 

3.3.1.4.3 Pump Water Upstream............................................................................................ 26

3.3.1.5 Manipulate Water Quality............................................................................................. 27 

3.3.1.5.1 Increase Levels of Alkalinity, Hardness, and Total Dissolved Solids.................. 27

3.3.1.5.2 Increase Levels of Nitrogen and/or Phosphorus.................................................. 29

3.3.1.6 Preserve Aquatic Resources........................................................................................... 33

3.3.2 Other Opportunities within the Nushagak and Kvichak River Watersheds................... 33

3.3.2.1 Remediate Old Mine Sites.............................................................................................. 33

3.3.2.2 Remove Roads................................................................................................................. 34

3.3.2.3 Retrofit Road Stream Crossings.................................................................................... 34

3.3.2.4 Construct Hatcheries...................................................................................................... 35

3.3.2.5 Stock Fish.......................................................................................................................... 36 

3.4 Other Suggested Compensation Measures.............................................................................. 36

4 Effectiveness of Compensation Measures at Offsetting Impacts to Salmonids.................... 37

5 Conclusions......................................................................................................................................... 38

6 References........................................................................................................................................... 39

1 
This appendix provides an overview of Clean Water Act Section 404 compensatory 

mitigation requirements for unavoidable impacts to aquatic resources, and discusses an 

array of measures that various entities have proposed as having the potential to 

compensate for the unavoidable impacts to wetlands, streams, and fish identified in the 

Bristol Bay Assessment. Please note that any formal determinations regarding 

compensatory mitigation can only take place in the context of a regulatory action. The 

Bristol Bay Assessment is not a regulatory action, and thus a complete evaluation of 

compensatory mitigation is outside the scope of the assessment.

1. Overview of Clean Water Act Section 404 Compensatory Mitigation 

Requirements

The overall objective of the Clean Water Act is to restore and maintain the chemical, 

physical and biological integrity of the nation’s waters. To help achieve that objective, 

Section 404 of the Clean Water Act establishes a program to regulate the discharge of 

dredged or fill material into waters of the United States, including wetlands. Section 

404 requires a permit before dredged or fill material may be discharged into waters of 

the United States, unless the activity is exempt from Section 404 regulation (e.g. certain 

farming and forestry activities). 

The U.S. Environmental Protection Agency (EPA) and the Department of the Army, 

operating through the Army Corps of Engineers (ACOE), share responsibilities for 

implementing the Section 404 program. Section 404(a) authorizes the ACOE to issue 

permits for the discharge of dredged or fill material into waters of the U.S. at specified 

disposal sites. Section 404(b) directs the ACOE to apply environmental criteria 

developed by EPA in making its permit decisions (these criteria are binding regulations 

known as the “Section 404(b)(1) Guidelines” (40 CFR Part 230)). Under EPA’s Section 

404(b)(1) Guidelines, no discharge of dredged or fill material may be permitted by the 

ACOE if: (1) a practicable alternative exists that is less damaging to the aquatic 

environment so long as that alternative does not have other significant adverse 

environmental consequences or (2) the nation’s waters would be significantly degraded. 

Under the Guidelines, a project must incorporate all appropriate and practicable 

measures to first avoid impacts to wetlands, streams, and other aquatic resources and 

then minimize unavoidable impacts; after avoidance and minimization measures have 

been applied, the project must include appropriate and practicable compensatory 

mitigation for the remaining unavoidable impacts.

Compensatory mitigation refers to the restoration, establishment, enhancement, and/or

preservation of wetlands, streams, or other aquatic resources conducted specifically for 

the purpose of offsetting authorized impacts to these resources (Hough and Robertson 

2009). Compensatory mitigation regulations jointly promulgated by EPA and the ACOE

(40 CFR §§ 230.91 - 230.98 and 33 CFR §§ 332.1 - 332.8) state that “the fundamental 

2 
objective of compensatory mitigation is to offset environmental losses resulting from 

unavoidable impacts to waters of the United States authorized by [Clean Water Act 

Section 404 permits issued by the ACOE]” (40 CFR Part 230.93(a)(1)). Compensatory 

mitigation enters the analysis only after a proposed project has incorporated all 

appropriate and practicable means to avoid and minimize adverse impacts to aquatic 

resources (40 CFR Part 230.91(c)). 

Section 404 permitting requirements for compensatory mitigation are based on what is 

“practicable and capable of compensating for the aquatic resource functions that will be 

lost as a result of the permitted activity” (40 CFR Part 230.93(a)(1)). In determining 

what type of compensatory mitigation will be “environmentally preferable,” the ACOE

“must assess the likelihood for ecological success and sustainability, the location of the 

compensation site relative to the impact site and their significance within the 

watershed, and the costs of the compensatory mitigation project”(40 CFR Part 

230.93(a)(1)). Furthermore, compensatory mitigation requirements must be 

commensurate with the amount and type of impact associated with a particular Section 

404 permit (40 CFR Part 230.93(a)(1)). The regulations recognize that there may be 

instances when the ACOE cannot issue a permit “because of the lack of appropriate and 

practicable compensatory mitigation options” (40 CFR Part 230.91(c)(3)).

 

1.1 Compensatory Mitigation Methods

Compensatory mitigation can occur through four methods: aquatic resource 

restoration, establishment, enhancement, or in certain circumstances, preservation (40 

CFR Part 230.93(a)(2)). 

• Restoration is the reestablishment or rehabilitation of a wetland, stream, or 

other aquatic resource with the goal of returning natural or historic functions 

and characteristics to a former or degraded aquatic resource. When it is an 

option, restoration is generally the preferred method, due in part to its higher 

likelihood of success as measured by gain in aquatic resource function, area, or 

both. 

• Establishment, or creation, is the development of a wetland or other aquatic 

resource where one did not exist previously, with success measured as a net gain 

in both area and function of the aquatic resource. 

• Enhancement includes activities conducted within existing aquatic resources that 

heighten, intensify, or improve one or more aquatic resource functions, without 

increasing the area of the aquatic resource. Examples include improved 

floodwater retention or wildlife habitat. 

• Preservation is the permanent protection of aquatic resources and/or upland 

buffers or riparian areas through legal and physical mechanisms, such as 

conservation easements and title transfers. Because preservation does not 

replace lost aquatic resource area or functions, regulations limit its use to 

situations in which the resources to be preserved provide important functions 

for and contribute significantly to the ecological sustainability of the watershed, 

3 
and those resources are under threat of destruction or adverse modification (40 

CFR Part 230.93(h)).

 

1.2 Compensatory Mitigation Mechanisms

There are three general mechanisms for achieving the four methods of compensatory 

mitigation (listed in order of preference as established in 40 CFR 230.93(b)): mitigation 

banks, in-lieu fee programs, and permittee-responsible mitigation. 

• A mitigation bank is a site with restored, established, enhanced, or preserved 

aquatic resources, riparian areas and/or upland buffers that the ACOE has 

approved for use to compensate for losses from future permitted activities. The 

bank approval process establishes the number of available compensation credits, 

which permittees may purchase upon ACOE approval that the bank represents 

appropriate compensation. The bank sponsor is responsible for the success of 

these mitigation sites. 

• For in-lieu fee mitigation, a permittee provides funds to an in-lieu fee program 

sponsor who conducts compensatory mitigation projects according to the 

compensation planning framework approved by ACOE. Typically specific 

compensatory mitigation projects are started only after pooling funds from 

multiple permittees. The in-lieu fee program sponsor is responsible for the 

success of these mitigation sites. 

• In permittee-responsible mitigation, the permittee undertakes and bears full 

responsibility for the implementation and success of the mitigation. Mitigation 

may occur either at the site where the regulated activity caused the loss of 

aquatic resources (on-site) or at a different location (off-site), preferably within 

the same watershed.

Although it is the permit applicant’s responsibility to propose an appropriate 

compensatory mitigation option, mitigation banks and in-lieu fee programs are the 

federal government’s preferred forms of compensatory mitigation as they “usually 

involve consolidating compensatory mitigation projects where ecologically appropriate, 

consolidating resources, providing financial planning and scientific expertise (which 

often is not practical for permittee-responsible compensatory mitigation projects), 

reducing temporal losses of functions, and reducing uncertainty over project success”

(40 CFR 230.93(a)(1); see also 40 CFR 230.93(b)). 

1.3 Location, Type, and Amount of Compensation

Regulations regarding compensatory mitigation require the use of a watershed 

approach to “establish compensatory mitigation requirements in [Department of the 

Army] permits to the extent appropriate and practicable” (40 CFR 230.93(c)(1)). Under 

these regulations, the watershed approach to compensatory mitigation site selection 

and planning is an analytical process for making compensatory mitigation decisions that 

support the sustainability or improvement of aquatic resources in a watershed. It 

4 
involves consideration of watershed needs and how locations and types of 

compensatory mitigation projects address those needs (40 CFR 230.92). The regulations

specifically state that compensatory mitigation generally should occur within the same 

watershed as the impact site and in a location where it is most likely to successfully 

replace lost functions and services (40 CFR 230.93(b)(1)). The goal of this watershed 

approach is to “maintain and improve the quality and quantity of aquatic resources 

within watersheds through strategic selection of compensatory mitigation sites” (40 CFR 

230.93(c)(1)). 

The regulations emphasize using existing watershed plans to inform compensatory 

mitigation decisions, when such plans are determined to be appropriate for use in this 

context (40 CFR 230.93(c)(1)). Watershed plans that could support compensatory 

mitigation decision-making are typically:

 

“...developed by federal, tribal, state, and/or local government agencies or 

appropriate non-governmental organizations, in consultation with relevant 

stakeholders, for the specific goal of aquatic resource restoration, establishment, 

enhancement and preservation. A watershed plan addresses aquatic resource 

conditions in the watershed, multiple stakeholder interests, and land uses. 

Watershed plans may also identify priority sites for aquatic resource restoration 

and protection” (40 CFR 230.92). 

Where appropriate plans do not exist, the regulations describe the types of 

considerations and information that should be used to support a watershed approach to 

compensation decision-making. Central to the watershed approach is consideration of

how the types and locations of potential compensatory mitigation projects would 

sustain aquatic resource functions in the watershed. To achieve that goal, the 

regulations emphasize that mitigation projects should, where practicable, replace the 

suite of functions typically provided by the affected aquatic resource, rather than focus 

on specific individual functions (40 CFR 230.93(c)(2)). For this purpose, “watershed” 

means an “area that drains to a common waterway, such as a stream, lake, estuary, 

wetland, or ultimately the ocean” (40 CFR 230.92). Although there is flexibility in 

defining geographic scale, the watershed “should not be larger than is appropriate to 

ensure that the aquatic resources provided through compensation activities will 

effectively compensate for adverse environmental impacts resulting from [permitted] 

activities” (40 CFR 230.93(c)(4)).

With regard to type, in-kind mitigation (i.e., involving resources similar to those being 

impacted) is generally preferable to out-of-kind mitigation, because it is most likely to 

compensate for functions lost at the impact site (40 CFR 230.93(e)(1)). Furthermore, 

the regulations recognize that, for difficult-to-replace resources such as bogs, fens, 

springs, and streams, in-kind “rehabilitation, enhancement, or preservation” should be 

the compensation of choice, given the greater likelihood of success of those types of 

mitigation (40 CFR 230.93(e)(3)). 

5 
The amount of compensatory mitigation required must be, to the extent practicable,

“sufficient to replace lost aquatic resource functions” (40 CFR 230.93(f)(1)), as 

determined through the use of a functional or condition assessment. If an applicable 

assessment methodology is not available, the regulations require a minimum one-toone acreage or linear foot compensation ratio (40 CFR 230.93(f)(1)). Certain 

circumstances require higher ratios, even in the absence of an assessment methodology

(e.g., use of preservation, lower likelihood of success, differences in functionality 

between the impact site and compensation project, difficulty of restoring lost functions, 

and the distance between the impact and compensation sites) (40 CFR 230.93(f)(2)). 

1.4 Compensatory Mitigation Guidance for Alaska

In addition to the federal regulations regarding compensatory mitigation, the agencies 

have also developed compensatory mitigation guidance applicable specifically to Alaska. 

In their 1994 Alaska Wetlands Initiative Summary Report, EPA and the Department of 

the Army concluded that it was not necessary to provide “broad exemptions” from 

mitigation sequencing in Alaska, given the “inherent flexibility provided by” the 

regulations and associated guidance. The agencies also recognized that “it may not 

always be practicable to provide compensatory mitigation through wetlands restoration 

or creation in areas where there is a high proportion of land which is wetlands. In cases 

where potential compensatory mitigation sites are not available due to the abundance 

of wetlands in a region and lack of enhancement or restoration sites, compensatory 

mitigation is not required under the [Section 404(b)(1)] Guidelines” (EPA et al., 1994). In 

promulgating the compensatory mitigation regulations in 2008, EPA and the ACOE

specifically referenced the 1994 policy and reiterated the flexibility and discretion 

available to decision-makers (e.g., 40 CFR 230.91(a)(1), 40 CFR 230.93(a)(1)).

Although opportunities for wetland restoration and creation continue to be rather 

limited in Alaska, a number of other wetland compensatory mitigation options (e.g., 

mitigation banks, in-lieu fee programs) have become available since 1994. Moreover, it 

is important to note that the 1994 policy applies only to compensatory mitigation for 

impacts to wetlands and does not address compensatory mitigation for impacts to 

Alaska streams. Furthermore, subsequent guidance issued by the ACOE Alaska District

in 2009 clarifies that fill placed in streams or in wetlands adjacent to anadromous fish 

streams in Alaska will require compensatory mitigation (ACOE 2009). A 2011 

supplement to the Alaska District’s 2009 guidance further recommends that projects in 

“difficult to replace” wetlands, fish-bearing waters, or wetlands within 500 feet of such 

waters will also likely require compensatory mitigation, as will “large scale projects with 

significant aquatic resource impacts,” such as “mining development” (ACOE 2011).

The ACOE’s 2009 Alaska guidance also provides sample compensatory mitigation ratios 

based on the type of mitigation and the ecological value of the impacted resource (high, 

moderate, or low). These guidelines include streams in the high quality category, 

6 
indicating compensation ratios of 2:1 for restoration and/or enhancement and 3:1 for 

preservation (ACOE 2009). 

2. Compensatory Mitigation Considerations for the Bristol Bay 

Assessment 

2.1 Important Ecological Functions and Services Provided by Affected Streams and 

Wetlands 

Bristol Bay’s stream and wetland resources support a world-class commercial and sport 

fishery for Pacific salmon and other important fish. They have also supported a salmonbased culture and subsistence-based lifestyle for Alaska Natives in the watershed for at 

least 4,000 years. Bristol Bay’s streams and wetlands support production of 35 species 

of fish including all five species of Pacific salmon found in North America: sockeye 

(Oncorhynchus nerka), coho (O. kisutch), Chinook or king (O. tshawytscha), chum (O. 

keta), and pink (O. gorbuscha). Because no hatchery fish are raised or released in the 

watershed, Bristol Bay’s salmon populations are entirely wild. These fish are 

anadromous, hatching and rearing in freshwater systems, migrating to the sea to grow 

to adult size, and returning to freshwater systems to spawn and die. 

In the Bristol Bay region, hydrologically-diverse riverine and wetland landscapes provide 

a variety of salmon spawning and rearing habitats. Environmental conditions can be 

very different among habitats in close proximity, with ponds, lakes and streams 

expressing very different flow, temperature, and physical habitat characteristics at very 

fine spatial scales (see Chapter 7 of the assessment for additional discussion). Recent 

research has highlighted the potential for local adaptations and fine-scale population 

structuring in Bristol Bay and neighboring watersheds associated with this 

environmental template (Quinn et al. 2001, Olsen et al. 2003, Ramstad et al. 2010, 

Quinn et al. 2012). For example, sockeye salmon that use spring-fed ponds and streams 

located approximately 1 km apart exhibit differences in traits such as spawn timing, 

spawn site fidelity, and productivity consistent with discrete populations (Quinn et al. 

2012). Bristol Bay’s streams and wetlands support a diverse array of salmon 

populations that are unique to specific drainages within the Bay and this population 

diversity is key to the stability of the overall Bristol Bay salmon fishery (i.e., the portfolio 

effect) (Schindler et al. 2010). 

As discussed in detail in the Bristol Bay Assessment (see Chapter 7), streams and 

wetlands that would be lost as a result of the mine footprints described in the 

assessment’s scenarios provide important ecological functions. These headwater 

streams provide spawning habitat for coho and sockeye salmon and likely spawning 

habitat for anadromous and resident forms of Dolly Varden. Headwater streams and 

associated wetlands also provide rearing habitat for chum salmon, sockeye salmon, 

Chinook salmon, coho salmon, Dolly Varden, rainbow trout, Arctic grayling, slimy 

7 
sculpin, northern pike, and ninespine stickleback (Johnson and Blanche 2012, ADFG 

2012a). Headwater streams and associated wetlands are often exploited by fish for 

spawning and rearing because they can provide refuge from predators and competitors 

that are more abundant downstream (Quinn 2005). Off-channel wetlands with their 

unique low-velocity, depositional environments and variable thermal conditions provide 

additional options for juvenile salmon feeding and rearing. For example, ephemeral 

swamps provided important thermal and hydraulic refuge for coho salmon in a coastal 

British Columbia stream (Brown and Hartman 1988). Off-channel ponds provided highly 

productive foraging environments and enhanced overwinter growth of coho salmon in 

an interior British Columbia stream (Swales and Levings 1989). 

It has long been recognized that in addition to providing habitat for stream fishes, 

headwater streams and wetlands serve an important role in the stream network by 

contributing nutrients, water, organic material, algae, bacteria and macroinvertebrates 

downstream, to higher order streams in the watershed (Vannote et al. 1980, Meyer et 

al. 2007). But only recently have specific subsidies from headwater systems been 

extensively quantified (Wipfli and Baxter 2010). The contributions of headwaters to 

downstream systems results from their high density in the dendritic stream network. 

Headwater streams also have high rates of instream nutrient processing and storage, 

thereby determining downstream water chemistry due to relatively large organic matter 

inputs, high retention capacity, high primary productively, bacteria-induced 

decomposition, and extensive hyporheic zone interactions (Richardson et al. 2005, 

Alexander et al. 2007, Meyer et al. 2007). Because of their crucial influence on 

downstream water flow, chemistry, and biota, impacts to headwaters reverberate 

throughout entire watersheds downstream (Freeman et al. 2007, Meyer et al. 2007). 

The majority of streams directly in the footprint of the mine scenarios are classified as 

small headwater streams (less than 0.15 m3/s mean annual streamflow) (see 

assessment Table 7-6). Because of their narrow width, headwater streams receive 

proportionally larger inputs of organic material than do larger stream channels (Vannote 

et al. 1980). This material is either used in the headwater environment (Tank et al. 

2010) or transported downstream as a subsidy to larger streams in the network (Wipfli 

et al. 2007). Consumers in headwater stream food webs, such as invertebrates, juvenile 

salmon, and other fishes rely heavily on the terrestrial inputs that enter the stream 

(Doucett et al. 1996, Eberle and Stanford 2010, Dekar et al. 2012). Headwater streams 

also encompass the upper limits of anadromous fish distribution, and may receive none, 

or lower quantities of marine-derived nutrients (MDN) from spawning salmon relative 

to downstream portions of the river network, making terrestrial nutrient sources 

relatively more important (Wipfli and Baxter 2010). 

Both invertebrates and detritus are exported from headwaters to downstream reaches 

and provide an important energy subsidy for juvenile salmonids (Wipfli and Gregovich 

2002, Meyer et al. 2007). Headwater wetlands and associated wetland vegetation can 

also be important sources of dissolved and particulate organic matter, and 

8 
macroinvertebrate diversity (King et al. 2012), contributing to the chemical, physical, 

and biological condition of downstream waters (Shaftel et al. 2011a, Shaftel et al. 

2011b, Dekar et al. 2012, Walker et al. 2012). Thus, losses of headwater streams and 

wetlands due to the mine scenario footprints would not only eliminate important fish 

habitat but also reduce inputs of organic material, nutrients, water, primary producers, 

bacteria, and macroinvertebrates to reaches downstream of the mine scenario

footprints. 

2.2 Identifying the Appropriate Watershed Scale for Compensatory Mitigation

As previously noted, the regulations regarding compensatory mitigation specifically 

state that compensatory mitigation generally should occur within the same watershed 

as the impact site and in a location where it is most likely to successfully replace lost 

functions and services (40 CFR 230.93(b)(1)).

For the mine scenarios evaluated in the Bristol Bay Assessment, the lost functions and 

services occur in the watersheds that drain to the North Fork Koktuli (NFK) and South 

Fork Koktuli (SFK) Rivers and Upper Talarik Creek (UTC) (see Figure 1). Accordingly, the 

most appropriate geographic scale at which to compensate for any unavoidable impacts 

resulting from such a project would be within these same watersheds, as this location 

would offer the greatest likelihood that compensation measures would replace the 

“suite of functions typically provided by the affected aquatic resource” (40 CFR 

230.93(c)(2), Yocom and Bernard 2013). An important consideration is that salmon 

populations in these watersheds may possess unique adaptations to local 

environmental conditions, as suggested by recent research in the region (Quinn et al. 

2001, Olsen et al. 2003, Ramstad et al. 2010, Quinn et al. 2012). Accordingly, 

maintenance of local biocomplexity (i.e., salmon genetic, behavioral, and phenotypic 

variation) and the environmental template upon which biocomplexity develops will be 

important for sustaining resilience of these populations (Hilborn et al. 2003, Schindler et 

al. 2010). Thus, the most appropriate spatial scale and context for compensation would 

be within the local watersheds where impacts to salmon populations occur. 

If there are no practicable or appropriate opportunities to provide compensation in 

these watersheds, it may be appropriate to explore options in adjoining watersheds. 

However, defining the watershed scale too broadly would likely fail to ensure that 

wetland, stream, and associated fish losses under the mine scenarios would be

effectively offset, because compensation in a different watershed(s) would not address 

impacts to the portfolio effect from losses in the impacted watersheds. Similarly, 

compensation in different watersheds would not address impacts to the subsistence 

fishery where users depend on a specific temporal and spatial distribution of fish to 

ensure nutritional needs and cultural values are maintained (see Bristol Bay Assessment 

Chapter 12).

9 
Figure 1. The boundaries of the Bristol Bay watershed (brown), the Nushagak and Kvichak River watersheds (green) and the 

North Fork Koktuli, South Fork Koktuli, and Upper Talarik Creek watersheds (blue). 

10
3. Potential Compensatory Mitigation Measures in Bristol Bay

As discussed in Chapter 7 of the Bristol Bay Assessment, impact avoidance and 

minimization measures do not eliminate all of the footprint impacts associated with the 

mining scenarios. Reasons impact avoidance and minimization measures fail to 

eliminate these kinds of impacts include: the large extent and wide distribution of 

wetlands and streams in the watersheds, the fact that substantial infrastructure would 

need to be built to support porphyry copper mining in this largely undeveloped area and 

the fact that ore body location constrains siting options. The mine scenarios evaluated 

in the assessment identify that the mine footprints alone would result in the 

unavoidable loss (i.e., filling, blocking or otherwise eliminating) of hundreds to 

thousands of acres of high-functioning wetlands and tens of miles of salmon-supporting 

streams (see Figure 2). 

The public and peer review comments on the draft Bristol Bay Assessment identified an 

array of compensation measures that some commenters believed could potentially 

offset these impacts to wetlands, streams, and fish. The following discussion considers 

the likely efficacy of the complete array of compensation measures proposed by 

commenters at offsetting potential adverse effects, organized in the order that the 

regulations prescribe for considering compensation mechanisms: 

1) Mitigation bank credits; 

2) In-lieu fee program credits; and 

3) Variations of permittee-responsible mitigation.

3.1 Mitigation Bank Credits

There are currently no approved mitigation banks with service areas1

 that cover the 

impact site for the mine scenarios; thus, no mitigation bank credits are available. 

Should one or more bank sponsors pursue the establishment of mitigation bank sites to 

address the impacts associated with the mine scenarios, they would likely encounter the 

same challenges described below (Section 3.3). 

1 The service area is the watershed, ecoregion, physiographic province, and/or other geographic area 

within which the mitigation bank or in-lieu fee program is authorized to provide compensatory mitigation 

(40 CFR 230.98(d)(6)(ii)(A)).

11

 
 

12

Figure 2. Streams, wetlands and other waters lost (eliminated, blocked, or dewatered) 

in the Pebble 6.5 scenario evaluated in the Bristol Bay Assessment. 
3.2 In-Lieu Fee Program Credits

There is currently one in-lieu fee program approved to operate in the Bristol Bay 

watershed, which has been administered by The Conservation Fund (TCF) since 1994. 

The TCF program operates statewide, and the Bristol Bay watershed falls within one of 

its service areas. According to TCF, its compensation projects consist almost entirely of 

wetland preservation. To date, TCF has completed four wetland preservation projects in 

the Bristol Bay watershed, financed in part with in-lieu fee funds. Although the majority 

of in-lieu fees collected by the TCF program have been for relatively small impacts to 

aquatic resources, TCF has accepted in-lieu fees to compensate for a few projects with 

over 50 acres of impacts statewide. To date, the largest impact represented in the TCF 

program is the loss of 267 acres of wetlands associated with the development of the 

Point Thomson natural gas production/processing facilities on Alaska’s Beaufort Sea 

coast. It is not clear if this program could effectively provide the magnitude of 

compensation necessary to address the loss of hundreds to thousands of acres of high 

functioning wetlands and tens of miles of salmon-supporting streams associated with 

the mine scenarios. In addition, it is likely that any in-lieu fee sponsor seeking to 

address the impacts associated with the mine scenarios would encounter the same 

challenges described below (Section 3.3). 

3.3 Permittee-Responsible Compensatory Mitigation

 

Currently, there is no watershed plan for the NFK, SFK, or UTC, or other components of 

the Nushagak or Kvichak River drainages that could serve as a guide to permitteeresponsible compensatory mitigation. In the absence of such a plan, the regulations call 

for the use of a watershed approach that considers information on watershed 

conditions and needs, including potential sites and priorities for restoration and 

preservation (40 CFR 230.93(c)). When a watershed approach is not practicable, the 

next option is to consider on-site (i.e., on the same site as the impacts or on adjoining 

land) and in-kind compensatory mitigation for project impacts, taking into account both 

practicability and compatibility with the proposed project (40 CFR 230.93(b)(5)). When 

such measures would be impracticable, incompatible, or inadequate, the last resort 

would be off-site and/or out-of-kind mitigation opportunities (40 CFR 230.93(b)(6)).

3.3.1 Opportunities within the NFK, SFK, and UTC Watersheds

In the context of the mine scenarios, the primary challenge to both a watershed 

approach and on-site compensatory mitigation is the absence of existing degraded 

resources within the NFK, SFK and UTC watersheds. Specifically, these three watersheds 

are largely unaltered by human activities; thus, opportunities for restoration or 

enhancement are very limited, and, as discussed below, likelihood of success appears to 

be very low. 

13
Here we discuss specific suggestions for potential compensation measures within the 

NFK, SFK and UTC watersheds that were provided in the public and peer review 

comments on the Bristol Bay Assessment. 

3.3.1.1 Increase Habitat Connectivity 

Connectivity among aquatic habitats within stream networks is an important attribute 

influencing the ability of mobile aquatic taxa to utilize the diversity and extent of 

habitats within those networks. Within riverine floodplain systems, a complex array of 

habitats can develop that express varying degrees of surface and sub-surface water 

connectivity to main channels (Stanford and Ward 1993). In the study area, off-channel 

floodplain habitats can include side channels (both inlet and outlet connections to main 

channel), various types of single-connection habitats including alcoves and percolation 

channels, and pools and ponds with no surface connection to the main channel during 

certain flow conditions (PLP 2011 Appendix 15.1D). Beaver can be very important 

modifiers and creators of habitat in these off-channel systems (Pollock et al. 2003, 

Rosell et al. 2005). As a result of their morphology and variable hydrology, the degree of 

surface-water connectivity and the ability of fish to move among floodplain habitats 

changes with surface water levels. Connectivity for fish movement at larger spatial 

scales within watersheds is influenced by barriers to longitudinal movements and 

migrations. Examples include dams and waterfalls.

Efforts to manage or enhance connectivity within aquatic systems have primarily 

focused on watersheds altered by human activities, where land uses and water 

utilization have lead to aquatic habitat fragmentation. Specific activities to increase 

habitat connectivity within human-dominated stream-wetland systems may include: 1) 

improving access around real or perceived barriers to migration (including dams 

constructed by humans or beaver); 2) removing or retrofitting of road culverts; and 3) 

excavating and engineering of channels to connect isolated wetlands and ponds to main 

channels. Within watersheds minimally impacted by human activity, efforts may include 

creation of passage around barrier waterfalls to expand the availability of habitat for 

species like Pacific salmon. Human-created dams do not offer any opportunities for 

habitat improvement or expansion in the Nushagak or Kvichak River watersheds 

because they are absent, so they are not discussed further. Since road stream crossing 

retrofits presently offer no opportunities for habitat improvement or expansion within 

the NFK, SFK, and UTC watersheds, but exist elsewhere in the larger Nushagak and 

Kvichak River watersheds, they are discussed in Section 3.3.2.3. Here, we focus on 

beaver dam removal and engineered connections to variably-connected floodplain 

habitats, and habitats upstream of barrier waterfalls. For each of these measures, the 

potential applicability, suitability, and effectiveness as mitigation tools within the study 

area watersheds are addressed.

14
3.3.1.1.1 Remove Beaver Dams 

Two commenters suggested the removal of beaver dams as a potential compensation 

measure. Presumably, the rationale for this recommendation is that beaver dams can 

block fish passage, limiting fish access to otherwise suitable habitat, thus, the removal of 

beaver dams could increase the amount of available fish habitat. This rationale is based

upon early research that led to the common fish management practice of removing 

beaver dams to protect certain fish populations like trout (Sayler 1934, Reid 1952, in

Pollock et al. 2004). However, more recent research has documented numerous 

benefits of beaver ponds to fish populations and habitat (Murphy et al. 1989, Pollock et 

al. 2003). For example, Bustard and Narver (1975) found that a series of beaver ponds 

on Vancouver Island had a survival rate for overwintering juvenile coho salmon that was 

twice as high as the 35% estimated for the entire stream. Pollock et al. (2004) estimated 

a 61% reduction in summer habitat capacity relative to historical levels, for coho salmon 

in one Washington watershed, largely due to loss of beaver ponds.

Kemp et al. (2012) recently published a definitive review of the effects of beaver in 

stream systems, indicating that they have a positive impact on sockeye, coho, and 

Chinook salmon as well as Dolly Varden, rainbow trout, and steelhead. Using metaanalysis and weight-of-evidence methodology, the review showed that most (71.4%) 

negative effects cited, such as low dissolved oxygen and impediment to fish movement, 

lack supportive data and are speculative in nature, whereas the majority (51.1%) of 

positive impacts cited are quantitative in nature and well-supported by data (Kemp et al. 

2012). In addition to increased invertebrate (i.e., food) production and habitat 

heterogeneity, the study cited the importance of beaver ponds as rearing habitat due to 

the increased cover and protection that higher levels of woody material and overall 

structural diversity provide. Other studies have identified beaver ponds as excellent 

salmon rearing habitat because they have high macrophyte cover, low flow velocity, and 

increased temperatures, and they trap organic materials and nutrients (Nickelson et al. 

1992, Collen and Gibson 2001, Lang et al. 2006). DeVries et al (2012) describe a stream 

restoration approach that attempts to mimic and facilitate beaver dam creation and the 

numerous positive benefits for stream habitat and riparian enhancement. Studies in 

Oregon have shown that salmon abundance is positively related to pool size, especially 

during low flow conditions (Reeves et al. 2011), and beaver ponds provide particularly 

large pools. During winter, beaver ponds typically retain liquid water below the frozen 

surface, providing refugia for species that overwinter in streams and off-channel 

habitats (Nickelson et al. 1992, Cunjak 1996). 

Beaver dams generally do not constitute significant barriers to salmonid migration even 

though their semi-permeability may temporarily limit fish movement during periods of 

low stream flow (Rupp 1954, Gard 1961, Bryant 1984, Pollock et al. 2003). Even when 

beaver dams impede fish movements, the effects are typically temporary, with higher 

flows from storm events ultimately overtopping them or blowing them out (LeidholtBruner et al. 1992, Kemp et al. 2012). Even the temporary effect may be limited, when 

15
seasonal rainfall is at least average (Snodgrass and Meffe 1998, Kemp et al. 2012). 

Adding to the body of evidence, Pacific salmon and other migratory fish species 

commonly occur above beaver dams, including above beaver dams in the study area 

(PLP 2011; Appendix 15.1D). One study in southeast Alaska documented coho salmon 

upstream of all surveyed beaver dams, including one that was two meters high; in fact, 

the survey recorded highest coho densities in streams with beaver (Bryant 1984). Other 

surveys have documented both adult and juvenile sockeye salmon, steelhead, cutthroat, 

and char upstream of beaver dams (Bryant 1984, Swales et al. 1988, Murphy et al. 1989, 

Pollock et al. 2003).

Beavers preferentially colonize headwater streams, such as those found near the Pebble 

deposit, because of their shallow depths and narrow widths (Collen and Gibson 2001, 

Pollock et al. 2003). An October 2005 aerial survey of active beaver dams in the mine

scenarios area mapped a total of 113 active beaver colonies (PLP 2011). The Pebble 

Limited Partnership’s (PLP) Environmental Baseline Document (EBD) highlights the 

significant role that beaver ponds are currently providing for Pacific salmon in this area 

when it states:

“[W]hile beaver ponds were relatively scarce in the mainstem UT 

[UTC], the off-channel habitat study revealed a preponderance of 

beaver ponds in the off-channel habitats. As in the SFK watershed, 

beaver ponds accounted for more than 90 percent of the offchannel habitat surveyed. Beaver ponds in the UT provided habitat 

for adult spawning and juvenile overwintering for Pacific salmon. 

The water temperature in beaver ponds in the UT was slightly 

warmer than in other habitat types and thus, beaver ponds may 

represent a more productive habitat as compared to other 

mainstem channel habitat types” (PLP 2011).

The current body of literature describing the effects of beaver dams on salmonid species 

reports more positive associations between beaver dam activity and salmonids than 

negative associations (Kemp et al. 2012). Hence, removal of beaver dams as a means of 

compensatory mitigation could lead to a net negative impact on salmonid abundance, 

growth, and productivity. Moreover, since the mine scenario would eliminate or block 

several streams with active beaver colonies in the headwaters of the SFK and UTC, the 

benefits provided by those habitats would be part of the suite of functions that 

compensatory mitigation should aim to offset. 

3.3.1.1.2 Connect Off-channel Habitats and Habitat Above Impassible Waterfalls

Off-channel habitats can provide important low-velocity rearing habitats for juvenile 

salmon and other native fishes. Floodplain-complex habitats including beaver ponds, 

side channels, oxbow channels, and alcoves can contribute significantly to juvenile 

salmonid rearing capacity (e.g., Beechie et al. 1994). Such habitats are a common 

16
feature of unmodified alluvial river corridors. These habitats may express varying 

degrees of surface-water connectivity to main channels that in unmodified rivers is 

dependent upon streamflow stage and natural channel dynamics. Off-channel habitats 

may become isolated from the main channel during certain streamflow conditions due 

to channel migration or avulsion, and in highly dynamic channels, connectivity may 

change frequently during bed-mobilizing events (Stanford and Ward 1993). This shifting 

mosaic of depositional and erosional habitats within the floodplain creates a diverse 

hydraulic and geomorphic setting, contributing to biocomplexity (Amoros and Bornette 

2002). In river systems modified by human activity, isolation or elimination of offchannel habitats has had severe impacts on salmon productivity (e.g., Beechie et al. 

1994), and re-connection and re-creation of off-channel habitats are now common tools 

for increasing juvenile salmonid habitat capacity in those systems (Morley et al. 2005, 

Roni et al. 2006). 

Waterfalls or high-gradient stream reaches can prevent mobile fish species from 

accessing upstream habitats, due to velocity barriers or drops that exceed passage 

capabilities of fish (Reiser et al. 2006). Waters upstream of barriers may be devoid of all 

fish life, or may contain resident fish species including genetically-distinct populations 

(e.g., Whiteley et al. 2010). Engineered passageways for fish around waterfalls have 

been used to create access to upstream lakes or stream systems for fish such as salmon. 

However, the response of resident fish species to barrier removal and the colonization 

success of species from downstream habitats may be difficult to predict (Kiffney et al. 

2009). Salmon population responses to a fishway in southeast Alaska depended on the 

species, and the ecological effects of fish passage on the upstream lake system and 

watershed are not fully understood (Bryant et al. 1999). Burger et al. (2000) provide a 

well-documented history of colonization of sockeye salmon in Frazer Lake, Alaska above 

a historically-impassible waterfall following passage installation and planting of salmon 

eggs, fry, and adults above the barrier. Their study documents how differing donor 

populations, each with different life-history characteristics, contributed differently 

toward the establishment of populations in the newly accessible habitats (Burger et al. 

2000). This study highlights the importance of genetics and life history adaptations of 

source populations to colonization success. 

Creating connectivity between parts of the river network that are naturally 

disconnected can have adverse ecological effects, including impacts to resident 

vertebrate and invertebrate communities, as well as disruptions to ecosystem 

processes. Introduction of fish to fish-less areas can lead to altered predator-prey 

interactions, food web changes, changes in algal production, nutrient cycling and metapopulation dynamics of other vertebrate species (see Section 3.3.2.5). For example, 

previous studies on the introduction of trout species to montane, wilderness lakes have 

shown that introducing fish to fish-less lakes can have substantial impacts to nutrient 

cycles (Knapp et al. 2001). The risk of disruption to the functions of naturally fish-less 

aquatic ecosystems should be fully evaluated before these approaches are used for the 

sole purpose of creating new fish habitat area. 

17
Rosenfeld and co-authors (Rosenfeld et al. 2008, Rosenfeld et al. 2009) conducted a 

variety of experiments and monitoring activities within a re-connected river meander in 

coastal British Columbia to explore the relationship of salmon productivity to habitat 

features. Their work highlights the importance of habitat configuration. In their study, 

spacing of pools (foraging habitats for fish) and riffles (source areas for invertebrate 

prey) was an important factor influencing growth rates of juvenile coho salmon. Given 

the high diversity of channel conditions within floodplain habitats in the project area 

(PLP 2011), it is likely that fish responses to increased connectivity would be highly 

variable.

Rosenfeld et al. (2008) point out the importance of considering the full suite of factors 

that influence habitat capacity and productivity when designing restoration or 

enhancement projects. For instance, ‘optimising’ habitat structure for one species may 

adversely impact species with differing habitat preferences, as demonstrated by Morley 

et al. (2005) who found differential responses of juvenile steelhead and juvenile coho 

salmon to conditions in constructed and natural off-channel habitats. Predator-prey 

relationships also need to be considered. Increased connectivity of off-channel habitats 

has been proposed as a strategy for enhancing northern pike production in northern 

Canada (Cott, 2004). How increased connectivity in the project area would influence 

trophic relationships among northern pike and salmon, trout and char is unknown, 

although introduced northern pike in other areas of Alaska have the potential to reduce 

local abundances of salmonids via predation (Sepulveda et al. 2013). Bryant et al. 

(1999) in their study of the effects of improved passage at a waterfall concluded that 

the effects on food webs, trophic relationships, and genetics among resident and newlycolonizing species were largely unknown. Rosenfeld and co-authors (2009) emphasize 

the high degree of uncertainty associated with channel design for enhanced fish 

productivity, stating: 

“...despite the enormous quantity of research on stream rearing

salmonids and their habitat associations, stream ecologists still lack 

a definitive understanding of the relationship between channel 

structure, prey production and habitat capacity for drift-feeding 

fishes” (Rosenfeld et al. 2009, page 581).

Several commenters proposed that enhanced or increased connectivity of off-channel 

habitats or habitats above waterfalls could provide fish access to habitat currently 

underutilized or inaccessible. This comment presumes that currently disconnected 

habitats would provide suitable mitigation sites. Based on the above, there are multiple 

criteria that would have to be met, and numerous assumptions that would have to be 

validated in order for these sites to qualify as valid mitigation sites. For such measures 

to succeed, the following conditions would need to be considered:

a. Are currently inaccessible habitats suitable for salmon and other target 

fish species?

18
b. Does improved access to habitat address a currently limiting factor or 

condition? 

c. Can the habitat be effectively connected in a way that enhances 

productivity? 

d. Will enhanced connectivity be sustainable over the long term (e.g., be 

maintained despite sediment dynamics or channel adjustments)?

e. If enhanced connectivity is not self-sustainable, can a feasible monitoring 

and maintenance plan ensure continued connectivity and effectiveness?

f. What is the risk that changes to the hydrology, chemistry, temperature 

and morphology of the habitat complex associated with the construction 

of hydrologic connectivity will fundamentally alter the habitat suitability 

of the site such that it is no longer addressing a habitat need? 

g. Would predators/competitors present within the existing disconnected 

habitat overwhelm the benefit to target species?

h. Are fish populations present in isolated habitats (e.g., above impassible 

waterfalls) genetically distinct or otherwise of special value, and 

potentially lost if connections to downstream fish populations are 

enabled? 

i. How would potential adverse ecosystem changes in fish-less isolated 

habitats (e.g., above impassible waterfalls) due to fish introductions be 

evaluated and addressed? 

Given the above considerations and examples of the challenges of connectivity 

management, use of fishways at waterfalls and engineered connections to off-channel 

habitats have many unanswered questions for the project area streams and wetlands. 

Such approaches would be effectively an “adaptive management experiment” 

(Rosenfeld et al. 2008); requiring careful monitoring and evaluation of alterations within 

an experimental context.

3.3.1.2 Increase Habitat Quality 

Addition of large structural elements such as wood and boulders to streams has been a 

common stream habitat rehabilitation approach in locations where stream habitats 

have been extensively simplified by mining, logging and associated timber 

transportation, or other disturbances (Roni et al. 2008). The goals of large structure 

additions are typically to create increased hydraulic and structural complexity and 

improve local-scale habitat conditions for fish in streams that are otherwise lacking in 

rearing or spawning microhabitats. Properly engineered structural additions to 

channels can increase hydraulic diversity, habitat complexity, and retention of 

19
substrates and organic materials in channels, but benefits for aquatic life have been 

difficult to quantify (see review by Palmer et al. 2010). The paucity of demonstrated 

beneficial biotic responses to stream structural enhancements is at odds with 

perceptions by managers whose evaluations tend to be overtly positive – but usually 

based on qualitative opinion rather than scientific observation (Jähnig et al. 2011). In 

addition, improperly sited or engineered structural additions can fail to achieve desired 

effects or have adverse, unanticipated consequences (e.g., via structural failure or scour 

and fill of sensitive non-target habitats (Frissell and Nawa 1992)), highlighting the need 

for appropriate design.

Commenters proposed that quality of stream habitats in the project area could be 

enhanced by increasing habitat complexity through the addition of boulders or large 

wood to existing off-channel habitats. Off-channel habitats can provide important lowvelocity rearing habitats for juvenile salmon and other native fishes. Floodplaincomplex habitats including beaver ponds, side channels, oxbow channels, and alcoves 

provide hydraulic diversity that can be important for fish in variable flows (Amoros and 

Bornette 2002, Rosenfeld et al. 2008). Beaver are a major player in the creation and 

maintenance of these habitats in the study area (PLP 2011, Appendix 15.1D), as has 

been noted elsewhere (Pollock et al. 2003, Rosell et al. 2005). Off-channel habitats also 

provide important foraging environments, and can be thermally-diverse, offering 

opportunities for thermoregulation or enhanced bioenergetic efficiency (Giannico and 

Hinch 2003). Off-channel habitats are relatively frequent and locally-abundant in area 

streams and rivers, particularly in lower-gradient, unconstrained valley settings and at 

tributary confluences (e.g., PLP 2011 Figure 15.1-15, cover photo of this assessment). 

PLP’s EBD, Appendix 15.1D (PLP 2011) contains an assessment of the natural fluvial 

processes creating and maintaining off-channel habitats, and their quality and quantity 

and function in the study area, including mechanisms of connectivity to the mainstem 

channels. This background information provides very useful information for evaluating 

the potential effectiveness of off-channel habitat modification.

Commenters proposed that off-channel habitats could also be improved by engineered 

modifications to the depth, shoreline development ratio, and configuration of offchannel habitats to create better overwintering habitat for juvenile salmon. The degree 

to which existing habitats could be enhanced to improve survival of juvenile salmon as 

proposed by commenters will be dependent upon several considerations, including an 

evaluation of factors known to influence the utilization, survival, and growth within 

these habitats. These considerations are discussed below.

Off-channel habitats surveyed by PLP and other investigators reveal that patterns of 

occupancy and density are high but variable among off-channel habitats (PLP 2011, 

Appendix 15.1D). Some of the highest densities observed were within off-channel 

habitats such as side channels and alcoves, but even some ‘isolated’ pools held fish (PLP 

2011, Appendix 15.1D). This variability could reflect variation in suitability, access, or 

other characteristics of individual off-channel habitats. Juvenile salmonids require a 

20
diverse suite of resources to meet habitat requirements – cover and visual isolation 

provided by habitat complexity is one such resource, but other critical resources include 

food, space, and suitable temperatures and water chemistry (Quinn 2005). Habitat 

configuration within constructed side-channel habitats can also strongly influence 

density, size and growth of juvenile salmonids (Rosenfeld and Raeburn 2009). Giannico 

and Hinch (2003) in experimental treatments in side channels in British Columbia, found 

that wood additions were beneficial to coho salmon growth and survival in surfacewater fed side channels, but not in groundwater-fed channels. They attributed this 

effect to differences in foraging strategy and bioenergetics of the juvenile coho salmon 

overwintering in the channels. Additions of wood had no effect, or even possibly a 

detrimental effect, on coho salmon survival in groundwater-fed side channels. These 

findings highlight the importance of understanding the ecology, bioenergetics, and 

behavior of the species and life histories present within habitats that may be quite 

diverse with regard to hydrology and geomorphology. 

It is not clear from current data that adding complexity would address any limiting 

factor within existing off-channel habitats, or that additions of boulders and wood 

would enhance salmonid abundance or survival. Placement of structures (e.g., 

boulders, large wood) within stream channels should also be guided by careful 

consideration of potential adverse consequences, including unanticipated shifts in 

hydraulic conditions that lead to bank erosion or loss of other desirable habitat features. 

Sustainability of off-channel habitat modifications is also in question. As stated in the 

EBD, off-channel habitats are a product of a dynamic floodplain environment and “..are 

continually being created and destroyed” (PLP 2011; Appendix 15.1D; page 2). 

Maintenance of engineered structures or altered morphologies of such habitats over the 

long term would be a challenging task. Observations from the EBD suggest that beaver 

are already providing desired complexity; to quote, “..habitat mapping from this offchannel study shows that the beaver ponds contain extensive and diverse habitats and 

dominate the active valley floor.” And, “...these off-channel habitats provide a critical 

habitat component of freshwater rearing of coho salmon, and to a lesser extent, other 

anadromous and resident species.” (PLP 2011, Appendix 15.1D page 14).

3.3.1.3 Increase Habitat Quantity 

The creation of spawning channels and off-channel habitats has been proposed as a 

means to compensate for lost salmon spawning and rearing areas. The intent of a 

constructed spawning channel is to simulate a natural salmon stream by regulating flow, 

gravel size, and spawner density (Hilborn 1992). Off-channel habitats may be enlarged 

or modified to alter habitat conditions and capacities for rearing juvenile salmonids. 

Examples include the many spawning channels (Bonnell 1991) and off-channel habitats 

(Cooperman 2006) enhanced or created in British Columbia and off-channel ponds 

rehabilitated by the City of Seattle (Hall and Wissmar 2004). 

21
Off-channel spawning and rearing habitats can be advantageous to salmon populations 

by providing diverse hydraulic and habitat characteristics. Redds constructed in these 

habitats may be less susceptible to scour compared to main channel habitats due to 

flow stability provided by their hyporheic or groundwater sources (Hall and Wissmar 

2004). Moderated thermal regimes can provide benefits for growth and survival for 

overwintering juveniles (Giannico and Hinch 2003). Morley et al. (2005) compared 11 

constructed off-channel habitats to naturally-occurring paired reference side channels 

and found that both natural and constructed off-channel habitats supported high 

densities of juvenile salmonids in both winter and summer. Although numerous studies 

have documented short-term or localized benefits of constructed off-channel habitats, 

ascertaining population-level effects is much more difficult. Any additional fry produced 

by spawning channels (if successful) would require additional suitable habitat for 

juvenile rearing and subsequent life stages in order to have a net positive effect on 

populations. Hilborn (1992) indicates that success, measured by increased production 

of adult fish from such channels, is unpredictable and generally unmonitored. A notable 

exception is the study by Sheng et al. (1990), which documented 2- to 8-fold increases in 

recruitment of coho spawner production from groundwater-fed off-channel habitats. 

Sheng et al. (1990) stated that effectiveness would be greatest in systems which 

currently lack adequate overwinter refuges. As with any rehabilitation strategy, 

population responses will be dependent upon whether factors actually limiting 

production are addressed. As stated elsewhere in this assessment, additional research 

and monitoring is required to quantify factors currently limiting production within 

project area watersheds. 

Replacing destroyed salmon habitats with new constructed channels is not a simple 

task. Factors for consideration in designing and implementing off-channel habitat 

development are outlined in Lister and Finnigan (1997), and include evaluation of 

species and life stages present, current habitat conditions, and factors limiting capacity 

or productivity (Roni et al. 2008). Research indicates that channels fed by hyporheic 

flow or groundwater may be most effective for creating suitable spawning and rearing 

habitats (Lister and Finnigan 1997). Near-stream excavation and compaction associated 

with channel construction can alter groundwater flowpaths, so designing projects to 

protect current function and groundwater connectivity is very important. 

Numerous researchers have emphasized that replacing lost habitats is not merely a 

process of providing habitat structure (Lake et al. 2007). Effective replacement of 

function also requires establishment of appropriate food web structure and productivity 

to support the food supply for fish – in essence, an entire ecosystem, including all full 

suite of organisms such as bacteria, algae, and invertebrates – needs to be in place in 

order for a constructed channel to begin to perform some of the same functions of a 

destroyed stream (Palmer et al. 2010). Quigley and Harper (2006b), in a review of 

stream rehabilitation projects, concluded “the ability to replicate ecosystem function is 

clearly limited.” 

22
There is some history of using constructed spawning channels to mitigate for the 

impacts of various development projects on fish, based on the premise that they would 

provide additional spawning habitat and produce more fry, which would presumably 

result in more adult fish returning (Hilborn 1992). Off-channel rearing habitats have 

also been used to create additional overwintering habitats in Pacific Northwest rivers 

(Roni et al. 2006), and spawning channels have also been shown to provide suitable 

overwintering habitats for juvenile coho salmon (Sheng et al. 1990). However, there are 

very few studies regarding the efficacy of such channels at enhancing adult salmon 

recruitment in the published literature. Constructed spawning channels, particularly 

those dependent upon surface flow, may also require annual maintenance and cleaning

(Hilborn 1992), and salmon using them can be prone to disease outbreaks (Mulcahy et 

al. 1982). The need for frequent maintenance would be contrary to the regulations’ 

intent that compensatory mitigation projects be self-sustaining (40 CFR 230.97(b)). Offchannel habitats to mainstems are also extremely difficult to engineer in a way that can 

self-sustain in the face of a dynamic fluvial environment. Alluvial channels frequently 

shift (Amoros and Bornette 2002), and beaver are highly effective ecosystem engineers 

whose activities are constantly re-arranging floodplain channels and creating new dams 

(Pollock et al. 2003) - including within engineered channels and culverts (Cooperman 

2006). 

In light of their uncertain track record, it does not appear that constructed spawning 

channels and engineered connections of off-channel habitats would provide reliable and 

sustainable fish habitat in the Bristol Bay region.

3.3.1.4 Manage Water Quantity 

Two commenters suggested a variety of techniques to manipulate water quantities 

within the NFK, SFK and UTC watersheds to improve fish productivity. Possible 

techniques for accomplishing this include: flow management, flow augmentation, and 

flow pump-back. 

3.3.1.4.1 Direct Excess On-site Water

Commenters suggested that fish habitat productivity could be improved through careful 

water management at the mine scenario site, including the storage and strategic 

delivery of excess water to streams and aquifers to maintain or enhance flow and/or 

thermal regimes in the receiving streams. Delivering such flows via groundwater (i.e., 

by using wastewater treatment plant (WWTP) discharges to “recharge and surcharge 

groundwater aquifers”) was identified as a preferred approach; commenters argued 

doing so would both render the measure less prone to operational anomalies at the 

WWTP and better mimic current natural flow patterns, thereby attenuating potential 

adverse effects related to discharge volume and temperature. Ideally, flow, 

temperature, and habitat modeling would inform the design and operation of flow 

23
management to optimize species and habitat benefits by, for example providing water 

at specific times to locations where low flow currently limits fish productivity.

Manipulation of surface flows at another mine in Alaska—Red Dog, in the northwest 

part of the state—has resulted in an increase in fish (Arctic grayling and Dolly Varden) 

use of the downstream creek (Scannell 2005, Ott 2004). The circumstances at Red Dog, 

however, differ from those in the NFK, SFK, and UTC area. As described in Scannell 

(2005), the near complete absence of fish in Red Dog Creek prior to implementation of 

the water management techniques was the direct result of water quality, not quantity, 

as the stream periodically experienced toxic levels of metals that occurred naturally as it 

flowed through and downslope of the exposed ore body. Furthermore, the Red Dog 

water management system primarily involves point-to-point diversion or transfer of 

surface, rather than groundwater, both around the ore body and from tributaries 

upstream of the mine. We have been unable to locate any documentation of successful 

attempts to manage flow volume or temperature from mine sites (or other industrial 

developments), via groundwater, for the benefit of fish and/or fish habitat.

Given that most streams in the area support multiple salmonid species and life stages, 

with differing habitat needs at different times, designing and managing a water delivery 

system to overcome limiting factors for one or more species without adversely 

impacting others would be a significant challenge. Given the complexity of the surfacegroundwater connectivity in the area, ensuring that discharges to groundwater actually 

reached the target habitat at the intended time would, perhaps, be the most difficult 

task. Quigley and Harper (2006b), in a review of stream rehabilitation projects,

concluded “the ability to replicate ecosystem function is clearly limited.” 

This challenge could potentially be easier to overcome where habitat limitations 

occurred only as a result of mine development, assuming pre-project modeling and 

verification accurately identified groundwater flow paths to those areas. It is important 

to note, however, that even if such actions appeared to be feasible, they likely would be 

required to avoid or minimize the adverse impacts of flow reduction due to mine 

development, rather than to compensate for unavoidable habitat losses. 

If it were an overall enhancement to pre-existing habitat, using WWTP discharges to 

groundwater to address natural limitation factors could be a form of compensatory 

mitigation. For example, PLP (2011) points out that productivity may be limited by the 

existence of “losing” reaches along the SFK mainstem and intermittent or ephemeral 

tributaries to both the SFK and NFK. Altering the natural flow regimes at such sites, 

however, could have unintended consequences on the local ecosystem and species 

assemblages (Poff et al. 1997). Moreover, “enhancing” these habitats through a WWTPsourced groundwater flow delivery system would be even more challenging than 

managing flow to avoid or minimize impacts to already productive habitat, because it 

would require “improving” the natural flow delivery system that currently results in the 

periodic drying/low flows. We have not located any documented successful application 

24
of this technique, making it a highly experimental approach to enhancing fish 

productivity, particularly in a natural stream system. Highly experimental and 

unpredictable activities are generally discouraged as compensatory mitigation (40 CFR 

230.93(a)(1); see also 73 FR 19633). The regulations also strongly discourage 

compensatory mitigation projects that require the long-term use of active engineering 

features (40 CFR 230.97(b)).

3.3.1.4.2 Augment Flows 

Another means suggested for maintaining or increasing habitat productivity 

downstream of the mine site is to increase flow volume into certain streams by creating 

new sources of surface flow and/or groundwater recharge, specifically, from 

impoundments and/or ice fields. We are unaware of any documented successful efforts 

to create impoundments or ice fields for the benefit of salmonids. As described in the 

previous section, actions to maintain or reestablish pre-mine flow in streams likely 

would be required as avoidance or minimization measures, and would not constitute 

compensatory mitigation for unavoidable impacts.

Only if it were an overall enhancement to existing habitat would creating 

impoundments and/or ice fields have the potential for offsetting unavoidable adverse 

impacts. Thus, the objective would be to target stream reaches where flow-habitat 

modeling indicated opportunities for enhancement.

PLP’s EBD notes that a portion of the SFK mainstem, as well as some Koktuli River 

tributaries, exhibit either intermittent or ephemeral flow that appears to be a limiting 

factor for salmonid productivity (PLP 2011). However, two of the tributaries are in the 

uppermost reaches of the SFK and would be eliminated by the mine scenarios. 

Although there are potential locations for impoundments to manage flow in the stream 

reaches identified as having ”sub-optimal” flow, logistical and environmental issues 

decrease the likely efficacy and sustainability of such an approach. Manipulating 

streamflows in particular watersheds would require diverting water from other basins 

or capturing water during peak flows for subsequent release at other times, with the 

concomitant engineering, construction, and maintenance challenges. Doing so would 

create additional adverse impacts from the construction of infrastructure and would be 

subject to modeling and perpetual management sufficient to ensure that water 

withdrawals from the “donor” watershed or from other times of the year would not 

adversely impact fish habitat and populations in its downstream waters. These 

concerns are in addition to those commonly associated with impoundments, such as 

alteration of flow, thermal, and sediment transport regimes.

Creating ice fields to increase the total volume of water available to a stream would also 

require water diversion, with the same challenges and concerns related to building and 

maintaining system infrastructure and reducing water volumes in the source watershed. 

25
Using ice fields to change the timing of water availability would encounter issues related 

to managing the melt to produce stream flow at the intended time (i.e., late summer or 

late winter low-flow periods). Moreover, since aquatic organisms supported by a 

particular water body typically have evolved specific life history, behavioral, and 

morphological traits consistent with the characteristics of that water body’s natural flow 

regime, local populations are inherently vulnerable to flow modification (Lytle and Poff 

2004). Any use of ice fields would face the potentially substantial challenges of the 

effects of climate change on ice production and preservation. Besides requiring active 

management in perpetuity, ice field creation for flow augmentation would be decidedly 

experimental, with high uncertainty regarding the likelihood of success. Flow 

augmentation techniques would also be inconsistent with the regulation’s provision that 

“[c]ompensatory mitigation projects shall be designed, to the maximum extent 

practicable, to be self-sustaining once performance standards have been achieved. This 

includes minimization of active engineering features...” (40 CFR 230.97(b)).

3.3.1.4.3 Pump Water Upstream 

Another option suggested for making flow in some stream reaches more persistent is to 

pump groundwater or surface water from a down-gradient site upstream to either a 

direct release point or a recharge area. This technique has been used for fish habitat 

restoration at sites in the continental U.S. (e.g., the Umatilla River, OR (Bronson and 

Duke 2005), the Lower Owens River, CA (LADWP 2013), and Muddy Creek, CO (AECOM 

et al. 2010 and GrandRiver Consulting 2008)), although we are unaware of any 

documentation addressing its efficacy in increasing salmonid productivity. As with flow 

management and augmentation, using this technique to offset flow reductions from 

mine operations would not be compensatory mitigation, limiting its potential use as 

such to reaches that already have sub-optimal flow. One such stream is NFK 1.190.10, a 

tributary that enters NFK 1.190 downstream of the tailings storage facility location. 

Flow modeling, however, indicates that mine development would diminish flow in that 

stream even further (see Figures 7-15 through 7-17 of the assessment).

For the periodically intermittent or ephemeral reaches identified in the EBD, potential 

source sites presumably would be in or along the lower reaches of the NFK or SFK, 

downstream of the mine, waste rock, and tailings storage facilities. Flow modeling 

indicates that the NFK would experience a decrease in flow under the Pebble 6.5 

scenario (see Figure 7-17 of the assessment), increasing the possibility that withdrawing 

additional water from the system to pump back upstream either would not be possible 

or would have adverse downstream impacts. Extensive modeling would be necessary to 

assess downstream effects in either watershed.

Even with sufficient downstream water, this technique would require substantial 

disturbance associated with the construction of tens of kilometers of water pipeline, 

power infrastructure, and access, along with maintenance of those facilities in 

perpetuity. It would also entail active management to ensure that releases occur at 

26
appropriate times, to increase the persistence of flow in target streams without 

otherwise adversely impacting their hydrographs or habitat. Such management would 

be another aspect of the approach that would be perpetual. In total, this technique 

would involve a great deal of uncertainty with regard to both efficacy and sustainability, 

making it a questionable mechanism for providing compensatory mitigation. This 

technique would also be inconsistent with the regulation’s provision that 

“[c]ompensatory mitigation projects shall be designed, to the maximum extent 

practicable, to be self-sustaining once performance standards have been achieved. This 

includes minimization of active engineering features (e.g., pumps) and appropriate siting 

to ensure that natural hydrology and landscape context will support long-term 

sustainability” (40 CFR 230.97(b)).

3.3.1.5 Manipulate Water Quality 

Two commenters suggested that alteration of stream water chemistry would improve 

fish production in the NFK, SFK and UTC. They suggest increasing two groups of water 

chemistry parameters: basic parameters such as alkalinity, hardness, and total dissolved 

solids, and nutrients such as nitrogen (N) and phosphorous (P). This argument suggests 

that low concentrations of basic parameters and/or nutrients limit the production of 

algae, which limits aquatic macroinvertebrate production and habitat complexity. This 

in turn can reduce overall fish production, reduce individual fish growth rates, or result 

in fish movements away from low production areas. 

3.3.1.5.1 Increase Levels of Alkalinity, Hardness, and Total Dissolved Solids 

Commenters propose that altering stream water chemistry to increase levels of 

alkalinity, hardness, and total dissolved solids would improve the buffering capacity, 

primary productivity, secondary productivity, and reduce the potential toxicity of metals 

at waters downstream of these altered locations. Commenters suggest two 

mechanisms to achieve these improvements: 1) the addition of limestone in some form 

at “appropriate” locations or 2) the discharge of higher alkalinity water into fishproducing streams through a water management program. Commenters argue that 

current levels of alkalinity, hardness, and total dissolved solids in the NFK, SFK and UTC 

are suboptimal for fish production and could be manipulated to improve fish 

production. However, the majority of the literature relating to alkalinity and limestone 

management, including every published study cited by commenters, evaluates these 

approaches in streams and lakes in northern Europe, eastern U.S., or eastern Canada 

whose fisheries have been heavily impacted by acid mine drainage, acid deposition or 

other mechanisms of acidification and even in these degraded water bodies, 

alkalinity/limestone treatment results were variable (Gunn and Keller 1984, Hasselrot 

and Hultberg 1984, Rosseland and Skogheim 1984, Zurbuch 1984, Gagen et al. 1989, 

Lacroix 1992, Clayton et al. 1998, McClurg et al. 2007). It is not clear from any of the 

published studies cited by commenters what effect the addition of limestome or higher 

27
alkalinity water would have on the kinds of unaltered stream systems and fishery 

resources found in the Bristol Bay region of Alaska.

Alkalinity has two potential roles. First, it is a measure of the ability of water to 

neutralize acids. If the intent is to neutralize acid rock drainage from the potential mine, 

that use constitutes impact minimization or remediation, not compensation. Second, 

alkalinity is primarily due to carbonate and bicarbonate, which is the source of carbon 

used by aquatic algae so increasing alkalinity is potentially fertilization. However, given 

that the streams at the site are relatively shallow and rapidly flowing, it is very unlikely 

that they are carbon limited. Therefore, it is unlikely that increasing alkalinity would 

increase algal production unless it is neutralizing acids from a mine.

Similar considerations apply to increasing hardness. Aqueous hardness is due to calcium 

and magnesium, which reduce the toxicity of divalent metals such as copper by 

competing for uptake sites. Increasing hardness would be a potential means of 

remediating the effects of high metal levels drainage from mine waste leachate into 

streams. Alternatively, calcium and magnesium are nutrient elements and 

hypothetically could be limiting production. However, the commenters produce no 

evidence that such limitations are occurring, and it is less credible than the potential N 

and P limitations discussed in the next section.

Manipulating water chemistry could have a deleterious effect on salmon populations. A 

key characteristic of Pacific salmon is their homing migrations from oceanic feeding 

grounds, through diverse habitats, to their natal river to spawn. Homing is generally 

precise and has resulted in reproductively isolated spawning populations with 

specialized adaptations for their natal habitat. (Wisby and Hasler 1954, Hasler and 

Scholz 1983, Quinn and Dittman 1992, Dittman et al. 1995, Dittman and Quinn 1996). 

Olfactory systems of salmon are acutely sensitive to changes in water chemistry 

(McIntyre et al. 2012). Physiological and behavioral experiments demonstrate that 

calcium is an important odorant enabling salmon to recognize individual waters and that 

sockeye salmon olfactory systems are acutely sensitive to calcium ions (Bodznik 1978). 

This would suggest that manipulating stream chemistry through the addition of 

limestone or higher alkalinity water could impede salmon from recognizing and homing 

to their natal streams. Some commenters who raised concerns about manipulating 

stream chemistry through these approaches point out that homing failure could reduce 

productivity if salmon die without spawning or stray to non-natal habitats to which they 

are poorly adapted and experience higher mortality.

We are not aware of any published studies describing projects where the chemistry of 

unaltered/un-degraded salmon streams in Alaska or elsewhere has been manipulated 

through the addition of limestone or higher alkalinity water to achieve improvements in 

buffering capacity against natural acidity, increase primary or secondary productivity, or 

reduce toxicity to naturally occurring metals. Rather, the scientific literature suggests 

that such chemical alterations could result in deleterious effects on salmon in 

28
unaltered/un-degraded stream systems. Manipulating stream chemistry in the NFK, SFK 

and UTC through the addition of limestone or higher alkalinity water would be a 

challenging and difficult experiment with an unknown outcome. 

3.3.1.5.2 Increase Levels of Nitrogen and/or Phosphorus

The same two commenters suggest altering stream water chemistry to increase levels of 

N and P where they are individually or co-limiting. They provide four categories of 

considerations for determining how to increase stream or lake nutrients: 

1) The spatial and temporal distribution of the limiting nutrients, 

2) The timing and duration of nutrient application(s), 

3) The desired concentrations of each nutrient and the ratio between N and P for 

each application location, and 

4) The need for detailed pre-project information including the biological species 

composition of the waterbody and a low level nutrient analysis. 

The commenters make a few general recommendations about how to consider these 

factors when developing mitigation in the NFK, SFK and UTC. They suggest that the 

spatial distribution could focus on existing or newly created side channels, sloughs, 

beaver ponds, alcoves, or, if necessary, the main channels at 10 km intervals. They 

suggest several possible temporal distribution options; of adding the nutrients only 

during the growing season, potentially earlier, or all winter in open water locations 

where biological production continues year round. They further indicate that the key 

considerations are access cost and maintenance requirements. The commenters note 

several types of nutrient delivery methods: liquid fertilizer, slow-release fertilizer, and

nutrient analogs (which are essentially slow-release pellets of processed fish).

As support for their conclusion that lake and stream fertilization represent 

“demonstrably successful mitigation techniques” for the NFK, SFK and UTC, the 

commenters cite a number of papers summarizing experiments and case studies, as well 

as references to several management programs in the U.S., Canada, and northern 

Europe. These studies have examined the use of increased levels of N and P, or fish 

carcasses, to improve ecosystem productivity and/or fish production. 

The two commenters argue that current levels of N and P in the NFK, SFK and UTC are 

suboptimal for fish production stating that benefits of fertilizing oligotrophic waters to

stimulate fish production have been demonstrated in many venues. Although 

numerous studies show an effect at one or more trophic levels in response to 

fertilization, these studies are insufficient for drawing conclusions regarding the longterm effectiveness of nutrient application to streams in the NFK, SFK and UTC

watersheds because they lack scientific controls or have not been replicated, do not 

account for potential confounding factors, were conducted in very different ecosystems, 

and/or only evaluated short-term effects. These differences are pointed out in the 

following paragraphs.

29
Commenters provided examples of experiments and studies aimed at increasing primary 

productivity and theoretically salmon productivity. These studies assume that nutrients 

are the limiting factor preventing increased salmon productivity, but that is not 

necessarily the case. Paleolimnetic studies in Alaska indicate nutrient inputs are not 

always tied to higher primary productivity or salmon productivity (Chen et al 2011). 

Wipfli and Baxter (2010) found that most fish consume food from external or very 

distant sources, including from marine systems borne by adult salmon, from fishless 

headwaters that transport prey to downstream fish, and from riparian vegetation and 

associated habitats. An increase in food via nutrients may not overcome other limiting 

factors such as habitat availability or interspecies competition. 

Most studies on stream and lake fertilization to increase productivity are short-term in 

duration and conducted in ecosystems with important differences from Bristol Bay (e.g.

Perrin et al. 1987, Raastad et al. 1993, Wipfli et al. 1998, Slaney et al. 2003). For 

example, studies conducted at the Keogh and Salmon Rivers (Ward et al. 2003, Slaney et 

al. 2003) examined the effect of nutrient supplement in the form of salmon carcasses 

and inorganic N and P, respectively, in two coastal river systems for a period of three 

years. A spike in productivity has been seen in a number of these studies, but long term 

studies call into question whether the trend will be sustained over longer periods as is 

described in the following two long-term studies. 

Results from the longest running study on stream fertilization raise concerns about 

using fertilization other than as an interim restorative measure. Slavik et al (2004) 

found that persistent increased levels of N and P can result in dramatic ecosystem shifts. 

This long term ecological research on the North Slope of Alaska examined the effect of P 

input into P-limited streams, finding an increase in production for some species at all 

trophic levels over the first few years. However, starting at seven or eight years,

nutrient enrichment caused a dramatic rise in moss (photos A and B) that changed 

ecosystem structure. Despite higher insect biomass in the fertilized area during this 

period, the growth of fish was no longer significantly greater than in the reference area 

(Slavik et al. 2004). The resulting decrease in fish productivity was thought to result 

from the effects of moss on preferred insect prey. Following cessation of nutrient 

enrichment, it took eight years of recovery to approach reference levels, after storms 

had scoured most remnant moss in the recovering reach. These results demonstrate 

that even at low concentrations, sustained nutrient enrichment can have “dramatic and 

persistent consequences” (Benstead et al. 2007).

30
Photos showing the difference in bottom coverage between the diatom state (Photo A, 

left) and the fertilized moss state (Photo B, right). Used with permission (Slavik et al.).

In another study, long-term nutrient enrichment produced an unanticipated trophic 

decoupling whereby enrichment continued to stimulate primary consumer production 

without a similar increase in predator fish. The majority of the increased ecosystem 

productivity was confined to lower trophic levels because the long-term enrichment 

primarily stimulated primary consumers that were relatively resistant to predation. 

Based on these results, the authors concluded that “even in ecosystems where energy 

flow is predicted to be relatively efficient, nutrient enrichment may still increase the 

production of non-target taxa (e.g. predator or grazer resistant prey), decrease the 

production of higher trophic levels, or lead to unintended consequences that may 

compromise the productivity of freshwater ecosystems” (Davis et al. 2010 p 124).

These unanticipated results raise important questions about the potential consequences 

of long-term nutrient supplementations. They also underscore the unpredictability of 

nutrient additions on the food web, and the greater likelihood of unintended 

consequences as the effects ripple through complex interactions between species. 

These implications are especially relevant considerations for potential long-term 

mitigation that would be necessary in the NFK, SFK and UTC. If long-term nutrient 

addition were to cause an ecosystem shift at lower trophic levels in the NFK, SFK and 

UTC, effects on higher trophic levels including the productivity of salmon and other 

target fish species are unknown. 

Studies examining the relationship between salmon carcasses and productivity at 

various trophic levels are another active area of investigation. Some research provides 

evidence that carcasses are superior to inorganic nutrient amendments for sustaining 

and restoring stream productivity, including fish production, potentially because 

inorganic nutrients lack biochemicals and macromolecules that are utilized directly by 

consumers (Wipfli et al. 2010, Martin et al. 2010, Heintz et al. 2010). Others have found 

the effects of carcasses can be transient, localized, and variable with no increase in fish 

growth (Cram et al. 2011). Few studies have documented the long-term impacts of 

carcass addition, and there are many remaining gaps in understanding the efficacy of 

this method of potentially improving salmon productivity. In addition, a number of 

31
authors express concern about the potential for the spread of toxins and pathogens

when carcasses are used as the supplemental nutrient source (Compton et al. 2006).

Setting aside questions of scientific efficacy and applicability, there are numerous 

practical challenges inherent in nutrient addition as a potential mitigation method. 

Conducting a long-term management protocol in remote waterways subject to extreme 

weather changes necessarily requires careful monitoring of water chemistry and precise 

application of nutrients, which calls into question the sustainability of altering stream 

water chemistry to improve the fish production. 

Authors of many of these studies state that the application of their results are relevant 

and appropriate for salmonid restoration in streams or lakes with depressed numbers 

(Larkin and Slaney 2011). The authors do not describe their results as informing 

methods to manipulate existing unaltered wild systems to further augment salmon 

production. Although the commenters draw heavily from Ashley and Stockner (2003), 

the authors of that study actually state: 

“The goal of stream and lake enrichment is to rebuild salmonid escapement 

to historical levels via temporary supplementations of limiting nutrients 

using organic and/or inorganic formulations. Stream and lake enrichment 

should not be used as a ‘techno-fix’ to perpetuate the existing 

mismanagement of salmonids when there is any possibility of reestablishing self-sustaining wild populations through harvest reductions and 

restoration of salmonid habitat. Therefore, fertilization should be viewed as 

an interim restorative measure that is most effective if all components of 

ecosystem recovery and key external factors (e.g. overfishing) are 

cooperatively achieved and coordinated. This paper reviews some of the 

technical and more applied aspects of stream, river, and lake enrichment as 

currently practiced in British Columbia and elsewhere. As a caveat, the 

discussion assumes that salmonid stock status of candidate lakes and 

streams has been quantified and classified as significantly depressed and 

that additional limiting factors (e.g. habitat/water quality and quantity) have 

been addressed and/or incorporated into an integrated basin or lake 

restoration plan.” (Ashley and Stockner 2003 p. 246) 

There are still many gaps in understanding the role of nutrients in fish productivity, so 

there is a great deal we do not know about whether nutrient addition can be a 

successful method to increase fish productivity. At this time there are no scientific 

studies showing how an increase in nutrients resulting in increase salmon productivity

can be reliably achieved on a long-term basis in the NFK, SFK and UTC watersheds or the 

larger Bristol Bay ecosystem without risk to the region’s existing robust populations. 

Just as for the addition of non-nutrients such as limestone, manipulating stream 

chemistry in this largely unaltered ecosystem through the addition of N and P would be 

a challenging and difficult experiment with many negative outcomes possible. 

32
3.3.1.6 Preserve Aquatic Resources

As described above, preservation as compensatory mitigation for the mine scenarios 

would require a site that is very large, performs similarly important aquatic functions, 

and is under threat of destruction or adverse modification. No commenters identified 

specific potential preservation sites, either within these watersheds or elsewhere in 

Bristol Bay. One challenge in identifying appropriate preservation sites is the high 

percentage of state and federal land ownership in the area. Public lands can provide 

mitigation, but only if the mitigating measure—in this case, preservation—is “over and 

above [that] provided by public programs already planned or in place” (40 CFR 

230.93(a)(3)). Further, the aquatic functions of any preservation site downstream from 

the proposed mine scenarios would be subject to degradation from the direct, 

secondary, and cumulative effects of the mine itself. These factors could limit most 

properties of adequate area and similar aquatic function from serving as acceptable 

mitigation sites. Moreover, there is no precedent for such a preservation-dominated 

compensation approach in the context of this type and magnitude of ecological loss.

3.3.2 Other Opportunities within the Nushagak and Kvichak River Watersheds

As noted above, if practicable or appropriate opportunities to provide compensation 

within the NFK, SFK or UTC watersheds are non-existent or limited, it may be 

appropriate to explore options in adjoining watersheds. For example, there are a few

scattered degraded sites in more distant portions of the Nushagak and Kvichak River 

watersheds that could potentially benefit from restoration or enhancement. 

Here we discuss specific suggestions for other potential compensation measures within 

the Nushagak and Kvichak River watersheds that were provided in the public and peer 

review comments on the Bristol Bay Assessment. 

3.3.2.1 Remediate Old Mine Sites 

The U.S. Geologic Survey (USGS) identifies four small mine sites within the Nushagak 

and Kvichak River watersheds: Red Top (in the Wood River drainage), Bonanza Creek (a 

Mulchatna River tributary), Synneva or Scynneva Creek (a Bonanza Creek tributary), and 

Portage Creek (in the Lake Clark drainage) (USGS 2008, 2012). These sites could provide 

opportunities for performing ecological restoration or enhancement. However, due to 

their relatively small size and distant location, it is unlikely that these sites could provide 

sufficient restored or enhanced acreage or ecological function to offset what would be 

lost under the assessment mine scenarios. Further, some mitigation measures have 

already occurred at these mines; for example, there have been some remediation 

activities at Red Top mine, although traces of mercury and diesel-range organics remain 

in soils (BLM 2000). Resolution of liability and contamination issues at these old mines 

33
would be necessary before they could serve as compensatory mitigation sites for other 

projects. 

3.3.2.2 Remove Roads 

Another potential type of restoration within the Nushagak and Kvichak River watersheds

is the removal of existing or abandoned roads. As described in detail in Appendix G of 

the assessment, roads have persistent, multifaceted impacts on ecosystems and can 

strongly affect water quality and fish habitat. Common long-term impacts from roads 

include: 1) permanent loss of natural habitat; 2) increased surface runoff and reduced 

groundwater flow; 3) channelization or structural simplification of streams and 

hydrologic connectivity; 4) persistent changes in the chemical composition of water and 

soil 5) disruption of movements of animals, including fishes and other freshwater 

species; 6) aerial transport of pollutants via road dust; and 7) disruption of near-surface 

groundwater processes, including interception or re-routing of hyporheic flows, and 

conversion of subsurface slope groundwater to surface flows (Darnell et al. 1976, 

Trombulak and Frissell 2000, Forman 2004). Road removal, thus, could facilitate not 

only the reestablishment of former wetlands and stream channels, but also the 

enhancement of nearby aquatic resources currently degraded by the road(s). 

Commenters did not offer specific suggestions for potential road removal sites. As 

Appendix G of the assessment highlights, the Nushagak and Kvichak River watersheds 

are almost entirely roadless areas (see Figure 1 of Appendix G). Further, it is unlikely 

that local communities would support removal of any segments of the few existing 

roads in the watersheds. Thus, it would appear there are very few, if any, viable 

opportunities to provide environmental benefits through road removal. 

3.3.2.3 Retrofit Road Stream Crossings 

Another potential type of enhancement within the Nushagak and Kvichak River 

watersheds is to retrofit existing road stream crossings to improve fish passage through 

these man-made features. Stream crossings can adversely impact spawning, rearing 

(Sheer and Steel 2006, Davis and Davis 2011), and refuge habitats (Price et al. 2010), as 

well as reduce genetic diversity (Wofford et al. 2005, Neville et al. 2009). These changes 

can in turn reduce long-term sustainability of salmon populations (Hilborn et al. 2003, 

Schindler et al. 2010). Blockage or inhibition of fish passage is a well-documented 

problem commonly associated with declines in salmon and other fish populations in

many regions of the U.S. (Nehlsen et al. 1991, Bates et al. 2003), including Alaska (ADFG 

2012b).

Removing and replacing crossings that serve as barriers to fishes could improve fish 

passage and re-open currently inaccessible habitat. However, as noted in Section 

3.3.2.2, the Nushagak and Kvichak River watersheds are almost entirely roadless areas, 

and thus offer few, if any, viable opportunities to provide the extent of environmental 

34
benefits necessary to offset the magnitude of impacts associated with the mine 

scenarios and associated development. Further, prior to concluding that any effort to 

retrofit existing stream crossings would be appropriate compensatory mitigation, it

would first be necessary to determine that no other party has responsibility for the 

maintenance of fish passage at those stream crossings (e.g., through the terms or 

conditions of a Section 404 permit that authorized the crossing). 

3.3.2.4 Construct Hatcheries

One commenter referenced the potential use of hatcheries as a compensation measure. 

Such a proposal could be very problematic, particularly in the context of Bristol Bay, 

where the current salmon population is entirely wild. There are several concerns over 

the introduction of hatchery-produced salmon to the Bristol Bay watershed, best 

expressed by the National Oceanic and Atmospheric Administration’s Northwest 

Fisheries Science Center: 

“Over the past several decades, wild salmon populations have declined 

dramatically, despite, and perhaps sometimes because of, the contribution of 

hatcheries. Many salmon stocks in Washington and Oregon are now listed as 

either threatened or endangered under the U.S. Endangered Species Act. With 

this decline has come an increased focus on the preservation of indigenous wild 

salmon stocks.

Hatcheries have the potential to assist in the conservation of wild stocks, but 

they also pose some risks. At this time, scientists still have many questions about 

the extent to which hatchery programs enhance or threaten the survival of wild 

populations. Additional research and investigation is needed.” (NOAA 2012)

Many of the potential risks associated with fish hatcheries concern reductions in fitness, 

growth, health, and productivity that result from decreases in genetic diversity when 

hatchery-reared stocks hybridize with wild salmon populations. Hatchery-raised salmon 

have lower genetic diversity than wild salmon (Christie et al. 2011, Yu et al. 2012). 

Consequently, when hatchery-raised salmon hybridize with wild salmon, the result can 

be a more genetically homogenous population, leading to decreases in genetic fitness 

(Waples 1991). In some cases, wild populations can become genetically swamped by 

hatchery stocks. Zhivitovsky et al. (2012) found evidence of such swamping in a wild 

chum salmon population in Kurilskiy Bay, Russia during a two-year period of high rates 

of escaped hatchery fish. This genetic homogenization is of concern because hatcheryraised fish stocks are considered less genetically “fit” and therefore could increase the 

risk of collapse of salmon fisheries. This concern is supported by Araki et al. (2008), a 

review of 14 studies which suggests that nonlocal hatchery stocks reproduce very poorly 

in the wild. The authors of this review also found that wild stocks reproduce better than 

both hatchery stocks and wild, local fish spawned and reared in hatcheries. 

35
Hatchery fish can also compete directly for food and resources with wild salmon 

populations in both freshwater and marine environments (Rand et al. 2012a). 

Ruggerone et al. (2012) examined the effect that Asian hatchery chum salmon have had 

on wild chum salmon in Norton Sound, Alaska since the early 1980s. They found that an 

increase in adult hatchery chum salmon abundance from 10 million to 80 million adult 

fish led to a 72% reduction in the abundance of the wild chum salmon population. They 

also found smaller adult length-at-age, delayed age-at-maturation, and reduced 

productivity were all associated with greater production of Asian hatchery chum since 

1965 (Ruggerone et al. 2012). In addition to this competition for resources, hatcheryraised subyearling salmon can also prey upon wild subyearling salmon, which tend to be 

smaller in size (Naman and Sharpe 2012).

Despite extensive efforts to restore federally listed Pacific Northwest salmon 

populations, they remain imperiled, and hatchery fish stocks may be a contributing 

stressor (Kostow 2009). Given the exceptional productivity of the wild Bristol Bay 

salmon population, hatcheries would appear to pose greater ecological risks than 

benefits to this unique and valuable wild salmon population.

3.3.2.5 Stock Fish 

Since many of the fish used in fish stocking originate in hatcheries, fish stocking raises 

many of the same concerns as hatcheries and thus would also be a problematic form of 

compensatory mitigation for the Bristol Bay region. Although stocking has been a 

common practice in other regions, even in previously fishless habitats (e.g., Red Dog 

Mine, Alaska), a large body of literature describes widespread adverse impacts of such 

management decisions. Fish stocking throughout western North America and 

worldwide has impacted other fish (Knapp et al. 2001, Townsend 2003), nutrient cycling 

(Schindler et al. 2001, Eby et al. 2006, Johnson et al. 2010), primary production 

(Townsend 2003, Cucherousset and Olden 2011), aquatic macroinvertebrates (Dunham 

et al. 2004, Pope et al. 2009 Cucherousset and Olden 2011), amphibians (Pilliod and 

Peterson 2001, Finlay and Vredenberg 2007), and terrestrial species (Epanchin et al. 

2010). Although fish stocking has provided limited benefits in certain circumstances, it 

would appear from the growing body of literature that the ecological costs of fish 

stocking far outweigh any potential benefits. 

3.4 Other Suggested Compensation Measures

Comments also included suggestions that compensatory mitigation for impacts to fish 

and other aquatic resources could take the form of making payments to organizations 

that support salmon sustainability or investing in various public education, outreach, or 

research activities designed to promote salmon sustainability. Although these kinds of 

initiatives can provide benefits in other contexts, compensatory mitigation for impacts 

authorized under Section 404 of the Clean Water Act can only be provided through

purchasing credits from an approved mitigation bank or in-lieu fee program or 

36
conducting permittee-responsible compensatory mitigation projects (40 CFR 230.92). 

One commenter also suggested reducing commercial fishery harvests to compensate for 

fish losses due to large-scale mining; however, such a measure would also be 

inconsistent with the definition of compensatory mitigation (40 CFR 230.92). 

4. Effectiveness of Compensation Measures at Offsetting Impacts to 

Salmonids

In North America, 73% of fish extinctions are linked to habitat alterations (Miller et al. 

1989). Although extensive efforts have been undertaken to create or improve salmon 

habitat and prevent losses to fisheries, the current status of U.S. salmon is a sobering 

testament to the billions spent on mitigation efforts given that all U.S. Atlantic salmon 

populations are endangered (NOAA 2013), 40% of Pacific salmon in the Lower 48 are 

extirpated from historic habitats (NRC 1996), and one third of remaining populations are 

threatened or endangered with extinction (Nehlsen et al. 1991, Slaney et al. 1996, 

Gustafson et al. 2007). Approximately one third of sockeye salmon population diversity 

is considered endangered or extinct (Rand et al. 2012b), and Bristol Bay sockeye salmon 

likely represent the most abundant diverse sockeye salmon populations left in the U.S. 

Since 1990, a billion dollars has been spent annually in the U.S. on stream and 

watershed restoration (Bernhardt et al. 2005) and more than 60% of the projects 

completed during this period were associated with salmon and trout habitat restoration 

efforts in the Pacific Northwest and California (Katz et al. 2007). Despite the 

proliferation of projects and the significant funds being expended on these efforts, 

debate continues over the effectiveness of various fish habitat restoration techniques 

and the cumulative impact of multiple, poorly coordinated restoration actions at a 

watershed or regional scale (Reeves et al. 1991, Chapman 1996, Roni et al. 2002, 

Kondolf et al. 2008). Further, independent evaluations of the effectiveness of fish 

habitat compensation projects are rare (Harper and Quigley 2005b, Quigley and Harper 

2006a, Quigley and Harper 2006b), and consequently the long-term success rates and 

efficacy of such projects are not well known (DFO 1997, Lister and Bengeyfield 1998, 

Lange et al. 2001, Quigley and Harper 2006a). A recent study by Roni et al. (2010) 

clearly questions the efficacy of mitigation to specifically offset salmon losses. 

The most comprehensive investigation, to date, of the efficacy of fish habitat mitigation 

measures was conducted by the Department of Fisheries and Oceans, Environment 

Canada (Harper and Quigley 2005a, Harper and Quigley 2005b, Quigley and Harper 

2006a, Quigley and Harper 2006b). Quigley and Harper (2006a) showed that 67% of 

compensation projects resulted in net losses to fish habitat and only 2% resulted in no 

net loss, whereas only 31% achieved a net gain in habitat area. Quigley and Harper 

(2006a) concluded that habitat compensation in Canada was, at best, only slowing the 

rate of fish habitat loss. Quigley and Harper (2006b) showed that 63% of projects 

resulted in net losses to aquatic habitat productivity and only 25% achieved no net loss, 

37
whereas only 12% provided net gains in aquatic habitat productivity. Quigley and 

Harper (2006b) concluded “the ability to replicate ecosystem function is clearly limited.”

Quigley and Harper (2006b) highlight the need for improvements in compensation 

science as well as institutional approaches such as better project planning, monitoring, 

and maintenance. However, they also recognize that, based on decades of experience 

in wetland replacement projects, simply achieving compliance with all regulatory 

requirements does not ensure that ecological functions are replaced (NRC 2001, Sudol 

and Ambrose 2002, Ambrose and Lee 2006, Kihslinger 2008). Although there are clearly 

opportunities to improve the performance of fish habitat compensation projects, 

Quigley and Harper (2006b) caution: 

“it is important to acknowledge that it is simply not possible to compensate for 

some habitats. Therefore, the option to compensate for HADDs [harmful 

alteration, disruption or destruction to fish habitat] may not be viable for some 

development proposals demanding careful exploration of alternative options 

including redesign, relocation, or rejection.”

5. Conclusions 

There are significant challenges regarding the potential efficacy, applicability and 

sustainability of compensation measures proposed by commenters for use in the Bristol 

Bay region, raising questions as to whether sufficient compensation measures exist that 

could address impacts of the type and magnitude described in the Bristol Bay 

Assessment. The mine scenarios evaluated in the assessment show that the mine 

footprint alone would result in the loss (i.e., filling, blocking or otherwise eliminating) of 

hundreds to thousands of acres of high-functioning wetlands and tens of miles of 

salmon-supporting streams. In addition to these direct losses, these mine scenarios 

would also result in extensive adverse secondary and cumulative impacts to wetlands, 

streams, and fish that would have to be addressed. Such extensive habitat losses and 

degradation could also result in the loss of unique salmon populations, eroding the 

genetic diversity essential to the stability of the overall Bristol Bay salmon fishery. 

38
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